Selection and Validation of Appropriate Reference Genes for qRT-PCR Analysis in Isatis indigotica Fort.

PubMed Central

Li, Tao; Wang, Jing; Lu, Miao; Zhang, Tianyi; Qu, Xinyun; Wang, Zhezhi

2017-01-01

Due to its sensitivity and specificity, real-time quantitative PCR (qRT-PCR) is a popular technique for investigating gene expression levels in plants. Based on the Minimum Information for Publication of Real-Time Quantitative PCR Experiments (MIQE) guidelines, it is necessary to select and validate putative appropriate reference genes for qRT-PCR normalization. In the current study, three algorithms, geNorm, NormFinder, and BestKeeper, were applied to assess the expression stability of 10 candidate reference genes across five different tissues and three different abiotic stresses in Isatis indigotica Fort. Additionally, the IiYUC6 gene associated with IAA biosynthesis was applied to validate the candidate reference genes. The analysis results of the geNorm, NormFinder, and BestKeeper algorithms indicated certain differences for the different sample sets and different experiment conditions. Considering all of the algorithms, PP2A-4 and TUB4 were recommended as the most stable reference genes for total and different tissue samples, respectively. Moreover, RPL15 and PP2A-4 were considered to be the most suitable reference genes for abiotic stress treatments. The obtained experimental results might contribute to improved accuracy and credibility for the expression levels of target genes by qRT-PCR normalization in I. indigotica. PMID:28702046

Evaluation and Validation of Reference Genes for qRT-PCR Normalization in Frankliniella occidentalis (Thysanoptera:Thripidae)

PubMed Central

Zheng, Yu-Tao; Li, Hong-Bo; Lu, Ming-Xing; Du, Yu-Zhou

2014-01-01

Quantitative real time PCR (qRT-PCR) has emerged as a reliable and reproducible technique for studying gene expression analysis. For accurate results, the normalization of data with reference genes is particularly essential. Once the transcriptome sequencing of Frankliniella occidentalis was completed, numerous unigenes were identified and annotated. Unfortunately, there are no studies on the stability of reference genes used in F. occidentalis. In this work, seven candidate reference genes, including actin, 18S rRNA, H3, tubulin, GAPDH, EF-1 and RPL32, were evaluated for their suitability as normalization genes under different experimental conditions using the statistical software programs BestKeeper, geNorm, Normfinder and the comparative ΔCt method. Because the rankings of the reference genes provided by each of the four programs were different, we chose a user-friendly web-based comprehensive tool RefFinder to get the final ranking. The result demonstrated that EF-1 and RPL32 displayed the most stable expression in different developmental stages; RPL32 and GAPDH showed the most stable expression at high temperatures, while 18S and EF-1 exhibited the most stable expression at low temperatures. In this study, we validated the suitable reference genes in F. occidentalis for gene expression profiling under different experimental conditions. The choice of internal standard is very important in the normalization of the target gene expression levels, thus validating and selecting the best genes will help improve the quality of gene expression data of F. occidentalis. What is more, these validated reference genes could serve as the basis for the selection of candidate reference genes in other insects. PMID:25356721

Evaluation and validation of reference genes for qRT-PCR normalization in Frankliniella occidentalis (Thysanoptera: Thripidae).

PubMed

Zheng, Yu-Tao; Li, Hong-Bo; Lu, Ming-Xing; Du, Yu-Zhou

2014-01-01

Quantitative real time PCR (qRT-PCR) has emerged as a reliable and reproducible technique for studying gene expression analysis. For accurate results, the normalization of data with reference genes is particularly essential. Once the transcriptome sequencing of Frankliniella occidentalis was completed, numerous unigenes were identified and annotated. Unfortunately, there are no studies on the stability of reference genes used in F. occidentalis. In this work, seven candidate reference genes, including actin, 18S rRNA, H3, tubulin, GAPDH, EF-1 and RPL32, were evaluated for their suitability as normalization genes under different experimental conditions using the statistical software programs BestKeeper, geNorm, Normfinder and the comparative ΔCt method. Because the rankings of the reference genes provided by each of the four programs were different, we chose a user-friendly web-based comprehensive tool RefFinder to get the final ranking. The result demonstrated that EF-1 and RPL32 displayed the most stable expression in different developmental stages; RPL32 and GAPDH showed the most stable expression at high temperatures, while 18S and EF-1 exhibited the most stable expression at low temperatures. In this study, we validated the suitable reference genes in F. occidentalis for gene expression profiling under different experimental conditions. The choice of internal standard is very important in the normalization of the target gene expression levels, thus validating and selecting the best genes will help improve the quality of gene expression data of F. occidentalis. What is more, these validated reference genes could serve as the basis for the selection of candidate reference genes in other insects.

Validation of reference genes for normalization of qPCR gene expression data from Coffea spp. hypocotyls inoculated with Colletotrichum kahawae

PubMed Central

2013-01-01

Background Coffee production in Africa represents a significant share of the total export revenues and influences the lives of millions of people, yet severe socio-economic repercussions are annually felt in result of the overall losses caused by the coffee berry disease (CBD). This quarantine disease is caused by the fungus Colletotrichum kahawae Waller and Bridge, which remains one of the most devastating threats to Coffea arabica production in Africa at high altitude, and its dispersal to Latin America and Asia represents a serious concern. Understanding the molecular genetic basis of coffee resistance to this disease is of high priority to support breeding strategies. Selection and validation of suitable reference genes presenting stable expression in the system studied is the first step to engage studies of gene expression profiling. Results In this study, a set of ten genes (S24, 14-3-3, RPL7, GAPDH, UBQ9, VATP16, SAND, UQCC, IDE and β-Tub9) was evaluated to identify reference genes during the first hours of interaction (12, 48 and 72 hpi) between resistant and susceptible coffee genotypes and C. kahawae. Three analyses were done for the selection of these genes considering the entire dataset and the two genotypes (resistant and susceptible), separately. The three statistical methods applied GeNorm, NormFinder, and BestKeeper, allowed identifying IDE as one of the most stable genes for all datasets analysed, and in contrast GADPH and UBQ9 as the least stable ones. In addition, the expression of two defense-related transcripts, encoding for a receptor like kinase and a pathogenesis related protein 10, were used to validate the reference genes selected. Conclusion Taken together, our results provide guidelines for reference gene(s) selection towards a more accurate and widespread use of qPCR to study the interaction between Coffea spp. and C. kahawae. PMID:24073624

A Tightly Regulated Genetic Selection System with Signaling-Active Alleles of Phytochrome B.

PubMed

Hu, Wei; Lagarias, J Clark

2017-01-01

Selectable markers derived from plant genes circumvent the potential risk of antibiotic/herbicide-resistance gene transfer into neighboring plant species, endophytic bacteria, and mycorrhizal fungi. Toward this goal, we have engineered and validated signaling-active alleles of phytochrome B (eYHB) as plant-derived selection marker genes in the model plant Arabidopsis (Arabidopsis thaliana). By probing the relationship of construct size and induction conditions to optimal phenotypic selection, we show that eYHB-based alleles are robust substitutes for antibiotic/herbicide-dependent marker genes as well as surprisingly sensitive reporters of off-target transgene expression. © 2017 American Society of Plant Biologists. All Rights Reserved.

A Tightly Regulated Genetic Selection System with Signaling-Active Alleles of Phytochrome B1[OPEN

PubMed Central

2017-01-01

Selectable markers derived from plant genes circumvent the potential risk of antibiotic/herbicide-resistance gene transfer into neighboring plant species, endophytic bacteria, and mycorrhizal fungi. Toward this goal, we have engineered and validated signaling-active alleles of phytochrome B (eYHB) as plant-derived selection marker genes in the model plant Arabidopsis (Arabidopsis thaliana). By probing the relationship of construct size and induction conditions to optimal phenotypic selection, we show that eYHB-based alleles are robust substitutes for antibiotic/herbicide-dependent marker genes as well as surprisingly sensitive reporters of off-target transgene expression. PMID:27881727

Transcriptome-wide selection of a reliable set of reference genes for gene expression studies in potato cyst nematodes (Globodera spp.).

PubMed

Sabeh, Michael; Duceppe, Marc-Olivier; St-Arnaud, Marc; Mimee, Benjamin

2018-01-01

Relative gene expression analyses by qRT-PCR (quantitative reverse transcription PCR) require an internal control to normalize the expression data of genes of interest and eliminate the unwanted variation introduced by sample preparation. A perfect reference gene should have a constant expression level under all the experimental conditions. However, the same few housekeeping genes selected from the literature or successfully used in previous unrelated experiments are often routinely used in new conditions without proper validation of their stability across treatments. The advent of RNA-Seq and the availability of public datasets for numerous organisms are opening the way to finding better reference genes for expression studies. Globodera rostochiensis is a plant-parasitic nematode that is particularly yield-limiting for potato. The aim of our study was to identify a reliable set of reference genes to study G. rostochiensis gene expression. Gene expression levels from an RNA-Seq database were used to identify putative reference genes and were validated with qRT-PCR analysis. Three genes, GR, PMP-3, and aaRS, were found to be very stable within the experimental conditions of this study and are proposed as reference genes for future work.

Selecting postoperative adjuvant systemic therapy for early stage breast cancer: A critical assessment of commercially available gene expression assays

PubMed Central

Schuur, Eric; Angel Aristizabal, Javier; Bargallo Rocha, Juan Enrique; Cabello, Cesar; Elizalde, Roberto; García‐Estévez, Laura; Gomez, Henry L.; Katz, Artur; Nuñez De Pierro, Aníbal

2017-01-01

Risk stratification of patients with early stage breast cancer may support adjuvant chemotherapy decision‐making. This review details the development and validation of six multi‐gene classifiers, each of which claims to provide useful prognostic and possibly predictive information for early stage breast cancer patients. A careful assessment is presented of each test's analytical validity, clinical validity, and clinical utility, as well as the quality of evidence supporting its use. PMID:28211064

Gene identification for risk of relapse in stage I lung adenocarcinoma patients: a combined methodology of gene expression profiling and computational gene network analysis.

PubMed

Ludovini, Vienna; Bianconi, Fortunato; Siggillino, Annamaria; Piobbico, Danilo; Vannucci, Jacopo; Metro, Giulio; Chiari, Rita; Bellezza, Guido; Puma, Francesco; Della Fazia, Maria Agnese; Servillo, Giuseppe; Crinò, Lucio

2016-05-24

Risk assessment and treatment choice remains a challenge in early non-small-cell lung cancer (NSCLC). The aim of this study was to identify novel genes involved in the risk of early relapse (ER) compared to no relapse (NR) in resected lung adenocarcinoma (AD) patients using a combination of high throughput technology and computational analysis. We identified 18 patients (n.13 NR and n.5 ER) with stage I AD. Frozen samples of patients in ER, NR and corresponding normal lung (NL) were subjected to Microarray technology and quantitative-PCR (Q-PCR). A gene network computational analysis was performed to select predictive genes. An independent set of 79 ADs stage I samples was used to validate selected genes by Q-PCR.From microarray analysis we selected 50 genes, using the fold change ratio of ER versus NR. They were validated both in pool and individually in patient samples (ER and NR) by Q-PCR. Fourteen increased and 25 decreased genes showed a concordance between two methods. They were used to perform a computational gene network analysis that identified 4 increased (HOXA10, CLCA2, AKR1B10, FABP3) and 6 decreased (SCGB1A1, PGC, TFF1, PSCA, SPRR1B and PRSS1) genes. Moreover, in an independent dataset of ADs samples, we showed that both high FABP3 expression and low SCGB1A1 expression was associated with a worse disease-free survival (DFS).Our results indicate that it is possible to define, through gene expression and computational analysis, a characteristic gene profiling of patients with an increased risk of relapse that may become a tool for patient selection for adjuvant therapy.

Validation of Reference Genes for RT-qPCR Studies of Gene Expression in Preharvest and Postharvest Longan Fruits under Different Experimental Conditions

PubMed Central

Wu, Jianyang; Zhang, Hongna; Liu, Liqin; Li, Weicai; Wei, Yongzan; Shi, Shengyou

2016-01-01

Reverse transcription quantitative PCR (RT-qPCR) as the accurate and sensitive method is use for gene expression analysis, but the veracity and reliability result depends on whether select appropriate reference gene or not. To date, several reliable reference gene validations have been reported in fruits trees, but none have been done on preharvest and postharvest longan fruits. In this study, 12 candidate reference genes, namely, CYP, RPL, GAPDH, TUA, TUB, Fe-SOD, Mn-SOD, Cu/Zn-SOD, 18SrRNA, Actin, Histone H3, and EF-1a, were selected. Expression stability of these genes in 150 longan samples was evaluated and analyzed using geNorm and NormFinder algorithms. Preharvest samples consisted of seven experimental sets, including different developmental stages, organs, hormone stimuli (NAA, 2,4-D, and ethephon) and abiotic stresses (bagging and girdling with defoliation). Postharvest samples consisted of different temperature treatments (4 and 22°C) and varieties. Our findings indicate that appropriate reference gene(s) should be picked for each experimental condition. Our data further showed that the commonly used reference gene Actin does not exhibit stable expression across experimental conditions in longan. Expression levels of the DlACO gene, which is a key gene involved in regulating fruit abscission under girdling with defoliation treatment, was evaluated to validate our findings. In conclusion, our data provide a useful framework for choice of suitable reference genes across different experimental conditions for RT-qPCR analysis of preharvest and postharvest longan fruits. PMID:27375640

Evaluation of New Reference Genes in Papaya for Accurate Transcript Normalization under Different Experimental Conditions

PubMed Central

Chen, Weixin; Chen, Jianye; Lu, Wangjin; Chen, Lei; Fu, Danwen

2012-01-01

Real-time reverse transcription PCR (RT-qPCR) is a preferred method for rapid and accurate quantification of gene expression studies. Appropriate application of RT-qPCR requires accurate normalization though the use of reference genes. As no single reference gene is universally suitable for all experiments, thus reference gene(s) validation under different experimental conditions is crucial for RT-qPCR analysis. To date, only a few studies on reference genes have been done in other plants but none in papaya. In the present work, we selected 21 candidate reference genes, and evaluated their expression stability in 246 papaya fruit samples using three algorithms, geNorm, NormFinder and RefFinder. The samples consisted of 13 sets collected under different experimental conditions, including various tissues, different storage temperatures, different cultivars, developmental stages, postharvest ripening, modified atmosphere packaging, 1-methylcyclopropene (1-MCP) treatment, hot water treatment, biotic stress and hormone treatment. Our results demonstrated that expression stability varied greatly between reference genes and that different suitable reference gene(s) or combination of reference genes for normalization should be validated according to the experimental conditions. In general, the internal reference genes EIF (Eukaryotic initiation factor 4A), TBP1 (TATA binding protein 1) and TBP2 (TATA binding protein 2) genes had a good performance under most experimental conditions, whereas the most widely present used reference genes, ACTIN (Actin 2), 18S rRNA (18S ribosomal RNA) and GAPDH (Glyceraldehyde-3-phosphate dehydrogenase) were not suitable in many experimental conditions. In addition, two commonly used programs, geNorm and Normfinder, were proved sufficient for the validation. This work provides the first systematic analysis for the selection of superior reference genes for accurate transcript normalization in papaya under different experimental conditions. PMID:22952972

Identification of positive selection in disease response genes within members of the Poaceae.

PubMed

Rech, Gabriel E; Vargas, Walter A; Sukno, Serenella A; Thon, Michael R

2012-12-01

Millions of years of coevolution between plants and pathogens can leave footprints on their genomes and genes involved on this interaction are expected to show patterns of positive selection in which novel, beneficial alleles are rapidly fixed within the population. Using information about upregulated genes in maize during Colletotrichum graminicola infection and resources available in the Phytozome database, we looked for evidence of positive selection in the Poaceae lineage, acting on protein coding sequences related with plant defense. We found six genes with evidence of positive selection and another eight with sites showing episodic selection. Some of them have already been described as evolving under positive selection, but others are reported here for the first time including genes encoding isocitrate lyase, dehydrogenases, a multidrug transporter, a protein containing a putative leucine-rich repeat and other proteins with unknown functions. Mapping positively selected residues onto the predicted 3-D structure of proteins showed that most of them are located on the surface, where proteins are in contact with other molecules. We present here a set of Poaceae genes that are likely to be involved in plant defense mechanisms and have evidence of positive selection. These genes are excellent candidates for future functional validation.

Predicting selective drug targets in cancer through metabolic networks

PubMed Central

Folger, Ori; Jerby, Livnat; Frezza, Christian; Gottlieb, Eyal; Ruppin, Eytan; Shlomi, Tomer

2011-01-01

The interest in studying metabolic alterations in cancer and their potential role as novel targets for therapy has been rejuvenated in recent years. Here, we report the development of the first genome-scale network model of cancer metabolism, validated by correctly identifying genes essential for cellular proliferation in cancer cell lines. The model predicts 52 cytostatic drug targets, of which 40% are targeted by known, approved or experimental anticancer drugs, and the rest are new. It further predicts combinations of synthetic lethal drug targets, whose synergy is validated using available drug efficacy and gene expression measurements across the NCI-60 cancer cell line collection. Finally, potential selective treatments for specific cancers that depend on cancer type-specific downregulation of gene expression and somatic mutations are compiled. PMID:21694718

Development of a gene-centered ssr atlas as a resource for papaya (Carica papaya) marker-assisted selection and population genetic studies.

PubMed

Vidal, Newton Medeiros; Grazziotin, Ana Laura; Ramos, Helaine Christine Cancela; Pereira, Messias Gonzaga; Venancio, Thiago Motta

2014-01-01

Carica papaya (papaya) is an economically important tropical fruit. Molecular marker-assisted selection is an inexpensive and reliable tool that has been widely used to improve fruit quality traits and resistance against diseases. In the present study we report the development and validation of an atlas of papaya simple sequence repeat (SSR) markers. We integrated gene predictions and functional annotations to provide a gene-centered perspective for marker-assisted selection studies. Our atlas comprises 160,318 SSRs, from which 21,231 were located in genic regions (i.e. inside exons, exon-intron junctions or introns). A total of 116,453 (72.6%) of all identified repeats were successfully mapped to one of the nine papaya linkage groups. Primer pairs were designed for markers from 9,594 genes (34.5% of the papaya gene complement). Using papaya-tomato orthology assessments, we assembled a list of 300 genes (comprising 785 SSRs) potentially involved in fruit ripening. We validated our atlas by screening 73 SSR markers (including 25 fruit ripening genes), achieving 100% amplification rate and uncovering 26% polymorphism rate between the parental genotypes (Sekati and JS12). The SSR atlas presented here is the first comprehensive gene-centered collection of annotated and genome positioned papaya SSRs. These features combined with thousands of high-quality primer pairs make the atlas an important resource for the papaya research community.

Genetic mechanisms involved in the evolution of the cephalopod camera eye revealed by transcriptomic and developmental studies

PubMed Central

2011-01-01

Background Coleoid cephalopods (squids and octopuses) have evolved a camera eye, the structure of which is very similar to that found in vertebrates and which is considered a classic example of convergent evolution. Other molluscs, however, possess mirror, pin-hole, or compound eyes, all of which differ from the camera eye in the degree of complexity of the eye structures and neurons participating in the visual circuit. Therefore, genes expressed in the cephalopod eye after divergence from the common molluscan ancestor could be involved in eye evolution through association with the acquisition of new structural components. To clarify the genetic mechanisms that contributed to the evolution of the cephalopod camera eye, we applied comprehensive transcriptomic analysis and conducted developmental validation of candidate genes involved in coleoid cephalopod eye evolution. Results We compared gene expression in the eyes of 6 molluscan (3 cephalopod and 3 non-cephalopod) species and selected 5,707 genes as cephalopod camera eye-specific candidate genes on the basis of homology searches against 3 molluscan species without camera eyes. First, we confirmed the expression of these 5,707 genes in the cephalopod camera eye formation processes by developmental array analysis. Second, using molecular evolutionary (dN/dS) analysis to detect positive selection in the cephalopod lineage, we identified 156 of these genes in which functions appeared to have changed after the divergence of cephalopods from the molluscan ancestor and which contributed to structural and functional diversification. Third, we selected 1,571 genes, expressed in the camera eyes of both cephalopods and vertebrates, which could have independently acquired a function related to eye development at the expression level. Finally, as experimental validation, we identified three functionally novel cephalopod camera eye genes related to optic lobe formation in cephalopods by in situ hybridization analysis of embryonic pygmy squid. Conclusion We identified 156 genes positively selected in the cephalopod lineage and 1,571 genes commonly found in the cephalopod and vertebrate camera eyes from the analysis of cephalopod camera eye specificity at the expression level. Experimental validation showed that the cephalopod camera eye-specific candidate genes include those expressed in the outer part of the optic lobes, which unique to coleoid cephalopods. The results of this study suggest that changes in gene expression and in the primary structure of proteins (through positive selection) from those in the common molluscan ancestor could have contributed, at least in part, to cephalopod camera eye acquisition. PMID:21702923

Genome-Wide Association Study for Identification and Validation of Novel SNP Markers for Sr6 Stem Rust Resistance Gene in Bread Wheat.

PubMed

Mourad, Amira M I; Sallam, Ahmed; Belamkar, Vikas; Wegulo, Stephen; Bowden, Robert; Jin, Yue; Mahdy, Ezzat; Bakheit, Bahy; El-Wafaa, Atif A; Poland, Jesse; Baenziger, Peter S

2018-01-01

Stem rust (caused by Puccinia graminis f. sp. tritici Erikss. & E. Henn.), is a major disease in wheat ( Triticum aestivium L.). However, in recent years it occurs rarely in Nebraska due to weather and the effective selection and gene pyramiding of resistance genes. To understand the genetic basis of stem rust resistance in Nebraska winter wheat, we applied genome-wide association study (GWAS) on a set of 270 winter wheat genotypes (A-set). Genotyping was carried out using genotyping-by-sequencing and ∼35,000 high-quality SNPs were identified. The tested genotypes were evaluated for their resistance to the common stem rust race in Nebraska (QFCSC) in two replications. Marker-trait association identified 32 SNP markers, which were significantly (Bonferroni corrected P < 0.05) associated with the resistance on chromosome 2D. The chromosomal location of the significant SNPs (chromosome 2D) matched the location of Sr6 gene which was expected in these genotypes based on pedigree information. A highly significant linkage disequilibrium (LD, r 2 ) was found between the significant SNPs and the specific SSR marker for the Sr6 gene ( Xcfd43 ). This suggests the significant SNP markers are tagging Sr6 gene. Out of the 32 significant SNPs, eight SNPs were in six genes that are annotated as being linked to disease resistance in the IWGSC RefSeq v1.0. The 32 significant SNP markers were located in nine haplotype blocks. All the 32 significant SNPs were validated in a set of 60 different genotypes (V-set) using single marker analysis. SNP markers identified in this study can be used in marker-assisted selection, genomic selection, and to develop KASP (Kompetitive Allele Specific PCR) marker for the Sr6 gene. Novel SNPs for Sr6 gene, an important stem rust resistant gene, were identified and validated in this study. These SNPs can be used to improve stem rust resistance in wheat.

Validation of reference genes aiming accurate normalization of qRT-PCR data in Dendrocalamus latiflorus Munro.

PubMed

Liu, Mingying; Jiang, Jing; Han, Xiaojiao; Qiao, Guirong; Zhuo, Renying

2014-01-01

Dendrocalamus latiflorus Munro distributes widely in subtropical areas and plays vital roles as valuable natural resources. The transcriptome sequencing for D. latiflorus Munro has been performed and numerous genes especially those predicted to be unique to D. latiflorus Munro were revealed. qRT-PCR has become a feasible approach to uncover gene expression profiling, and the accuracy and reliability of the results obtained depends upon the proper selection of stable reference genes for accurate normalization. Therefore, a set of suitable internal controls should be validated for D. latiflorus Munro. In this report, twelve candidate reference genes were selected and the assessment of gene expression stability was performed in ten tissue samples and four leaf samples from seedlings and anther-regenerated plants of different ploidy. The PCR amplification efficiency was estimated, and the candidate genes were ranked according to their expression stability using three software packages: geNorm, NormFinder and Bestkeeper. GAPDH and EF1α were characterized to be the most stable genes among different tissues or in all the sample pools, while CYP showed low expression stability. RPL3 had the optimal performance among four leaf samples. The application of verified reference genes was illustrated by analyzing ferritin and laccase expression profiles among different experimental sets. The analysis revealed the biological variation in ferritin and laccase transcript expression among the tissues studied and the individual plants. geNorm, NormFinder, and BestKeeper analyses recommended different suitable reference gene(s) for normalization according to the experimental sets. GAPDH and EF1α had the highest expression stability across different tissues and RPL3 for the other sample set. This study emphasizes the importance of validating superior reference genes for qRT-PCR analysis to accurately normalize gene expression of D. latiflorus Munro.

Supervised group Lasso with applications to microarray data analysis

PubMed Central

Ma, Shuangge; Song, Xiao; Huang, Jian

2007-01-01

Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods. PMID:17316436

Selection and validation of endogenous reference genes for qRT-PCR analysis in leafy spurge (Euphorbia esula)

USDA-ARS?s Scientific Manuscript database

Quantitative real-time polymerase chain reaction (qRT-PCR) is the most important tool in measuring levels of gene expression due to its accuracy, specificity, and sensitivity. However, the accuracy of qRT-PCR analysis strongly depends on transcript normalization using stably expressed reference gene...

Identification and validation of superior reference gene for gene expression normalization via RT-qPCR in staminate and pistillate flowers of Jatropha curcas - A biodiesel plant.

PubMed

Karuppaiya, Palaniyandi; Yan, Xiao-Xue; Liao, Wang; Wu, Jun; Chen, Fang; Tang, Lin

2017-01-01

Physic nut (Jatropha curcas L) seed oil is a natural resource for the alternative production of fossil fuel. Seed oil production is mainly depended on seed yield, which was restricted by the low ratio of staminate flowers to pistillate flowers. Further, the mechanism of physic nut flower sex differentiation has not been fully understood yet. Quantitative Real Time-Polymerase Chain Reaction is a reliable and widely used technique to quantify the gene expression pattern in biological samples. However, for accuracy of qRT-PCR, appropriate reference gene is highly desirable to quantify the target gene level. Hence, the present study was aimed to identify the stable reference genes in staminate and pistillate flowers of J. curcas. In this study, 10 candidate reference genes were selected and evaluated for their expression stability in staminate and pistillate flowers, and their stability was validated by five different algorithms (ΔCt, BestKeeper, NormFinder, GeNorm and RefFinder). Resulting, TUB and EF found to be the two most stably expressed reference for staminate flower; while GAPDH1 and EF found to be the most stably expressed reference gene for pistillate flowers. Finally, RT-qPCR assays of target gene AGAMOUS using the identified most stable reference genes confirmed the reliability of selected reference genes in different stages of flower development. AGAMOUS gene expression levels at different stages were further proved by gene copy number analysis. Therefore, the present study provides guidance for selecting appropriate reference genes for analyzing the expression pattern of floral developmental genes in staminate and pistillate flowers of J. curcas.

Identification and validation of superior reference gene for gene expression normalization via RT-qPCR in staminate and pistillate flowers of Jatropha curcas – A biodiesel plant

PubMed Central

Karuppaiya, Palaniyandi; Yan, Xiao-Xue; Liao, Wang; Chen, Fang; Tang, Lin

2017-01-01

Physic nut (Jatropha curcas L) seed oil is a natural resource for the alternative production of fossil fuel. Seed oil production is mainly depended on seed yield, which was restricted by the low ratio of staminate flowers to pistillate flowers. Further, the mechanism of physic nut flower sex differentiation has not been fully understood yet. Quantitative Real Time—Polymerase Chain Reaction is a reliable and widely used technique to quantify the gene expression pattern in biological samples. However, for accuracy of qRT-PCR, appropriate reference gene is highly desirable to quantify the target gene level. Hence, the present study was aimed to identify the stable reference genes in staminate and pistillate flowers of J. curcas. In this study, 10 candidate reference genes were selected and evaluated for their expression stability in staminate and pistillate flowers, and their stability was validated by five different algorithms (ΔCt, BestKeeper, NormFinder, GeNorm and RefFinder). Resulting, TUB and EF found to be the two most stably expressed reference for staminate flower; while GAPDH1 and EF found to be the most stably expressed reference gene for pistillate flowers. Finally, RT-qPCR assays of target gene AGAMOUS using the identified most stable reference genes confirmed the reliability of selected reference genes in different stages of flower development. AGAMOUS gene expression levels at different stages were further proved by gene copy number analysis. Therefore, the present study provides guidance for selecting appropriate reference genes for analyzing the expression pattern of floral developmental genes in staminate and pistillate flowers of J. curcas. PMID:28234941

Gene Expression Profile Analysis is Directly Affected by the Selected Reference Gene: The Case of Leaf-Cutting Atta Sexdens

PubMed Central

Máximo, Wesley P. F.; Zanetti, Ronald; Paiva, Luciano V.

2018-01-01

Although several ant species are important targets for the development of molecular control strategies, only a few studies focus on identifying and validating reference genes for quantitative reverse transcription polymerase chain reaction (RT-qPCR) data normalization. We provide here an extensive study to identify and validate suitable reference genes for gene expression analysis in the ant Atta sexdens, a threatening agricultural pest in South America. The optimal number of reference genes varies according to each sample and the result generated by RefFinder differed about which is the most suitable reference gene. Results suggest that the RPS16, NADH and SDHB genes were the best reference genes in the sample pool according to stability values. The SNF7 gene expression pattern was stable in all evaluated sample set. In contrast, when using less stable reference genes for normalization a large variability in SNF7 gene expression was recorded. There is no universal reference gene suitable for all conditions under analysis, since these genes can also participate in different cellular functions, thus requiring a systematic validation of possible reference genes for each specific condition. The choice of reference genes on SNF7 gene normalization confirmed that unstable reference genes might drastically change the expression profile analysis of target candidate genes. PMID:29419794

Pathway-driven gene stability selection of two rheumatoid arthritis GWAS identifies and validates new susceptibility genes in receptor mediated signalling pathways.

PubMed

Eleftherohorinou, Hariklia; Hoggart, Clive J; Wright, Victoria J; Levin, Michael; Coin, Lachlan J M

2011-09-01

Rheumatoid arthritis (RA) is the commonest chronic, systemic, inflammatory disorder affecting ∼1% of the world population. It has a strong genetic component and a growing number of associated genes have been discovered in genome-wide association studies (GWAS), which nevertheless only account for 23% of the total genetic risk. We aimed to identify additional susceptibility loci through the analysis of GWAS in the context of biological function. We bridge the gap between pathway and gene-oriented analyses of GWAS, by introducing a pathway-driven gene stability-selection methodology that identifies potential causal genes in the top-associated disease pathways that may be driving the pathway association signals. We analysed the WTCCC and the NARAC studies of ∼5000 and ∼2000 subjects, respectively. We examined 700 pathways comprising ∼8000 genes. Ranking pathways by significance revealed that the NARAC top-ranked ∼6% laid within the top 10% of WTCCC. Gene selection on those pathways identified 58 genes in WTCCC and 61 in NARAC; 21 of those were common (P(overlap)< 10(-21)), of which 16 were novel discoveries. Among the identified genes, we validated 10 known RA associations in WTCCC and 13 in NARAC, not discovered using single-SNP approaches on the same data. Gene ontology functional enrichment analysis on the identified genes showed significant over-representation of signalling activity (P< 10(-29)) in both studies. Our findings suggest a novel model of RA genetic predisposition, which involves cell-membrane receptors and genes in second messenger signalling systems, in addition to genes that regulate immune responses, which have been the focus of interest previously.

Entropy-based gene ranking without selection bias for the predictive classification of microarray data.

PubMed

Furlanello, Cesare; Serafini, Maria; Merler, Stefano; Jurman, Giuseppe

2003-11-06

We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process). With E-RFE, we speed up the recursive feature elimination (RFE) with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

Identification and Validation of Selected Universal Stress Protein Domain Containing Drought-Responsive Genes in Pigeonpea (Cajanus cajan L.)

PubMed Central

Sinha, Pallavi; Pazhamala, Lekha T.; Singh, Vikas K.; Saxena, Rachit K.; Krishnamurthy, L.; Azam, Sarwar; Khan, Aamir W.; Varshney, Rajeev K.

2016-01-01

Pigeonpea is a resilient crop, which is relatively more drought tolerant than many other legume crops. To understand the molecular mechanisms of this unique feature of pigeonpea, 51 genes were selected using the Hidden Markov Models (HMM) those codes for proteins having close similarity to universal stress protein domain. Validation of these genes was conducted on three pigeonpea genotypes (ICPL 151, ICPL 8755, and ICPL 227) having different levels of drought tolerance. Gene expression analysis using qRT-PCR revealed 6, 8, and 18 genes to be ≥2-fold differentially expressed in ICPL 151, ICPL 8755, and ICPL 227, respectively. A total of 10 differentially expressed genes showed ≥2-fold up-regulation in the more drought tolerant genotype, which encoded four different classes of proteins. These include plant U-box protein (four genes), universal stress protein A-like protein (four genes), cation/H(+) antiporter protein (one gene) and an uncharacterized protein (one gene). Genes C.cajan_29830 and C.cajan_33874 belonging to uspA, were found significantly expressed in all the three genotypes with ≥2-fold expression variations. Expression profiling of these two genes on the four other legume crops revealed their specific role in pigeonpea. Therefore, these genes seem to be promising candidates for conferring drought tolerance specifically to pigeonpea. PMID:26779199

Experimental validation of predicted cancer genes using FRET

NASA Astrophysics Data System (ADS)

Guala, Dimitri; Bernhem, Kristoffer; Ait Blal, Hammou; Jans, Daniel; Lundberg, Emma; Brismar, Hjalmar; Sonnhammer, Erik L. L.

2018-07-01

Huge amounts of data are generated in genome wide experiments, designed to investigate diseases with complex genetic causes. Follow up of all potential leads produced by such experiments is currently cost prohibitive and time consuming. Gene prioritization tools alleviate these constraints by directing further experimental efforts towards the most promising candidate targets. Recently a gene prioritization tool called MaxLink was shown to outperform other widely used state-of-the-art prioritization tools in a large scale in silico benchmark. An experimental validation of predictions made by MaxLink has however been lacking. In this study we used Fluorescence Resonance Energy Transfer, an established experimental technique for detection of protein-protein interactions, to validate potential cancer genes predicted by MaxLink. Our results provide confidence in the use of MaxLink for selection of new targets in the battle with polygenic diseases.

Selection and validation of reference genes for quantitative gene expression analyses in various tissues and seeds at different developmental stages in Bixa orellana L.

PubMed

Moreira, Viviane S; Soares, Virgínia L F; Silva, Raner J S; Sousa, Aurizangela O; Otoni, Wagner C; Costa, Marcio G C

2018-05-01

Bixa orellana L., popularly known as annatto, produces several secondary metabolites of pharmaceutical and industrial interest, including bixin, whose molecular basis of biosynthesis remain to be determined. Gene expression analysis by quantitative real-time PCR (qPCR) is an important tool to advance such knowledge. However, correct interpretation of qPCR data requires the use of suitable reference genes in order to reduce experimental variations. In the present study, we have selected four different candidates for reference genes in B. orellana , coding for 40S ribosomal protein S9 (RPS9), histone H4 (H4), 60S ribosomal protein L38 (RPL38) and 18S ribosomal RNA (18SrRNA). Their expression stabilities in different tissues (e.g. flower buds, flowers, leaves and seeds at different developmental stages) were analyzed using five statistical tools (NormFinder, geNorm, BestKeeper, ΔCt method and RefFinder). The results indicated that RPL38 is the most stable gene in different tissues and stages of seed development and 18SrRNA is the most unstable among the analyzed genes. In order to validate the candidate reference genes, we have analyzed the relative expression of a target gene coding for carotenoid cleavage dioxygenase 1 (CCD1) using the stable RPL38 and the least stable gene, 18SrRNA , for normalization of the qPCR data. The results demonstrated significant differences in the interpretation of the CCD1 gene expression data, depending on the reference gene used, reinforcing the importance of the correct selection of reference genes for normalization.

Selection of Reference Genes for Expression Studies in Diaphorina citri (Hemiptera: Liviidae).

PubMed

Bassan, Meire Menezes; Angelotti-Mendonc A, Je Ssika; Alves, Gustavo Rodrigues; Yamamoto, Pedro Takao; Moura O Filho, Francisco de Assis Alves

2017-12-05

The Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera: Liviidae), is considered the main vector of the bacteria associated with huanglongbing, a very serious disease that has threatened the world citrus industry. The absence of efficient control management protocols, including a lack of resistant cultivars, has led to the development of different approaches to study this pathosystem. The production of resistant genotypes relies on D. citri gene expression analyses by RT-qPCR to assess control of the vector population. High-quality, reliable RT-qPCR analyses depend upon proper reference gene selection and validation. However, adequate D. citri reference genes have not yet been identified. In the present study, we evaluated the genes EF 1-α, ACT, GAPDH, RPL7, RPL17, and TUB as candidate reference genes for this insect. Gene expression stability was evaluated using the mathematical algorithms deltaCt, NormFinder, BestKeeper, and geNorm, at five insect developmental stages, grown on two different plant hosts [Citrus sinensis (L.) Osbeck (Sapindales: Rutaceae) and Murraya paniculata (L.) Jack (Sapindales: Rutaceae)]. The final gene ranking was calculated using RefFinder software, and the V-ATPase-A gene was selected for validation. According to our results, two reference genes are recommended when different plant hosts and developmental stages are considered. Considering gene expression studies in D. citri grown on M. paniculata, regardless of the insect developmental stage, GAPDH and RPL7 have the best fit as reference genes in RT-qPCR analyses, whereas GAPDH and EF 1-α are recommended as reference genes in insect studies using C. sinensis. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Selection of reference genes for microRNA analysis associated to early stress response to handling and confinement in Salmo salar.

PubMed

Zavala, Eduardo; Reyes, Daniela; Deerenberg, Robert; Vidal, Rodrigo

2017-05-11

MicroRNAs are key non-coding RNA molecules that play a relevant role in the regulation of gene expression through translational repression and/or transcript cleavage during normal development and physiological adaptation processes like stress. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) has become the approach normally used to determine the levels of microRNAs. However, this approach needs the use of endogenous reference. An improper selection of endogenous references can result in confusing interpretation of data. The aim of this study was to identify and validate appropriate endogenous reference miRNA genes for normalizing RT-qPCR survey of miRNAs expression in four different tissues of Atlantic salmon, under handling and confinement stress conditions associated to early or primary stress response. Nine candidate reference normalizers, including microRNAs and nuclear genes, normally used in vertebrate microRNA expression studies were selected from literature, validated by RT-qPCR and analyzed by the algorithms geNorm and NormFinder. The results revealed that the ssa-miR-99-5p gene was the most stable overall and that ssa-miR-99-5p and ssa-miR-23a-5p genes were the best combination. Moreover, the suitability of ssa-miR-99-5p and ssa-miR-23a-5p as endogeneuos reference genes was demostrated by the expression analysis of ssa-miR-193-5p gene.

Development of a Gene-Centered SSR Atlas as a Resource for Papaya (Carica papaya) Marker-Assisted Selection and Population Genetic Studies

PubMed Central

Vidal, Newton Medeiros; Grazziotin, Ana Laura; Ramos, Helaine Christine Cancela; Pereira, Messias Gonzaga; Venancio, Thiago Motta

2014-01-01

Carica papaya (papaya) is an economically important tropical fruit. Molecular marker-assisted selection is an inexpensive and reliable tool that has been widely used to improve fruit quality traits and resistance against diseases. In the present study we report the development and validation of an atlas of papaya simple sequence repeat (SSR) markers. We integrated gene predictions and functional annotations to provide a gene-centered perspective for marker-assisted selection studies. Our atlas comprises 160,318 SSRs, from which 21,231 were located in genic regions (i.e. inside exons, exon-intron junctions or introns). A total of 116,453 (72.6%) of all identified repeats were successfully mapped to one of the nine papaya linkage groups. Primer pairs were designed for markers from 9,594 genes (34.5% of the papaya gene complement). Using papaya-tomato orthology assessments, we assembled a list of 300 genes (comprising 785 SSRs) potentially involved in fruit ripening. We validated our atlas by screening 73 SSR markers (including 25 fruit ripening genes), achieving 100% amplification rate and uncovering 26% polymorphism rate between the parental genotypes (Sekati and JS12). The SSR atlas presented here is the first comprehensive gene-centered collection of annotated and genome positioned papaya SSRs. These features combined with thousands of high-quality primer pairs make the atlas an important resource for the papaya research community. PMID:25393538

Comparative Oncogenomics for Peripheral Nerve Sheath Cancer Gene Discovery

DTIC Science & Technology

2015-06-01

neurofibromas and MPNSTs, establish gene signatures defining distinct tumor subtypes and functionally test the role of selected driver mutations ...allografted tumor cells, and a variety of in vitro functional assays. We will validate the relevance of these mutated mouse genes in human neurofibromas...and MPNSTs by determining whether these same genes are mutated in human tumors. 15. SUBJECT TERMS Nothing listed 16. SECURITY CLASSIFICATION OF: 17

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

PubMed

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Validation and Implementation of Marker-Assisted Selection (MAS) for PVY Resistance (Ryadg gene) in a Tetraploid Potato Breeding Program

USDA-ARS?s Scientific Manuscript database

The gene Ryadg from S. tuberosum ssp. andigena provides extreme resistance to PVY. This gene has been mapped to chromosome XI and linked PCR-based DNA markers have been identified. Advanced tetraploid russeted potato clones developed by the U.S. Pacific Northwest Potato Breeding Program with Ryadg P...

Selection of appropriate reference genes for RT-qPCR analysis in a streptozotocin-induced Alzheimer's disease model of cynomolgus monkeys (Macaca fascicularis).

PubMed

Park, Sang-Je; Kim, Young-Hyun; Lee, Youngjeon; Kim, Kyoung-Min; Kim, Heui-Soo; Lee, Sang-Rae; Kim, Sun-Uk; Kim, Sang-Hyun; Kim, Ji-Su; Jeong, Kang-Jin; Lee, Kyoung-Min; Huh, Jae-Won; Chang, Kyu-Tae

2013-01-01

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) has been widely used to quantify relative gene expression because of the specificity, sensitivity, and accuracy of this technique. In order to obtain reliable gene expression data from RT-qPCR experiments, it is important to utilize optimal reference genes for the normalization of target gene expression under varied experimental conditions. Previously, we developed and validated a novel icv-STZ cynomolgus monkey model for Alzheimer's disease (AD) research. However, in order to enhance the reliability of this disease model, appropriate reference genes must be selected to allow meaningful analysis of the gene expression levels in the icv-STZ cynomolgus monkey brain. In this study, we assessed the expression stability of 9 candidate reference genes in 2 matched-pair brain samples (5 regions) of control cynomolgus monkeys and those who had received intracerebroventricular injection of streptozotocin (icv-STZ). Three well-known analytical programs geNorm, NormFinder, and BestKeeper were used to choose the suitable reference genes from the total sample group, control group, and icv-STZ group. Combination analysis of the 3 different programs clearly indicated that the ideal reference genes are RPS19 and YWHAZ in the total sample group, GAPDH and RPS19 in the control group, and ACTB and GAPDH in the icv-STZ group. Additionally, we validated the normalization accuracy of the most appropriate reference genes (RPS19 and YWHAZ) by comparison with the least stable gene (TBP) using quantification of the APP and MAPT genes in the total sample group. To the best of our knowledge, this research is the first study to identify and validate the appropriate reference genes in cynomolgus monkey brains. These findings provide useful information for future studies involving the expression of target genes in the cynomolgus monkey.

Validation of Reference Genes for Real-Time Quantitative PCR (qPCR) Analysis of Avibacterium paragallinarum.

PubMed

Wen, Shuxiang; Chen, Xiaoling; Xu, Fuzhou; Sun, Huiling

2016-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) offers a robust method for measurement of gene expression levels. Selection of reliable reference gene(s) for gene expression study is conducive to reduce variations derived from different amounts of RNA and cDNA, the efficiency of the reverse transcriptase or polymerase enzymes. Until now reference genes identified for other members of the family Pasteurellaceae have not been validated for Avibacterium paragallinarum. The aim of this study was to validate nine reference genes of serovars A, B, and C strains of A. paragallinarum in different growth phase by qRT-PCR. Three of the most widely used statistical algorithms, geNorm, NormFinder and ΔCT method were used to evaluate the expression stability of reference genes. Data analyzed by overall rankings showed that in exponential and stationary phase of serovar A, the most stable reference genes were gyrA and atpD respectively; in exponential and stationary phase of serovar B, the most stable reference genes were atpD and recN respectively; in exponential and stationary phase of serovar C, the most stable reference genes were rpoB and recN respectively. This study provides recommendations for stable endogenous control genes for use in further studies involving measurement of gene expression levels.

The druggable genome and support for target identification and validation in drug development.

PubMed

Finan, Chris; Gaulton, Anna; Kruger, Felix A; Lumbers, R Thomas; Shah, Tina; Engmann, Jorgen; Galver, Luana; Kelley, Ryan; Karlsson, Anneli; Santos, Rita; Overington, John P; Hingorani, Aroon D; Casas, Juan P

2017-03-29

Target identification (determining the correct drug targets for a disease) and target validation (demonstrating an effect of target perturbation on disease biomarkers and disease end points) are important steps in drug development. Clinically relevant associations of variants in genes encoding drug targets model the effect of modifying the same targets pharmacologically. To delineate drug development (including repurposing) opportunities arising from this paradigm, we connected complex disease- and biomarker-associated loci from genome-wide association studies to an updated set of genes encoding druggable human proteins, to agents with bioactivity against these targets, and, where there were licensed drugs, to clinical indications. We used this set of genes to inform the design of a new genotyping array, which will enable association studies of druggable genes for drug target selection and validation in human disease. Copyright © 2017, American Association for the Advancement of Science.

Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning.

PubMed

Zhao, Jonathan Z L; Mucaki, Eliseos J; Rogan, Peter K

2018-01-01

Background: Gene signatures derived from transcriptomic data using machine learning methods have shown promise for biodosimetry testing. These signatures may not be sufficiently robust for large scale testing, as their performance has not been adequately validated on external, independent datasets. The present study develops human and murine signatures with biochemically-inspired machine learning that are strictly validated using k-fold and traditional approaches. Methods: Gene Expression Omnibus (GEO) datasets of exposed human and murine lymphocytes were preprocessed via nearest neighbor imputation and expression of genes implicated in the literature to be responsive to radiation exposure (n=998) were then ranked by Minimum Redundancy Maximum Relevance (mRMR). Optimal signatures were derived by backward, complete, and forward sequential feature selection using Support Vector Machines (SVM), and validated using k-fold or traditional validation on independent datasets. Results: The best human signatures we derived exhibit k-fold validation accuracies of up to 98% ( DDB2 ,  PRKDC , TPP2 , PTPRE , and GADD45A ) when validated over 209 samples and traditional validation accuracies of up to 92% ( DDB2 ,  CD8A ,  TALDO1 ,  PCNA ,  EIF4G2 ,  LCN2 ,  CDKN1A ,  PRKCH ,  ENO1 ,  and PPM1D ) when validated over 85 samples. Some human signatures are specific enough to differentiate between chemotherapy and radiotherapy. Certain multi-class murine signatures have sufficient granularity in dose estimation to inform eligibility for cytokine therapy (assuming these signatures could be translated to humans). We compiled a list of the most frequently appearing genes in the top 20 human and mouse signatures. More frequently appearing genes among an ensemble of signatures may indicate greater impact of these genes on the performance of individual signatures. Several genes in the signatures we derived are present in previously proposed signatures. Conclusions: Gene signatures for ionizing radiation exposure derived by machine learning have low error rates in externally validated, independent datasets, and exhibit high specificity and granularity for dose estimation.

Nearly neutral evolution in IFNL3 gene retains the immune function to detect and clear the viral infection in HCV.

PubMed

Singh, Pratichi; Dass, J Febin Prabhu

2018-05-07

IFNL3 gene plays a crucial role in immune defense against viruses. It induces the interferon stimulated genes (ISGs) with antiviral properties by activating the JAK-STAT pathway. In this study, we investigated the evolutionary force involved in shaping the IFNL3 gene to perform its downstream function as a regulatory gene in HCV clearance. We have selected 25 IFNL3 coding sequences with human gene as a reference sequence and constructed a phylogeny. Furthermore, rate of variation, substitution saturation test, phylogenetic informativeness and differential selection were also analysed. The codon evolution result suggests that nearly neutral mutation is the key pattern in shaping the IFNL3 evolution. The results were validated by subjecting the human IFNL3 protein variants to that of the native through a molecular dynamics simulation study. The molecular dynamics simulation clearly depicts the negative impact on the reported variants in human IFNL3 protein. However, these detrimental mutations (R157Q and R157W) were shown to be negatively selected in the evolutionary study of the mammals. Hence, the variation revealed a mild impact on the IFNL3 function and may be removed from the population through negative selection due to its high functional constraints. In a nutshell, our study may contribute the overall evidence in phylotyping and structural transformation that takes place in the non-synonymous substitutions of IFNL3 protein. Substantially, our obtained theoretical knowledge will lay the path to extend the experimental validation in HCV clearance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Genome-wide association study for Identification and validation of novel SNP markers for Sr6 stem rust resistance gene in bread wheat

USDA-ARS?s Scientific Manuscript database

Stem rust (caused by Puccinia graminis f. sp. tritici Erikss. & E. Henn.), is a major disease in wheat (Triticum aestivium L.). However, in recent years it occurs rarely in Nebraska due to weather and the effective selection and gene pyramiding of resistance genes. To understand the genetic basis of...

Endometrial gene expression profile of pregnant sows with extreme phenotypes for reproductive efficiency.

PubMed

Córdoba, S; Balcells, I; Castelló, A; Ovilo, C; Noguera, J L; Timoneda, O; Sánchez, A

2015-10-05

Prolificacy can directly impact porcine profitability, but large genetic variation and low heritability have been found regarding litter size among porcine breeds. To identify key differences in gene expression associated to swine reproductive efficiency, we performed a transcriptome analysis of sows' endometrium from an Iberian x Meishan F2 population at day 30-32 of gestation, classified according to their estimated breeding value (EBV) as high (H, EBV > 0) and low (L, EBV < 0) prolificacy phenotypes. For each sample, mRNA and small RNA libraries were RNA-sequenced, identifying 141 genes and 10 miRNAs differentially expressed between H and L groups. We selected four miRNAs based on their role in reproduction, and five genes displaying the highest differences and a positive mapping into known reproductive QTLs for RT-qPCR validation on the whole extreme population. Significant differences were validated for genes: PTGS2 (p = 0.03; H/L ratio = 3.50), PTHLH (p = 0.03; H/L ratio = 3.69), MMP8 (p = 0.01; H/L ratio =4.41) and SCNN1G (p = 0.04; H/L ratio = 3.42). Although selected miRNAs showed similar expression levels between H and L groups, significant correlation was found between the expression level of ssc-miR-133a (p < 0.01) and ssc-miR-92a (p < 0.01) and validated genes. These results provide a better understanding of the genetic architecture of prolificacy-related traits and embryo implantation failure in pigs.

Illumina whole-genome complementary DNA-mediated annealing, selection, extension and ligation platform: assessing its performance in formalin-fixed, paraffin-embedded samples and identifying invasion pattern-related genes in oral squamous cell carcinoma.

PubMed

Loudig, Olivier; Brandwein-Gensler, Margaret; Kim, Ryung S; Lin, Juan; Isayeva, Tatyana; Liu, Christina; Segall, Jeffrey E; Kenny, Paraic A; Prystowsky, Michael B

2011-12-01

High-throughput gene expression profiling from formalin-fixed, paraffin-embedded tissues has become a reality, and several methods are now commercially available. The Illumina whole-genome complementary DNA-mediated annealing, selection, extension and ligation assay (Illumina, Inc) is a full-transcriptome version of the original 512-gene complementary DNA-mediated annealing, selection, extension and ligation assay, allowing high-throughput profiling of 24,526 annotated genes from degraded and formalin-fixed, paraffin-embedded RNA. This assay has the potential to allow identification of novel gene signatures associated with clinical outcome using banked archival pathology specimen resources. We tested the reproducibility of the whole-genome complementary DNA-mediated annealing, selection, extension and ligation assay and its sensitivity for detecting differentially expressed genes in RNA extracted from matched fresh and formalin-fixed, paraffin-embedded cells, after 1 and 13 months of storage, using the human breast cell lines MCF7 and MCF10A. Then, using tumor worst pattern of invasion as a classifier, 1 component of the "risk model," we selected 12 formalin-fixed, paraffin-embedded oral squamous cell carcinomas for whole-genome complementary DNA-mediated annealing, selection, extension and ligation assay analysis. We profiled 5 tumors with nonaggressive, nondispersed pattern of invasion, and 7 tumors with aggressive dispersed pattern of invasion and satellites scattered at least 1 mm apart. To minimize variability, the formalin-fixed, paraffin-embedded specimens were prepared from snap-frozen tissues, and RNA was obtained within 24 hours of fixation. One hundred four down-regulated genes and 72 up-regulated genes in tumors with aggressive dispersed pattern of invasion were identified. We performed quantitative reverse transcriptase polymerase chain reaction validation of 4 genes using Taqman assays and in situ protein detection of 1 gene by immunohistochemistry. Functional cluster analysis of genes up-regulated in tumors with aggressive pattern of invasion suggests presence of genes involved in cellular cytoarchitecture, some of which already associated with tumor invasion. Identification of these genes provides biologic rationale for our histologic classification, with regard to tumor invasion, and demonstrates that the whole-genome complementary DNA-mediated annealing, selection, extension and ligation assay is a powerful assay for profiling degraded RNA from archived specimens when combined with quantitative reverse transcriptase polymerase chain reaction validation. Copyright © 2011 Elsevier Inc. All rights reserved.

An Ensemble Framework Coping with Instability in the Gene Selection Process.

PubMed

Castellanos-Garzón, José A; Ramos, Juan; López-Sánchez, Daniel; de Paz, Juan F; Corchado, Juan M

2018-03-01

This paper proposes an ensemble framework for gene selection, which is aimed at addressing instability problems presented in the gene filtering task. The complex process of gene selection from gene expression data faces different instability problems from the informative gene subsets found by different filter methods. This makes the identification of significant genes by the experts difficult. The instability of results can come from filter methods, gene classifier methods, different datasets of the same disease and multiple valid groups of biomarkers. Even though there is a wide number of proposals, the complexity imposed by this problem remains a challenge today. This work proposes a framework involving five stages of gene filtering to discover biomarkers for diagnosis and classification tasks. This framework performs a process of stable feature selection, facing the problems above and, thus, providing a more suitable and reliable solution for clinical and research purposes. Our proposal involves a process of multistage gene filtering, in which several ensemble strategies for gene selection were added in such a way that different classifiers simultaneously assess gene subsets to face instability. Firstly, we apply an ensemble of recent gene selection methods to obtain diversity in the genes found (stability according to filter methods). Next, we apply an ensemble of known classifiers to filter genes relevant to all classifiers at a time (stability according to classification methods). The achieved results were evaluated in two different datasets of the same disease (pancreatic ductal adenocarcinoma), in search of stability according to the disease, for which promising results were achieved.

Validation of reference genes for quantitative RT-PCR studies of gene expression in perennial ryegrass (Lolium perenne L.)

PubMed Central

2010-01-01

Background Perennial ryegrass (Lolium perenne L.) is an important pasture and turf crop. Biotechniques such as gene expression studies are being employed to improve traits in this temperate grass. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is among the best methods available for determining changes in gene expression. Before analysis of target gene expression, it is essential to select an appropriate normalisation strategy to control for non-specific variation between samples. Reference genes that have stable expression at different biological and physiological states can be effectively used for normalisation; however, their expression stability must be validated before use. Results Existing Serial Analysis of Gene Expression data were queried to identify six moderately expressed genes that had relatively stable gene expression throughout the year. These six candidate reference genes (eukaryotic elongation factor 1 alpha, eEF1A; TAT-binding protein homolog 1, TBP-1; eukaryotic translation initiation factor 4 alpha, eIF4A; YT521-B-like protein family protein, YT521-B; histone 3, H3; ubiquitin-conjugating enzyme, E2) were validated for qRT-PCR normalisation in 442 diverse perennial ryegrass (Lolium perenne L.) samples sourced from field- and laboratory-grown plants under a wide range of experimental conditions. Eukaryotic EF1A is encoded by members of a multigene family exhibiting differential expression and necessitated the expression analysis of different eEF1A encoding genes; a highly expressed eEF1A (h), a moderately, but stably expressed eEF1A (s), and combined expression of multigene eEF1A (m). NormFinder identified eEF1A (s) and YT521-B as the best combination of two genes for normalisation of gene expression data in perennial ryegrass following different defoliation management in the field. Conclusions This study is unique in the magnitude of samples tested with the inclusion of numerous field-grown samples, helping pave the way to conduct gene expression studies in perennial biomass crops under field-conditions. From our study several stably expressed reference genes have been validated. This provides useful candidates for reference gene selection in perennial ryegrass under conditions other than those tested here. PMID:20089196

Identification and validation of reference genes for normalization of gene expression analysis using qRT-PCR in Helicoverpa armigera (Lepidoptera: Noctuidae).

PubMed

Zhang, Songdou; An, Shiheng; Li, Zhen; Wu, Fengming; Yang, Qingpo; Liu, Yichen; Cao, Jinjun; Zhang, Huaijiang; Zhang, Qingwen; Liu, Xiaoxia

2015-01-25

Recent studies have focused on determining functional genes and microRNAs in the pest Helicoverpa armigera (Lepidoptera: Noctuidae). Most of these studies used quantitative real-time PCR (qRT-PCR). Suitable reference genes are necessary to normalize gene expression data of qRT-PCR. However, a comprehensive study on the reference genes in H. armigera remains lacking. Twelve candidate reference genes of H. armigera were selected and evaluated for their expression stability under different biotic and abiotic conditions. The comprehensive stability ranking of candidate reference genes was recommended by RefFinder and the optimal number of reference genes was calculated by geNorm. Two target genes, thioredoxin (TRX) and Cu/Zn superoxide dismutase (SOD), were used to validate the selection of reference genes. Results showed that the most suitable candidate combinations of reference genes were as follows: 28S and RPS15 for developmental stages; RPS15 and RPL13 for larvae tissues; EF and RPL27 for adult tissues; GAPDH, RPL27, and β-TUB for nuclear polyhedrosis virus infection; RPS15 and RPL32 for insecticide treatment; RPS15 and RPL27 for temperature treatment; and RPL32, RPS15, and RPL27 for all samples. This study not only establishes an accurate method for normalizing qRT-PCR data in H. armigera but also serve as a reference for further study on gene transcription in H. armigera and other insects. Copyright © 2014 Elsevier B.V. All rights reserved.

Validation of RNAi Silencing Efficiency Using Gene Array Data shows 18.5% Failure Rate across 429 Independent Experiments.

PubMed

Munkácsy, Gyöngyi; Sztupinszki, Zsófia; Herman, Péter; Bán, Bence; Pénzváltó, Zsófia; Szarvas, Nóra; Győrffy, Balázs

2016-09-27

No independent cross-validation of success rate for studies utilizing small interfering RNA (siRNA) for gene silencing has been completed before. To assess the influence of experimental parameters like cell line, transfection technique, validation method, and type of control, we have to validate these in a large set of studies. We utilized gene chip data published for siRNA experiments to assess success rate and to compare methods used in these experiments. We searched NCBI GEO for samples with whole transcriptome analysis before and after gene silencing and evaluated the efficiency for the target and off-target genes using the array-based expression data. Wilcoxon signed-rank test was used to assess silencing efficacy and Kruskal-Wallis tests and Spearman rank correlation were used to evaluate study parameters. All together 1,643 samples representing 429 experiments published in 207 studies were evaluated. The fold change (FC) of down-regulation of the target gene was above 0.7 in 18.5% and was above 0.5 in 38.7% of experiments. Silencing efficiency was lowest in MCF7 and highest in SW480 cells (FC = 0.59 and FC = 0.30, respectively, P = 9.3E-06). Studies utilizing Western blot for validation performed better than those with quantitative polymerase chain reaction (qPCR) or microarray (FC = 0.43, FC = 0.47, and FC = 0.55, respectively, P = 2.8E-04). There was no correlation between type of control, transfection method, publication year, and silencing efficiency. Although gene silencing is a robust feature successfully cross-validated in the majority of experiments, efficiency remained insufficient in a significant proportion of studies. Selection of cell line model and validation method had the highest influence on silencing proficiency.

Epigenomic Elements Analyses for Promoters Identify ESRRG as a New Susceptibility Gene for Obesity-related Traits

PubMed Central

Dong, Shan-Shan; Guo, Yan; Zhu, Dong-Li; Chen, Xiao-Feng; Wu, Xiao-Ming; Shen, Hui; Chen, Xiang-Ding; Tan, Li-Jun; Tian, Qing; Deng, Hong-Wen; Yang, Tie-Lin

2016-01-01

OBJECTIVES With ENCODE epigenomic data and results from published genome-wide association studies (GWASs), we aimed to find regulatory signatures of obesity genes and discover novel susceptibility genes. METHODS Obesity genes were obtained from public GWASs databases and their promoters were annotated based on the regulatory elements information. Significantly enriched or depleted epigenomic elements in the promoters of obesity genes were evaluated and all human genes were then prioritized according to the existence of the selected elements to predict new candidate genes. Top ranked genes were subsequently applied to validate their associations with obesity-related traits in three independent in-house GWASs samples. RESULTS We identified RAD21 and EZH2 as over-represented, STAT2 and IRF3 as depleted transcription factors. Histone modification of H3K9me3 and chromatin state segmentation of “poised promoter” and “repressed” were overrepresented. All genes were prioritized and we selected the top five genes for validation at population level. Combined results from the three GWASs samples, rs7522101 in ESRRG remained significantly associated with BMI after multiple testing corrections (P = 7.25 × 10−5). It was also associated with β-cell function (P = 1.99 × 10−3) and fasting glucose level (P < 0.05) in the meta-analyses of glucose and insulin-related traits consortium (MAGIC) dataset. CONCLUSIONS In summary, we identified epigenomic characteristics for obesity genes and suggested ESRRG as a novel obesity susceptibility gene. PMID:27113491

SNPs in stress-responsive rice genes: validation, genotyping, functional relevance and population structure

PubMed Central

2012-01-01

Background Single nucleotide polymorphism (SNP) validation and large-scale genotyping are required to maximize the use of DNA sequence variation and determine the functional relevance of candidate genes for complex stress tolerance traits through genetic association in rice. We used the bead array platform-based Illumina GoldenGate assay to validate and genotype SNPs in a select set of stress-responsive genes to understand their functional relevance and study the population structure in rice. Results Of the 384 putative SNPs assayed, we successfully validated and genotyped 362 (94.3%). Of these 325 (84.6%) showed polymorphism among the 91 rice genotypes examined. Physical distribution, degree of allele sharing, admixtures and introgression, and amino acid replacement of SNPs in 263 abiotic and 62 biotic stress-responsive genes provided clues for identification and targeted mapping of trait-associated genomic regions. We assessed the functional and adaptive significance of validated SNPs in a set of contrasting drought tolerant upland and sensitive lowland rice genotypes by correlating their allelic variation with amino acid sequence alterations in catalytic domains and three-dimensional secondary protein structure encoded by stress-responsive genes. We found a strong genetic association among SNPs in the nine stress-responsive genes with upland and lowland ecological adaptation. Higher nucleotide diversity was observed in indica accessions compared with other rice sub-populations based on different population genetic parameters. The inferred ancestry of 16% among rice genotypes was derived from admixed populations with the maximum between upland aus and wild Oryza species. Conclusions SNPs validated in biotic and abiotic stress-responsive rice genes can be used in association analyses to identify candidate genes and develop functional markers for stress tolerance in rice. PMID:22921105

Selection and validation of reference genes for gene expression analysis in apomictic and sexual Cenchrus ciliaris

PubMed Central

2013-01-01

Background Apomixis is a naturally occurring asexual mode of seed reproduction resulting in offspring genetically identical to the maternal plant. Identifying differential gene expression patterns between apomictic and sexual plants is valuable to help deconstruct the trait. Quantitative RT-PCR (qRT-PCR) is a popular method for analyzing gene expression. Normalizing gene expression data using proper reference genes which show stable expression under investigated conditions is critical in qRT-PCR analysis. We used qRT-PCR to validate expression and stability of six potential reference genes (EF1alpha, EIF4A, UBCE, GAPDH, ACT2 and TUBA) in vegetative and reproductive tissues of B-2S and B-12-9 accessions of C. ciliaris. Findings Among tissue types evaluated, EF1alpha showed the highest level of expression while TUBA showed the lowest. When all tissue types were evaluated and compared between genotypes, EIF4A was the most stable reference gene. Gene expression stability for specific ovary stages of B-2S and B-12-9 was also determined. Except for TUBA, all other tested reference genes could be used for any stage-specific ovary tissue normalization, irrespective of the mode of reproduction. Conclusion Our gene expression stability assay using six reference genes, in sexual and apomictic accessions of C. ciliaris, suggests that EIF4A is the most stable gene across all tissue types analyzed. All other tested reference genes, with the exception of TUBA, could be used for gene expression comparison studies between sexual and apomictic ovaries over multiple developmental stages. This reference gene validation data in C. ciliaris will serve as an important base for future apomixis-related transcriptome data validation. PMID:24083672

The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression.

PubMed

Catto, James W F; Abbod, Maysam F; Wild, Peter J; Linkens, Derek A; Pilarsky, Christian; Rehman, Ishtiaq; Rosario, Derek J; Denzinger, Stefan; Burger, Maximilian; Stoehr, Robert; Knuechel, Ruth; Hartmann, Arndt; Hamdy, Freddie C

2010-03-01

New methods for identifying bladder cancer (BCa) progression are required. Gene expression microarrays can reveal insights into disease biology and identify novel biomarkers. However, these experiments produce large datasets that are difficult to interpret. To develop a novel method of microarray analysis combining two forms of artificial intelligence (AI): neurofuzzy modelling (NFM) and artificial neural networks (ANN) and validate it in a BCa cohort. We used AI and statistical analyses to identify progression-related genes in a microarray dataset (n=66 tumours, n=2800 genes). The AI-selected genes were then investigated in a second cohort (n=262 tumours) using immunohistochemistry. We compared the accuracy of AI and statistical approaches to identify tumour progression. AI identified 11 progression-associated genes (odds ratio [OR]: 0.70; 95% confidence interval [CI], 0.56-0.87; p=0.0004), and these were more discriminate than genes chosen using statistical analyses (OR: 1.24; 95% CI, 0.96-1.60; p=0.09). The expression of six AI-selected genes (LIG3, FAS, KRT18, ICAM1, DSG2, and BRCA2) was determined using commercial antibodies and successfully identified tumour progression (concordance index: 0.66; log-rank test: p=0.01). AI-selected genes were more discriminate than pathologic criteria at determining progression (Cox multivariate analysis: p=0.01). Limitations include the use of statistical correlation to identify 200 genes for AI analysis and that we did not compare regression identified genes with immunohistochemistry. AI and statistical analyses use different techniques of inference to determine gene-phenotype associations and identify distinct prognostic gene signatures that are equally valid. We have identified a prognostic gene signature whose members reflect a variety of carcinogenic pathways that could identify progression in non-muscle-invasive BCa. 2009 European Association of Urology. Published by Elsevier B.V. All rights reserved.

A statistical approach to selecting and confirming validation targets in -omics experiments

PubMed Central

2012-01-01

Background Genomic technologies are, by their very nature, designed for hypothesis generation. In some cases, the hypotheses that are generated require that genome scientists confirm findings about specific genes or proteins. But one major advantage of high-throughput technology is that global genetic, genomic, transcriptomic, and proteomic behaviors can be observed. Manual confirmation of every statistically significant genomic result is prohibitively expensive. This has led researchers in genomics to adopt the strategy of confirming only a handful of the most statistically significant results, a small subset chosen for biological interest, or a small random subset. But there is no standard approach for selecting and quantitatively evaluating validation targets. Results Here we present a new statistical method and approach for statistically validating lists of significant results based on confirming only a small random sample. We apply our statistical method to show that the usual practice of confirming only the most statistically significant results does not statistically validate result lists. We analyze an extensively validated RNA-sequencing experiment to show that confirming a random subset can statistically validate entire lists of significant results. Finally, we analyze multiple publicly available microarray experiments to show that statistically validating random samples can both (i) provide evidence to confirm long gene lists and (ii) save thousands of dollars and hundreds of hours of labor over manual validation of each significant result. Conclusions For high-throughput -omics studies, statistical validation is a cost-effective and statistically valid approach to confirming lists of significant results. PMID:22738145

Metagenomic analysis of faecal microbiome as a tool towards targeted non-invasive biomarkers for colorectal cancer.

PubMed

Yu, Jun; Feng, Qiang; Wong, Sunny Hei; Zhang, Dongya; Liang, Qiao Yi; Qin, Youwen; Tang, Longqing; Zhao, Hui; Stenvang, Jan; Li, Yanli; Wang, Xiaokai; Xu, Xiaoqiang; Chen, Ning; Wu, William Ka Kei; Al-Aama, Jumana; Nielsen, Hans Jørgen; Kiilerich, Pia; Jensen, Benjamin Anderschou Holbech; Yau, Tung On; Lan, Zhou; Jia, Huijue; Li, Junhua; Xiao, Liang; Lam, Thomas Yuen Tung; Ng, Siew Chien; Cheng, Alfred Sze-Lok; Wong, Vincent Wai-Sun; Chan, Francis Ka Leung; Xu, Xun; Yang, Huanming; Madsen, Lise; Datz, Christian; Tilg, Herbert; Wang, Jian; Brünner, Nils; Kristiansen, Karsten; Arumugam, Manimozhiyan; Sung, Joseph Jao-Yiu; Wang, Jun

2017-01-01

To evaluate the potential for diagnosing colorectal cancer (CRC) from faecal metagenomes. We performed metagenome-wide association studies on faecal samples from 74 patients with CRC and 54 controls from China, and validated the results in 16 patients and 24 controls from Denmark. We further validated the biomarkers in two published cohorts from France and Austria. Finally, we employed targeted quantitative PCR (qPCR) assays to evaluate diagnostic potential of selected biomarkers in an independent Chinese cohort of 47 patients and 109 controls. Besides confirming known associations of Fusobacterium nucleatum and Peptostreptococcus stomatis with CRC, we found significant associations with several species, including Parvimonas micra and Solobacterium moorei. We identified 20 microbial gene markers that differentiated CRC and control microbiomes, and validated 4 markers in the Danish cohort. In the French and Austrian cohorts, these four genes distinguished CRC metagenomes from controls with areas under the receiver-operating curve (AUC) of 0.72 and 0.77, respectively. qPCR measurements of two of these genes accurately classified patients with CRC in the independent Chinese cohort with AUC=0.84 and OR of 23. These genes were enriched in early-stage (I-II) patient microbiomes, highlighting the potential for using faecal metagenomic biomarkers for early diagnosis of CRC. We present the first metagenomic profiling study of CRC faecal microbiomes to discover and validate microbial biomarkers in ethnically different cohorts, and to independently validate selected biomarkers using an affordable clinically relevant technology. Our study thus takes a step further towards affordable non-invasive early diagnostic biomarkers for CRC from faecal samples. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Integration of biological data by kernels on graph nodes allows prediction of new genes involved in mitotic chromosome condensation

PubMed Central

Hériché, Jean-Karim; Lees, Jon G.; Morilla, Ian; Walter, Thomas; Petrova, Boryana; Roberti, M. Julia; Hossain, M. Julius; Adler, Priit; Fernández, José M.; Krallinger, Martin; Haering, Christian H.; Vilo, Jaak; Valencia, Alfonso; Ranea, Juan A.; Orengo, Christine; Ellenberg, Jan

2014-01-01

The advent of genome-wide RNA interference (RNAi)–based screens puts us in the position to identify genes for all functions human cells carry out. However, for many functions, assay complexity and cost make genome-scale knockdown experiments impossible. Methods to predict genes required for cell functions are therefore needed to focus RNAi screens from the whole genome on the most likely candidates. Although different bioinformatics tools for gene function prediction exist, they lack experimental validation and are therefore rarely used by experimentalists. To address this, we developed an effective computational gene selection strategy that represents public data about genes as graphs and then analyzes these graphs using kernels on graph nodes to predict functional relationships. To demonstrate its performance, we predicted human genes required for a poorly understood cellular function—mitotic chromosome condensation—and experimentally validated the top 100 candidates with a focused RNAi screen by automated microscopy. Quantitative analysis of the images demonstrated that the candidates were indeed strongly enriched in condensation genes, including the discovery of several new factors. By combining bioinformatics prediction with experimental validation, our study shows that kernels on graph nodes are powerful tools to integrate public biological data and predict genes involved in cellular functions of interest. PMID:24943848

Selection and Validation of Reference Genes for Quantitative Real-Time Polymerase Chain Reaction Studies in Mossy Maze Polypore, Cerrena unicolor (Higher Basidiomycetes).

PubMed

Yang, Jie; Lin, Qi; Lin, Juan; Ye, Xiuyun

2016-01-01

With its ability to produce ligninolytic enzymes such as laccases, white-rot basidiomycete Cerrena unicolor, a medicinal mushroom, has great potential in biotechnology. Elucidation of the expression profiles of genes encoding ligninolytic enzymes are important for increasing their production. Quantitative real-time polymerase chain reaction (qPCR) is a powerful tool to study transcriptional regulation of genes of interest. To ensure accuracy and reliability of qPCR analysis of C. unicolor, expression levels of seven candidate reference genes were studied at different growth phases, under various induction conditions, and with a range of carbon/nitrogen ratios and carbon and nitrogen sources. The stability of the genes were analyzed with five statistical approaches, namely geNorm, NormFinder, BestKeeper, the ΔCt method, and RefFinder. Our results indicated that the selection of reference genes varied with sample sets. A combination of four reference genes (Cyt-c, ATP6, TEF1, and β-tubulin) were recommended for normalizing gene expression at different growth phases. GAPDH and Cyt-c were the appropriate reference genes under different induction conditions. ATP6 and TEF1 were most stable in fermentation media with various carbon/nitrogen ratios. In the fermentation media with various carbon or nitrogen sources, 18S rRNA and GAPDH were the references of choice. The present study represents the first validation analysis of reference genes in C. unicolor and serves as a foundation for its qPCR analysis.

Ontology-oriented retrieval of putative microRNAs in Vitis vinifera via GrapeMiRNA: a web database of de novo predicted grape microRNAs.

PubMed

Lazzari, Barbara; Caprera, Andrea; Cestaro, Alessandro; Merelli, Ivan; Del Corvo, Marcello; Fontana, Paolo; Milanesi, Luciano; Velasco, Riccardo; Stella, Alessandra

2009-06-29

Two complete genome sequences are available for Vitis vinifera Pinot noir. Based on the sequence and gene predictions produced by the IASMA, we performed an in silico detection of putative microRNA genes and of their targets, and collected the most reliable microRNA predictions in a web database. The application is available at http://www.itb.cnr.it/ptp/grapemirna/. The program FindMiRNA was used to detect putative microRNA genes in the grape genome. A very high number of predictions was retrieved, calling for validation. Nine parameters were calculated and, based on the grape microRNAs dataset available at miRBase, thresholds were defined and applied to FindMiRNA predictions having targets in gene exons. In the resulting subset, predictions were ranked according to precursor positions and sequence similarity, and to target identity. To further validate FindMiRNA predictions, comparisons to the Arabidopsis genome, to the grape Genoscope genome, and to the grape EST collection were performed. Results were stored in a MySQL database and a web interface was prepared to query the database and retrieve predictions of interest. The GrapeMiRNA database encompasses 5,778 microRNA predictions spanning the whole grape genome. Predictions are integrated with information that can be of use in selection procedures. Tools added in the web interface also allow to inspect predictions according to gene ontology classes and metabolic pathways of targets. The GrapeMiRNA database can be of help in selecting candidate microRNA genes to be validated.

Bioinformatics approach for choosing the correct reference genes when studying gene expression in human keratinocytes.

PubMed

Beer, Lucian; Mlitz, Veronika; Gschwandtner, Maria; Berger, Tanja; Narzt, Marie-Sophie; Gruber, Florian; Brunner, Patrick M; Tschachler, Erwin; Mildner, Michael

2015-10-01

Reverse transcription polymerase chain reaction (qRT-PCR) has become a mainstay in many areas of skin research. To enable quantitative analysis, it is necessary to analyse expression of reference genes (RGs) for normalization of target gene expression. The selection of reliable RGs therefore has an important impact on the experimental outcome. In this study, we aimed to identify and validate the best suited RGs for qRT-PCR in human primary keratinocytes (KCs) over a broad range of experimental conditions using the novel bioinformatics tool 'RefGenes', which is based on a manually curated database of published microarray data. Expression of 6 RGs identified by RefGenes software and 12 commonly used RGs were validated by qRT-PCR. We assessed whether these 18 markers fulfilled the requirements for a valid RG by the comprehensive ranking of four bioinformatics tools and the coefficient of variation (CV). In an overall ranking, we found GUSB to be the most stably expressed RG, whereas the expression values of the commonly used RGs, GAPDH and B2M were significantly affected by varying experimental conditions. Our results identify RefGenes as a powerful tool for the identification of valid RGs and suggest GUSB as the most reliable RG for KCs. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Selection of reliable reference genes for quantitative real-time PCR gene expression analysis in Jute (Corchorus capsularis) under stress treatments

PubMed Central

Niu, Xiaoping; Qi, Jianmin; Zhang, Gaoyang; Xu, Jiantang; Tao, Aifen; Fang, Pingping; Su, Jianguang

2015-01-01

To accurately measure gene expression using quantitative reverse transcription PCR (qRT-PCR), reliable reference gene(s) are required for data normalization. Corchorus capsularis, an annual herbaceous fiber crop with predominant biodegradability and renewability, has not been investigated for the stability of reference genes with qRT-PCR. In this study, 11 candidate reference genes were selected and their expression levels were assessed using qRT-PCR. To account for the influence of experimental approach and tissue type, 22 different jute samples were selected from abiotic and biotic stress conditions as well as three different tissue types. The stability of the candidate reference genes was evaluated using geNorm, NormFinder, and BestKeeper programs, and the comprehensive rankings of gene stability were generated by aggregate analysis. For the biotic stress and NaCl stress subsets, ACT7 and RAN were suitable as stable reference genes for gene expression normalization. For the PEG stress subset, UBC, and DnaJ were sufficient for accurate normalization. For the tissues subset, four reference genes TUBβ, UBI, EF1α, and RAN were sufficient for accurate normalization. The selected genes were further validated by comparing expression profiles of WRKY15 in various samples, and two stable reference genes were recommended for accurate normalization of qRT-PCR data. Our results provide researchers with appropriate reference genes for qRT-PCR in C. capsularis, and will facilitate gene expression study under these conditions. PMID:26528312

Predicting essential genes for identifying potential drug targets in Aspergillus fumigatus.

PubMed

Lu, Yao; Deng, Jingyuan; Rhodes, Judith C; Lu, Hui; Lu, Long Jason

2014-06-01

Aspergillus fumigatus (Af) is a ubiquitous and opportunistic pathogen capable of causing acute, invasive pulmonary disease in susceptible hosts. Despite current therapeutic options, mortality associated with invasive Af infections remains unacceptably high, increasing 357% since 1980. Therefore, there is an urgent need for the development of novel therapeutic strategies, including more efficacious drugs acting on new targets. Thus, as noted in a recent review, "the identification of essential genes in fungi represents a crucial step in the development of new antifungal drugs". Expanding the target space by rapidly identifying new essential genes has thus been described as "the most important task of genomics-based target validation". In previous research, we were the first to show that essential gene annotation can be reliably transferred between distantly related four Prokaryotic species. In this study, we extend our machine learning approach to the much more complex Eukaryotic fungal species. A compendium of essential genes is predicted in Af by transferring known essential gene annotations from another filamentous fungus Neurospora crassa. This approach predicts essential genes by integrating diverse types of intrinsic and context-dependent genomic features encoded in microbial genomes. The predicted essential datasets contained 1674 genes. We validated our results by comparing our predictions with known essential genes in Af, comparing our predictions with those predicted by homology mapping, and conducting conditional expressed alleles. We applied several layers of filters and selected a set of potential drug targets from the predicted essential genes. Finally, we have conducted wet lab knockout experiments to verify our predictions, which further validates the accuracy and wide applicability of the machine learning approach. The approach presented here significantly extended our ability to predict essential genes beyond orthologs and made it possible to predict an inventory of essential genes in Eukaryotic fungal species, amongst which a preferred subset of suitable drug targets may be selected. By selecting the best new targets, we believe that resultant drugs would exhibit an unparalleled clinical impact against a naive pathogen population. Additional benefits that a compendium of essential genes can provide are important information on cell function and evolutionary biology. Furthermore, mapping essential genes to pathways may also reveal critical check points in the pathogen's metabolism. Finally, this approach is highly reproducible and portable, and can be easily applied to predict essential genes in many more pathogenic microbes, especially those unculturable. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sequencing and Validation of Reference Genes to Analyze Endogenous Gene Expression and Quantify Yellow Dwarf Viruses Using RT-qPCR in Viruliferous Rhopalosiphum padi

PubMed Central

Wu, Keke; Liu, Wenwen; Mar, Thithi; Liu, Yan; Wu, Yunfeng; Wang, Xifeng

2014-01-01

The bird cherry-oat aphid (Rhopalosiphum padi), an important pest of cereal crops, not only directly sucks sap from plants, but also transmits a number of plant viruses, collectively the yellow dwarf viruses (YDVs). For quantifying changes in gene expression in vector aphids, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is a touchstone method, but the selection and validation of housekeeping genes (HKGs) as reference genes to normalize the expression level of endogenous genes of the vector and for exogenous genes of the virus in the aphids is critical to obtaining valid results. Such an assessment has not been done, however, for R. padi and YDVs. Here, we tested three algorithms (GeNorm, NormFinder and BestKeeper) to assess the suitability of candidate reference genes (EF-1α, ACT1, GAPDH, 18S rRNA) in 6 combinations of YDV and vector aphid morph. EF-1α and ACT1 together or in combination with GAPDH or with GAPDH and 18S rRNA could confidently be used to normalize virus titre and expression levels of endogenous genes in winged or wingless R. padi infected with Barley yellow dwarf virus isolates (BYDV)-PAV and BYDV-GAV. The use of only one reference gene, whether the most stably expressed (EF-1α) or the least stably expressed (18S rRNA), was not adequate for obtaining valid relative expression data from the RT-qPCR. Because of discrepancies among values for changes in relative expression obtained using 3 regions of the same gene, different regions of an endogenous aphid gene, including each terminus and the middle, should be analyzed at the same time with RT-qPCR. Our results highlight the necessity of choosing the best reference genes to obtain valid experimental data and provide several HKGs for relative quantification of virus titre in YDV-viruliferous aphids. PMID:24810421

A multi-strategy approach to informative gene identification from gene expression data.

PubMed

Liu, Ziying; Phan, Sieu; Famili, Fazel; Pan, Youlian; Lenferink, Anne E G; Cantin, Christiane; Collins, Catherine; O'Connor-McCourt, Maureen D

2010-02-01

An unsupervised multi-strategy approach has been developed to identify informative genes from high throughput genomic data. Several statistical methods have been used in the field to identify differentially expressed genes. Since different methods generate different lists of genes, it is very challenging to determine the most reliable gene list and the appropriate method. This paper presents a multi-strategy method, in which a combination of several data analysis techniques are applied to a given dataset and a confidence measure is established to select genes from the gene lists generated by these techniques to form the core of our final selection. The remainder of the genes that form the peripheral region are subject to exclusion or inclusion into the final selection. This paper demonstrates this methodology through its application to an in-house cancer genomics dataset and a public dataset. The results indicate that our method provides more reliable list of genes, which are validated using biological knowledge, biological experiments, and literature search. We further evaluated our multi-strategy method by consolidating two pairs of independent datasets, each pair is for the same disease, but generated by different labs using different platforms. The results showed that our method has produced far better results.

Identification and Validation of Reference Genes and Their Impact on Normalized Gene Expression Studies across Cultivated and Wild Cicer Species

PubMed Central

Reddy, Palakolanu Sudhakar; Sri Cindhuri, Katamreddy; Sivaji Ganesh, Adusumalli; Sharma, Kiran Kumar

2016-01-01

Quantitative Real-Time PCR (qPCR) is a preferred and reliable method for accurate quantification of gene expression to understand precise gene functions. A total of 25 candidate reference genes including traditional and new generation reference genes were selected and evaluated in a diverse set of chickpea samples. The samples used in this study included nine chickpea genotypes (Cicer spp.) comprising of cultivated and wild species, six abiotic stress treatments (drought, salinity, high vapor pressure deficit, abscisic acid, cold and heat shock), and five diverse tissues (leaf, root, flower, seedlings and seed). The geNorm, NormFinder and RefFinder algorithms used to identify stably expressed genes in four sample sets revealed stable expression of UCP and G6PD genes across genotypes, while TIP41 and CAC were highly stable under abiotic stress conditions. While PP2A and ABCT genes were ranked as best for different tissues, ABCT, UCP and CAC were most stable across all samples. This study demonstrated the usefulness of new generation reference genes for more accurate qPCR based gene expression quantification in cultivated as well as wild chickpea species. Validation of the best reference genes was carried out by studying their impact on normalization of aquaporin genes PIP1;4 and TIP3;1, in three contrasting chickpea genotypes under high vapor pressure deficit (VPD) treatment. The chickpea TIP3;1 gene got significantly up regulated under high VPD conditions with higher relative expression in the drought susceptible genotype, confirming the suitability of the selected reference genes for expression analysis. This is the first comprehensive study on the stability of the new generation reference genes for qPCR studies in chickpea across species, different tissues and abiotic stresses. PMID:26863232

Identification and Validation of Reference Genes and Their Impact on Normalized Gene Expression Studies across Cultivated and Wild Cicer Species.

PubMed

Reddy, Dumbala Srinivas; Bhatnagar-Mathur, Pooja; Reddy, Palakolanu Sudhakar; Sri Cindhuri, Katamreddy; Sivaji Ganesh, Adusumalli; Sharma, Kiran Kumar

2016-01-01

Quantitative Real-Time PCR (qPCR) is a preferred and reliable method for accurate quantification of gene expression to understand precise gene functions. A total of 25 candidate reference genes including traditional and new generation reference genes were selected and evaluated in a diverse set of chickpea samples. The samples used in this study included nine chickpea genotypes (Cicer spp.) comprising of cultivated and wild species, six abiotic stress treatments (drought, salinity, high vapor pressure deficit, abscisic acid, cold and heat shock), and five diverse tissues (leaf, root, flower, seedlings and seed). The geNorm, NormFinder and RefFinder algorithms used to identify stably expressed genes in four sample sets revealed stable expression of UCP and G6PD genes across genotypes, while TIP41 and CAC were highly stable under abiotic stress conditions. While PP2A and ABCT genes were ranked as best for different tissues, ABCT, UCP and CAC were most stable across all samples. This study demonstrated the usefulness of new generation reference genes for more accurate qPCR based gene expression quantification in cultivated as well as wild chickpea species. Validation of the best reference genes was carried out by studying their impact on normalization of aquaporin genes PIP1;4 and TIP3;1, in three contrasting chickpea genotypes under high vapor pressure deficit (VPD) treatment. The chickpea TIP3;1 gene got significantly up regulated under high VPD conditions with higher relative expression in the drought susceptible genotype, confirming the suitability of the selected reference genes for expression analysis. This is the first comprehensive study on the stability of the new generation reference genes for qPCR studies in chickpea across species, different tissues and abiotic stresses.

Epigenomic elements analyses for promoters identify ESRRG as a new susceptibility gene for obesity-related traits.

PubMed

Dong, S-S; Guo, Y; Zhu, D-L; Chen, X-F; Wu, X-M; Shen, H; Chen, X-D; Tan, L-J; Tian, Q; Deng, H-W; Yang, T-L

2016-07-01

With ENCODE epigenomic data and results from published genome-wide association studies (GWASs), we aimed to find regulatory signatures of obesity genes and discover novel susceptibility genes. Obesity genes were obtained from public GWAS databases and their promoters were annotated based on the regulatory element information. Significantly enriched or depleted epigenomic elements in the promoters of obesity genes were evaluated and all human genes were then prioritized according to the existence of the selected elements to predict new candidate genes. Top-ranked genes were subsequently applied to validate their associations with obesity-related traits in three independent in-house GWAS samples. We identified RAD21 and EZH2 as over-represented, and STAT2 (signal transducer and activator of transcription 2) and IRF3 (interferon regulatory transcription factor 3) as depleted transcription factors. Histone modification of H3K9me3 and chromatin state segmentation of 'poised promoter' and 'repressed' were over-represented. All genes were prioritized and we selected the top five genes for validation at the population level. Combining results from the three GWAS samples, rs7522101 in ESRRG (estrogen-related receptor-γ) remained significantly associated with body mass index after multiple testing corrections (P=7.25 × 10(-5)). It was also associated with β-cell function (P=1.99 × 10(-3)) and fasting glucose level (P<0.05) in the meta-analyses of glucose and insulin-related traits consortium (MAGIC) data set.Cnoclusions:In summary, we identified epigenomic characteristics for obesity genes and suggested ESRRG as a novel obesity-susceptibility gene.

Effect of carbon monoxide on gene expression in cerebrocortical astrocytes: Validation of reference genes for quantitative real-time PCR.

PubMed

Oliveira, Sara R; Vieira, Helena L A; Duarte, Carlos B

2015-09-15

Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is a widely used technique to characterize changes in gene expression in complex cellular and tissue processes, such as cytoprotection or inflammation. The accurate assessment of changes in gene expression depends on the selection of adequate internal reference gene(s). Carbon monoxide (CO) affects several metabolic pathways and de novo protein synthesis is crucial in the cellular responses to this gasotransmitter. Herein a selection of commonly used reference genes was analyzed to identify the most suitable internal control genes to evaluate the effect of CO on gene expression in cultured cerebrocortical astrocytes. The cells were exposed to CO by treatment with CORM-A1 (CO releasing molecule A1) and four different algorithms (geNorm, NormFinder, Delta Ct and BestKeeper) were applied to evaluate the stability of eight putative reference genes. Our results indicate that Gapdh (glyceraldehyde-3-phosphate dehydrogenase) together with Ppia (peptidylpropyl isomerase A) is the most suitable gene pair for normalization of qRT-PCR results under the experimental conditions used. Pgk1 (phosphoglycerate kinase 1), Hprt1 (hypoxanthine guanine phosphoribosyl transferase I), Sdha (Succinate Dehydrogenase Complex, Subunit A), Tbp (TATA box binding protein), Actg1 (actin gamma 1) and Rn18s (18S rRNA) genes presented less stable expression profiles in cultured cortical astrocytes exposed to CORM-A1 for up to 60 min. For validation, we analyzed the effect of CO on the expression of Bdnf and bcl-2. Different results were obtained, depending on the reference genes used. A significant increase in the expression of both genes was found when the results were normalized with Gapdh and Ppia, in contrast with the results obtained when the other genes were used as reference. These findings highlight the need for a proper and accurate selection of the reference genes used in the quantification of qRT-PCR results in studies on the effect of CO in gene expression. Copyright © 2015 Elsevier Inc. All rights reserved.

In-depth analysis of internal control genes for quantitative real-time PCR in Brassica oleracea var. botrytis.

PubMed

Sheng, X G; Zhao, Z Q; Yu, H F; Wang, J S; Zheng, C F; Gu, H H

2016-07-15

Quantitative reverse-transcription PCR (qRT-PCR) is a versatile technique for the analysis of gene expression. The selection of stable reference genes is essential for the application of this technique. Cauliflower (Brassica oleracea L. var. botrytis) is a commonly consumed vegetable that is rich in vitamin, calcium, and iron. Thus far, to our knowledge, there have been no reports on the validation of suitable reference genes for the data normalization of qRT-PCR in cauliflower. In the present study, we analyzed 12 candidate housekeeping genes in cauliflower subjected to different abiotic stresses, hormone treatment conditions, and accessions. geNorm and NormFinder algorithms were used to assess the expression stability of these genes. ACT2 and TIP41 were selected as suitable reference genes across all experimental samples in this study. When different accessions were compared, ACT2 and UNK3 were found to be the most suitable reference genes. In the hormone and abiotic stress treatments, ACT2, TIP41, and UNK2 were the most stably expressed. Our study also provided guidelines for selecting the best reference genes under various experimental conditions.

Anticancer drug sensitivity prediction in cell lines from baseline gene expression through recursive feature selection.

PubMed

Dong, Zuoli; Zhang, Naiqian; Li, Chun; Wang, Haiyun; Fang, Yun; Wang, Jun; Zheng, Xiaoqi

2015-06-30

An enduring challenge in personalized medicine is to select right drug for individual patients. Testing drugs on patients in large clinical trials is one way to assess their efficacy and toxicity, but it is impractical to test hundreds of drugs currently under development. Therefore the preclinical prediction model is highly expected as it enables prediction of drug response to hundreds of cell lines in parallel. Recently, two large-scale pharmacogenomic studies screened multiple anticancer drugs on over 1000 cell lines in an effort to elucidate the response mechanism of anticancer drugs. To this aim, we here used gene expression features and drug sensitivity data in Cancer Cell Line Encyclopedia (CCLE) to build a predictor based on Support Vector Machine (SVM) and a recursive feature selection tool. Robustness of our model was validated by cross-validation and an independent dataset, the Cancer Genome Project (CGP). Our model achieved good cross validation performance for most drugs in the Cancer Cell Line Encyclopedia (≥80% accuracy for 10 drugs, ≥75% accuracy for 19 drugs). Independent tests on eleven common drugs between CCLE and CGP achieved satisfactory performance for three of them, i.e., AZD6244, Erlotinib and PD-0325901, using expression levels of only twelve, six and seven genes, respectively. These results suggest that drug response could be effectively predicted from genomic features. Our model could be applied to predict drug response for some certain drugs and potentially play a complementary role in personalized medicine.

Gene selection in cancer classification using sparse logistic regression with Bayesian regularization.

PubMed

Cawley, Gavin C; Talbot, Nicola L C

2006-10-01

Gene selection algorithms for cancer classification, based on the expression of a small number of biomarker genes, have been the subject of considerable research in recent years. Shevade and Keerthi propose a gene selection algorithm based on sparse logistic regression (SLogReg) incorporating a Laplace prior to promote sparsity in the model parameters, and provide a simple but efficient training procedure. The degree of sparsity obtained is determined by the value of a regularization parameter, which must be carefully tuned in order to optimize performance. This normally involves a model selection stage, based on a computationally intensive search for the minimizer of the cross-validation error. In this paper, we demonstrate that a simple Bayesian approach can be taken to eliminate this regularization parameter entirely, by integrating it out analytically using an uninformative Jeffrey's prior. The improved algorithm (BLogReg) is then typically two or three orders of magnitude faster than the original algorithm, as there is no longer a need for a model selection step. The BLogReg algorithm is also free from selection bias in performance estimation, a common pitfall in the application of machine learning algorithms in cancer classification. The SLogReg, BLogReg and Relevance Vector Machine (RVM) gene selection algorithms are evaluated over the well-studied colon cancer and leukaemia benchmark datasets. The leave-one-out estimates of the probability of test error and cross-entropy of the BLogReg and SLogReg algorithms are very similar, however the BlogReg algorithm is found to be considerably faster than the original SLogReg algorithm. Using nested cross-validation to avoid selection bias, performance estimation for SLogReg on the leukaemia dataset takes almost 48 h, whereas the corresponding result for BLogReg is obtained in only 1 min 24 s, making BLogReg by far the more practical algorithm. BLogReg also demonstrates better estimates of conditional probability than the RVM, which are of great importance in medical applications, with similar computational expense. A MATLAB implementation of the sparse logistic regression algorithm with Bayesian regularization (BLogReg) is available from http://theoval.cmp.uea.ac.uk/~gcc/cbl/blogreg/

When is hub gene selection better than standard meta-analysis?

PubMed

Langfelder, Peter; Mischel, Paul S; Horvath, Steve

2013-01-01

Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when) hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data). Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis) and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility) in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA) in three comprehensive and unbiased empirical studies: (1) Finding genes predictive of lung cancer survival, (2) finding methylation markers related to age, and (3) finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1). However, standard meta-analysis methods perform as good as (if not better than) a consensus network approach in terms of validation success (criterion 2). The article also reports a comparison of meta-analysis techniques applied to gene expression data and presents novel R functions for carrying out consensus network analysis, network based screening, and meta analysis.

Selection and validation of reference genes for qRT-PCR analysis during biological invasions: The thermal adaptability of Bemisia tabaci MED.

PubMed

Dai, Tian-Mei; Lü, Zhi-Chuang; Liu, Wan-Xue; Wan, Fang-Hao

2017-01-01

The Bemisia tabaci Mediterranean (MED) cryptic species has been rapidly invading to most parts of the world owing to its strong ecological adaptability, which is considered as a model insect for stress tolerance studies under rapidly changing environments. Selection of a suitable reference gene for quantitative stress-responsive gene expression analysis based on qRT-PCR is critical for elaborating the molecular mechanisms of thermotolerance. To obtain accurate and reliable normalization data in MED, eight candidate reference genes (β-act, GAPDH, β-tub, EF1-α, GST, 18S, RPL13A and α-tub) were examined under various thermal stresses for varied time periods by using geNorm, NormFinder and BestKeeper algorithms, respectively. Our results revealed that β-tub and EF1-α were the best reference genes across all sample sets. On the other hand, 18S and GADPH showed the least stability for all the samples studied. β-act was proved to be highly stable only in case of short-term thermal stresses. To our knowledge this was the first comprehensive report on validation of reference genes under varying temperature stresses in MED. The study could expedite particular discovery of thermotolerance genes in MED. Further, the present results can form the basis of further research on suitable reference genes in this invasive insect and will facilitate transcript profiling in other invasive insects.

Validation of reference genes for quantitative gene expression analysis in experimental epilepsy.

PubMed

Sadangi, Chinmaya; Rosenow, Felix; Norwood, Braxton A

2017-12-01

To grasp the molecular mechanisms and pathophysiology underlying epilepsy development (epileptogenesis) and epilepsy itself, it is important to understand the gene expression changes that occur during these phases. Quantitative real-time polymerase chain reaction (qPCR) is a technique that rapidly and accurately determines gene expression changes. It is crucial, however, that stable reference genes are selected for each experimental condition to ensure that accurate values are obtained for genes of interest. If reference genes are unstably expressed, this can lead to inaccurate data and erroneous conclusions. To date, epilepsy studies have used mostly single, nonvalidated reference genes. This is the first study to systematically evaluate reference genes in male Sprague-Dawley rat models of epilepsy. We assessed 15 potential reference genes in hippocampal tissue obtained from 2 different models during epileptogenesis, 1 model during chronic epilepsy, and a model of noninjurious seizures. Reference gene ranking varied between models and also differed between epileptogenesis and chronic epilepsy time points. There was also some variance between the four mathematical models used to rank reference genes. Notably, we found novel reference genes to be more stably expressed than those most often used in experimental epilepsy studies. The consequence of these findings is that reference genes suitable for one epilepsy model may not be appropriate for others and that reference genes can change over time. It is, therefore, critically important to validate potential reference genes before using them as normalizing factors in expression analysis in order to ensure accurate, valid results. © 2017 Wiley Periodicals, Inc.

First siRNA library screening in hard-to-transfect HUVEC cells

PubMed Central

Zumbansen, Markus; Altrogge, Ludger M; Spottke, Nicole UE; Spicker, Sonja; Offizier, Sheila M; Domzalski, Sandra BS; St Amand, Allison L; Toell, Andrea; Leake, Devin; Mueller-Hartmann, Herbert A

2010-01-01

Meaningful RNAi-based data for target gene identification are strongly dependent on the use of a biologically relevant cell type and efficient delivery of highly functional siRNA reagents into the selected cell type. Here we report the use of the Amaxa® Nucleofector® 96-well Shuttle® System for siRNA screening in primary cells. Lonza's Clonetics® HUVEC-Human Umbilical Vein Endothelial Cells were transfected with Thermo Scientific Dharmacon siGENOME® siRNA Libraries targeting protein kinases and cell cycle related genes and screened for genes important for cell viability. Of the 37 primary hits, down-regulation of 33 led to reduced proliferation or increased cell death, while down-regulation of two allowed for better cell viability. The validated four genes out of the 16 strongest primary hits (COPB2, PYCS, CDK4 and MYC) influenced cell proliferation to varying degrees, reflecting differing importance for survival of HUVEC cells. Our results demonstrate that the Nucleofector® 96-well Shuttle® System allows the delivery of siRNA libraries in cell types previously considered to be difficult to transfect. Thus, identification and validation of gene targets can now be conducted in primary cells, as the selection of cell types is not limited to those accessible by lipid-mediated transfection. PMID:20628494

Analysis of the GRNs Inference by Using Tsallis Entropy and a Feature Selection Approach

NASA Astrophysics Data System (ADS)

Lopes, Fabrício M.; de Oliveira, Evaldo A.; Cesar, Roberto M.

An important problem in the bioinformatics field is to understand how genes are regulated and interact through gene networks. This knowledge can be helpful for many applications, such as disease treatment design and drugs creation purposes. For this reason, it is very important to uncover the functional relationship among genes and then to construct the gene regulatory network (GRN) from temporal expression data. However, this task usually involves data with a large number of variables and small number of observations. In this way, there is a strong motivation to use pattern recognition and dimensionality reduction approaches. In particular, feature selection is specially important in order to select the most important predictor genes that can explain some phenomena associated with the target genes. This work presents a first study about the sensibility of entropy methods regarding the entropy functional form, applied to the problem of topology recovery of GRNs. The generalized entropy proposed by Tsallis is used to study this sensibility. The inference process is based on a feature selection approach, which is applied to simulated temporal expression data generated by an artificial gene network (AGN) model. The inferred GRNs are validated in terms of global network measures. Some interesting conclusions can be drawn from the experimental results, as reported for the first time in the present paper.

Gene selection heuristic algorithm for nutrigenomics studies.

PubMed

Valour, D; Hue, I; Grimard, B; Valour, B

2013-07-15

Large datasets from -omics studies need to be deeply investigated. The aim of this paper is to provide a new method (LEM method) for the search of transcriptome and metabolome connections. The heuristic algorithm here described extends the classical canonical correlation analysis (CCA) to a high number of variables (without regularization) and combines well-conditioning and fast-computing in "R." Reduced CCA models are summarized in PageRank matrices, the product of which gives a stochastic matrix that resumes the self-avoiding walk covered by the algorithm. Then, a homogeneous Markov process applied to this stochastic matrix converges the probabilities of interconnection between genes, providing a selection of disjointed subsets of genes. This is an alternative to regularized generalized CCA for the determination of blocks within the structure matrix. Each gene subset is thus linked to the whole metabolic or clinical dataset that represents the biological phenotype of interest. Moreover, this selection process reaches the aim of biologists who often need small sets of genes for further validation or extended phenotyping. The algorithm is shown to work efficiently on three published datasets, resulting in meaningfully broadened gene networks.

Gene Therapy in Heart Failure.

PubMed

Fargnoli, Anthony S; Katz, Michael G; Bridges, Charles R; Hajjar, Roger J

2017-01-01

Heart failure is a significant burden to the global healthcare system and represents an underserved market for new pharmacologic strategies, especially therapies which can address root cause myocyte dysfunction. Modern drugs, surgeries, and state-of-the-art interventions are costly and do not improve survival outcome measures. Gene therapy is an attractive strategy, whereby selected gene targets and their associated regulatory mechanisms can be permanently managed therapeutically in a single treatment. This in theory could be sustainable for the patient's life. Despite the promise, however, gene therapy has numerous challenges that must be addressed together as a treatment plan comprising these key elements: myocyte physiologic target validation, gene target manipulation strategy, vector selection for the correct level of manipulation, and carefully utilizing an efficient delivery route that can be implemented in the clinic to efficiently transfer the therapy within safety limits. This chapter summarizes the key developments in cardiac gene therapy from the perspective of understanding each of these components of the treatment plan. The latest pharmacologic gene targets, gene therapy vectors, delivery routes, and strategies are reviewed.

Validation of endogenous reference genes for qRT-PCR analysis of human visceral adipose samples

PubMed Central

2010-01-01

Background Given the epidemic proportions of obesity worldwide and the concurrent prevalence of metabolic syndrome, there is an urgent need for better understanding the underlying mechanisms of metabolic syndrome, in particular, the gene expression differences which may participate in obesity, insulin resistance and the associated series of chronic liver conditions. Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in different tissues and experimental conditions. However, variations in amount of starting material, enzymatic efficiency and presence of inhibitors can lead to quantification errors. Hence the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Recent studies have shown that both obesity and presence of insulin resistance influence an expression of commonly used reference genes in omental fat. In this study we validated candidate reference genes suitable for qRT-PCR profiling experiments using visceral adipose samples from obese and lean individuals. Results Cross-validation of expression stability of eight selected reference genes using three popular algorithms, GeNorm, NormFinder and BestKeeper found ACTB and RPII as most stable reference genes. Conclusions We recommend ACTB and RPII as stable reference genes most suitable for gene expression studies of human visceral adipose tissue. The use of these genes as a reference pair may further enhance the robustness of qRT-PCR in this model system. PMID:20492695

Validation of endogenous reference genes for qRT-PCR analysis of human visceral adipose samples.

PubMed

Mehta, Rohini; Birerdinc, Aybike; Hossain, Noreen; Afendy, Arian; Chandhoke, Vikas; Younossi, Zobair; Baranova, Ancha

2010-05-21

Given the epidemic proportions of obesity worldwide and the concurrent prevalence of metabolic syndrome, there is an urgent need for better understanding the underlying mechanisms of metabolic syndrome, in particular, the gene expression differences which may participate in obesity, insulin resistance and the associated series of chronic liver conditions. Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in different tissues and experimental conditions. However, variations in amount of starting material, enzymatic efficiency and presence of inhibitors can lead to quantification errors. Hence the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Recent studies have shown that both obesity and presence of insulin resistance influence an expression of commonly used reference genes in omental fat. In this study we validated candidate reference genes suitable for qRT-PCR profiling experiments using visceral adipose samples from obese and lean individuals. Cross-validation of expression stability of eight selected reference genes using three popular algorithms, GeNorm, NormFinder and BestKeeper found ACTB and RPII as most stable reference genes. We recommend ACTB and RPII as stable reference genes most suitable for gene expression studies of human visceral adipose tissue. The use of these genes as a reference pair may further enhance the robustness of qRT-PCR in this model system.

Digital gene expression profiling analysis and its application in the identification of genes associated with improved response to neoadjuvant chemotherapy in breast cancer.

PubMed

Liu, Xiaozhen; Jin, Gan; Qian, Jiacheng; Yang, Hongjian; Tang, Hongchao; Meng, Xuli; Li, Yongfeng

2018-04-23

This study aimed to screen sensitive biomarkers for the efficacy evaluation of neoadjuvant chemotherapy in breast cancer. In this study, Illumina digital gene expression sequencing technology was applied and differentially expressed genes (DEGs) between patients presenting pathological complete response (pCR) and non-pathological complete response (NpCR) were identified. Further, gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were then performed. The genes in significant enriched pathways were finally quantified by quantitative real-time PCR (qRT-PCR) to confirm that they were differentially expressed. Additionally, GSE23988 from Gene Expression Omnibus database was used as the validation dataset to confirm the DEGs. After removing the low-quality reads, 715 DEGs were finally detected. After mapping to KEGG pathways, 10 DEGs belonging to the ubiquitin proteasome pathway (HECTD3, PSMB10, UBD, UBE2C, and UBE2S) and cytokine-cytokine receptor interactions (CCL2, CCR1, CXCL10, CXCL11, and IL2RG) were selected for further analysis. These 10 genes were finally quantified by qRT-PCR to confirm that they were differentially expressed (the log 2 fold changes of selected genes were - 5.34, 7.81, 6.88, 5.74, 3.11, 19.58, 8.73, 8.88, 7.42, and 34.61 for HECTD3, PSMB10, UBD, UBE2C, UBE2S, CCL2, CCR1, CXCL10, CXCL11, and IL2RG, respectively). Moreover, 53 common genes were confirmed by the validation dataset, including downregulated UBE2C and UBE2S. Our results suggested that these 10 genes belonging to these two pathways might be useful as sensitive biomarkers for the efficacy evaluation of neoadjuvant chemotherapy in breast cancer.

Analysis of genetic association using hierarchical clustering and cluster validation indices.

PubMed

Pagnuco, Inti A; Pastore, Juan I; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia L

2017-10-01

It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, based on some criteria of similarity. This task is usually performed by clustering algorithms, where the genes are clustered into meaningful groups based on their expression values in a set of experiment. In this work, we propose a method to find sets of co-expressed genes, based on cluster validation indices as a measure of similarity for individual gene groups, and a combination of variants of hierarchical clustering to generate the candidate groups. We evaluated its ability to retrieve significant sets on simulated correlated and real genomics data, where the performance is measured based on its detection ability of co-regulated sets against a full search. Additionally, we analyzed the quality of the best ranked groups using an online bioinformatics tool that provides network information for the selected genes. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of Differentially Expressed Genes and Pathways for Myofiber Characteristics in Soleus Muscles between Chicken Breeds Differing in Meat Quality.

PubMed

Du, Y F; Ding, Q L; Li, Y M; Fang, W R

2017-04-03

In the modern chicken industry, fast-growing broilers have undergone strong artificial selection for muscle growth, which has led to remarkable phenotypic variations compared with slow-growing chickens. However, the molecular mechanism underlying these phenotypes differences remains unknown. In this study, a systematic identification of candidate genes and new pathways related to myofiber development and composition in chicken Soleus muscle (SOL) has been made using gene expression profiles of two distinct breeds: Qingyuan partridge (QY), a slow-growing Chinese breed possessing high meat quality and Cobb 500 (CB), a commercial fast-growing broiler line. Agilent cDNA microarray analyses were conducted to determine gene expression profiles of soleus muscle sampled at sexual maturity age of QY (112 d) and CB (42 d). The 1318 genes with at least 2-fold differences were identified (P < 0.05, FDR <0.05, FC ≥ 2) in SOL muscles of QY and CB chickens. Differentially expressed genes (DEGs) related to muscle development, energy metabolism or lipid metabolism processes were examined further in each breed based on Gene Ontology (GO) analysis, and 11 genes involved in these processes were selected for further validation studies by qRT-PCR. In addition, based on KEGG pathway analysis of DEGs in both QY and CB chickens, it was found that in addition to pathways affecting myogenic fibre-type development and differentiation (pathways for Hedgehog & Calcium signaling), energy metabolism (Phosphatidylinositol signaling system, VEGF signaling pathway, Purine metabolism, Pyrimidine metabolism) were also enriched and might form a network with pathways related to muscle metabolism to influence the development of myofibers. This study is the first stage in the understanding of molecular mechanisms underlying variations in poultry meat quality. Large scale analyses are now required to validate the role of the genes identified and ultimately to find molecular markers that can be used for selection or to optimize rearing practices.

Generation and validation of PAX7 reporter lines from human iPS cells using CRISPR/Cas9 technology.

PubMed

Wu, Jianbo; Hunt, Samuel D; Xue, Haipeng; Liu, Ying; Darabi, Radbod

2016-03-01

Directed differentiation of iPS cells toward various tissue progenitors has been the focus of recent research. Therefore, generation of tissue-specific reporter iPS cell lines provides better understanding of developmental stages in iPS cells. This technical report describes an efficient strategy for generation and validation of knock-in reporter lines in human iPS cells using the Cas9-nickase system. Here, we have generated a knock-in human iPS cell line for the early myogenic lineage specification gene of PAX7. By introduction of site-specific double-stranded breaks (DSB) in the genomic locus of PAX7 using CRISPR/Cas9 nickase pairs, a 2A-GFP reporter with selection markers has been incorporated before the stop codon of the PAX7 gene at the last exon. After positive and negative selection, single cell-derived human iPS clones have been isolated and sequenced for in-frame positioning of the reporter construct. Finally, by using a nuclease-dead Cas9 activator (dCas9-VP160) system, the promoter region of PAX7 has been targeted for transient gene induction to validate the GFP reporter activity. This was confirmed by flow cytometry analysis and immunostaining for PAX7 and GFP. This technical report provides a practical guideline for generation and validation of knock-in reporters using CRISPR/Cas9 system. Published by Elsevier B.V.

Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma | Office of Cancer Genomics

Cancer.gov

In a recent Nature article, Morin et al. uncovered a novel role for chromatin modification in driving the progression of two non-Hodgkin lymphomas (NHLs), follicular lymphoma and diffuse large B-cell lymphoma. Through DNA and RNA sequencing of 117 tumor samples and 10 assorted cell lines, the authors identified and validated 109 genes with multiple mutations in these B-cell NHLs. Of the 109 genes, several genes not previously linked to lymphoma demonstrated positive selection for mutation including two genes involved in histone modification, MLL2 and MEF2B.

Genes@Work: an efficient algorithm for pattern discovery and multivariate feature selection in gene expression data.

PubMed

Lepre, Jorge; Rice, J Jeremy; Tu, Yuhai; Stolovitzky, Gustavo

2004-05-01

Despite the growing literature devoted to finding differentially expressed genes in assays probing different tissues types, little attention has been paid to the combinatorial nature of feature selection inherent to large, high-dimensional gene expression datasets. New flexible data analysis approaches capable of searching relevant subgroups of genes and experiments are needed to understand multivariate associations of gene expression patterns with observed phenotypes. We present in detail a deterministic algorithm to discover patterns of multivariate gene associations in gene expression data. The patterns discovered are differential with respect to a control dataset. The algorithm is exhaustive and efficient, reporting all existent patterns that fit a given input parameter set while avoiding enumeration of the entire pattern space. The value of the pattern discovery approach is demonstrated by finding a set of genes that differentiate between two types of lymphoma. Moreover, these genes are found to behave consistently in an independent dataset produced in a different laboratory using different arrays, thus validating the genes selected using our algorithm. We show that the genes deemed significant in terms of their multivariate statistics will be missed using other methods. Our set of pattern discovery algorithms including a user interface is distributed as a package called Genes@Work. This package is freely available to non-commercial users and can be downloaded from our website (http://www.research.ibm.com/FunGen).

Systems Biology-Based Identification of Mycobacterium tuberculosis Persistence Genes in Mouse Lungs

PubMed Central

Dutta, Noton K.; Bandyopadhyay, Nirmalya; Veeramani, Balaji; Lamichhane, Gyanu; Karakousis, Petros C.; Bader, Joel S.

2014-01-01

ABSTRACT Identifying Mycobacterium tuberculosis persistence genes is important for developing novel drugs to shorten the duration of tuberculosis (TB) treatment. We developed computational algorithms that predict M. tuberculosis genes required for long-term survival in mouse lungs. As the input, we used high-throughput M. tuberculosis mutant library screen data, mycobacterial global transcriptional profiles in mice and macrophages, and functional interaction networks. We selected 57 unique, genetically defined mutants (18 previously tested and 39 untested) to assess the predictive power of this approach in the murine model of TB infection. We observed a 6-fold enrichment in the predicted set of M. tuberculosis genes required for persistence in mouse lungs relative to randomly selected mutant pools. Our results also allowed us to reclassify several genes as required for M. tuberculosis persistence in vivo. Finally, the new results implicated additional high-priority candidate genes for testing. Experimental validation of computational predictions demonstrates the power of this systems biology approach for elucidating M. tuberculosis persistence genes. PMID:24549847

A large-scale benchmark of gene prioritization methods.

PubMed

Guala, Dimitri; Sonnhammer, Erik L L

2017-04-21

In order to maximize the use of results from high-throughput experimental studies, e.g. GWAS, for identification and diagnostics of new disease-associated genes, it is important to have properly analyzed and benchmarked gene prioritization tools. While prospective benchmarks are underpowered to provide statistically significant results in their attempt to differentiate the performance of gene prioritization tools, a strategy for retrospective benchmarking has been missing, and new tools usually only provide internal validations. The Gene Ontology(GO) contains genes clustered around annotation terms. This intrinsic property of GO can be utilized in construction of robust benchmarks, objective to the problem domain. We demonstrate how this can be achieved for network-based gene prioritization tools, utilizing the FunCoup network. We use cross-validation and a set of appropriate performance measures to compare state-of-the-art gene prioritization algorithms: three based on network diffusion, NetRank and two implementations of Random Walk with Restart, and MaxLink that utilizes network neighborhood. Our benchmark suite provides a systematic and objective way to compare the multitude of available and future gene prioritization tools, enabling researchers to select the best gene prioritization tool for the task at hand, and helping to guide the development of more accurate methods.

Evaluation of Suitable Reference Genes for Normalization of qPCR Gene Expression Studies in Brinjal (Solanum melongena L.) During Fruit Developmental Stages.

PubMed

Kanakachari, Mogilicherla; Solanke, Amolkumar U; Prabhakaran, Narayanasamy; Ahmad, Israr; Dhandapani, Gurusamy; Jayabalan, Narayanasamy; Kumar, Polumetla Ananda

2016-02-01

Brinjal/eggplant/aubergine is one of the major solanaceous vegetable crops. Recent availability of genome information greatly facilitates the fundamental research on brinjal. Gene expression patterns during different stages of fruit development can provide clues towards the understanding of its biological functions. Quantitative real-time PCR (qPCR) has become one of the most widely used methods for rapid and accurate quantification of gene expression. However, its success depends on the use of a suitable reference gene for data normalization. For qPCR analysis, a single reference gene is not universally suitable for all experiments. Therefore, reference gene validation is a crucial step. Suitable reference genes for qPCR analysis of brinjal fruit development have not been investigated so far. In this study, we have selected 21 candidate reference genes from the Brinjal (Solanum melongena) Plant Gene Indices database (compbio.dfci.harvard.edu/tgi/plant.html) and studied their expression profiles by qPCR during six different fruit developmental stages (0, 5, 10, 20, 30, and 50 days post anthesis) along with leaf samples of the Pusa Purple Long (PPL) variety. To evaluate the stability of gene expression, geNorm and NormFinder analytical softwares were used. geNorm identified SAND (SAND family protein) and TBP (TATA binding protein) as the best pairs of reference genes in brinjal fruit development. The results showed that for brinjal fruit development, individual or a combination of reference genes should be selected for data normalization. NormFinder identified Expressed gene (expressed sequence) as the best single reference gene in brinjal fruit development. In this study, we have identified and validated for the first time reference genes to provide accurate transcript normalization and quantification at various fruit developmental stages of brinjal which can also be useful for gene expression studies in other Solanaceae plant species.

Selective targeting of KRAS-Mutant cells by miR-126 through repression of multiple genes essential for the survival of KRAS-Mutant cells

PubMed Central

Hara, Toshifumi; Jones, Matthew F.; Subramanian, Murugan; Li, Xiao Ling; Ou, Oliver; Zhu, Yuelin; Yang, Yuan; Wakefield, Lalage M.; Hussain, S. Perwez; Gaedcke, Jochen; Ried, Thomas; Luo, Ji; Caplen, Natasha J.; Lal, Ashish

2014-01-01

MicroRNAs (miRNAs) regulate the expression of hundreds of genes. However, identifying the critical targets within a miRNA-regulated gene network is challenging. One approach is to identify miRNAs that exert a context-dependent effect, followed by expression profiling to determine how specific targets contribute to this selective effect. In this study, we performed miRNA mimic screens in isogenic KRAS-Wild-type (WT) and KRAS-Mutant colorectal cancer (CRC) cell lines to identify miRNAs selectively targeting KRAS-Mutant cells. One of the miRNAs we identified as a selective inhibitor of the survival of multiple KRAS-Mutant CRC lines was miR-126. In KRAS-Mutant cells, miR-126 over-expression increased the G1 compartment, inhibited clonogenicity and tumorigenicity, while exerting no effect on KRAS-WT cells. Unexpectedly, the miR-126-regulated transcriptome of KRAS-WT and KRAS-Mutant cells showed no significant differences. However, by analyzing the overlap between miR-126 targets with the synthetic lethal genes identified by RNAi in KRAS-Mutant cells, we identified and validated a subset of miR-126-regulated genes selectively required for the survival and clonogenicity of KRAS-Mutant cells. Our strategy therefore identified critical target genes within the miR-126-regulated gene network. We propose that the selective effect of miR-126 on KRAS-Mutant cells could be utilized for the development of targeted therapy for KRAS mutant tumors. PMID:25245095

Selection of reference genes for transcriptional analysis of edible tubers of potato (Solanum tuberosum L.).

PubMed

Mariot, Roberta Fogliatto; de Oliveira, Luisa Abruzzi; Voorhuijzen, Marleen M; Staats, Martijn; Hutten, Ronald C B; Van Dijk, Jeroen P; Kok, Esther; Frazzon, Jeverson

2015-01-01

Potato (Solanum tuberosum) yield has increased dramatically over the last 50 years and this has been achieved by a combination of improved agronomy and biotechnology efforts. Gene studies are taking place to improve new qualities and develop new cultivars. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is a bench-marking analytical tool for gene expression analysis, but its accuracy is highly dependent on a reliable normalization strategy of an invariant reference genes. For this reason, the goal of this work was to select and validate reference genes for transcriptional analysis of edible tubers of potato. To do so, RT-qPCR primers were designed for ten genes with relatively stable expression in potato tubers as observed in RNA-Seq experiments. Primers were designed across exon boundaries to avoid genomic DNA contamination. Differences were observed in the ranking of candidate genes identified by geNorm, NormFinder and BestKeeper algorithms. The ranks determined by geNorm and NormFinder were very similar and for all samples the most stable candidates were C2, exocyst complex component sec3 (SEC3) and ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A). According to BestKeeper, the importin alpha and ubiquitin-associated/ts-n genes were the most stable. Three genes were selected as reference genes for potato edible tubers in RT-qPCR studies. The first one, called C2, was selected in common by NormFinder and geNorm, the second one is SEC3, selected by NormFinder, and the third one is CUL3A, selected by geNorm. Appropriate reference genes identified in this work will help to improve the accuracy of gene expression quantification analyses by taking into account differences that may be observed in RNA quality or reverse transcription efficiency across the samples.

Augmenting the Genetic Toolbox for Sulfolobus islandicus with a Stringent Positive Selectable Marker for Agmatine Prototrophy

PubMed Central

Cooper, Tara E.; Krause, David J.

2013-01-01

Sulfolobus species have become the model organisms for studying the unique biology of the crenarchaeal division of the archaeal domain. In particular, Sulfolobus islandicus provides a powerful opportunity to explore natural variation via experimental functional genomics. To support these efforts, we further expanded genetic tools for S. islandicus by developing a stringent positive selection for agmatine prototrophs in strains in which the argD gene, encoding arginine decarboxylase, has been deleted. Strains with deletions in argD were shown to be auxotrophic for agmatine even in nutrient-rich medium, but growth could be restored by either supplementation of exogenous agmatine or reintroduction of a functional copy of the argD gene from S. solfataricus P2 into the ΔargD host. Using this stringent selection, a robust targeted gene knockout system was established via an improved next generation of the MID (marker insertion and unmarked target gene deletion) method. Application of this novel system was validated by targeted knockout of the upsEF genes involved in UV-inducible cell aggregation formation. PMID:23835176

Reconstruction of the metabolic network of Pseudomonas aeruginosa to interrogate virulence factor synthesis

NASA Astrophysics Data System (ADS)

Bartell, Jennifer A.; Blazier, Anna S.; Yen, Phillip; Thøgersen, Juliane C.; Jelsbak, Lars; Goldberg, Joanna B.; Papin, Jason A.

2017-03-01

Virulence-linked pathways in opportunistic pathogens are putative therapeutic targets that may be associated with less potential for resistance than targets in growth-essential pathways. However, efficacy of virulence-linked targets may be affected by the contribution of virulence-related genes to metabolism. We evaluate the complex interrelationships between growth and virulence-linked pathways using a genome-scale metabolic network reconstruction of Pseudomonas aeruginosa strain PA14 and an updated, expanded reconstruction of P. aeruginosa strain PAO1. The PA14 reconstruction accounts for the activity of 112 virulence-linked genes and virulence factor synthesis pathways that produce 17 unique compounds. We integrate eight published genome-scale mutant screens to validate gene essentiality predictions in rich media, contextualize intra-screen discrepancies and evaluate virulence-linked gene distribution across essentiality datasets. Computational screening further elucidates interconnectivity between inhibition of virulence factor synthesis and growth. Successful validation of selected gene perturbations using PA14 transposon mutants demonstrates the utility of model-driven screening of therapeutic targets.

Selection of suitable reference genes for gene expression studies in Staphylococcus capitis during growth under erythromycin stress.

PubMed

Cui, Bintao; Smooker, Peter M; Rouch, Duncan A; Deighton, Margaret A

2016-08-01

Accurate and reproducible measurement of gene transcription requires appropriate reference genes, which are stably expressed under different experimental conditions to provide normalization. Staphylococcus capitis is a human pathogen that produces biofilm under stress, such as imposed by antimicrobial agents. In this study, a set of five commonly used staphylococcal reference genes (gyrB, sodA, recA, tuf and rpoB) were systematically evaluated in two clinical isolates of Staphylococcus capitis (S. capitis subspecies urealyticus and capitis, respectively) under erythromycin stress in mid-log and stationary phases. Two public software programs (geNorm and NormFinder) and two manual calculation methods, reference residue normalization (RRN) and relative quantitative (RQ), were applied. The potential reference genes selected by the four algorithms were further validated by comparing the expression of a well-studied biofilm gene (icaA) with phenotypic biofilm formation in S. capitis under four different experimental conditions. The four methods differed considerably in their ability to predict the most suitable reference gene or gene combination for comparing icaA expression under different conditions. Under the conditions used here, the RQ method provided better selection of reference genes than the other three algorithms; however, this finding needs to be confirmed with a larger number of isolates. This study reinforces the need to assess the stability of reference genes for analysis of target gene expression under different conditions and the use of more than one algorithm in such studies. Although this work was conducted using a specific human pathogen, it emphasizes the importance of selecting suitable reference genes for accurate normalization of gene expression more generally.

Evaluation of reference genes for quantitative real-time PCR in oil palm elite planting materials propagated by tissue culture.

PubMed

Chan, Pek-Lan; Rose, Ray J; Abdul Murad, Abdul Munir; Zainal, Zamri; Low, Eng-Ti Leslie; Ooi, Leslie Cheng-Li; Ooi, Siew-Eng; Yahya, Suzaini; Singh, Rajinder

2014-01-01

The somatic embryogenesis tissue culture process has been utilized to propagate high yielding oil palm. Due to the low callogenesis and embryogenesis rates, molecular studies were initiated to identify genes regulating the process, and their expression levels are usually quantified using reverse transcription quantitative real-time PCR (RT-qPCR). With the recent release of oil palm genome sequences, it is crucial to establish a proper strategy for gene analysis using RT-qPCR. Selection of the most suitable reference genes should be performed for accurate quantification of gene expression levels. In this study, eight candidate reference genes selected from cDNA microarray study and literature review were evaluated comprehensively across 26 tissue culture samples using RT-qPCR. These samples were collected from two tissue culture lines and media treatments, which consisted of leaf explants cultures, callus and embryoids from consecutive developmental stages. Three statistical algorithms (geNorm, NormFinder and BestKeeper) confirmed that the expression stability of novel reference genes (pOP-EA01332, PD00380 and PD00569) outperformed classical housekeeping genes (GAPDH, NAD5, TUBULIN, UBIQUITIN and ACTIN). PD00380 and PD00569 were identified as the most stably expressed genes in total samples, MA2 and MA8 tissue culture lines. Their applicability to validate the expression profiles of a putative ethylene-responsive transcription factor 3-like gene demonstrated the importance of using the geometric mean of two genes for normalization. Systematic selection of the most stably expressed reference genes for RT-qPCR was established in oil palm tissue culture samples. PD00380 and PD00569 were selected for accurate and reliable normalization of gene expression data from RT-qPCR. These data will be valuable to the research associated with the tissue culture process. Also, the method described here will facilitate the selection of appropriate reference genes in other oil palm tissues and in the expression profiling of genes relating to yield, biotic and abiotic stresses.

Data-adaptive test statistics for microarray data.

PubMed

Mukherjee, Sach; Roberts, Stephen J; van der Laan, Mark J

2005-09-01

An important task in microarray data analysis is the selection of genes that are differentially expressed between different tissue samples, such as healthy and diseased. However, microarray data contain an enormous number of dimensions (genes) and very few samples (arrays), a mismatch which poses fundamental statistical problems for the selection process that have defied easy resolution. In this paper, we present a novel approach to the selection of differentially expressed genes in which test statistics are learned from data using a simple notion of reproducibility in selection results as the learning criterion. Reproducibility, as we define it, can be computed without any knowledge of the 'ground-truth', but takes advantage of certain properties of microarray data to provide an asymptotically valid guide to expected loss under the true data-generating distribution. We are therefore able to indirectly minimize expected loss, and obtain results substantially more robust than conventional methods. We apply our method to simulated and oligonucleotide array data. By request to the corresponding author.

Sheep genome functional annotation reveals proximal regulatory elements contributed to the evolution of modern breeds.

PubMed

Naval-Sanchez, Marina; Nguyen, Quan; McWilliam, Sean; Porto-Neto, Laercio R; Tellam, Ross; Vuocolo, Tony; Reverter, Antonio; Perez-Enciso, Miguel; Brauning, Rudiger; Clarke, Shannon; McCulloch, Alan; Zamani, Wahid; Naderi, Saeid; Rezaei, Hamid Reza; Pompanon, Francois; Taberlet, Pierre; Worley, Kim C; Gibbs, Richard A; Muzny, Donna M; Jhangiani, Shalini N; Cockett, Noelle; Daetwyler, Hans; Kijas, James

2018-02-28

Domestication fundamentally reshaped animal morphology, physiology and behaviour, offering the opportunity to investigate the molecular processes driving evolutionary change. Here we assess sheep domestication and artificial selection by comparing genome sequence from 43 modern breeds (Ovis aries) and their Asian mouflon ancestor (O. orientalis) to identify selection sweeps. Next, we provide a comparative functional annotation of the sheep genome, validated using experimental ChIP-Seq of sheep tissue. Using these annotations, we evaluate the impact of selection and domestication on regulatory sequences and find that sweeps are significantly enriched for protein coding genes, proximal regulatory elements of genes and genome features associated with active transcription. Finally, we find individual sites displaying strong allele frequency divergence are enriched for the same regulatory features. Our data demonstrate that remodelling of gene expression is likely to have been one of the evolutionary forces that drove phenotypic diversification of this common livestock species.

With Reference to Reference Genes: A Systematic Review of Endogenous Controls in Gene Expression Studies.

PubMed

Chapman, Joanne R; Waldenström, Jonas

2015-01-01

The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR gene expression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate gene expression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies.

Microarray RNA expression analysis of cerebral white matter lesions reveals changes in multiple functional pathways.

PubMed

Simpson, Julie E; Hosny, Ola; Wharton, Stephen B; Heath, Paul R; Holden, Hazel; Fernando, Malee S; Matthews, Fiona; Forster, Gill; O'Brien, John T; Barber, Robert; Kalaria, Raj N; Brayne, Carol; Shaw, Pamela J; Lewis, Claire E; Ince, Paul G

2009-02-01

White matter lesions (WML) in brain aging are linked to dementia and depression. Ischemia contributes to their pathogenesis but other mechanisms may contribute. We used RNA microarray analysis with functional pathway grouping as an unbiased approach to investigate evidence for additional pathogenetic mechanisms. WML were identified by MRI and pathology in brains donated to the Medical Research Council Cognitive Function and Ageing Study Cognitive Function and Aging Study. RNA was extracted to compare WML with nonlesional white matter samples from cases with lesions (WM[L]), and from cases with no lesions (WM[C]) using RNA microarray and pathway analysis. Functional pathways were validated for selected genes by quantitative real-time polymerase chain reaction and immunocytochemistry. We identified 8 major pathways in which multiple genes showed altered RNA transcription (immune regulation, cell cycle, apoptosis, proteolysis, ion transport, cell structure, electron transport, metabolism) among 502 genes that were differentially expressed in WML compared to WM[C]. In WM[L], 409 genes were altered involving the same pathways. Genes selected to validate this microarray data all showed the expected changes in RNA levels and immunohistochemical expression of protein. WML represent areas with a complex molecular phenotype. From this and previous evidence, WML may arise through tissue ischemia but may also reflect the contribution of additional factors like blood-brain barrier dysfunction. Differential expression of genes in WM[L] compared to WM[C] indicate a "field effect" in the seemingly normal surrounding white matter.

Selection of Valid Reference Genes for Reverse Transcription Quantitative PCR Analysis in Heliconius numata (Lepidoptera: Nymphalidae)

PubMed Central

Chouteau, Mathieu; Whibley, Annabel; Joron, Mathieu; Llaurens, Violaine

2016-01-01

Identifying the genetic basis of adaptive variation is challenging in non-model organisms and quantitative real time PCR. is a useful tool for validating predictions regarding the expression of candidate genes. However, comparing expression levels in different conditions requires rigorous experimental design and statistical analyses. Here, we focused on the neotropical passion-vine butterflies Heliconius, non-model species studied in evolutionary biology for their adaptive variation in wing color patterns involved in mimicry and in the signaling of their toxicity to predators. We aimed at selecting stable reference genes to be used for normalization of gene expression data in RT-qPCR analyses from developing wing discs according to the minimal guidelines described in Minimum Information for publication of Quantitative Real-Time PCR Experiments (MIQE). To design internal RT-qPCR controls, we studied the stability of expression of nine candidate reference genes (actin, annexin, eF1α, FK506BP, PolyABP, PolyUBQ, RpL3, RPS3A, and tubulin) at two developmental stages (prepupal and pupal) using three widely used programs (GeNorm, NormFinder and BestKeeper). Results showed that, despite differences in statistical methods, genes RpL3, eF1α, polyABP, and annexin were stably expressed in wing discs in late larval and pupal stages of Heliconius numata. This combination of genes may be used as a reference for a reliable study of differential expression in wings for instance for genes involved in important phenotypic variation, such as wing color pattern variation. Through this example, we provide general useful technical recommendations as well as relevant statistical strategies for evolutionary biologists aiming to identify candidate-genes involved adaptive variation in non-model organisms. PMID:27271971

Reference genes for real-time PCR quantification of messenger RNAs and microRNAs in mouse model of obesity.

PubMed

Matoušková, Petra; Bártíková, Hana; Boušová, Iva; Hanušová, Veronika; Szotáková, Barbora; Skálová, Lenka

2014-01-01

Obesity and metabolic syndrome is increasing health problem worldwide. Among other ways, nutritional intervention using phytochemicals is important method for treatment and prevention of this disease. Recent studies have shown that certain phytochemicals could alter the expression of specific genes and microRNAs (miRNAs) that play a fundamental role in the pathogenesis of obesity. For study of the obesity and its treatment, monosodium glutamate (MSG)-injected mice with developed central obesity, insulin resistance and liver lipid accumulation are frequently used animal models. To understand the mechanism of phytochemicals action in obese animals, the study of selected genes expression together with miRNA quantification is extremely important. For this purpose, real-time quantitative PCR is a sensitive and reproducible method, but it depends on proper normalization entirely. The aim of present study was to identify the appropriate reference genes for mRNA and miRNA quantification in MSG mice treated with green tea catechins, potential anti-obesity phytochemicals. Two sets of reference genes were tested: first set contained seven commonly used genes for normalization of messenger RNA, the second set of candidate reference genes included ten small RNAs for normalization of miRNA. The expression stability of these reference genes were tested upon treatment of mice with catechins using geNorm, NormFinder and BestKeeper algorithms. Selected normalizers for mRNA quantification were tested and validated on expression of quinone oxidoreductase, biotransformation enzyme known to be modified by catechins. The effect of selected normalizers for miRNA quantification was tested on two obesity- and diabetes- related miRNAs, miR-221 and miR-29b, respectively. Finally, the combinations of B2M/18S/HPRT1 and miR-16/sno234 were validated as optimal reference genes for mRNA and miRNA quantification in liver and 18S/RPlP0/HPRT1 and sno234/miR-186 in small intestine of MSG mice. These reference genes will be used for mRNA and miRNA normalization in further study of green tea catechins action in obese mice.

An Integrative Framework for Bayesian Variable Selection with Informative Priors for Identifying Genes and Pathways

PubMed Central

Ander, Bradley P.; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R.; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with ‘large p, small n’ problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed. PMID:23844055

An integrative framework for Bayesian variable selection with informative priors for identifying genes and pathways.

PubMed

Peng, Bin; Zhu, Dianwen; Ander, Bradley P; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with 'large p, small n' problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed.

Toward a comprehensive and systematic methylome signature in colorectal cancers.

PubMed

Ashktorab, Hassan; Rahi, Hamed; Wansley, Daniel; Varma, Sudhir; Shokrani, Babak; Lee, Edward; Daremipouran, Mohammad; Laiyemo, Adeyinka; Goel, Ajay; Carethers, John M; Brim, Hassan

2013-08-01

CpG Island Methylator Phenotype (CIMP) is one of the underlying mechanisms in colorectal cancer (CRC). This study aimed to define a methylome signature in CRC through a methylation microarray analysis and a compilation of promising CIMP markers from the literature. Illumina HumanMethylation27 (IHM27) array data was generated and analyzed based on statistical differences in methylation data (1st approach) or based on overall differences in methylation percentages using lower 95% CI (2nd approach). Pyrosequencing was performed for the validation of nine genes. A meta-analysis was used to identify CIMP and non-CIMP markers that were hypermethylated in CRC but did not yet make it to the CIMP genes' list. Our 1st approach for array data analysis demonstrated the limitations in selecting genes for further validation, highlighting the need for the 2nd bioinformatics approach to adequately select genes with differential aberrant methylation. A more comprehensive list, which included non-CIMP genes, such as APC, EVL, CD109, PTEN, TWIST1, DCC, PTPRD, SFRP1, ICAM5, RASSF1A, EYA4, 30ST2, LAMA1, KCNQ5, ADHEF1, and TFPI2, was established. Array data are useful to categorize and cluster colonic lesions based on their global methylation profiles; however, its usefulness in identifying robust methylation markers is limited and rely on the data analysis method. We have identified 16 non-CIMP-panel genes for which we provide rationale for inclusion in a more comprehensive characterization of CIMP+ CRCs. The identification of a definitive list for methylome specific genes in CRC will contribute to better clinical management of CRC patients.

Exploring valid internal-control genes in Porphyra yezoensis (Bangiaceae) during stress response conditions

NASA Astrophysics Data System (ADS)

Wang, Wenlei; Wu, Xiaojie; Wang, Chao; Jia, Zhaojun; He, Linwen; Wei, Yifan; Niu, Jianfeng; Wang, Guangce

2014-07-01

To screen the stable expression genes related to the stress (strong light, dehydration and temperature shock) we applied Absolute real-time PCR technology to determine the transcription numbers of the selected test genes in P orphyra yezoensis, which has been regarded as a potential model species responding the stress conditions in the intertidal. Absolute real-time PCR technology was applied to determine the transcription numbers of the selected test genes in P orphyra yezoensis, which has been regarded as a potential model species in stress responding. According to the results of photosynthesis parameters, we observed that Y(II) and F v/ F m were significantly affected when stress was imposed on the thalli of P orphyra yezoensis, but underwent almost completely recovered under normal conditions, which were collected for the following experiments. Then three samples, which were treated with different grade stresses combined with salinity, irradiation and temperature, were collected. The transcription numbers of seven constitutive expression genes in above samples were determined after RNA extraction and cDNA synthesis. Finally, a general insight into the selection of internal control genes during stress response was obtained. We found that there were no obvious effects in terms of salinity stress (at salinity 90) on transcription of most genes used in the study. The 18S ribosomal RNA gene had the highest expression level, varying remarkably among different tested groups. RPS8 expression showed a high irregular variance between samples. GAPDH presented comparatively stable expression and could thus be selected as the internal control. EF-1α showed stable expression during the series of multiple-stress tests. Our research provided available references for the selection of internal control genes for transcripts determination of P. yezoensis.

Positive Selection at the Polyhomeotic Locus Led to Decreased Thermosensitivity of Gene Expression in Temperate Drosophila melanogaster

PubMed Central

Voigt, Susanne; Laurent, Stefan; Litovchenko, Maria; Stephan, Wolfgang

2015-01-01

Drosophila melanogaster as a cosmopolitan species has successfully adapted to a wide range of different environments. Variation in temperature is one important environmental factor that influences the distribution of species in nature. In particular for insects, which are mostly ectotherms, ambient temperature plays a major role in their ability to colonize new habitats. Chromatin-based gene regulation is known to be sensitive to temperature. Ambient temperature leads to changes in the activation of genes regulated in this manner. One such regulatory system is the Polycomb group (PcG) whose target genes are more expressed at lower temperatures than at higher ones. Therefore, a greater range in ambient temperature in temperate environments may lead to greater variability (plasticity) in the expression of these genes. This might have detrimental effects, such that positive selection acts to lower the degree of the expression plasticity. We provide evidence for this process in a genomic region that harbors two PcG-regulated genes, polyhomeotic proximal (ph-p) and CG3835. We found a signature of positive selection in this gene region in European populations of D. melanogaster and investigated the region by means of reporter gene assays. The target of selection is located in the intergenic fragment between the two genes. It overlaps with the promoters of both genes and an experimentally validated Polycomb response element (PRE). This fragment harbors five sequence variants that are highly differentiated between European and African populations. The African alleles confer a temperature-induced plasticity in gene expression, which is typical for PcG-mediated gene regulation, whereas thermosensitivity is reduced for the European alleles. PMID:25855066

Analytical validation of a psychiatric pharmacogenomic test.

PubMed

Jablonski, Michael R; King, Nina; Wang, Yongbao; Winner, Joel G; Watterson, Lucas R; Gunselman, Sandra; Dechairo, Bryan M

2018-05-01

The aim of this study was to validate the analytical performance of a combinatorial pharmacogenomics test designed to aid in the appropriate medication selection for neuropsychiatric conditions. Genomic DNA was isolated from buccal swabs. Twelve genes (65 variants/alleles) associated with psychotropic medication metabolism, side effects, and mechanisms of actions were evaluated by bead array, MALDI-TOF mass spectrometry, and/or capillary electrophoresis methods (GeneSight Psychotropic, Assurex Health, Inc.). The combinatorial pharmacogenomics test has a dynamic range of 2.5-20 ng/μl of input genomic DNA, with comparable performance for all assays included in the test. Both the precision and accuracy of the test were >99.9%, with individual gene components between 99.4 and 100%. This study demonstrates that the combinatorial pharmacogenomics test is robust and reproducible, making it suitable for clinical use.

Gene set analysis of purine and pyrimidine antimetabolites cancer therapies.

PubMed

Fridley, Brooke L; Batzler, Anthony; Li, Liang; Li, Fang; Matimba, Alice; Jenkins, Gregory D; Ji, Yuan; Wang, Liewei; Weinshilboum, Richard M

2011-11-01

Responses to therapies, either with regard to toxicities or efficacy, are expected to involve complex relationships of gene products within the same molecular pathway or functional gene set. Therefore, pathways or gene sets, as opposed to single genes, may better reflect the true underlying biology and may be more appropriate units for analysis of pharmacogenomic studies. Application of such methods to pharmacogenomic studies may enable the detection of more subtle effects of multiple genes in the same pathway that may be missed by assessing each gene individually. A gene set analysis of 3821 gene sets is presented assessing the association between basal messenger RNA expression and drug cytotoxicity using ethnically defined human lymphoblastoid cell lines for two classes of drugs: pyrimidines [gemcitabine (dFdC) and arabinoside] and purines [6-thioguanine and 6-mercaptopurine]. The gene set nucleoside-diphosphatase activity was found to be significantly associated with both dFdC and arabinoside, whereas gene set γ-aminobutyric acid catabolic process was associated with dFdC and 6-thioguanine. These gene sets were significantly associated with the phenotype even after adjusting for multiple testing. In addition, five associated gene sets were found in common between the pyrimidines and two gene sets for the purines (3',5'-cyclic-AMP phosphodiesterase activity and γ-aminobutyric acid catabolic process) with a P value of less than 0.0001. Functional validation was attempted with four genes each in gene sets for thiopurine and pyrimidine antimetabolites. All four genes selected from the pyrimidine gene sets (PSME3, CANT1, ENTPD6, ADRM1) were validated, but only one (PDE4D) was validated for the thiopurine gene sets. In summary, results from the gene set analysis of pyrimidine and purine therapies, used often in the treatment of various cancers, provide novel insight into the relationship between genomic variation and drug response.

Selection and validation of suitable reference genes for miRNA expression normalization by quantitative RT-PCR in citrus somatic embryogenic and adult tissues.

PubMed

Kou, Shu-Jun; Wu, Xiao-Meng; Liu, Zheng; Liu, Yuan-Long; Xu, Qiang; Guo, Wen-Wu

2012-12-01

miRNAs have recently been reported to modulate somatic embryogenesis (SE), a key pathway of plant regeneration in vitro. For expression level detection and subsequent function dissection of miRNAs in certain biological processes, qRT-PCR is one of the most effective and sensitive techniques, for which suitable reference gene selection is a prerequisite. In this study, three miRNAs and eight non-coding RNAs (ncRNA) were selected as reference candidates, and their expression stability was inspected in developing citrus SE tissues cultured at 20, 25, and 30 °C. Stability of the eight non-miRNA ncRNAs was further validated in five adult tissues without temperature treatment. The best single reference gene for SE tissues was snoR14 or snoRD25, while for the adult tissues the best one was U4; although they were not as stable as the optimal multiple references snoR14 + U6 for SE tissues and snoR14 + U5 for adult tissues. For expression normalization of less abundant miRNAs in SE tissues, miR3954 was assessed as a viable reference. Single reference gene snoR14 outperformed multiple references for the overall SE and adult tissues. As one of the pioneer systematic studies on reference gene identification for plant miRNA normalization, this study benefits future exploration on miRNA function in citrus and provides valuable information for similar studies in other higher plants. Three miRNAs and eight non-coding RNAs were tested as reference candidates on developing citrus SE tissues. Best single references snoR14 or snoRD25 and optimal multiple references snoR14 + U6, snoR14 + U5 were identified.

Antibiotic Combinations That Enable One-Step, Targeted Mutagenesis of Chromosomal Genes.

PubMed

Lee, Wonsik; Do, Truc; Zhang, Ge; Kahne, Daniel; Meredith, Timothy C; Walker, Suzanne

2018-06-08

Targeted modification of bacterial chromosomes is necessary to understand new drug targets, investigate virulence factors, elucidate cell physiology, and validate results of -omics-based approaches. For some bacteria, reverse genetics remains a major bottleneck to progress in research. Here, we describe a compound-centric strategy that combines new negative selection markers with known positive selection markers to achieve simple, efficient one-step genome engineering of bacterial chromosomes. The method was inspired by the observation that certain nonessential metabolic pathways contain essential late steps, suggesting that antibiotics targeting a late step can be used to select for the absence of genes that control flux into the pathway. Guided by this hypothesis, we have identified antibiotic/counterselectable markers to accelerate reverse engineering of two increasingly antibiotic-resistant pathogens, Staphylococcus aureus and Acinetobacter baumannii. For S. aureus, we used wall teichoic acid biosynthesis inhibitors to select for the absence of tarO and for A. baumannii, we used colistin to select for the absence of lpxC. We have obtained desired gene deletions, gene fusions, and promoter swaps in a single plating step with perfect efficiency. Our method can also be adapted to generate markerless deletions of genes using FLP recombinase. The tools described here will accelerate research on two important pathogens, and the concept we outline can be readily adapted to any organism for which a suitable target pathway can be identified.

Reference genes for quantitative real-time PCR analysis in symbiont Entomomyces delphacidicola of Nilaparvata lugens (Stål)

PubMed Central

Wan, Pin-Jun; Tang, Yao-Hua; Yuan, San-Yue; He, Jia-Chun; Wang, Wei-Xia; Lai, Feng-Xiang; Fu, Qiang

2017-01-01

Nilaparvata lugens (Stål) (Hemiptera: Delphacidae) is a major rice pest that harbors an endosymbiont ascomycete fungus, Entomomyces delphacidicola str. NLU (also known as yeast-like symbiont, YLS). Driving by demand of novel population management tactics (e.g. RNAi), the importance of YLS has been studied and revealed, which greatly boosts the interest of molecular level studies related to YLS. The current study focuses on reference genes for RT-qPCR studies related to YLS. Eight previously unreported YLS genes were cloned, and their expressions were evaluated for N. lugens samples of different developmental stages and sexes, and under different nutritional conditions and temperatures. Expression stabilities were analyzed by BestKeeper, geNorm, NormFinder, ΔCt method and RefFinder. Furthermore, the selected reference genes for RT-qPCR of YLS genes were validated using targeted YLS genes that respond to different nutritional conditions (amino acid deprivation) and RNAi. The results suggest that ylsRPS15p/ylsACT are the most suitable reference genes for temporal gene expression profiling, while ylsTUB/ylsACT and ylsRPS15e/ylsGADPH are the most suitable reference gene choices for evaluating nutrition and temperature effects. Validation studies demonstrated the advantage of using endogenous YLS reference genes for YLS studies. PMID:28198810

Identification of in vivo regulators of the Vibrio cholerae xds gene using a high-throughput genetic selection

PubMed Central

McDonough, EmilyKate; Lazinski, David W.; Camilli, Andrew

2014-01-01

Summary Vibrio cholerae, the causative agent of cholera, remains a threat to public health in areas with inadequate sanitation. As a waterborne pathogen, V. cholerae moves between two dissimilar environments, aquatic reservoirs and the intestinal tract of humans. Accordingly, this pathogen undergoes adaptive shifts in gene expression throughout the different stages of its lifecycle. One particular gene, xds, encodes a secreted exonuclease that was previously identified as being induced during infection. Here we sought to identify regulators responsible for the in vivo-specific induction of xds. A transcriptional fusion of xds to two consecutive antibiotic resistance genes was used to select transposon mutants that had inserted within or adjacent to regulatory genes and thereby caused increased expression of the xds fusion under non-inducing conditions. Large pools of selected insertion sites were sequenced in a high throughput manner using Tn-seq to identify potential mechanisms of xds regulation. Our selection identified the two-component system PhoB/R as the dominant activator of xds expression. In vitro validation confirmed that PhoB, a protein which is only active during phosphate limitation, was responsible for xds activation. Using xds expression as a biosensor of the extracellular phosphate level, we observed that the mouse small intestine is a phosphate-limited environment. PMID:24673931

Characterization of circulating microRNA expression in patients with a ventricular septal defect.

PubMed

Li, Dong; Ji, Long; Liu, Lianbo; Liu, Yizhi; Hou, Haifeng; Yu, Kunkun; Sun, Qiang; Zhao, Zhongtang

2014-01-01

Ventricular septal defect (VSD), one of the most common types of congenital heart disease (CHD), results from a combination of environmental and genetic factors. Recent studies demonstrated that microRNAs (miRNAs) are involved in development of CHD. This study was to characterize the expression of miRNAs that might be involved in the development or reflect the consequences of VSD. MiRNA microarray analysis and reverse transcription-polymerase chain reaction (RT-PCR) were employed to determine the miRNA expression profile from 3 patients with VSD and 3 VSD-free controls. 3 target gene databases were employed to predict the target genes of differentially expressed miRNAs. miRNAs that were generally consensus across the three databases were selected and then independently validated using real time PCR in plasma samples from 20 VSD patients and 15 VSD-free controls. Target genes of validated 8 miRNAs were predicted using bioinformatic methods. 36 differentially expressed miRNAs were found in the patients with VSD and the VSD-free controls. Compared with VSD-free controls, expression of 15 miRNAs were up-regulated and 21 miRNAs were downregulated in the VSD group. 15 miRNAs were selected based on database analysis results and expression levels of 8 miRNAs were validated. The results of the real time PCR were consistent with those of the microarray analysis. Gene ontology analysis indicated that the top target genes were mainly related to cardiac right ventricle morphogenesis. NOTCH1, HAND1, ZFPM2, and GATA3 were predicted as targets of hsa-let-7e-5p, hsa-miR-222-3p and hsa-miR-433. We report for the first time the circulating miRNA profile for patients with VSD and showed that 7 miRNAs were downregulated and 1 upregulated when matched to VSD-free controls. Analysis revealed target genes involved in cardiac development were probably regulated by these miRNAs.

TargetCompare: A web interface to compare simultaneous miRNAs targets

PubMed Central

Moreira, Fabiano Cordeiro; Dustan, Bruno; Hamoy, Igor G; Ribeiro-dos-Santos, André M; dos Santos, Ândrea Ribeiro

2014-01-01

MicroRNAs (miRNAs) are small non-coding nucleotide sequences between 17 and 25 nucleotides in length that primarily function in the regulation of gene expression. A since miRNA has thousand of predict targets in a complex, regulatory cell signaling network. Therefore, it is of interest to study multiple target genes simultaneously. Hence, we describe a web tool (developed using Java programming language and MySQL database server) to analyse multiple targets of pre-selected miRNAs. We cross validated the tool in eight most highly expressed miRNAs in the antrum region of stomach. This helped to identify 43 potential genes that are target of at least six of the referred miRNAs. The developed tool aims to reduce the randomness and increase the chance of selecting strong candidate target genes and miRNAs responsible for playing important roles in the studied tissue. Availability http://lghm.ufpa.br/targetcompare PMID:25352731

TargetCompare: A web interface to compare simultaneous miRNAs targets.

PubMed

Moreira, Fabiano Cordeiro; Dustan, Bruno; Hamoy, Igor G; Ribeiro-Dos-Santos, André M; Dos Santos, Andrea Ribeiro

2014-01-01

MicroRNAs (miRNAs) are small non-coding nucleotide sequences between 17 and 25 nucleotides in length that primarily function in the regulation of gene expression. A since miRNA has thousand of predict targets in a complex, regulatory cell signaling network. Therefore, it is of interest to study multiple target genes simultaneously. Hence, we describe a web tool (developed using Java programming language and MySQL database server) to analyse multiple targets of pre-selected miRNAs. We cross validated the tool in eight most highly expressed miRNAs in the antrum region of stomach. This helped to identify 43 potential genes that are target of at least six of the referred miRNAs. The developed tool aims to reduce the randomness and increase the chance of selecting strong candidate target genes and miRNAs responsible for playing important roles in the studied tissue. http://lghm.ufpa.br/targetcompare.

Selecting and validating reference genes for quantitative real-time PCR in Plutella xylostella (L.).

PubMed

You, Yanchun; Xie, Miao; Vasseur, Liette; You, Minsheng

2018-05-01

Gene expression analysis provides important clues regarding gene functions, and quantitative real-time PCR (qRT-PCR) is a widely used method in gene expression studies. Reference genes are essential for normalizing and accurately assessing gene expression. In the present study, 16 candidate reference genes (ACTB, CyPA, EF1-α, GAPDH, HSP90, NDPk, RPL13a, RPL18, RPL19, RPL32, RPL4, RPL8, RPS13, RPS4, α-TUB, and β-TUB) from Plutella xylostella were selected to evaluate gene expression stability across different experimental conditions using five statistical algorithms (geNorm, NormFinder, Delta Ct, BestKeeper, and RefFinder). The results suggest that different reference genes or combinations of reference genes are suitable for normalization in gene expression studies of P. xylostella according to the different developmental stages, strains, tissues, and insecticide treatments. Based on the given experimental sets, the most stable reference genes were RPS4 across different developmental stages, RPL8 across different strains and tissues, and EF1-α across different insecticide treatments. A comprehensive and systematic assessment of potential reference genes for gene expression normalization is essential for post-genomic functional research in P. xylostella, a notorious pest with worldwide distribution and a high capacity to adapt and develop resistance to insecticides.

Tabu search and binary particle swarm optimization for feature selection using microarray data.

PubMed

Chuang, Li-Yeh; Yang, Cheng-Huei; Yang, Cheng-Hong

2009-12-01

Gene expression profiles have great potential as a medical diagnosis tool because they represent the state of a cell at the molecular level. In the classification of cancer type research, available training datasets generally have a fairly small sample size compared to the number of genes involved. This fact poses an unprecedented challenge to some classification methodologies due to training data limitations. Therefore, a good selection method for genes relevant for sample classification is needed to improve the predictive accuracy, and to avoid incomprehensibility due to the large number of genes investigated. In this article, we propose to combine tabu search (TS) and binary particle swarm optimization (BPSO) for feature selection. BPSO acts as a local optimizer each time the TS has been run for a single generation. The K-nearest neighbor method with leave-one-out cross-validation and support vector machine with one-versus-rest serve as evaluators of the TS and BPSO. The proposed method is applied and compared to the 11 classification problems taken from the literature. Experimental results show that our method simplifies features effectively and either obtains higher classification accuracy or uses fewer features compared to other feature selection methods.

Identification of Suitable Reference Genes for Gene Expression Normalization in qRT-PCR Analysis in Watermelon

PubMed Central

Gao, Lingyun; Zhao, Shuang; Jiang, Wei; Huang, Yuan; Bie, Zhilong

2014-01-01

Watermelon is one of the major Cucurbitaceae crops and the recent availability of genome sequence greatly facilitates the fundamental researches on it. Quantitative real-time reverse transcriptase PCR (qRT–PCR) is the preferred method for gene expression analyses, and using validated reference genes for normalization is crucial to ensure the accuracy of this method. However, a systematic validation of reference genes has not been conducted on watermelon. In this study, transcripts of 15 candidate reference genes were quantified in watermelon using qRT–PCR, and the stability of these genes was compared using geNorm and NormFinder. geNorm identified ClTUA and ClACT, ClEF1α and ClACT, and ClCAC and ClTUA as the best pairs of reference genes in watermelon organs and tissues under normal growth conditions, abiotic stress, and biotic stress, respectively. NormFinder identified ClYLS8, ClUBCP, and ClCAC as the best single reference genes under the above experimental conditions, respectively. ClYLS8 and ClPP2A were identified as the best reference genes across all samples. Two to nine reference genes were required for more reliable normalization depending on the experimental conditions. The widely used watermelon reference gene 18SrRNA was less stable than the other reference genes under the experimental conditions. Catalase family genes were identified in watermelon genome, and used to validate the reliability of the identified reference genes. ClCAT1and ClCAT2 were induced and upregulated in the first 24 h, whereas ClCAT3 was downregulated in the leaves under low temperature stress. However, the expression levels of these genes were significantly overestimated and misinterpreted when 18SrRNA was used as a reference gene. These results provide a good starting point for reference gene selection in qRT–PCR analyses involving watermelon. PMID:24587403

Identification of suitable reference genes for gene expression normalization in qRT-PCR analysis in watermelon.

PubMed

Kong, Qiusheng; Yuan, Jingxian; Gao, Lingyun; Zhao, Shuang; Jiang, Wei; Huang, Yuan; Bie, Zhilong

2014-01-01

Watermelon is one of the major Cucurbitaceae crops and the recent availability of genome sequence greatly facilitates the fundamental researches on it. Quantitative real-time reverse transcriptase PCR (qRT-PCR) is the preferred method for gene expression analyses, and using validated reference genes for normalization is crucial to ensure the accuracy of this method. However, a systematic validation of reference genes has not been conducted on watermelon. In this study, transcripts of 15 candidate reference genes were quantified in watermelon using qRT-PCR, and the stability of these genes was compared using geNorm and NormFinder. geNorm identified ClTUA and ClACT, ClEF1α and ClACT, and ClCAC and ClTUA as the best pairs of reference genes in watermelon organs and tissues under normal growth conditions, abiotic stress, and biotic stress, respectively. NormFinder identified ClYLS8, ClUBCP, and ClCAC as the best single reference genes under the above experimental conditions, respectively. ClYLS8 and ClPP2A were identified as the best reference genes across all samples. Two to nine reference genes were required for more reliable normalization depending on the experimental conditions. The widely used watermelon reference gene 18SrRNA was less stable than the other reference genes under the experimental conditions. Catalase family genes were identified in watermelon genome, and used to validate the reliability of the identified reference genes. ClCAT1and ClCAT2 were induced and upregulated in the first 24 h, whereas ClCAT3 was downregulated in the leaves under low temperature stress. However, the expression levels of these genes were significantly overestimated and misinterpreted when 18SrRNA was used as a reference gene. These results provide a good starting point for reference gene selection in qRT-PCR analyses involving watermelon.

The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data.

PubMed

Mansourian, Robert; Mutch, David M; Antille, Nicolas; Aubert, Jerome; Fogel, Paul; Le Goff, Jean-Marc; Moulin, Julie; Petrov, Anton; Rytz, Andreas; Voegel, Johannes J; Roberts, Matthew-Alan

2004-11-01

Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. The GEA code for R software is freely available upon request to authors.

Identification of Alternative Splicing and Fusion Transcripts in Non-Small Cell Lung Cancer by RNA Sequencing.

PubMed

Hong, Yoonki; Kim, Woo Jin; Bang, Chi Young; Lee, Jae Cheol; Oh, Yeon-Mok

2016-04-01

Lung cancer is the most common cause of cancer related death. Alterations in gene sequence, structure, and expression have an important role in the pathogenesis of lung cancer. Fusion genes and alternative splicing of cancer-related genes have the potential to be oncogenic. In the current study, we performed RNA-sequencing (RNA-seq) to investigate potential fusion genes and alternative splicing in non-small cell lung cancer. RNA was isolated from lung tissues obtained from 86 subjects with lung cancer. The RNA samples from lung cancer and normal tissues were processed with RNA-seq using the HiSeq 2000 system. Fusion genes were evaluated using Defuse and ChimeraScan. Candidate fusion transcripts were validated by Sanger sequencing. Alternative splicing was analyzed using multivariate analysis of transcript sequencing and validated using quantitative real time polymerase chain reaction. RNA-seq data identified oncogenic fusion genes EML4-ALK and SLC34A2-ROS1 in three of 86 normal-cancer paired samples. Nine distinct fusion transcripts were selected using DeFuse and ChimeraScan; of which, four fusion transcripts were validated by Sanger sequencing. In 33 squamous cell carcinoma, 29 tumor specific skipped exon events and six mutually exclusive exon events were identified. ITGB4 and PYCR1 were top genes that showed significant tumor specific splice variants. In conclusion, RNA-seq data identified novel potential fusion transcripts and splice variants. Further evaluation of their functional significance in the pathogenesis of lung cancer is required.

Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma.

PubMed

Chen, Ming-Huang; Yang, Wu-Lung R; Lin, Kuan-Ting; Liu, Chia-Hung; Liu, Yu-Wen; Huang, Kai-Wen; Chang, Peter Mu-Hsin; Lai, Jin-Mei; Hsu, Chun-Nan; Chao, Kun-Mao; Kao, Cheng-Yan; Huang, Chi-Ying F

2011-01-01

Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis. Currently, only sorafenib is approved by the FDA for advanced HCC treatment; therefore, there is an urgent need to discover candidate therapeutic drugs for HCC. We hypothesized that if a drug signature could reverse, at least in part, the gene expression signature of HCC, it might have the potential to inhibit HCC-related pathways and thereby treat HCC. To test this hypothesis, we first built an integrative platform, the "Encyclopedia of Hepatocellular Carcinoma genes Online 2", dubbed EHCO2, to systematically collect, organize and compare the publicly available data from HCC studies. The resulting collection includes a total of 4,020 genes. To systematically query the Connectivity Map (CMap), which includes 6,100 drug-mediated expression profiles, we further designed various gene signature selection and enrichment methods, including a randomization technique, majority vote, and clique analysis. Subsequently, 28 out of 50 prioritized drugs, including tanespimycin, trichostatin A, thioguanosine, and several anti-psychotic drugs with anti-tumor activities, were validated via MTT cell viability assays and clonogenic assays in HCC cell lines. To accelerate their future clinical use, possibly through drug-repurposing, we selected two well-established drugs to test in mice, chlorpromazine and trifluoperazine. Both drugs inhibited orthotopic liver tumor growth. In conclusion, we successfully discovered and validated existing drugs for potential HCC therapeutic use with the pipeline of Connectivity Map analysis and lab verification, thereby suggesting the usefulness of this procedure to accelerate drug repurposing for HCC treatment.

rpb2 is a reliable reference gene for quantitative gene expression analysis in the dermatophyte Trichophyton rubrum.

PubMed

Jacob, Tiago R; Peres, Nalu T A; Persinoti, Gabriela F; Silva, Larissa G; Mazucato, Mendelson; Rossi, Antonio; Martinez-Rossi, Nilce M

2012-05-01

The selection of reference genes used for data normalization to quantify gene expression by real-time PCR amplifications (qRT-PCR) is crucial for the accuracy of this technique. In spite of this, little information regarding such genes for qRT-PCR is available for gene expression analyses in pathogenic fungi. Thus, we investigated the suitability of eight candidate reference genes in isolates of the human dermatophyte Trichophyton rubrum subjected to several environmental challenges, such as drug exposure, interaction with human nail and skin, and heat stress. The stability of these genes was determined by geNorm, NormFinder and Best-Keeper programs. The gene with the most stable expression in the majority of the conditions tested was rpb2 (DNA-dependent RNA polymerase II), which was validated in three T. rubrum strains. Moreover, the combination of rpb2 and chs1 (chitin synthase) genes provided for the most reliable qRT-PCR data normalization in T. rubrum under a broad range of biological conditions. To the best of our knowledge this is the first report on the selection of reference genes for qRT-PCR data normalization in dermatophytes and the results of these studies should permit further analysis of gene expression under several experimental conditions, with improved accuracy and reliability.

Reference Genes for Accurate Transcript Normalization in Citrus Genotypes under Different Experimental Conditions

PubMed Central

Mafra, Valéria; Kubo, Karen S.; Alves-Ferreira, Marcio; Ribeiro-Alves, Marcelo; Stuart, Rodrigo M.; Boava, Leonardo P.; Rodrigues, Carolina M.; Machado, Marcos A.

2012-01-01

Real-time reverse transcription PCR (RT-qPCR) has emerged as an accurate and widely used technique for expression profiling of selected genes. However, obtaining reliable measurements depends on the selection of appropriate reference genes for gene expression normalization. The aim of this work was to assess the expression stability of 15 candidate genes to determine which set of reference genes is best suited for transcript normalization in citrus in different tissues and organs and leaves challenged with five pathogens (Alternaria alternata, Phytophthora parasitica, Xylella fastidiosa and Candidatus Liberibacter asiaticus). We tested traditional genes used for transcript normalization in citrus and orthologs of Arabidopsis thaliana genes described as superior reference genes based on transcriptome data. geNorm and NormFinder algorithms were used to find the best reference genes to normalize all samples and conditions tested. Additionally, each biotic stress was individually analyzed by geNorm. In general, FBOX (encoding a member of the F-box family) and GAPC2 (GAPDH) was the most stable candidate gene set assessed under the different conditions and subsets tested, while CYP (cyclophilin), TUB (tubulin) and CtP (cathepsin) were the least stably expressed genes found. Validation of the best suitable reference genes for normalizing the expression level of the WRKY70 transcription factor in leaves infected with Candidatus Liberibacter asiaticus showed that arbitrary use of reference genes without previous testing could lead to misinterpretation of data. Our results revealed FBOX, SAND (a SAND family protein), GAPC2 and UPL7 (ubiquitin protein ligase 7) to be superior reference genes, and we recommend their use in studies of gene expression in citrus species and relatives. This work constitutes the first systematic analysis for the selection of superior reference genes for transcript normalization in different citrus organs and under biotic stress. PMID:22347455

Gene Expression Differences in Peripheral Blood of Parkinson’s Disease Patients with Distinct Progression Profiles

PubMed Central

Soreq, Lilach; Lobo, Patrícia P.; Mestre, Tiago; Coelho, Miguel; Rosa, Mário M.; Gonçalves, Nilza; Wales, Pauline; Mendes, Tiago; Gerhardt, Ellen; Fahlbusch, Christiane; Bonifati, Vincenzo; Bonin, Michael; Miltenberger-Miltényi, Gabriel; Borovecki, Fran; Soreq, Hermona; Ferreira, Joaquim J.; F. Outeiro, Tiago

2016-01-01

The prognosis of neurodegenerative disorders is clinically challenging due to the inexistence of established biomarkers for predicting disease progression. Here, we performed an exploratory cross-sectional, case-control study aimed at determining whether gene expression differences in peripheral blood may be used as a signature of Parkinson’s disease (PD) progression, thereby shedding light into potential molecular mechanisms underlying disease development. We compared transcriptional profiles in the blood from 34 PD patients who developed postural instability within ten years with those of 33 patients who did not develop postural instability within this time frame. Our study identified >200 differentially expressed genes between the two groups. The expression of several of the genes identified was previously found deregulated in animal models of PD and in PD patients. Relevant genes were selected for validation by real-time PCR in a subset of patients. The genes validated were linked to nucleic acid metabolism, mitochondria, immune response and intracellular-transport. Interestingly, we also found deregulation of these genes in a dopaminergic cell model of PD, a simple paradigm that can now be used to further dissect the role of these molecular players on dopaminergic cell loss. Altogether, our study provides preliminary evidence that expression changes in specific groups of genes and pathways, detected in peripheral blood samples, may be correlated with differential PD progression. Our exploratory study suggests that peripheral gene expression profiling may prove valuable for assisting in prediction of PD prognosis, and identifies novel culprits possibly involved in dopaminergic cell death. Given the exploratory nature of our study, further investigations using independent, well-characterized cohorts will be essential in order to validate our candidates as predictors of PD prognosis and to definitively confirm the value of gene expression analysis in aiding patient stratification and therapeutic intervention. PMID:27322389

Validating internal controls for quantitative plant gene expression studies.

PubMed

Brunner, Amy M; Yakovlev, Igor A; Strauss, Steven H

2004-08-18

Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed. Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied. Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments.

Systematic identification and validation of candidate genes for detection of circulating tumor cells in peripheral blood specimens of colorectal cancer patients.

PubMed

Findeisen, Peter; Röckel, Matthias; Nees, Matthias; Röder, Christian; Kienle, Peter; Von Knebel Doeberitz, Magnus; Kalthoff, Holger; Neumaier, Michael

2008-11-01

The presence of tumor cells in peripheral blood is being regarded increasingly as a clinically relevant prognostic factor for colorectal cancer patients. Current molecular methods are very sensitive but due to low specificity their diagnostic value is limited. This study was undertaken in order to systematically identify and validate new colorectal cancer (CRC) marker genes for improved detection of minimal residual disease in peripheral blood mononuclear cells of colorectal cancer patients. Marker genes with upregulated gene expression in colorectal cancer tissue and cell lines were identified using microarray experiments and publicly available gene expression data. A systematic iterative approach was used to reduce a set of 346 candidate genes, reportedly associated with CRC to a selection of candidate genes that were then further validated by relative quantitative real-time RT-PCR. Analytical sensitivity of RT-PCR assays was determined by spiking experiments with CRC cells. Diagnostic sensitivity as well as specificity was tested on a control group consisting of 18 CRC patients compared to 12 individuals without malignant disease. From a total of 346-screened genes only serine (or cysteine) proteinase inhibitor, clade B (ovalbumin), member 5 (SERPINB5) showed significantly elevated transcript levels in peripheral venous blood specimens of tumor patients when compared to the nonmalignant control group. These results were confirmed by analysis of an enlarged collective consisting of 63 CRC patients and 36 control individuals without malignant disease. In conclusion SERPINB5 seems to be a promising marker for detection of circulating tumor cells in peripheral blood of colorectal cancer patients.

Transcriptome-wide single nucleotide polymorphisms (SNPs) for abalone (Haliotis midae): validation and application using GoldenGate medium-throughput genotyping assays.

PubMed

Bester-Van Der Merwe, Aletta; Blaauw, Sonja; Du Plessis, Jana; Roodt-Wilding, Rouvay

2013-09-23

Haliotis midae is one of the most valuable commercial abalone species in the world, but is highly vulnerable, due to exploitation, habitat destruction and predation. In order to preserve wild and cultured stocks, genetic management and improvement of the species has become crucial. Fundamental to this is the availability and employment of molecular markers, such as microsatellites and single nucleotide (SNPs). Transcriptome sequences generated through sequencing-by-synthesis technology were utilized for the in vitro and in silico identification of 505 putative SNPs from a total of 316 selected contigs. A subset of 234 SNPs were further validated and characterized in wild and cultured abalone using two Illumina GoldenGate genotyping assays. Combined with VeraCode technology, this genotyping platform yielded a 65%-69% conversion rate (percentage polymorphic markers) with a global genotyping success rate of 76%-85% and provided a viable means for validating SNP markers in a non-model species. The utility of 31 of the validated SNPs in population structure analysis was confirmed, while a large number of SNPs (174) were shown to be informative and are, thus, good candidates for linkage map construction. The non-synonymous SNPs (50) located in coding regions of genes that showed similarities with known proteins will also be useful for genetic applications, such as the marker-assisted selection of genes of relevance to abalone aquaculture.

Development and Validation of a qRT-PCR Classifier for Lung Cancer Prognosis

PubMed Central

Chen, Guoan; Kim, Sinae; Taylor, Jeremy MG; Wang, Zhuwen; Lee, Oliver; Ramnath, Nithya; Reddy, Rishindra M; Lin, Jules; Chang, Andrew C; Orringer, Mark B; Beer, David G

2011-01-01

Purpose This prospective study aimed to develop a robust and clinically-applicable method to identify high-risk early stage lung cancer patients and then to validate this method for use in future translational studies. Patients and Methods Three published Affymetrix microarray data sets representing 680 primary tumors were used in the survival-related gene selection procedure using clustering, Cox model and random survival forest (RSF) analysis. A final set of 91 genes was selected and tested as a predictor of survival using a qRT-PCR-based assay utilizing an independent cohort of 101 lung adenocarcinomas. Results The RSF model built from 91 genes in the training set predicted patient survival in an independent cohort of 101 lung adenocarcinomas, with a prediction error rate of 26.6%. The mortality risk index (MRI) was significantly related to survival (Cox model p < 0.00001) and separated all patients into low, medium, and high-risk groups (HR = 1.00, 2.82, 4.42). The MRI was also related to survival in stage 1 patients (Cox model p = 0.001), separating patients into low, medium, and high-risk groups (HR = 1.00, 3.29, 3.77). Conclusions The development and validation of this robust qRT-PCR platform allows prediction of patient survival with early stage lung cancer. Utilization will now allow investigators to evaluate it prospectively by incorporation into new clinical trials with the goal of personalized treatment of lung cancer patients and improving patient survival. PMID:21792073

Evaluation of Reference Genes for Quantitative Real-Time PCR in Oil Palm Elite Planting Materials Propagated by Tissue Culture

PubMed Central

Chan, Pek-Lan; Rose, Ray J.; Abdul Murad, Abdul Munir; Zainal, Zamri; Leslie Low, Eng-Ti; Ooi, Leslie Cheng-Li; Ooi, Siew-Eng; Yahya, Suzaini; Singh, Rajinder

2014-01-01

Background The somatic embryogenesis tissue culture process has been utilized to propagate high yielding oil palm. Due to the low callogenesis and embryogenesis rates, molecular studies were initiated to identify genes regulating the process, and their expression levels are usually quantified using reverse transcription quantitative real-time PCR (RT-qPCR). With the recent release of oil palm genome sequences, it is crucial to establish a proper strategy for gene analysis using RT-qPCR. Selection of the most suitable reference genes should be performed for accurate quantification of gene expression levels. Results In this study, eight candidate reference genes selected from cDNA microarray study and literature review were evaluated comprehensively across 26 tissue culture samples using RT-qPCR. These samples were collected from two tissue culture lines and media treatments, which consisted of leaf explants cultures, callus and embryoids from consecutive developmental stages. Three statistical algorithms (geNorm, NormFinder and BestKeeper) confirmed that the expression stability of novel reference genes (pOP-EA01332, PD00380 and PD00569) outperformed classical housekeeping genes (GAPDH, NAD5, TUBULIN, UBIQUITIN and ACTIN). PD00380 and PD00569 were identified as the most stably expressed genes in total samples, MA2 and MA8 tissue culture lines. Their applicability to validate the expression profiles of a putative ethylene-responsive transcription factor 3-like gene demonstrated the importance of using the geometric mean of two genes for normalization. Conclusions Systematic selection of the most stably expressed reference genes for RT-qPCR was established in oil palm tissue culture samples. PD00380 and PD00569 were selected for accurate and reliable normalization of gene expression data from RT-qPCR. These data will be valuable to the research associated with the tissue culture process. Also, the method described here will facilitate the selection of appropriate reference genes in other oil palm tissues and in the expression profiling of genes relating to yield, biotic and abiotic stresses. PMID:24927412

Identification of appropriate reference genes for normalizing transcript expression by quantitative real-time PCR in Litsea cubeba.

PubMed

Lin, Liyuan; Han, Xiaojiao; Chen, Yicun; Wu, Qingke; Wang, Yangdong

2013-12-01

Quantitative real-time PCR has emerged as a highly sensitive and widely used method for detection of gene expression profiles, via which accurate detection depends on reliable normalization. Since no single control is appropriate for all experimental treatments, it is generally advocated to select suitable internal controls prior to use for normalization. This study reported the evaluation of the expression stability of twelve potential reference genes in different tissue/organs and six fruit developmental stages of Litsea cubeba in order to screen the superior internal reference genes for data normalization. Two softwares-geNorm, and NormFinder-were used to identify stability of these candidate genes. The cycle threshold difference and coefficient of variance were also calculated to evaluate the expression stability of candidate genes. F-BOX, EF1α, UBC, and TUA were selected as the most stable reference genes across 11 sample pools. F-BOX, EF1α, and EIF4α exhibited the highest expression stability in different tissue/organs and different fruit developmental stages. Besides, a combination of two stable reference genes would be sufficient for gene expression normalization in different fruit developmental stages. In addition, the relative expression profiles of DXS and DXR were evaluated by EF1α, UBC, and SAMDC. The results further validated the reliability of stable reference genes and also highlighted the importance of selecting suitable internal controls for L. cubeba. These reference genes will be of great importance for transcript normalization in future gene expression studies on L. cubeba.

Selective AR Modulators that Distinguish Proliferative from Differentiative Gene Promoters

DTIC Science & Technology

2015-08-01

approved drugs, were tested in multiple screens. The two best hits were confirmed in rescreens and validated for differential effects on AR activity in...ulate by different mecha- nisms, with dox more cell type specific than Cpd05. The data also indicate that dox can stimulate sARE- lucifer - ase at...with R1881 (1 nM) and compounds or DMSO.   7   Effect of compounds on endogenous gene expression. To determine whether the differential effects

A Simple Screening Approach To Prioritize Genes for Functional Analysis Identifies a Role for Interferon Regulatory Factor 7 in the Control of Respiratory Syncytial Virus Disease

PubMed Central

McDonald, Jacqueline U.; Kaforou, Myrsini; Clare, Simon; Hale, Christine; Ivanova, Maria; Huntley, Derek; Dorner, Marcus; Wright, Victoria J.; Levin, Michael; Martinon-Torres, Federico; Herberg, Jethro A.

2016-01-01

ABSTRACT Greater understanding of the functions of host gene products in response to infection is required. While many of these genes enable pathogen clearance, some enhance pathogen growth or contribute to disease symptoms. Many studies have profiled transcriptomic and proteomic responses to infection, generating large data sets, but selecting targets for further study is challenging. Here we propose a novel data-mining approach combining multiple heterogeneous data sets to prioritize genes for further study by using respiratory syncytial virus (RSV) infection as a model pathogen with a significant health care impact. The assumption was that the more frequently a gene is detected across multiple studies, the more important its role is. A literature search was performed to find data sets of genes and proteins that change after RSV infection. The data sets were standardized, collated into a single database, and then panned to determine which genes occurred in multiple data sets, generating a candidate gene list. This candidate gene list was validated by using both a clinical cohort and in vitro screening. We identified several genes that were frequently expressed following RSV infection with no assigned function in RSV control, including IFI27, IFIT3, IFI44L, GBP1, OAS3, IFI44, and IRF7. Drilling down into the function of these genes, we demonstrate a role in disease for the gene for interferon regulatory factor 7, which was highly ranked on the list, but not for IRF1, which was not. Thus, we have developed and validated an approach for collating published data sets into a manageable list of candidates, identifying novel targets for future analysis. IMPORTANCE Making the most of “big data” is one of the core challenges of current biology. There is a large array of heterogeneous data sets of host gene responses to infection, but these data sets do not inform us about gene function and require specialized skill sets and training for their utilization. Here we describe an approach that combines and simplifies these data sets, distilling this information into a single list of genes commonly upregulated in response to infection with RSV as a model pathogen. Many of the genes on the list have unknown functions in RSV disease. We validated the gene list with new clinical, in vitro, and in vivo data. This approach allows the rapid selection of genes of interest for further, more-detailed studies, thus reducing time and costs. Furthermore, the approach is simple to use and widely applicable to a range of diseases. PMID:27822537

The Joint Effects of Background Selection and Genetic Recombination on Local Gene Genealogies

PubMed Central

Zeng, Kai; Charlesworth, Brian

2011-01-01

Background selection, the effects of the continual removal of deleterious mutations by natural selection on variability at linked sites, is potentially a major determinant of DNA sequence variability. However, the joint effects of background selection and genetic recombination on the shape of the neutral gene genealogy have proved hard to study analytically. The only existing formula concerns the mean coalescent time for a pair of alleles, making it difficult to assess the importance of background selection from genome-wide data on sequence polymorphism. Here we develop a structured coalescent model of background selection with recombination and implement it in a computer program that efficiently generates neutral gene genealogies for an arbitrary sample size. We check the validity of the structured coalescent model against forward-in-time simulations and show that it accurately captures the effects of background selection. The model produces more accurate predictions of the mean coalescent time than the existing formula and supports the conclusion that the effect of background selection is greater in the interior of a deleterious region than at its boundaries. The level of linkage disequilibrium between sites is elevated by background selection, to an extent that is well summarized by a change in effective population size. The structured coalescent model is readily extendable to more realistic situations and should prove useful for analyzing genome-wide polymorphism data. PMID:21705759

The joint effects of background selection and genetic recombination on local gene genealogies.

PubMed

Zeng, Kai; Charlesworth, Brian

2011-09-01

Background selection, the effects of the continual removal of deleterious mutations by natural selection on variability at linked sites, is potentially a major determinant of DNA sequence variability. However, the joint effects of background selection and genetic recombination on the shape of the neutral gene genealogy have proved hard to study analytically. The only existing formula concerns the mean coalescent time for a pair of alleles, making it difficult to assess the importance of background selection from genome-wide data on sequence polymorphism. Here we develop a structured coalescent model of background selection with recombination and implement it in a computer program that efficiently generates neutral gene genealogies for an arbitrary sample size. We check the validity of the structured coalescent model against forward-in-time simulations and show that it accurately captures the effects of background selection. The model produces more accurate predictions of the mean coalescent time than the existing formula and supports the conclusion that the effect of background selection is greater in the interior of a deleterious region than at its boundaries. The level of linkage disequilibrium between sites is elevated by background selection, to an extent that is well summarized by a change in effective population size. The structured coalescent model is readily extendable to more realistic situations and should prove useful for analyzing genome-wide polymorphism data.

Transcriptional Profiling of Breast Cancer Metastases Identifies Liver Metastasis-Selective Genes Associated with Adverse Outcome in Luminal A Primary Breast Cancer.

PubMed

Kimbung, Siker; Johansson, Ida; Danielsson, Anna; Veerla, Srinivas; Egyhazi Brage, Suzanne; Frostvik Stolt, Marianne; Skoog, Lambert; Carlsson, Lena; Einbeigi, Zakaria; Lidbrink, Elisabet; Linderholm, Barbro; Loman, Niklas; Malmström, Per-Olof; Söderberg, Martin; Walz, Thomas M; Fernö, Mårten; Hatschek, Thomas; Hedenfalk, Ingrid

2016-01-01

The complete molecular basis of the organ-specificity of metastasis is elusive. This study aimed to provide an independent characterization of the transcriptional landscape of breast cancer metastases with the specific objective to identify liver metastasis-selective genes of prognostic importance following primary tumor diagnosis. A cohort of 304 women with advanced breast cancer was studied. Associations between the site of recurrence and clinicopathologic features were investigated. Fine-needle aspirates of metastases (n = 91) were subjected to whole-genome transcriptional profiling. Liver metastasis-selective genes were identified by significance analysis of microarray (SAM) analyses and independently validated in external datasets. Finally, the prognostic relevance of the liver metastasis-selective genes in primary breast cancer was tested. Liver relapse was associated with estrogen receptor (ER) expression (P = 0.002), luminal B subtype (P = 0.01), and was prognostic for an inferior postrelapse survival (P = 0.01). The major variation in the transcriptional landscape of metastases was also associated with ER expression and molecular subtype. However, liver metastases displayed unique transcriptional fingerprints, characterized by downregulation of extracellular matrix (i.e., stromal) genes. Importantly, we identified a 17-gene liver metastasis-selective signature, which was significantly and independently prognostic for shorter relapse-free (P < 0.001) and overall (P = 0.001) survival in ER-positive tumors. Remarkably, this signature remained independently prognostic for shorter relapse-free survival (P = 0.001) among luminal A tumors. Extracellular matrix (stromal) genes can be used to partition breast cancer by site of relapse and may be used to further refine prognostication in ER positive primary breast cancer. ©2015 American Association for Cancer Research.

Transcriptome Profiling of Human FoxP3+ Regulatory T Cells

PubMed Central

Bhairavabhotla, Ravikiran; Kim, Yong C.; Glass, Deborah D.; Escobar, Thelma M.; Patel, Mira C.; Zahr, Rami; Nguyen, Cuong K.; Kilaru, Gokhul K.; Muljo, Stefan A.; Shevach, Ethan M.

2015-01-01

The major goal of this study was to perform an in depth characterization of the “gene signature” of human FoxP3+ T regulatory cells (Tregs). Highly purified Tregs and T conventional cells (Tconvs) from multiple healthy donors (HD), either freshly explanted or activated in vitro, were analyzed via RNA sequencing (RNA-seq) and gene expression changes validated using the nCounter system. Additionally, we analyzed microRNA (miRNA) expression using TaqMan low-density arrays. Our results confirm previous studies demonstrating selective gene expression of FoxP3, IKZF2, and CTLA4 in Tregs. Notably, a number of yet uncharacterized genes (RTKN2, LAYN, UTS2, CSF2RB, TRIB1, F5, CECAM4, CD70, ENC1 and NKG7) were identified and validated as being differentially expressed in human Tregs. We further characterize the functional roles of RTKN2 and LAYN by analyzing their roles in vitro human Treg suppression assays by knocking them down in Tregs and overexpressing them in Tconvs. In order to facilitate a better understanding of the human Treg gene expression signature, we have generated from our results a hypothetical interactome of genes and miRNAs in Tregs and Tconvs, PMID:26686412

Validation of Reference Genes for Quantitative Expression Analysis by Real-Time RT-PCR in Four Lepidopteran Insects

PubMed Central

Teng, Xiaolu; Zhang, Zan; He, Guiling; Yang, Liwen; Li, Fei

2012-01-01

Quantitative real-time polymerase chain reaction (qPCR) is an efficient and widely used technique to monitor gene expression. Housekeeping genes (HKGs) are often empirically selected as the reference genes for data normalization. However, the suitability of HKGs used as the reference genes has been seldom validated. Here, six HKGs were chosen (actin A3, actin A1, GAPDH, G3PDH, E2F, rp49) in four lepidopteran insects Bombyx mori L. (Lepidoptera: Bombycidae), Plutella xylostella L. (Plutellidae), Chilo suppressalis Walker (Crambidae), and Spodoptera exigua Hübner (Noctuidae) to study their expression stability. The algorithms of geNorm, NormFinder, stability index, and ΔCt analysis were used to evaluate these HKGs. Across different developmental stages, actin A1 was the most stable in P. xylostella and C. suppressalis, but it was the least stable in B. mori and S. exigua. Rp49 and GAPDH were the most stable in B. mori and S. exigua, respectively. In different tissues, GAPDH, E2F, and Rp49 were the most stable in B. mori, S. exigua, and C. suppressalis, respectively. The relative abundances of Siwi genes estimated by 2-ΔΔCt method were tested with different HKGs as the reference gene, proving the importance of internal controls in qPCR data analysis. The results not only presented a list of suitable reference genes in four lepidopteran insects, but also proved that the expression stabilities of HKGs were different among evolutionarily close species. There was no single universal reference gene that could be used in all situations. It is indispensable to validate the expression of HKGs before using them as the internal control in qPCR. PMID:22938136

Validation of reference genes for quantitative expression analysis by real-time rt-PCR in four lepidopteran insects.

PubMed

Teng, Xiaolu; Zhang, Zan; He, Guiling; Yang, Liwen; Li, Fei

2012-01-01

Quantitative real-time polymerase chain reaction (qPCR) is an efficient and widely used technique to monitor gene expression. Housekeeping genes (HKGs) are often empirically selected as the reference genes for data normalization. However, the suitability of HKGs used as the reference genes has been seldom validated. Here, six HKGs were chosen (actin A3, actin A1, GAPDH, G3PDH, E2F, rp49) in four lepidopteran insects Bombyx mori L. (Lepidoptera: Bombycidae), Plutella xylostella L. (Plutellidae), Chilo suppressalis Walker (Crambidae), and Spodoptera exigua Hübner (Noctuidae) to study their expression stability. The algorithms of geNorm, NormFinder, stability index, and ΔCt analysis were used to evaluate these HKGs. Across different developmental stages, actin A1 was the most stable in P. xylostella and C. suppressalis, but it was the least stable in B. mori and S. exigua. Rp49 and GAPDH were the most stable in B. mori and S. exigua, respectively. In different tissues, GAPDH, E2F, and Rp49 were the most stable in B. mori, S. exigua, and C. suppressalis, respectively. The relative abundances of Siwi genes estimated by 2(-ΔΔCt) method were tested with different HKGs as the reference gene, proving the importance of internal controls in qPCR data analysis. The results not only presented a list of suitable reference genes in four lepidopteran insects, but also proved that the expression stabilities of HKGs were different among evolutionarily close species. There was no single universal reference gene that could be used in all situations. It is indispensable to validate the expression of HKGs before using them as the internal control in qPCR.

Twenty-four signature genes predict the prognosis of oral squamous cell carcinoma with high accuracy and repeatability

PubMed Central

Gao, Jianyong; Tian, Gang; Han, Xu; Zhu, Qiang

2018-01-01

Oral squamous cell carcinoma (OSCC) is the sixth most common type cancer worldwide, with poor prognosis. The present study aimed to identify gene signatures that could classify OSCC and predict prognosis in different stages. A training data set (GSE41613) and two validation data sets (GSE42743 and GSE26549) were acquired from the online Gene Expression Omnibus database. In the training data set, patients were classified based on the tumor-node-metastasis staging system, and subsequently grouped into low stage (L) or high stage (H). Signature genes between L and H stages were selected by disparity index analysis, and classification was performed by the expression of these signature genes. The established classification was compared with the L and H classification, and fivefold cross validation was used to evaluate the stability. Enrichment analysis for the signature genes was implemented by the Database for Annotation, Visualization and Integration Discovery. Two validation data sets were used to determine the precise of classification. Survival analysis was conducted followed each classification using the package ‘survival’ in R software. A set of 24 signature genes was identified based on the classification model with the Fi value of 0.47, which was used to distinguish OSCC samples in two different stages. Overall survival of patients in the H stage was higher than those in the L stage. Signature genes were primarily enriched in ‘ether lipid metabolism’ pathway and biological processes such as ‘positive regulation of adaptive immune response’ and ‘apoptotic cell clearance’. The results provided a novel 24-gene set that may be used as biomarkers to predict OSCC prognosis with high accuracy, which may be used to determine an appropriate treatment program for patients with OSCC in addition to the traditional evaluation index. PMID:29257303

Genes under positive selection in a model plant pathogenic fungus, Botrytis.

PubMed

Aguileta, Gabriela; Lengelle, Juliette; Chiapello, Hélène; Giraud, Tatiana; Viaud, Muriel; Fournier, Elisabeth; Rodolphe, François; Marthey, Sylvain; Ducasse, Aurélie; Gendrault, Annie; Poulain, Julie; Wincker, Patrick; Gout, Lilian

2012-07-01

The rapid evolution of particular genes is essential for the adaptation of pathogens to new hosts and new environments. Powerful methods have been developed for detecting targets of selection in the genome. Here we used divergence data to compare genes among four closely related fungal pathogens adapted to different hosts to elucidate the functions putatively involved in adaptive processes. For this goal, ESTs were sequenced in the specialist fungal pathogens Botrytis tulipae and Botrytis ficariarum, and compared with genome sequences of Botrytis cinerea and Sclerotinia sclerotiorum, responsible for diseases on over 200 plant species. A maximum likelihood-based analysis of 642 predicted orthologs detected 21 genes showing footprints of positive selection. These results were validated by resequencing nine of these genes in additional Botrytis species, showing they have also been rapidly evolving in other related species. Twenty of the 21 genes had not previously been identified as pathogenicity factors in B. cinerea, but some had functions related to plant-fungus interactions. The putative functions were involved in respiratory and energy metabolism, protein and RNA metabolism, signal transduction or virulence, similarly to what was detected in previous studies using the same approach in other pathogens. Mutants of B. cinerea were generated for four of these genes as a first attempt to elucidate their functions. Copyright © 2012 Elsevier B.V. All rights reserved.

Arabidopsis Ensemble Reverse-Engineered Gene Regulatory Network Discloses Interconnected Transcription Factors in Oxidative Stress[W

PubMed Central

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-01-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. PMID:25549671

Arabidopsis ensemble reverse-engineered gene regulatory network discloses interconnected transcription factors in oxidative stress.

PubMed

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-12-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. © 2014 American Society of Plant Biologists. All rights reserved.

Identification of in vivo regulators of the Vibrio cholerae xds gene using a high-throughput genetic selection.

PubMed

McDonough, Emilykate; Lazinski, David W; Camilli, Andrew

2014-04-01

Vibrio cholerae, the causative agent of cholera, remains a threat to public health in areas with inadequate sanitation. As a waterborne pathogen, V. cholerae moves between two dissimilar environments, aquatic reservoirs and the intestinal tract of humans. Accordingly, this pathogen undergoes adaptive shifts in gene expression throughout the different stages of its lifecycle. One particular gene, xds, encodes a secreted exonuclease that was previously identified as being induced during infection. Here we sought to identify regulators responsible for the in vivo-specific induction of xds. A transcriptional fusion of xds to two consecutive antibiotic resistance genes was used to select transposon mutants that had inserted within or adjacent to regulatory genes and thereby caused increased expression of the xds fusion under non-inducing conditions. Large pools of selected insertion sites were sequenced in a high throughput manner using Tn-seq to identify potential mechanisms of xds regulation. Our selection identified the two-component system PhoB/R as the dominant activator of xds expression. In vitro validation confirmed that PhoB, a protein which is only active during phosphate limitation, was responsible for xds activation. Using xds expression as a biosensor of the extracellular phosphate level, we observed that the mouse small intestine is a phosphate-limited environment. © 2014 John Wiley & Sons Ltd.

Selection of Suitable Reference Genes for RT-qPCR Normalization under Abiotic Stresses and Hormone Stimulation in Persimmon (Diospyros kaki Thunb)

PubMed Central

Wang, Peihong; Xiong, Aisheng; Gao, Zhihong; Yu, Xinyi; Li, Man; Hou, Yingjun; Sun, Chao; Qu, Shenchun

2016-01-01

The success of quantitative real-time reverse transcription polymerase chain reaction (RT-qPCR) to quantify gene expression depends on the stability of the reference genes used for data normalization. To date, systematic screening for reference genes in persimmon (Diospyros kaki Thunb) has never been reported. In this study, 13 candidate reference genes were cloned from 'Nantongxiaofangshi' using information available in the transcriptome database. Their expression stability was assessed by geNorm and NormFinder algorithms under abiotic stress and hormone stimulation. Our results showed that the most suitable reference genes across all samples were UBC and GAPDH, and not the commonly used persimmon reference gene ACT. In addition, UBC combined with RPII or TUA were found to be appropriate for the "abiotic stress" group and α-TUB combined with PP2A were found to be appropriate for the "hormone stimuli" group. For further validation, the transcript level of the DkDREB2C homologue under heat stress was studied with the selected genes (CYP, GAPDH, TUA, UBC, α-TUB, and EF1-α). The results suggested that it is necessary to choose appropriate reference genes according to the test materials or experimental conditions. Our study will be useful for future studies on gene expression in persimmon. PMID:27513755

Expression Profiling in Bemisia tabaci under Insecticide Treatment: Indicating the Necessity for Custom Reference Gene Selection

PubMed Central

Zhou, Xuguo; Gao, Xiwu

2014-01-01

Finding a suitable reference gene is the key for qRT-PCR analysis. However, none of the reference gene discovered thus far can be utilized universally under various biotic and abiotic experimental conditions. In this study, we further examine the stability of candidate reference genes under a single abiotic factor, insecticide treatment. After being exposed to eight commercially available insecticides, which belong to five different classes, the expression profiles of eight housekeeping genes in the sweetpotato whitefly, Bemisia tabaci, one of the most invasive and destructive pests in the world, were investigated using qRT-PCR analysis. In summary, elongation factor 1α (EF1α), α-tubulin (TUB1α) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were identified as the most stable reference genes under the insecticide treatment. The initial assessment of candidate reference genes was further validated with the expression of two target genes, a P450 (Cyp6cm1) and a glutathione S-transferase (GST). However, ranking of reference genes varied substantially among intra- and inter-classes of insecticides. These combined data strongly suggested the necessity of conducting custom reference gene selection designed for each and every experimental condition, even when examining the same abiotic or biotic factor. PMID:24498122

Validation of Reference Genes for Gene Expression Studies in Virus-Infected Nicotiana benthamiana Using Quantitative Real-Time PCR

PubMed Central

Han, Chenggui; Yu, Jialin; Li, Dawei; Zhang, Yongliang

2012-01-01

Nicotiana benthamiana is the most widely-used experimental host in plant virology. The recent release of the draft genome sequence for N. benthamiana consolidates its role as a model for plant–pathogen interactions. Quantitative real-time PCR (qPCR) is commonly employed for quantitative gene expression analysis. For valid qPCR analysis, accurate normalisation of gene expression against an appropriate internal control is required. Yet there has been little systematic investigation of reference gene stability in N. benthamiana under conditions of viral infections. In this study, the expression profiles of 16 commonly used housekeeping genes (GAPDH, 18S, EF1α, SAMD, L23, UK, PP2A, APR, UBI3, SAND, ACT, TUB, GBP, F-BOX, PPR and TIP41) were determined in N. benthamiana and those with acceptable expression levels were further selected for transcript stability analysis by qPCR of complementary DNA prepared from N. benthamiana leaf tissue infected with one of five RNA plant viruses (Tobacco necrosis virus A, Beet black scorch virus, Beet necrotic yellow vein virus, Barley stripe mosaic virus and Potato virus X). Gene stability was analysed in parallel by three commonly-used dedicated algorithms: geNorm, NormFinder and BestKeeper. Statistical analysis revealed that the PP2A, F-BOX and L23 genes were the most stable overall, and that the combination of these three genes was sufficient for accurate normalisation. In addition, the suitability of PP2A, F-BOX and L23 as reference genes was illustrated by expression-level analysis of AGO2 and RdR6 in virus-infected N. benthamiana leaves. This is the first study to systematically examine and evaluate the stability of different reference genes in N. benthamiana. Our results not only provide researchers studying these viruses a shortlist of potential housekeeping genes to use as normalisers for qPCR experiments, but should also guide the selection of appropriate reference genes for gene expression studies of N. benthamiana under other biotic and abiotic stress conditions. PMID:23029521

Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis.

PubMed

dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

2015-01-01

Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis.

Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis

PubMed Central

dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

2015-01-01

Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis. PMID:26393928

Development of a RAD-Seq Based DNA Polymorphism Identification Software, AgroMarker Finder, and Its Application in Rice Marker-Assisted Breeding

PubMed Central

Luo, Zhijing; Chen, Mingjiao; Zhao, Xiangxiang; Zhang, Dabing; Qi, Yiping; Yuan, Zheng

2016-01-01

Rapid and accurate genome-wide marker detection is essential to the marker-assisted breeding and functional genomics studies. In this work, we developed an integrated software, AgroMarker Finder (AMF: http://erp.novelbio.com/AMF), for providing graphical user interface (GUI) to facilitate the recently developed restriction-site associated DNA (RAD) sequencing data analysis in rice. By application of AMF, a total of 90,743 high-quality markers (82,878 SNPs and 7,865 InDels) were detected between rice varieties JP69 and Jiaoyuan5A. The density of the identified markers is 0.2 per Kb for SNP markers, and 0.02 per Kb for InDel markers. Sequencing validation revealed that the accuracy of genome-wide marker detection by AMF is 93%. In addition, a validated subset of 82 SNPs and 31 InDels were found to be closely linked to 117 important agronomic trait genes, providing a basis for subsequent marker-assisted selection (MAS) and variety identification. Furthermore, we selected 12 markers from 31 validated InDel markers to identify seed authenticity of variety Jiaoyuanyou69, and we also identified 10 markers closely linked to the fragrant gene BADH2 to minimize linkage drag for Wuxiang075 (BADH2 donor)/Jiachang1 recombinants selection. Therefore, this software provides an efficient approach for marker identification from RAD-seq data, and it would be a valuable tool for plant MAS and variety protection. PMID:26799713

Development of a RAD-Seq Based DNA Polymorphism Identification Software, AgroMarker Finder, and Its Application in Rice Marker-Assisted Breeding.

PubMed

Fan, Wei; Zong, Jie; Luo, Zhijing; Chen, Mingjiao; Zhao, Xiangxiang; Zhang, Dabing; Qi, Yiping; Yuan, Zheng

2016-01-01

Rapid and accurate genome-wide marker detection is essential to the marker-assisted breeding and functional genomics studies. In this work, we developed an integrated software, AgroMarker Finder (AMF: http://erp.novelbio.com/AMF), for providing graphical user interface (GUI) to facilitate the recently developed restriction-site associated DNA (RAD) sequencing data analysis in rice. By application of AMF, a total of 90,743 high-quality markers (82,878 SNPs and 7,865 InDels) were detected between rice varieties JP69 and Jiaoyuan5A. The density of the identified markers is 0.2 per Kb for SNP markers, and 0.02 per Kb for InDel markers. Sequencing validation revealed that the accuracy of genome-wide marker detection by AMF is 93%. In addition, a validated subset of 82 SNPs and 31 InDels were found to be closely linked to 117 important agronomic trait genes, providing a basis for subsequent marker-assisted selection (MAS) and variety identification. Furthermore, we selected 12 markers from 31 validated InDel markers to identify seed authenticity of variety Jiaoyuanyou69, and we also identified 10 markers closely linked to the fragrant gene BADH2 to minimize linkage drag for Wuxiang075 (BADH2 donor)/Jiachang1 recombinants selection. Therefore, this software provides an efficient approach for marker identification from RAD-seq data, and it would be a valuable tool for plant MAS and variety protection.

Composite selection signals can localize the trait specific genomic regions in multi-breed populations of cattle and sheep

PubMed Central

2014-01-01

Background Discerning the traits evolving under neutral conditions from those traits evolving rapidly because of various selection pressures is a great challenge. We propose a new method, composite selection signals (CSS), which unifies the multiple pieces of selection evidence from the rank distribution of its diverse constituent tests. The extreme CSS scores capture highly differentiated loci and underlying common variants hauling excess haplotype homozygosity in the samples of a target population. Results The data on high-density genotypes were analyzed for evidence of an association with either polledness or double muscling in various cohorts of cattle and sheep. In cattle, extreme CSS scores were found in the candidate regions on autosome BTA-1 and BTA-2, flanking the POLL locus and MSTN gene, for polledness and double muscling, respectively. In sheep, the regions with extreme scores were localized on autosome OAR-2 harbouring the MSTN gene for double muscling and on OAR-10 harbouring the RXFP2 gene for polledness. In comparison to the constituent tests, there was a partial agreement between the signals at the four candidate loci; however, they consistently identified additional genomic regions harbouring no known genes. Persuasively, our list of all the additional significant CSS regions contains genes that have been successfully implicated to secondary phenotypic diversity among several subpopulations in our data. For example, the method identified a strong selection signature for stature in cattle capturing selective sweeps harbouring UQCC-GDF5 and PLAG1-CHCHD7 gene regions on BTA-13 and BTA-14, respectively. Both gene pairs have been previously associated with height in humans, while PLAG1-CHCHD7 has also been reported for stature in cattle. In the additional analysis, CSS identified significant regions harbouring multiple genes for various traits under selection in European cattle including polledness, adaptation, metabolism, growth rate, stature, immunity, reproduction traits and some other candidate genes for dairy and beef production. Conclusions CSS successfully localized the candidate regions in validation datasets as well as identified previously known and novel regions for various traits experiencing selection pressure. Together, the results demonstrate the utility of CSS by its improved power, reduced false positives and high-resolution of selection signals as compared to individual constituent tests. PMID:24636660

Selection Shapes Transcriptional Logic and Regulatory Specialization in Genetic Networks.

PubMed

Fogelmark, Karl; Peterson, Carsten; Troein, Carl

2016-01-01

Living organisms need to regulate their gene expression in response to environmental signals and internal cues. This is a computational task where genes act as logic gates that connect to form transcriptional networks, which are shaped at all scales by evolution. Large-scale mutations such as gene duplications and deletions add and remove network components, whereas smaller mutations alter the connections between them. Selection determines what mutations are accepted, but its importance for shaping the resulting networks has been debated. To investigate the effects of selection in the shaping of transcriptional networks, we derive transcriptional logic from a combinatorially powerful yet tractable model of the binding between DNA and transcription factors. By evolving the resulting networks based on their ability to function as either a simple decision system or a circadian clock, we obtain information on the regulation and logic rules encoded in functional transcriptional networks. Comparisons are made between networks evolved for different functions, as well as with structurally equivalent but non-functional (neutrally evolved) networks, and predictions are validated against the transcriptional network of E. coli. We find that the logic rules governing gene expression depend on the function performed by the network. Unlike the decision systems, the circadian clocks show strong cooperative binding and negative regulation, which achieves tight temporal control of gene expression. Furthermore, we find that transcription factors act preferentially as either activators or repressors, both when binding multiple sites for a single target gene and globally in the transcriptional networks. This separation into positive and negative regulators requires gene duplications, which highlights the interplay between mutation and selection in shaping the transcriptional networks.

Lex-SVM: exploring the potential of exon expression profiling for disease classification.

PubMed

Yuan, Xiongying; Zhao, Yi; Liu, Changning; Bu, Dongbo

2011-04-01

Exon expression profiling technologies, including exon arrays and RNA-Seq, measure the abundance of every exon in a gene. Compared with gene expression profiling technologies like 3' array, exon expression profiling technologies could detect alterations in both transcription and alternative splicing, therefore they are expected to be more sensitive in diagnosis. However, exon expression profiling also brings higher dimension, more redundancy, and significant correlation among features. Ignoring the correlation structure among exons of a gene, a popular classification method like L1-SVM selects exons individually from each gene and thus is vulnerable to noise. To overcome this limitation, we present in this paper a new variant of SVM named Lex-SVM to incorporate correlation structure among exons and known splicing patterns to promote classification performance. Specifically, we construct a new norm, ex-norm, including our prior knowledge on exon correlation structure to regularize the coefficients of a linear SVM. Lex-SVM can be solved efficiently using standard linear programming techniques. The advantage of Lex-SVM is that it can select features group-wisely, force features in a subgroup to take equal weihts and exclude the features that contradict the majority in the subgroup. Experimental results suggest that on exon expression profile, Lex-SVM is more accurate than existing methods. Lex-SVM also generates a more compact model and selects genes more consistently in cross-validation. Unlike L1-SVM selecting only one exon in a gene, Lex-SVM assigns equal weights to as many exons in a gene as possible, lending itself easier for further interpretation.

Identification of differentially expressed genes in the oviduct of two rabbit lines divergently selected for uterine capacity using suppression subtractive hybridization.

PubMed

Ballester, M; Castelló, A; Peiró, R; Argente, M J; Santacreu, M A; Folch, J M

2013-06-01

Suppressive subtractive hybridization libraries from oviduct at 62 h post-mating of two lines of rabbits divergently selected for uterine capacity were generated to identify differentially expressed genes. A total of 438 singletons and 126 contigs were obtained by cluster assembly and sequence alignment of 704 expressed sequence tags (ESTs), of which 54% showed homology to known proteins of the non-redundant NCBI databases. Differential screening by dot blot validated 71 ESTs, of which 47 showed similarity to known genes. Transcripts of genes were functionally annotated in the molecular function and the biological process gene ontology categories using the BLAST2GO software and were assigned to reproductive developmental process, immune response, amino acid metabolism and degradation, response to stress and apoptosis terms. Finally, three interesting genes, PGR, HSD17B4 and ERO1L, were identified as overexpressed in the low line using RT-qPCR. Our study provides a list of candidate genes that can be useful to understanding the molecular mechanisms underlying the phenotypic differences observed in early embryo survival and development traits. © 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.

Genomic Signatures Reveal New Evidences for Selection of Important Traits in Domestic Cattle

PubMed Central

Xu, Lingyang; Bickhart, Derek M.; Cole, John B.; Schroeder, Steven G.; Song, Jiuzhou; Tassell, Curtis P. Van; Sonstegard, Tad S.; Liu, George E.

2015-01-01

We investigated diverse genomic selections using high-density single nucleotide polymorphism data of five distinct cattle breeds. Based on allele frequency differences, we detected hundreds of candidate regions under positive selection across Holstein, Angus, Charolais, Brahman, and N'Dama. In addition to well-known genes such as KIT, MC1R, ASIP, GHR, LCORL, NCAPG, WIF1, and ABCA12, we found evidence for a variety of novel and less-known genes under selection in cattle, such as LAP3, SAR1B, LRIG3, FGF5, and NUDCD3. Selective sweeps near LAP3 were then validated by next-generation sequencing. Genome-wide association analysis involving 26,362 Holsteins confirmed that LAP3 and SAR1B were related to milk production traits, suggesting that our candidate regions were likely functional. In addition, haplotype network analyses further revealed distinct selective pressures and evolution patterns across these five cattle breeds. Our results provided a glimpse into diverse genomic selection during cattle domestication, breed formation, and recent genetic improvement. These findings will facilitate genome-assisted breeding to improve animal production and health. PMID:25431480

Robust diagnosis of non-Hodgkin lymphoma phenotypes validated on gene expression data from different laboratories.

PubMed

Bhanot, Gyan; Alexe, Gabriela; Levine, Arnold J; Stolovitzky, Gustavo

2005-01-01

A major challenge in cancer diagnosis from microarray data is the need for robust, accurate, classification models which are independent of the analysis techniques used and can combine data from different laboratories. We propose such a classification scheme originally developed for phenotype identification from mass spectrometry data. The method uses a robust multivariate gene selection procedure and combines the results of several machine learning tools trained on raw and pattern data to produce an accurate meta-classifier. We illustrate and validate our method by applying it to gene expression datasets: the oligonucleotide HuGeneFL microarray dataset of Shipp et al. (www.genome.wi.mit.du/MPR/lymphoma) and the Hu95Av2 Affymetrix dataset (DallaFavera's laboratory, Columbia University). Our pattern-based meta-classification technique achieves higher predictive accuracies than each of the individual classifiers , is robust against data perturbations and provides subsets of related predictive genes. Our techniques predict that combinations of some genes in the p53 pathway are highly predictive of phenotype. In particular, we find that in 80% of DLBCL cases the mRNA level of at least one of the three genes p53, PLK1 and CDK2 is elevated, while in 80% of FL cases, the mRNA level of at most one of them is elevated.

Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

PubMed

Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

2017-11-01

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

Validating internal controls for quantitative plant gene expression studies

PubMed Central

Brunner, Amy M; Yakovlev, Igor A; Strauss, Steven H

2004-01-01

Background Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed. Results Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied. Conclusion Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments. PMID:15317655

FlyPrimerBank: An Online Database for Drosophila melanogaster Gene Expression Analysis and Knockdown Evaluation of RNAi Reagents

PubMed Central

Hu, Yanhui; Sopko, Richelle; Foos, Marianna; Kelley, Colleen; Flockhart, Ian; Ammeux, Noemie; Wang, Xiaowei; Perkins, Lizabeth; Perrimon, Norbert; Mohr, Stephanie E.

2013-01-01

The evaluation of specific endogenous transcript levels is important for understanding transcriptional regulation. More specifically, it is useful for independent confirmation of results obtained by the use of microarray analysis or RNA-seq and for evaluating RNA interference (RNAi)-mediated gene knockdown. Designing specific and effective primers for high-quality, moderate-throughput evaluation of transcript levels, i.e., quantitative, real-time PCR (qPCR), is nontrivial. To meet community needs, predefined qPCR primer pairs for mammalian genes have been designed and sequences made available, e.g., via PrimerBank. In this work, we adapted and refined the algorithms used for the mammalian PrimerBank to design 45,417 primer pairs for 13,860 Drosophila melanogaster genes, with three or more primer pairs per gene. We experimentally validated primer pairs for ~300 randomly selected genes expressed in early Drosophila embryos, using SYBR Green-based qPCR and sequence analysis of products derived from conventional PCR. All relevant information, including primer sequences, isoform specificity, spatial transcript targeting, and any available validation results and/or user feedback, is available from an online database (www.flyrnai.org/flyprimerbank). At FlyPrimerBank, researchers can retrieve primer information for fly genes either one gene at a time or in batch mode. Importantly, we included the overlap of each predicted amplified sequence with RNAi reagents from several public resources, making it possible for researchers to choose primers suitable for knockdown evaluation of RNAi reagents (i.e., to avoid amplification of the RNAi reagent itself). We demonstrate the utility of this resource for validation of RNAi reagents in vivo. PMID:23893746

In silico characterization and transcriptomic analysis of nif family genes from Anabaena sp. PCC7120.

PubMed

Singh, Shilpi; Shrivastava, Alok Kumar

2017-10-01

In silico approaches in conjunction with morphology, nitrogenase activity, and qRT-PCR explore the impact of selected abiotic stressor such as arsenic, salt, cadmium, copper, and butachlor on nitrogen fixing (nif family) genes of diazotrophic cyanobacterium Anabaena sp. PCC7120. A total of 19 nif genes are present within the Anabaena genome that is involved in the process of nitrogen fixation. Docking studies revealed the interaction between these nif gene-encoded proteins and the selected abiotic stressors which were further validated through decreased heterocyst frequency, fragmentation of filaments, and downregulation of nitrogenase activity under these stresses indicating towards their toxic impact on nitrogen fixation potential of filamentous cyanobacterium Anabaena sp. PCC7120. Another appealing finding of this study is even though having similar binding energy and similar interacting residues between arsenic/salt and copper/cadmium to nif-encoded proteins, arsenic and cadmium are more toxic than salt and copper for nitrogenase activity of Anabaena which is crucial for growth and yield of rice paddy and soil reclamation.

Metabolomic profiling and genomic analysis of wheat aneuploid lines to identify genes controlling biochemical pathways in mature grain.

PubMed

Francki, Michael G; Hayton, Sarah; Gummer, Joel P A; Rawlinson, Catherine; Trengove, Robert D

2016-02-01

Metabolomics is becoming an increasingly important tool in plant genomics to decipher the function of genes controlling biochemical pathways responsible for trait variation. Although theoretical models can integrate genes and metabolites for trait variation, biological networks require validation using appropriate experimental genetic systems. In this study, we applied an untargeted metabolite analysis to mature grain of wheat homoeologous group 3 ditelosomic lines, selected compounds that showed significant variation between wheat lines Chinese Spring and at least one ditelosomic line, tracked the genes encoding enzymes of their biochemical pathway using the wheat genome survey sequence and determined the genetic components underlying metabolite variation. A total of 412 analytes were resolved in the wheat grain metabolome, and principal component analysis indicated significant differences in metabolite profiles between Chinese Spring and each ditelosomic lines. The grain metabolome identified 55 compounds positively matched against a mass spectral library where the majority showed significant differences between Chinese Spring and at least one ditelosomic line. Trehalose and branched-chain amino acids were selected for detailed investigation, and it was expected that if genes encoding enzymes directly related to their biochemical pathways were located on homoeologous group 3 chromosomes, then corresponding ditelosomic lines would have a significant reduction in metabolites compared with Chinese Spring. Although a proportion showed a reduction, some lines showed significant increases in metabolites, indicating that genes directly and indirectly involved in biosynthetic pathways likely regulate the metabolome. Therefore, this study demonstrated that wheat aneuploid lines are suitable experimental genetic system to validate metabolomics-genomics networks. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Directed evolution induces tributyrin hydrolysis in a virulence factor of Xylella fastidiosa using a duplicated gene as a template.

PubMed

Gouran, Hossein; Chakraborty, Sandeep; Rao, Basuthkar J; Asgeirsson, Bjarni; Dandekar, Abhaya

2014-01-01

Duplication of genes is one of the preferred ways for natural selection to add advantageous functionality to the genome without having to reinvent the wheel with respect to catalytic efficiency and protein stability. The duplicated secretory virulence factors of Xylella fastidiosa (LesA, LesB and LesC), implicated in Pierce's disease of grape and citrus variegated chlorosis of citrus species, epitomizes the positive selection pressures exerted on advantageous genes in such pathogens. A deeper insight into the evolution of these lipases/esterases is essential to develop resistance mechanisms in transgenic plants. Directed evolution, an attempt to accelerate the evolutionary steps in the laboratory, is inherently simple when targeted for loss of function. A bigger challenge is to specify mutations that endow a new function, such as a lost functionality in a duplicated gene. Previously, we have proposed a method for enumerating candidates for mutations intended to transfer the functionality of one protein into another related protein based on the spatial and electrostatic properties of the active site residues (DECAAF). In the current work, we present in vivo validation of DECAAF by inducing tributyrin hydrolysis in LesB based on the active site similarity to LesA. The structures of these proteins have been modeled using RaptorX based on the closely related LipA protein from Xanthomonas oryzae. These mutations replicate the spatial and electrostatic conformation of LesA in the modeled structure of the mutant LesB as well, providing in silico validation before proceeding to the laborious in vivo work. Such focused mutations allows one to dissect the relevance of the duplicated genes in finer detail as compared to gene knockouts, since they do not interfere with other moonlighting functions, protein expression levels or protein-protein interaction.

CRISPR Genome-Wide Screening Identifies Dependence on the Proteasome Subunit PSMC6 for Bortezomib Sensitivity in Multiple Myeloma.

PubMed

Shi, Chang-Xin; Kortüm, K Martin; Zhu, Yuan Xiao; Bruins, Laura A; Jedlowski, Patrick; Votruba, Patrick G; Luo, Moulun; Stewart, Robert A; Ahmann, Jonathan; Braggio, Esteban; Stewart, A Keith

2017-12-01

Bortezomib is highly effective in the treatment of multiple myeloma; however, emergent drug resistance is common. Consequently, we employed CRISPR targeting 19,052 human genes to identify unbiased targets that contribute to bortezomib resistance. Specifically, we engineered an RPMI8226 multiple myeloma cell line to express Cas9 infected by lentiviral vector CRISPR library and cultured derived cells in doses of bortezomib lethal to parental cells. Sequencing was performed on surviving cells to identify inactivated genes responsible for drug resistance. From two independent whole-genome screens, we selected 31 candidate genes and constructed a second CRISPR sgRNA library, specifically targeting each of these 31 genes with four sgRNAs. After secondary screening for bortezomib resistance, the top 20 "resistance" genes were selected for individual validation. Of these 20 targets, the proteasome regulatory subunit PSMC6 was the only gene validated to reproducibly confer bortezomib resistance. We confirmed that inhibition of chymotrypsin-like proteasome activity by bortezomib was significantly reduced in cells lacking PSMC6. We individually investigated other members of the PSMC group (PSMC1 to 5) and found that deficiency in each of those subunits also imparts bortezomib resistance. We found 36 mutations in 19S proteasome subunits out of 895 patients in the IA10 release of the CoMMpass study (https://themmrf.org). Our findings demonstrate that the PSMC6 subunit is the most prominent target required for bortezomib sensitivity in multiple myeloma cells and should be examined in drug-refractory populations. Mol Cancer Ther; 16(12); 2862-70. ©2017 AACR . ©2017 American Association for Cancer Research.

Directed evolution induces tributyrin hydrolysis in a virulence factor of Xylella fastidiosa using a duplicated gene as a template

PubMed Central

Rao, Basuthkar J.; Asgeirsson, Bjarni; Dandekar, Abhaya

2014-01-01

Duplication of genes is one of the preferred ways for natural selection to add advantageous functionality to the genome without having to reinvent the wheel with respect to catalytic efficiency and protein stability. The duplicated secretory virulence factors of Xylella fastidiosa (LesA, LesB and LesC), implicated in Pierce's disease of grape and citrus variegated chlorosis of citrus species, epitomizes the positive selection pressures exerted on advantageous genes in such pathogens. A deeper insight into the evolution of these lipases/esterases is essential to develop resistance mechanisms in transgenic plants. Directed evolution, an attempt to accelerate the evolutionary steps in the laboratory, is inherently simple when targeted for loss of function. A bigger challenge is to specify mutations that endow a new function, such as a lost functionality in a duplicated gene. Previously, we have proposed a method for enumerating candidates for mutations intended to transfer the functionality of one protein into another related protein based on the spatial and electrostatic properties of the active site residues (DECAAF). In the current work, we present in vivo validation of DECAAF by inducing tributyrin hydrolysis in LesB based on the active site similarity to LesA. The structures of these proteins have been modeled using RaptorX based on the closely related LipA protein from Xanthomonas oryzae. These mutations replicate the spatial and electrostatic conformation of LesA in the modeled structure of the mutant LesB as well, providing in silico validation before proceeding to the laborious in vivo work. Such focused mutations allows one to dissect the relevance of the duplicated genes in finer detail as compared to gene knockouts, since they do not interfere with other moonlighting functions, protein expression levels or protein-protein interaction. PMID:25717364

A novel selection signature in stearoyl-coenzyme A desaturase (SCD) gene for enhanced milk fat content in Bubalus bubalis.

PubMed

Maryam, J; Babar, M E; Bao, Zhang; Nadeem, A

2016-10-01

Modern molecular interventions are dynamic gears for breeding animals with superior genetic make-up. These scientific efforts lead us toward sustainable dairy herds with improved milk production in terms of yield and quality. Many of candidate genes have been dissected at molecular level, and suitable genetic markers have been identified in cattle, but this work has not been validated in buffaloes so far. Stearoyl-coenzyme A desaturase (SCD) has been a potential candidate gene for fat content of milk. Genomic analysis of SCD revealed a total of six variations that were identified through DNA sequencing of animals with lower and higher butter fat %age. After statistical analysis, genotype AB of p.K158I could be associated (P value <0.0001) with higher milk fat %age (10.5 ± 0.5464). This SNP was validated on larger data set by cleaved amplified polymorphic sequences (CAPS) by using DdeI. To scrutinize the functional consequences of p.K158I, 3D protein structure of SCD was predicted by homology modeling and this variation was found located in the vicinity of functional domain and a part of transmembrane helix of this membrane integrated protein. This is a first report toward genetic screening of SCD gene at molecular level in buffalo. This report illustrates the implication of SCD gene and in particular p.K158I variation, in imparting its effect on milk fat %age, which can be targeted in selection of superior dairy buffaloes.

Diversification, phylogeny and evolution of auxin response factor (ARF) family: insights gained from analyzing maize ARF genes.

PubMed

Wang, Yijun; Deng, Dexiang; Shi, Yating; Miao, Nan; Bian, Yunlong; Yin, Zhitong

2012-03-01

Auxin response factors (ARFs), member of the plant-specific B3 DNA binding superfamily, target specifically to auxin response elements (AuxREs) in promoters of primary auxin-responsive genes and heterodimerize with Aux/IAA proteins in auxin signaling transduction cascade. In previous research, we have isolated and characterized maize Aux/IAA genes in whole-genome scale. Here, we report the comprehensive analysis of ARF genes in maize. A total of 36 ARF genes were identified and validated from the B73 maize genome through an iterative strategy. Thirty-six maize ARF genes are distributed in all maize chromosomes except chromosome 7. Maize ARF genes expansion is mainly due to recent segmental duplications. Maize ARF proteins share one B3 DNA binding domain which consists of seven-stranded β sheets and two short α helixes. Twelve maize ARFs with glutamine-rich middle regions could be as activators in modulating expression of auxin-responsive genes. Eleven maize ARF proteins are lack of homo- and heterodimerization domains. Putative cis-elements involved in phytohormones and light signaling responses, biotic and abiotic stress adaption locate in promoters of maize ARF genes. Expression patterns vary greatly between clades and sister pairs of maize ARF genes. The B3 DNA binding and auxin response factor domains of maize ARF proteins are primarily subjected to negative selection during selective sweep. The mixed selective forces drive the diversification and evolution of genomic regions outside of B3 and ARF domains. Additionally, the dicot-specific proliferation of ARF genes was detected. Comparative genomics analysis indicated that maize, sorghum and rice duplicate chromosomal blocks containing ARF homologs are highly syntenic. This study provides insights into the distribution, phylogeny and evolution of ARF gene family.

Global transcriptomic responses of Escherichia coli K-12 to volatile organic compounds.

PubMed

Yung, Pui Yi; Grasso, Letizia Lo; Mohidin, Abeed Fatima; Acerbi, Enzo; Hinks, Jamie; Seviour, Thomas; Marsili, Enrico; Lauro, Federico M

2016-01-28

Volatile organic compounds (VOCs) are commonly used as solvents in various industrial settings. Many of them present a challenge to receiving environments, due to their toxicity and low bioavailability for degradation. Microorganisms are capable of sensing and responding to their surroundings and this makes them ideal detectors for toxic compounds. This study investigates the global transcriptomic responses of Escherichia coli K-12 to selected VOCs at sub-toxic levels. Cells grown in the presence of VOCs were harvested during exponential growth, followed by whole transcriptome shotgun sequencing (RNAseq). The analysis of the data revealed both shared and unique genetic responses compared to cells without exposure to VOCs. Results suggest that various functional gene categories, for example, those relating to Fe/S cluster biogenesis, oxidative stress responses and transport proteins, are responsive to selected VOCs in E. coli. The differential expression (DE) of genes was validated using GFP-promoter fusion assays. A variety of genes were differentially expressed even at non-inhibitory concentrations and when the cells are at their balanced-growth. Some of these genes belong to generic stress response and others could be specific to VOCs. Such candidate genes and their regulatory elements could be used as the basis for designing biosensors for selected VOCs.

Global transcriptomic responses of Escherichia coli K-12 to volatile organic compounds

PubMed Central

Yung, Pui Yi; Grasso, Letizia Lo; Mohidin, Abeed Fatima; Acerbi, Enzo; Hinks, Jamie; Seviour, Thomas; Marsili, Enrico; Lauro, Federico M.

2016-01-01

Volatile organic compounds (VOCs) are commonly used as solvents in various industrial settings. Many of them present a challenge to receiving environments, due to their toxicity and low bioavailability for degradation. Microorganisms are capable of sensing and responding to their surroundings and this makes them ideal detectors for toxic compounds. This study investigates the global transcriptomic responses of Escherichia coli K-12 to selected VOCs at sub-toxic levels. Cells grown in the presence of VOCs were harvested during exponential growth, followed by whole transcriptome shotgun sequencing (RNAseq). The analysis of the data revealed both shared and unique genetic responses compared to cells without exposure to VOCs. Results suggest that various functional gene categories, for example, those relating to Fe/S cluster biogenesis, oxidative stress responses and transport proteins, are responsive to selected VOCs in E. coli. The differential expression (DE) of genes was validated using GFP-promoter fusion assays. A variety of genes were differentially expressed even at non-inhibitory concentrations and when the cells are at their balanced-growth. Some of these genes belong to generic stress response and others could be specific to VOCs. Such candidate genes and their regulatory elements could be used as the basis for designing biosensors for selected VOCs. PMID:26818886

Reciprocal Translocation Observed in End-of-Production Cells of a Commercial CHO-Based Process.

PubMed

Rouiller, Yolande; Kleuser, Beate; Toso, Emiliano; Palinksy, Wolf; Rossi, Mara; Rossatto, Paola; Barberio, Davide; Broly, Hervé

2015-01-01

During the validation of an additional working cell bank derived from a validated master cell bank to support the commercial production continuum of a recombinant protein, we observed an unexpected chromosomal location of the gene of interest in some end-of-production cells. This event-identified by fluorescence in situ hybridization and multicolour chromosome painting as a reciprocal translocation involving a chromosome region containing the gene of interest with its integral coding and flanking sequences-was unique, occurred probably during or prior to multicolour chromosome painting establishment, and was transmitted to the descending generations. Cells bearing the translocation had a transient and process-independent selective advantage, which did not affect process performance and product quality. However, this first report of a translocation affecting the gene of interest location in Chinese Hamster Ovary cells used for producing a biotherapeutic indicates the importance of the demonstration of the integrity of the gene of interest in end-of-production cells. The expression of recombinant therapeutic proteins in mammalian cells depends on the establishment of a cell line with the gene of interest integrated in the host genome and stably expressed over time. Before being used for commercial production, cell lines are submitted to a qualification program in order to ensure their phenotypic and genotypic characteristics and the efficacy and safety of the product. During the production life cycle of a therapeutic protein, additional cells banks have to be validated after exhaustion of the current qualified cell bank in order to support the commercial production continuum of the recombinant protein. It is during the validation of an additional working cell bank derived from a validated master cell bank that we detected a different chromosome bearing the gene of interest in a portion of cells at the end of the upstream production phase. In our case, this event did not affect the process performance, the product quality, or its safety profile, but it highlights the need to characterize the integrity of the gene of interest in end-of-production cells when producing recombinant proteins for human use. © PDA, Inc. 2015.

Evaluation of Reference Genes for Quantitative Real-Time PCR in Songbirds

PubMed Central

Zinzow-Kramer, Wendy M.; Horton, Brent M.; Maney, Donna L.

2014-01-01

Quantitative real-time PCR (qPCR) is becoming a popular tool for the quantification of gene expression in the brain and endocrine tissues of songbirds. Accurate analysis of qPCR data relies on the selection of appropriate reference genes for normalization, yet few papers on songbirds contain evidence of reference gene validation. Here, we evaluated the expression of ten potential reference genes (18S, ACTB, GAPDH, HMBS, HPRT, PPIA, RPL4, RPL32, TFRC, and UBC) in brain, pituitary, ovary, and testis in two species of songbird: zebra finch and white-throated sparrow. We used two algorithms, geNorm and NormFinder, to assess the stability of these reference genes in our samples. We found that the suitability of some of the most popular reference genes for target gene normalization in mammals, such as 18S, depended highly on tissue type. Thus, they are not the best choices for brain and gonad in these songbirds. In contrast, we identified alternative genes, such as HPRT, RPL4 and PPIA, that were highly stable in brain, pituitary, and gonad in these species. Our results suggest that the validation of reference genes in mammals does not necessarily extrapolate to other taxonomic groups. For researchers wishing to identify and evaluate suitable reference genes for qPCR songbirds, our results should serve as a starting point and should help increase the power and utility of songbird models in behavioral neuroendocrinology. PMID:24780145

Automated ensemble assembly and validation of microbial genomes.

PubMed

Koren, Sergey; Treangen, Todd J; Hill, Christopher M; Pop, Mihai; Phillippy, Adam M

2014-05-03

The continued democratization of DNA sequencing has sparked a new wave of development of genome assembly and assembly validation methods. As individual research labs, rather than centralized centers, begin to sequence the majority of new genomes, it is important to establish best practices for genome assembly. However, recent evaluations such as GAGE and the Assemblathon have concluded that there is no single best approach to genome assembly. Instead, it is preferable to generate multiple assemblies and validate them to determine which is most useful for the desired analysis; this is a labor-intensive process that is often impossible or unfeasible. To encourage best practices supported by the community, we present iMetAMOS, an automated ensemble assembly pipeline; iMetAMOS encapsulates the process of running, validating, and selecting a single assembly from multiple assemblies. iMetAMOS packages several leading open-source tools into a single binary that automates parameter selection and execution of multiple assemblers, scores the resulting assemblies based on multiple validation metrics, and annotates the assemblies for genes and contaminants. We demonstrate the utility of the ensemble process on 225 previously unassembled Mycobacterium tuberculosis genomes as well as a Rhodobacter sphaeroides benchmark dataset. On these real data, iMetAMOS reliably produces validated assemblies and identifies potential contamination without user intervention. In addition, intelligent parameter selection produces assemblies of R. sphaeroides comparable to or exceeding the quality of those from the GAGE-B evaluation, affecting the relative ranking of some assemblers. Ensemble assembly with iMetAMOS provides users with multiple, validated assemblies for each genome. Although computationally limited to small or mid-sized genomes, this approach is the most effective and reproducible means for generating high-quality assemblies and enables users to select an assembly best tailored to their specific needs.

Identification and characterization of DNAzymes targeting DNA methyltransferase I for suppressing bladder cancer proliferation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Xiangbo; Zhang, Lu; Ding, Nianhua

2015-05-29

Epigenetic inactivation of genes plays a critical role in many important human diseases, especially in cancer. A core mechanism for epigenetic inactivation of the genes is methylation of CpG islands in genome DNA, which is catalyzed by DNA methyltransferases (DNMTs). The inhibition of DNMTs may lead to demethylation and expression of the silenced tumor suppressor genes. Although DNMT inhibitors are currently being developed as potential anticancer agents, only limited success is achieved due to substantial toxicity. Here, we utilized a multiplex selection system to generate efficient RNA-cleaving DNAzymes targeting DNMT1. The lead molecule from the selection was shown to possessmore » efficient kinetic profiles and high efficiency in inhibiting the enzyme activity. Transfection of the DNAzyme caused significant down-regulation of DNMT1 expression and reactivation of p16 gene, resulting in reduced cell proliferation of bladder cancers. This study provides an alternative for targeting DNMTs for potential cancer therapy. - Highlights: • Identified DNMT1-targeted DNAzymes by multiplex selection system. • Biochemically characterized a lead DNAzyme with high kinetic efficiency. • Validated DNMT1-targeted DNAzyme in its enzymatic and cellular activities.« less

Respiration Traits as Novel Markers for Plant Robustness Under the Threat of Climate Change: A Protocol for Validation.

PubMed

Arnholdt-Schmitt, Birgit

2017-01-01

Respiration traits allow calculating temperature-dependent carbon use efficiency and prediction of growth rates. This protocol aims (1) to enable validation of respiration traits as non-DNA biomarkers for breeding on robust plants in support of sustainable and healthy plant production; (2) to provide an efficient, novel way to identify and predict functionality of DNA-based markers (genes, polymorphisms, edited genes, transgenes, genomes, and hologenomes), and (3) to directly help farmers select robust material appropriate for a specified region. The protocol is based on applying isothermal calorespirometry and consists of four steps: plant tissue preparation, calorespirometry measurements, data processing, and final validation through massive field-based data.The methodology can serve selection and improvement for a wide range of crops. Several of them are currently being tested in the author's lab. Among them are important cereals, such as wheat, barley, and rye, and diverse vegetables. However, it is critical that the protocol for measuring respiration traits be well adjusted to the plant species by considering deep knowledge on the specific physiology and functional cell biology behind the final target trait for production. Here, Daucus carota L. is chosen as an advanced example to demonstrate critical species-specific steps for protocol development. Carrot is an important global vegetable that is grown worldwide and in all climate regions (moderate, subtropical, and tropical). Recently, this species is also used in my lab as a model for studies on alternative oxidase (AOX) gene diversity and evolutionary dynamics in interaction with endophytes.

A Hybrid Computational Method for the Discovery of Novel Reproduction-Related Genes

PubMed Central

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

2015-01-01

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations. PMID:25768094

A hybrid computational method for the discovery of novel reproduction-related genes.

PubMed

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

2015-01-01

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

Androgen Receptor Gene Polymorphisms and Alterations in Prostate Cancer: Of Humanized Mice and Men

PubMed Central

Robins, Diane M.

2011-01-01

Germline polymorphisms and somatic mutations of the androgen receptor (AR) have been intensely investigated in prostate cancer but even with genomic approaches their impact remains controversial. To assess the functional significance of AR genetic variation, we converted the mouse gene to the human sequence by germline recombination and engineered alleles to query the role of a polymorphic glutamine (Q) tract implicated in cancer risk. In a prostate cancer model, AR Q tract length influences progression and castration response. Mutation profiling in mice provides direct evidence that somatic AR variants are selected by therapy, a finding validated in human metastases from distinct treatment groups. Mutant ARs exploit multiple mechanisms to resist hormone ablation, including alterations in ligand specificity, target gene selectivity, chaperone interaction and nuclear localization. Regardless of their frequency, these variants permute normal function to reveal novel means to target wild type AR and its key interacting partners. PMID:21689727

Whole-genome sequence analyses of Western Central African Pygmy hunter-gatherers reveal a complex demographic history and identify candidate genes under positive natural selection

PubMed Central

Hsieh, PingHsun; Veeramah, Krishna R.; Lachance, Joseph; Tishkoff, Sarah A.; Wall, Jeffrey D.; Hammer, Michael F.; Gutenkunst, Ryan N.

2016-01-01

African Pygmies practicing a mobile hunter-gatherer lifestyle are phenotypically and genetically diverged from other anatomically modern humans, and they likely experienced strong selective pressures due to their unique lifestyle in the Central African rainforest. To identify genomic targets of adaptation, we sequenced the genomes of four Biaka Pygmies from the Central African Republic and jointly analyzed these data with the genome sequences of three Baka Pygmies from Cameroon and nine Yoruba famers. To account for the complex demographic history of these populations that includes both isolation and gene flow, we fit models using the joint allele frequency spectrum and validated them using independent approaches. Our two best-fit models both suggest ancient divergence between the ancestors of the farmers and Pygmies, 90,000 or 150,000 yr ago. We also find that bidirectional asymmetric gene flow is statistically better supported than a single pulse of unidirectional gene flow from farmers to Pygmies, as previously suggested. We then applied complementary statistics to scan the genome for evidence of selective sweeps and polygenic selection. We found that conventional statistical outlier approaches were biased toward identifying candidates in regions of high mutation or low recombination rate. To avoid this bias, we assigned P-values for candidates using whole-genome simulations incorporating demography and variation in both recombination and mutation rates. We found that genes and gene sets involved in muscle development, bone synthesis, immunity, reproduction, cell signaling and development, and energy metabolism are likely to be targets of positive natural selection in Western African Pygmies or their recent ancestors. PMID:26888263

Genome-wide scan for selection signatures in six cattle breeds in South Africa.

PubMed

Makina, Sithembile O; Muchadeyi, Farai C; van Marle-Köster, Este; Taylor, Jerry F; Makgahlela, Mahlako L; Maiwashe, Azwihangwisi

2015-11-26

The detection of selection signatures in breeds of livestock species can contribute to the identification of regions of the genome that are, or have been, functionally important and, as a consequence, have been targeted by selection. This study used two approaches to detect signatures of selection within and between six cattle breeds in South Africa, including Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), Bonsmara (n = 44), Angus (n = 31) and Holstein (n = 29). The first approach was based on the detection of genomic regions in which haplotypes have been driven towards complete fixation within breeds. The second approach identified regions of the genome that had very different allele frequencies between populations (F ST). Forty-seven candidate genomic regions were identified as harbouring putative signatures of selection using both methods. Twelve of these candidate selected regions were shared among the breeds and ten were validated by previous studies. Thirty-three of these regions were successfully annotated and candidate genes were identified. Among these genes the keratin genes (KRT222, KRT24, KRT25, KRT26, and KRT27) and one heat shock protein gene (HSPB9) on chromosome 19 between 42,896,570 and 42,897,840 bp were detected for the Nguni breed. These genes were previously associated with adaptation to tropical environments in Zebu cattle. In addition, a number of candidate genes associated with the nervous system (WNT5B, FMOD, PRELP, and ATP2B), immune response (CYM, CDC6, and CDK10), production (MTPN, IGFBP4, TGFB1, and AJAP1) and reproductive performance (ADIPOR2, OVOS2, and RBBP8) were also detected as being under selection. The results presented here provide a foundation for detecting mutations that underlie genetic variation of traits that have economic importance for cattle breeds in South Africa.

An integrated approach for identifying wrongly labelled samples when performing classification in microarray data.

PubMed

Leung, Yuk Yee; Chang, Chun Qi; Hung, Yeung Sam

2012-01-01

Using hybrid approach for gene selection and classification is common as results obtained are generally better than performing the two tasks independently. Yet, for some microarray datasets, both classification accuracy and stability of gene sets obtained still have rooms for improvement. This may be due to the presence of samples with wrong class labels (i.e. outliers). Outlier detection algorithms proposed so far are either not suitable for microarray data, or only solve the outlier detection problem on their own. We tackle the outlier detection problem based on a previously proposed Multiple-Filter-Multiple-Wrapper (MFMW) model, which was demonstrated to yield promising results when compared to other hybrid approaches (Leung and Hung, 2010). To incorporate outlier detection and overcome limitations of the existing MFMW model, three new features are introduced in our proposed MFMW-outlier approach: 1) an unbiased external Leave-One-Out Cross-Validation framework is developed to replace internal cross-validation in the previous MFMW model; 2) wrongly labeled samples are identified within the MFMW-outlier model; and 3) a stable set of genes is selected using an L1-norm SVM that removes any redundant genes present. Six binary-class microarray datasets were tested. Comparing with outlier detection studies on the same datasets, MFMW-outlier could detect all the outliers found in the original paper (for which the data was provided for analysis), and the genes selected after outlier removal were proven to have biological relevance. We also compared MFMW-outlier with PRAPIV (Zhang et al., 2006) based on same synthetic datasets. MFMW-outlier gave better average precision and recall values on three different settings. Lastly, artificially flipped microarray datasets were created by removing our detected outliers and flipping some of the remaining samples' labels. Almost all the 'wrong' (artificially flipped) samples were detected, suggesting that MFMW-outlier was sufficiently powerful to detect outliers in high-dimensional microarray datasets.

Selection of reference genes for gene expression studies in virus-infected monocots using quantitative real-time PCR.

PubMed

Zhang, Kun; Niu, Shaofang; Di, Dianping; Shi, Lindan; Liu, Deshui; Cao, Xiuling; Miao, Hongqin; Wang, Xianbing; Han, Chenggui; Yu, Jialin; Li, Dawei; Zhang, Yongliang

2013-10-10

Both genome-wide transcriptomic surveys of the mRNA expression profiles and virus-induced gene silencing-based molecular studies of target gene during virus-plant interaction involve the precise estimation of the transcript abundance. Quantitative real-time PCR (qPCR) is the most widely adopted technique for mRNA quantification. In order to obtain reliable quantification of transcripts, identification of the best reference genes forms the basis of the preliminary work. Nevertheless, the stability of internal controls in virus-infected monocots needs to be fully explored. In this work, the suitability of ten housekeeping genes (ACT, EF1α, FBOX, GAPDH, GTPB, PP2A, SAND, TUBβ, UBC18 and UK) for potential use as reference genes in qPCR were investigated in five different monocot plants (Brachypodium, barley, sorghum, wheat and maize) under infection with different viruses including Barley stripe mosaic virus (BSMV), Brome mosaic virus (BMV), Rice black-streaked dwarf virus (RBSDV) and Sugarcane mosaic virus (SCMV). By using three different algorithms, the most appropriate reference genes or their combinations were identified for different experimental sets and their effectiveness for the normalisation of expression studies were further validated by quantitative analysis of a well-studied PR-1 gene. These results facilitate the selection of desirable reference genes for more accurate gene expression studies in virus-infected monocots. Copyright © 2013 Elsevier B.V. All rights reserved.

Enteropeptidase: A Gene Associated with a Starvation Human Phenotype and a Novel Target for Obesity Treatment

PubMed Central

Braud, Sandrine; Ciufolini, Marco A.; Harosh, Itzik

2012-01-01

Background Obesity research focuses essentially on gene targets associated with the obese phenotype. None of these targets have yet provided a viable drug therapy. Focusing instead on genes that are involved in energy absorption and that are associated with a “human starvation phenotype”, we have identified enteropeptidase (EP), a gene associated with congenital enteropeptidase deficiency, as a novel target for obesity treatment. The advantages of this target are that the gene is expressed exclusively in the brush border of the intestine; it is peripheral and not redundant. Methodology/Principal Findings Potent and selective EP inhibitors were designed around a boroarginine or borolysine motif. Oral administration of these compounds to mice restricted the bioavailability of dietary energy, and in a long-term treatment it significantly diminished the rate of increase in body weight, despite ad libitum food intake. No adverse reactions of the type seen with lipase inhibitors, such as diarrhea or steatorrhea, were observed. This validates EP as a novel, druggable target for obesity treatment. Conclusions In vivo testing of novel boroarginine or borolysine-based EP inhibitors validates a novel approach to the treatment of obesity. PMID:23185382

Expression profiling in canine osteosarcoma: identification of biomarkers and pathways associated with outcome

PubMed Central

2010-01-01

Background Osteosarcoma (OSA) spontaneously arises in the appendicular skeleton of large breed dogs and shares many physiological and molecular biological characteristics with human OSA. The standard treatment for OSA in both species is amputation or limb-sparing surgery, followed by chemotherapy. Unfortunately, OSA is an aggressive cancer with a high metastatic rate. Characterization of OSA with regard to its metastatic potential and chemotherapeutic resistance will improve both prognostic capabilities and treatment modalities. Methods We analyzed archived primary OSA tissue from dogs treated with limb amputation followed by doxorubicin or platinum-based drug chemotherapy. Samples were selected from two groups: dogs with disease free intervals (DFI) of less than 100 days (n = 8) and greater than 300 days (n = 7). Gene expression was assessed with Affymetrix Canine 2.0 microarrays and analyzed with a two-tailed t-test. A subset of genes was confirmed using qRT-PCR and used in classification analysis to predict prognosis. Systems-based gene ontology analysis was conducted on genes selected using a standard J5 metric. The genes identified using this approach were converted to their human homologues and assigned to functional pathways using the GeneGo MetaCore platform. Results Potential biomarkers were identified using gene expression microarray analysis and 11 differentially expressed (p < 0.05) genes were validated with qRT-PCR (n = 10/group). Statistical classification models using the qRT-PCR profiles predicted patient outcomes with 100% accuracy in the training set and up to 90% accuracy upon stratified cross validation. Pathway analysis revealed alterations in pathways associated with oxidative phosphorylation, hedgehog and parathyroid hormone signaling, cAMP/Protein Kinase A (PKA) signaling, immune responses, cytoskeletal remodeling and focal adhesion. Conclusions This profiling study has identified potential new biomarkers to predict patient outcome in OSA and new pathways that may be targeted for therapeutic intervention. PMID:20860831

Pharmacological Validation of Candidate Causal Sleep Genes Identified in an N2 Cross

PubMed Central

Brunner, Joseph I.; Gotter, Anthony L.; Millstein, Joshua; Garson, Susan; Binns, Jacquelyn; Fox, Steven V.; Savitz, Alan T.; Yang, He S.; Fitzpatrick, Karrie; Zhou, Lili; Owens, Joseph R.; Webber, Andrea L.; Vitaterna, Martha H.; Kasarskis, Andrew; Uebele, Victor N.; Turek, Fred; Renger, John J.; Winrow, Christopher J.

2013-01-01

Despite the substantial impact of sleep disturbances on human health and the many years of study dedicated to understanding sleep pathologies, the underlying genetic mechanisms that govern sleep and wake largely remain unknown. Recently, we completed large scale genetic and gene expression analyses in a segregating inbred mouse cross and identified candidate causal genes that regulate the mammalian sleep-wake cycle, across multiple traits including total sleep time, amounts of REM, non-REM, sleep bout duration and sleep fragmentation. Here we describe a novel approach toward validating candidate causal genes, while also identifying potential targets for sleep-related indications. Select small molecule antagonists and agonists were used to interrogate candidate causal gene function in rodent sleep polysomnography assays to determine impact on overall sleep architecture and to evaluate alignment with associated sleep-wake traits. Significant effects on sleep architecture were observed in validation studies using compounds targeting the muscarinic acetylcholine receptor M3 subunit (Chrm3)(wake promotion), nicotinic acetylcholine receptor alpha4 subunit (Chrna4)(wake promotion), dopamine receptor D5 subunit (Drd5)(sleep induction), serotonin 1D receptor (Htr1d)(altered REM fragmentation), glucagon-like peptide-1 receptor (Glp1r)(light sleep promotion and reduction of deep sleep), and Calcium channel, voltage-dependent, T type, alpha 1I subunit (Cacna1i)(increased bout duration slow wave sleep). Taken together, these results show the complexity of genetic components that regulate sleep-wake traits and highlight the importance of evaluating this complex behavior at a systems level. Pharmacological validation of genetically identified putative targets provides a rapid alternative to generating knock out or transgenic animal models, and may ultimately lead towards new therapeutic opportunities. PMID:22091728

In vitro validation of self designed "universal human Influenza A siRNA".

PubMed

Jain, Bhawana; Jain, Amita; Prakash, Om; Singh, Ajay Kr; Dangi, Tanushree; Singh, Mastan; Singh, K P

2015-08-01

The genomic variability of Influenza A virus (IAV) makes it difficult for the existing vaccines or anti-influenza drugs to control. The siRNA targeting viral gene induces RNAi mechanism in the host and silent the gene by cleaving mRNA. In this study, we developed an universal siRNA and validated its efficiency in vitro. The siRNA was designed rationally, targeting the most conserved region (delineated with the help of multiple sequence alignment) of M gene of IAV strains. Three level screening method was adopted, and the most efficient one was selected on the basis of its unique position in the conserved region. The siRNA efficacy was confirmed in vitro with the Madin Darby Canine Kidney (MDCK) cell line for IAV propagation using two clinical isolates i.e., Influenza A/H3N2 and Influenza A/pdmH1N1. Of the total 168 strains worldwide and 33 strains from India, 97 bp long (position 137-233) conserved region was identified. The longest ORF of matrix gene was targeted by the selected siRNA, which showed 73.6% inhibition in replication of Influenza A/pdmH1N1 and 62.1% inhibition in replication of Influenza A/H3N2 at 48 h post infection on MDCK cell line. This study provides a basis for the development of siRNA which can be used as universal anti-IAV therapeutic agent.

Clinical application of 2.7M Cytogenetics array for CNV detection in subjects with idiopathic autism and/or intellectual disability.

PubMed

Qiao, Y; Tyson, C; Hrynchak, M; Lopez-Rangel, E; Hildebrand, J; Martell, S; Fawcett, C; Kasmara, L; Calli, K; Harvard, C; Liu, X; Holden, J J A; Lewis, S M E; Rajcan-Separovic, E

2013-02-01

Higher resolution whole-genome arrays facilitate the identification of smaller copy number variations (CNVs) and their integral genes contributing to autism and/or intellectual disability (ASD/ID). Our study describes the use of one of the highest resolution arrays, the Affymetrix(®) Cytogenetics 2.7M array, coupled with quantitative multiplex polymerase chain reaction (PCR) of short fluorescent fragments (QMPSF) for detection and validation of small CNVs. We studied 82 subjects with ASD and ID in total (30 in the validation and 52 in the application cohort) and detected putatively pathogenic CNVs in 6/52 cases from the application cohort. This included a 130-kb maternal duplication spanning exons 64-79 of the DMD gene which was found in a 3-year-old boy manifesting autism and mild neuromotor delays. Other pathogenic CNVs involved 4p14, 12q24.31, 14q32.31, 15q13.2-13.3, and 17p13.3. We established the optimal experimental conditions which, when applied to select small CNVs for QMPSF confirmation, reduced the false positive rate from 60% to 25%. Our work suggests that selection of small CNVs based on the function of integral genes, followed by review of array experimental parameters resulting in highest confirmation rate using multiplex PCR, may enhance the usefulness of higher resolution platforms for ASD and ID gene discovery. © 2012 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.

Identification and validation of reference genes for quantification of target gene expression with quantitative real-time PCR for tall fescue under four abiotic stresses.

PubMed

Yang, Zhimin; Chen, Yu; Hu, Baoyun; Tan, Zhiqun; Huang, Bingru

2015-01-01

Tall fescue (Festuca arundinacea Schreb.) is widely utilized as a major forage and turfgrass species in the temperate regions of the world and is a valuable plant material for studying molecular mechanisms of grass stress tolerance due to its superior drought and heat tolerance among cool-season species. Selection of suitable reference genes for quantification of target gene expression is important for the discovery of molecular mechanisms underlying improved growth traits and stress tolerance. The stability of nine potential reference genes (ACT, TUB, EF1a, GAPDH, SAND, CACS, F-box, PEPKR1 and TIP41) was evaluated using four programs, GeNorm, NormFinder, BestKeeper, and RefFinder. The combinations of SAND and TUB or TIP41 and TUB were most stably expressed in salt-treated roots or leaves. The combinations of GAPDH with TIP41 or TUB were stable in roots and leaves under drought stress. TIP41 and PEPKR1 exhibited stable expression in cold-treated roots, and the combination of F-box, TIP41 and TUB was also stable in cold-treated leaves. CACS and TUB were the two most stable reference genes in heat-stressed roots. TIP41 combined with TUB and ACT was stably expressed in heat-stressed leaves. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) assays of the target gene FaWRKY1 using the identified most stable reference genes confirmed the reliability of selected reference genes. The selection of suitable reference genes in tall fescue will allow for more accurate identification of stress-tolerance genes and molecular mechanisms conferring stress tolerance in this stress-tolerant species.

Validation of candidate gene markers for marker-assisted selection of potato cultivars with improved tuber quality.

PubMed

Li, Li; Tacke, Eckhard; Hofferbert, Hans-Reinhardt; Lübeck, Jens; Strahwald, Josef; Draffehn, Astrid M; Walkemeier, Birgit; Gebhardt, Christiane

2013-04-01

Tuber yield, starch content, starch yield and chip color are complex traits that are important for industrial uses and food processing of potato. Chip color depends on the quantity of reducing sugars glucose and fructose in the tubers, which are generated by starch degradation. Reducing sugars accumulate when tubers are stored at low temperatures. Early and efficient selection of cultivars with superior yield, starch yield and chip color is hampered by the fact that reliable phenotypic selection requires multiple year and location trials. Application of DNA-based markers early in the breeding cycle, which are diagnostic for superior alleles of genes that control natural variation of tuber quality, will reduce the number of clones to be evaluated in field trials. Association mapping using genes functional in carbohydrate metabolism as markers has discovered alleles of invertases and starch phosphorylases that are associated with tuber quality traits. Here, we report on new DNA variants at loci encoding ADP-glucose pyrophosphorylase and the invertase Pain-1, which are associated with positive or negative effect with chip color, tuber starch content and starch yield. Marker-assisted selection (MAS) and marker validation were performed in tetraploid breeding populations, using various combinations of 11 allele-specific markers associated with tuber quality traits. To facilitate MAS, user-friendly PCR assays were developed for specific candidate gene alleles. In a multi-parental population of advanced breeding clones, genotypes were selected for having different combinations of five positive and the corresponding negative marker alleles. Genotypes combining five positive marker alleles performed on average better than genotypes with four negative alleles and one positive allele. When tested individually, seven of eight markers showed an effect on at least one quality trait. The direction of effect was as expected. Combinations of two to three marker alleles were identified that significantly improved average chip quality after cold storage and tuber starch content. In F1 progeny of a single-cross combination, MAS with six markers did not give the expected result. Reasons and implications for MAS in potato are discussed.

Using RNA-seq data to select reference genes for normalizing gene expression in apple roots.

PubMed

Zhou, Zhe; Cong, Peihua; Tian, Yi; Zhu, Yanmin

2017-01-01

Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for their potential use as reliable reference genes. These genes were selected based on their low variance of gene expression in apple root tissues from a recent RNA-seq data set, and a few previously reported apple reference genes for other tissue types. Four methods, Delta Ct, geNorm, NormFinder and BestKeeper, were used to evaluate their stability in apple root tissues of various genotypes and under different experimental conditions. A small panel of stably expressed genes, MDP0000095375, MDP0000147424, MDP0000233640, MDP0000326399 and MDP0000173025 were recommended for normalizing quantitative gene expression data in apple roots under various abiotic or biotic stresses. When the most stable and least stable reference genes were used for data normalization, significant differences were observed on the expression patterns of two target genes, MdLecRLK5 (MDP0000228426, a gene encoding a lectin receptor like kinase) and MdMAPK3 (MDP0000187103, a gene encoding a mitogen-activated protein kinase). Our data also indicated that for those carefully validated reference genes, a single reference gene is sufficient for reliable normalization of the quantitative gene expression. Depending on the experimental conditions, the most suitable reference genes can be specific to the sample of interest for more reliable RT-qPCR data normalization.

Using RNA-seq data to select reference genes for normalizing gene expression in apple roots

PubMed Central

Zhou, Zhe; Cong, Peihua; Tian, Yi

2017-01-01

Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for their potential use as reliable reference genes. These genes were selected based on their low variance of gene expression in apple root tissues from a recent RNA-seq data set, and a few previously reported apple reference genes for other tissue types. Four methods, Delta Ct, geNorm, NormFinder and BestKeeper, were used to evaluate their stability in apple root tissues of various genotypes and under different experimental conditions. A small panel of stably expressed genes, MDP0000095375, MDP0000147424, MDP0000233640, MDP0000326399 and MDP0000173025 were recommended for normalizing quantitative gene expression data in apple roots under various abiotic or biotic stresses. When the most stable and least stable reference genes were used for data normalization, significant differences were observed on the expression patterns of two target genes, MdLecRLK5 (MDP0000228426, a gene encoding a lectin receptor like kinase) and MdMAPK3 (MDP0000187103, a gene encoding a mitogen-activated protein kinase). Our data also indicated that for those carefully validated reference genes, a single reference gene is sufficient for reliable normalization of the quantitative gene expression. Depending on the experimental conditions, the most suitable reference genes can be specific to the sample of interest for more reliable RT-qPCR data normalization. PMID:28934340

Genome-wide identification of suitable zebrafish Danio rerio reference genes for normalization of gene expression data by RT-qPCR.

PubMed

Xu, H; Li, C; Zeng, Q; Agrawal, I; Zhu, X; Gong, Z

2016-06-01

In this study, to systematically identify the most stably expressed genes for internal reference in zebrafish Danio rerio investigations, 37 D. rerio transcriptomic datasets (both RNA sequencing and microarray data) were collected from gene expression omnibus (GEO) database and unpublished data, and gene expression variations were analysed under three experimental conditions: tissue types, developmental stages and chemical treatments. Forty-four putative candidate genes were identified with the c.v. <0·2 from all datasets. Following clustering into different functional groups, 21 genes, in addition to four conventional housekeeping genes (eef1a1l1, b2m, hrpt1l and actb1), were selected from different functional groups for further quantitative real-time (qrt-)PCR validation using 25 RNA samples from different adult tissues, developmental stages and chemical treatments. The qrt-PCR data were then analysed using the statistical algorithm refFinder for gene expression stability. Several new candidate genes showed better expression stability than the conventional housekeeping genes in all three categories. It was found that sep15 and metap1 were the top two stable genes for tissue types, ube2a and tmem50a the top two for different developmental stages, and rpl13a and rp1p0 the top two for chemical treatments. Thus, based on the extensive transcriptomic analyses and qrt-PCR validation, these new reference genes are recommended for normalization of D. rerio qrt-PCR data respectively for the three different experimental conditions. © 2016 The Fisheries Society of the British Isles.

In Silico Gene Prioritization by Integrating Multiple Data Sources

PubMed Central

Zhou, Yingyao; Shields, Robert; Chanda, Sumit K.; Elston, Robert C.; Li, Jing

2011-01-01

Identifying disease genes is crucial to the understanding of disease pathogenesis, and to the improvement of disease diagnosis and treatment. In recent years, many researchers have proposed approaches to prioritize candidate genes by considering the relationship of candidate genes and existing known disease genes, reflected in other data sources. In this paper, we propose an expandable framework for gene prioritization that can integrate multiple heterogeneous data sources by taking advantage of a unified graphic representation. Gene-gene relationships and gene-disease relationships are then defined based on the overall topology of each network using a diffusion kernel measure. These relationship measures are in turn normalized to derive an overall measure across all networks, which is utilized to rank all candidate genes. Based on the informativeness of available data sources with respect to each specific disease, we also propose an adaptive threshold score to select a small subset of candidate genes for further validation studies. We performed large scale cross-validation analysis on 110 disease families using three data sources. Results have shown that our approach consistently outperforms other two state of the art programs. A case study using Parkinson disease (PD) has identified four candidate genes (UBB, SEPT5, GPR37 and TH) that ranked higher than our adaptive threshold, all of which are involved in the PD pathway. In particular, a very recent study has observed a deletion of TH in a patient with PD, which supports the importance of the TH gene in PD pathogenesis. A web tool has been implemented to assist scientists in their genetic studies. PMID:21731658

Identification of reference genes for RT-qPCR analysis in peach genotypes with contrasting chilling requirements.

PubMed

Marini, N; Bevilacqua, C B; Büttow, M V; Raseira, M C B; Bonow, S

2017-05-25

Selecting and validating reference genes are the first steps in studying gene expression by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR). The present study aimed to evaluate the stability of five reference genes for the purpose of normalization when studying gene expression in various cultivars of Prunus persica with different chilling requirements. Flower bud tissues of nine peach genotypes from Embrapa's peach breeding program with different chilling requirements were used, and five candidate reference genes based on the RT-qPCR that were useful for studying the relative quantitative gene expression and stability were evaluated using geNorm, NormFinder, and bestKeeper software packages. The results indicated that among the genes tested, the most stable genes to be used as reference genes are Act and UBQ10. This study is the first survey of the stability of reference genes in peaches under chilling stress and provides guidelines for more accurate RT-qPCR results.

Decoy receptor 1 (DCR1) promoter hypermethylation and response to irinotecan in metastatic colorectal cancer

PubMed Central

Bosch, Linda J.W.; Coupé, Veerle M.H.; Mongera, Sandra; Haan, Josien C.; Richman, Susan D.; Koopman, Miriam; Tol, Jolien; de Meyer, Tim; Louwagie, Joost; Dehaspe, Luc; van Grieken, Nicole C.T.; Ylstra, Bauke; Verheul, Henk M.W.; van Engeland, Manon; Nagtegaal, Iris D.; Herman, James G.; Quirke, Philip; Seymour, Matthew T.; Punt, Cornelis J.A.; van Criekinge, Wim; Carvalho, Beatriz; Meijer, Gerrit A.

2017-01-01

Diversity in colorectal cancer biology is associated with variable responses to standard chemotherapy. We aimed to identify and validate DNA hypermethylated genes as predictive biomarkers for irinotecan treatment of metastatic CRC patients. Candidate genes were selected from 389 genes involved in DNA Damage Repair by correlation analyses between gene methylation status and drug response in 32 cell lines. A large series of samples (n=818) from two phase III clinical trials was used to evaluate these candidate genes by correlating methylation status to progression-free survival after treatment with first-line single-agent fluorouracil (Capecitabine or 5-fluorouracil) or combination chemotherapy (Capecitabine or 5-fluorouracil plus irinotecan (CAPIRI/FOLFIRI)). In the discovery (n=185) and initial validation set (n=166), patients with methylated Decoy Receptor 1 (DCR1) did not benefit from CAPIRI over Capecitabine treatment (discovery set: HR=1.2 (95%CI 0.7-1.9, p=0.6), validation set: HR=0.9 (95%CI 0.6-1.4, p=0.5)), whereas patients with unmethylated DCR1 did (discovery set: HR=0.4 (95%CI 0.3-0.6, p=0.00001), validation set: HR=0.5 (95%CI 0.3-0.7, p=0.0008)). These results could not be replicated in the external data set (n=467), where a similar effect size was found in patients with methylated and unmethylated DCR1 for FOLFIRI over 5FU treatment (methylated DCR1: HR=0.7 (95%CI 0.5-0.9, p=0.01), unmethylated DCR1: HR=0.8 (95%CI 0.6-1.2, p=0.4)). In conclusion, DCR1 promoter hypermethylation status is a potential predictive biomarker for response to treatment with irinotecan, when combined with capecitabine. This finding could not be replicated in an external validation set, in which irinotecan was combined with 5FU. These results underline the challenge and importance of extensive clinical evaluation of candidate biomarkers in multiple trials. PMID:28968978

Decoy receptor 1 (DCR1) promoter hypermethylation and response to irinotecan in metastatic colorectal cancer.

PubMed

Bosch, Linda J W; Trooskens, Geert; Snaebjornsson, Petur; Coupé, Veerle M H; Mongera, Sandra; Haan, Josien C; Richman, Susan D; Koopman, Miriam; Tol, Jolien; de Meyer, Tim; Louwagie, Joost; Dehaspe, Luc; van Grieken, Nicole C T; Ylstra, Bauke; Verheul, Henk M W; van Engeland, Manon; Nagtegaal, Iris D; Herman, James G; Quirke, Philip; Seymour, Matthew T; Punt, Cornelis J A; van Criekinge, Wim; Carvalho, Beatriz; Meijer, Gerrit A

2017-09-08

Diversity in colorectal cancer biology is associated with variable responses to standard chemotherapy. We aimed to identify and validate DNA hypermethylated genes as predictive biomarkers for irinotecan treatment of metastatic CRC patients. Candidate genes were selected from 389 genes involved in DNA Damage Repair by correlation analyses between gene methylation status and drug response in 32 cell lines. A large series of samples (n=818) from two phase III clinical trials was used to evaluate these candidate genes by correlating methylation status to progression-free survival after treatment with first-line single-agent fluorouracil (Capecitabine or 5-fluorouracil) or combination chemotherapy (Capecitabine or 5-fluorouracil plus irinotecan (CAPIRI/FOLFIRI)). In the discovery (n=185) and initial validation set (n=166), patients with methylated Decoy Receptor 1 ( DCR1) did not benefit from CAPIRI over Capecitabine treatment (discovery set: HR=1.2 (95%CI 0.7-1.9, p =0.6), validation set: HR=0.9 (95%CI 0.6-1.4, p =0.5)), whereas patients with unmethylated DCR1 did (discovery set: HR=0.4 (95%CI 0.3-0.6, p =0.00001), validation set: HR=0.5 (95%CI 0.3-0.7, p =0.0008)). These results could not be replicated in the external data set (n=467), where a similar effect size was found in patients with methylated and unmethylated DCR1 for FOLFIRI over 5FU treatment (methylated DCR1 : HR=0.7 (95%CI 0.5-0.9, p =0.01), unmethylated DCR1 : HR=0.8 (95%CI 0.6-1.2, p =0.4)). In conclusion, DCR1 promoter hypermethylation status is a potential predictive biomarker for response to treatment with irinotecan, when combined with capecitabine. This finding could not be replicated in an external validation set, in which irinotecan was combined with 5FU. These results underline the challenge and importance of extensive clinical evaluation of candidate biomarkers in multiple trials.

Identification and validation of reference genes for quantitative real-time PCR normalization and its applications in lycium.

PubMed

Zeng, Shaohua; Liu, Yongliang; Wu, Min; Liu, Xiaomin; Shen, Xiaofei; Liu, Chunzhao; Wang, Ying

2014-01-01

Lycium barbarum and L. ruthenicum are extensively used as traditional Chinese medicinal plants. Next generation sequencing technology provides a powerful tool for analyzing transcriptomic profiles of gene expression in non-model species. Such gene expression can then be confirmed with quantitative real-time polymerase chain reaction (qRT-PCR). Therefore, use of systematically identified suitable reference genes is a prerequisite for obtaining reliable gene expression data. Here, we calculated the expression stability of 18 candidate reference genes across samples from different tissues and grown under salt stress using geNorm and NormFinder procedures. The geNorm-determined rank of reference genes was similar to those defined by NormFinder with some differences. Both procedures confirmed that the single most stable reference gene was ACNTIN1 for L. barbarum fruits, H2B1 for L. barbarum roots, and EF1α for L. ruthenicum fruits. PGK3, H2B2, and PGK3 were identified as the best stable reference genes for salt-treated L. ruthenicum leaves, roots, and stems, respectively. H2B1 and GAPDH1+PGK1 for L. ruthenicum and SAMDC2+H2B1 for L. barbarum were the best single and/or combined reference genes across all samples. Finally, expression of salt-responsive gene NAC, fruit ripening candidate gene LrPG, and anthocyanin genes were investigated to confirm the validity of the selected reference genes. Suitable reference genes identified in this study provide a foundation for accurately assessing gene expression and further better understanding of novel gene function to elucidate molecular mechanisms behind particular biological/physiological processes in Lycium.

Selection Shapes Transcriptional Logic and Regulatory Specialization in Genetic Networks

PubMed Central

Fogelmark, Karl; Peterson, Carsten; Troein, Carl

2016-01-01

Background Living organisms need to regulate their gene expression in response to environmental signals and internal cues. This is a computational task where genes act as logic gates that connect to form transcriptional networks, which are shaped at all scales by evolution. Large-scale mutations such as gene duplications and deletions add and remove network components, whereas smaller mutations alter the connections between them. Selection determines what mutations are accepted, but its importance for shaping the resulting networks has been debated. Methodology To investigate the effects of selection in the shaping of transcriptional networks, we derive transcriptional logic from a combinatorially powerful yet tractable model of the binding between DNA and transcription factors. By evolving the resulting networks based on their ability to function as either a simple decision system or a circadian clock, we obtain information on the regulation and logic rules encoded in functional transcriptional networks. Comparisons are made between networks evolved for different functions, as well as with structurally equivalent but non-functional (neutrally evolved) networks, and predictions are validated against the transcriptional network of E. coli. Principal Findings We find that the logic rules governing gene expression depend on the function performed by the network. Unlike the decision systems, the circadian clocks show strong cooperative binding and negative regulation, which achieves tight temporal control of gene expression. Furthermore, we find that transcription factors act preferentially as either activators or repressors, both when binding multiple sites for a single target gene and globally in the transcriptional networks. This separation into positive and negative regulators requires gene duplications, which highlights the interplay between mutation and selection in shaping the transcriptional networks. PMID:26927540

Biologic determinants of tumor recurrence in stage II colon cancer: validation study of the 12-gene recurrence score in cancer and leukemia group B (CALGB) 9581.

PubMed

Venook, Alan P; Niedzwiecki, Donna; Lopatin, Margarita; Ye, Xing; Lee, Mark; Friedman, Paula N; Frankel, Wendy; Clark-Langone, Kim; Millward, Carl; Shak, Steven; Goldberg, Richard M; Mahmoud, Najjia N; Warren, Robert S; Schilsky, Richard L; Bertagnolli, Monica M

2013-05-10

A greater understanding of the biology of tumor recurrence should improve adjuvant treatment decision making. We conducted a validation study of the 12-gene recurrence score (RS), a quantitative assay integrating stromal response and cell cycle gene expression, in tumor specimens from patients enrolled onto Cancer and Leukemia Group B (CALGB) 9581. CALGB 9581 randomly assigned 1,713 patients with stage II colon cancer to treatment with edrecolomab or observation and found no survival difference. The analysis reported here included all patients with available tissue and recurrence (n = 162) and a random (approximately 1:3) selection of nonrecurring patients. RS was assessed in 690 formalin-fixed paraffin-embedded tumor samples with quantitative reverse transcriptase polymerase chain reaction by using prespecified genes and a previously validated algorithm. Association of RS and recurrence was analyzed by weighted Cox proportional hazards regression. Continuous RS was significantly associated with risk of recurrence (P = .013) as was mismatch repair (MMR) gene deficiency (P = .044). In multivariate analyses, RS was the strongest predictor of recurrence (P = .004), independent of T stage, MMR, number of nodes examined, grade, and lymphovascular invasion. In T3 MMR-intact (MMR-I) patients, prespecified low and high RS groups had average 5-year recurrence risks of 13% (95% CI, 10% to 16%) and 21% (95% CI, 16% to 26%), respectively. The 12-gene RS predicts recurrence in stage II colon cancer in CALGB 9581. This is consistent with the importance of stromal response and cell cycle gene expression in colon tumor recurrence. RS appears to be most discerning for patients with T3 MMR-I tumors, although markers such as grade and lymphovascular invasion did not add value in this subset of patients.

Transcriptome analysis of the plateau fish (Triplophysa dalaica): Implications for adaptation to hypoxia in fishes.

PubMed

Wang, Ying; Yang, Liandong; Wu, Bo; Song, Zhaobin; He, Shunping

2015-07-10

Triplophysa dalaica, endemic species of Qinghai-Tibetan Plateau, is informative for understanding the genetic basis of adaptation to hypoxic conditions of high altitude habitats. Here, a comprehensive gene repertoire for this plateau fish was generated using the Illumina deep paired-end high-throughput sequencing technology. De novo assembly yielded 145, 256 unigenes with an average length of 1632 bp. Blast searches against GenBank non-redundant database annotated 74,594 (51.4%) unigenes encoding for 30,047 gene descriptions in T. dalaica. Functional annotation and classification of assembled sequences were performed using Gene Ontology (GO), clusters of euKaryotic Orthologous Groups (KOG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. After comparison with other fish transcriptomes, including silver carp (Hypophthalmichthys molitrix) and mud loach (Misgurnus anguillicaudatus), 2621 high-quality orthologous gene alignments were constructed among these species. 61 (2.3%) of the genes were identified as having undergone positive selection in the T. dalaica lineage. Within the positively selected genes, 13 genes were involved in hypoxia response, of which 11 were listed in HypoxiaDB. Furthermore, duplicated hif-α (hif-1αA/B and hif-2αA/B), EGLN1 and PPARA candidate genes involved in adaptation to hypoxia were identified in T. dalaica transcriptome. Branch-site model in PAML validated that hif-1αB and hif-2αA genes have undergone positive selection in T.dalaica. Finally, 37,501 simple sequence repeats (SSRs) and 19,497 high-quality single nucleotide polymorphisms (SNPs) were identified in T. dalaica. The identified SSR and SNP markers will facilitate the genetic structure, population geography and ecological studies of Triplophysa fishes. Copyright © 2015 Elsevier B.V. All rights reserved.

Evolutionary Approach for Relative Gene Expression Algorithms

PubMed Central

Czajkowski, Marcin

2014-01-01

A Relative Expression Analysis (RXA) uses ordering relationships in a small collection of genes and is successfully applied to classiffication using microarray data. As checking all possible subsets of genes is computationally infeasible, the RXA algorithms require feature selection and multiple restrictive assumptions. Our main contribution is a specialized evolutionary algorithm (EA) for top-scoring pairs called EvoTSP which allows finding more advanced gene relations. We managed to unify the major variants of relative expression algorithms through EA and introduce weights to the top-scoring pairs. Experimental validation of EvoTSP on public available microarray datasets showed that the proposed solution significantly outperforms in terms of accuracy other relative expression algorithms and allows exploring much larger solution space. PMID:24790574

Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae

PubMed Central

Teste, Marie-Ange; Duquenne, Manon; François, Jean M; Parrou, Jean-Luc

2009-01-01

Background Real-time RT-PCR is the recommended method for quantitative gene expression analysis. A compulsory step is the selection of good reference genes for normalization. A few genes often referred to as HouseKeeping Genes (HSK), such as ACT1, RDN18 or PDA1 are among the most commonly used, as their expression is assumed to remain unchanged over a wide range of conditions. Since this assumption is very unlikely, a geometric averaging of multiple, carefully selected internal control genes is now strongly recommended for normalization to avoid this problem of expression variation of single reference genes. The aim of this work was to search for a set of reference genes for reliable gene expression analysis in Saccharomyces cerevisiae. Results From public microarray datasets, we selected potential reference genes whose expression remained apparently invariable during long-term growth on glucose. Using the algorithm geNorm, ALG9, TAF10, TFC1 and UBC6 turned out to be genes whose expression remained stable, independent of the growth conditions and the strain backgrounds tested in this study. We then showed that the geometric averaging of any subset of three genes among the six most stable genes resulted in very similar normalized data, which contrasted with inconsistent results among various biological samples when the normalization was performed with ACT1. Normalization with multiple selected genes was therefore applied to transcriptional analysis of genes involved in glycogen metabolism. We determined an induction ratio of 100-fold for GPH1 and 20-fold for GSY2 between the exponential phase and the diauxic shift on glucose. There was no induction of these two genes at this transition phase on galactose, although in both cases, the kinetics of glycogen accumulation was similar. In contrast, SGA1 expression was independent of the carbon source and increased by 3-fold in stationary phase. Conclusion In this work, we provided a set of genes that are suitable reference genes for quantitative gene expression analysis by real-time RT-PCR in yeast biological samples covering a large panel of physiological states. In contrast, we invalidated and discourage the use of ACT1 as well as other commonly used reference genes (PDA1, TDH3, RDN18, etc) as internal controls for quantitative gene expression analysis in yeast. PMID:19874630

Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae.

PubMed

Teste, Marie-Ange; Duquenne, Manon; François, Jean M; Parrou, Jean-Luc

2009-10-30

Real-time RT-PCR is the recommended method for quantitative gene expression analysis. A compulsory step is the selection of good reference genes for normalization. A few genes often referred to as HouseKeeping Genes (HSK), such as ACT1, RDN18 or PDA1 are among the most commonly used, as their expression is assumed to remain unchanged over a wide range of conditions. Since this assumption is very unlikely, a geometric averaging of multiple, carefully selected internal control genes is now strongly recommended for normalization to avoid this problem of expression variation of single reference genes. The aim of this work was to search for a set of reference genes for reliable gene expression analysis in Saccharomyces cerevisiae. From public microarray datasets, we selected potential reference genes whose expression remained apparently invariable during long-term growth on glucose. Using the algorithm geNorm, ALG9, TAF10, TFC1 and UBC6 turned out to be genes whose expression remained stable, independent of the growth conditions and the strain backgrounds tested in this study. We then showed that the geometric averaging of any subset of three genes among the six most stable genes resulted in very similar normalized data, which contrasted with inconsistent results among various biological samples when the normalization was performed with ACT1. Normalization with multiple selected genes was therefore applied to transcriptional analysis of genes involved in glycogen metabolism. We determined an induction ratio of 100-fold for GPH1 and 20-fold for GSY2 between the exponential phase and the diauxic shift on glucose. There was no induction of these two genes at this transition phase on galactose, although in both cases, the kinetics of glycogen accumulation was similar. In contrast, SGA1 expression was independent of the carbon source and increased by 3-fold in stationary phase. In this work, we provided a set of genes that are suitable reference genes for quantitative gene expression analysis by real-time RT-PCR in yeast biological samples covering a large panel of physiological states. In contrast, we invalidated and discourage the use of ACT1 as well as other commonly used reference genes (PDA1, TDH3, RDN18, etc) as internal controls for quantitative gene expression analysis in yeast.

Discrete Biogeography Based Optimization for Feature Selection in Molecular Signatures.

PubMed

Liu, Bo; Tian, Meihong; Zhang, Chunhua; Li, Xiangtao

2015-04-01

Biomarker discovery from high-dimensional data is a complex task in the development of efficient cancer diagnoses and classification. However, these data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in the field of bioinformatics. In this paper, a discrete biogeography based optimization is proposed to select the good subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the fisher-markov selector is used to choose fixed number of gene data. Secondly, to make biogeography based optimization suitable for the feature selection problem; discrete migration model and discrete mutation model are proposed to balance the exploration and exploitation ability. Then, discrete biogeography based optimization, as we called DBBO, is proposed by integrating discrete migration model and discrete mutation model. Finally, the DBBO method is used for feature selection, and three classifiers are used as the classifier with the 10 fold cross-validation method. In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on four breast cancer dataset benchmarks. Comparison with genetic algorithm, particle swarm optimization, differential evolution algorithm and hybrid biogeography based optimization, experimental results demonstrate that the proposed method is better or at least comparable with previous method from literature when considering the quality of the solutions obtained. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

More complete gene silencing by fewer siRNAs: transparent optimized design and biophysical signature

PubMed Central

Ladunga, Istvan

2007-01-01

Highly accurate knockdown functional analyses based on RNA interference (RNAi) require the possible most complete hydrolysis of the targeted mRNA while avoiding the degradation of untargeted genes (off-target effects). This in turn requires significant improvements to target selection for two reasons. First, the average silencing activity of randomly selected siRNAs is as low as 62%. Second, applying more than five different siRNAs may lead to saturation of the RNA-induced silencing complex (RISC) and to the degradation of untargeted genes. Therefore, selecting a small number of highly active siRNAs is critical for maximizing knockdown and minimizing off-target effects. To satisfy these needs, a publicly available and transparent machine learning tool is presented that ranks all possible siRNAs for each targeted gene. Support vector machines (SVMs) with polynomial kernels and constrained optimization models select and utilize the most predictive effective combinations from 572 sequence, thermodynamic, accessibility and self-hairpin features over 2200 published siRNAs. This tool reaches an accuracy of 92.3% in cross-validation experiments. We fully present the underlying biophysical signature that involves free energy, accessibility and dinucleotide characteristics. We show that while complete silencing is possible at certain structured target sites, accessibility information improves the prediction of the 90% active siRNA target sites. Fast siRNA activity predictions can be performed on our web server at . PMID:17169992

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray

PubMed Central

2010-01-01

Background Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. Conclusion All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues. PMID:20964859

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray.

PubMed

Fenart, Stéphane; Ndong, Yves-Placide Assoumou; Duarte, Jorge; Rivière, Nathalie; Wilmer, Jeroen; van Wuytswinkel, Olivier; Lucau, Anca; Cariou, Emmanuelle; Neutelings, Godfrey; Gutierrez, Laurent; Chabbert, Brigitte; Guillot, Xavier; Tavernier, Reynald; Hawkins, Simon; Thomasset, Brigitte

2010-10-21

Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues.

Genomic analysis of human lung fibroblasts exposed to vanadium pentoxide to identify candidate genes for occupational bronchitis

PubMed Central

Ingram, Jennifer L; Antao-Menezes, Aurita; Turpin, Elizabeth A; Wallace, Duncan G; Mangum, James B; Pluta, Linda J; Thomas, Russell S; Bonner, James C

2007-01-01

Background Exposure to vanadium pentoxide (V2O5) is a cause of occupational bronchitis. We evaluated gene expression profiles in cultured human lung fibroblasts exposed to V2O5 in vitro in order to identify candidate genes that could play a role in inflammation, fibrosis, and repair during the pathogenesis of V2O5-induced bronchitis. Methods Normal human lung fibroblasts were exposed to V2O5 in a time course experiment. Gene expression was measured at various time points over a 24 hr period using the Affymetrix Human Genome U133A 2.0 Array. Selected genes that were significantly changed in the microarray experiment were validated by RT-PCR. Results V2O5 altered more than 1,400 genes, of which ~300 were induced while >1,100 genes were suppressed. Gene ontology categories (GO) categories unique to induced genes included inflammatory response and immune response, while GO catogories unique to suppressed genes included ubiquitin cycle and cell cycle. A dozen genes were validated by RT-PCR, including growth factors (HBEGF, VEGF, CTGF), chemokines (IL8, CXCL9, CXCL10), oxidative stress response genes (SOD2, PIPOX, OXR1), and DNA-binding proteins (GAS1, STAT1). Conclusion Our study identified a variety of genes that could play pivotal roles in inflammation, fibrosis and repair during V2O5-induced bronchitis. The induction of genes that mediate inflammation and immune responses, as well as suppression of genes involved in growth arrest appear to be important to the lung fibrotic reaction to V2O5. PMID:17459161

Searching for the molecular benchmark of physiological intestinal anastomotic healing in rats: an experimental study.

PubMed

Seifert, Gabriel J; Seifert, Michael; Kulemann, Birte; Holzner, Philipp A; Glatz, Torben; Timme, Sylvia; Sick, Olivia; Höppner, Jens; Hopt, Ulrich T; Marjanovic, Goran

2014-01-01

This investigation focuses on the physiological characteristics of gene transcription of intestinal tissue following anastomosis formation. In eight rats, end-to-end ileo-ileal anastomoses were performed (n = 2/group). The healthy intestinal tissue resected for this operation was used as a control. On days 0, 2, 4 and 8, 10-mm perianastomotic segments were resected. Control and perianastomotic segments were examined with an Affymetrix microarray chip to assess changes in gene regulation. Microarray findings were validated using real-time PCR for selected genes. In addition to screening global gene expression, we identified genes intensely regulated during healing and also subjected our data sets to an overrepresentation analysis using the Gene Ontology (GO) and Kyoto Encyclopedia for Genes and Genomes (KEGG). Compared to the control group, we observed that the number of differentially regulated genes peaked on day 2 with a total of 2,238 genes, decreasing by day 4 to 1,687 genes and to 1,407 genes by day 8. PCR validation for matrix metalloproteinases-3 and -13 showed not only identical transcription patterns but also analogous regulation intensity. When setting the cutoff of upregulation at 10-fold to identify genes likely to be relevant, the total gene count was significantly lower with 55, 45 and 37 genes on days 2, 4 and 8, respectively. A total of 947 GO subcategories were significantly overrepresented during anastomotic healing. Furthermore, 23 overrepresented KEGG pathways were identified. This study is the first of its kind that focuses explicitly on gene transcription during intestinal anastomotic healing under standardized conditions. Our work sets a foundation for further studies toward a more profound understanding of the physiology of anastomotic healing.

Sequencing, annotation and comparative analysis of nine BACs of giant panda (Ailuropoda melanoleuca).

PubMed

Zheng, Yang; Cai, Jing; Li, JianWen; Li, Bo; Lin, Runmao; Tian, Feng; Wang, XiaoLing; Wang, Jun

2010-01-01

A 10-fold BAC library for giant panda was constructed and nine BACs were selected to generate finish sequences. These BACs could be used as a validation resource for the de novo assembly accuracy of the whole genome shotgun sequencing reads of giant panda newly generated by the Illumina GA sequencing technology. Complete sanger sequencing, assembly, annotation and comparative analysis were carried out on the selected BACs of a joint length 878 kb. Homologue search and de novo prediction methods were used to annotate genes and repeats. Twelve protein coding genes were predicted, seven of which could be functionally annotated. The seven genes have an average gene size of about 41 kb, an average coding size of about 1.2 kb and an average exon number of 6 per gene. Besides, seven tRNA genes were found. About 27 percent of the BAC sequence is composed of repeats. A phylogenetic tree was constructed using neighbor-join algorithm across five species, including giant panda, human, dog, cat and mouse, which reconfirms dog as the most related species to giant panda. Our results provide detailed sequence and structure information for new genes and repeats of giant panda, which will be helpful for further studies on the giant panda.

Balancing selection and genetic drift at major histocompatibility complex class II genes in isolated populations of golden snub-nosed monkey (Rhinopithecus roxellana)

PubMed Central

2012-01-01

Background Small, isolated populations often experience loss of genetic variation due to random genetic drift. Unlike neutral or nearly neutral markers (such as mitochondrial genes or microsatellites), major histocompatibility complex (MHC) genes in these populations may retain high levels of polymorphism due to balancing selection. The relative roles of balancing selection and genetic drift in either small isolated or bottlenecked populations remain controversial. In this study, we examined the mechanisms maintaining polymorphisms of MHC genes in small isolated populations of the endangered golden snub-nosed monkey (Rhinopithecus roxellana) by comparing genetic variation found in MHC and microsatellite loci. There are few studies of this kind conducted on highly endangered primate species. Results Two MHC genes were sequenced and sixteen microsatellite loci were genotyped from samples representing three isolated populations. We isolated nine DQA1 alleles and sixteen DQB1 alleles and validated expression of the alleles. Lowest genetic variation for both MHC and microsatellites was found in the Shennongjia (SNJ) population. Historical balancing selection was revealed at both the DQA1 and DQB1 loci, as revealed by excess non-synonymous substitutions at antigen binding sites (ABS) and maximum-likelihood-based random-site models. Patterns of microsatellite variation revealed population structure. FST outlier analysis showed that population differentiation at the two MHC loci was similar to the microsatellite loci. Conclusions MHC genes and microsatellite loci showed the same allelic richness pattern with the lowest genetic variation occurring in SNJ, suggesting that genetic drift played a prominent role in these isolated populations. As MHC genes are subject to selective pressures, the maintenance of genetic variation is of particular interest in small, long-isolated populations. The results of this study may contribute to captive breeding and translocation programs for endangered species. PMID:23083308

Construction of a novel multi-gene assay (42-gene classifier) for prediction of late recurrence in ER-positive breast cancer patients.

PubMed

Tsunashima, Ryo; Naoi, Yasuto; Shimazu, Kenzo; Kagara, Naofumi; Shimoda, Masashi; Tanei, Tomonori; Miyake, Tomohiro; Kim, Seung Jin; Noguchi, Shinzaburo

2018-05-04

Prediction models for late (> 5 years) recurrence in ER-positive breast cancer need to be developed for the accurate selection of patients for extended hormonal therapy. We attempted to develop such a prediction model focusing on the differences in gene expression between breast cancers with early and late recurrence. For the training set, 779 ER-positive breast cancers treated with tamoxifen alone for 5 years were selected from the databases (GSE6532, GSE12093, GSE17705, and GSE26971). For the validation set, 221 ER-positive breast cancers treated with adjuvant hormonal therapy for 5 years with or without chemotherapy at our hospital were included. Gene expression was assayed by DNA microarray analysis (Affymetrix U133 plus 2.0). With the 42 genes differentially expressed in early and late recurrence breast cancers in the training set, a prediction model (42GC) for late recurrence was constructed. The patients classified by 42GC into the late recurrence-like group showed a significantly (P = 0.006) higher late recurrence rate as expected but a significantly (P = 1.62 × E-13) lower rate for early recurrence than non-late recurrence-like group. These observations were confirmed for the validation set, i.e., P = 0.020 for late recurrence and P = 5.70 × E-5 for early recurrence. We developed a unique prediction model (42GC) for late recurrence by focusing on the biological differences between breast cancers with early and late recurrence. Interestingly, patients in the late recurrence-like group by 42GC were at low risk for early recurrence.

Molecular and genetic characterization of the Ry adg locus on chromosome XI from Andigena potatoes conferring extreme resistance to potato virus Y.

PubMed

Herrera, María Del Rosario; Vidalon, Laura Jara; Montenegro, Juan D; Riccio, Cinzia; Guzman, Frank; Bartolini, Ida; Ghislain, Marc

2018-05-31

We have elucidated the Andigena origin of the potato Ry adg gene on chromosome XI of CIP breeding lines and developed two marker assays to facilitate its introgression in potato by marker-assisted selection. Potato virus Y (PVY) is causing yield and quality losses forcing farmers to renew periodically their seeds from clean stocks. Two loci for extreme resistance to PVY, one on chromosome XI and the other on XII, have been identified and used in breeding. The latter corresponds to a well-known source of resistance (Solanum stoloniferum), whereas the one on chromosome XI was reported from S. stoloniferum and S. tuberosum group Andigena as well. To elucidate its taxonomic origin in our breeding lines, we analyzed the nucleotide sequences of tightly linked markers (M45, M6) and screened 251 landraces of S. tuberosum group Andigena for the presence of this gene. Our results indicate that the PVY resistance allele on chromosome XI in our breeding lines originated from S. tuberosum group Andigena. We have developed two marker assays to accelerate the introgression of Ry adg gene into breeding lines by marker-assisted selection (MAS). First, we have multiplexed RYSC3, M6 and M45 DNA markers flanking the Ry adg gene and validated it on potato varieties with known presence/absence of the Ry adg gene and a progeny of 6,521 individuals. Secondly, we developed an allele-dosage assay particularly useful to identify multiplex Ry adg progenitors. The assay based on high-resolution melting analysis at the M6 marker confirmed Ry adg plex level as nulliplex, simplex and duplex progenitors and few triplex progenies. These marker assays have been validated and can be used to facilitate MAS in potato breeding.

Generation of novel pharmacogenomic candidates in the response to methotrexate in juvenile idiopathic arthritis: correlation between gene expression and genotype

PubMed Central

Moncrieffe, Halima; Hinks, Anne; Ursu, Simona; Kassoumeri, Laura; Etheridge, Angela; Hubank, Mike; Martin, Paul; Weiler, Tracey; Glass, David N; Thompson, Susan D.; Thomson, Wendy; Wedderburn, Lucy R

2010-01-01

Objectives Little is known about mechanisms of efficacy of methotrexate (MTX) in childhood arthritis, or genetic influences upon response to MTX. The aims of this study were to use gene expression profiling to identify novel pathways/genes altered by MTX and then investigate these genes for genotype associations with response to MTX treatment. Methods Gene expression profiling before and after MTX treatment was performed on 11 children with juvenile idiopathic arthritis (JIA) treated with MTX, in whom response at 6 months of treatment was defined. Genes showing the most differential gene expression after treatment were selected for SNP genotyping. Genotype frequencies were compared between non-responders and responders (ACR-Ped70). An independent cohort was available for validation. Results Gene expression profiling before and after MTX treatment revealed 1222 differentially expressed probes sets (fold change >1.7, p< 0.05) and 1065 when restricted to full responder cases only. Six highly differentially expressed genes were analysed for genetic association to response to MTX. Three SNPs in the SLC16A7 gene showed significant association with MTX response. One SNP showed validated association in an independent cohort. Conclusions This study is the first, to our knowledge, to evaluate gene expression profiles in children with JIA before and after MTX, and to analyse genetic variation in differentially expressed genes. We have identified a gene which may contribute to genetic variability in MTX response in JIA, and established as proof of principle that genes which are differentially expressed at mRNA level after drug administration may also be good candidates for genetic analysis. PMID:20827233

Unraveling patterns of site-to-site synonymous rates variation and associated gene properties of protein domains and families.

PubMed

Dimitrieva, Slavica; Anisimova, Maria

2014-01-01

In protein-coding genes, synonymous mutations are often thought not to affect fitness and therefore are not subject to natural selection. Yet increasingly, cases of non-neutral evolution at certain synonymous sites were reported over the last decade. To evaluate the extent and the nature of site-specific selection on synonymous codons, we computed the site-to-site synonymous rate variation (SRV) and identified gene properties that make SRV more likely in a large database of protein-coding gene families and protein domains. To our knowledge, this is the first study that explores the determinants and patterns of the SRV in real data. We show that the SRV is widespread in the evolution of protein-coding sequences, putting in doubt the validity of the synonymous rate as a standard neutral proxy. While protein domains rarely undergo adaptive evolution, the SRV appears to play important role in optimizing the domain function at the level of DNA. In contrast, protein families are more likely to evolve by positive selection, but are less likely to exhibit SRV. Stronger SRV was detected in genes with stronger codon bias and tRNA reusage, those coding for proteins with larger number of interactions or forming larger number of structures, located in intracellular components and those involved in typically conserved complex processes and functions. Genes with extreme SRV show higher expression levels in nearly all tissues. This indicates that codon bias in a gene, which often correlates with gene expression, may often be a site-specific phenomenon regulating the speed of translation along the sequence, consistent with the co-translational folding hypothesis. Strikingly, genes with SRV were strongly overrepresented for metabolic pathways and those associated with several genetic diseases, particularly cancers and diabetes.

Selection of reliable reference genes for RT-qPCR studies in Octopus vulgaris paralarvae during development and immune-stimulation.

PubMed

García-Fernández, P; Castellanos-Martínez, S; Iglesias, J; Otero, J J; Gestal, C

2016-07-01

The common octopus, Octopus vulgaris is a new candidate species for aquaculture. However, rearing of octopus paralarvae is hampered by high mortality and poor growth rates that impede its entire culture. The study of genes involved in the octopus development and immune response capability could help to understand the key of paralarvae survival and thus, to complete the octopus life cycle. Quantitative real-time PCR (RT-qPCR) is the most frequently tool used to quantify the gene expression because of specificity and sensitivity. However, reliability of RT-qPCR requires the selection of appropriate normalization genes whose expression must be stable across the different experimental conditions of the study. Hence, the aim of the present work is to evaluate the stability of six candidate genes: β-actin (ACT), elongation factor 1-α (EF), ubiquitin (UBI), β-tubulin (TUB), glyceraldehyde 3-phosphate dehydrogenase (GADPH) and ribosomal RNA 18 (18S) in order to select the best reference gene. The stability of gene expression was analyzed using geNorm, NormFinder and Bestkeeper, in octopus paralarvae of seven developmental stages (embryo, paralarvae of 0, 10, 15, 20, 30 and 34days) and paralarvae of 20days after challenge with Vibrio lentus and Vibrio splendidus. The results were validated by measuring the expression of PGRP, a stimuli-specific gene. Our results showed UBI, EF and 18S as the most suitable reference genes during development of octopus paralarvae, and UBI, ACT and 18S for bacterial infection. These results provide a basis for further studies exploring molecular mechanism of their development and innate immune defense. Copyright © 2016 Elsevier Inc. All rights reserved.

Selection and evaluation of reference genes for RT-qPCR expression studies on Burkholderia tropica strain Ppe8, a sugarcane-associated diazotrophic bacterium grown with different carbon sources or sugarcane juice.

PubMed

da Silva, Paula Renata Alves; Vidal, Marcia Soares; de Paula Soares, Cleiton; Polese, Valéria; Simões-Araújo, Jean Luís; Baldani, José Ivo

2016-11-01

Among the members of the genus Burkholderia, Burkholderia tropica has the ability to fix nitrogen and promote sugarcane plant growth as well as act as a biological control agent. There is little information about how this bacterium metabolizes carbohydrates as well as those carbon sources found in the sugarcane juice that accumulates in stems during plant growth. Reverse transcription quantitative PCR (RT-qPCR) can be used to evaluate changes in gene expression during bacterial growth on different carbon sources. Here we tested the expression of six reference genes, lpxC, gyrB, recA, rpoA, rpoB, and rpoD, when cells were grown with glucose, fructose, sucrose, mannitol, aconitic acid, and sugarcane juice as carbon sources. The lpxC, gyrB, and recA were selected as the most stable reference genes based on geNorm and NormFinder software analyses. Validation of these three reference genes during strain Ppe8 growth on the same carbon sources showed that genes involved in glycogen biosynthesis (glgA, glgB, glgC) and trehalose biosynthesis (treY and treZ) were highly expressed when Ppe8 was grown in aconitic acid relative to other carbon sources, while otsA expression (trehalose biosynthesis) was reduced with all carbon sources. In addition, the expression level of the ORF_6066 (gluconolactonase) gene was reduced on sugarcane juice. The results confirmed the stability of the three selected reference genes (lpxC, gyrB, and recA) during the RT-qPCR and also their robustness by evaluating the relative expression of genes involved in glycogen and trehalose biosynthesis when strain Ppe8 was grown on different carbon sources and sugarcane juice.

Protective pathways against colitis mediated by appendicitis and appendectomy

PubMed Central

Cheluvappa, R; Luo, A S; Palmer, C; Grimm, M C

2011-01-01

Appendicitis followed by appendectomy (AA) at a young age protects against inflammatory bowel disease (IBD). Using a novel murine appendicitis model, we showed that AA protected against subsequent experimental colitis. To delineate genes/pathways involved in this protection, AA was performed and samples harvested from the most distal colon. RNA was extracted from four individual colonic samples per group (AA group and double-laparotomy control group) and each sample microarray analysed followed by gene-set enrichment analysis (GSEA). The gene-expression study was validated by quantitative reverse transcription–polymerase chain reaction (RT–PCR) of 14 selected genes across the immunological spectrum. Distal colonic expression of 266 gene-sets was up-regulated significantly in AA group samples (false discovery rates < 1%; P-value < 0·001). Time–course RT–PCR experiments involving the 14 genes displayed down-regulation over 28 days. The IBD-associated genes tnfsf10, SLC22A5, C3, ccr5, irgm, ptger4 and ccl20 were modulated in AA mice 3 days after surgery. Many key immunological and cellular function-associated gene-sets involved in the protective effect of AA in experimental colitis were identified. The down-regulation of 14 selected genes over 28 days after surgery indicates activation, repression or de-repression of these genes leading to downstream AA-conferred anti-colitis protection. Further analysis of these genes, profiles and biological pathways may assist in developing better therapeutic strategies in the management of intractable IBD. PMID:21707591

Association of RUNX2 and TNFSF11 genes with production traits in a paternal broiler line.

PubMed

Grupioni, N V; Stafuzza, N B; Carvajal, A B; Ibelli, A M G; Peixoto, J O; Ledur, M C; Munari, D P

2017-03-22

Intense selection for production traits has improved the genetic gain of important economic traits. However, selection for performance and carcass traits has led to the onset of locomotors problems and decreasing bone strength in broilers. Thus, genes associated with bone integrity traits have become candidates for genetic studies in order to reduce the impact of bone disorders in broilers. This study investigated the association of the RUNX2 and TNFSF11 genes with 79 traits related to performance, carcass composition, organs, and bone integrity in a paternal broiler line. Analyses of genetic association between single-nucleotide polymorphisms (SNPs) and traits were carried out using the maximum likelihood procedures for mixed models. Genetic associations (P < 0.05) were found between SNP g.124,883A>G in the RUNX2 gene and chilled femur weight (additive plus dominance deviation effects within sex) and with performance traits (additive within sex and additive effects). The SNP g.14,862T>C in the TNFSF11 gene presented genetic associations (P < 0.05) with additive plus dominance deviation effects within sex for performance traits. Suggestive genetic associations (P < 0.10) were found with abdominal fat and its yield. Selection based on SNPs g.14,862T>C in TNFSF11 and g.124,883A>G in RUNX2 could be used to improve performance and carcass quality traits in the population studied, although SNP g.14,862T>C was not in Hardy-Weinberg equilibrium because it was not undergoing a selection process. Furthermore, it is important to validate these markers in an unrelated population for use in the selection process.

Classification based upon gene expression data: bias and precision of error rates.

PubMed

Wood, Ian A; Visscher, Peter M; Mengersen, Kerrie L

2007-06-01

Gene expression data offer a large number of potentially useful predictors for the classification of tissue samples into classes, such as diseased and non-diseased. The predictive error rate of classifiers can be estimated using methods such as cross-validation. We have investigated issues of interpretation and potential bias in the reporting of error rate estimates. The issues considered here are optimization and selection biases, sampling effects, measures of misclassification rate, baseline error rates, two-level external cross-validation and a novel proposal for detection of bias using the permutation mean. Reporting an optimal estimated error rate incurs an optimization bias. Downward bias of 3-5% was found in an existing study of classification based on gene expression data and may be endemic in similar studies. Using a simulated non-informative dataset and two example datasets from existing studies, we show how bias can be detected through the use of label permutations and avoided using two-level external cross-validation. Some studies avoid optimization bias by using single-level cross-validation and a test set, but error rates can be more accurately estimated via two-level cross-validation. In addition to estimating the simple overall error rate, we recommend reporting class error rates plus where possible the conditional risk incorporating prior class probabilities and a misclassification cost matrix. We also describe baseline error rates derived from three trivial classifiers which ignore the predictors. R code which implements two-level external cross-validation with the PAMR package, experiment code, dataset details and additional figures are freely available for non-commercial use from http://www.maths.qut.edu.au/profiles/wood/permr.jsp

Validation of reference genes for gene expression analysis in olive (Olea europaea) mesocarp tissue by quantitative real-time RT-PCR

PubMed Central

2014-01-01

Background Gene expression analysis using quantitative reverse transcription PCR (qRT-PCR) is a robust method wherein the expression levels of target genes are normalised using internal control genes, known as reference genes, to derive changes in gene expression levels. Although reference genes have recently been suggested for olive tissues, combined/independent analysis on different cultivars has not yet been tested. Therefore, an assessment of reference genes was required to validate the recent findings and select stably expressed genes across different olive cultivars. Results A total of eight candidate reference genes [glyceraldehyde 3-phosphate dehydrogenase (GAPDH), serine/threonine-protein phosphatase catalytic subunit (PP2A), elongation factor 1 alpha (EF1-alpha), polyubiquitin (OUB2), aquaporin tonoplast intrinsic protein (TIP2), tubulin alpha (TUBA), 60S ribosomal protein L18-3 (60S RBP L18-3) and polypyrimidine tract-binding protein homolog 3 (PTB)] were chosen based on their stability in olive tissues as well as in other plants. Expression stability was examined by qRT-PCR across 12 biological samples, representing mesocarp tissues at various developmental stages in three different olive cultivars, Barnea, Frantoio and Picual, independently and together during the 2009 season with two software programs, GeNorm and BestKeeper. Both software packages identified GAPDH, EF1-alpha and PP2A as the three most stable reference genes across the three cultivars and in the cultivar, Barnea. GAPDH, EF1-alpha and 60S RBP L18-3 were found to be most stable reference genes in the cultivar Frantoio while 60S RBP L18-3, OUB2 and PP2A were found to be most stable reference genes in the cultivar Picual. Conclusions The analyses of expression stability of reference genes using qRT-PCR revealed that GAPDH, EF1-alpha, PP2A, 60S RBP L18-3 and OUB2 are suitable reference genes for expression analysis in developing Olea europaea mesocarp tissues, displaying the highest level of expression stability across three different olive cultivars, Barnea, Frantoio and Picual, however the combination of the three most stable reference genes do vary amongst individual cultivars. This study will provide guidance to other researchers to select reference genes for normalization against target genes by qPCR across tissues obtained from the mesocarp region of the olive fruit in the cultivars, Barnea, Frantoio and Picual. PMID:24884716

Long-term affected flat oyster (Ostrea edulis) haemocytes show differential gene expression profiles from naïve oysters in response to Bonamia ostreae.

PubMed

Ronza, P; Cao, A; Robledo, D; Gómez-Tato, A; Álvarez-Dios, J A; Hasanuzzaman, A F M; Quiroga, M I; Villalba, A; Pardo, B G; Martínez, P

2018-04-18

European flat oyster (Ostrea edulis) production has suffered a severe decline due to bonamiosis. The responsible parasite enters in oyster haemocytes, causing an acute inflammatory response frequently leading to death. We used an immune-enriched oligo-microarray to understand the haemocyte response to Bonamia ostreae by comparing expression profiles between naïve (NS) and long-term affected (AS) populations along a time series (1 d, 30 d, 90 d). AS showed a much higher response just after challenge, which might be indicative of selection for resistance. No regulated genes were detected at 30 d in both populations while a notable reactivation was observed at 90 d, suggesting parasite latency during infection. Genes related to extracellular matrix and protease inhibitors, up-regulated in AS, and those related to histones, down-regulated in NS, might play an important role along the infection. Twenty-four candidate genes related to resistance should be further validated for selection programs aimed to control bonamiosis. Copyright © 2018 Elsevier Inc. All rights reserved.

Identifying key genes in glaucoma based on a benchmarked dataset and the gene regulatory network.

PubMed

Chen, Xi; Wang, Qiao-Ling; Zhang, Meng-Hui

2017-10-01

The current study aimed to identify key genes in glaucoma based on a benchmarked dataset and gene regulatory network (GRN). Local and global noise was added to the gene expression dataset to produce a benchmarked dataset. Differentially-expressed genes (DEGs) between patients with glaucoma and normal controls were identified utilizing the Linear Models for Microarray Data (Limma) package based on benchmarked dataset. A total of 5 GRN inference methods, including Zscore, GeneNet, context likelihood of relatedness (CLR) algorithm, Partial Correlation coefficient with Information Theory (PCIT) and GEne Network Inference with Ensemble of Trees (Genie3) were evaluated using receiver operating characteristic (ROC) and precision and recall (PR) curves. The interference method with the best performance was selected to construct the GRN. Subsequently, topological centrality (degree, closeness and betweenness) was conducted to identify key genes in the GRN of glaucoma. Finally, the key genes were validated by performing reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A total of 176 DEGs were detected from the benchmarked dataset. The ROC and PR curves of the 5 methods were analyzed and it was determined that Genie3 had a clear advantage over the other methods; thus, Genie3 was used to construct the GRN. Following topological centrality analysis, 14 key genes for glaucoma were identified, including IL6 , EPHA2 and GSTT1 and 5 of these 14 key genes were validated by RT-qPCR. Therefore, the current study identified 14 key genes in glaucoma, which may be potential biomarkers to use in the diagnosis of glaucoma and aid in identifying the molecular mechanism of this disease.

Selection of growth-related genes and dominant genotypes in transgenic Yellow River carp Cyprinus carpio L.

PubMed

Luo, Lifei; Huang, Rong; Zhang, Aidi; Yang, Cheng; Chen, Liangming; Zhu, Denghui; Li, Yongming; He, Libo; Liao, Lanjie; Zhu, Zuoyan; Wang, Yaping

2018-07-01

Transgenic Yellow River carp is characterized by rapid growth rate and high feed-conversion efficiency and exhibits a great application prospect. However, there is still a significant separation of growth traits in the transgenic Yellow River carp family; as such, growth-related genotypes must be screened for molecular marker-assisted selection. In this study, 23 growth-related candidate genes containing 48 SNP markers were screened through bulked segregant analysis (BSA) among transgenic Yellow River carp family members showing significant separation of growth traits. Then, two growth-related genes (Nos. 17 and 14 genes) were identified through combined genome-wide association study (GWAS) of candidate genes and validation of the full-sibling family approach. Nos. 17 and 14 genes encode BR serine/threonine-protein kinase 2 (BRSK2) and eukaryotic translation-initiation factor 2-alpha kinase 3 (Eif2ak3), respectively. The average body weight of three subgroups carrying the genotypes 17GG, 17GG + 14CC, and 17GG + 14TT of these two genes increased by 27.96, 38.28, and 33.72%, respectively, compared with the controls. The proportion of individuals with body weight > 500 g in these subgroups increased by 19.22, 26.82, and 30.92%, respectively. The results showed that appropriate genotype carriers can be selected from the progeny population through BSA sequencing combined with simplified GWAS analysis. Hence, basic population for breeding can be constructed and transgenic Yellow River carp strains with stable production performance and uniform phenotypic properties can be bred.

An efficient system for the generation of marked genetic mutants in members of the genus Burkholderia.

PubMed

Shastri, Sravanthi; Spiewak, Helena L; Sofoluwe, Aderonke; Eidsvaag, Vigdis A; Asghar, Atif H; Pereira, Tyrone; Bull, Edward H; Butt, Aaron T; Thomas, Mark S

2017-01-01

To elucidate the function of a gene in bacteria it is vital that targeted gene inactivation (allelic replacement) can be achieved. Allelic replacement is often carried out by disruption of the gene of interest by insertion of an antibiotic-resistance marker followed by subsequent transfer of the mutant allele to the genome of the host organism in place of the wild-type gene. However, due to their intrinsic resistance to many antibiotics only selected antibiotic-resistance markers can be used in members of the genus Burkholderia, including the Burkholderia cepacia complex (Bcc). Here we describe the construction of improved antibiotic-resistance cassettes that specify resistance to kanamycin, chloramphenicol or trimethoprim effectively in the Bcc and related species. These were then used in combination with and/or to construct a series enhanced suicide vectors, pSHAFT2, pSHAFT3 and pSHAFT-GFP to facilitate effective allelic replacement in the Bcc. Validation of these improved suicide vectors was demonstrated by the genetic inactivation of selected genes in the Bcc species Burkholderia cenocepacia and B. lata, and in the non-Bcc species, B. thailandensis. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Effects of chronic morphine and morphine withdrawal on gene expression in rat peripheral blood mononuclear cells.

PubMed

Desjardins, Stephane; Belkai, Emilie; Crete, Dominique; Cordonnier, Laurie; Scherrmann, Jean-Michel; Noble, Florence; Marie-Claire, Cynthia

2008-12-01

Chronic morphine treatment alters gene expression in brain structures. There are increasing evidences showing a correlation, in gene expression modulation, between blood cells and brain in psychological troubles. To test whether gene expression regulation in blood cells could be found in drug addiction, we investigated gene expression profiles in peripheral blood mononuclear (PBMC) cells of saline and morphine-treated rats. In rats chronically treated with morphine, the behavioral signs of spontaneous withdrawal were observed and a withdrawal score was determined. This score enabled to select the time points at which the animals displayed the mildest and strongest withdrawal signs (12 h and 36 h after the last injection). Oligonucleotide arrays were used to assess differential gene expression in the PBMCs and quantitative real-time RT-PCR to validate the modulation of several candidate genes 12 h and 36 h after the last injection. Among the 812 differentially expressed candidates, several genes (Adcy5, Htr2a) and pathways (Map kinases, G-proteins, integrins) have already been described as modulated in the brain of morphine-treated rats. Sixteen out of the twenty-four tested candidates were validated at 12 h, some of them showed a sustained modulation at 36 h while for most of them the modulation evolved as the withdrawal score increased. This study suggests similarities between the gene expression profile in PBMCs and brain of morphine-treated rats. Thus, the searching of correlations between the severity of the withdrawal and the PBMCs gene expression pattern by transcriptional analysis of blood cells could be promising for the study of the mechanisms of addiction.

CX3CR1 is dysregulated in blood and brain from schizophrenia patients.

PubMed

Bergon, Aurélie; Belzeaux, Raoul; Comte, Magali; Pelletier, Florence; Hervé, Mylène; Gardiner, Erin J; Beveridge, Natalie J; Liu, Bing; Carr, Vaughan; Scott, Rodney J; Kelly, Brian; Cairns, Murray J; Kumarasinghe, Nishantha; Schall, Ulrich; Blin, Olivier; Boucraut, José; Tooney, Paul A; Fakra, Eric; Ibrahim, El Chérif

2015-10-01

The molecular mechanisms underlying schizophrenia remain largely unknown. Although schizophrenia is a mental disorder, there is increasing evidence to indicate that inflammatory processes driven by diverse environmental factors play a significant role in its development. With gene expression studies having been conducted across a variety of sample types, e.g., blood and postmortem brain, it is possible to investigate convergent signatures that may reveal interactions between the immune and nervous systems in schizophrenia pathophysiology. We conducted two meta-analyses of schizophrenia microarray gene expression data (N=474) and non-psychiatric control (N=485) data from postmortem brain and blood. Then, we assessed whether significantly dysregulated genes in schizophrenia could be shared between blood and brain. To validate our findings, we selected a top gene candidate and analyzed its expression by RT-qPCR in a cohort of schizophrenia subjects stabilized by atypical antipsychotic monotherapy (N=29) and matched controls (N=31). Meta-analyses highlighted inflammation as the major biological process associated with schizophrenia and that the chemokine receptor CX3CR1 was significantly down-regulated in schizophrenia. This differential expression was also confirmed in our validation cohort. Given both the recent data demonstrating selective CX3CR1 expression in subsets of neuroimmune cells, as well as behavioral and neuropathological observations of CX3CR1 deficiency in mouse models, our results of reduced CX3CR1 expression adds further support for a role played by monocyte/microglia in the neurodevelopment of schizophrenia. Copyright © 2015 Elsevier B.V. All rights reserved.

Identification of a novel MYO7A mutation in Usher syndrome type 1.

PubMed

Cheng, Ling; Yu, Hongsong; Jiang, Yan; He, Juan; Pu, Sisi; Li, Xin; Zhang, Li

2018-01-05

Usher syndrome (USH) is an autosomal recessive disease characterized by deafness and retinitis pigmentosa. In view of the high phenotypic and genetic heterogeneity in USH, performing genetic screening with traditional methods is impractical. In the present study, we carried out targeted next-generation sequencing (NGS) to uncover the underlying gene in an USH family (2 USH patients and 15 unaffected relatives). One hundred and thirty-five genes associated with inherited retinal degeneration were selected for deep exome sequencing. Subsequently, variant analysis, Sanger validation and segregation tests were utilized to identify the disease-causing mutations in this family. All affected individuals had a classic USH type I (USH1) phenotype which included deafness, vestibular dysfunction and retinitis pigmentosa. Targeted NGS and Sanger sequencing validation suggested that USH1 patients carried an unreported splice site mutation, c.5168+1G>A, as a compound heterozygous mutation with c.6070C>T (p.R2024X) in the MYO7A gene. A functional study revealed decreased expression of the MYO7A gene in the individuals carrying heterozygous mutations. In conclusion, targeted next-generation sequencing provided a comprehensive and efficient diagnosis for USH1. This study revealed the genetic defects in the MYO7A gene and expanded the spectrum of clinical phenotypes associated with USH1 mutations.

Identification of Direct Target Genes Using Joint Sequence and Expression Likelihood with Application to DAF-16

PubMed Central

Yu, Ron X.; Liu, Jie; True, Nick; Wang, Wei

2008-01-01

A major challenge in the post-genome era is to reconstruct regulatory networks from the biological knowledge accumulated up to date. The development of tools for identifying direct target genes of transcription factors (TFs) is critical to this endeavor. Given a set of microarray experiments, a probabilistic model called TRANSMODIS has been developed which can infer the direct targets of a TF by integrating sequence motif, gene expression and ChIP-chip data. The performance of TRANSMODIS was first validated on a set of transcription factor perturbation experiments (TFPEs) involving Pho4p, a well studied TF in Saccharomyces cerevisiae. TRANSMODIS removed elements of arbitrariness in manual target gene selection process and produced results that concur with one's intuition. TRANSMODIS was further validated on a genome-wide scale by comparing it with two other methods in Saccharomyces cerevisiae. The usefulness of TRANSMODIS was then demonstrated by applying it to the identification of direct targets of DAF-16, a critical TF regulating ageing in Caenorhabditis elegans. We found that 189 genes were tightly regulated by DAF-16. In addition, DAF-16 has differential preference for motifs when acting as an activator or repressor, which awaits experimental verification. TRANSMODIS is computationally efficient and robust, making it a useful probabilistic framework for finding immediate targets. PMID:18350157

A closer look at cross-validation for assessing the accuracy of gene regulatory networks and models.

PubMed

Tabe-Bordbar, Shayan; Emad, Amin; Zhao, Sihai Dave; Sinha, Saurabh

2018-04-26

Cross-validation (CV) is a technique to assess the generalizability of a model to unseen data. This technique relies on assumptions that may not be satisfied when studying genomics datasets. For example, random CV (RCV) assumes that a randomly selected set of samples, the test set, well represents unseen data. This assumption doesn't hold true where samples are obtained from different experimental conditions, and the goal is to learn regulatory relationships among the genes that generalize beyond the observed conditions. In this study, we investigated how the CV procedure affects the assessment of supervised learning methods used to learn gene regulatory networks (or in other applications). We compared the performance of a regression-based method for gene expression prediction estimated using RCV with that estimated using a clustering-based CV (CCV) procedure. Our analysis illustrates that RCV can produce over-optimistic estimates of the model's generalizability compared to CCV. Next, we defined the 'distinctness' of test set from training set and showed that this measure is predictive of performance of the regression method. Finally, we introduced a simulated annealing method to construct partitions with gradually increasing distinctness and showed that performance of different gene expression prediction methods can be better evaluated using this method.

Selection of housekeeping genes as internal controls for quantitative RT-PCR analysis of the veined rapa whelk (Rapana venosa).

PubMed

Song, Hao; Dang, Xin; He, Yuan-Qiu; Zhang, Tao; Wang, Hai-Yan

2017-01-01

The veined rapa whelk Rapana venosa is an important commercial shellfish in China and quantitative real-time PCR (qRT-PCR) has become the standard method to study gene expression in R. venosa . For accurate and reliable gene expression results, qRT-PCR assays require housekeeping genes as internal controls, which display highly uniform expression in different tissues or stages of development. However, to date no studies have validated housekeeping genes in R. venosa for use as internal controls for qRT-PCR. In this study, we selected the following 13 candidate genes for suitability as internal controls: elongation factor-1 α ( EF-1α ), α -actin ( ACT ), cytochrome c oxidase subunit 1 ( COX1 ), nicotinamide adenine dinucleotide dehydrogenase (ubiquinone) 1 α subcomplex subunit 7 ( NDUFA7 ), 60S ribosomal protein L5 ( RL5 ), 60S ribosomal protein L28 ( RL28 ), glyceraldehyde 3-phosphate dehydrogenase ( GAPDH ), β -tubulin ( TUBB ), 40S ribosomal protein S25 ( RS25 ), 40S ribosomal protein S8 ( RS8 ), ubiquitin-conjugating enzyme E2 ( UBE2 ), histone H3 ( HH3 ), and peptidyl-prolyl cis-trans isomerase A ( PPIA ). We measured the expression levels of these 13 candidate internal controls in eight different tissues and twelve larvae developmental stages by qRT-PCR. Further analysis of the expression stability of the tested genes was performed using GeNorm and RefFinder algorithms. Of the 13 candidate genes tested, we found that EF-1α was the most stable internal control gene in almost all adult tissue samples investigated with RL5 and RL28 as secondary choices. For the normalization of a single specific tissue, we suggested that EF-1α and NDUFA7 are the best combination in gonad, as well as COX1 and RL28 for intestine, EF-1α and RL5 for kidney, EF-1α and COX1 for gill, EF-1α and RL28 for Leiblein and mantle, EF-1α , RL5 , and NDUFA7 for liver , GAPDH , PPIA , and RL28 for hemocyte. From a developmental perspective, we found that RL28 was the most stable gene in all developmental stages measured, and COX1 and RL5 were appropriate secondary choices. For the specific developmental stage, we recommended the following combination for normalization, PPIA , RS25 , and RL28 for stage 1, RL5 and RL28 for stage 2 and 5, RL28 and NDUFA7 for stage 3, and PPIA and TUBB for stage 4. Our results are instrumental for the selection of appropriately validated housekeeping genes for use as internal controls for gene expression studies in adult tissues or larval development of R. venosa in the future.

Identification of suitable internal control genes for expression studies in Coffea arabica under different experimental conditions

PubMed Central

Barsalobres-Cavallari, Carla F; Severino, Fábio E; Maluf, Mirian P; Maia, Ivan G

2009-01-01

Background Quantitative data from gene expression experiments are often normalized by transcription levels of reference or housekeeping genes. An inherent assumption for their use is that the expression of these genes is highly uniform in living organisms during various phases of development, in different cell types and under diverse environmental conditions. To date, the validation of reference genes in plants has received very little attention and suitable reference genes have not been defined for a great number of crop species including Coffea arabica. The aim of the research reported herein was to compare the relative expression of a set of potential reference genes across different types of tissue/organ samples of coffee. We also validated the expression profiles of the selected reference genes at various stages of development and under a specific biotic stress. Results The expression levels of five frequently used housekeeping genes (reference genes), namely alcohol dehydrogenase (adh), 14-3-3, polyubiquitin (poly), β-actin (actin) and glyceraldehyde-3-phosphate dehydrogenase (gapdh) was assessed by quantitative real-time RT-PCR over a set of five tissue/organ samples (root, stem, leaf, flower, and fruits) of Coffea arabica plants. In addition to these commonly used internal controls, three other genes encoding a cysteine proteinase (cys), a caffeine synthase (ccs) and the 60S ribosomal protein L7 (rpl7) were also tested. Their stability and suitability as reference genes were validated by geNorm, NormFinder and BestKeeper programs. The obtained results revealed significantly variable expression levels of all reference genes analyzed, with the exception of gapdh, which showed no significant changes in expression among the investigated experimental conditions. Conclusion Our data suggests that the expression of housekeeping genes is not completely stable in coffee. Based on our results, gapdh, followed by 14-3-3 and rpl7 were found to be homogeneously expressed and are therefore adequate for normalization purposes, showing equivalent transcript levels in different tissue/organ samples. Gapdh is therefore the recommended reference gene for measuring gene expression in Coffea arabica. Its use will enable more accurate and reliable normalization of tissue/organ-specific gene expression studies in this important cherry crop plant. PMID:19126214

Selection of reference genes for gene expression studies related to intramuscular fat deposition in Capra hircus skeletal muscle.

PubMed

Zhu, Wuzheng; Lin, Yaqiu; Liao, Honghai; Wang, Yong

2015-01-01

The identification of suitable reference genes is critical for obtaining reliable results from gene expression studies using quantitative real-time PCR (qPCR) because the expression of reference genes may vary considerably under different experimental conditions. In most cases, however, commonly used reference genes are employed in data normalization without proper validation, which may lead to incorrect data interpretation. Here, we aim to select a set of optimal reference genes for the accurate normalization of gene expression associated with intramuscular fat (IMF) deposition during development. In the present study, eight reference genes (PPIB, HMBS, RPLP0, B2M, YWHAZ, 18S, GAPDH and ACTB) were evaluated by three different algorithms (geNorm, NormFinder and BestKeeper) in two types of muscle tissues (longissimus dorsi muscle and biceps femoris muscle) across different developmental stages. All three algorithms gave similar results. PPIB and HMBS were identified as the most stable reference genes, while the commonly used reference genes 18S and GAPDH were the most variably expressed, with expression varying dramatically across different developmental stages. Furthermore, to reveal the crucial role of appropriate reference genes in obtaining a reliable result, analysis of PPARG expression was performed by normalization to the most and the least stable reference genes. The relative expression levels of PPARG normalized to the most stable reference genes greatly differed from those normalized to the least stable one. Therefore, evaluation of reference genes must be performed for a given experimental condition before the reference genes are used. PPIB and HMBS are the optimal reference genes for analysis of gene expression associated with IMF deposition in skeletal muscle during development.

Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer

PubMed Central

2015-01-01

Background microRNA (miRNA) expression plays an influential role in cancer classification and malignancy, and miRNAs are feasible as alternative diagnostic markers for pancreatic cancer, a highly aggressive neoplasm with silent early symptoms, high metastatic potential, and resistance to conventional therapies. Methods In this study, we evaluated the benefits of multi-omics data analysis by integrating miRNA and mRNA expression data in pancreatic cancer. Using support vector machine (SVM) modelling and leave-one-out cross validation (LOOCV), we evaluated the diagnostic performance of single- or multi-markers based on miRNA and mRNA expression profiles from 104 PDAC tissues and 17 benign pancreatic tissues. For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) data depositories. For validation, miRNA activity was estimated by miRNA-target gene interaction and mRNA expression datasets in pancreatic cancer. Results Using a comprehensive identification approach, we successfully identified 705 multi-markers having powerful diagnostic performance for PDAC. In addition, these marker candidates annotated with cancer pathways using gene ontology analysis. Conclusions Our prediction models have strong potential for the diagnosis of pancreatic cancer. PMID:26328610

Detection of selective sweeps in cattle using genome-wide SNP data

PubMed Central

2013-01-01

Background The domestication and subsequent selection by humans to create breeds and biological types of cattle undoubtedly altered the patterning of variation within their genomes. Strong selection to fix advantageous large-effect mutations underlying domesticability, breed characteristics or productivity created selective sweeps in which variation was lost in the chromosomal region flanking the selected allele. Selective sweeps have now been identified in the genomes of many animal species including humans, dogs, horses, and chickens. Here, we attempt to identify and characterise regions of the bovine genome that have been subjected to selective sweeps. Results Two datasets were used for the discovery and validation of selective sweeps via the fixation of alleles at a series of contiguous SNP loci. BovineSNP50 data were used to identify 28 putative sweep regions among 14 diverse cattle breeds. Affymetrix BOS 1 prescreening assay data for five breeds were used to identify 85 regions and validate 5 regions identified using the BovineSNP50 data. Many genes are located within these regions and the lack of sequence data for the analysed breeds precludes the nomination of selected genes or variants and limits the prediction of the selected phenotypes. However, phenotypes that we predict to have historically been under strong selection include horned-polled, coat colour, stature, ear morphology, and behaviour. Conclusions The bias towards common SNPs in the design of the BovineSNP50 assay led to the identification of recent selective sweeps associated with breed formation and common to only a small number of breeds rather than ancient events associated with domestication which could potentially be common to all European taurines. The limited SNP density, or marker resolution, of the BovineSNP50 assay significantly impacted the rate of false discovery of selective sweeps, however, we found sweeps in common between breeds which were confirmed using an ultra-high-density assay scored in a small number of animals from a subset of the breeds. No sweep regions were shared between indicine and taurine breeds reflecting their divergent selection histories and the very different environmental habitats to which these sub-species have adapted. PMID:23758707

Evaluation of gene expression classification studies: factors associated with classification performance.

PubMed

Novianti, Putri W; Roes, Kit C B; Eijkemans, Marinus J C

2014-01-01

Classification methods used in microarray studies for gene expression are diverse in the way they deal with the underlying complexity of the data, as well as in the technique used to build the classification model. The MAQC II study on cancer classification problems has found that performance was affected by factors such as the classification algorithm, cross validation method, number of genes, and gene selection method. In this paper, we study the hypothesis that the disease under study significantly determines which method is optimal, and that additionally sample size, class imbalance, type of medical question (diagnostic, prognostic or treatment response), and microarray platform are potentially influential. A systematic literature review was used to extract the information from 48 published articles on non-cancer microarray classification studies. The impact of the various factors on the reported classification accuracy was analyzed through random-intercept logistic regression. The type of medical question and method of cross validation dominated the explained variation in accuracy among studies, followed by disease category and microarray platform. In total, 42% of the between study variation was explained by all the study specific and problem specific factors that we studied together.

Development and validation of a microarray for the investigation of the CAZymes encoded by the human gut microbiome.

PubMed

El Kaoutari, Abdessamad; Armougom, Fabrice; Leroy, Quentin; Vialettes, Bernard; Million, Matthieu; Raoult, Didier; Henrissat, Bernard

2013-01-01

Distal gut bacteria play a pivotal role in the digestion of dietary polysaccharides by producing a large number of carbohydrate-active enzymes (CAZymes) that the host otherwise does not produce. We report here the design of a custom microarray that we used to spot non-redundant DNA probes for more than 6,500 genes encoding glycoside hydrolases and lyases selected from 174 reference genomes from distal gut bacteria. The custom microarray was tested and validated by the hybridization of bacterial DNA extracted from the stool samples of lean, obese and anorexic individuals. Our results suggest that a microarray-based study can detect genes from low-abundance bacteria better than metagenomic-based studies. A striking example was the finding that a gene encoding a GH6-family cellulase was present in all subjects examined, whereas metagenomic studies have consistently failed to detect this gene in both human and animal gut microbiomes. In addition, an examination of eight stool samples allowed the identification of a corresponding CAZome core containing 46 families of glycoside hydrolases and polysaccharide lyases, which suggests the functional stability of the gut microbiota despite large taxonomical variations between individuals.

Selection and evaluation of novel reference genes for quantitative reverse transcription PCR (qRT-PCR) based on genome and transcriptome data in Brassica napus L.

PubMed

Yang, Hongli; Liu, Jing; Huang, Shunmou; Guo, Tingting; Deng, Linbin; Hua, Wei

2014-03-15

Selection of reference genes in Brassica napus, a tetraploid (4×) species, is a very difficult task without information on genome and transcriptome. By now, only several traditional reference genes which show significant expression differentiation under different conditions are used in B. napus. In the present study, based on genome and transcriptome data of the rapeseed Zhongshuang-11 cultivar, 14 candidate reference genes were screened for investigation in different tissues, cultivars, and treated conditions of B. napus. These genes were as follows: ELF5, ENTH, F-BOX7, F-BOX2, FYPP1, GDI1, GYF, MCP2d, OTP80, PPR, SPOC, Unknown1, Unknown2 and UBA. Among them, excluding GYF and FYPP1, another 12 genes, were identified to perform better than traditional reference genes ACTIN7 and GAPDH. To further validate the accuracy of the newly developed reference genes in normalization, expression levels of BnCAT1 (B. napus catalase 1) in different rapeseed tissues and seedlings under stress conditions were normalized by the three most stable reference genes PPR, GDI1, and ENTH and little difference existed in normalization results. To the best of our knowledge, this is the first time B. napus reference genes have been provided with the help of complete genome and transcriptome information. The new reference genes provided in this study are more accurate than previously reported reference genes in quantifying expression levels of B. napus genes. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

Meta-Analysis and Experimental Validation Identified FREM2 and SPRY1 as New Glioblastoma Marker Candidates.

PubMed

Vidak, Marko; Jovcevska, Ivana; Samec, Neja; Zottel, Alja; Liovic, Mirjana; Rozman, Damjana; Dzeroski, Saso; Juvan, Peter; Komel, Radovan

2018-05-04

Glioblastoma (GB) is the most aggressive brain malignancy. Although some potential glioblastoma biomarkers have already been identified, there is a lack of cell membrane-bound biomarkers capable of distinguishing brain tissue from glioblastoma and/or glioblastoma stem cells (GSC), which are responsible for the rapid post-operative tumor reoccurrence. In order to find new GB/GSC marker candidates that would be cell surface proteins (CSP), we have performed meta-analysis of genome-scale mRNA expression data from three data repositories (GEO, ArrayExpress and GLIOMASdb). The search yielded ten appropriate datasets, and three (GSE4290/GDS1962, GSE23806/GDS3885, and GLIOMASdb) were used for selection of new GB/GSC marker candidates, while the other seven (GSE4412/GDS1975, GSE4412/GDS1976, E-GEOD-52009, E-GEOD-68848, E-GEOD-16011, E-GEOD-4536, and E-GEOD-74571) were used for bioinformatic validation. The selection identified four new CSP-encoding candidate genes— CD276 , FREM2 , SPRY1 , and SLC47A1 —and the bioinformatic validation confirmed these findings. A review of the literature revealed that CD276 is not a novel candidate, while SLC47A1 had lower validation test scores than the other new candidates and was therefore not considered for experimental validation. This validation revealed that the expression of FREM2—but not SPRY1—is higher in glioblastoma cell lines when compared to non-malignant astrocytes. In addition, FREM2 gene and protein expression levels are higher in GB stem-like cell lines than in conventional glioblastoma cell lines. FREM2 is thus proposed as a novel GB biomarker and a putative biomarker of glioblastoma stem cells. Both FREM2 and SPRY1 are expressed on the surface of the GB cells, while SPRY1 alone was found overexpressed in the cytosol of non-malignant astrocytes.

Exploring valid reference genes for quantitative real-time PCR analysis in Sesamia inferens (Lepidoptera: Noctuidae).

PubMed

Sun, Meng; Lu, Ming-Xing; Tang, Xiao-Tian; Du, Yu-Zhou

2015-01-01

The pink stem borer, Sesamia inferens, which is endemic in China and other parts of Asia, is a major pest of rice and causes significant yield loss in this host plant. Very few studies have addressed gene expression in S. inferens. Quantitative real-time PCR (qRT-PCR) is currently the most accurate and sensitive method for gene expression analysis. In qRT-PCR, data are normalized using reference genes, which help control for internal differences and reduce error between samples. In this study, seven candidate reference genes, 18S ribosomal RNA (18S rRNA), elongation factor 1 (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein S13 (RPS13), ribosomal protein S20 (RPS20), tubulin (TUB), and β-actin (ACTB) were evaluated for their suitability in normalizing gene expression under different experimental conditions. The results indicated that three genes (RPS13, RPS20, and EF1) were optimal for normalizing gene expression in different insect tissues (head, epidermis, fat body, foregut, midgut, hindgut, Malpighian tubules, haemocytes, and salivary glands). 18S rRNA, EF1, and GAPDH were best for normalizing expression with respect to developmental stages and sex (egg masses; first, second, third, fourth, fifth, and sixth instar larvae; male and female pupae; and one-day-old male and female adults). 18S rRNA, RPS20, and TUB were optimal for fifth instars exposed to different temperatures (-8, -6, -4, -2, 0, and 27°C). To validate this recommendation, the expression profile of a target gene heat shock protein 83 gene (hsp83) was investigated, and results showed the selection was necessary and effective. In conclusion, this study describes reference gene sets that can be used to accurately measure gene expression in S. inferens.

Detecting selection signatures between Duroc and Duroc synthetic pig populations using high-density SNP chip.

PubMed

Edea, Z; Hong, J-K; Jung, J-H; Kim, D-W; Kim, Y-M; Kim, E-S; Shin, S S; Jung, Y C; Kim, K-S

2017-08-01

The development of high throughput genotyping techniques has facilitated the identification of selection signatures of pigs. The detection of genomic selection signals in a population subjected to differential selection pressures may provide insights into the genes associated with economically and biologically important traits. To identify genomic regions under selection, we genotyped 488 Duroc (D) pigs and 155 D × Korean native pigs (DKNPs) using the Porcine SNP70K BeadChip. By applying the F ST and extended haplotype homozygosity (EHH-Rsb) methods, we detected genes under directional selection associated with growth/stature (DOCK7, PLCB4, HS2ST1, FBP2 and TG), carcass and meat quality (TG, COL14A1, FBXO5, NR3C1, SNX7, ARHGAP26 and DPYD), number of teats (LOC100153159 and LRRC1), pigmentation (MME) and ear morphology (SOX5), which are all mostly near or at fixation. These results could be a basis for investigating the underlying mutations associated with observed phenotypic variation. Validation using genome-wide association analysis would also facilitate the inclusion of some of these markers in genetic evaluation programs. © 2017 Stichting International Foundation for Animal Genetics.

A genetic replacement system for selection-based engineering of essential proteins

PubMed Central

2012-01-01

Background Essential genes represent the core of biological functions required for viability. Molecular understanding of essentiality as well as design of synthetic cellular systems includes the engineering of essential proteins. An impediment to this effort is the lack of growth-based selection systems suitable for directed evolution approaches. Results We established a simple strategy for genetic replacement of an essential gene by a (library of) variant(s) during a transformation. The system was validated using three different essential genes and plasmid combinations and it reproducibly shows transformation efficiencies on the order of 107 transformants per microgram of DNA without any identifiable false positives. This allowed for reliable recovery of functional variants out of at least a 105-fold excess of non-functional variants. This outperformed selection in conventional bleach-out strains by at least two orders of magnitude, where recombination between functional and non-functional variants interfered with reliable recovery even in recA negative strains. Conclusions We propose that this selection system is extremely suitable for evaluating large libraries of engineered essential proteins resulting in the reliable isolation of functional variants in a clean strain background which can readily be used for in vivo applications as well as expression and purification for use in in vitro studies. PMID:22898007

Biomarker discovery and transcriptomic responses in Daphnia magna exposed to munitions constituents.

PubMed

Garcia-Reyero, Natalia; Poynton, Helen C; Kennedy, Alan J; Guan, Xin; Escalon, B Lynn; Chang, Bonnie; Varshavsky, Julia; Loguinov, Alex V; Vulpe, Chris D; Perkins, Edward J

2009-06-01

Ecotoxicogenomic approaches are emerging as alternative methods in environmental monitoring because they allow insight into pollutant modes of action and help assess the causal agents and potential toxicity beyond the traditional end points of death, growth, and reproduction. Gene expression analysis has shown particular promise for identifying gene expression biomarkers of chemical exposure that can be further used to monitor specific chemical exposures in the environment. We focused on the development of gene expression markers to detect and discriminate between chemical exposures. Using a custom cDNA microarray for Daphnia magna, we identified distinct expression fingerprints in response to exposure at sublethal concentrations of Cu, Zn, Pb, and munitions constituents. Using the results obtained from microarray analysis, we chose a suite of potential biomarkers for each of the specific exposures. The selected potential biomarkers were tested in independent chemical exposures for specificity using quantitative reverse transcription polymerase chain reaction. Six genes were confirmed as differentially regulated bythe selected chemical exposures. Furthermore, each exposure was identified by response of a unique combination (suite) of individual gene expression biomarkers. These results demonstrate the potential for discovery and validation of novel biomarkers of chemical exposures using gene expression analysis, which could have broad applicability in environmental monitoring.

A novel salt-inducible gene SbSI-1 from Salicornia brachiata confers salt and desiccation tolerance in E. coli.

PubMed

Yadav, Narendra Singh; Rashmi, Deo; Singh, Dinkar; Agarwal, Pradeep K; Jha, Bhavanath

2012-02-01

Salicornia brachiata is one of the extreme salt tolerant plants and grows luxuriantly in coastal areas. Previously we have reported isolation and characterization of ESTs from S. brachiata with large number of unknown gene sequences. Reverse Northern analysis showed upregulation and downregulation of few unknown genes in response to salinity. Some of these unknown genes were made full length and their functional analysis is being tested. In this study, we have selected a novel unknown salt inducible gene SbSI-1 (Salicornia brachiata salt inducible-1) for the functional validation. The SbSI-1 (Gen-Bank accession number JF 965339) was made full length and characterized in detail for its functional validation under desiccation and salinity. The SbSI-1 gene is 917 bp long, and contained 437 bp 3' UTR, and 480 bp ORF region encoding 159 amino acids protein with estimated molecular mass of 18.39 kDa and pI 8.58. The real time PCR analysis revealed high transcript expression in salt, desiccation, cold and heat stresses. However, the maximum expression was obtained by desiccation. The ORF region of SbSI-1 was cloned in pET28a vector and transformed in BL21 (DE3) E. coli cells. The SbSI-1 recombinant E. coli cells showed tolerance to desiccation and salinity stress compared to only vector in the presence of stress.

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR.

PubMed

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch.

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR

PubMed Central

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch. PMID:21917859

Evolution of the Bovine TLR Gene Family and Member Associations with Mycobacterium avium Subspecies paratuberculosis Infection

PubMed Central

Fisher, Colleen A.; Bhattarai, Eric K.; Osterstock, Jason B.; Dowd, Scot E.; Seabury, Paul M.; Vikram, Meenu; Whitlock, Robert H.; Schukken, Ynte H.; Schnabel, Robert D.; Taylor, Jeremy F.; Womack, James E.; Seabury, Christopher M.

2011-01-01

Members of the Toll-like receptor (TLR) gene family occupy key roles in the mammalian innate immune system by functioning as sentries for the detection of invading pathogens, thereafter provoking host innate immune responses. We utilized a custom next-generation sequencing approach and allele-specific genotyping assays to detect and validate 280 biallelic variants across all 10 bovine TLR genes, including 71 nonsynonymous single nucleotide polymorphisms (SNPs) and one putative nonsense SNP. Bayesian haplotype reconstructions and median joining networks revealed haplotype sharing between Bos taurus taurus and Bos taurus indicus breeds at every locus, and specialized beef and dairy breeds could not be differentiated despite an average polymorphism density of 1 marker/158 bp. Collectively, 160 tagSNPs and two tag insertion-deletion mutations (indels) were sufficient to predict 100% of the variation at 280 variable sites for both Bos subspecies and their hybrids, whereas 118 tagSNPs and 1 tagIndel predictively captured 100% of the variation at 235 variable sites for B. t. taurus. Polyphen and SIFT analyses of amino acid (AA) replacements encoded by bovine TLR SNPs indicated that up to 32% of the AA substitutions were expected to impact protein function. Classical and newly developed tests of diversity provide strong support for balancing selection operating on TLR3 and TLR8, and purifying selection acting on TLR10. An investigation of the persistence and continuity of linkage disequilibrium (r2≥0.50) between adjacent variable sites also supported the presence of selection acting on TLR3 and TLR8. A case-control study employing validated variants from bovine TLR genes recognizing bacterial ligands revealed six SNPs potentially eliciting small effects on susceptibility to Mycobacterium avium spp paratuberculosis infection in dairy cattle. The results of this study will broadly impact domestic cattle research by providing the necessary foundation to explore several avenues of bovine translational genomics, and the potential for marker-assisted vaccination. PMID:22164200

Complexity of Gene Expression Evolution after Duplication: Protein Dosage Rebalancing

PubMed Central

Rogozin, Igor B.

2014-01-01

Ongoing debates about functional importance of gene duplications have been recently intensified by a heated discussion of the “ortholog conjecture” (OC). Under the OC, which is central to functional annotation of genomes, orthologous genes are functionally more similar than paralogous genes at the same level of sequence divergence. However, a recent study challenged the OC by reporting a greater functional similarity, in terms of gene ontology (GO) annotations and expression profiles, among within-species paralogs compared to orthologs. These findings were taken to indicate that functional similarity of homologous genes is primarily determined by the cellular context of the genes, rather than evolutionary history. Subsequent studies suggested that the OC appears to be generally valid when applied to mammalian evolution but the complete picture of evolution of gene expression also has to incorporate lineage-specific aspects of paralogy. The observed complexity of gene expression evolution after duplication can be explained through selection for gene dosage effect combined with the duplication-degeneration-complementation model. This paper discusses expression divergence of recent duplications occurring before functional divergence of proteins encoded by duplicate genes. PMID:25197576

Development and validation of the JAX Cancer Treatment Profile™ for detection of clinically actionable mutations in solid tumors

PubMed Central

Ananda, Guruprasad; Mockus, Susan; Lundquist, Micaela; Spotlow, Vanessa; Simons, Al; Mitchell, Talia; Stafford, Grace; Philip, Vivek; Stearns, Timothy; Srivastava, Anuj; Barter, Mary; Rowe, Lucy; Malcolm, Joan; Bult, Carol; Karuturi, Radha Krishna Murthy; Rasmussen, Karen; Hinerfeld, Douglas

2015-01-01

Background The continued development of targeted therapeutics for cancer treatment has required the concomitant development of more expansive methods for the molecular profiling of the patient’s tumor. We describe the validation of the JAX Cancer Treatment Profile™ (JAX-CTP™), a next generation sequencing (NGS)-based molecular diagnostic assay that detects actionable mutations in solid tumors to inform the selection of targeted therapeutics for cancer treatment. Methods NGS libraries are generated from DNA extracted from formalin fixed paraffin embedded tumors. Using hybrid capture, the genes of interest are enriched and sequenced on the Illumina HiSeq 2500 or MiSeq sequencers followed by variant detection and functional and clinical annotation for the generation of a clinical report. Results The JAX-CTP™ detects actionable variants, in the form of single nucleotide variations and small insertions and deletions (≤50bp) in 190 genes in specimens with a neoplastic cell content of ≥10%. The JAX-CTP™ is also validated for the detection of clinically actionable gene amplifications. Conclusions There is a lack of consensus in the molecular diagnostics field on the best method for the validation of NGS-based assays in oncology, thus the importance of communicating methods, as contained in this report. The growing number of targeted therapeutics and the complexity of the tumor genome necessitates continued development and refinement of advanced assays for tumor profiling to enable precision cancer treatment. PMID:25562415

Integrated Analysis of Long Noncoding RNA and mRNA Expression Profile in Advanced Laryngeal Squamous Cell Carcinoma.

PubMed

Feng, Ling; Wang, Ru; Lian, Meng; Ma, Hongzhi; He, Ning; Liu, Honggang; Wang, Haizhou; Fang, Jugao

2016-01-01

Long non-coding RNA (lncRNA) plays an important role in tumorigenesis. However, the expression pattern and function of lncRNAs in laryngeal squamous cell carcinoma (LSCC) are still unclear. To investigate the aberrantly expressed lncRNAs and mRNAs in advanced LSCC, we screened lncRNA and mRNA expression profiles in 9 pairs of primary Stage IVA LSCC tissues and adjacent non-neoplastic tissues by lncRNA and mRNA integrated microarrays. Gene Ontology and pathway analysis were performed to find out the significant function and pathway of the differentially expressed mRNAs, gene-gene functional interaction network and ceRNA network were constructed to select core mRNAs, and lncRNA-mRNA expression correlation network was built to identify the interactions between lncRNA and mRNA. qRT-PCR was performed to further validate the expressions of selected lncRNAs and mRNAs in advanced LSCC. We found 1459 differentially expressed lncRNAs and 2381 differentially expressed mRNAs, including 846 up-regulated lncRNAs and 613 down-regulated lncRNAs, 1542 up-regulated mRNAs and 839 down-regulated mRNAs. The mRNAs ITGB1, HIF1A, and DDIT4 were selected as core mRNAs, which are mainly involved in biological processes, such as matrix organization, cell cycle, adhesion, and metabolic pathway. LncRNA-mRNA expression correlation network showed LncRNA NR_027340, MIR31HG were positively correlated with ITGB1, HIF1A respectively. LncRNA SOX2-OT was negatively correlated with DDIT4. qRT-PCR further validated the expression of these lncRNAs and mRNAs. The work provides convincing evidence that the identified lncRNAs and mRNAs are potential biomarkers in advanced LSCC for further future studies.

Evaluation of stability and validation of reference genes for RT-qPCR expression studies in rice plants under water deficit.

PubMed

Auler, Priscila Ariane; Benitez, Letícia Carvalho; do Amaral, Marcelo Nogueira; Vighi, Isabel Lopes; Dos Santos Rodrigues, Gabriela; da Maia, Luciano Carlos; Braga, Eugenia Jacira Bolacel

2017-05-01

Many studies use strategies that allow for the identification of a large number of genes expressed in response to different stress conditions to which the plant is subjected throughout its cycle. In order to obtain accurate and reliable results in gene expression studies, it is necessary to use reference genes, which must have uniform expression in the majority of cells in the organism studied. RNA isolation of leaves and expression analysis in real-time quantitative polymerase chain reaction (RT-qPCR) were carried out. In this study, nine candidate reference genes were tested, actin 11 (ACT11), ubiquitin conjugated to E2 enzyme (UBC-E2), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), beta tubulin (β-tubulin), eukaryotic initiation factor 4α (eIF-4α), ubiquitin 10 (UBQ10), ubiquitin 5 (UBQ5), aquaporin TIP41 (TIP41-Like) and cyclophilin, in two genotypes of rice, AN Cambará and BRS Querência, with different levels of soil moisture (20%, 10% and recovery) in the vegetative (V5) and reproductive stages (period preceding flowering). Currently, there are different softwares that perform stability analyses and define the most suitable reference genes for a particular study. In this study, we used five different methods: geNorm, BestKeeper, ΔCt method, NormFinder and RefFinder. The results indicate that UBC-E2 and UBQ5 can be used as reference genes in all samples and softwares evaluated. The genes β-tubulin and eIF-4α, traditionally used as reference genes, along with GAPDH, presented lower stability values. The gene expression of basic leucine zipper (bZIP23 and bZIP72) was used to validate the selected reference genes, demonstrating that the use of an inappropriate reference can induce erroneous results.

TARGET Research Goals

Cancer.gov

TARGET researchers use various sequencing and array-based methods to examine the genomes, transcriptomes, and for some diseases epigenomes of select childhood cancers. This “multi-omic” approach generates a comprehensive profile of molecular alterations for each cancer type. Alterations are changes in DNA or RNA, such as rearrangements in chromosome structure or variations in gene expression, respectively. Through computational analyses and assays to validate biological function, TARGET researchers predict which alterations disrupt the function of a gene or pathway and promote cancer growth, progression, and/or survival. Researchers identify candidate therapeutic targets and/or prognostic markers from the cancer-associated alterations.

Development and validation of qualitative SYBR®Green real-time PCR for detection and discrimination of Listeria spp. and Listeria monocytogenes.

PubMed

Barbau-Piednoir, Elodie; Botteldoorn, Nadine; Yde, Marc; Mahillon, Jacques; Roosens, Nancy H

2013-05-01

A combination of four qualitative SYBR®Green qPCR screening assays targeting two levels of discrimination: Listeria genus (except Listeria grayi) and Listeria monocytogenes, is presented. These assays have been developed to be run simultaneously using the same polymerase chain reaction (PCR) programme. The paper also proposes a new validation procedure to specifically validate qPCR assays applied to food microbiology according to two guidelines: the ISO 22118 norm and the "Definition of minimum performance requirements for analytical methods of GMO testing". The developed assays target the iap, prs and hlyA genes that belong to or neighbour the virulence cluster of Listeria spp. The selected primers were designed to amplify short fragments (60 to 103 bp) in order to obtain optimal PCR efficiency (between 97 and 107 % efficiency). The limit of detection of the SYBR®Green qPCR assays is two to five copies of target genes per qPCR reaction. These assays are highly accurate (98.08 and 100 % accuracy for the Listeria spp. and L. monocytogenes assays, respectively).

Expression profiling of endometrium from women with endometriosis reveals candidate genes for disease-based implantation failure and infertility.

PubMed

Kao, L C; Germeyer, A; Tulac, S; Lobo, S; Yang, J P; Taylor, R N; Osteen, K; Lessey, B A; Giudice, L C

2003-07-01

Endometriosis is clinically associated with pelvic pain and infertility, with implantation failure strongly suggested as an underlying cause for the observed infertility. Eutopic endometrium of women with endometriosis provides a unique experimental paradigm for investigation into molecular mechanisms of reproductive dysfunction and an opportunity to identify specific markers for this disease. We applied paralleled gene expression profiling using high-density oligonucleotide microarrays to investigate differentially regulated genes in endometrium from women with vs. without endometriosis. Fifteen endometrial biopsy samples (obtained during the window of implantation from eight subjects with and seven subjects without endometriosis) were processed for expression profiling on Affymetrix Hu95A microarrays. Data analysis was conducted with GeneChip Analysis Suite, version 4.01, and GeneSpring version 4.0.4. Nonparametric testing was applied, using a P value of 0.05, to assess statistical significance. Of the 12,686 genes analyzed, 91 genes were significantly increased more than 2-fold in their expression, and 115 genes were decreased more than 2-fold. Unsupervised clustering demonstrated down-regulation of several known cell adhesion molecules, endometrial epithelial secreted proteins, and proteins not previously known to be involved in the pathogenesis of endometriosis, as well as up-regulated genes. Selected dysregulated genes were randomly chosen and validated with RT-PCR and/or Northern/dot-blot analyses, and confirmed up-regulation of collagen alpha2 type I, 2.6-fold; bile salt export pump, 2.0-fold; and down-regulation of N-acetylglucosamine-6-O-sulfotransferase (important in synthesis of L-selectin ligands), 1.7-fold; glycodelin, 51.5-fold; integrin alpha2, 1.8-fold; and B61 (Ephrin A1), 4.5-fold. Two-way overlapping layer analysis used to compare endometrial genes in the window of implantation from women with and without endometriosis further identified three unique groups of target genes, which differ with respect to the implantation window and the presence of disease. Group 1 target genes are up-regulated during the normal window of implantation but significantly decreased in women with endometriosis: IL-15, proline-rich protein, B61, Dickkopf-1, glycodelin, N-acetylglucosamine-6-O-sulfotransferase, G0S2 protein, and purine nucleoside phosphorylase. Group 2 genes are normally down-regulated during the window of implantation but are significantly increased with endometriosis: semaphorin E, neuronal olfactomedin-related endoplasmic reticulum localized protein mRNA and Sam68-like phosphotyrosine protein alpha. Group 3 consists of a single gene, neuronal pentraxin II, normally down-regulated during the window of implantation and further decreased in endometrium from women with endometriosis. The data support dysregulation of select genes leading to an inhospitable environment for implantation, including genes involved in embryonic attachment, embryo toxicity, immune dysfunction, and apoptotic responses, as well as genes likely contributing to the pathogenesis of endometriosis, including aromatase, progesterone receptor, angiogenic factors, and others. Identification and validation of selected genes and their functions will contribute to uncovering previously unknown mechanism(s) underlying implantation failure in women with endometriosis and infertility, mechanisms underlying the pathogenesis of endometriosis and providing potential new targets for diagnostic screening and intervention.

cDNA-AFLP analysis reveals differential gene expression in compatible interaction of wheat challenged with Puccinia striiformis f. sp. tritici

PubMed Central

Wang, Xiaojie; Tang, Chunlei; Zhang, Gang; Li, Yingchun; Wang, Chenfang; Liu, Bo; Qu, Zhipeng; Zhao, Jie; Han, Qingmei; Huang, Lili; Chen, Xianming; Kang, Zhensheng

2009-01-01

Background Puccinia striiformis f. sp. tritici is a fungal pathogen causing stripe rust, one of the most important wheat diseases worldwide. The fungus is strictly biotrophic and thus, completely dependent on living host cells for its reproduction, which makes it difficult to study genes of the pathogen. In spite of its economic importance, little is known about the molecular basis of compatible interaction between the pathogen and wheat host. In this study, we identified wheat and P. striiformis genes associated with the infection process by conducting a large-scale transcriptomic analysis using cDNA-AFLP. Results Of the total 54,912 transcript derived fragments (TDFs) obtained using cDNA-AFLP with 64 primer pairs, 2,306 (4.2%) displayed altered expression patterns after inoculation, of which 966 showed up-regulated and 1,340 down-regulated. 186 TDFs produced reliable sequences after sequencing of 208 TDFs selected, of which 74 (40%) had known functions through BLAST searching the GenBank database. Majority of the latter group had predicted gene products involved in energy (13%), signal transduction (5.4%), disease/defence (5.9%) and metabolism (5% of the sequenced TDFs). BLAST searching of the wheat stem rust fungus genome database identified 18 TDFs possibly from the stripe rust pathogen, of which 9 were validated of the pathogen origin using PCR-based assays followed by sequencing confirmation. Of the 186 reliable TDFs, 29 homologous to genes known to play a role in disease/defense, signal transduction or uncharacterized genes were further selected for validation of cDNA-AFLP expression patterns using qRT-PCR analyses. Results confirmed the altered expression patterns of 28 (96.5%) genes revealed by the cDNA-AFLP technique. Conclusion The results show that cDNA-AFLP is a reliable technique for studying expression patterns of genes involved in the wheat-stripe rust interactions. Genes involved in compatible interactions between wheat and the stripe rust pathogen were identified and their expression patterns were determined. The present study should be helpful in elucidating the molecular basis of the infection process, and identifying genes that can be targeted for inhibiting the growth and reproduction of the pathogen. Moreover, this study can also be used to elucidate the defence responses of the genes that were of plant origin. PMID:19566949

Discovery and Characterization of a Highly Potent and Selective Aminopyrazoline-Based in Vivo Probe (BAY-598) for the Protein Lysine Methyltransferase SMYD2.

PubMed

Eggert, Erik; Hillig, Roman C; Koehr, Silke; Stöckigt, Detlef; Weiske, Jörg; Barak, Naomi; Mowat, Jeffrey; Brumby, Thomas; Christ, Clara D; Ter Laak, Antonius; Lang, Tina; Fernandez-Montalvan, Amaury E; Badock, Volker; Weinmann, Hilmar; Hartung, Ingo V; Barsyte-Lovejoy, Dalia; Szewczyk, Magdalena; Kennedy, Steven; Li, Fengling; Vedadi, Masoud; Brown, Peter J; Santhakumar, Vijayaratnam; Arrowsmith, Cheryl H; Stellfeld, Timo; Stresemann, Carlo

2016-05-26

Protein lysine methyltransferases have recently emerged as a new target class for the development of inhibitors that modulate gene transcription or signaling pathways. SET and MYND domain containing protein 2 (SMYD2) is a catalytic SET domain containing methyltransferase reported to monomethylate lysine residues on histone and nonhistone proteins. Although several studies have uncovered an important role of SMYD2 in promoting cancer by protein methylation, the biology of SMYD2 is far from being fully understood. Utilization of highly potent and selective chemical probes for target validation has emerged as a concept which circumvents possible limitations of knockdown experiments and, in particular, could result in an improved exploration of drug targets with a complex underlying biology. Here, we report the development of a potent, selective, and cell-active, substrate-competitive inhibitor of SMYD2, which is the first reported inhibitor suitable for in vivo target validation studies in rodents.

Identification of Candidate Genes Involved in the Salt Tolerance of Date Palm (Phoenix dactylifera L.) Based on a Yeast Functional Bioassay.

PubMed

Patankar, Himanshu V; Al-Harrasi, Ibtisam; Al-Yahyai, Rashid; Yaish, Mahmoud W

2018-06-01

Although date palm is a relatively salt-tolerant plant, the molecular basis of this tolerance is complex and poorly understood. Therefore, this study aimed to identify the genes involved in salinity tolerance using a basic yeast functional bioassay. To achieve this, a date palm cDNA library was overexpressed in Saccharomyces cerevisiae cells. The expression levels of selected genes that make yeast cells tolerant to salt were subsequently validated in the leaf and root tissues of date palm seedlings using a quantitative PCR method. About 6000 yeast transformant cells were replica printed and screened on a synthetic minimal medium containing 1.0 M of NaCl. The screening results showed the presence of 62 salt-tolerant transformant colonies. Sequence analysis of the recombinant yeast plasmids revealed the presence of a group of genes with potential salt-tolerance functions, such as aquaporins (PIP), serine/threonine protein kinases (STKs), ethylene-responsive transcription factor 1 (ERF1), and peroxidases (PRX). The expression pattern of the selected genes endorsed the hypothesis that these genes may be involved in salinity tolerance, as they showed a significant (p < 0.05) overexpression trend in both the leaf and root tissues in response to salinity. The genes identified in this project are suitable candidates for the further functional characterization of date palms.

Reanalysis of RNA-Sequencing Data Reveals Several Additional Fusion Genes with Multiple Isoforms

PubMed Central

Kangaspeska, Sara; Hultsch, Susanne; Edgren, Henrik; Nicorici, Daniel; Murumägi, Astrid; Kallioniemi, Olli

2012-01-01

RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts. PMID:23119097

Reanalysis of RNA-sequencing data reveals several additional fusion genes with multiple isoforms.

PubMed

Kangaspeska, Sara; Hultsch, Susanne; Edgren, Henrik; Nicorici, Daniel; Murumägi, Astrid; Kallioniemi, Olli

2012-01-01

RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts.

Genome-Wide Identification of CBX2 Targets: Insights in the Human Sex Development Network

PubMed Central

Eid, Wassim; Opitz, Lennart

2015-01-01

Chromobox homolog 2 (CBX2) is a chromatin modifier that plays an important role in sexual development and its disorders (disorders of sex development [DSD]), yet the exact rank and function of human CBX2 in this pathway remains unclear. Here, we performed large-scale mapping and analysis of in vivo target loci of the protein CBX2 in Sertoli-like NT-2D1 cells, using the DNA adenine methyltransferase identification technique. We identified close to 1600 direct targets for CBX2. Intriguingly, validation of selected candidate genes using qRT-PCR in cells overexpressing CBX2 or in which CBX2 has been knocked down indicated that several CBX2-responsive genes encode proteins that are involved in DSD. We further validated these effects on the candidate genes using a mutated CBX2 causing DSD in human patient. Overall, our findings suggest that CBX2 role in the sex development cascade is to stimulate the male pathway and concurrently inhibit the female pathway. These data provide fundamental insights into potential etiology of DSD. PMID:25569159

Gene transfer preferentially selects MHC class I positive tumour cells and enhances tumour immunogenicity.

PubMed

Hacker, Ulrich T; Schildhauer, Ines; Barroso, Margarita Céspedes; Kofler, David M; Gerner, Franz M; Mysliwietz, Josef; Buening, Hildegard; Hallek, Michael; King, Susan B S

2006-05-01

The modulated expression of MHC class I on tumour tissue is well documented. Although the effect of MHC class I expression on the tumorigenicity and immunogenicity of MHC class I negative tumour cell lines has been rigorously studied, less is known about the validity of gene transfer and selection in cell lines with a mixed MHC class I phenotype. To address this issue we identified a C26 cell subline that consists of distinct populations of MHC class I (H-2D/K) positive and negative cells. Transient transfection experiments using liposome-based transfer showed a lower transgene expression in MHC class I negative cells. In addition, MHC class I negative cells were more sensitive to antibiotic selection. This led to the generation of fully MHC class I positive cell lines. In contrast to C26 cells, all transfectants were rejected in vivo and induced protection against the parental tumour cells in rechallenge experiments. Tumour cell specificity of the immune response was demonstrated in in vitro cytokine secretion and cytotoxicity assays. Transfectants expressing CD40 ligand and hygromycin phosphotransferase were not more immunogenic than cells expressing hygromycin resistance alone. We suggest that the MHC class I positive phenotype of the C26 transfectants had a bearing on their immunogenicity, because selected MHC class I positive cells were more immunogenic than parental C26 cells and could induce specific anti-tumour immune responses. These data demonstrate that the generation of tumour cell transfectants can lead to the selection of subpopulations that show an altered phenotype compared to the parental cell line and display altered immunogenicity independent of selection marker genes or other immune modulatory genes. Our results show the importance of monitoring gene transfer in the whole tumour cell population, especially for the evaluation of in vivo therapies targeted to heterogeneous tumour cell populations.

Urine cell-based DNA methylation classifier for monitoring bladder cancer.

PubMed

van der Heijden, Antoine G; Mengual, Lourdes; Ingelmo-Torres, Mercedes; Lozano, Juan J; van Rijt-van de Westerlo, Cindy C M; Baixauli, Montserrat; Geavlete, Bogdan; Moldoveanud, Cristian; Ene, Cosmin; Dinney, Colin P; Czerniak, Bogdan; Schalken, Jack A; Kiemeney, Lambertus A L M; Ribal, Maria J; Witjes, J Alfred; Alcaraz, Antonio

2018-01-01

Current standard methods used to detect and monitor bladder cancer (BC) are invasive or have low sensitivity. This study aimed to develop a urine methylation biomarker classifier for BC monitoring and validate this classifier in patients in follow-up for bladder cancer (PFBC). Voided urine samples ( N  = 725) from BC patients, controls, and PFBC were prospectively collected in four centers. Finally, 626 urine samples were available for analysis. DNA was extracted from the urinary cells and bisulfite modificated, and methylation status was analyzed using pyrosequencing. Cytology was available from a subset of patients ( N  = 399). In the discovery phase, seven selected genes from the literature ( CDH13 , CFTR , NID2 , SALL3 , TMEFF2 , TWIST1 , and VIM2 ) were studied in 111 BC and 57 control samples. This training set was used to develop a gene classifier by logistic regression and was validated in 458 PFBC samples (173 with recurrence). A three-gene methylation classifier containing CFTR , SALL3 , and TWIST1 was developed in the training set (AUC 0.874). The classifier achieved an AUC of 0.741 in the validation series. Cytology results were available for 308 samples from the validation set. Cytology achieved AUC 0.696 whereas the classifier in this subset of patients reached an AUC 0.768. Combining the methylation classifier with cytology results achieved an AUC 0.86 in the validation set, with a sensitivity of 96%, a specificity of 40%, and a positive and negative predictive value of 56 and 92%, respectively. The combination of the three-gene methylation classifier and cytology results has high sensitivity and high negative predictive value in a real clinical scenario (PFBC). The proposed classifier is a useful test for predicting BC recurrence and decrease the number of cystoscopies in the follow-up of BC patients. If only patients with a positive combined classifier result would be cystoscopied, 36% of all cystoscopies can be prevented.

Multigene signature for predicting prognosis of patients with 1p19q co-deletion diffuse glioma.

PubMed

Hu, Xin; Martinez-Ledesma, Emmanuel; Zheng, Siyuan; Kim, Hoon; Barthel, Floris; Jiang, Tao; Hess, Kenneth R; Verhaak, Roel G W

2017-06-01

Co-deletion of 1p and 19q marks a diffuse glioma subtype associated with relatively favorable overall survival; however, heterogeneous clinical outcomes are observed within this category. We assembled gene expression profiles and sample annotation of 374 glioma patients carrying the 1p/19q co-deletion. We predicted 1p/19q status using gene expression when annotation was missing. A first cohort was randomly split into training (n = 170) and a validation dataset (n = 163). A second validation set consisted of 41 expression profiles. An elastic-net penalized Cox proportional hazards model was applied to build a classifier model through cross-validation within the training dataset. The selected 35-gene signature was used to identify high-risk and low-risk groups in the validation set, which showed significantly different overall survival (P = .00058, log-rank test). For time-to-death events, the high-risk group predicted by the gene signature yielded a hazard ratio of 1.78 (95% confidence interval, 1.02-3.11). The signature was also significantly associated with clinical outcome in the The Cancer Genome Atlas (CGA) IDH-mutant 1p/19q wild-type and IDH-wild-type glioma cohorts. Pathway analysis suggested that high risk was associated with increased acetylation activity and inflammatory response. Tumor purity was found to be significantly decreased in high-risk IDH-mutant with 1p/19q co-deletion gliomas and IDH-wild-type glioblastomas but not in IDH-wild-type lower grade or IDH-mutant, non-co-deleted gliomas. We identified a 35-gene signature that identifies high-risk and low-risk categories of 1p/19q positive glioma patients. We have demonstrated heterogeneity amongst a relatively new glioma subtype and provided a stepping stone towards risk stratification. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Protective pathways against colitis mediated by appendicitis and appendectomy.

PubMed

Cheluvappa, R; Luo, A S; Palmer, C; Grimm, M C

2011-09-01

Appendicitis followed by appendectomy (AA) at a young age protects against inflammatory bowel disease (IBD). Using a novel murine appendicitis model, we showed that AA protected against subsequent experimental colitis. To delineate genes/pathways involved in this protection, AA was performed and samples harvested from the most distal colon. RNA was extracted from four individual colonic samples per group (AA group and double-laparotomy control group) and each sample microarray analysed followed by gene-set enrichment analysis (GSEA). The gene-expression study was validated by quantitative reverse transcription-polymerase chain reaction (RT-PCR) of 14 selected genes across the immunological spectrum. Distal colonic expression of 266 gene-sets was up-regulated significantly in AA group samples (false discovery rates < 1%; P-value < 0·001). Time-course RT-PCR experiments involving the 14 genes displayed down-regulation over 28 days. The IBD-associated genes tnfsf10, SLC22A5, C3, ccr5, irgm, ptger4 and ccl20 were modulated in AA mice 3 days after surgery. Many key immunological and cellular function-associated gene-sets involved in the protective effect of AA in experimental colitis were identified. The down-regulation of 14 selected genes over 28 days after surgery indicates activation, repression or de-repression of these genes leading to downstream AA-conferred anti-colitis protection. Further analysis of these genes, profiles and biological pathways may assist in developing better therapeutic strategies in the management of intractable IBD. © 2011 The Authors. Clinical and Experimental Immunology © 2011 British Society for Immunology.

Identification of genes showing differential expression profile associated with growth rate in skeletal muscle tissue of Landrace weanling pig.

PubMed

Komatsu, Yuuta; Sukegawa, Shin; Yamashita, Mai; Katsuda, Naoki; Tong, Bin; Ohta, Takeshi; Kose, Hiroyuki; Yamada, Takahisa

2016-06-01

Suppression subtractive hybridization was used to identify genes showing differential expression profile associated with growth rate in skeletal muscle tissue of Landrace weanling pig. Two subtracted cDNA populations were generated from musculus longissimus muscle tissues of selected pigs with extreme expected breeding values at the age of 100 kg. Three upregulated genes (EEF1A2, TSG101 and TTN) and six downregulated genes (ATP5B, ATP5C1, COQ3, HADHA, MYH1 and MYH7) in pig with genetic propensity for higher growth rate were identified by sequence analysis of 12 differentially expressed clones selected by differential screening following the generation of the subtracted cDNA population. Real-time PCR analysis confirmed difference in expression profiles of the identified genes in musculus longissimus muscle tissues between the two Landrace weanling pig groups with divergent genetic propensity for growth rate. Further, differential expression of the identified genes except for the TTN was validated by Western blot analysis. Additionally, the eight genes other than the ATP5C1 colocalized with the same chromosomal positions as QTLs that have been previously identified for growth rate traits. Finally, the changes of expression predicted from gene function suggested association of upregulation of expression of the EEF1A2, TSG101 and TTN genes and downregulation of the ATP5B, ATP5C1, COQ3, HADHA, MYH1 and MYH7 gene expression with increased growth rate. The identified genes will provide an important insight in understanding the molecular mechanism underlying growth rate in Landrace pig breed.

Prediction of plant lncRNA by ensemble machine learning classifiers.

PubMed

Simopoulos, Caitlin M A; Weretilnyk, Elizabeth A; Golding, G Brian

2018-05-02

In plants, long non-protein coding RNAs are believed to have essential roles in development and stress responses. However, relative to advances on discerning biological roles for long non-protein coding RNAs in animal systems, this RNA class in plants is largely understudied. With comparatively few validated plant long non-coding RNAs, research on this potentially critical class of RNA is hindered by a lack of appropriate prediction tools and databases. Supervised learning models trained on data sets of mostly non-validated, non-coding transcripts have been previously used to identify this enigmatic RNA class with applications largely focused on animal systems. Our approach uses a training set comprised only of empirically validated long non-protein coding RNAs from plant, animal, and viral sources to predict and rank candidate long non-protein coding gene products for future functional validation. Individual stochastic gradient boosting and random forest classifiers trained on only empirically validated long non-protein coding RNAs were constructed. In order to use the strengths of multiple classifiers, we combined multiple models into a single stacking meta-learner. This ensemble approach benefits from the diversity of several learners to effectively identify putative plant long non-coding RNAs from transcript sequence features. When the predicted genes identified by the ensemble classifier were compared to those listed in GreeNC, an established plant long non-coding RNA database, overlap for predicted genes from Arabidopsis thaliana, Oryza sativa and Eutrema salsugineum ranged from 51 to 83% with the highest agreement in Eutrema salsugineum. Most of the highest ranking predictions from Arabidopsis thaliana were annotated as potential natural antisense genes, pseudogenes, transposable elements, or simply computationally predicted hypothetical protein. Due to the nature of this tool, the model can be updated as new long non-protein coding transcripts are identified and functionally verified. This ensemble classifier is an accurate tool that can be used to rank long non-protein coding RNA predictions for use in conjunction with gene expression studies. Selection of plant transcripts with a high potential for regulatory roles as long non-protein coding RNAs will advance research in the elucidation of long non-protein coding RNA function.

Mapping QTLs for water-use efficiency reveals the potential candidate genes involved in regulating the trait in apple under drought stress.

PubMed

Wang, Haibo; Zhao, Shuang; Mao, Ke; Dong, Qinglong; Liang, Bowen; Li, Chao; Wei, Zhiwei; Li, Mingjun; Ma, Fengwang

2018-06-26

Improvement of water-use efficiency (WUE) can effectively reduce production losses caused by drought stress. A better understanding of the genetic determination of WUE in crops under drought stress has great potential value for developing cultivars adapted to arid regions. To identify the genetic loci associated with WUE and reveal genes responsible for the trait in apple, we aim to map the quantitative trait loci (QTLs) for carbon isotope composition, the proxy for WUE, applying two contrasting irrigating regimes over the two-year experiment and search for the candidate genes encompassed in the mapped QTLs. We constructed a high-density genetic linkage map with 10,172 markers of apple, using single nucleotide polymorphism (SNP) markers obtained through restriction site-associated DNA sequencing (RADseq) and a final segregating population of 350 seedlings from the cross of Honeycrisp and Qinguan. In total, 33 QTLs were identified for carbon isotope composition in apple under both well-watered and drought-stressed conditions. Three QTLs were stable over 2 years under drought stress on linkage groups LG8, LG15 and LG16, as validated by Kompetitive Allele-Specific PCR (KASP) assays. In those validated QTLs, 258 genes were screened according to their Gene Ontology functional annotations. Among them, 28 genes were identified, which exhibited significant responses to drought stress in 'Honeycrisp' and/or 'Qinguan'. These genes are involved in signaling, photosynthesis, response to stresses, carbohydrate metabolism, protein metabolism and modification, hormone metabolism and transport, transport, respiration, transcriptional regulation, and development regulation. They, especially those for photoprotection and relevant signal transduction, are potential candidate genes connected with WUE regulation in drought-stressed apple. We detected three stable QTLs for carbon isotope composition in apple under drought stress over 2 years, and validated them by KASP assay. Twenty-eight candidate genes encompassed in these QTLs were identified. These stable genetic loci and series of genes provided here serve as a foundation for further studies on marker-assisted selection of high WUE and regulatory mechanism of WUE in apple exposed to drought conditions, respectively.

Effective Classification and Gene Expression Profiling for the Facioscapulohumeral Muscular Dystrophy

PubMed Central

González-Navarro, Félix F.; Belanche-Muñoz, Lluís A.; Silva-Colón, Karen A.

2013-01-01

The Facioscapulohumeral Muscular Dystrophy (FSHD) is an autosomal dominant neuromuscular disorder whose incidence is estimated in about one in 400,000 to one in 20,000. No effective therapeutic strategies are known to halt progression or reverse muscle weakness and atrophy. It is known that the FSHD is caused by modifications located within a D4ZA repeat array in the chromosome 4q, while recent advances have linked these modifications to the DUX4 gene. Unfortunately, the complete mechanisms responsible for the molecular pathogenesis and progressive muscle weakness still remain unknown. Although there are many studies addressing cancer databases from a machine learning perspective, there is no such precedent in the analysis of the FSHD. This study aims to fill this gap by analyzing two specific FSHD databases. A feature selection algorithm is used as the main engine to select genes promoting the highest possible classification capacity. The combination of feature selection and classification aims at obtaining simple models (in terms of very low numbers of genes) capable of good generalization, that may be associated with the disease. We show that the reported method is highly efficient in finding genes to discern between healthy cases (not affected by the FSHD) and FSHD cases, allowing the discovery of very parsimonious models that yield negligible repeated cross-validation error. These models in turn give rise to very simple decision procedures in the form of a decision tree. Current biological evidence regarding these genes shows that they are linked to skeletal muscle processes concerning specific human conditions. PMID:24349187

SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models

PubMed Central

2014-01-01

Background Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. Results SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. Conclusions SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/. PMID:24980894

Filtered selection coupled with support vector machines generate a functionally relevant prediction model for colorectal cancer

PubMed Central

Gabere, Musa Nur; Hussein, Mohamed Aly; Aziz, Mohammad Azhar

2016-01-01

Purpose There has been considerable interest in using whole-genome expression profiles for the classification of colorectal cancer (CRC). The selection of important features is a crucial step before training a classifier. Methods In this study, we built a model that uses support vector machine (SVM) to classify cancer and normal samples using Affymetrix exon microarray data obtained from 90 samples of 48 patients diagnosed with CRC. From the 22,011 genes, we selected the 20, 30, 50, 100, 200, 300, and 500 genes most relevant to CRC using the minimum-redundancy–maximum-relevance (mRMR) technique. With these gene sets, an SVM model was designed using four different kernel types (linear, polynomial, radial basis function [RBF], and sigmoid). Results The best model, which used 30 genes and RBF kernel, outperformed other combinations; it had an accuracy of 84% for both ten fold and leave-one-out cross validations in discriminating the cancer samples from the normal samples. With this 30 genes set from mRMR, six classifiers were trained using random forest (RF), Bayes net (BN), multilayer perceptron (MLP), naïve Bayes (NB), reduced error pruning tree (REPT), and SVM. Two hybrids, mRMR + SVM and mRMR + BN, were the best models when tested on other datasets, and they achieved a prediction accuracy of 95.27% and 91.99%, respectively, compared to other mRMR hybrid models (mRMR + RF, mRMR + NB, mRMR + REPT, and mRMR + MLP). Ingenuity pathway analysis was used to analyze the functions of the 30 genes selected for this model and their potential association with CRC: CDH3, CEACAM7, CLDN1, IL8, IL6R, MMP1, MMP7, and TGFB1 were predicted to be CRC biomarkers. Conclusion This model could be used to further develop a diagnostic tool for predicting CRC based on gene expression data from patient samples. PMID:27330311

Posttranslationally modified progesterone receptors direct ligand-specific expression of breast cancer stem cell-associated gene programs.

PubMed

Knutson, Todd P; Truong, Thu H; Ma, Shihong; Brady, Nicholas J; Sullivan, Megan E; Raj, Ganesh; Schwertfeger, Kathryn L; Lange, Carol A

2017-04-17

Estrogen and progesterone are potent breast mitogens. In addition to steroid hormones, multiple signaling pathways input to estrogen receptor (ER) and progesterone receptor (PR) actions via posttranslational events. Protein kinases commonly activated in breast cancers phosphorylate steroid hormone receptors (SRs) and profoundly impact their activities. To better understand the role of modified PRs in breast cancer, we measured total and phospho-Ser294 PRs in 209 human breast tumors represented on 2754 individual tissue spots within a tissue microarray and assayed the regulation of this site in human tumor explants cultured ex vivo. To complement this analysis, we assayed PR target gene regulation in T47D luminal breast cancer models following treatment with progestin (promegestone; R5020) and antiprogestins (mifepristone, onapristone, or aglepristone) in conditions under which the receptor is regulated by Lys388 SUMOylation (K388 intact) or is SUMO-deficient (via K388R mutation to mimic persistent Ser294 phosphorylation). Selected phospho-PR-driven target genes were validated by qRT-PCR and following RUNX2 shRNA knockdown in breast cancer cell lines. Primary and secondary mammosphere assays were performed to implicate phospho-Ser294 PRs, epidermal growth factor signaling, and RUNX2 in breast cancer stem cell biology. Phospho-Ser294 PR species were abundant in a majority (54%) of luminal breast tumors, and PR promoter selectivity was exquisitely sensitive to posttranslational modifications. Phospho-PR expression and target gene programs were significantly associated with invasive lobular carcinoma (ILC). Consistent with our finding that activated phospho-PRs undergo rapid ligand-dependent turnover, unique phospho-PR gene signatures were most prevalent in breast tumors clinically designated as PR-low to PR-null (luminal B) and included gene sets associated with cancer stem cell biology (HER2, PAX2, AHR, AR, RUNX). Validation studies demonstrated a requirement for RUNX2 in the regulation of selected phospho-PR target genes (SLC37A2). In vitro mammosphere formation assays support a role for phospho-Ser294-PRs via growth factor (EGF) signaling as well as RUNX2 as potent drivers of breast cancer stem cell fate. We conclude that PR Ser294 phosphorylation is a common event in breast cancer progression that is required to maintain breast cancer stem cell fate, in part via cooperation with growth factor-initiated signaling pathways and key phospho-PR target genes including SLC37A2 and RUNX2. Clinical measurement of phosphorylated PRs should be considered a useful marker of breast tumor stem cell potential. Alternatively, unique phospho-PR target gene sets may provide useful tools with which to identify patients likely to respond to selective PR modulators that block PR Ser294 phosphorylation as part of rational combination (i.e., with antiestrogens) endocrine therapies designed to durably block breast cancer recurrence.

DNA methylation as an adjunct to histopathology to detect prevalent, inconspicuous dysplasia and early-stage neoplasia in Barrett’s esophagus

PubMed Central

Alvi, Muhammad A; Liu, Xinxue; O’Donovan, Maria; Newton, Richard; Wernisch, Lorenz; Shannon, Nicholas B; Shariff, Kareem; di Pietro, Massimiliano; Bergman, Jacques J G H M; Ragunath, Krish; Fitzgerald, Rebecca C

2016-01-01

Purpose Endoscopic surveillance of Barrett’s esophagus (BE) is problematic because dysplasia/early-stage neoplasia are frequently invisible and likely to be missed due to sampling bias. Molecular abnormalities may be more diffuse than dysplasia. The aim was therefore to test whether DNA methylation; especially on imprinted and X-chromosome genes; is able to detect dysplasia/early-stage neoplasia. Experimental design 27K methylation arrays were used to find genes best able to differentiate between 22 BE and 24 esophageal adenocarcinoma (EAC) samples. These were validated using pyrosequencing on a retrospective cohort (60 BE, 36 dysplastic and 90 EAC) and then in a prospective multicenter study (98 BE patients, including 28 dysplastic and 9 early EAC) designed to utilize biomarkers to stratify patients according to their prevalent dysplasia/EAC status. Results 23% genes on the array, including 7% of X-linked and 69% of imprinted genes, demonstrated statistically significant changes in methylation in EAC vs. BE (Wilcoxon P<0.05). 6/7 selected candidate genes were successfully internally (Pearson’s P<0.01) and externally validated (ANOVA P<0.001). Four genes (SLC22A18, PIGR, GJA12 and RIN2) showed the greatest area under curve (0.988) to distinguish between BE and dysplasia/EAC in the retrospective cohort. This methylation panel was able to stratify patients from the prospective cohort into three risk groups based on the number of genes methylated (low risk: <2 genes, intermediate: 2 and high: >2). Conclusion Widespread DNA methylation changes were observed in Barrett’s carcinogenesis including ≈70% of known imprinted genes. A four-gene methylation panel stratified BE patients into three risk groups with potential clinical utility. PMID:23243219

Expression profiling of chickpea genes differentially regulated during a resistance response to Ascochyta rabiei.

PubMed

Coram, Tristan E; Pang, Edwin C K

2006-11-01

Using microarray technology and a set of chickpea (Cicer arietinum L.) unigenes, grasspea (Lathyrus sativus L.) expressed sequence tags (ESTs) and lentil (Lens culinaris Med.) resistance gene analogues, the ascochyta blight (Ascochyta rabiei (Pass.) L.) resistance response was studied in four chickpea genotypes, including resistant, moderately resistant, susceptible and wild relative (Cicer echinospermum L.) genotypes. The experimental system minimized environmental effects and was conducted in reference design, in which samples from mock-inoculated controls acted as reference against post-inoculation samples. Robust data quality was achieved through the use of three biological replicates (including a dye swap), the inclusion of negative controls and strict selection criteria for differentially expressed genes, including a fold change cut-off determined by self-self hybridizations, Student's t-test and multiple testing correction (P < 0.05). Microarray observations were also validated by quantitative reverse transcriptase-polymerase chain reaction (RT-PCR). The time course expression patterns of 756 microarray features resulted in the differential expression of 97 genes in at least one genotype at one time point. k-means clustering grouped the genes into clusters of similar observations for each genotype, and comparisons between A. rabiei-resistant and A. rabiei-susceptible genotypes revealed potential gene 'signatures' predictive of effective A. rabiei resistance. These genes included several pathogenesis-related proteins, SNAKIN2 antimicrobial peptide, proline-rich protein, disease resistance response protein DRRG49-C, environmental stress-inducible protein, leucine-zipper protein, polymorphic antigen membrane protein, Ca-binding protein and several unknown proteins. The potential involvement of these genes and their pathways of induction are discussed. This study represents the first large-scale gene expression profiling in chickpea, and future work will focus on the functional validation of the genes of interest.

RUCS: rapid identification of PCR primers for unique core sequences.

PubMed

Thomsen, Martin Christen Frølund; Hasman, Henrik; Westh, Henrik; Kaya, Hülya; Lund, Ole

2017-12-15

Designing PCR primers to target a specific selection of whole genome sequenced strains can be a long, arduous and sometimes impractical task. Such tasks would benefit greatly from an automated tool to both identify unique targets, and to validate the vast number of potential primer pairs for the targets in silico. Here we present RUCS, a program that will find PCR primer pairs and probes for the unique core sequences of a positive genome dataset complement to a negative genome dataset. The resulting primer pairs and probes are in addition to simple selection also validated through a complex in silico PCR simulation. We compared our method, which identifies the unique core sequences, against an existing tool called ssGeneFinder, and found that our method was 6.5-20 times more sensitive. We used RUCS to design primer pairs that would target a set of genomes known to contain the mcr-1 colistin resistance gene. Three of the predicted pairs were chosen for experimental validation using PCR and gel electrophoresis. All three pairs successfully produced an amplicon with the target length for the samples containing mcr-1 and no amplification products were produced for the negative samples. The novel methods presented in this manuscript can reduce the time needed to identify target sequences, and provide a quick virtual PCR validation to eliminate time wasted on ambiguously binding primers. Source code is freely available on https://bitbucket.org/genomicepidemiology/rucs. Web service is freely available on https://cge.cbs.dtu.dk/services/RUCS. mcft@cbs.dtu.dk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

A gene expression inflammatory signature specifically predicts multiple myeloma evolution and patients survival.

PubMed

Botta, C; Di Martino, M T; Ciliberto, D; Cucè, M; Correale, P; Rossi, M; Tagliaferri, P; Tassone, P

2016-12-16

Multiple myeloma (MM) is closely dependent on cross-talk between malignant plasma cells and cellular components of the inflammatory/immunosuppressive bone marrow milieu, which promotes disease progression, drug resistance, neo-angiogenesis, bone destruction and immune-impairment. We investigated the relevance of inflammatory genes in predicting disease evolution and patient survival. A bioinformatics study by Ingenuity Pathway Analysis on gene expression profiling dataset of monoclonal gammopathy of undetermined significance, smoldering and symptomatic-MM, identified inflammatory and cytokine/chemokine pathways as the most progressively affected during disease evolution. We then selected 20 candidate genes involved in B-cell inflammation and we investigated their role in predicting clinical outcome, through univariate and multivariate analyses (log-rank test, logistic regression and Cox-regression model). We defined an 8-genes signature (IL8, IL10, IL17A, CCL3, CCL5, VEGFA, EBI3 and NOS2) identifying each condition (MGUS/smoldering/symptomatic-MM) with 84% accuracy. Moreover, six genes (IFNG, IL2, LTA, CCL2, VEGFA, CCL3) were found independently correlated with patients' survival. Patients whose MM cells expressed high levels of Th1 cytokines (IFNG/LTA/IL2/CCL2) and low levels of CCL3 and VEGFA, experienced the longest survival. On these six genes, we built a prognostic risk score that was validated in three additional independent datasets. In this study, we provide proof-of-concept that inflammation has a critical role in MM patient progression and survival. The inflammatory-gene prognostic signature validated in different datasets clearly indicates novel opportunities for personalized anti-MM treatment.

Biologic Determinants of Tumor Recurrence in Stage II Colon Cancer: Validation Study of the 12-Gene Recurrence Score in Cancer and Leukemia Group B (CALGB) 9581

PubMed Central

Venook, Alan P.; Niedzwiecki, Donna; Lopatin, Margarita; Ye, Xing; Lee, Mark; Friedman, Paula N.; Frankel, Wendy; Clark-Langone, Kim; Millward, Carl; Shak, Steven; Goldberg, Richard M.; Mahmoud, Najjia N.; Warren, Robert S.; Schilsky, Richard L.; Bertagnolli, Monica M.

2013-01-01

Purpose A greater understanding of the biology of tumor recurrence should improve adjuvant treatment decision making. We conducted a validation study of the 12-gene recurrence score (RS), a quantitative assay integrating stromal response and cell cycle gene expression, in tumor specimens from patients enrolled onto Cancer and Leukemia Group B (CALGB) 9581. Patients and Methods CALGB 9581 randomly assigned 1,713 patients with stage II colon cancer to treatment with edrecolomab or observation and found no survival difference. The analysis reported here included all patients with available tissue and recurrence (n = 162) and a random (approximately 1:3) selection of nonrecurring patients. RS was assessed in 690 formalin-fixed paraffin-embedded tumor samples with quantitative reverse transcriptase polymerase chain reaction by using prespecified genes and a previously validated algorithm. Association of RS and recurrence was analyzed by weighted Cox proportional hazards regression. Results Continuous RS was significantly associated with risk of recurrence (P = .013) as was mismatch repair (MMR) gene deficiency (P = .044). In multivariate analyses, RS was the strongest predictor of recurrence (P = .004), independent of T stage, MMR, number of nodes examined, grade, and lymphovascular invasion. In T3 MMR-intact (MMR-I) patients, prespecified low and high RS groups had average 5-year recurrence risks of 13% (95% CI, 10% to 16%) and 21% (95% CI, 16% to 26%), respectively. Conclusion The 12-gene RS predicts recurrence in stage II colon cancer in CALGB 9581. This is consistent with the importance of stromal response and cell cycle gene expression in colon tumor recurrence. RS appears to be most discerning for patients with T3 MMR-I tumors, although markers such as grade and lymphovascular invasion did not add value in this subset of patients. PMID:23530100

Augmenting Microarray Data with Literature-Based Knowledge to Enhance Gene Regulatory Network Inference

PubMed Central

Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C.

2014-01-01

Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology. PMID:24921649

Augmenting microarray data with literature-based knowledge to enhance gene regulatory network inference.

PubMed

Chen, Guocai; Cairelli, Michael J; Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C

2014-06-01

Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology.

SFM: A novel sequence-based fusion method for disease genes identification and prioritization.

PubMed

Yousef, Abdulaziz; Moghadam Charkari, Nasrollah

2015-10-21

The identification of disease genes from human genome is of great importance to improve diagnosis and treatment of disease. Several machine learning methods have been introduced to identify disease genes. However, these methods mostly differ in the prior knowledge used to construct the feature vector for each instance (gene), the ways of selecting negative data (non-disease genes) where there is no investigational approach to find them and the classification methods used to make the final decision. In this work, a novel Sequence-based fusion method (SFM) is proposed to identify disease genes. In this regard, unlike existing methods, instead of using a noisy and incomplete prior-knowledge, the amino acid sequence of the proteins which is universal data has been carried out to present the genes (proteins) into four different feature vectors. To select more likely negative data from candidate genes, the intersection set of four negative sets which are generated using distance approach is considered. Then, Decision Tree (C4.5) has been applied as a fusion method to combine the results of four independent state-of the-art predictors based on support vector machine (SVM) algorithm, and to make the final decision. The experimental results of the proposed method have been evaluated by some standard measures. The results indicate the precision, recall and F-measure of 82.6%, 85.6% and 84, respectively. These results confirm the efficiency and validity of the proposed method. Copyright © 2015 Elsevier Ltd. All rights reserved.

Iodine-131 dose-dependent gene expression: alterations in both normal and tumour thyroid tissues of post-Chernobyl thyroid cancers.

PubMed

Abend, M; Pfeiffer, R M; Ruf, C; Hatch, M; Bogdanova, T I; Tronko, M D; Hartmann, J; Meineke, V; Mabuchi, K; Brenner, A V

2013-10-15

A strong, consistent association between childhood irradiation and subsequent thyroid cancer provides an excellent model for studying radiation carcinogenesis. We evaluated gene expression in 63 paired RNA specimens from frozen normal and tumour thyroid tissues with individual iodine-131 (I-131) doses (0.008-8.6 Gy, no unirradiated controls) received from Chernobyl fallout during childhood (Ukrainian-American cohort). Approximately half of these randomly selected samples (32 tumour/normal tissue RNA specimens) were hybridised on 64 whole-genome microarrays (Agilent, 4 × 44 K). Associations between I-131 dose and gene expression were assessed separately in normal and tumour tissues using Kruskal-Wallis and linear trend tests. Of 155 genes significantly associated with I-131 after Bonferroni correction and with ≥2-fold increase per dose category, we selected 95 genes. On the remaining 31 RNA samples these genes were used for validation purposes using qRT-PCR. Expression of eight genes (ABCC3, C1orf9, C6orf62, FGFR1OP2, HEY2, NDOR1, STAT3, and UCP3) in normal tissue and six genes (ANKRD46, CD47, HNRNPH1, NDOR1, SCEL, and SERPINA1) in tumour tissue was significantly associated with I-131. PANTHER/DAVID pathway analyses demonstrated significant over-representation of genes coding for nucleic acid binding in normal and tumour tissues, and for p53, EGF, and FGF signalling pathways in tumour tissue. The multistep process of radiation carcinogenesis begins in histologically normal thyroid tissue and may involve dose-dependent gene expression changes.

Integrative Approach to Pain Genetics Identifies Pain Sensitivity Loci across Diseases

PubMed Central

Ruau, David; Dudley, Joel T.; Chen, Rong; Phillips, Nicholas G.; Swan, Gary E.; Lazzeroni, Laura C.; Clark, J. David

2012-01-01

Identifying human genes relevant for the processing of pain requires difficult-to-conduct and expensive large-scale clinical trials. Here, we examine a novel integrative paradigm for data-driven discovery of pain gene candidates, taking advantage of the vast amount of existing disease-related clinical literature and gene expression microarray data stored in large international repositories. First, thousands of diseases were ranked according to a disease-specific pain index (DSPI), derived from Medical Subject Heading (MESH) annotations in MEDLINE. Second, gene expression profiles of 121 of these human diseases were obtained from public sources. Third, genes with expression variation significantly correlated with DSPI across diseases were selected as candidate pain genes. Finally, selected candidate pain genes were genotyped in an independent human cohort and prospectively evaluated for significant association between variants and measures of pain sensitivity. The strongest signal was with rs4512126 (5q32, ABLIM3, P = 1.3×10−10) for the sensitivity to cold pressor pain in males, but not in females. Significant associations were also observed with rs12548828, rs7826700 and rs1075791 on 8q22.2 within NCALD (P = 1.7×10−4, 1.8×10−4, and 2.2×10−4 respectively). Our results demonstrate the utility of a novel paradigm that integrates publicly available disease-specific gene expression data with clinical data curated from MEDLINE to facilitate the discovery of pain-relevant genes. This data-derived list of pain gene candidates enables additional focused and efficient biological studies validating additional candidates. PMID:22685391

Investigating the mechanisms of glyphosate resistance in goosegrass (Eleusine indica (L.) Gaertn.) by RNA sequencing technology.

PubMed

Chen, Jingchao; Huang, Hongjuan; Wei, Shouhui; Huang, Zhaofeng; Wang, Xu; Zhang, Chaoxian

2017-01-01

Glyphosate is an important non-selective herbicide that is in common use worldwide. However, evolved glyphosate-resistant (GR) weeds significantly affect crop yields. Unfortunately, the mechanisms underlying resistance in GR weeds, such as goosegrass (Eleusine indica (L.) Gaertn.), an annual weed found worldwide, have not been fully elucidated. In this study, transcriptome analysis was conducted to further assess the potential mechanisms of glyphosate resistance in goosegrass. The RNA sequencing libraries generated 24 597 462 clean reads. De novo assembly analysis produced 48 852 UniGenes with an average length of 847 bp. All UniGenes were annotated using seven databases. Sixteen candidate differentially expressed genes selected by digital gene expression analysis were validated by quantitative real-time PCR (qRT-PCR). Among these UniGenes, the EPSPS and PFK genes were constitutively up-regulated in resistant (R) individuals and showed a higher copy number than that in susceptible (S) individuals. The expressions of four UniGenes relevant to photosynthesis were inhibited by glyphosate in S individuals, and this toxic response was confirmed by gas exchange analysis. Two UniGenes annotated as glutathione transferase (GST) were constitutively up-regulated in R individuals, and were induced by glyphosate both in R and S. In addition, the GST activities in R individuals were higher than in S. Our research confirmed that two UniGenes (PFK, EPSPS) were strongly associated with target resistance, and two GST-annotated UniGenes may play a role in metabolic glyphosate resistance in goosegrass. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

Selection and validation of reference genes for RT-qPCR indicates that juice of sugarcane varieties modulate the expression of C metabolism genes in the endophytic diazotrophic Herbaspirillum rubrisubalbicans strain HCC103.

PubMed

Polese, Valéria; de Paula Soares, Cleiton; da Silva, Paula Renata Alves; Simões-Araújo, Jean Luiz; Baldani, José Ivo; Vidal, Marcia Soares

2017-12-01

Quantitative reverse transcription PCR (RT-qPCR) is an important tool for evaluating gene expression. However, this technique requires that specific internal normalizing genes be identified for different experimental conditions. To date, no internal normalizing genes are available for validation of data analyses for Herbaspirillum rubrisubalbicans strain HCC103, an endophyte that is part of the sugarcane consortium inoculant. This work seeks to identify and evaluate suitable reference genes for gene expression studies in HCC103 grown until middle log phase in sugarcane juice obtained from four sugarcane varieties or media with three different carbon sources. The mRNA levels of five candidate genes (rpoA, gyrA, dnaG, recA and gmK) and seven target genes involved in carbon metabolism (acnA, fbp, galE, suhB, wcaA, ORF_0127.0101 and _0127.0123) were quantified by RT-qPCR. Analysis of expression stability of these genes was carried out using geNorm and Normfinder software. The results indicated that the HCC103 dnaG and gyrA genes are the most stable and showed adequate relative expression level changes among the different sugarcane juices. The highest expression level was seen for ORF_0127.0101, which encodes a sugar transporter, in juice from sugarcane variety RB867515 and glucose as the carbon source. The suhB gene, encoding SuhB inositol monophosphatase, had a higher relative expression level on 0.5% glucose, 100% sugarcane juice from variety RB867515 and 0.5% aconitate. Together the results suggest that dnaG and gyrA genes are suitable as reference genes for RT-qPCR analysis of strain HCC103 and that juice from different sugarcane varieties modulates the expression of key genes involved in carbon metabolism.

Discovery and validation of a glioblastoma co-expressed gene module

PubMed Central

Dunwoodie, Leland J.; Poehlman, William L.; Ficklin, Stephen P.; Feltus, Frank Alexander

2018-01-01

Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network. PMID:29541392

Discovery and validation of a glioblastoma co-expressed gene module.

PubMed

Dunwoodie, Leland J; Poehlman, William L; Ficklin, Stephen P; Feltus, Frank Alexander

2018-02-16

Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network.

Identification and validation of quantitative real-time reverse transcription PCR reference genes for gene expression analysis in teak (Tectona grandis L.f.)

PubMed Central

2014-01-01

Background Teak (Tectona grandis L.f.) is currently the preferred choice of the timber trade for fabrication of woody products due to its extraordinary qualities and is widely grown around the world. Gene expression studies are essential to explore wood formation of vascular plants, and quantitative real-time reverse transcription PCR (qRT-PCR) is a sensitive technique employed for quantifying gene expression levels. One or more appropriate reference genes are crucial to accurately compare mRNA transcripts through different tissues/organs and experimental conditions. Despite being the focus of some genetic studies, a lack of molecular information has hindered genetic exploration of teak. To date, qRT-PCR reference genes have not been identified and validated for teak. Results Identification and cloning of nine commonly used qRT-PCR reference genes from teak, including ribosomal protein 60s (rp60s), clathrin adaptor complexes medium subunit family (Cac), actin (Act), histone 3 (His3), sand family (Sand), β-Tubulin (Β-Tub), ubiquitin (Ubq), elongation factor 1-α (Ef-1α), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Expression profiles of these genes were evaluated by qRT-PCR in six tissue and organ samples (leaf, flower, seedling, root, stem and branch secondary xylem) of teak. Appropriate gene cloning and sequencing, primer specificity and amplification efficiency was verified for each gene. Their stability as reference genes was validated by NormFinder, BestKeeper, geNorm and Delta Ct programs. Results obtained from all programs showed that TgUbq and TgEf-1α are the most stable genes to use as qRT-PCR reference genes and TgAct is the most unstable gene in teak. The relative expression of the teak cinnamyl alcohol dehydrogenase (TgCAD) gene in lignified tissues at different ages was assessed by qRT-PCR, using TgUbq and TgEf-1α as internal controls. These analyses exposed a consistent expression pattern with both reference genes. Conclusion This study proposes a first broad collection of teak tissue and organ mRNA expression data for nine selected candidate qRT-PCR reference genes. NormFinder, Bestkeeper, geNorm and Delta Ct analyses suggested that TgUbq and TgEf-1α have the highest expression stability and provided similar results when evaluating TgCAD gene expression, while the commonly used Act should be avoided. PMID:25048176

How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population.

PubMed

De Keyser, Ellen; Desmet, Laurence; Van Bockstaele, Erik; De Riek, Jan

2013-06-24

Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population. An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H. Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway.

How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population

PubMed Central

2013-01-01

Background Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population. Results An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H. Conclusions Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway. PMID:23800303

Genomic Approach to Study Floral Development Genes in Rosa sp.

PubMed Central

Chauvet, Aurélie; Maene, Marion; Pécrix, Yann; Yang, Shu-Hua; Jeauffre, Julien; Thouroude, Tatiana; Boltz, Véronique; Martin-Magniette, Marie-Laure; Janczarski, Stéphane; Legeai, Fabrice; Renou, Jean-Pierre; Vergne, Philippe; Le Bris, Manuel; Foucher, Fabrice; Bendahmane, Mohammed

2011-01-01

Cultivated for centuries, the varieties of rose have been selected based on a number of flower traits. Understanding the genetic and molecular basis that contributes to these traits will impact on future improvements for this economically important ornamental plant. In this study, we used scanning electron microscopy and sections of meristems and flowers to establish a precise morphological calendar from early rose flower development stages to senescing flowers. Global gene expression was investigated from floral meristem initiation up to flower senescence in three rose genotypes exhibiting contrasted floral traits including continuous versus once flowering and simple versus double flower architecture, using a newly developed Affymetrix microarray (Rosa1_Affyarray) tool containing sequences representing 4765 unigenes expressed during flower development. Data analyses permitted the identification of genes associated with floral transition, floral organs initiation up to flower senescence. Quantitative real time PCR analyses validated the mRNA accumulation changes observed in microarray hybridizations for a selection of 24 genes expressed at either high or low levels. Our data describe the early flower development stages in Rosa sp, the production of a rose microarray and demonstrate its usefulness and reliability to study gene expression during extensive development phases, from the vegetative meristem to the senescent flower. PMID:22194838

cDNA Microarray Analysis of Host-Pathogen Interactions in a Porcine In Vitro Model for Toxoplasma gondii Infection†

PubMed Central

Okomo-Adhiambo, Margaret; Beattie, Craig; Rink, Anette

2006-01-01

Toxoplasma gondii induces the expression of proinflammatory cytokines, reorganizes organelles, scavenges nutrients, and inhibits apoptosis in infected host cells. We used a cDNA microarray of 420 annotated porcine expressed sequence tags to analyze the molecular basis of these changes at eight time points over a 72-hour period in porcine kidney epithelial (PK13) cells infected with T. gondii. A total of 401 genes with Cy3 and Cy5 spot intensities of ≥500 were selected for analysis, of which 263 (65.6%) were induced ≥2-fold (expression ratio, ≥2.0; P ≤ 0.05 [t test]) over at least one time point and 48 (12%) were significantly down-regulated. At least 12 functional categories of genes were modulated (up- or down-regulated) by T. gondii. The majority of induced genes were clustered as transcription, signal transduction, host immune response, nutrient metabolism, and apoptosis related. The expression of selected genes altered by T. gondii was validated by quantitative real-time reverse transcription-PCR. These results suggest that significant changes in gene expression occur in response to T. gondii infection in PK13 cells, facilitating further analysis of host-pathogen interactions in toxoplasmosis in a secondary host. PMID:16790800

Gene expression complex networks: synthesis, identification, and analysis.

PubMed

Lopes, Fabrício M; Cesar, Roberto M; Costa, Luciano Da F

2011-10-01

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdös-Rényi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabási-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree variation, decreasing its network recovery rate with the increase of . The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Transporter genes identified in landraces associated with high zinc in polished rice through panicle transcriptome for biofortification

PubMed Central

Kulkarni, Kalyani S.; Madhu Babu, P.; Sanjeeva Rao, D.; Surekha, K.; Ravindra Babu, V

2018-01-01

Polished rice is poor source of micronutrients, however wide genotypic variability exists for zinc uptake and remobilization and zinc content in brown and polished grains in rice. Two landraces (Chittimutyalu and Kala Jeera Joha) and one popular improved variety (BPT 5204) were grown under zinc sufficient soil and their analyses showed high zinc in straw of improved variety, but high zinc in polished rice in landraces suggesting better translocation ability of zinc into the grain in landraces. Transcriptome analyses of the panicle tissue showed 41182 novel transcripts across three samples. Out of 1011 differentially expressed exclusive transcripts by two landraces, 311 were up regulated and 534 were down regulated. Phosphate transporter-exporter (PHO), proton-coupled peptide transporters (POT) and vacuolar iron transporter (VIT) showed enhanced and significant differential expression in landraces. Out of 24 genes subjected to quantitative real time analyses for confirmation, eight genes showed significant differential expression in landraces. Through mapping, six rice microsatellite markers spanning the genomic regions of six differentially expressed genes were validated for their association with zinc in brown and polished rice using recombinant inbred lines (RIL) of BPT 5204/Chittimutyalu. Thus, this study reports repertoire of genes associated with high zinc in polished rice and a proof concept for deployment of transcriptome information for validation in mapping population and its use in marker assisted selection for biofortification of rice with zinc. PMID:29394277

Transcriptional Analysis of Drought-Induced Genes in the Roots of a Tolerant Genotype of the Common Bean (Phaseolus vulgaris L.)

PubMed Central

Recchia, Gustavo Henrique; Caldas, Danielle Gregorio Gomes; Beraldo, Ana Luiza Ahern; da Silva, Márcio José; Tsai, Siu Mui

2013-01-01

In Brazil, common bean (Phaseolus vulgaris L.) productivity is severely affected by drought stress due to low technology cultivation systems. Our purpose was to identify differentially expressed genes in roots of a genotype tolerant to water deficit (BAT 477) when submitted to an interruption of irrigation during its development. A SSH library was constructed taking as “driver” the genotype Carioca 80SH (susceptible to drought). After clustering and data mining, 1572 valid reads were obtained, resulting in 1120 ESTs (expressed sequence tags). We found sequences for transcription factors, carbohydrates metabolism, proline-rich proteins, aquaporins, chaperones and ubiquitins, all of them organized according to their biological processes. Our suppressive subtractive hybridization (SSH) library was validated through RT-qPCR experiment by assessing the expression patterns of 10 selected genes in both genotypes under stressed and control conditions. Finally, the expression patterns of 31 ESTs, putatively related to drought responses, were analyzed in a time-course experiment. Our results confirmed that such genes are more expressed in the tolerant genotype during stress; however, they are not exclusive, since different levels of these transcripts were also detected in the susceptible genotype. In addition, we observed a fluctuation in gene regulation over time for both the genotypes, which seem to adopt and adapt different strategies in order to develop tolerance against this stress. PMID:23538843

Synthetic Lethality Reveals Mechanisms of Mycobacterium tuberculosis Resistance to β-Lactams

PubMed Central

Lun, Shichun; Miranda, David; Kubler, Andre; Guo, Haidan; Maiga, Mariama C.; Winglee, Kathryn; Pelly, Shaaretha

2014-01-01

ABSTRACT Most β-lactam antibiotics are ineffective against Mycobacterium tuberculosis due to the microbe’s innate resistance. The emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains has prompted interest to repurpose this class of drugs. To identify the genetic determinants of innate β-lactam resistance, we carried out a synthetic lethality screen on a transposon mutant library for susceptibility to imipenem, a carbapenem β-lactam antibiotic. Mutations in 74 unique genes demonstrated synthetic lethality. The majority of mutations were in genes associated with cell wall biosynthesis. A second quantitative real-time PCR (qPCR)-based synthetic lethality screen of randomly selected mutants confirmed the role of cell wall biosynthesis in β-lactam resistance. The global transcriptional response of the bacterium to β-lactams was investigated, and changes in levels of expression of cell wall biosynthetic genes were identified. Finally, we validated these screens in vivo using the MT1616 transposon mutant, which lacks a functional acyl-transferase gene. Mice infected with the mutant responded to β-lactam treatment with a 100-fold decrease in bacillary lung burden over 4 weeks, while the numbers of organisms in the lungs of mice infected with wild-type bacilli proliferated. These findings reveal a road map of genes required for β-lactam resistance and validate synthetic lethality screening as a promising tool for repurposing existing classes of licensed, safe, well-characterized antimicrobials against tuberculosis. PMID:25227469

Transporter genes identified in landraces associated with high zinc in polished rice through panicle transcriptome for biofortification.

PubMed

Neeraja, C N; Kulkarni, Kalyani S; Madhu Babu, P; Sanjeeva Rao, D; Surekha, K; Ravindra Babu, V

2018-01-01

Polished rice is poor source of micronutrients, however wide genotypic variability exists for zinc uptake and remobilization and zinc content in brown and polished grains in rice. Two landraces (Chittimutyalu and Kala Jeera Joha) and one popular improved variety (BPT 5204) were grown under zinc sufficient soil and their analyses showed high zinc in straw of improved variety, but high zinc in polished rice in landraces suggesting better translocation ability of zinc into the grain in landraces. Transcriptome analyses of the panicle tissue showed 41182 novel transcripts across three samples. Out of 1011 differentially expressed exclusive transcripts by two landraces, 311 were up regulated and 534 were down regulated. Phosphate transporter-exporter (PHO), proton-coupled peptide transporters (POT) and vacuolar iron transporter (VIT) showed enhanced and significant differential expression in landraces. Out of 24 genes subjected to quantitative real time analyses for confirmation, eight genes showed significant differential expression in landraces. Through mapping, six rice microsatellite markers spanning the genomic regions of six differentially expressed genes were validated for their association with zinc in brown and polished rice using recombinant inbred lines (RIL) of BPT 5204/Chittimutyalu. Thus, this study reports repertoire of genes associated with high zinc in polished rice and a proof concept for deployment of transcriptome information for validation in mapping population and its use in marker assisted selection for biofortification of rice with zinc.

Harnessing pain heterogeneity and RNA transcriptome to identify blood–based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model

PubMed Central

Grace, Peter M.; Hurley, Daniel; Barratt, Daniel T.; Tsykin, Anna; Watkins, Linda R.; Rolan, Paul E.; Hutchinson, Mark R.

2017-01-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. PMID:22697386

Genome-scale CRISPR-Cas9 knockout screening in human cells.

PubMed

Shalem, Ophir; Sanjana, Neville E; Hartenian, Ella; Shi, Xi; Scott, David A; Mikkelson, Tarjei; Heckl, Dirk; Ebert, Benjamin L; Root, David E; Doench, John G; Zhang, Feng

2014-01-03

The simplicity of programming the CRISPR (clustered regularly interspaced short palindromic repeats)-associated nuclease Cas9 to modify specific genomic loci suggests a new way to interrogate gene function on a genome-wide scale. We show that lentiviral delivery of a genome-scale CRISPR-Cas9 knockout (GeCKO) library targeting 18,080 genes with 64,751 unique guide sequences enables both negative and positive selection screening in human cells. First, we used the GeCKO library to identify genes essential for cell viability in cancer and pluripotent stem cells. Next, in a melanoma model, we screened for genes whose loss is involved in resistance to vemurafenib, a therapeutic RAF inhibitor. Our highest-ranking candidates include previously validated genes NF1 and MED12, as well as novel hits NF2, CUL3, TADA2B, and TADA1. We observe a high level of consistency between independent guide RNAs targeting the same gene and a high rate of hit confirmation, demonstrating the promise of genome-scale screening with Cas9.

Exploring Valid Reference Genes for Quantitative Real-time PCR Analysis in Plutella xylostella (Lepidoptera: Plutellidae)

PubMed Central

Fu, Wei; Xie, Wen; Zhang, Zhuo; Wang, Shaoli; Wu, Qingjun; Liu, Yong; Zhou, Xiaomao; Zhou, Xuguo; Zhang, Youjun

2013-01-01

Abstract: Quantitative real-time PCR (qRT-PCR), a primary tool in gene expression analysis, requires an appropriate normalization strategy to control for variation among samples. The best option is to compare the mRNA level of a target gene with that of reference gene(s) whose expression level is stable across various experimental conditions. In this study, expression profiles of eight candidate reference genes from the diamondback moth, Plutella xylostella, were evaluated under diverse experimental conditions. RefFinder, a web-based analysis tool, integrates four major computational programs including geNorm, Normfinder, BestKeeper, and the comparative ΔCt method to comprehensively rank the tested candidate genes. Elongation factor 1 (EF1) was the most suited reference gene for the biotic factors (development stage, tissue, and strain). In contrast, although appropriate reference gene(s) do exist for several abiotic factors (temperature, photoperiod, insecticide, and mechanical injury), we were not able to identify a single universal reference gene. Nevertheless, a suite of candidate reference genes were specifically recommended for selected experimental conditions. Our finding is the first step toward establishing a standardized qRT-PCR analysis of this agriculturally important insect pest. PMID:23983612

Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

PubMed

Zhou, Xionghui; Liu, Juan

2014-01-01

Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for phenotypic change.

Genetic reprogramming of human amniotic cells with episomal vectors: neural rosettes as sentinels in candidate selection for validation assays.

PubMed

Wilson, Patricia G; Payne, Tiffany

2014-01-01

The promise of genetic reprogramming has prompted initiatives to develop banks of induced pluripotent stem cells (iPSCs) from diverse sources. Sentinel assays for pluripotency could maximize available resources for generating iPSCs. Neural rosettes represent a primitive neural tissue that is unique to differentiating PSCs and commonly used to identify derivative neural/stem progenitors. Here, neural rosettes were used as a sentinel assay for pluripotency in selection of candidates to advance to validation assays. Candidate iPSCs were generated from independent populations of amniotic cells with episomal vectors. Phase imaging of living back up cultures showed neural rosettes in 2 of the 5 candidate populations. Rosettes were immunopositive for the Sox1, Sox2, Pax6 and Pax7 transcription factors that govern neural development in the earliest stage of development and for the Isl1/2 and Otx2 transcription factors that are expressed in the dorsal and ventral domains, respectively, of the neural tube in vivo. Dissociation of rosettes produced cultures of differentiation competent neural/stem progenitors that generated immature neurons that were immunopositive for βIII-tubulin and glia that were immunopositive for GFAP. Subsequent validation assays of selected candidates showed induced expression of endogenous pluripotency genes, epigenetic modification of chromatin and formation of teratomas in immunodeficient mice that contained derivatives of the 3 embryonic germ layers. Validated lines were vector-free and maintained a normal karyotype for more than 60 passages. The credibility of rosette assembly as a sentinel assay for PSCs is supported by coordinate loss of nuclear-localized pluripotency factors Oct4 and Nanog in neural rosettes that emerge spontaneously in cultures of self-renewing validated lines. Taken together, these findings demonstrate value in neural rosettes as sentinels for pluripotency and selection of promising candidates for advance to validation assays.

Genetic reprogramming of human amniotic cells with episomal vectors: neural rosettes as sentinels in candidate selection for validation assays

PubMed Central

Payne, Tiffany

2014-01-01

The promise of genetic reprogramming has prompted initiatives to develop banks of induced pluripotent stem cells (iPSCs) from diverse sources. Sentinel assays for pluripotency could maximize available resources for generating iPSCs. Neural rosettes represent a primitive neural tissue that is unique to differentiating PSCs and commonly used to identify derivative neural/stem progenitors. Here, neural rosettes were used as a sentinel assay for pluripotency in selection of candidates to advance to validation assays. Candidate iPSCs were generated from independent populations of amniotic cells with episomal vectors. Phase imaging of living back up cultures showed neural rosettes in 2 of the 5 candidate populations. Rosettes were immunopositive for the Sox1, Sox2, Pax6 and Pax7 transcription factors that govern neural development in the earliest stage of development and for the Isl1/2 and Otx2 transcription factors that are expressed in the dorsal and ventral domains, respectively, of the neural tube in vivo. Dissociation of rosettes produced cultures of differentiation competent neural/stem progenitors that generated immature neurons that were immunopositive for βIII-tubulin and glia that were immunopositive for GFAP. Subsequent validation assays of selected candidates showed induced expression of endogenous pluripotency genes, epigenetic modification of chromatin and formation of teratomas in immunodeficient mice that contained derivatives of the 3 embryonic germ layers. Validated lines were vector-free and maintained a normal karyotype for more than 60 passages. The credibility of rosette assembly as a sentinel assay for PSCs is supported by coordinate loss of nuclear-localized pluripotency factors Oct4 and Nanog in neural rosettes that emerge spontaneously in cultures of self-renewing validated lines. Taken together, these findings demonstrate value in neural rosettes as sentinels for pluripotency and selection of promising candidates for advance to validation assays. PMID:25426336

Integration of mouse and human genome-wide association data identifies KCNIP4 as an asthma gene.

PubMed

Himes, Blanca E; Sheppard, Keith; Berndt, Annerose; Leme, Adriana S; Myers, Rachel A; Gignoux, Christopher R; Levin, Albert M; Gauderman, W James; Yang, James J; Mathias, Rasika A; Romieu, Isabelle; Torgerson, Dara G; Roth, Lindsey A; Huntsman, Scott; Eng, Celeste; Klanderman, Barbara; Ziniti, John; Senter-Sylvia, Jody; Szefler, Stanley J; Lemanske, Robert F; Zeiger, Robert S; Strunk, Robert C; Martinez, Fernando D; Boushey, Homer; Chinchilli, Vernon M; Israel, Elliot; Mauger, David; Koppelman, Gerard H; Postma, Dirkje S; Nieuwenhuis, Maartje A E; Vonk, Judith M; Lima, John J; Irvin, Charles G; Peters, Stephen P; Kubo, Michiaki; Tamari, Mayumi; Nakamura, Yusuke; Litonjua, Augusto A; Tantisira, Kelan G; Raby, Benjamin A; Bleecker, Eugene R; Meyers, Deborah A; London, Stephanie J; Barnes, Kathleen C; Gilliland, Frank D; Williams, L Keoki; Burchard, Esteban G; Nicolae, Dan L; Ober, Carole; DeMeo, Dawn L; Silverman, Edwin K; Paigen, Beverly; Churchill, Gary; Shapiro, Steve D; Weiss, Scott T

2013-01-01

Asthma is a common chronic respiratory disease characterized by airway hyperresponsiveness (AHR). The genetics of asthma have been widely studied in mouse and human, and homologous genomic regions have been associated with mouse AHR and human asthma-related phenotypes. Our goal was to identify asthma-related genes by integrating AHR associations in mouse with human genome-wide association study (GWAS) data. We used Efficient Mixed Model Association (EMMA) analysis to conduct a GWAS of baseline AHR measures from males and females of 31 mouse strains. Genes near or containing SNPs with EMMA p-values <0.001 were selected for further study in human GWAS. The results of the previously reported EVE consortium asthma GWAS meta-analysis consisting of 12,958 diverse North American subjects from 9 study centers were used to select a subset of homologous genes with evidence of association with asthma in humans. Following validation attempts in three human asthma GWAS (i.e., Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG) and two human AHR GWAS (i.e., SHARP, DAG), the Kv channel interacting protein 4 (KCNIP4) gene was identified as nominally associated with both asthma and AHR at a gene- and SNP-level. In EVE, the smallest KCNIP4 association was at rs6833065 (P-value 2.9e-04), while the strongest associations for Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG were 1.5e-03, 1.0e-03, 3.1e-03 at rs7664617, rs4697177, rs4696975, respectively. At a SNP level, the strongest association across all asthma GWAS was at rs4697177 (P-value 1.1e-04). The smallest P-values for association with AHR were 2.3e-03 at rs11947661 in SHARP and 2.1e-03 at rs402802 in DAG. Functional studies are required to validate the potential involvement of KCNIP4 in modulating asthma susceptibility and/or AHR. Our results suggest that a useful approach to identify genes associated with human asthma is to leverage mouse AHR association data.

Evaluation and Selection of Candidate Reference Genes for Normalization of Quantitative RT-PCR in Withania somnifera (L.) Dunal

PubMed Central

Singh, Varinder; Kaul, Sunil C.; Wadhwa, Renu; Pati, Pratap Kumar

2015-01-01

Quantitative real-time PCR (qRT-PCR) is now globally used for accurate analysis of transcripts levels in plants. For reliable quantification of transcripts, identification of the best reference genes is a prerequisite in qRT-PCR analysis. Recently, Withania somnifera has attracted lot of attention due to its immense therapeutic potential. At present, biotechnological intervention for the improvement of this plant is being seriously pursued. In this background, it is important to have comprehensive studies on finding suitable reference genes for this high valued medicinal plant. In the present study, 11 candidate genes were evaluated for their expression stability under biotic (fungal disease), abiotic (wounding, salt, drought, heat and cold) stresses, in different plant tissues and in response to various plant growth regulators (methyl jasmonate, salicylic acid, abscisic acid). The data as analyzed by various software packages (geNorm, NormFinder, Bestkeeper and ΔCt method) suggested that cyclophilin (CYP) is a most stable gene under wounding, heat, methyl jasmonate, different tissues and all stress conditions. T-SAND was found to be a best reference gene for salt and salicylic acid (SA) treated samples, while 26S ribosomal RNA (26S), ubiquitin (UBQ) and beta-tubulin (TUB) were the most stably expressed genes under drought, biotic and cold treatment respectively. For abscisic acid (ABA) treated samples 18S-rRNA was found to stably expressed gene. Finally, the relative expression level of the three genes involved in the withanolide biosynthetic pathway was detected to validate the selection of reliable reference genes. The present work will significantly contribute to gene analysis studies in W. somnifera and facilitate in improving the quality of gene expression data in this plant as well as and other related plant species. PMID:25769035

Selection of Reliable Reference Genes for Gene Expression Studies on Rhododendron molle G. Don.

PubMed

Xiao, Zheng; Sun, Xiaobo; Liu, Xiaoqing; Li, Chang; He, Lisi; Chen, Shangping; Su, Jiale

2016-01-01

The quantitative real-time polymerase chain reaction (qRT-PCR) approach has become a widely used method to analyze expression patterns of target genes. The selection of an optimal reference gene is a prerequisite for the accurate normalization of gene expression in qRT-PCR. The present study constitutes the first systematic evaluation of potential reference genes in Rhododendron molle G. Don. Eleven candidate reference genes in different tissues and flowers at different developmental stages of R. molle were assessed using the following three software packages: GeNorm, NormFinder, and BestKeeper. The results showed that EF1- α (elongation factor 1-alpha), 18S (18s ribosomal RNA), and RPL3 (ribosomal protein L3) were the most stable reference genes in developing rhododendron flowers and, thus, in all of the tested samples, while tublin ( TUB ) was the least stable. ACT5 (actin), RPL3 , 18S , and EF1- α were found to be the top four choices for different tissues, whereas TUB was not found to favor qRT-PCR normalization in these tissues. Three stable reference genes are recommended for the normalization of qRT-PCR data in R. molle . Furthermore, the expression profiles of RmPSY (phytoene synthase) and RmPDS (phytoene dehydrogenase) were assessed using EF1- α, 18S , ACT5 , RPL3 , and their combination as internals. Similar trends were found, but these trends varied when the least stable reference gene TUB was used. The results further prove that it is necessary to validate the stability of reference genes prior to their use for normalization under different experimental conditions. This study provides useful information for reliable qRT-PCR data normalization in gene studies of R. molle .

Six stroma-based RNA markers diagnostic for prostate cancer in European-Americans validated at the RNA and protein levels in patients in China

PubMed Central

Zhu, Jianguo; Pan, Cong; Jiang, Jun; Deng, Mingsen; Gao, Hengjun; Men, Bozhao; McClelland, Michael; Mercola, Dan; Zhong, Wei-De; Jia, Zhenyu

2015-01-01

We previously analyzed human prostate tissue containing stroma near to tumor and from cancer-negative tissues of volunteers. Over 100 candidate gene expression differences were identified and used to develop a classifier that could detect nearby tumor with an accuracy of 97% (sensitivity = 98% and specificity = 88%) based on 364 independent test cases from primarily European American cases. These stroma-based gene signatures have the potential to identify cancer patients among those with negative biopsies. In this study, we used prostate tissues from Chinese cases to validate six of these markers (CAV1, COL4A2, HSPB1, ITGB3, MAP1A and MCAM). In validation by real-time PCR, four genes (COL4A2, HSPB1, ITGB3, and MAP1A) demonstrated significantly lower expression in tumor-adjacent stroma compared to normal stroma (p value ≤ 0.05). Next, we tested whether these expression differences could be extended to the protein level. In IHC assays, all six selected proteins showed lower expression in tumor-adjacent stroma compared to the normal stroma, of which COL4A2, HSPB1 and ITGB3 showed significant differences (p value ≤ 0.05). These results suggest that biomarkers for diagnosing prostate cancer based on tumor microenvironment may be applicable across multiple racial groups. PMID:26158290

GFD-Net: A novel semantic similarity methodology for the analysis of gene networks.

PubMed

Díaz-Montaña, Juan J; Díaz-Díaz, Norberto; Gómez-Vela, Francisco

2017-04-01

Since the popularization of biological network inference methods, it has become crucial to create methods to validate the resulting models. Here we present GFD-Net, the first methodology that applies the concept of semantic similarity to gene network analysis. GFD-Net combines the concept of semantic similarity with the use of gene network topology to analyze the functional dissimilarity of gene networks based on Gene Ontology (GO). The main innovation of GFD-Net lies in the way that semantic similarity is used to analyze gene networks taking into account the network topology. GFD-Net selects a functionality for each gene (specified by a GO term), weights each edge according to the dissimilarity between the nodes at its ends and calculates a quantitative measure of the network functional dissimilarity, i.e. a quantitative value of the degree of dissimilarity between the connected genes. The robustness of GFD-Net as a gene network validation tool was demonstrated by performing a ROC analysis on several network repositories. Furthermore, a well-known network was analyzed showing that GFD-Net can also be used to infer knowledge. The relevance of GFD-Net becomes more evident in Section "GFD-Net applied to the study of human diseases" where an example of how GFD-Net can be applied to the study of human diseases is presented. GFD-Net is available as an open-source Cytoscape app which offers a user-friendly interface to configure and execute the algorithm as well as the ability to visualize and interact with the results(http://apps.cytoscape.org/apps/gfdnet). Copyright © 2017 Elsevier Inc. All rights reserved.

Selection of housekeeping genes as internal controls for quantitative RT-PCR analysis of the veined rapa whelk (Rapana venosa)

PubMed Central

Song, Hao; Dang, Xin; He, Yuan-qiu

2017-01-01

Background The veined rapa whelk Rapana venosa is an important commercial shellfish in China and quantitative real-time PCR (qRT-PCR) has become the standard method to study gene expression in R. venosa. For accurate and reliable gene expression results, qRT-PCR assays require housekeeping genes as internal controls, which display highly uniform expression in different tissues or stages of development. However, to date no studies have validated housekeeping genes in R. venosa for use as internal controls for qRT-PCR. Methods In this study, we selected the following 13 candidate genes for suitability as internal controls: elongation factor-1α (EF-1α), α-actin (ACT), cytochrome c oxidase subunit 1 (COX1), nicotinamide adenine dinucleotide dehydrogenase (ubiquinone) 1α subcomplex subunit 7 (NDUFA7), 60S ribosomal protein L5 (RL5), 60S ribosomal protein L28 (RL28), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), β-tubulin (TUBB), 40S ribosomal protein S25 (RS25), 40S ribosomal protein S8 (RS8), ubiquitin-conjugating enzyme E2 (UBE2), histone H3 (HH3), and peptidyl-prolyl cis-trans isomerase A (PPIA). We measured the expression levels of these 13 candidate internal controls in eight different tissues and twelve larvae developmental stages by qRT-PCR. Further analysis of the expression stability of the tested genes was performed using GeNorm and RefFinder algorithms. Results Of the 13 candidate genes tested, we found that EF-1α was the most stable internal control gene in almost all adult tissue samples investigated with RL5 and RL28 as secondary choices. For the normalization of a single specific tissue, we suggested that EF-1α and NDUFA7 are the best combination in gonad, as well as COX1 and RL28 for intestine, EF-1α and RL5 for kidney, EF-1α and COX1 for gill, EF-1α and RL28 for Leiblein and mantle, EF-1α, RL5, and NDUFA7 for liver, GAPDH, PPIA, and RL28 for hemocyte. From a developmental perspective, we found that RL28 was the most stable gene in all developmental stages measured, and COX1 and RL5 were appropriate secondary choices. For the specific developmental stage, we recommended the following combination for normalization, PPIA, RS25, and RL28 for stage 1, RL5 and RL28 for stage 2 and 5, RL28 and NDUFA7 for stage 3, and PPIA and TUBB for stage 4. Discussion Our results are instrumental for the selection of appropriately validated housekeeping genes for use as internal controls for gene expression studies in adult tissues or larval development of R. venosa in the future. PMID:28584723

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

PubMed

Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

2018-04-23

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis and benefit the therapy improvement.

MetaKTSP: a meta-analytic top scoring pair method for robust cross-study validation of omics prediction analysis.

PubMed

Kim, SungHwan; Lin, Chien-Wei; Tseng, George C

2016-07-01

Supervised machine learning is widely applied to transcriptomic data to predict disease diagnosis, prognosis or survival. Robust and interpretable classifiers with high accuracy are usually favored for their clinical and translational potential. The top scoring pair (TSP) algorithm is an example that applies a simple rank-based algorithm to identify rank-altered gene pairs for classifier construction. Although many classification methods perform well in cross-validation of single expression profile, the performance usually greatly reduces in cross-study validation (i.e. the prediction model is established in the training study and applied to an independent test study) for all machine learning methods, including TSP. The failure of cross-study validation has largely diminished the potential translational and clinical values of the models. The purpose of this article is to develop a meta-analytic top scoring pair (MetaKTSP) framework that combines multiple transcriptomic studies and generates a robust prediction model applicable to independent test studies. We proposed two frameworks, by averaging TSP scores or by combining P-values from individual studies, to select the top gene pairs for model construction. We applied the proposed methods in simulated data sets and three large-scale real applications in breast cancer, idiopathic pulmonary fibrosis and pan-cancer methylation. The result showed superior performance of cross-study validation accuracy and biomarker selection for the new meta-analytic framework. In conclusion, combining multiple omics data sets in the public domain increases robustness and accuracy of the classification model that will ultimately improve disease understanding and clinical treatment decisions to benefit patients. An R package MetaKTSP is available online. (http://tsenglab.biostat.pitt.edu/software.htm). ctseng@pitt.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Gene Expression (mRNA) Markers for Differentiating between Malignant and Benign Follicular Thyroid Tumours

PubMed Central

Wojtas, Bartosz; Pfeifer, Aleksandra; Oczko-Wojciechowska, Malgorzata; Krajewska, Jolanta; Czarniecka, Agnieszka; Kukulska, Aleksandra; Eszlinger, Markus; Musholt, Thomas; Stokowy, Tomasz; Swierniak, Michal; Stobiecka, Ewa; Chmielik, Ewa; Rusinek, Dagmara; Tyszkiewicz, Tomasz; Halczok, Monika; Hauptmann, Steffen; Lange, Dariusz; Jarzab, Michal; Paschke, Ralf; Jarzab, Barbara

2017-01-01

Distinguishing between follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA) constitutes a long-standing diagnostic problem resulting in equivocal histopathological diagnoses. There is therefore a need for additional molecular markers. To identify molecular differences between FTC and FTA, we analyzed the gene expression microarray data of 52 follicular neoplasms. We also performed a meta-analysis involving 14 studies employing high throughput methods (365 follicular neoplasms analyzed). Based on these two analyses, we selected 18 genes differentially expressed between FTA and FTC. We validated them by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent set of 71 follicular neoplasms from formaldehyde-fixed paraffin embedded (FFPE) tissue material. We confirmed differential expression for 7 genes (CPQ, PLVAP, TFF3, ACVRL1, ZFYVE21, FAM189A2, and CLEC3B). Finally, we created a classifier that distinguished between FTC and FTA with an accuracy of 78%, sensitivity of 76%, and specificity of 80%, based on the expression of 4 genes (CPQ, PLVAP, TFF3, ACVRL1). In our study, we have demonstrated that meta-analysis is a valuable method for selecting possible molecular markers. Based on our results, we conclude that there might exist a plausible limit of gene classifier accuracy of approximately 80%, when follicular tumors are discriminated based on formalin-fixed postoperative material. PMID:28574441

Gene Expression (mRNA) Markers for Differentiating between Malignant and Benign Follicular Thyroid Tumours.

PubMed

Wojtas, Bartosz; Pfeifer, Aleksandra; Oczko-Wojciechowska, Malgorzata; Krajewska, Jolanta; Czarniecka, Agnieszka; Kukulska, Aleksandra; Eszlinger, Markus; Musholt, Thomas; Stokowy, Tomasz; Swierniak, Michal; Stobiecka, Ewa; Chmielik, Ewa; Rusinek, Dagmara; Tyszkiewicz, Tomasz; Halczok, Monika; Hauptmann, Steffen; Lange, Dariusz; Jarzab, Michal; Paschke, Ralf; Jarzab, Barbara

2017-06-02

Distinguishing between follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA) constitutes a long-standing diagnostic problem resulting in equivocal histopathological diagnoses. There is therefore a need for additional molecular markers. To identify molecular differences between FTC and FTA, we analyzed the gene expression microarray data of 52 follicular neoplasms. We also performed a meta-analysis involving 14 studies employing high throughput methods (365 follicular neoplasms analyzed). Based on these two analyses, we selected 18 genes differentially expressed between FTA and FTC. We validated them by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent set of 71 follicular neoplasms from formaldehyde-fixed paraffin embedded (FFPE) tissue material. We confirmed differential expression for 7 genes ( CPQ , PLVAP , TFF3 , ACVRL1 , ZFYVE21 , FAM189A2 , and CLEC3B ). Finally, we created a classifier that distinguished between FTC and FTA with an accuracy of 78%, sensitivity of 76%, and specificity of 80%, based on the expression of 4 genes ( CPQ , PLVAP , TFF3 , ACVRL1 ). In our study, we have demonstrated that meta-analysis is a valuable method for selecting possible molecular markers. Based on our results, we conclude that there might exist a plausible limit of gene classifier accuracy of approximately 80%, when follicular tumors are discriminated based on formalin-fixed postoperative material.

Reference gene selection for normalization of RT-qPCR gene expression data from Actinidia deliciosa leaves infected with Pseudomonas syringae pv. actinidiae

PubMed Central

Petriccione, Milena; Mastrobuoni, Francesco; Zampella, Luigi; Scortichini, Marco

2015-01-01

Normalization of data, by choosing the appropriate reference genes (RGs), is fundamental for obtaining reliable results in reverse transcription-quantitative PCR (RT-qPCR). In this study, we assessed Actinidia deliciosa leaves inoculated with two doses of Pseudomonas syringae pv. actinidiae during a period of 13 days for the expression profile of nine candidate RGs. Their expression stability was calculated using four algorithms: geNorm, NormFinder, BestKeeper and the deltaCt method. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and protein phosphatase 2A (PP2A) were the most stable genes, while β-tubulin and 7s-globulin were the less stable. Expression analysis of three target genes, chosen for RGs validation, encoding the reactive oxygen species scavenging enzymes ascorbate peroxidase (APX), superoxide dismutase (SOD) and catalase (CAT) indicated that a combination of stable RGs, such as GAPDH and PP2A, can lead to an accurate quantification of the expression levels of such target genes. The APX level varied during the experiment time course and according to the inoculum doses, whereas both SOD and CAT resulted down-regulated during the first four days, and up-regulated afterwards, irrespective of inoculum dose. These results can be useful for better elucidating the molecular interaction in the A. deliciosa/P. s. pv. actinidiae pathosystem and for RGs selection in bacteria-plant pathosystems. PMID:26581656

Regional gene mapping using mixed radiation hybrids and reverse chromosome painting.

PubMed

Lin, J Y; Bedford, J S

1997-11-01

We describe a new approach for low-resolution physical mapping using pooled DNA probe from mixed (non-clonal) populations of human-CHO cell hybrids and reverse chromosome painting. This mapping method is based on a process in which the human chromosome fragments bearing a complementing gene were selectively retained in a large non-clonal population of CHO-human hybrid cells during a series of 12- to 15-Gy gamma irradiations each followed by continuous growth selection. The location of the gene could then be identified by reverse chromosome painting on normal human metaphase spreads using biotinylated DNA from this population of "enriched" hybrid cells. We tested the validity of this method by correctly mapping the complementing human HPRT gene, whose location is well established. We then demonstrated the method's usefulness by mapping the chromosome location of a human gene which complemented the defect responsible for the hypersensitivity to ionizing radiation in CHO irs-20 cells. This method represents an efficient alternative to conventional concordance analysis in somatic cell hybrids where detailed chromosome analysis of numerous hybrid clones is necessary. Using this approach, it is possible to localize a gene for which there is no prior sequence or linkage information to a subchromosomal region, thus facilitating association with known mapping landmarks (e.g. RFLP, YAC or STS contigs) for higher-resolution mapping.

Multiple-endpoints gene alteration-based (MEGA) assay: A toxicogenomics approach for water quality assessment of wastewater effluents.

PubMed

Fukushima, Toshikazu; Hara-Yamamura, Hiroe; Nakashima, Koji; Tan, Lea Chua; Okabe, Satoshi

2017-12-01

Wastewater effluents contain a significant number of toxic contaminants, which, even at low concentrations, display a wide variety of toxic actions. In this study, we developed a multiple-endpoints gene alteration-based (MEGA) assay, a real-time PCR-based transcriptomic analysis, to assess the water quality of wastewater effluents for human health risk assessment and management. Twenty-one genes from the human hepatoblastoma cell line (HepG2), covering the basic health-relevant stress responses such as response to xenobiotics, genotoxicity, and cytotoxicity, were selected and incorporated into the MEGA assay. The genes related to the p53-mediated DNA damage response and cytochrome P450 were selected as markers for genotoxicity and response to xenobiotics, respectively. Additionally, the genes that were dose-dependently regulated by exposure to the wastewater effluents were chosen as markers for cytotoxicity. The alterations in the expression of an individual gene, induced by exposure to the wastewater effluents, were evaluated by real-time PCR and the results were validated by genotoxicity (e.g., comet assay) and cell-based cytotoxicity tests. In summary, the MEGA assay is a real-time PCR-based assay that targets cellular responses to contaminants present in wastewater effluents at the transcriptional level; it is rapid, cost-effective, and high-throughput and can thus complement any chemical analysis for water quality assessment and management. Copyright © 2017 Elsevier Ltd. All rights reserved.

SLEPR: A Sample-Level Enrichment-Based Pathway Ranking Method — Seeking Biological Themes through Pathway-Level Consistency

PubMed Central

Yi, Ming; Stephens, Robert M.

2008-01-01

Analysis of microarray and other high throughput data often involves identification of genes consistently up or down-regulated across samples as the first step in extraction of biological meaning. This gene-level paradigm can be limited as a result of valid sample fluctuations and biological complexities. In this report, we describe a novel method, SLEPR, which eliminates this limitation by relying on pathway-level consistencies. Our method first selects the sample-level differentiated genes from each individual sample, capturing genes missed by other analysis methods, ascertains the enrichment levels of associated pathways from each of those lists, and then ranks annotated pathways based on the consistency of enrichment levels of individual samples from both sample classes. As a proof of concept, we have used this method to analyze three public microarray datasets with a direct comparison with the GSEA method, one of the most popular pathway-level analysis methods in the field. We found that our method was able to reproduce the earlier observations with significant improvements in depth of coverage for validated or expected biological themes, but also produced additional insights that make biological sense. This new method extends existing analyses approaches and facilitates integration of different types of HTP data. PMID:18818771

Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients

PubMed Central

2016-01-01

Abstract Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z -score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z -score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z -score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications. PMID:26504096

The Role of the Y-Located TSPY Gene in Prostatic Oncogenesis

DTIC Science & Technology

2007-02-01

to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data ...from CIS to invasive germ cell tumors [7, 31]. To validate the microarray data , we had selected 4 up-regulated (RGC32, PDGFC, WNT5A and CCND2) and 4...on selection medium ( data not shown). eEF1A1 is one of two isoforms (eEF1A1 and eEF1A2) of translation elongation factor alpha (eEF1A). eEF1A1 is

Candidate Reference Genes Selection and Application for RT-qPCR Analysis in Kenaf with Cytoplasmic Male Sterility Background

PubMed Central

Zhou, Bujin; Chen, Peng; Khan, Aziz; Zhao, Yanhong; Chen, Lihong; Liu, Dongmei; Liao, Xiaofang; Kong, Xiangjun; Zhou, Ruiyang

2017-01-01

Cytoplasmic male sterility (CMS) is a maternally inherited trait that results in the production of dysfunctional pollen. Based on reliable reference gene-normalized real-time quantitative PCR (RT-qPCR) data, examining gene expression profile can provide valuable information on the molecular mechanism of kenaf CMS. However, studies have not been conducted regarding selection of reference genes for normalizing RT-qPCR data in the CMS and maintainer lines of kenaf crop. Therefore, we studied 10 candidate reference genes (ACT3, ELF1A, G6PD, PEPKR1, TUB, TUA, CYP, GAPDH, H3, and 18S) to assess their expression stability at three stages of pollen development in CMS line 722A and maintainer line 722B of kenaf. Five computational statistical approaches (GeNorm, NormFinder, ΔCt, BestKeeper, and RefFinder) were used to evaluate the expression stability levels of these genes. According to RefFinder and GeNorm, the combination of TUB, CYP, and PEPKR1 was identified as an internal control for the accurate normalization across all sample set, which was further confirmed by validating the expression of HcPDIL5-2a. Furthermore, the combination of TUB, CYP, and PEPKR1 was used to differentiate the expression pattern of five mitochondria F1F0-ATPase subunit genes (atp1, atp4, atp6, atp8, and atp9) by RT-qPCR during pollen development in CMS line 722A and maintainer line 722B. We found that atp1, atp6, and atp9 exhibited significantly different expression patterns during pollen development in line 722A compared with line 722B. This is the first systematic study of reference genes selection for CMS and will provide useful information for future research on the gene expressions and molecular mechanisms underlying CMS in kenaf. PMID:28919905

Cancer Biomarkers from Genome-Scale DNA Methylation: Comparison of Evolutionary and Semantic Analysis Methods

PubMed Central

Valavanis, Ioannis; Pilalis, Eleftherios; Georgiadis, Panagiotis; Kyrtopoulos, Soterios; Chatziioannou, Aristotelis

2015-01-01

DNA methylation profiling exploits microarray technologies, thus yielding a wealth of high-volume data. Here, an intelligent framework is applied, encompassing epidemiological genome-scale DNA methylation data produced from the Illumina’s Infinium Human Methylation 450K Bead Chip platform, in an effort to correlate interesting methylation patterns with cancer predisposition and, in particular, breast cancer and B-cell lymphoma. Feature selection and classification are employed in order to select, from an initial set of ~480,000 methylation measurements at CpG sites, predictive cancer epigenetic biomarkers and assess their classification power for discriminating healthy versus cancer related classes. Feature selection exploits evolutionary algorithms or a graph-theoretic methodology which makes use of the semantics information included in the Gene Ontology (GO) tree. The selected features, corresponding to methylation of CpG sites, attained moderate-to-high classification accuracies when imported to a series of classifiers evaluated by resampling or blindfold validation. The semantics-driven selection revealed sets of CpG sites performing similarly with evolutionary selection in the classification tasks. However, gene enrichment and pathway analysis showed that it additionally provides more descriptive sets of GO terms and KEGG pathways regarding the cancer phenotypes studied here. Results support the expediency of this methodology regarding its application in epidemiological studies. PMID:27600245

Overexpression of Plasminogen Activator Inhibitor-1 in Advanced Gastric Cancer with Aggressive Lymph Node Metastasis

PubMed Central

Suh, Yun-Suhk; Yu, Jieun; Kim, Byung Chul; Choi, Boram; Han, Tae-Su; Ahn, Hye Seong; Kong, Seong-Ho; Lee, Hyuk-Joon; Kim, Woo Ho; Yang, Han-Kwang

2015-01-01

Purpose The purpose of this study is to investigate differentially expressed genes using DNA microarray between advanced gastric cancer (AGC) with aggressive lymph node (LN) metastasis and that with a more advanced tumor stage but without LN metastasis. Materials and Methods Five sample pairs of gastric cancer tissue and normal gastric mucosa were taken from three patients with T3N3 stage (highN) and two with T4N0 stage (lowN). Data from triplicate DNA microarray experiments were analyzed, and candidate genes were identified using a volcano plot that showed ≥ 2-fold differential expression and were significant by Welch's t test (p < 0.05) between highN and lowN. Those selected genes were validated independently by reverse-transcriptase–polymerase chain reaction (RT-PCR) using five AGC patients, and tissue-microarray (TMA) comprising 47 AGC patients. Results CFTR, LAMC2, SERPINE2, F2R, MMP7, FN1, TIMP1, plasminogen activator inhibitor-1 (PAI-1), ITGB8, SDS, and TMPRSS4 were commonly up-regulated over 2-fold in highN. REG3A, CD24, ITLN1, and WBP5 were commonly down-regulated over 2-fold in lowN. Among these genes, overexpression of PAI-1 was validated by RT-PCR, and TMA showed 16.7% (7/42) PAI-1 expression in T3N3, but none (0/5) in T4N0 (p=0.393). Conclusion DNA microarray analysis and validation by RT-PCR and TMA showed that overexpression of PAI-1 is related to aggressive LN metastasis in AGC. PMID:25687870

A Systematic Investigation into Aging Related Genes in Brain and Their Relationship with Alzheimer's Disease.

PubMed

Meng, Guofeng; Zhong, Xiaoyan; Mei, Hongkang

2016-01-01

Aging, as a complex biological process, is accompanied by the accumulation of functional loses at different levels, which makes age to be the biggest risk factor to many neurological diseases. Even following decades of investigation, the process of aging is still far from being fully understood, especially at a systematic level. In this study, we identified aging related genes in brain by collecting the ones with sustained and consistent gene expression or DNA methylation changes in the aging process. Functional analysis with Gene Ontology to these genes suggested transcriptional regulators to be the most affected genes in the aging process. Transcription regulation analysis found some transcription factors, especially Specificity Protein 1 (SP1), to play important roles in regulating aging related gene expression. Module-based functional analysis indicated these genes to be associated with many well-known aging related pathways, supporting the validity of our approach to select aging related genes. Finally, we investigated the roles of aging related genes on Alzheimer's Disease (AD). We found that aging and AD related genes both involved some common pathways, which provided a possible explanation why aging made the brain more vulnerable to Alzheimer's Disease.

Transcriptional analysis of abdominal fat in chickens divergently selected on bodyweight at two ages reveals novel mechanisms controlling adiposity: validating visceral adipose tissue as a dynamic endocrine and metabolic organ.

PubMed

Resnyk, C W; Carré, W; Wang, X; Porter, T E; Simon, J; Le Bihan-Duval, E; Duclos, M J; Aggrey, S E; Cogburn, L A

2017-08-16

Decades of intensive genetic selection in the domestic chicken (Gallus gallus domesticus) have enabled the remarkable rapid growth of today's broiler (meat-type) chickens. However, this enhanced growth rate was accompanied by several unfavorable traits (i.e., increased visceral fatness, leg weakness, and disorders of metabolism and reproduction). The present descriptive analysis of the abdominal fat transcriptome aimed to identify functional genes and biological pathways that likely contribute to an extreme difference in visceral fatness of divergently selected broiler chickens. We used the Del-Mar 14 K Chicken Integrated Systems microarray to take time-course snapshots of global gene transcription in abdominal fat of juvenile [1-11 weeks of age (wk)] chickens divergently selected on bodyweight at two ages (8 and 36 wk). Further, a RNA sequencing analysis was completed on the same abdominal fat samples taken from high-growth (HG) and low-growth (LG) cockerels at 7 wk, the age with the greatest divergence in body weight (3.2-fold) and visceral fatness (19.6-fold). Time-course microarray analysis revealed 312 differentially expressed genes (FDR ≤ 0.05) as the main effect of genotype (HG versus LG), 718 genes in the interaction of age and genotype, and 2918 genes as the main effect of age. The RNA sequencing analysis identified 2410 differentially expressed genes in abdominal fat of HG versus LG chickens at 7 wk. The HG chickens are fatter and over-express numerous genes that support higher rates of visceral adipogenesis and lipogenesis. In abdominal fat of LG chickens, we found higher expression of many genes involved in hemostasis, energy catabolism and endocrine signaling, which likely contribute to their leaner phenotype and slower growth. Many transcription factors and their direct target genes identified in HG and LG chickens could be involved in their divergence in adiposity and growth rate. The present analyses of the visceral fat transcriptome in chickens divergently selected for a large difference in growth rate and abdominal fatness clearly demonstrate that abdominal fat is a very dynamic metabolic and endocrine organ in the chicken. The HG chickens overexpress many transcription factors and their direct target genes, which should enhance in situ lipogenesis and ultimately adiposity. Our observation of enhanced expression of hemostasis and endocrine-signaling genes in diminished abdominal fat of LG cockerels provides insight into genetic mechanisms involved in divergence of abdominal fatness and somatic growth in avian and perhaps mammalian species, including humans.

DeepSAGE Based Differential Gene Expression Analysis under Cold and Freeze Stress in Seabuckthorn (Hippophae rhamnoides L.)

PubMed Central

Chaudhary, Saurabh; Sharma, Prakash C.

2015-01-01

Seabuckthorn (Hippophae rhamnoides L.), an important plant species of Indian Himalayas, is well known for its immense medicinal and nutritional value. The plant has the ability to sustain growth in harsh environments of extreme temperatures, drought and salinity. We employed DeepSAGE, a tag based approach, to identify differentially expressed genes under cold and freeze stress in seabuckthorn. In total 36.2 million raw tags including 13.9 million distinct tags were generated using Illumina sequencing platform for three leaf tissue libraries including control (CON), cold stress (CS) and freeze stress (FS). After discarding low quality tags, 35.5 million clean tags including 7 million distinct clean tags were obtained. In all, 11922 differentially expressed genes (DEGs) including 6539 up regulated and 5383 down regulated genes were identified in three comparative setups i.e. CON vs CS, CON vs FS and CS vs FS. Gene ontology and KEGG pathway analysis were performed to assign gene ontology term to DEGs and ascertain their biological functions. DEGs were mapped back to our existing seabuckthorn transcriptome assembly comprising of 88,297 putative unigenes leading to the identification of 428 cold and freeze stress responsive genes. Expression of randomly selected 22 DEGs was validated using qRT-PCR that further supported our DeepSAGE results. The present study provided a comprehensive view of global gene expression profile of seabuckthorn under cold and freeze stresses. The DeepSAGE data could also serve as a valuable resource for further functional genomics studies aiming selection of candidate genes for development of abiotic stress tolerant transgenic plants. PMID:25803684

DeepSAGE based differential gene expression analysis under cold and freeze stress in seabuckthorn (Hippophae rhamnoides L.).

PubMed

Chaudhary, Saurabh; Sharma, Prakash C

2015-01-01

Seabuckthorn (Hippophae rhamnoides L.), an important plant species of Indian Himalayas, is well known for its immense medicinal and nutritional value. The plant has the ability to sustain growth in harsh environments of extreme temperatures, drought and salinity. We employed DeepSAGE, a tag based approach, to identify differentially expressed genes under cold and freeze stress in seabuckthorn. In total 36.2 million raw tags including 13.9 million distinct tags were generated using Illumina sequencing platform for three leaf tissue libraries including control (CON), cold stress (CS) and freeze stress (FS). After discarding low quality tags, 35.5 million clean tags including 7 million distinct clean tags were obtained. In all, 11922 differentially expressed genes (DEGs) including 6539 up regulated and 5383 down regulated genes were identified in three comparative setups i.e. CON vs CS, CON vs FS and CS vs FS. Gene ontology and KEGG pathway analysis were performed to assign gene ontology term to DEGs and ascertain their biological functions. DEGs were mapped back to our existing seabuckthorn transcriptome assembly comprising of 88,297 putative unigenes leading to the identification of 428 cold and freeze stress responsive genes. Expression of randomly selected 22 DEGs was validated using qRT-PCR that further supported our DeepSAGE results. The present study provided a comprehensive view of global gene expression profile of seabuckthorn under cold and freeze stresses. The DeepSAGE data could also serve as a valuable resource for further functional genomics studies aiming selection of candidate genes for development of abiotic stress tolerant transgenic plants.

Transcriptome Sequencing Identified Genes and Gene Ontologies Associated with Early Freezing Tolerance in Maize

PubMed Central

Li, Zhao; Hu, Guanghui; Liu, Xiangfeng; Zhou, Yao; Li, Yu; Zhang, Xu; Yuan, Xiaohui; Zhang, Qian; Yang, Deguang; Wang, Tianyu; Zhang, Zhiwu

2016-01-01

Originating in a tropical climate, maize has faced great challenges as cultivation has expanded to the majority of the world's temperate zones. In these zones, frost and cold temperatures are major factors that prevent maize from reaching its full yield potential. Among 30 elite maize inbred lines adapted to northern China, we identified two lines of extreme, but opposite, freezing tolerance levels—highly tolerant and highly sensitive. During the seedling stage of these two lines, we used RNA-seq to measure changes in maize whole genome transcriptome before and after freezing treatment. In total, 19,794 genes were expressed, of which 4550 exhibited differential expression due to either treatment (before or after freezing) or line type (tolerant or sensitive). Of the 4550 differently expressed genes, 948 exhibited differential expression due to treatment within line or lines under freezing condition. Analysis of gene ontology found that these 948 genes were significantly enriched for binding functions (DNA binding, ATP binding, and metal ion binding), protein kinase activity, and peptidase activity. Based on their enrichment, literature support, and significant levels of differential expression, 30 of these 948 genes were selected for quantitative real-time PCR (qRT-PCR) validation. The validation confirmed our RNA-Seq-based findings, with squared correlation coefficients of 80% and 50% in the tolerance and sensitive lines, respectively. This study provided valuable resources for further studies to enhance understanding of the molecular mechanisms underlying maize early freezing response and enable targeted breeding strategies for developing varieties with superior frost resistance to achieve yield potential. PMID:27774095

The expression dynamics of mechanosensitive genes in extra-embryonic vasculature after heart starts to beat in chick embryo.

PubMed

Rajendran, Saranya; Sundaresan, Lakshmikirupa; Rajendran, Krithika; Selvaraj, Monica; Gupta, Ravi; Chatterjee, Suvro

2016-02-11

Fluid flow plays an important role in vascular development. However, the detailed mechanisms, particularly the link between flow and modulation of gene expression during vascular development, remain unexplored. In chick embryo, the key events of vascular development from initiation of heart beat to establishment of effective blood flow occur between the stages HH10 and HH13. Therefore, we propose a novel in vivo model to study the flow experienced by developing endothelium. Using this model, we aimed to capture the transcriptome dynamics of the pre- and post-flow conditions. RNA was isolated from extra embryonic area vasculosa (EE-AV) pooled from three chick embryos between HH10-HH13 and RNA sequencing was performed. The whole transcriptome sequencing of chick identified up-regulation of some of the previously well-known mechanosensitive genes including NFR2, HAND1, CTGF and KDR. GO analyses of the up-regulated genes revealed enrichment of several biological processes including heart development, extracellular matrix organization, cell-matrix adhesion, cell migration, blood vessel development, patterning of blood vessels, collagen fibril organization. Genes encoding for gap junctions proteins which are involved in vascular remodeling and arterial-venous differentiation, and genes involved in cell-cell adhesion, and ECM interactions were significantly up-regulated. Validation of selected genes through semi quantitative PCR was performed. The study indicates that shear stress plays a major role in development. Through appropriate validation, this platform can serve as an in vivo model to study conditions of disturbed flow in pathology as well as normal flow during development.

THE INVOLVEMENT OF HUMAN MONOGENIC CARDIOMYOPATHY GENES IN EXPERIMENTAL POLYGENIC CARDIAC HYPERTROPHY.

PubMed

Prestes, Priscilla R; Marques, Francine Z; Lopez-Campos, Guillermo; Lewandowski, Paul; Delbridge, Lea M D; Charchar, Fadi J; Harrap, Stephen B

2018-05-18

Hypertrophic cardiomyopathy thickens heart muscles reducing functionality and increasing risk of cardiac disease and morbidity. Genetic factors are involved, but their contribution is poorly understood. We used the hypertrophic heart rat (HHR), a unique normotensive polygenic model of cardiac hypertrophy and heart failure to investigate the role of genes associated with monogenic human cardiomyopathy. We selected 42 genes involved in monogenic human cardiomyopathies to study: 1) DNA variants, by sequencing the whole-genome of 13-week old HHR and age-matched normal heart rat (NHR), its genetic control strain; 2) mRNA expression, by targeted RNA-sequencing in left ventricles of HHR and NHR at five ages (2-days old, 4-, 13-, 33- and 50-weeks old) compared to human idiopathic dilated data; and 3) microRNA expression, with rat microRNA microarrays in left ventricles of 2-days old HHR and age-matched NHR. We also investigated experimentally validated microRNA-mRNA interactions. Whole-genome sequencing revealed unique variants mostly located in non-coding regions of HHR and NHR. We found 29 genes differentially expressed in at least one age. Genes encoding desmoglein 2 (Dsg2) and transthyretin (Ttr) were significantly differentially expressed at all ages in the HHR, but only Ttr was also differentially expressed in human idiopathic cardiomyopathy. Lastly, only two microRNAs differentially expressed in the HHR were present in our comparison of validated microRNA-mRNA interactions. These two microRNAs interact with five of the genes studied. Our study shows that genes involved in monogenic forms of human cardiomyopathies may also influence polygenic forms of the disease.

Characterization and Targeting of the Aldehyde Dehydrogenase Subpopulation in Ovarian Cancer

DTIC Science & Technology

2012-07-01

Targeting the Hedgehog pathway reverses taxane resistance in ovarian cancer. Proceedings of the 42 nd Annual Society of Gynecologic Oncologists...Meeting, 2011. Steg AD, Ziebarth AA, Katre A, Landen CN Jr. Targeting hedgehog reverses taxane resistance by Gli-dependent and independent mechanisms in...pathways ( Hedgehog , Notch, TGF-b, and Wnt). Select genes of interest were validated as important targets using siRNA-mediated downregulation. Results

[Prognostic and predictive molecular markers for urologic cancers].

PubMed

Hartmann, A; Schlomm, T; Bertz, S; Heinzelmann, J; Hölters, S; Simon, R; Stoehr, R; Junker, K

2014-04-01

Molecular prognostic factors and genetic alterations as predictive markers for cancer-specific targeted therapies are used today in the clinic for many malignancies. In recent years, many molecular markers for urogenital cancers have also been identified. However, these markers are not clinically used yet. In prostate cancer, novel next-generation sequencing methods revealed a detailed picture of the molecular changes. There is growing evidence that a combination of classical histopathological and validated molecular markers could lead to a more precise estimation of prognosis, thus, resulting in an increasing number of patients with active surveillance as a possible treatment option. In patients with urothelial carcinoma, histopathological factors but also the proliferation of the tumor, mutations in oncogenes leading to an increasing proliferation rate and changes in genes responsible for invasion and metastasis are important. In addition, gene expression profiles which could distinguish aggressive tumors with high risk of metastasis from nonmetastasizing tumors have been recently identified. In the future, this could potentially allow better selection of patients needing systemic perioperative treatment. In renal cell carcinoma, many molecular markers that are associated with metastasis and survival have been identified. Some of these markers were also validated as independent prognostic markers. Selection of patients with primarily organ-confined tumors and increased risk of metastasis for adjuvant systemic therapy could be clinically relevant in the future.

Transcriptome Wide Identification and Validation of Calcium Sensor Gene Family in the Developing Spikes of Finger Millet Genotypes for Elucidating Its Role in Grain Calcium Accumulation

PubMed Central

Singh, Uma M.; Chandra, Muktesh; Shankhdhar, Shailesh C.; Kumar, Anil

2014-01-01

Background In finger millet, calcium is one of the important and abundant mineral elements. The molecular mechanisms involved in calcium accumulation in plants remains poorly understood. Transcriptome sequencing of genetically diverse genotypes of finger millet differing in grain calcium content will help in understanding the trait. Principal Finding In this study, the transcriptome sequencing of spike tissues of two genotypes of finger millet differing in their grain calcium content, were performed for the first time. Out of 109,218 contigs, 78 contigs in case of GP-1 (Low Ca genotype) and out of 120,130 contigs 76 contigs in case of GP-45 (High Ca genotype), were identified as calcium sensor genes. Through in silico analysis all 82 unique calcium sensor genes were classified into eight calcium sensor gene family viz., CaM & CaMLs, CBLs, CIPKs, CRKs, PEPRKs, CDPKs, CaMKs and CCaMK. Out of 82 genes, 12 were found diverse from the rice orthologs. The differential expression analysis on the basis of FPKM value resulted in 24 genes highly expressed in GP-45 and 11 genes highly expressed in GP-1. Ten of the 35 differentially expressed genes could be assigned to three documented pathways involved mainly in stress responses. Furthermore, validation of selected calcium sensor responder genes was also performed by qPCR, in developing spikes of both genotypes grown on different concentration of exogenous calcium. Conclusion Through de novo transcriptome data assembly and analysis, we reported the comprehensive identification and functional characterization of calcium sensor gene family. The calcium sensor gene family identified and characterized in this study will facilitate in understanding the molecular basis of calcium accumulation and development of calcium biofortified crops. Moreover, this study also supported that identification and characterization of gene family through Illumina paired-end sequencing is a potential tool for generating the genomic information of gene family in non-model species. PMID:25157851

Transcriptome wide identification and validation of calcium sensor gene family in the developing spikes of finger millet genotypes for elucidating its role in grain calcium accumulation.

PubMed

Singh, Uma M; Chandra, Muktesh; Shankhdhar, Shailesh C; Kumar, Anil

2014-01-01

In finger millet, calcium is one of the important and abundant mineral elements. The molecular mechanisms involved in calcium accumulation in plants remains poorly understood. Transcriptome sequencing of genetically diverse genotypes of finger millet differing in grain calcium content will help in understanding the trait. In this study, the transcriptome sequencing of spike tissues of two genotypes of finger millet differing in their grain calcium content, were performed for the first time. Out of 109,218 contigs, 78 contigs in case of GP-1 (Low Ca genotype) and out of 120,130 contigs 76 contigs in case of GP-45 (High Ca genotype), were identified as calcium sensor genes. Through in silico analysis all 82 unique calcium sensor genes were classified into eight calcium sensor gene family viz., CaM & CaMLs, CBLs, CIPKs, CRKs, PEPRKs, CDPKs, CaMKs and CCaMK. Out of 82 genes, 12 were found diverse from the rice orthologs. The differential expression analysis on the basis of FPKM value resulted in 24 genes highly expressed in GP-45 and 11 genes highly expressed in GP-1. Ten of the 35 differentially expressed genes could be assigned to three documented pathways involved mainly in stress responses. Furthermore, validation of selected calcium sensor responder genes was also performed by qPCR, in developing spikes of both genotypes grown on different concentration of exogenous calcium. Through de novo transcriptome data assembly and analysis, we reported the comprehensive identification and functional characterization of calcium sensor gene family. The calcium sensor gene family identified and characterized in this study will facilitate in understanding the molecular basis of calcium accumulation and development of calcium biofortified crops. Moreover, this study also supported that identification and characterization of gene family through Illumina paired-end sequencing is a potential tool for generating the genomic information of gene family in non-model species.

A lung cancer risk classifier comprising genome maintenance genes measured in normal bronchial epithelial cells.

PubMed

Yeo, Jiyoun; Crawford, Erin L; Zhang, Xiaolu; Khuder, Sadik; Chen, Tian; Levin, Albert; Blomquist, Thomas M; Willey, James C

2017-05-02

Annual low dose CT (LDCT) screening of individuals at high demographic risk reduces lung cancer mortality by more than 20%. However, subjects selected for screening based on demographic criteria typically have less than a 10% lifetime risk for lung cancer. Thus, there is need for a biomarker that better stratifies subjects for LDCT screening. Toward this goal, we previously reported a lung cancer risk test (LCRT) biomarker comprising 14 genome-maintenance (GM) pathway genes measured in normal bronchial epithelial cells (NBEC) that accurately classified cancer (CA) from non-cancer (NC) subjects. The primary goal of the studies reported here was to optimize the LCRT biomarker for high specificity and ease of clinical implementation. Targeted competitive multiplex PCR amplicon libraries were prepared for next generation sequencing (NGS) analysis of transcript abundance at 68 sites among 33 GM target genes in NBEC specimens collected from a retrospective cohort of 120 subjects, including 61 CA cases and 59 NC controls. Genes were selected for analysis based on contribution to the previously reported LCRT biomarker and/or prior evidence for association with lung cancer risk. Linear discriminant analysis was used to identify the most accurate classifier suitable to stratify subjects for screening. After cross-validation, a model comprising expression values from 12 genes (CDKN1A, E2F1, ERCC1, ERCC4, ERCC5, GPX1, GSTP1, KEAP1, RB1, TP53, TP63, and XRCC1) and demographic factors age, gender, and pack-years smoking, had Receiver Operator Characteristic area under the curve (ROC AUC) of 0.975 (95% CI: 0.96-0.99). The overall classification accuracy was 93% (95% CI 88%-98%) with sensitivity 93.1%, specificity 92.9%, positive predictive value 93.1% and negative predictive value 93%. The ROC AUC for this classifier was significantly better (p < 0.0001) than the best model comprising demographic features alone. The LCRT biomarker reported here displayed high accuracy and ease of implementation on a high throughput, quality-controlled targeted NGS platform. As such, it is optimized for clinical validation in specimens from the ongoing LCRT blinded prospective cohort study. Following validation, the biomarker is expected to have clinical utility by better stratifying subjects for annual lung cancer screening compared to current demographic criteria alone.

Identification of reference genes for RT-qPCR in the Antarctic moss Sanionia uncinata under abiotic stress conditions

PubMed Central

Park, Mira; Hong, Soon Gyu; Park, Hyun; Lee, Byeong-ha

2018-01-01

Sanionia uncinata is a dominant moss species in the maritime Antarctic. Due to its high adaptability to harsh environments, this extremophile plant has been considered a good target for studying the molecular adaptation mechanisms of plants to a variety of environmental stresses. Despite the importance of S. uncinata as a representative Antarctic plant species for the identification and characterization of genes associated with abiotic stress tolerance, suitable reference genes, which are critical for RT-qPCR analyses, have not yet been identified. In this report, 11 traditionally used and 6 novel candidate reference genes were selected from transcriptome data of S. uncinata and the expression stability of these genes was evaluated under various abiotic stress conditions using three statistical algorithms; geNorm, NormFinder, and BestKeeper. The stability ranking analysis selected the best reference genes depending on the stress conditions. Among the 17 candidates, the most stable references were POB1 and UFD2 for cold stress, POB1 and AKB for drought treatment, and UFD2 and AKB for the field samples from a different water contents in Antarctica. Overall, novel genes POB1 and AKB were the most reliable references across all samples, irrespective of experimental conditions. In addition, 6 novel candidate genes including AKB, POB1 and UFD2, were more stable than the housekeeping genes traditionally used for internal controls, indicating that transcriptome data can be useful for identifying novel robust normalizers. The reference genes validated in this study will be useful for improving the accuracy of RT-qPCR analysis for gene expression studies of S. uncinata in Antarctica and for further functional genomic analysis of bryophytes. PMID:29920565

Transcriptional profiling identifies differentially expressed genes in developing turkey skeletal muscle

PubMed Central

2011-01-01

Background Skeletal muscle growth and development from embryo to adult consists of a series of carefully regulated changes in gene expression. Understanding these developmental changes in agriculturally important species is essential to the production of high quality meat products. For example, consumer demand for lean, inexpensive meat products has driven the turkey industry to unprecedented production through intensive genetic selection. However, achievements of increased body weight and muscle mass have been countered by an increased incidence of myopathies and meat quality defects. In a previous study, we developed and validated a turkey skeletal muscle-specific microarray as a tool for functional genomics studies. The goals of the current study were to utilize this microarray to elucidate functional pathways of genes responsible for key events in turkey skeletal muscle development and to compare differences in gene expression between two genetic lines of turkeys. To achieve these goals, skeletal muscle samples were collected at three critical stages in muscle development: 18d embryo (hyperplasia), 1d post-hatch (shift from myoblast-mediated growth to satellite cell-modulated growth by hypertrophy), and 16wk (market age) from two genetic lines: a randombred control line (RBC2) maintained without selection pressure, and a line (F) selected from the RBC2 line for increased 16wk body weight. Array hybridizations were performed in two experiments: Experiment 1 directly compared the developmental stages within genetic line, while Experiment 2 directly compared the two lines within each developmental stage. Results A total of 3474 genes were differentially expressed (false discovery rate; FDR < 0.001) by overall effect of development, while 16 genes were differentially expressed (FDR < 0.10) by overall effect of genetic line. Ingenuity Pathways Analysis was used to group annotated genes into networks, functions, and canonical pathways. The expression of 28 genes involved in extracellular matrix regulation, cell death/apoptosis, and calcium signaling/muscle function, as well as genes with miscellaneous function was confirmed by qPCR. Conclusions The current study identified gene pathways and uncovered novel genes important in turkey muscle growth and development. Future experiments will focus further on several of these candidate genes and the expression and mechanism of action of their protein products. PMID:21385442

Validation of housekeeping genes as an internal control for gene expression studies in Giardia lamblia using quantitative real-time PCR.

PubMed

Marcial-Quino, Jaime; Fierro, Francisco; De la Mora-De la Mora, Ignacio; Enríquez-Flores, Sergio; Gómez-Manzo, Saúl; Vanoye-Carlo, America; Garcia-Torres, Itzhel; Sierra-Palacios, Edgar; Reyes-Vivas, Horacio

2016-04-25

The analysis of transcript levels of specific genes is important for understanding transcriptional regulation and for the characterization of gene function. Real-time quantitative reverse transcriptase PCR (RT-qPCR) has become a powerful tool to quantify gene expression. The objective of this study was to identify reliable housekeeping genes in Giardia lamblia. Twelve genes were selected for this purpose, and their expression was analyzed in the wild type WB strain and in two strains with resistance to nitazoxanide (NTZ) and metronidazole (MTZ), respectively. RefFinder software analysis showed that the expression of the genes is different in the three strains. The integrated data from the four analyses showed that the NADH oxidase (NADH) and aldolase (ALD) genes were the most steadily expressed genes, whereas the glyceraldehyde-3-phosphate dehydrogenase gene was the most unstable. Additionally, the relative expression of seven genes were quantified in the NTZ- and MTZ-resistant strains by RT-qPCR, using the aldolase gene as the internal control, and the results showed a consistent differential pattern of expression in both strains. The housekeeping genes found in this work will facilitate the analysis of mRNA expression levels of other genes of interest in G. lamblia. Copyright © 2016 Elsevier B.V. All rights reserved.

GSNFS: Gene subnetwork biomarker identification of lung cancer expression data.

PubMed

Doungpan, Narumol; Engchuan, Worrawat; Chan, Jonathan H; Meechai, Asawin

2016-12-05

Gene expression has been used to identify disease gene biomarkers, but there are ongoing challenges. Single gene or gene-set biomarkers are inadequate to provide sufficient understanding of complex disease mechanisms and the relationship among those genes. Network-based methods have thus been considered for inferring the interaction within a group of genes to further study the disease mechanism. Recently, the Gene-Network-based Feature Set (GNFS), which is capable of handling case-control and multiclass expression for gene biomarker identification, has been proposed, partly taking into account of network topology. However, its performance relies on a greedy search for building subnetworks and thus requires further improvement. In this work, we establish a new approach named Gene Sub-Network-based Feature Selection (GSNFS) by implementing the GNFS framework with two proposed searching and scoring algorithms, namely gene-set-based (GS) search and parent-node-based (PN) search, to identify subnetworks. An additional dataset is used to validate the results. The two proposed searching algorithms of the GSNFS method for subnetwork expansion are concerned with the degree of connectivity and the scoring scheme for building subnetworks and their topology. For each iteration of expansion, the neighbour genes of a current subnetwork, whose expression data improved the overall subnetwork score, is recruited. While the GS search calculated the subnetwork score using an activity score of a current subnetwork and the gene expression values of its neighbours, the PN search uses the expression value of the corresponding parent of each neighbour gene. Four lung cancer expression datasets were used for subnetwork identification. In addition, using pathway data and protein-protein interaction as network data in order to consider the interaction among significant genes were discussed. Classification was performed to compare the performance of the identified gene subnetworks with three subnetwork identification algorithms. The two searching algorithms resulted in better classification and gene/gene-set agreement compared to the original greedy search of the GNFS method. The identified lung cancer subnetwork using the proposed searching algorithm resulted in an improvement of the cross-dataset validation and an increase in the consistency of findings between two independent datasets. The homogeneity measurement of the datasets was conducted to assess dataset compatibility in cross-dataset validation. The lung cancer dataset with higher homogeneity showed a better result when using the GS search while the dataset with low homogeneity showed a better result when using the PN search. The 10-fold cross-dataset validation on the independent lung cancer datasets showed higher classification performance of the proposed algorithms when compared with the greedy search in the original GNFS method. The proposed searching algorithms provide a higher number of genes in the subnetwork expansion step than the greedy algorithm. As a result, the performance of the subnetworks identified from the GSNFS method was improved in terms of classification performance and gene/gene-set level agreement depending on the homogeneity of the datasets used in the analysis. Some common genes obtained from the four datasets using different searching algorithms are genes known to play a role in lung cancer. The improvement of classification performance and the gene/gene-set level agreement, and the biological relevance indicated the effectiveness of the GSNFS method for gene subnetwork identification using expression data.

Genetic analyses of bolting in bulb onion (Allium cepa L.).

PubMed

Baldwin, Samantha; Revanna, Roopashree; Pither-Joyce, Meeghan; Shaw, Martin; Wright, Kathryn; Thomson, Susan; Moya, Leire; Lee, Robyn; Macknight, Richard; McCallum, John

2014-03-01

We present the first evidence for a QTL conditioning an adaptive trait in bulb onion, and the first linkage and population genetics analyses of candidate genes involved in photoperiod and vernalization physiology. Economic production of bulb onion (Allium cepa L.) requires adaptation to photoperiod and temperature such that a bulb is formed in the first year and a flowering umbel in the second. 'Bolting', or premature flowering before bulb maturation, is an undesirable trait strongly selected against by breeders during adaptation of germplasm. To identify genome regions associated with adaptive traits we conducted linkage mapping and population genetic analyses of candidate genes, and QTL analysis of bolting using a low-density linkage map. We performed tagged amplicon sequencing of ten candidate genes, including the FT-like gene family, in eight diverse populations to identify polymorphisms and seek evidence of differentiation. Low nucleotide diversity and negative estimates of Tajima's D were observed for most genes, consistent with purifying selection. Significant population differentiation was observed only in AcFT2 and AcSOC1. Selective genotyping in a large 'Nasik Red × CUDH2150' F2 family revealed genome regions on chromosomes 1, 3 and 6 associated (LOD > 3) with bolting. Validation genotyping of two F2 families grown in two environments confirmed that a QTL on chromosome 1, which we designate AcBlt1, consistently conditions bolting susceptibility in this cross. The chromosome 3 region, which coincides with a functionally characterised acid invertase, was not associated with bolting in other environments, but showed significant association with bulb sucrose content in this and other mapping pedigrees. These putative QTL and candidate genes were placed on the onion map, enabling future comparative studies of adaptive traits.

Characteristics of genomic signatures derived using univariate methods and mechanistically anchored functional descriptors for predicting drug- and xenobiotic-induced nephrotoxicity.

PubMed

Shi, Weiwei; Bugrim, Andrej; Nikolsky, Yuri; Nikolskya, Tatiana; Brennan, Richard J

2008-01-01

ABSTRACT The ideal toxicity biomarker is composed of the properties of prediction (is detected prior to traditional pathological signs of injury), accuracy (high sensitivity and specificity), and mechanistic relationships to the endpoint measured (biological relevance). Gene expression-based toxicity biomarkers ("signatures") have shown good predictive power and accuracy, but are difficult to interpret biologically. We have compared different statistical methods of feature selection with knowledge-based approaches, using GeneGo's database of canonical pathway maps, to generate gene sets for the classification of renal tubule toxicity. The gene set selection algorithms include four univariate analyses: t-statistics, fold-change, B-statistics, and RankProd, and their combination and overlap for the identification of differentially expressed probes. Enrichment analysis following the results of the four univariate analyses, Hotelling T-square test, and, finally out-of-bag selection, a variant of cross-validation, were used to identify canonical pathway maps-sets of genes coordinately involved in key biological processes-with classification power. Differentially expressed genes identified by the different statistical univariate analyses all generated reasonably performing classifiers of tubule toxicity. Maps identified by enrichment analysis or Hotelling T-square had lower classification power, but highlighted perturbed lipid homeostasis as a common discriminator of nephrotoxic treatments. The out-of-bag method yielded the best functionally integrated classifier. The map "ephrins signaling" performed comparably to a classifier derived using sparse linear programming, a machine learning algorithm, and represents a signaling network specifically involved in renal tubule development and integrity. Such functional descriptors of toxicity promise to better integrate predictive toxicogenomics with mechanistic analysis, facilitating the interpretation and risk assessment of predictive genomic investigations.

A polynomial based model for cell fate prediction in human diseases.

PubMed

Ma, Lichun; Zheng, Jie

2017-12-21

Cell fate regulation directly affects tissue homeostasis and human health. Research on cell fate decision sheds light on key regulators, facilitates understanding the mechanisms, and suggests novel strategies to treat human diseases that are related to abnormal cell development. In this study, we proposed a polynomial based model to predict cell fate. This model was derived from Taylor series. As a case study, gene expression data of pancreatic cells were adopted to test and verify the model. As numerous features (genes) are available, we employed two kinds of feature selection methods, i.e. correlation based and apoptosis pathway based. Then polynomials of different degrees were used to refine the cell fate prediction function. 10-fold cross-validation was carried out to evaluate the performance of our model. In addition, we analyzed the stability of the resultant cell fate prediction model by evaluating the ranges of the parameters, as well as assessing the variances of the predicted values at randomly selected points. Results show that, within both the two considered gene selection methods, the prediction accuracies of polynomials of different degrees show little differences. Interestingly, the linear polynomial (degree 1 polynomial) is more stable than others. When comparing the linear polynomials based on the two gene selection methods, it shows that although the accuracy of the linear polynomial that uses correlation analysis outcomes is a little higher (achieves 86.62%), the one within genes of the apoptosis pathway is much more stable. Considering both the prediction accuracy and the stability of polynomial models of different degrees, the linear model is a preferred choice for cell fate prediction with gene expression data of pancreatic cells. The presented cell fate prediction model can be extended to other cells, which may be important for basic research as well as clinical study of cell development related diseases.

Genome wide association study (GWAS) for grain yield in rice cultivated under water deficit.

PubMed

Pantalião, Gabriel Feresin; Narciso, Marcelo; Guimarães, Cléber; Castro, Adriano; Colombari, José Manoel; Breseghello, Flavio; Rodrigues, Luana; Vianello, Rosana Pereira; Borba, Tereza Oliveira; Brondani, Claudio

2016-12-01

The identification of rice drought tolerant materials is crucial for the development of best performing cultivars for the upland cultivation system. This study aimed to identify markers and candidate genes associated with drought tolerance by Genome Wide Association Study analysis, in order to develop tools for use in rice breeding programs. This analysis was made with 175 upland rice accessions (Oryza sativa), evaluated in experiments with and without water restriction, and 150,325 SNPs. Thirteen SNP markers associated with yield under drought conditions were identified. Through stepwise regression analysis, eight SNP markers were selected and validated in silico, and when tested by PCR, two out of the eight SNP markers were able to identify a group of rice genotypes with higher productivity under drought. These results are encouraging for deriving markers for the routine analysis of marker assisted selection. From the drought experiment, including the genes inherited in linkage blocks, 50 genes were identified, from which 30 were annotated, and 10 were previously related to drought and/or abiotic stress tolerance, such as the transcription factors WRKY and Apetala2, and protein kinases.

UDP-galactose and acetyl-CoA transporters as Plasmodium multidrug resistance genes.

PubMed

Lim, Michelle Yi-Xiu; LaMonte, Gregory; Lee, Marcus C S; Reimer, Christin; Tan, Bee Huat; Corey, Victoria; Tjahjadi, Bianca F; Chua, Adeline; Nachon, Marie; Wintjens, René; Gedeck, Peter; Malleret, Benoit; Renia, Laurent; Bonamy, Ghislain M C; Ho, Paul Chi-Lui; Yeung, Bryan K S; Chow, Eric D; Lim, Liting; Fidock, David A; Diagana, Thierry T; Winzeler, Elizabeth A; Bifani, Pablo

2016-09-19

A molecular understanding of drug resistance mechanisms enables surveillance of the effectiveness of new antimicrobial therapies during development and deployment in the field. We used conventional drug resistance selection as well as a regime of limiting dilution at early stages of drug treatment to probe two antimalarial imidazolopiperazines, KAF156 and GNF179. The latter approach permits the isolation of low-fitness mutants that might otherwise be out-competed during selection. Whole-genome sequencing of 24 independently derived resistant Plasmodium falciparum clones revealed four parasites with mutations in the known cyclic amine resistance locus (pfcarl) and a further 20 with mutations in two previously unreported P. falciparum drug resistance genes, an acetyl-CoA transporter (pfact) and a UDP-galactose transporter (pfugt). Mutations were validated both in vitro by CRISPR editing in P. falciparum and in vivo by evolution of resistant Plasmodium berghei mutants. Both PfACT and PfUGT were localized to the endoplasmic reticulum by fluorescence microscopy. As mutations in pfact and pfugt conveyed resistance against additional unrelated chemical scaffolds, these genes are probably involved in broad mechanisms of antimalarial drug resistance.

Evaluation of four endogenous reference genes and their real-time PCR assays for common wheat quantification in GMOs detection.

PubMed

Huang, Huali; Cheng, Fang; Wang, Ruoan; Zhang, Dabing; Yang, Litao

2013-01-01

Proper selection of endogenous reference genes and their real-time PCR assays is quite important in genetically modified organisms (GMOs) detection. To find a suitable endogenous reference gene and its real-time PCR assay for common wheat (Triticum aestivum L.) DNA content or copy number quantification, four previously reported wheat endogenous reference genes and their real-time PCR assays were comprehensively evaluated for the target gene sequence variation and their real-time PCR performance among 37 common wheat lines. Three SNPs were observed in the PKABA1 and ALMT1 genes, and these SNPs significantly decreased the efficiency of real-time PCR amplification. GeNorm analysis of the real-time PCR performance of each gene among common wheat lines showed that the Waxy-D1 assay had the lowest M values with the best stability among all tested lines. All results indicated that the Waxy-D1 gene and its real-time PCR assay were most suitable to be used as an endogenous reference gene for common wheat DNA content quantification. The validated Waxy-D1 gene assay will be useful in establishing accurate and creditable qualitative and quantitative PCR analysis of GM wheat.

Evaluation of Four Endogenous Reference Genes and Their Real-Time PCR Assays for Common Wheat Quantification in GMOs Detection

PubMed Central

Huang, Huali; Cheng, Fang; Wang, Ruoan; Zhang, Dabing; Yang, Litao

2013-01-01

Proper selection of endogenous reference genes and their real-time PCR assays is quite important in genetically modified organisms (GMOs) detection. To find a suitable endogenous reference gene and its real-time PCR assay for common wheat (Triticum aestivum L.) DNA content or copy number quantification, four previously reported wheat endogenous reference genes and their real-time PCR assays were comprehensively evaluated for the target gene sequence variation and their real-time PCR performance among 37 common wheat lines. Three SNPs were observed in the PKABA1 and ALMT1 genes, and these SNPs significantly decreased the efficiency of real-time PCR amplification. GeNorm analysis of the real-time PCR performance of each gene among common wheat lines showed that the Waxy-D1 assay had the lowest M values with the best stability among all tested lines. All results indicated that the Waxy-D1 gene and its real-time PCR assay were most suitable to be used as an endogenous reference gene for common wheat DNA content quantification. The validated Waxy-D1 gene assay will be useful in establishing accurate and creditable qualitative and quantitative PCR analysis of GM wheat. PMID:24098735

De novo characterization of Larimichthys crocea transcriptome for growth-/immune-related gene identification and massive microsatellite (SSR) marker development

NASA Astrophysics Data System (ADS)

Han, Zhaofang; Xiao, Shijun; Liu, Xiande; Liu, Yang; Li, Jiakai; Xie, Yangjie; Wang, Zhiyong

2017-03-01

The large yellow croaker, Larimichthys crocea is an important marine fish in China with a high economic value. In the last decade, the stock conservation and aquaculture industry of this species have been facing severe challenges because of wild population collapse and degeneration of important economic traits. However, genes contributing to growth and immunity in L. crocea have not been thoroughly analyzed, and available molecular markers are still not sufficient for genetic resource management and molecular selection. In this work, we sequenced the transcriptome in L. crocea liver tissue with a Roche 454 sequencing platform and assembled the transcriptome into 93 801 transcripts. Of them, 38 856 transcripts were successfully annotated in nt, nr, Swiss-Prot, InterPro, COG, GO and KEGG databases. Based on the annotation information, 3 165 unigenes related to growth and immunity were identified. Additionally, a total of 6 391 simple sequence repeats (SSRs) were identified from the transcriptome, among which 4 498 SSRs had enough flanking regions to design primers for polymerase chain reactions (PCR). To access the polymorphism of these markers, 30 primer pairs were randomly selected for PCR amplification and validation in 30 individuals, and 12 primer pairs (40.0%) exhibited obvious length polymorphisms. This work applied RNA-Seq to assemble and analyze a live transcriptome in L. crocea. With gene annotation and sequence information, genes related to growth and immunity were identified and massive SSR markers were developed, providing valuable genetic resources for future gene functional analysis and selective breeding of L. crocea.

A Novel Strategy for Selection and Validation of Reference Genes in Dynamic Multidimensional Experimental Design in Yeast

PubMed Central

Cankorur-Cetinkaya, Ayca; Dereli, Elif; Eraslan, Serpil; Karabekmez, Erkan; Dikicioglu, Duygu; Kirdar, Betul

2012-01-01

Background Understanding the dynamic mechanism behind the transcriptional organization of genes in response to varying environmental conditions requires time-dependent data. The dynamic transcriptional response obtained by real-time RT-qPCR experiments could only be correctly interpreted if suitable reference genes are used in the analysis. The lack of available studies on the identification of candidate reference genes in dynamic gene expression studies necessitates the identification and the verification of a suitable gene set for the analysis of transient gene expression response. Principal Findings In this study, a candidate reference gene set for RT-qPCR analysis of dynamic transcriptional changes in Saccharomyces cerevisiae was determined using 31 different publicly available time series transcriptome datasets. Ten of the twelve candidates (TPI1, FBA1, CCW12, CDC19, ADH1, PGK1, GCN4, PDC1, RPS26A and ARF1) we identified were not previously reported as potential reference genes. Our method also identified the commonly used reference genes ACT1 and TDH3. The most stable reference genes from this pool were determined as TPI1, FBA1, CDC19 and ACT1 in response to a perturbation in the amount of available glucose and as FBA1, TDH3, CCW12 and ACT1 in response to a perturbation in the amount of available ammonium. The use of these newly proposed gene sets outperformed the use of common reference genes in the determination of dynamic transcriptional response of the target genes, HAP4 and MEP2, in response to relaxation from glucose and ammonium limitations, respectively. Conclusions A candidate reference gene set to be used in dynamic real-time RT-qPCR expression profiling in yeast was proposed for the first time in the present study. Suitable pools of stable reference genes to be used under different experimental conditions could be selected from this candidate set in order to successfully determine the expression profiles for the genes of interest. PMID:22675547

Massive NGS Data Analysis Reveals Hundreds Of Potential Novel Gene Fusions in Human Cell Lines.

PubMed

Gioiosa, Silvia; Bolis, Marco; Flati, Tiziano; Massini, Annalisa; Garattini, Enrico; Chillemi, Giovanni; Fratelli, Maddalena; Castrignanò, Tiziana

2018-06-01

Gene fusions derive from chromosomal rearrangements and the resulting chimeric transcripts are often endowed with oncogenic potential. Furthermore, they serve as diagnostic tools for the clinical classification of cancer subgroups with different prognosis and, in some cases, they can provide specific drug targets. So far, many efforts have been carried out to study gene fusion events occurring in tumor samples. In recent years, the availability of a comprehensive Next Generation Sequencing dataset for all the existing human tumor cell lines has provided the opportunity to further investigate these data in order to identify novel and still uncharacterized gene fusion events. In our work, we have extensively reanalyzed 935 paired-end RNA-seq experiments downloaded from "The Cancer Cell Line Encyclopedia" repository, aiming at addressing novel putative cell-line specific gene fusion events in human malignancies. The bioinformatics analysis has been performed by the execution of four different gene fusion detection algorithms. The results have been further prioritized by running a bayesian classifier which makes an in silico validation. The collection of fusion events supported by all of the predictive softwares results in a robust set of ∼ 1,700 in-silico predicted novel candidates suitable for downstream analyses. Given the huge amount of data and information produced, computational results have been systematized in a database named LiGeA. The database can be browsed through a dynamical and interactive web portal, further integrated with validated data from other well known repositories. Taking advantage of the intuitive query forms, the users can easily access, navigate, filter and select the putative gene fusions for further validations and studies. They can also find suitable experimental models for a given fusion of interest. We believe that the LiGeA resource can represent not only the first compendium of both known and putative novel gene fusion events in the catalog of all of the human malignant cell lines, but it can also become a handy starting point for wet-lab biologists who wish to investigate novel cancer biomarkers and specific drug targets.

Development and validation of a gene expression oligo microarray for the gilthead sea bream (Sparus aurata).

PubMed

Ferraresso, Serena; Vitulo, Nicola; Mininni, Alba N; Romualdi, Chiara; Cardazzo, Barbara; Negrisolo, Enrico; Reinhardt, Richard; Canario, Adelino V M; Patarnello, Tomaso; Bargelloni, Luca

2008-12-03

Aquaculture represents the most sustainable alternative of seafood supply to substitute for the declining marine fisheries, but severe production bottlenecks remain to be solved. The application of genomic technologies offers much promise to rapidly increase our knowledge on biological processes in farmed species and overcome such bottlenecks. Here we present an integrated platform for mRNA expression profiling in the gilthead sea bream (Sparus aurata), a marine teleost of great importance for aquaculture. A public data base was constructed, consisting of 19,734 unique clusters (3,563 contigs and 16,171 singletons). Functional annotation was obtained for 8,021 clusters. Over 4,000 sequences were also associated with a GO entry. Two 60mer probes were designed for each gene and in-situ synthesized on glass slides using Agilent SurePrint technology. Platform reproducibility and accuracy were assessed on two early stages of sea bream development (one-day and four days old larvae). Correlation between technical replicates was always > 0.99, with strong positive correlation between paired probes. A two class SAM test identified 1,050 differentially expressed genes between the two developmental stages. Functional analysis suggested that down-regulated transcripts (407) in older larvae are mostly essential/housekeeping genes, whereas tissue-specific genes are up-regulated in parallel with the formation of key organs (eye, digestive system). Cross-validation of microarray data was carried out using quantitative qRT-PCR on 11 target genes, selected to reflect the whole range of fold-change and both up-regulated and down-regulated genes. A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates. Good concordance between qRT-PCR and microarray data was observed between 2- and 7-fold change, while fold-change compression in the microarray was present for differences greater than 10-fold in the qRT-PCR. A highly reliable oligo-microarray platform was developed and validated for the gilthead sea bream despite the presently limited knowledge of the species transcriptome. Because of the flexible design this array will be able to accommodate additional probes as soon as novel unique transcripts are available.

Endothelial pro-atherosclerotic response to extracellular diabetic-like environment: possible role of thioredoxin-interacting protein.

PubMed

Zitman-Gal, Tali; Green, Janice; Pasmanik-Chor, Metsada; Oron-Karni, Varda; Bernheim, Jacques

2010-07-01

BACKGROUND. High blood and tissue concentrations of glucose and advanced glycation end-products (AGEs) are thought to play an important role in the development of vascular diabetic complications. Therefore, the impact of extracellular AGEs and different glucose concentrations was evaluated by studying the gene expressions and the underlying cellular pathways involved in the development of inflammatory pro-atherosclerotic processes observed in cultured endothelial cells. METHODS. Fresh human umbilical vein cord endothelial cells (HUVEC) were treated in the presence of elevated extracellular glucose concentrations (5.5-28 mmol/l) with and without AGE-human serum albumin (HSA). Affymetrix GeneChip(R) Human Gene 1.0 ST arrays were used for gene expression analysis (total 20 chips). Genes of interest were further validated using real-time PCR and western blot techniques. RESULTS. Microarray analysis revealed significant changes in some gene expressions in the presence of the different stimuli, suggesting that different pathways are involved. Six genes were selected for validation as follows: thioredoxin-interacting protein (TXNIP), thioredoxin (TXN), nuclear factor of kappa B (NF-kappaB), interleukin 6 (IL6), interleukin 8 (IL8) and receptor of advanced glycation end-products (RAGE). Interestingly, it was found that the association of AGEs together with the highest pathophysiological concentration of glucose (28 mmol/l) diminished the expression of these specific genes, excluding TXN. CONCLUSIONS. In the present model that mimics a diabetic environment, the relatively short-term experimental conditions used showed an unexpected blunting action of AGEs in the presence of the highest glucose concentration (28 mmol/l). The interactive cellular pathways involved in these processes should be further investigated.

Investigating the different mechanisms of genotoxic and non-genotoxic carcinogens by a gene set analysis.

PubMed

Lee, Won Jun; Kim, Sang Cheol; Lee, Seul Ji; Lee, Jeongmi; Park, Jeong Hill; Yu, Kyung-Sang; Lim, Johan; Kwon, Sung Won

2014-01-01

Based on the process of carcinogenesis, carcinogens are classified as either genotoxic or non-genotoxic. In contrast to non-genotoxic carcinogens, many genotoxic carcinogens have been reported to cause tumor in carcinogenic bioassays in animals. Thus evaluating the genotoxicity potential of chemicals is important to discriminate genotoxic from non-genotoxic carcinogens for health care and pharmaceutical industry safety. Additionally, investigating the difference between the mechanisms of genotoxic and non-genotoxic carcinogens could provide the foundation for a mechanism-based classification for unknown compounds. In this study, we investigated the gene expression of HepG2 cells treated with genotoxic or non-genotoxic carcinogens and compared their mechanisms of action. To enhance our understanding of the differences in the mechanisms of genotoxic and non-genotoxic carcinogens, we implemented a gene set analysis using 12 compounds for the training set (12, 24, 48 h) and validated significant gene sets using 22 compounds for the test set (24, 48 h). For a direct biological translation, we conducted a gene set analysis using Globaltest and selected significant gene sets. To validate the results, training and test compounds were predicted by the significant gene sets using a prediction analysis for microarrays (PAM). Finally, we obtained 6 gene sets, including sets enriched for genes involved in the adherens junction, bladder cancer, p53 signaling pathway, pathways in cancer, peroxisome and RNA degradation. Among the 6 gene sets, the bladder cancer and p53 signaling pathway sets were significant at 12, 24 and 48 h. We also found that the DDB2, RRM2B and GADD45A, genes related to the repair and damage prevention of DNA, were consistently up-regulated for genotoxic carcinogens. Our results suggest that a gene set analysis could provide a robust tool in the investigation of the different mechanisms of genotoxic and non-genotoxic carcinogens and construct a more detailed understanding of the perturbation of significant pathways.

Investigating the Different Mechanisms of Genotoxic and Non-Genotoxic Carcinogens by a Gene Set Analysis

PubMed Central

Lee, Won Jun; Kim, Sang Cheol; Lee, Seul Ji; Lee, Jeongmi; Park, Jeong Hill; Yu, Kyung-Sang; Lim, Johan; Kwon, Sung Won

2014-01-01

Based on the process of carcinogenesis, carcinogens are classified as either genotoxic or non-genotoxic. In contrast to non-genotoxic carcinogens, many genotoxic carcinogens have been reported to cause tumor in carcinogenic bioassays in animals. Thus evaluating the genotoxicity potential of chemicals is important to discriminate genotoxic from non-genotoxic carcinogens for health care and pharmaceutical industry safety. Additionally, investigating the difference between the mechanisms of genotoxic and non-genotoxic carcinogens could provide the foundation for a mechanism-based classification for unknown compounds. In this study, we investigated the gene expression of HepG2 cells treated with genotoxic or non-genotoxic carcinogens and compared their mechanisms of action. To enhance our understanding of the differences in the mechanisms of genotoxic and non-genotoxic carcinogens, we implemented a gene set analysis using 12 compounds for the training set (12, 24, 48 h) and validated significant gene sets using 22 compounds for the test set (24, 48 h). For a direct biological translation, we conducted a gene set analysis using Globaltest and selected significant gene sets. To validate the results, training and test compounds were predicted by the significant gene sets using a prediction analysis for microarrays (PAM). Finally, we obtained 6 gene sets, including sets enriched for genes involved in the adherens junction, bladder cancer, p53 signaling pathway, pathways in cancer, peroxisome and RNA degradation. Among the 6 gene sets, the bladder cancer and p53 signaling pathway sets were significant at 12, 24 and 48 h. We also found that the DDB2, RRM2B and GADD45A, genes related to the repair and damage prevention of DNA, were consistently up-regulated for genotoxic carcinogens. Our results suggest that a gene set analysis could provide a robust tool in the investigation of the different mechanisms of genotoxic and non-genotoxic carcinogens and construct a more detailed understanding of the perturbation of significant pathways. PMID:24497971

Exploring Valid Reference Genes for Quantitative Real-Time PCR Analysis in Sesamia inferens (Lepidoptera: Noctuidae)

PubMed Central

Sun, Meng; Lu, Ming-Xing; Tang, Xiao-Tian; Du, Yu-Zhou

2015-01-01

The pink stem borer, Sesamia inferens, which is endemic in China and other parts of Asia, is a major pest of rice and causes significant yield loss in this host plant. Very few studies have addressed gene expression in S. inferens. Quantitative real-time PCR (qRT-PCR) is currently the most accurate and sensitive method for gene expression analysis. In qRT-PCR, data are normalized using reference genes, which help control for internal differences and reduce error between samples. In this study, seven candidate reference genes, 18S ribosomal RNA (18S rRNA), elongation factor 1 (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein S13 (RPS13), ribosomal protein S20 (RPS20), tubulin (TUB), and β-actin (ACTB) were evaluated for their suitability in normalizing gene expression under different experimental conditions. The results indicated that three genes (RPS13, RPS20, and EF1) were optimal for normalizing gene expression in different insect tissues (head, epidermis, fat body, foregut, midgut, hindgut, Malpighian tubules, haemocytes, and salivary glands). 18S rRNA, EF1, and GAPDH were best for normalizing expression with respect to developmental stages and sex (egg masses; first, second, third, fourth, fifth, and sixth instar larvae; male and female pupae; and one-day-old male and female adults). 18S rRNA, RPS20, and TUB were optimal for fifth instars exposed to different temperatures (−8, −6, −4, −2, 0, and 27°C). To validate this recommendation, the expression profile of a target gene heat shock protein 83 gene (hsp83) was investigated, and results showed the selection was necessary and effective. In conclusion, this study describes reference gene sets that can be used to accurately measure gene expression in S. inferens. PMID:25585250

Selection and Validation of Reference Genes for Accurate RT-qPCR Data Normalization in Coffea spp. under a Climate Changes Context of Interacting Elevated [CO2] and Temperature

PubMed Central

Martins, Madlles Q.; Fortunato, Ana S.; Rodrigues, Weverton P.; Partelli, Fábio L.; Campostrini, Eliemar; Lidon, Fernando C.; DaMatta, Fábio M.; Ramalho, José C.; Ribeiro-Barros, Ana I.

2017-01-01

World coffee production has faced increasing challenges associated with ongoing climatic changes. Several studies, which have been almost exclusively based on temperature increase, have predicted extensive reductions (higher than half by 2,050) of actual coffee cropped areas. However, recent studies showed that elevated [CO2] can strongly mitigate the negative impacts of heat stress at the physiological and biochemical levels in coffee leaves. In addition, it has also been shown that coffee genotypes can successfully cope with temperatures above what has been traditionally accepted. Altogether, this information suggests that the real impact of climate changes on coffee growth and production could be significantly lower than previously estimated. Gene expression studies are an important tool to unravel crop acclimation ability, demanding the use of adequate reference genes. We have examined the transcript stability of 10 candidate reference genes to normalize RT-qPCR expression studies using a set of 24 cDNAs from leaves of three coffee genotypes (CL153, Icatu, and IPR108), grown under 380 or 700 μL CO2 L−1, and submitted to increasing temperatures from 25/20°C (day/night) to 42/34°C. Samples were analyzed according to genotype, [CO2], temperature, multiple stress interaction ([CO2], temperature) and total stress interaction (genotype, [CO2], and temperature). The transcript stability of each gene was assessed through a multiple analytical approach combining the Coeficient of Variation method and three algorithms (geNorm, BestKeeper, NormFinder). The transcript stability varied according to the type of stress for most genes, but the consensus ranking obtained with RefFinder, classified MDH as the gene with the highest mRNA stability to a global use, followed by ACT and S15, whereas α-TUB and CYCL showed the least stable mRNA contents. Using the coffee expression profiles of the gene encoding the large-subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase (RLS), results from the in silico aggregation and experimental validation of the best number of reference genes showed that two reference genes are adequate to normalize RT-qPCR data. Altogether, this work highlights the importance of an adequate selection of reference genes for each single or combined experimental condition and constitutes the basis to accurately study molecular responses of Coffea spp. in a context of climate changes and global warming. PMID:28326094

Selection and Validation of Reference Genes for Accurate RT-qPCR Data Normalization in Coffea spp. under a Climate Changes Context of Interacting Elevated [CO2] and Temperature.

PubMed

Martins, Madlles Q; Fortunato, Ana S; Rodrigues, Weverton P; Partelli, Fábio L; Campostrini, Eliemar; Lidon, Fernando C; DaMatta, Fábio M; Ramalho, José C; Ribeiro-Barros, Ana I

2017-01-01

World coffee production has faced increasing challenges associated with ongoing climatic changes. Several studies, which have been almost exclusively based on temperature increase, have predicted extensive reductions (higher than half by 2,050) of actual coffee cropped areas. However, recent studies showed that elevated [CO 2 ] can strongly mitigate the negative impacts of heat stress at the physiological and biochemical levels in coffee leaves. In addition, it has also been shown that coffee genotypes can successfully cope with temperatures above what has been traditionally accepted. Altogether, this information suggests that the real impact of climate changes on coffee growth and production could be significantly lower than previously estimated. Gene expression studies are an important tool to unravel crop acclimation ability, demanding the use of adequate reference genes. We have examined the transcript stability of 10 candidate reference genes to normalize RT-qPCR expression studies using a set of 24 cDNAs from leaves of three coffee genotypes (CL153, Icatu, and IPR108), grown under 380 or 700 μL CO 2 L -1 , and submitted to increasing temperatures from 25/20°C (day/night) to 42/34°C. Samples were analyzed according to genotype, [CO 2 ], temperature, multiple stress interaction ([CO 2 ], temperature) and total stress interaction (genotype, [CO 2 ], and temperature). The transcript stability of each gene was assessed through a multiple analytical approach combining the Coeficient of Variation method and three algorithms (geNorm, BestKeeper, NormFinder). The transcript stability varied according to the type of stress for most genes, but the consensus ranking obtained with RefFinder, classified MDH as the gene with the highest mRNA stability to a global use, followed by ACT and S15 , whereas α -TUB and CYCL showed the least stable mRNA contents. Using the coffee expression profiles of the gene encoding the large-subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase ( RLS ), results from the in silico aggregation and experimental validation of the best number of reference genes showed that two reference genes are adequate to normalize RT-qPCR data. Altogether, this work highlights the importance of an adequate selection of reference genes for each single or combined experimental condition and constitutes the basis to accurately study molecular responses of Coffea spp. in a context of climate changes and global warming.

Selection of reference genes as internal controls for gene expression in tissues of red abalone Haliotis rufescens (Mollusca, Vetigastropoda; Swainson, 1822).

PubMed

López-Landavery, Edgar A; Portillo-López, Amelia; Gallardo-Escárate, Cristian; Del Río-Portilla, Miguel A

2014-10-10

The red abalone Haliotis rufescens is one of the most important species for aquaculture in Baja California, México, and despite this, few gene expression studies have been done in tissues such as gill, head and gonad. For this purpose, reverse transcription and quantitative real time PCR (RT-qPCR) is a powerful tool for gene expression evaluation. For a reliable analysis, however, it is necessary to select and validate housekeeping genes that allow proper transcription quantification. Stability of nine housekeeping genes (ACTB, BGLU, TUBB, CY, GAPDH, HPRTI, RPL5, SDHA and UBC) was evaluated in different tissues of red abalone (gill, head and gonad/digestive gland). Four-fold serial dilutions of cDNA (from 25 ngμL(-1) to 0.39 ngμL(-1)) were used to prepare the standard curve, and it showed gene efficiencies between 0.95 and 0.99, with R(2)=0.99. geNorm and NormFinder analysis showed that RPL5 and CY were the most stable genes considering all tissues, whereas in gill HPRTI and BGLU were most stable. In gonad/digestive gland, RPL5 and TUBB were the most stable genes with geNorm, while SDHA and HPRTI were the best using NormFinder. Similarly, in head the best genes were RPL5 and UBC with geNorm, and GAPDH and CY with NormFinder. The technical variability analysis with RPL5 and abalone gonad/digestive gland tissue indicated a high repeatability with a variation coefficient within groups ≤ 0.56% and between groups ≤ 1.89%. These results will help us for further research in reproduction, thermoregulation and endocrinology in red abalone. Copyright © 2014 Elsevier B.V. All rights reserved.

Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis.

PubMed

Shchetynsky, Klementy; Diaz-Gallo, Lina-Marcella; Folkersen, Lasse; Hensvold, Aase Haj; Catrina, Anca Irinel; Berg, Louise; Klareskog, Lars; Padyukov, Leonid

2017-02-02

Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of "connector" genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA.

Analysis of 60 reported glioma risk SNPs replicates published GWAS findings but fails to replicate associations from published candidate-gene studies.

PubMed

Walsh, Kyle M; Anderson, Erik; Hansen, Helen M; Decker, Paul A; Kosel, Matt L; Kollmeyer, Thomas; Rice, Terri; Zheng, Shichun; Xiao, Yuanyuan; Chang, Jeffrey S; McCoy, Lucie S; Bracci, Paige M; Wiemels, Joe L; Pico, Alexander R; Smirnov, Ivan; Lachance, Daniel H; Sicotte, Hugues; Eckel-Passow, Jeanette E; Wiencke, John K; Jenkins, Robert B; Wrensch, Margaret R

2013-02-01

Genomewide association studies (GWAS) and candidate-gene studies have implicated single-nucleotide polymorphisms (SNPs) in at least 45 different genes as putative glioma risk factors. Attempts to validate these associations have yielded variable results and few genetic risk factors have been consistently replicated. We conducted a case-control study of Caucasian glioma cases and controls from the University of California San Francisco (810 cases, 512 controls) and the Mayo Clinic (852 cases, 789 controls) in an attempt to replicate previously reported genetic risk factors for glioma. Sixty SNPs selected from the literature (eight from GWAS and 52 from candidate-gene studies) were successfully genotyped on an Illumina custom genotyping panel. Eight SNPs in/near seven different genes (TERT, EGFR, CCDC26, CDKN2A, PHLDB1, RTEL1, TP53) were significantly associated with glioma risk in the combined dataset (P < 0.05), with all associations in the same direction as in previous reports. Several SNP associations showed considerable differences across histologic subtype. All eight successfully replicated associations were first identified by GWAS, although none of the putative risk SNPs from candidate-gene studies was associated in the full case-control sample (all P values > 0.05). Although several confirmed associations are located near genes long known to be involved in gliomagenesis (e.g., EGFR, CDKN2A, TP53), these associations were first discovered by the GWAS approach and are in noncoding regions. These results highlight that the deficiencies of the candidate-gene approach lay in selecting both appropriate genes and relevant SNPs within these genes. © 2012 WILEY PERIODICALS, INC.

Gene Expression Profiling Specifies Chemokine, Mitochondrial and Lipid Metabolism Signatures in Leprosy

PubMed Central

Guerreiro, Luana Tatiana Albuquerque; Robottom-Ferreira, Anna Beatriz; Ribeiro-Alves, Marcelo; Toledo-Pinto, Thiago Gomes; Rosa Brito, Tiana; Rosa, Patrícia Sammarco; Sandoval, Felipe Galvan; Jardim, Márcia Rodrigues; Antunes, Sérgio Gomes; Shannon, Edward J.; Sarno, Euzenir Nunes; Pessolani, Maria Cristina Vidal; Williams, Diana Lynn; Moraes, Milton Ozório

2013-01-01

Herein, we performed microarray experiments in Schwann cells infected with live M. leprae and identified novel differentially expressed genes (DEG) in M. leprae infected cells. Also, we selected candidate genes associated or implicated with leprosy in genetic studies and biological experiments. Forty-seven genes were selected for validation in two independent types of samples by multiplex qPCR. First, an in vitro model using THP-1 cells was infected with live Mycobacterium leprae and M. bovis bacillus Calmette-Guérin (BCG). In a second situation, mRNA obtained from nerve biopsies from patients with leprosy or other peripheral neuropathies was tested. We detected DEGs that discriminate M. bovis BCG from M. leprae infection. Specific signatures of susceptible responses after M. leprae infection when compared to BCG lead to repression of genes, including CCL2, CCL3, IL8 and SOD2. The same 47-gene set was screened in nerve biopsies, which corroborated the down-regulation of CCL2 and CCL3 in leprosy, but also evidenced the down-regulation of genes involved in mitochondrial metabolism, and the up-regulation of genes involved in lipid metabolism and ubiquitination. Finally, a gene expression signature from DEG was identified in patients confirmed of having leprosy. A classification tree was able to ascertain 80% of the cases as leprosy or non-leprous peripheral neuropathy based on the expression of only LDLR and CCL4. A general immune and mitochondrial hypo-responsive state occurs in response to M. leprae infection. Also, the most important genes and pathways have been highlighted providing new tools for early diagnosis and treatment of leprosy. PMID:23798993

Identification and characterization of microRNAs and their target genes from Nile tilapia (Oreochromis niloticus).

PubMed

Huang, Yong; Ma, Xiu Ying; Yang, You Bing; Ren, Hong Tao; Sun, Xi Hong; Wang, Li Rui

MicroRNAs (miRNAs) are a class of small single-stranded, endogenous 21-22 nt non-coding RNAs that regulate their target mRNA levels by causing either inactivation or degradation of the mRNAs. In recent years, miRNA genes have been identified from mammals, insects, worms, plants, and viruses. In this research, bioinformatics approaches were used to predict potential miRNAs and their targets in Nile tilapia from the expressed sequence tag (EST) and genomic survey sequence (GSS) database, respectively, based on the conservation of miRNAs in many animal species. A total of 19 potential miRNAs were detected following a range of strict filtering criteria. To test the validity of the bioinformatics method, seven predicted Nile tilapia miRNA genes were selected for further biological validation, and their mature miRNA transcripts were successfully detected by stem-loop RT-PCR experiments. Using these potential miRNAs, we found 56 potential targets in this species. Most of the target mRNAs appear to be involved in development, metabolism, signal transduction, transcription regulation and stress responses. Overall, our findings will provide an important foundation for further research on miRNAs function in the Nile tilapia.

The cross-validated AUC for MCP-logistic regression with high-dimensional data.

PubMed

Jiang, Dingfeng; Huang, Jian; Zhang, Ying

2013-10-01

We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selection. The CV-AUC criterion is specifically designed for optimizing the classification performance for binary outcome data. To implement the proposed approach, we derive an efficient coordinate descent algorithm to compute the MCP-logistic regression solution surface. Simulation studies are conducted to evaluate the finite sample performance of the proposed method and its comparison with the existing methods including the Akaike information criterion (AIC), Bayesian information criterion (BIC) or Extended BIC (EBIC). The model selected based on the CV-AUC criterion tends to have a larger predictive AUC and smaller classification error than those with tuning parameters selected using the AIC, BIC or EBIC. We illustrate the application of the MCP-logistic regression with the CV-AUC criterion on three microarray datasets from the studies that attempt to identify genes related to cancers. Our simulation studies and data examples demonstrate that the CV-AUC is an attractive method for tuning parameter selection for penalized methods in high-dimensional logistic regression models.

Development of a targeted transgenesis strategy in highly differentiated cells: a powerful tool for functional genomic analysis.

PubMed

Puttini, Stefania; Ouvrard-Pascaud, Antoine; Palais, Gael; Beggah, Ahmed T; Gascard, Philippe; Cohen-Tannoudji, Michel; Babinet, Charles; Blot-Chabaud, Marcel; Jaisser, Frederic

2005-03-16

Functional genomic analysis is a challenging step in the so-called post-genomic field. Identification of potential targets using large-scale gene expression analysis requires functional validation to identify those that are physiologically relevant. Genetically modified cell models are often used for this purpose allowing up- or down-expression of selected targets in a well-defined and if possible highly differentiated cell type. However, the generation of such models remains time-consuming and expensive. In order to alleviate this step, we developed a strategy aimed at the rapid and efficient generation of genetically modified cell lines with conditional, inducible expression of various target genes. Efficient knock-in of various constructs, called targeted transgenesis, in a locus selected for its permissibility to the tet inducible system, was obtained through the stimulation of site-specific homologous recombination by the meganuclease I-SceI. Our results demonstrate that targeted transgenesis in a reference inducible locus greatly facilitated the functional analysis of the selected recombinant cells. The efficient screening strategy we have designed makes possible automation of the transfection and selection steps. Furthermore, this strategy could be applied to a variety of highly differentiated cells.

De novo assembly and transcriptome analysis of the rubber tree (Hevea brasiliensis) and SNP markers development for rubber biosynthesis pathways.

PubMed

Mantello, Camila Campos; Cardoso-Silva, Claudio Benicio; da Silva, Carla Cristina; de Souza, Livia Moura; Scaloppi Junior, Erivaldo José; de Souza Gonçalves, Paulo; Vicentini, Renato; de Souza, Anete Pereira

2014-01-01

Hevea brasiliensis (Willd. Ex Adr. Juss.) Muell.-Arg. is the primary source of natural rubber that is native to the Amazon rainforest. The singular properties of natural rubber make it superior to and competitive with synthetic rubber for use in several applications. Here, we performed RNA sequencing (RNA-seq) of H. brasiliensis bark on the Illumina GAIIx platform, which generated 179,326,804 raw reads on the Illumina GAIIx platform. A total of 50,384 contigs that were over 400 bp in size were obtained and subjected to further analyses. A similarity search against the non-redundant (nr) protein database returned 32,018 (63%) positive BLASTx hits. The transcriptome analysis was annotated using the clusters of orthologous groups (COG), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam databases. A search for putative molecular marker was performed to identify simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). In total, 17,927 SSRs and 404,114 SNPs were detected. Finally, we selected sequences that were identified as belonging to the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, which are involved in rubber biosynthesis, to validate the SNP markers. A total of 78 SNPs were validated in 36 genotypes of H. brasiliensis. This new dataset represents a powerful information source for rubber tree bark genes and will be an important tool for the development of microsatellites and SNP markers for use in future genetic analyses such as genetic linkage mapping, quantitative trait loci identification, investigations of linkage disequilibrium and marker-assisted selection.

Gene doping detection: evaluation of approach for direct detection of gene transfer using erythropoietin as a model system.

PubMed

Baoutina, A; Coldham, T; Bains, G S; Emslie, K R

2010-08-01

As clinical gene therapy has progressed toward realizing its potential, concern over misuse of the technology to enhance performance in athletes is growing. Although 'gene doping' is banned by the World Anti-Doping Agency, its detection remains a major challenge. In this study, we developed a methodology for direct detection of the transferred genetic material and evaluated its feasibility for gene doping detection in blood samples from athletes. Using erythropoietin (EPO) as a model gene and a simple in vitro system, we developed real-time PCR assays that target sequences within the transgene complementary DNA corresponding to exon/exon junctions. As these junctions are absent in the endogenous gene due to their interruption by introns, the approach allows detection of trace amounts of a transgene in a large background of the endogenous gene. Two developed assays and one commercial gene expression assay for EPO were validated. On the basis of ability of these assays to selectively amplify transgenic DNA and analysis of literature on testing of gene transfer in preclinical and clinical gene therapy, it is concluded that the developed approach would potentially be suitable to detect gene doping through gene transfer by analysis of small volumes of blood using regular out-of-competition testing.

Characterization and expression of the ABC family (G group) in 'Dangshansuli' pear (Pyrus bretschneideri Rehd.) and its russet mutant.

PubMed

Hou, Zhaoqi; Jia, Bing; Li, Fei; Liu, Pu; Liu, Li; Ye, Zhenfeng; Zhu, Liwu; Wang, Qi; Heng, Wei

2018-01-01

The plant genes encoding ABCGs that have been identified to date play a role in suberin formation in response to abiotic and biotic stress. In the present study, 80 ABCG genes were identified in 'Dangshansuli' Chinese white pear and designated as PbABCGs. Based on the structural characteristics and phylogenetic analysis, the PbABCG family genes could be classified into seven main groups: classes A-G. Segmental and dispersed duplications were the primary forces underlying the PbABCG gene family expansion in 'Dangshansuli' pear. Most of the PbABCG duplicated gene pairs date to the recent whole-genome duplication that occurred 30~45 million years ago. Purifying selection has also played a critical role in the evolution of the ABCG genes. Ten PbABCG genes screened in the transcriptome of 'Dangshansuli' pear and its russet mutant 'Xiusu' were validated, and the expression levels of the PbABCG genes exhibited significant differences at different stages. The results presented here will undoubtedly be useful for better understanding of the complexity of the PbABCG gene family and will facilitate the functional characterization of suberin formation in the russet mutant.

Optimized RNP transfection for highly efficient CRISPR/Cas9-mediated gene knockout in primary T cells.

PubMed

Seki, Akiko; Rutz, Sascha

2018-03-05

CRISPR (clustered, regularly interspaced, short palindromic repeats)/Cas9 (CRISPR-associated protein 9) has become the tool of choice for generating gene knockouts across a variety of species. The ability for efficient gene editing in primary T cells not only represents a valuable research tool to study gene function but also holds great promise for T cell-based immunotherapies, such as next-generation chimeric antigen receptor (CAR) T cells. Previous attempts to apply CRIPSR/Cas9 for gene editing in primary T cells have resulted in highly variable knockout efficiency and required T cell receptor (TCR) stimulation, thus largely precluding the study of genes involved in T cell activation or differentiation. Here, we describe an optimized approach for Cas9/RNP transfection of primary mouse and human T cells without TCR stimulation that results in near complete loss of target gene expression at the population level, mitigating the need for selection. We believe that this method will greatly extend the feasibly of target gene discovery and validation in primary T cells and simplify the gene editing process for next-generation immunotherapies. © 2018 Genentech.

Pathway-focused gene expression profiles and immunohistochemistry detection identify contrasting association of caspase 3 (CASP3) expression with prognosis in pediatric classical Hodgkin lymphoma.

PubMed

Vera-Lozada, Gabriela; Segges, Priscilla; Stefanoff, Claudio Gustavo; Barros, Mário Henrique M; Niedobitek, Gerald; Hassan, Rocio

2018-06-14

The search for clinically relevant molecular markers in classical Hodgkin lymphoma (cHL) is hampered by the histopathological complexity of the disease, resulting from the admixture of a small number of neoplastic Hodgkin and Reed-Sternberg (H-RS) cells with an abundant and heterogeneous microenvironment. In this study, we evaluated gene expression profiles of 11 selected genes previously proposed as a molecular score for adult cHL, aiming to validate its application in the pediatric setting. Assays were performed by RT-qPCR from formalin-fixed paraffin-embedded (FFPE) lymph nodes in 80 patients with cHL. Selected genes were associated with cell cycle (CENPF, CDK1, CCNA2, CCNE2, and HMMR), apoptosis (BCL2, BCL2L1, and CASP3), and monocytes/macrophages (LYZ and STAT1). Despite using controlled preanalytical and analytical strategies, we were not able to validate the 11-gene score to be applied in pediatric cHL. Principal component analysis (PCA) disclosed 3 components that accounted for 65.7% of the total variability. The second PC included microenvironment and apoptosis genes, from which CASP3 expression was associated with a short time of progression-free survival, which impact was maintained in the unfavorable risk group, Epstein-Barr virus-negative cases, and multivariate analysis (P < .05). Because this is a counterintuitive association, CASP3 active expression was assessed at the protein level in H-RS cells by double immunohistochemistry. In contrast to the association of mRNA levels with a poor therapeutic response, a high number of cleaved CASP3+ cells were associated with longer progression-free survival (P = .03) and overall survival (P = .002). Our results demonstrate the feasibility of using FFPE samples as RNA source for molecular prognostication, but argue against the concept of direct and wide applicability of molecular scores in cHL. We reinforce the potential of CASP3 as an interesting target to be explored in adult and pediatric cHL, and alert for its dual biological role in H-RS cells and tumor microenvironment. Copyright © 2018 John Wiley & Sons, Ltd.

Φ-score: A cell-to-cell phenotypic scoring method for sensitive and selective hit discovery in cell-based assays.

PubMed

Guyon, Laurent; Lajaunie, Christian; Fer, Frédéric; Bhajun, Ricky; Sulpice, Eric; Pinna, Guillaume; Campalans, Anna; Radicella, J Pablo; Rouillier, Philippe; Mary, Mélissa; Combe, Stéphanie; Obeid, Patricia; Vert, Jean-Philippe; Gidrol, Xavier

2015-09-18

Phenotypic screening monitors phenotypic changes induced by perturbations, including those generated by drugs or RNA interference. Currently-used methods for scoring screen hits have proven to be problematic, particularly when applied to physiologically relevant conditions such as low cell numbers or inefficient transfection. Here, we describe the Φ-score, which is a novel scoring method for the identification of phenotypic modifiers or hits in cell-based screens. Φ-score performance was assessed with simulations, a validation experiment and its application to gene identification in a large-scale RNAi screen. Using robust statistics and a variance model, we demonstrated that the Φ-score showed better sensitivity, selectivity and reproducibility compared to classical approaches. The improved performance of the Φ-score paves the way for cell-based screening of primary cells, which are often difficult to obtain from patients in sufficient numbers. We also describe a dedicated merging procedure to pool scores from small interfering RNAs targeting the same gene so as to provide improved visualization and hit selection.

Φ-score: A cell-to-cell phenotypic scoring method for sensitive and selective hit discovery in cell-based assays

PubMed Central

Guyon, Laurent; Lajaunie, Christian; fer, Frédéric; bhajun, Ricky; sulpice, Eric; pinna, Guillaume; campalans, Anna; radicella, J. Pablo; rouillier, Philippe; mary, Mélissa; combe, Stéphanie; obeid, Patricia; vert, Jean-Philippe; gidrol, Xavier

2015-01-01

Phenotypic screening monitors phenotypic changes induced by perturbations, including those generated by drugs or RNA interference. Currently-used methods for scoring screen hits have proven to be problematic, particularly when applied to physiologically relevant conditions such as low cell numbers or inefficient transfection. Here, we describe the Φ-score, which is a novel scoring method for the identification of phenotypic modifiers or hits in cell-based screens. Φ-score performance was assessed with simulations, a validation experiment and its application to gene identification in a large-scale RNAi screen. Using robust statistics and a variance model, we demonstrated that the Φ-score showed better sensitivity, selectivity and reproducibility compared to classical approaches. The improved performance of the Φ-score paves the way for cell-based screening of primary cells, which are often difficult to obtain from patients in sufficient numbers. We also describe a dedicated merging procedure to pool scores from small interfering RNAs targeting the same gene so as to provide improved visualization and hit selection. PMID:26382112

Selection of Reference Genes for Quantitative Gene Expression in Porcine Mesenchymal Stem Cells Derived from Various Sources along with Differentiation into Multilineages

PubMed Central

Lee, Won-Jae; Jeon, Ryoung-Hoon; Jang, Si-Jung; Park, Ji-Sung; Lee, Seung-Chan; Baregundi Subbarao, Raghavendra; Lee, Sung-Lim; Park, Bong-Wook; King, William Allan; Rho, Gyu-Jin

2015-01-01

The identification of stable reference genes is a prerequisite for ensuring accurate validation of gene expression, yet too little is known about stable reference genes of porcine MSCs. The present study was, therefore, conducted to assess the stability of reference genes in porcine MSCs derived from bone marrow (BMSCs), adipose (AMSCs), and skin (SMSCs) with their in vitro differentiated cells into mesenchymal lineages such as adipocytes, osteocytes, and chondrocytes. Twelve commonly used reference genes were investigated for their threshold cycle (Ct) values by qRT-PCR. The Ct values of candidate reference genes were analyzed by geNorm software to clarify stable expression regardless of experimental conditions. Thus, Pearson's correlation was applied to determine correlation between the three most stable reference genes (NF3) and optimal number of reference genes (NFopt). In assessment of stability of reference gene across experimental conditions by geNorm analysis, undifferentiated MSCs and each differentiated status into mesenchymal lineages showed slightly different results but similar patterns about more or less stable rankings. Furthermore, Pearson's correlation revealed high correlation (r > 0.9) between NF3 and NFopt. Overall, the present study showed that HMBS, YWHAZ, SDHA, and TBP are suitable reference genes for qRT-PCR in porcine MSCs. PMID:25972899

Selective gene silencing by viral delivery of short hairpin RNA

PubMed Central

2010-01-01

RNA interference (RNAi) technology has not only become a powerful tool for functional genomics, but also allows rapid drug target discovery and in vitro validation of these targets in cell culture. Furthermore, RNAi represents a promising novel therapeutic option for treating human diseases, in particular cancer. Selective gene silencing by RNAi can be achieved essentially by two nucleic acid based methods: i) cytoplasmic delivery of short double-stranded (ds) interfering RNA oligonucleotides (siRNA), where the gene silencing effect is only transient in nature, and possibly not suitable for all applications; or ii) nuclear delivery of gene expression cassettes that express short hairpin RNA (shRNA), which are processed like endogenous interfering RNA and lead to stable gene down-regulation. Both processes involve the use of nucleic acid based drugs, which are highly charged and do not cross cell membranes by free diffusion. Therefore, in vivo delivery of RNAi therapeutics must use technology that enables the RNAi therapeutic to traverse biological membrane barriers in vivo. Viruses and the vectors derived from them carry out precisely this task and have become a major delivery system for shRNA. Here, we summarize and compare different currently used viral delivery systems, give examples of in vivo applications, and indicate trends for new developments, such as replicating viruses for shRNA delivery to cancer cells. PMID:20858246

Regulation of Isoflavone Biosynthesis by miRNAs in Two Contrasting Soybean Genotypes at Different Seed Developmental Stages.

PubMed

Gupta, Om P; Nigam, Deepti; Dahuja, Anil; Kumar, Sanjeev; Vinutha, T; Sachdev, Archana; Praveen, Shelly

2017-01-01

Owing to the presence of nutritionally important, health-promoting bioactive compounds, especially isoflavones, soybean has acquired the status of a functional food. miRNAs are tiny riboregulator of gene expression by either decreasing and/or increasing the expression of their corresponding target genes. Despite several works on identification and functional characterization of plant miRNAs, the role of miRNAs in the regulation of isoflavones metabolism is still a virgin field. In the present study, we identified a total of 31 new miRNAs along with their 245 putative target genes from soybean seed-specific ESTs using computational approach. The Kyoto Encyclopedia of Genes and Genomes pathway analyses indicated that miRNA putatively regulates metabolism and genetic information processing. Out of that, a total of 5 miRNAs ( Gma -miRNA12, Gma -miRNA24, Gma -miRNA26, Gma -miRNA28, and Gma -miRNA29) were predicted and validated for their probable role during isoflavone biosynthesis. We also validated their five target genes using RA-PCR, which is as good as 5'RLM-RACE. Temporal regulation [35 days after flowering, 45, 55, and 65 DAF] of miRNAs and their targets showed differential expression schema. Differential expression of Gma -miR26 and Gma -miRNA28 along with their corresponding target genes ( Glyma.10G197900 and Glyma.09G127200 ) showed a direct relationship with the total isoflavone content. Therefore, understanding the miRNA-based genetic regulation of isoflavone pathway would assist in selection and manipulation to get high-performing soybean genotypes with better isoflavone yield.

Evaluation of miRNA-196a2 and apoptosis-related target genes: ANXA1, DFFA and PDCD4 expression in gastrointestinal cancer patients: A pilot study

PubMed Central

Toraih, Eman A.; Ibrahiem, Afaf; Abdeldayem, Hala; Mohamed, Amany O.; Abdel-Daim, Mohamed M.

2017-01-01

Previous reports have suggested the significant association of miRNAs aberrant expression with tumor initiation, progression and metastasis in cancer, including gastrointestinal (GI) cancers. The current preliminary study aimed to evaluate the relative expression levels of miR-196a2 and three of its selected apoptosis-related targets; ANXA1, DFFA and PDCD4 in a sample of GI cancer patients. Quantitative real-time PCR for miR-196a2 and its selected mRNA targets, as well as immunohistochemical assay for annexin A1 protein expression were detected in 58 tissues with different GI cancer samples. In addition, correlation with the clinicopathological features and in silico network analysis of the selected molecular markers were analyzed. Stratified analyses by cancer site revealed elevated levels of miR-196a2 and low expression of the selected target genes. Annexin protein expression was positively correlated with its gene expression profile. In colorectal cancer, miR-196a over-expression was negatively correlated with annexin A1 protein expression (r = -0.738, p < 0.001), and both were indicators of unfavorable prognosis in terms of poor differentiation, larger tumor size, and advanced clinical stage. Taken together, aberrant expression of miR-196a2 and the selected apoptosis-related biomarkers might be involved in GI cancer development and progression and could have potential diagnostic and prognostic roles in these types of cancer; particularly colorectal cancer, provided the results experimentally validated and confirmed in larger multi-center studies. PMID:29091952

Accuracy of genomic selection models in a large population of open-pollinated families in white spruce

PubMed Central

Beaulieu, J; Doerksen, T; Clément, S; MacKay, J; Bousquet, J

2014-01-01

Genomic selection (GS) is of interest in breeding because of its potential for predicting the genetic value of individuals and increasing genetic gains per unit of time. To date, very few studies have reported empirical results of GS potential in the context of large population sizes and long breeding cycles such as for boreal trees. In this study, we assessed the effectiveness of marker-aided selection in an undomesticated white spruce (Picea glauca (Moench) Voss) population of large effective size using a GS approach. A discovery population of 1694 trees representative of 214 open-pollinated families from 43 natural populations was phenotyped for 12 wood and growth traits and genotyped for 6385 single-nucleotide polymorphisms (SNPs) mined in 2660 gene sequences. GS models were built to predict estimated breeding values using all the available SNPs or SNP subsets of the largest absolute effects, and they were validated using various cross-validation schemes. The accuracy of genomic estimated breeding values (GEBVs) varied from 0.327 to 0.435 when the training and the validation data sets shared half-sibs that were on average 90% of the accuracies achieved through traditionally estimated breeding values. The trend was also the same for validation across sites. As expected, the accuracy of GEBVs obtained after cross-validation with individuals of unknown relatedness was lower with about half of the accuracy achieved when half-sibs were present. We showed that with the marker densities used in the current study, predictions with low to moderate accuracy could be obtained within a large undomesticated population of related individuals, potentially resulting in larger gains per unit of time with GS than with the traditional approach. PMID:24781808

Mutation analysis in 129 genes associated with other forms of retinal dystrophy in 157 families with retinitis pigmentosa based on exome sequencing.

PubMed

Xu, Yan; Guan, Liping; Xiao, Xueshan; Zhang, Jianguo; Li, Shiqiang; Jiang, Hui; Jia, Xiaoyun; Yang, Jianhua; Guo, Xiangming; Yin, Ye; Wang, Jun; Zhang, Qingjiong

2015-01-01

Mutations in 60 known genes were previously identified by exome sequencing in 79 of 157 families with retinitis pigmentosa (RP). This study analyzed variants in 129 genes associated with other forms of hereditary retinal dystrophy in the same cohort. Apart from the 73 genes previously analyzed, a further 129 genes responsible for other forms of hereditary retinal dystrophy were selected based on RetNet. Variants in the 129 genes determined by whole exome sequencing were selected and filtered by bioinformatics analysis. Candidate variants were confirmed by Sanger sequencing and validated by analysis of available family members and controls. A total of 90 candidate variants were present in the 129 genes. Sanger sequencing confirmed 83 of the 90 variants. Analysis of family members and controls excluded 76 of these 83 variants. The remaining seven variants were considered to be potential pathogenic mutations; these were c.899A>G, c.1814C>G, and c.2107C>T in BBS2; c.1073C>T and c.1669C>T in INPP5E; and c.3582C>G and c.5704-5C>G in CACNA1F. Six of these seven mutations were novel. The mutations were detected in five unrelated patients without a family history, including three patients with homozygous or compound heterozygous mutations in BBS2 and INPP5E, and two patients with hemizygous mutations in CACNA1F. None of the patients had mutations in the genes associated with autosome dominant retinal dystrophy. Only a small portion of patients with RP, about 3% (5/157), had causative mutations in the 129 genes associated with other forms of hereditary retinal dystrophy.

Harnessing pain heterogeneity and RNA transcriptome to identify blood-based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model.

PubMed

Grace, Peter M; Hurley, Daniel; Barratt, Daniel T; Tsykin, Anna; Watkins, Linda R; Rolan, Paul E; Hutchinson, Mark R

2012-09-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. © 2012 The Authors. Journal of Neurochemistry © 2012 International Society for Neurochemistry.

Receptor-Mediated Delivery of CRISPR-Cas9 Endonuclease for Cell-Type-Specific Gene Editing.

PubMed

Rouet, Romain; Thuma, Benjamin A; Roy, Marc D; Lintner, Nathanael G; Rubitski, David M; Finley, James E; Wisniewska, Hanna M; Mendonsa, Rima; Hirsh, Ariana; de Oñate, Lorena; Compte Barrón, Joan; McLellan, Thomas J; Bellenger, Justin; Feng, Xidong; Varghese, Alison; Chrunyk, Boris A; Borzilleri, Kris; Hesp, Kevin D; Zhou, Kaihong; Ma, Nannan; Tu, Meihua; Dullea, Robert; McClure, Kim F; Wilson, Ross C; Liras, Spiros; Mascitti, Vincent; Doudna, Jennifer A

2018-05-30

CRISPR-Cas RNA-guided endonucleases hold great promise for disrupting or correcting genomic sequences through site-specific DNA cleavage and repair. However, the lack of methods for cell- and tissue-selective delivery currently limits both research and clinical uses of these enzymes. We report the design and in vitro evaluation of S. pyogenes Cas9 proteins harboring asialoglycoprotein receptor ligands (ASGPrL). In particular, we demonstrate that the resulting ribonucleoproteins (Cas9-ASGPrL RNP) can be engineered to be preferentially internalized into cells expressing the corresponding receptor on their surface. Uptake of such fluorescently labeled proteins in liver-derived cell lines HEPG2 (ASGPr+) and SKHEP (control; diminished ASGPr) was studied by live cell imaging and demonstrates increased accumulation of Cas9-ASGPrL RNP in HEPG2 cells as a result of effective ASGPr-mediated endocytosis. When uptake occurred in the presence of a peptide with endosomolytic properties, we observed receptor-facilitated and cell-type specific gene editing that did not rely on electroporation or the use of transfection reagents. Overall, these in vitro results validate the receptor-mediated delivery of genome-editing enzymes as an approach for cell-selective gene editing and provide a framework for future potential applications to hepatoselective gene editing in vivo.

Reduced Set of Virulence Genes Allows High Accuracy Prediction of Bacterial Pathogenicity in Humans

PubMed Central

Iraola, Gregorio; Vazquez, Gustavo; Spangenberg, Lucía; Naya, Hugo

2012-01-01

Although there have been great advances in understanding bacterial pathogenesis, there is still a lack of integrative information about what makes a bacterium a human pathogen. The advent of high-throughput sequencing technologies has dramatically increased the amount of completed bacterial genomes, for both known human pathogenic and non-pathogenic strains; this information is now available to investigate genetic features that determine pathogenic phenotypes in bacteria. In this work we determined presence/absence patterns of different virulence-related genes among more than finished bacterial genomes from both human pathogenic and non-pathogenic strains, belonging to different taxonomic groups (i.e: Actinobacteria, Gammaproteobacteria, Firmicutes, etc.). An accuracy of 95% using a cross-fold validation scheme with in-fold feature selection is obtained when classifying human pathogens and non-pathogens. A reduced subset of highly informative genes () is presented and applied to an external validation set. The statistical model was implemented in the BacFier v1.0 software (freely available at ), that displays not only the prediction (pathogen/non-pathogen) and an associated probability for pathogenicity, but also the presence/absence vector for the analyzed genes, so it is possible to decipher the subset of virulence genes responsible for the classification on the analyzed genome. Furthermore, we discuss the biological relevance for bacterial pathogenesis of the core set of genes, corresponding to eight functional categories, all with evident and documented association with the phenotypes of interest. Also, we analyze which functional categories of virulence genes were more distinctive for pathogenicity in each taxonomic group, which seems to be a completely new kind of information and could lead to important evolutionary conclusions. PMID:22916122

Validation of reference and identity-defining genes in human mesenchymal stem cells cultured under unrelated fetal bovine serum batches for basic science and clinical application.

PubMed

Banfi, Federica; Colombini, Alessandra; Perucca Orfei, Carlotta; Parazzi, Valentina; Ragni, Enrico

2018-05-26

The molecular profile of human mesenchymal stem cells (MSCs) have emerged as a key factor in defining their identity. Nevertheless, the effect of fetal bovine serum (FBS) batches or origin on MSC molecular signature has been neglected. In this frame, chemical fingerprint of FBS batches from unrelated countries showed strong correlation between chemical composition and country of origin. Thus, the aim of this study was to evaluate in stem cells isolated from bone marrow (BMMSCs) and umbilical cord-blood (CBMSCs) the effects of independently collected FBS batches on both twelve commonly used reference genes (RGs) and a selected panel of thirty-eight genes crucial for MSC definition in both research and clinical settings. Gene expression stability was estimated comparing the outcomes of two applets: geNorm and NormFinder. The bioinformatics analysis emphasized that, in a panorama of general balance, few RG candidates (YWHAZ/UBC for BMMSCs, RPLP0/EF1A for CBMSCs and EF1A/TBP for both MSCs scored together) showed superior stability. In addition, a wider study on genes involved in differentiation/proliferation/stemness processes, often used to define MSC potency, showed that these genes exhibited no major transcriptional modulation after treatment with different FBS, and allowed the identification of genes strongly discriminating between BM- and CBMSC populations. Therefore, in conclusion, FBS origin does not dramatically impact the general molecular profile of MSCs, although we could identify validated candidates able to allow more reliable comparison of data regarding MSC identity and potency and obtained by research laboratories and clinical manufacturers using different sera.

Novel Genes Affecting the Interaction between the Cabbage Whitefly and Arabidopsis Uncovered by Genome-Wide Association Mapping

PubMed Central

Broekgaarden, Colette; Bucher, Johan; Bac-Molenaar, Johanna; Keurentjes, Joost J. B.; Kruijer, Willem; Voorrips, Roeland E.; Vosman, Ben

2015-01-01

Plants have evolved a variety of ways to defend themselves against biotic attackers. This has resulted in the presence of substantial variation in defense mechanisms among plants, even within a species. Genome-wide association (GWA) mapping is a useful tool to study the genetic architecture of traits, but has so far only had limited exploitation in studies of plant defense. Here, we study the genetic architecture of defense against the phloem-feeding insect cabbage whitefly (Aleyrodes proletella) in Arabidopsis thaliana. We determined whitefly performance, i.e. the survival and reproduction of whitefly females, on 360 worldwide selected natural accessions and subsequently performed GWA mapping using 214,051 SNPs. Substantial variation for whitefly adult survival and oviposition rate (number of eggs laid per female per day) was observed between the accessions. We identified 39 candidate SNPs for either whitefly adult survival or oviposition rate, all with relatively small effects, underpinning the complex architecture of defense traits. Among the corresponding candidate genes, i.e. genes in linkage disequilibrium (LD) with candidate SNPs, none have previously been identified as a gene playing a role in the interaction between plants and phloem-feeding insects. Whitefly performance on knock-out mutants of a number of candidate genes was significantly affected, validating the potential of GWA mapping for novel gene discovery in plant-insect interactions. Our results show that GWA analysis is a very useful tool to gain insight into the genetic architecture of plant defense against herbivorous insects, i.e. we identified and validated several genes affecting whitefly performance that have not previously been related to plant defense against herbivorous insects. PMID:26699853

Subtraction of cap-trapped full-length cDNA libraries to select rare transcripts.

PubMed

Hirozane-Kishikawa, Tomoko; Shiraki, Toshiyuki; Waki, Kazunori; Nakamura, Mari; Arakawa, Takahiro; Kawai, Jun; Fagiolini, Michela; Hensch, Takao K; Hayashizaki, Yoshihide; Carninci, Piero

2003-09-01

The normalization and subtraction of highly expressed cDNAs from relatively large tissues before cloning dramatically enhanced the gene discovery by sequencing for the mouse full-length cDNA encyclopedia, but these methods have not been suitable for limited RNA materials. To normalize and subtract full-length cDNA libraries derived from limited quantities of total RNA, here we report a method to subtract plasmid libraries excised from size-unbiased amplified lambda phage cDNA libraries that avoids heavily biasing steps such as PCR and plasmid library amplification. The proportion of full-length cDNAs and the gene discovery rate are high, and library diversity can be validated by in silico randomization.

Identification and Expression Analyses of miRNAs from Two Contrasting Flower Color Cultivars of Canna by Deep Sequencing.

PubMed

Roy, Sribash; Tripathi, Abhinandan Mani; Yadav, Amrita; Mishra, Parneeta; Nautiyal, Chandra Shekhar

2016-01-01

miRNAs are endogenous small RNA (sRNA) that play critical roles in plant development processes. Canna is an ornamental plant belonging to family Cannaceae. Here, we report for the first time the identification and differential expression of miRNAs in two contrasting flower color cultivars of Canna, Tropical sunrise and Red president. A total of 313 known miRNAs belonging to 78 miRNA families were identified from both the cultivars. Thirty one miRNAs (17 miRNA families) were specific to Tropical sunrise and 43 miRNAs (10 miRNA families) were specific to Red president. Thirty two and 18 putative new miRNAs were identified from Tropical sunrise and Red president, respectively. One hundred and nine miRNAs were differentially expressed in the two cultivars targeting 1343 genes. Among these, 16 miRNAs families targeting 60 genes were involved in flower development related traits and five miRNA families targeting five genes were involved in phenyl propanoid and pigment metabolic processes. We further validated the expression analysis of a few miRNA and their target genes by qRT-PCR. Transcription factors were the major miRNA targets identified. Target validation of a few randomly selected miRNAs by RLM-RACE was performed but was successful with only miR162. These findings will help in understanding flower development processes, particularly the color development in Canna.

PTCH1 expression at diagnosis predicts imatinib failure in chronic myeloid leukaemia patients in chronic phase.

PubMed

Alonso-Dominguez, Juan M; Grinfeld, Jacob; Alikian, Mary; Marin, David; Reid, Alistair; Daghistani, Mustafa; Hedgley, Corinne; O'Brien, Stephen; Clark, Richard E; Apperley, Jane; Foroni, Letizia; Gerrard, Gareth

2015-01-01

The tyrosine kinase inhibitor (TKI) imatinib has revolutionized the management of chronic myeloid leukaemia (CML). However, around 25% of patients fail to sustain an adequate response. We sought to identify gene-expression biomarkers that could be used to predict imatinib response. The expression of 29 genes, previously implicated in CML pathogenesis, were measured by TaqMan Low Density Array in 73 CML patient samples. Patients were divided into low and high expression for each gene and imatinib failure (IF), probability of achieving CCyR, progression free survival and CML related OS were compared by Kaplan-Meier and log-rank. Results were validated in a second cohort of 56 patients, with a further technical validation using custom gene-expression assays in a conventional RT-qPCR in a sub-cohort of 37 patients. Patients with low PTCH1 expression showed a worse clinical response for all variables in all cohorts. PTCH1 was the most significant predictor in the multivariate analysis compared with Sokal, age and EUTOS. PTCH1 expression assay showed the adequate sensitivity, specificity and predictive values to predict for IF. Given the different treatments available for CML, measuring PTCH1 expression at diagnosis may help establish who will benefit best from imatinib and who is better selected for second generation TKI. © 2014 Wiley Periodicals, Inc.

Design and Validation of Real-Time PCR: Quantitative Diagnosis of Common Leishmania Species in Iran.

PubMed

Fekri Soofi Abadi, Maryam; Dabiri, Shahriar; Fotouhi Ardakani, Reza; Fani Malaki, Lina; Amirpoor Rostami, Sahar; Ziasistani, Mahsa; Dabiri, Donya

2016-07-01

Design and validation of Real-time PCR on the protected gene region ITS2 to quantify the parasite load in common leishmania (L) species. Probe and primer were designed from the ITS2 region between the rRNA genes with minimum gene variation in three common leishmania species followed by a Real-time PCR using the Taq man probe method in the form of absolute quantification. A series of different concentrations of leishmania were analyzed. After the purified PCR product was successfully placed in a PTG19-T plasmid vector, specialized ITS2 region was cloned in this plasmid. In the last phase, the cloned gene was transferred to the Ecoli.Top10F bacteria. The standard plasmid was provided in 10(7) to 10(1) copies/rxn concentrations. The specification and clinical sensitivity of the data was analyzed using inter and intra scales. The probe and primer were designed using three species, including L. infantum, L. major, and L.tropica. Seven concentrations of purified parasite in culture media showed that the selected region for quantifying the parasite is suitable. Clinical and analytical specificity and sensitivity were both 100%, respectively. The Taq man method for the ITS2 region in leishmania is one the most sensitive diagnostic test for identifying the parasite load and is suggested as a tool for fast identification and quantification of species.

A microarray whole-genome gene expression dataset in a rat model of inflammatory corneal angiogenesis.

PubMed

Mukwaya, Anthony; Lindvall, Jessica M; Xeroudaki, Maria; Peebo, Beatrice; Ali, Zaheer; Lennikov, Anton; Jensen, Lasse Dahl Ejby; Lagali, Neil

2016-11-22

In angiogenesis with concurrent inflammation, many pathways are activated, some linked to VEGF and others largely VEGF-independent. Pathways involving inflammatory mediators, chemokines, and micro-RNAs may play important roles in maintaining a pro-angiogenic environment or mediating angiogenic regression. Here, we describe a gene expression dataset to facilitate exploration of pro-angiogenic, pro-inflammatory, and remodelling/normalization-associated genes during both an active capillary sprouting phase, and in the restoration of an avascular phenotype. The dataset was generated by microarray analysis of the whole transcriptome in a rat model of suture-induced inflammatory corneal neovascularisation. Regions of active capillary sprout growth or regression in the cornea were harvested and total RNA extracted from four biological replicates per group. High quality RNA was obtained for gene expression analysis using microarrays. Fold change of selected genes was validated by qPCR, and protein expression was evaluated by immunohistochemistry. We provide a gene expression dataset that may be re-used to investigate corneal neovascularisation, and may also have implications in other contexts of inflammation-mediated angiogenesis.

Selection and validation of reference genes for quantitative real-time PCR in Artemisia sphaerocephala based on transcriptome sequence data.

PubMed

Hu, Xiaowei; Zhang, Lijing; Nan, Shuzhen; Miao, Xiumei; Yang, Pengfang; Duan, Guoqin; Fu, Hua

2018-05-30

Artemisia sphaerocephala, a dicotyledonous perennial semi-shrub belonging to the Artemisia genus of the Compositae family, is widely distributed in northwestern China. This shrub is one of the most important pioneer plants which is capable of protecting rangelands from wind erosion. It therefore plays a vital role in maintaining desert ecosystem stability. In addition, to its use as a forage grass, it has excellent prospective applications as a source of plant oil and as a plant-based fuel. The use of internal genes is the basis for accurately assessing Real time quantitative PCR. In this study, based on transcriptome data of A. sphaerocephala, we analyzed 21 candidate internal genes to determine the optimal internal genes in this shrub. The stabilities of candidate genes were evaluated in 16 samples of A. sphaerocephala. Finally, UBC9 and TIP41-like were determined as the optimal reference genes in A. sphaerocephala by Delta Ct and three various programs. There were GeNorm, NormFinder and BestKeeper. Copyright © 2018 Elsevier B.V. All rights reserved.

New strategies in drug discovery.

PubMed

Ohlstein, Eliot H; Johnson, Anthony G; Elliott, John D; Romanic, Anne M

2006-01-01

Gene identification followed by determination of the expression of genes in a given disease and understanding of the function of the gene products is central to the drug discovery process. The ability to associate a specific gene with a disease can be attributed primarily to the extraordinary progress that has been made in the areas of gene sequencing and information technologies. Selection and validation of novel molecular targets have become of great importance in light of the abundance of new potential therapeutic drug targets that have emerged from human gene sequencing. In response to this revolution within the pharmaceutical industry, the development of high-throughput methods in both biology and chemistry has been necessitated. Further, the successful translation of basic scientific discoveries into clinical experimental medicine and novel therapeutics is an increasing challenge. As such, a new paradigm for drug discovery has emerged. This process involves the integration of clinical, genetic, genomic, and molecular phenotype data partnered with cheminformatics. Central to this process, the data generated are managed, collated, and interpreted with the use of informatics. This review addresses the use of new technologies that have arisen to deal with this new paradigm.

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer

PubMed Central

Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-01-01

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies. PMID:26397224

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer.

PubMed

Nguyen, Minh Nam; Choi, Tae Gyu; Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-10-13

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

An SSH library responsive to azadirachtin A constructed in Spodoptera litura Fabricius cell lines.

PubMed

Yan, Chao; Zhang, Zhi-Xiang; Xu, Han-Hong

2012-05-31

The present study revealed differentially expressed genes responsive to azadirachtin A (Aza) in Spodoptera litura cell line through suppression subtractive hybridization. In the Aza-responsive SSH library, approximately 270 sequences represent 53 different identified genes encoding proteins with various predicted functions, and the percentages of the gene clusters were 26.09% (genetic information processing), 11.41% (cell growth and death), 7.07% (metabolism), 6.52% (signal transduction/transport) and 2.72% (immunity), respectively. Eleven clones homologous to identified genes were selected to be confirmed through quantitative real time polymerase chain reaction. Among the eleven clones validated, all but one transcript of lipase showed an increase in SL cell line collected from ETA, whereas the transcripts of other genes were lower in the SL cell line collected from ETA compared with that of UETA. These genes were considered to be related to the response of SL cell line to Aza. These will provide a new clue to uncover the molecular mechanisms of Aza acting on SL cell line. Copyright © 2012 Elsevier B.V. All rights reserved.

Genome-Wide Screening and Characterization of the Dof Gene Family in Physic Nut (Jatropha curcas L.).

PubMed

Wang, Peipei; Li, Jing; Gao, Xiaoyang; Zhang, Di; Li, Anlin; Liu, Changning

2018-05-29

Physic nut ( Jatropha curcas L.) is a species of flowering plant with great potential for biofuel production and as an emerging model organism for functional genomic analysis, particularly in the Euphorbiaceae family. DNA binding with one finger (Dof) transcription factors play critical roles in numerous biological processes in plants. Nevertheless, the knowledge about members, and the evolutionary and functional characteristics of the Dof gene family in physic nut is insufficient. Therefore, we performed a genome-wide screening and characterization of the Dof gene family within the physic nut draft genome. In total, 24 JcDof genes (encoding 33 JcDof proteins) were identified. All the JcDof genes were divided into three major groups based on phylogenetic inference, which was further validated by the subsequent gene structure and motif analysis. Genome comparison revealed that segmental duplication may have played crucial roles in the expansion of the JcDof gene family, and gene expansion was mainly subjected to positive selection. The expression profile demonstrated the broad involvement of JcDof genes in response to various abiotic stresses, hormonal treatments and functional divergence. This study provides valuable information for better understanding the evolution of JcDof genes, and lays a foundation for future functional exploration of JcDof genes.

Selection of reference genes for expression studies with fish myogenic cell cultures.

PubMed

Bower, Neil I; Johnston, Ian A

2009-08-10

Relatively few studies have used cell culture systems to investigate gene expression and the regulation of myogenesis in fish. To produce robust data from quantitative real-time PCR mRNA levels need to be normalised using internal reference genes which have stable expression across all experimental samples. We have investigated the expression of eight candidate genes to identify suitable reference genes for use in primary myogenic cell cultures from Atlantic salmon (Salmo salar L.). The software analysis packages geNorm, Normfinder and Best keeper were used to rank genes according to their stability across 42 samples during the course of myogenic differentiation. Initial results showed several of the candidate genes exhibited stable expression throughout myogenic culture while Sdha was identified as the least stable gene. Further analysis with geNorm, Normfinder and Bestkeeper identified Ef1alpha, Hprt1, Ppia and RNApolII as stably expressed. Comparison of data normalised with the geometric average obtained from combinations of any three of these genes showed no significant differences, indicating that any combination of these genes is valid. The geometric average of any three of Hprt1, Ef1alpha, Ppia and RNApolII is suitable for normalisation of gene expression data in primary myogenic cultures from Atlantic salmon.

Selection of reference genes for qRT-PCR analysis of gene expression in sea cucumber Apostichopus japonicus during aestivation

NASA Astrophysics Data System (ADS)

Zhao, Ye; Chen, Muyan; Wang, Tianming; Sun, Lina; Xu, Dongxue; Yang, Hongsheng

2014-11-01

Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is a technique that is widely used for gene expression analysis, and its accuracy depends on the expression stability of the internal reference genes used as normalization factors. However, many applications of qRT-PCR used housekeeping genes as internal controls without validation. In this study, the expression stability of eight candidate reference genes in three tissues (intestine, respiratory tree, and muscle) of the sea cucumber Apostichopus japonicus was assessed during normal growth and aestivation using the geNorm, NormFinder, delta CT, and RefFinder algorithms. The results indicate that the reference genes exhibited significantly different expression patterns among the three tissues during aestivation. In general, the β-tubulin (TUBB) gene was relatively stable in the intestine and respiratory tree tissues. The optimal reference gene combination for intestine was 40S ribosomal protein S18 (RPS18), TUBB, and NADH dehydrogenase (NADH); for respiratory tree, it was β-actin (ACTB), TUBB, and succinate dehydrogenase cytochrome B small subunit (SDHC); and for muscle it was α-tubulin (TUBA) and NADH dehydrogenase [ubiquinone] 1 α subcomplex subunit 13 (NDUFA13). These combinations of internal control genes should be considered for use in further studies of gene expression in A. japonicus during aestivation.

Avoiding pitfalls of internal controls: validation of reference genes for analysis by qRT-PCR and Western blot throughout rat retinal development.

PubMed

Rocha-Martins, Maurício; Njaine, Brian; Silveira, Mariana S

2012-01-01

Housekeeping genes have been commonly used as reference to normalize gene expression and protein content data because of its presumed constitutive expression. In this paper, we challenge the consensual idea that housekeeping genes are reliable controls for expression studies in the retina through the investigation of a panel of reference genes potentially suitable for analysis of different stages of retinal development. We applied statistical tools on combinations of retinal developmental stages to assess the most stable internal controls for quantitative RT-PCR (qRT-PCR). The stability of expression of seven putative reference genes (Actb, B2m, Gapdh, Hprt1, Mapk1, Ppia and Rn18s) was analyzed using geNorm, BestKeeper and Normfinder software. In addition, several housekeeping genes were tested as loading controls for Western blot in the same sample panel, using Image J. Overall, for qRT-PCR the combination of Gapdh and Mapk1 showed the highest stability for most experimental sets. Actb was downregulated in more mature stages, while Rn18s and Hprt1 showed the highest variability. We normalized the expression of cyclin D1 using various reference genes and demonstrated that spurious results may result from blind selection of internal controls. For Western blot significant variation could be seen among four putative internal controls (β-actin, cyclophilin b, α-tubulin and lamin A/C), while MAPK1 was stably expressed. Putative housekeeping genes exhibit significant variation in both mRNA and protein content during retinal development. Our results showed that distinct combinations of internal controls fit for each experimental set in the case of qRT-PCR and that MAPK1 is a reliable loading control for Western blot. The results indicate that biased study outcomes may follow the use of reference genes without prior validation for qRT-PCR and Western blot.

Transcription Profiling of the mgrA Regulon in Staphylococcus aureus

PubMed Central

Luong, Thanh T.; Dunman, Paul M.; Murphy, Ellen; Projan, Steven J.; Lee, Chia Y.

2006-01-01

MgrA has been shown to affect multiple Staphylococcus aureus genes involved in virulence and antibiotic resistance. To comprehensively identify the target genes regulated by mgrA, we employed a microarray method to analyze the transcription profiles of S. aureus Newman, its isogeneic mgrA mutant, and an MgrA-overproducing derivative. We compared genes that were differentially expressed at exponential or early stationary growth phases. Our results showed that MgrA affected an impressive number of genes, 175 of which were positively regulated and 180 of which were negatively regulated in an mgrA-specific manner. The target genes included all functional categories. The microarray results were validated by real-time reverse transcription-PCR quantitation of a set of selected genes from different functional categories. Our data also indicate that mgrA regulates virulence factors in a fashion analogous to that of the accessory gene regulatory locus (agr). Accordingly, exoproteins are upregulated and surface proteins are downregulated by the regulator, suggesting that mgrA may function in concert with agr. The fact that a large number of genes are regulated by mgrA implies that MgrA is a major global regulator in S. aureus. PMID:16484201

Identification and mapping of Sr46 from Aegilops tauschii accession CIae 25 conferring resistance to race TTKSK (Ug99) of wheat stem rust pathogen.

PubMed

Yu, Guotai; Zhang, Qijun; Friesen, Timothy L; Rouse, Matthew N; Jin, Yue; Zhong, Shaobin; Rasmussen, Jack B; Lagudah, Evans S; Xu, Steven S

2015-03-01

Mapping studies confirm that resistance to Ug99 race of stem rust pathogen in Aegilops tauschii accession Clae 25 is conditioned by Sr46 and markers linked to the gene were developed for marker-assisted selection. The race TTKSK (Ug99) of Puccinia graminis f. sp. tritici, the causal pathogen for wheat stem rust, is considered as a major threat to global wheat production. To address this threat, researchers across the world have been devoted to identifying TTKSK-resistant genes. Here, we report the identification and mapping of a stem rust resistance gene in Aegilops tauschii accession CIae 25 that confers resistance to TTKSK and the development of molecular markers for the gene. An F2 population of 710 plants from an Ae. tauschii cross CIae 25 × AL8/78 were first evaluated against race TPMKC. A set of 14 resistant and 116 susceptible F2:3 families from the F2 plants were then evaluated for their reactions to TTKSK. Based on the tests, 179 homozygous susceptible F2 plants were selected as the mapping population to identify the simple sequence repeat (SSR) and sequence tagged site (STS) markers linked to the gene by bulk segregant analysis. A dominant stem rust resistance gene was identified and mapped with 16 SSR and five new STS markers to the deletion bin 2DS5-0.47-1.00 of chromosome arm 2DS in which Sr46 was located. Molecular marker and stem rust tests on CIae 25 and two Ae. tauschii accessions carrying Sr46 confirmed that the gene in CIae 25 is Sr46. This study also demonstrated that Sr46 is temperature-sensitive being less effective at low temperatures. The marker validation indicated that two closely linked markers Xgwm210 and Xwmc111 can be used for marker-assisted selection of Sr46 in wheat breeding programs.

Integrative approach for inference of gene regulatory networks using lasso-based random featuring and application to psychiatric disorders.

PubMed

Kim, Dongchul; Kang, Mingon; Biswas, Ashis; Liu, Chunyu; Gao, Jean

2016-08-10

Inferring gene regulatory networks is one of the most interesting research areas in the systems biology. Many inference methods have been developed by using a variety of computational models and approaches. However, there are two issues to solve. First, depending on the structural or computational model of inference method, the results tend to be inconsistent due to innately different advantages and limitations of the methods. Therefore the combination of dissimilar approaches is demanded as an alternative way in order to overcome the limitations of standalone methods through complementary integration. Second, sparse linear regression that is penalized by the regularization parameter (lasso) and bootstrapping-based sparse linear regression methods were suggested in state of the art methods for network inference but they are not effective for a small sample size data and also a true regulator could be missed if the target gene is strongly affected by an indirect regulator with high correlation or another true regulator. We present two novel network inference methods based on the integration of three different criteria, (i) z-score to measure the variation of gene expression from knockout data, (ii) mutual information for the dependency between two genes, and (iii) linear regression-based feature selection. Based on these criterion, we propose a lasso-based random feature selection algorithm (LARF) to achieve better performance overcoming the limitations of bootstrapping as mentioned above. In this work, there are three main contributions. First, our z score-based method to measure gene expression variations from knockout data is more effective than similar criteria of related works. Second, we confirmed that the true regulator selection can be effectively improved by LARF. Lastly, we verified that an integrative approach can clearly outperform a single method when two different methods are effectively jointed. In the experiments, our methods were validated by outperforming the state of the art methods on DREAM challenge data, and then LARF was applied to inferences of gene regulatory network associated with psychiatric disorders.

Validation of Reference Genes for Relative Quantitative Gene Expression Studies in Cassava (Manihot esculenta Crantz) by Using Quantitative Real-Time PCR

PubMed Central

Hu, Meizhen; Hu, Wenbin; Xia, Zhiqiang; Zhou, Xincheng; Wang, Wenquan

2016-01-01

Reverse transcription quantitative real-time polymerase chain reaction (real-time PCR, also referred to as quantitative RT-PCR or RT-qPCR) is a highly sensitive and high-throughput method used to study gene expression. Despite the numerous advantages of RT-qPCR, its accuracy is strongly influenced by the stability of internal reference genes used for normalizations. To date, few studies on the identification of reference genes have been performed on cassava (Manihot esculenta Crantz). Therefore, we selected 26 candidate reference genes mainly via the three following channels: reference genes used in previous studies on cassava, the orthologs of the most stable Arabidopsis genes, and the sequences obtained from 32 cassava transcriptome sequence data. Then, we employed ABI 7900 HT and SYBR Green PCR mix to assess the expression of these genes in 21 materials obtained from various cassava samples under different developmental and environmental conditions. The stability of gene expression was analyzed using two statistical algorithms, namely geNorm and NormFinder. geNorm software suggests the combination of cassava4.1_017977 and cassava4.1_006391 as sufficient reference genes for major cassava samples, the union of cassava4.1_014335 and cassava4.1_006884 as best choice for drought stressed samples, and the association of cassava4.1_012496 and cassava4.1_006391 as optimal choice for normally grown samples. NormFinder software recommends cassava4.1_006884 or cassava4.1_006776 as superior reference for qPCR analysis of different materials and organs of drought stressed or normally grown cassava, respectively. Results provide an important resource for cassava reference genes under specific conditions. The limitations of these findings were also discussed. Furthermore, we suggested some strategies that may be used to select candidate reference genes. PMID:27242878

The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization

PubMed Central

2012-01-01

Background Cancer-related genes show racial differences. Therefore, identification and characterization of DNA copy number alteration regions in different racial groups helps to dissect the mechanism of tumorigenesis. Methods Array-comparative genomic hybridization (array-CGH) was analyzed for DNA copy number profile in 40 Asian and 20 Caucasian lung cancer patients. Three methods including MetaCore analysis for disease and pathway correlations, concordance analysis between array-CGH database and the expression array database, and literature search for copy number variation genes were performed to select novel lung cancer candidate genes. Four candidate oncogenes were validated for DNA copy number and mRNA and protein expression by quantitative polymerase chain reaction (qPCR), chromogenic in situ hybridization (CISH), reverse transcriptase-qPCR (RT-qPCR), and immunohistochemistry (IHC) in more patients. Results We identified 20 chromosomal imbalance regions harboring 459 genes for Caucasian and 17 regions containing 476 genes for Asian lung cancer patients. Seven common chromosomal imbalance regions harboring 117 genes, included gain on 3p13-14, 6p22.1, 9q21.13, 13q14.1, and 17p13.3; and loss on 3p22.2-22.3 and 13q13.3 were found both in Asian and Caucasian patients. Gene validation for four genes including ARHGAP19 (10q24.1) functioning in Rho activity control, FRAT2 (10q24.1) involved in Wnt signaling, PAFAH1B1 (17p13.3) functioning in motility control, and ZNF322A (6p22.1) involved in MAPK signaling was performed using qPCR and RT-qPCR. Mean gene dosage and mRNA expression level of the four candidate genes in tumor tissues were significantly higher than the corresponding normal tissues (P<0.001~P=0.06). In addition, CISH analysis of patients indicated that copy number amplification indeed occurred for ARHGAP19 and ZNF322A genes in lung cancer patients. IHC analysis of paraffin blocks from Asian Caucasian patients demonstrated that the frequency of PAFAH1B1 protein overexpression was 68% in Asian and 70% in Caucasian. Conclusions Our study provides an invaluable database revealing common and differential imbalance regions at specific chromosomes among Asian and Caucasian lung cancer patients. Four validation methods confirmed our database, which would help in further studies on the mechanism of lung tumorigenesis. PMID:22691236

RNA-Seq transcriptome analysis of Amaranthus palmeri with differential tolerance to glufosinate herbicide

PubMed Central

Salas-Perez, Reiofeli A.; Saski, Christopher A.; Noorai, Rooksana E.; Srivastava, Subodh K.; Lawton-Rauh, Amy L.; Nichols, Robert L.

2018-01-01

Amaranthus palmeri (Amaranthaceae) is a noxious weed in several agroecosystems and in some cases seriously threatens the sustainability of crop production in North America. Glyphosate-resistant Amaranthus species are widespread, prompting the use of alternatives to glyphosate such as glufosinate, in conjunction with glufosinate-resistant crop cultivars, to help control glyphosate-resistant weeds. An experiment was conducted to analyze the transcriptome of A. palmeri plants that survived exposure to 0.55 kg ha-1 glufosinate. Since there was no record of glufosinate use at the collection site, survival of plants within the population are likely due to genetic expression that pre-dates selection; in the formal parlance of weed science this is described as natural tolerance. Leaf tissues from glufosinate-treated and non-treated seedlings were harvested 24 h after treatment (HAT) for RNA-Seq analysis. Global gene expression was measured using Illumina DNA sequence reads from non-treated and treated surviving (presumably tolerant, T) and susceptible (S) plants. The same plants were used to determine the mechanisms conferring differential tolerance to glufosinate. The S plants accumulated twice as much ammonia as did the T plants, 24 HAT. The relative copy number of the glufosinate target gene GS2 did not differ between T and S plants, with 1 to 3 GS2 copies in both biotypes. A reference cDNA transcriptome consisting of 72,780 contigs was assembled, with 65,282 sequences putatively annotated. Sequences of GS2 from the transcriptome assembly did not have polymorphisms unique to the tolerant plants. Five hundred sixty-seven genes were differentially expressed between treated T and S plants. Of the upregulated genes in treated T plants, 210 were more highly induced than were the upregulated genes in the treated S plants. Glufosinate-tolerant plants had greater induction of ABC transporter, glutathione S-transferase (GST), NAC transcription factor, nitronate monooxygenase (NMO), chitin elicitor receptor kinase (CERK1), heat shock protein 83, ethylene transcription factor, heat stress transcription factor, NADH-ubiquinone oxidoreductase, ABA 8’-hydroxylase, and cytochrome P450 genes (CYP72A, CYP94A1). Seven candidate genes were selected for validation using quantitative real time-PCR. While GST was upregulated in treated tolerant plants in at least one population, CYP72A219 was consistently highly expressed in all treated tolerant biotypes. These genes are candidates for contributing tolerance to glufosinate. Taken together, these results show that differential induction of stress-protection genes in a population can enable some individuals to survive herbicide application. Elevated expression of detoxification-related genes can get fixed in a population with sustained selection pressure, leading to evolution of resistance. Alternatively, sustained selection pressure could select for mutation(s) in the GS2 gene with the same consequence. PMID:29672568

Selective pharmacological inhibition of DDR1 prevents experimentally-induced glomerulonephritis in prevention and therapeutic regime.

PubMed

Moll, Solange; Yasui, Yukari; Abed, Ahmed; Murata, Takeshi; Shimada, Hideaki; Maeda, Akira; Fukushima, Naoshi; Kanamori, Masakazu; Uhles, Sabine; Badi, Laura; Cagarelli, Thomas; Formentini, Ivan; Drawnel, Faye; Georges, Guy; Bergauer, Tobias; Gasser, Rodolfo; Bonfil, R Daniel; Fridman, Rafael; Richter, Hans; Funk, Juergen; Moeller, Marcus J; Chatziantoniou, Christos; Prunotto, Marco

2018-06-01

Discoidin domain receptor 1 (DDR1) is a collagen-activated receptor tyrosine kinase extensively implicated in diseases such as cancer, atherosclerosis and fibrosis. Multiple preclinical studies, performed using either a gene deletion or a gene silencing approaches, have shown this receptor being a major driver target of fibrosis and glomerulosclerosis. The present study investigated the role and relevance of DDR1 in human crescentic glomerulonephritis (GN). Detailed DDR1 expression was first characterized in detail in human GN biopsies using a novel selective anti-DDR1 antibody using immunohistochemistry. Subsequently the protective role of DDR1 was investigated using a highly selective, novel, small molecule inhibitor in a nephrotoxic serum (NTS) GN model in a prophylactic regime and in the NEP25 GN mouse model using a therapeutic intervention regime. DDR1 expression was shown to be mainly limited to renal epithelium. In humans, DDR1 is highly induced in injured podocytes, in bridging cells expressing both parietal epithelial cell (PEC) and podocyte markers and in a subset of PECs forming the cellular crescents in human GN. Pharmacological inhibition of DDR1 in NTS improved both renal function and histological parameters. These results, obtained using a prophylactic regime, were confirmed in the NEP25 GN mouse model using a therapeutic intervention regime. Gene expression analysis of NTS showed that pharmacological blockade of DDR1 specifically reverted fibrotic and inflammatory gene networks and modulated expression of the glomerular cell gene signature, further validating DDR1 as a major mediator of cell fate in podocytes and PECs. Together, these results suggest that DDR1 inhibition might be an attractive and promising pharmacological intervention for the treatment of GN, predominantly by targeting the renal epithelium.

Genetic variation predicting cisplatin cytotoxicity associated with overall survival in lung cancer patients receiving platinum-based chemotherapy †, ‡

PubMed Central

Tan, Xiang-Lin; Moyer, Ann M.; Fridley, Brooke L.; Schaid, Daniel J.; Niu, Nifang; Batzler, Anthony J.; Jenkins, Gregory D.; Abo, Ryan P.; Li, Liang; Cunningham, Julie M.; Sun, Zhifu; Yang, Ping; Wang, Liewei

2011-01-01

Purpose Inherited variability in the prognosis of lung cancer patients treated with platinum-based chemotherapy has been widely investigated. However, the overall contribution of genetic variation to platinum response is not well established. To identify novel candidate SNPs/genes, we performed a genome-wide association study (GWAS) for cisplatin cytotoxicity using lymphoblastoid cell lines (LCLs), followed by an association study of selected SNPs from the GWAS with overall survival (OS) in lung cancer patients. Experimental Design GWAS for cisplatin were performed with 283 ethnically diverse LCLs. 168 top SNPs were genotyped in 222 small cell and 961 non-small cell lung cancer (SCLC, NSCLC) patients treated with platinum-based therapy. Association of the SNPs with OS was determined using the Cox regression model. Selected candidate genes were functionally validated by siRNA knockdown in human lung cancer cells. Results Among 157 successfully genotyped SNPs, 9 and 10 SNPs were top SNPs associated with OS for patients with NSCLC and SCLC, respectively, although they were not significant after adjusting for multiple testing. Fifteen genes, including 7 located within 200 kb up or downstream of the four top SNPs and 8 genes for which expression was correlated with three SNPs in LCLs were selected for siRNA screening. Knockdown of DAPK3 and METTL6, for which expression levels were correlated with the rs11169748 and rs2440915 SNPs, significantly decreased cisplatin sensitivity in lung cancer cells. Conclusions This series of clinical and complementary laboratory-based functional studies identified several candidate genes/SNPs that might help predict treatment outcomes for platinum-based therapy of lung cancer. PMID:21775533

A radiosensitivity gene signature and PD-L1 status predict clinical outcome of patients with invasive breast carcinoma in The Cancer Genome Atlas (TCGA) dataset.

PubMed

Jang, Bum-Sup; Kim, In Ah

2017-09-01

We investigated the link between the radiosensitivity gene signature and programmed cell death ligand 1 (PD-L1) status and clinical outcome in order to identify a group of patients that would possibly receive clinical benefit of radiotherapy (RT) combined with anti-PD1/PD-L1 therapy. We validated the identified gene signature related to radiosensitivity and analyzed the PD-L1 status of invasive breast cancer in The Cancer Genome Atlas (TCGA) dataset. To validate the gene signature, 1045 patients were selected and divided into two clusters using a consensus clustering algorithm based on their radiosensitive (RS) or radioresistant (RR) designation according to their prognosis. Patients were also stratified as PD-L1-high or PD-L1-low based on the median value of CD274 mRNA expression level as surrogates of PD-L1. Patents assigned to the RS group had decreased risk of recurrence-free survival (RFS) rate than patients in the RR group by univariate analysis (HR 0.45, 95% CI 0.25-0.81, p=0.008) only when treated with RT. The RS group was independently associated with the PD-L1-high group, and CD274 mRNA expression was significantly higher in the RS group (p<0.001) than the RR group. In the PD-L1-high group, the RS group was associated with better RFS compared to the RR group (HR 0.37, 95% CI 0.16-0.87, p=0.022) in multivariate analysis. The level of PD-L1 expression may represent the immunogenicity of tumors, and thus, we speculated that the PD-L1-high group had more immunogenic tumors, which could be more sensitive to radiation-induced immunologic cell death. We first evaluated the predictive value of the radiosensitivity gene signature and described a relationship with this radiosensitivity gene signature and PD-L1. The radiosensitivity gene signature and PD-L1 status were important factors for prediction of the clinical outcome of RT in patients with invasive breast cancer and may be used for selecting patients who will benefit from RT combined with anti-PD1/PDL1 therapy. Copyright © 2017 Elsevier B.V. All rights reserved.

High-resolution molecular validation of self-renewal and spontaneous differentiation in adipose-tissue derived human mesenchymal stem cells cultured in human platelet lysate

PubMed Central

Dudakovic, Amel Dudakovic; Camilleri, Emily; Riester, Scott M.; Lewallen, Eric A.; Kvasha, Sergiy; Chen, Xiaoyue; Radel, Darcie J.; Anderson, Jarett M.; Nair, Asha A.; Evans, Jared M.; Krych, Aaron J.; Smith, Jay; Deyle, David R.; Stein, Janet L.; Stein, Gary S.; Im, Hee-Jeong; Cool, Simon M.; Westendorf, Jennifer J.; Kakar, Sanjeev; Dietz, Allan B.; van Wijnen, Andre J.

2014-01-01

Improving the effectiveness of adipose-tissue derived human mesenchymal stromal/stem cells (AMSCs) for skeletal therapies requires a detailed characterization of mechanisms supporting cell proliferation and multi-potency. We investigated the molecular phenotype of AMSCs that were either actively proliferating in platelet lysate or in a basal non-proliferative state. Flow cytometry combined with high-throughput RNA sequencing (RNASeq) and RT-qPCR analyses validate that AMSCs express classic mesenchymal cell surface markers (e.g., CD44, CD73/NT5E, CD90/THY1 and CD105/ENG). Expression of CD90 is selectively elevated at confluence. Self-renewing AMSCs express a standard cell cycle program that successively mediates DNA replication, chromatin packaging, cyto-architectural enlargement and mitotic division. Confluent AMSCs preferentially express genes involved in extracellular matrix (ECM) formation and cellular communication. For example, cell cycle-related biomarkers (e.g., cyclins E2 and B2, transcription factor E2F1) and histone-related genes (e.g., H4, HINFP, NPAT) are elevated in proliferating AMSCs, while ECM genes are strongly upregulated (>10 fold) in quiescent AMSCs. AMSCs also express pluripotency genes (e.g., POU5F1, NANOG, KLF4) and early mesenchymal markers (e.g., NES, ACTA2) consistent with their multipotent phenotype. Strikingly, AMSCs modulate expression of WNT signaling components and switch production of WNT ligands (from WNT5A/WNT5B/WNT7B to WNT2/WNT2B), while up-regulating WNT-related genes (WISP2, SFRP2 and SFRP4). Furthermore, post-proliferative AMSCs spontaneously express fibroblastic, osteogenic, chondrogenic and adipogenic biomarkers when maintained in confluent cultures. Our findings validate the biological properties of self-renewing and multi-potent AMSCs by providing high-resolution quality control data that support their clinical versatility. PMID:24905804

Selection of reference genes for quantitative real time RT-PCR during dimorphism in the zygomycete Mucor circinelloides.

PubMed

Valle-Maldonado, Marco I; Jácome-Galarza, Irvin E; Gutiérrez-Corona, Félix; Ramírez-Díaz, Martha I; Campos-García, Jesús; Meza-Carmen, Víctor

2015-03-01

Mucor circinelloides is a dimorphic fungal model for studying several biological processes including cell differentiation (yeast-mold transitions) as well as biodiesel and carotene production. The recent release of the first draft sequence of the M. circinelloides genome, combined with the availability of analytical methods to determine patterns of gene expression, such as quantitative Reverse transcription-Polymerase chain reaction (qRT-PCR), and the development of molecular genetic tools for the manipulation of the fungus, may help identify M. circinelloides gene products and analyze their relevance in different biological processes. However, no information is available on M. circinelloides genes of stable expression that could serve as internal references in qRT-PCR analyses. One approach to solve this problem consists in the use of housekeeping genes as internal references. However, validation of the usability of these reference genes is a fundamental step prior to initiating qRT-PCR assays. This work evaluates expression of several constitutive genes by qRT-PCR throughout the morphological differentiation stages of M. circinelloides; our results indicate that tfc-1 and ef-1 are the most stable genes for qRT-PCR assays during differentiation studies and they are proposed as reference genes to carry out gene expression studies in this fungus.

FlyAtlas: database of gene expression in the tissues of Drosophila melanogaster

PubMed Central

Robinson, Scott W.; Herzyk, Pawel; Dow, Julian A. T.; Leader, David P.

2013-01-01

The FlyAtlas resource contains data on the expression of the genes of Drosophila melanogaster in different tissues (currently 25—17 adult and 8 larval) obtained by hybridization of messenger RNA to Affymetrix Drosophila Genome 2 microarrays. The microarray probe sets cover 13 250 Drosophila genes, detecting 12 533 in an unambiguous manner. The data underlying the original web application (http://flyatlas.org) have been restructured into a relational database and a Java servlet written to provide a new web interface, FlyAtlas 2 (http://flyatlas.gla.ac.uk/), which allows several additional queries. Users can retrieve data for individual genes or for groups of genes belonging to the same or related ontological categories. Assistance in selecting valid search terms is provided by an Ajax ‘autosuggest’ facility that polls the database as the user types. Searches can also focus on particular tissues, and data can be retrieved for the most highly expressed genes, for genes of a particular category with above-average expression or for genes with the greatest difference in expression between the larval and adult stages. A novel facility allows the database to be queried with a specific gene to find other genes with a similar pattern of expression across the different tissues. PMID:23203866

FlyAtlas: database of gene expression in the tissues of Drosophila melanogaster.

PubMed

Robinson, Scott W; Herzyk, Pawel; Dow, Julian A T; Leader, David P

2013-01-01

The FlyAtlas resource contains data on the expression of the genes of Drosophila melanogaster in different tissues (currently 25-17 adult and 8 larval) obtained by hybridization of messenger RNA to Affymetrix Drosophila Genome 2 microarrays. The microarray probe sets cover 13,250 Drosophila genes, detecting 12,533 in an unambiguous manner. The data underlying the original web application (http://flyatlas.org) have been restructured into a relational database and a Java servlet written to provide a new web interface, FlyAtlas 2 (http://flyatlas.gla.ac.uk/), which allows several additional queries. Users can retrieve data for individual genes or for groups of genes belonging to the same or related ontological categories. Assistance in selecting valid search terms is provided by an Ajax 'autosuggest' facility that polls the database as the user types. Searches can also focus on particular tissues, and data can be retrieved for the most highly expressed genes, for genes of a particular category with above-average expression or for genes with the greatest difference in expression between the larval and adult stages. A novel facility allows the database to be queried with a specific gene to find other genes with a similar pattern of expression across the different tissues.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, X; Zhou, Z; Thomas, K

Purpose: The goal of this work is to investigate the use of contrast enhanced computed tomographic (CT) features for the prediction of mutations of BAP1, PBRM1, and VHL genes in renal cell carcinoma (RCC). Methods: For this study, we used two patient databases with renal cell carcinoma (RCC). The first one consisted of 33 patients from our institution (UT Southwestern Medical Center, UTSW). The second one consisted of 24 patients from the Cancer Imaging Archive (TCIA), where each patient is connected by a unique identi?er to the tissue samples from the Cancer Genome Atlas (TCGA). From the contrast enhanced CTmore » image of each patient, tumor contour was first delineated by a physician. Geometry, intensity, and texture features were extracted from the delineated tumor. Based on UTSW dataset, we completed feature selection and trained a support vector machine (SVM) classifier to predict mutations of BAP1, PBRM1 and VHL genes. We then used TCIA-TCGA dataset to validate the predictive model build upon UTSW dataset. Results: The prediction accuracy of gene expression of TCIA-TCGA patients was 0.83 (20 of 24), 0.83 (20 of 24), and 0.75 (18 of 24) for BAP1, PBRM1, and VHL respectively. For BAP1 gene, texture feature was the most prominent feature type. For PBRM1 gene, intensity feature was the most prominent. For VHL gene, geometry, intensity, and texture features were all important. Conclusion: Using our feature selection strategy and models, we achieved predictive accuracy over 0.75 for all three genes under the condition of using patient data from one institution for training and data from other institutions for testing. These results suggest that radiogenomics can be used to aid in prognosis and used as convenient surrogates for expensive and time consuming gene assay procedures.« less

Whole genome sequencing and comparative genomics of closely related Fusarium Head Blight fungi: Fusarium graminearum, F. meridionale and F. asiaticum.

PubMed

Walkowiak, Sean; Rowland, Owen; Rodrigue, Nicolas; Subramaniam, Rajagopal

2016-12-09

The Fusarium graminearum species complex is composed of many distinct fungal species that cause several diseases in economically important crops, including Fusarium Head Blight of wheat. Despite being closely related, these species and individuals within species have distinct phenotypic differences in toxin production and pathogenicity, with some isolates reported as non-pathogenic on certain hosts. In this report, we compare genomes and gene content of six new isolates from the species complex, including the first available genomes of F. asiaticum and F. meridionale, with four other genomes reported in previous studies. A comparison of genome structure and gene content revealed a 93-99% overlap across all ten genomes. We identified more than 700 k base pairs (kb) of single nucleotide polymorphisms (SNPs), insertions, and deletions (indels) within common regions of the genome, which validated the species and genetic populations reported within species. We constructed a non-redundant pan gene list containing 15,297 genes from the ten genomes and among them 1827 genes or 12% were absent in at least one genome. These genes were co-localized in telomeric regions and select regions within chromosomes with a corresponding increase in SNPs and indels. Many are also predicted to encode for proteins involved in secondary metabolism and other functions associated with disease. Genes that were common between isolates contained high levels of nucleotide variation and may be pseudogenes, allelic, or under diversifying selection. The genomic resources we have contributed will be useful for the identification of genes that contribute to the phenotypic variation and niche specialization that have been reported among members of the F. graminearum species complex.

Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process

PubMed Central

Expósito-Rodríguez, Marino; Borges, Andrés A; Borges-Pérez, Andrés; Pérez, José A

2008-01-01

Background The elucidation of gene expression patterns leads to a better understanding of biological processes. Real-time quantitative RT-PCR has become the standard method for in-depth studies of gene expression. A biologically meaningful reporting of target mRNA quantities requires accurate and reliable normalization in order to identify real gene-specific variation. The purpose of normalization is to control several variables such as different amounts and quality of starting material, variable enzymatic efficiencies of retrotranscription from RNA to cDNA, or differences between tissues or cells in overall transcriptional activity. The validity of a housekeeping gene as endogenous control relies on the stability of its expression level across the sample panel being analysed. In the present report we describe the first systematic evaluation of potential internal controls during tomato development process to identify which are the most reliable for transcript quantification by real-time RT-PCR. Results In this study, we assess the expression stability of 7 traditional and 4 novel housekeeping genes in a set of 27 samples representing different tissues and organs of tomato plants at different developmental stages. First, we designed, tested and optimized amplification primers for real-time RT-PCR. Then, expression data from each candidate gene were evaluated with three complementary approaches based on different statistical procedures. Our analysis suggests that SGN-U314153 (CAC), SGN-U321250 (TIP41), SGN-U346908 ("Expressed") and SGN-U316474 (SAND) genes provide superior transcript normalization in tomato development studies. We recommend different combinations of these exceptionally stable housekeeping genes for suited normalization of different developmental series, including the complete tomato development process. Conclusion This work constitutes the first effort for the selection of optimal endogenous controls for quantitative real-time RT-PCR studies of gene expression during tomato development process. From our study a tool-kit of control genes emerges that outperform the traditional genes in terms of expression stability. PMID:19102748

Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets.

PubMed

Best, Myron G; Sol, Nik; In 't Veld, Sjors G J G; Vancura, Adrienne; Muller, Mirte; Niemeijer, Anna-Larissa N; Fejes, Aniko V; Tjon Kon Fat, Lee-Ann; Huis In 't Veld, Anna E; Leurs, Cyra; Le Large, Tessa Y; Meijer, Laura L; Kooi, Irsan E; Rustenburg, François; Schellen, Pepijn; Verschueren, Heleen; Post, Edward; Wedekind, Laurine E; Bracht, Jillian; Esenkbrink, Michelle; Wils, Leon; Favaro, Francesca; Schoonhoven, Jilian D; Tannous, Jihane; Meijers-Heijboer, Hanne; Kazemier, Geert; Giovannetti, Elisa; Reijneveld, Jaap C; Idema, Sander; Killestein, Joep; Heger, Michal; de Jager, Saskia C; Urbanus, Rolf T; Hoefer, Imo E; Pasterkamp, Gerard; Mannhalter, Christine; Gomez-Arroyo, Jose; Bogaard, Harm-Jan; Noske, David P; Vandertop, W Peter; van den Broek, Daan; Ylstra, Bauke; Nilsson, R Jonas A; Wesseling, Pieter; Karachaliou, Niki; Rosell, Rafael; Lee-Lewandrowski, Elizabeth; Lewandrowski, Kent B; Tannous, Bakhos A; de Langen, Adrianus J; Smit, Egbert F; van den Heuvel, Michel M; Wurdinger, Thomas

2017-08-14

Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92-0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83-0.95; p < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Gabrb3 gene deficient mice exhibit impaired social and exploratory behaviors, deficits in non-selective attention and hypoplasia of cerebellar vermal lobules: a potential model of autism spectrum disorder

PubMed Central

DeLorey, Timothy M.; Sahbaie, Peyman; Hashemi, Ezzat; Homanics, Gregg E.; Clark, J. David

2009-01-01

Objective GABAA receptors play an important regulatory role in the developmental events leading to the formation of complex neuronal networks and to the behaviors they govern. The primary aim of this study was to assess whether gabrb3 gene deficient (gabrb3-/-) mice exhibit abnormal social behavior, a core deficit associated with autism spectrum disorder. Methods Social and exploratory behaviors along with non-selective attention were assessed in gabrb3-/-, littermates (gabrb3+/+) and progenitor strains, C57BL/6J and 129/SvJ. In addition, semi-quantitative assessments of the size of cerebellar vermal lobules were performed on gabrb3+/+ and gabrb3-/- mice. Results Relative to controls, gabrb3-/- mice exhibited significant deficits in activities related to social behavior including sociability, social novelty and nesting. In addition, gabrb3-/- mice also exhibited differences in exploratory behavior compared to controls, as well as reductions in the frequency and duration of rearing episodes, suggested as being an index of non-selective attention. Gabrb3-/- mice also displayed significant hypoplasia of the cerebellar vermis compared to gabrb3+/+ mice. Conclusions The observed behavioral deficits, especially regarding social behaviors, strengthens the face validity of the gabrb3 gene deficient mouse as being a model of autism spectrum disorder. PMID:17983671

Biocomputational identification and validation of novel microRNAs predicted from bubaline whole genome shotgun sequences.

PubMed

Manku, H K; Dhanoa, J K; Kaur, S; Arora, J S; Mukhopadhyay, C S

2017-10-01

MicroRNAs (miRNAs) are small (19-25 base long), non-coding RNAs that regulate post-transcriptional gene expression by cleaving targeted mRNAs in several eukaryotes. The miRNAs play vital roles in multiple biological and metabolic processes, including developmental timing, signal transduction, cell maintenance and differentiation, diseases and cancers. Experimental identification of microRNAs is expensive and lab-intensive. Alternatively, computational approaches for predicting putative miRNAs from genomic or exomic sequences rely on features of miRNAs viz. secondary structures, sequence conservation, minimum free energy index (MFEI) etc. To date, not a single miRNA has been identified in bubaline (Bubalus bubalis), which is an economically important livestock. The present study aims at predicting the putative miRNAs of buffalo using comparative computational approach from buffalo whole genome shotgun sequencing data (INSDC: AWWX00000000.1). The sequences were blasted against the known mammalian miRNA. The obtained miRNAs were then passed through a series of filtration criteria to obtain the set of predicted (putative and novel) bubaline miRNA. Eight miRNAs were selected based on lowest E-value and validated by real time PCR (SYBR green chemistry) using RNU6 as endogenous control. The results from different trails of real time PCR shows that out of selected 8 miRNAs, only 2 (hsa-miR-1277-5p; bta-miR-2285b) are not expressed in bubaline PBMCs. The potential target genes based on their sequence complementarities were then predicted using miRanda. This work is the first report on prediction of bubaline miRNA from whole genome sequencing data followed by experimental validation. The finding could pave the way to future studies in economically important traits in buffalo. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of Novel Androgen-Regulated Pathways and mRNA Isoforms through Genome-Wide Exon-Specific Profiling of the LNCaP Transcriptome

PubMed Central

Carling, Phillippa J.; Buist, Thomas; Zhang, Chaolin; Grellscheid, Sushma N.; Armstrong, Kelly; Stockley, Jacqueline; Simillion, Cedric; Gaughan, Luke; Kalna, Gabriela; Zhang, Michael Q.; Robson, Craig N.; Leung, Hing Y.; Elliott, David J.

2011-01-01

Androgens drive the onset and progression of prostate cancer (PCa) by modulating androgen receptor (AR) transcriptional activity. Although several microarray-based studies have identified androgen-regulated genes, here we identify in-parallel global androgen-dependent changes in both gene and alternative mRNA isoform expression by exon-level analyses of the LNCaP transcriptome. While genome-wide gene expression changes correlated well with previously-published studies, we additionally uncovered a subset of 226 novel androgen-regulated genes. Gene expression pathway analysis of this subset revealed gene clusters associated with, and including the tyrosine kinase LYN, as well as components of the mTOR (mammalian target of rapamycin) pathway, which is commonly dysregulated in cancer. We also identified 1279 putative androgen-regulated alternative events, of which 325 (∼25%) mapped to known alternative splicing events or alternative first/last exons. We selected 30 androgen-dependent alternative events for RT-PCR validation, including mRNAs derived from genes encoding tumour suppressors and cell cycle regulators. Of seven positively-validating events (∼23%), five events involved transcripts derived from alternative promoters of known AR gene targets. In particular, we found a novel androgen-dependent mRNA isoform derived from an alternative internal promoter within the TSC2 tumour suppressor gene, which is predicted to encode a protein lacking an interaction domain required for mTOR inhibition. We confirmed that expression of this alternative TSC2 mRNA isoform was directly regulated by androgens, and chromatin immunoprecipitation indicated recruitment of AR to the alternative promoter region at early timepoints following androgen stimulation, which correlated with expression of alternative transcripts. Together, our data suggest that alternative mRNA isoform expression might mediate the cellular response to androgens, and may have roles in clinical PCa. PMID:22194994

Whole-Genome Thermodynamic Analysis Reduces siRNA Off-Target Effects

PubMed Central

Chen, Xi; Liu, Peng; Chou, Hui-Hsien

2013-01-01

Small interfering RNAs (siRNAs) are important tools for knocking down targeted genes, and have been widely applied to biological and biomedical research. To design siRNAs, two important aspects must be considered: the potency in knocking down target genes and the off-target effect on any nontarget genes. Although many studies have produced useful tools to design potent siRNAs, off-target prevention has mostly been delegated to sequence-level alignment tools such as BLAST. We hypothesize that whole-genome thermodynamic analysis can identify potential off-targets with higher precision and help us avoid siRNAs that may have strong off-target effects. To validate this hypothesis, two siRNA sets were designed to target three human genes IDH1, ITPR2 and TRIM28. They were selected from the output of two popular siRNA design tools, siDirect and siDesign. Both siRNA design tools have incorporated sequence-level screening to avoid off-targets, thus their output is believed to be optimal. However, one of the sets we tested has off-target genes predicted by Picky, a whole-genome thermodynamic analysis tool. Picky can identify off-target genes that may hybridize to a siRNA within a user-specified melting temperature range. Our experiments validated that some off-target genes predicted by Picky can indeed be inhibited by siRNAs. Similar experiments were performed using commercially available siRNAs and a few off-target genes were also found to be inhibited as predicted by Picky. In summary, we demonstrate that whole-genome thermodynamic analysis can identify off-target genes that are missed in sequence-level screening. Because Picky prediction is deterministic according to thermodynamics, if a siRNA candidate has no Picky predicted off-targets, it is unlikely to cause off-target effects. Therefore, we recommend including Picky as an additional screening step in siRNA design. PMID:23484018

Deciphering signature of selection affecting beef quality traits in Angus cattle.

PubMed

Taye, Mengistie; Yoon, Joon; Dessie, Tadelle; Cho, Seoae; Oh, Sung Jong; Lee, Hak-Kyo; Kim, Heebal

2018-01-01

Artificial selection towards a desired phenotype/trait has modified the genomes of livestock dramatically that generated breeds that greatly differ in morphology, production and environmental adaptation traits. Angus cattle are among the famous cattle breeds developed for superior beef quality. This paper aimed at exploring genomic regions under selection in Angus cattle that are associated with meat quality traits and other associated phenotypes. The whole genome of 10 Angus cattle was compared with 11 Hanwoo (A-H) and 9 Jersey (A-J) cattle breeds using a cross-population composite likelihood ratio (XP-CLR) statistical method. The top 1% of the empirical distribution was taken as significant and annotated using UMD3.1. As a result, 255 and 210 genes were revealed under selection from A-H and A-J comparisons, respectively. The WebGestalt gene ontology analysis resulted in sixteen (A-H) and five (A-J) significantly enriched KEGG pathways. Several pathways associated with meat quality traits (insulin signaling, type II diabetes mellitus pathway, focal adhesion pathway, and ECM-receptor interaction), and feeding efficiency (olfactory transduction, tight junction, and metabolic pathways) were enriched. Genes affecting beef quality traits (e.g., FABP3, FTO, DGAT2, ACS, ACAA2, CPE, TNNI1), stature and body size (e.g., PLAG1, LYN, CHCHD7, RPS20), fertility and dystocia (e.g., ESR1, RPS20, PPP2R1A, GHRL, PLAG1), feeding efficiency (e.g., PIK3CD, DNAJC28, DNAJC3, GHRL, PLAG1), coat color (e.g., MC1-R) and genetic disorders (e.g., ITGB6, PLAG1) were found to be under positive selection in Angus cattle. The study identified genes and pathways that are related to meat quality traits and other phenotypes of Angus cattle. The findings in this study, after validation using additional or independent dataset, will provide useful information for the study of Angus cattle in particular and beef cattle in general.

Impact of selection and demography on the diffusion of lactase persistence.

PubMed

Gerbault, Pascale; Moret, Céline; Currat, Mathias; Sanchez-Mazas, Alicia

2009-07-24

The lactase enzyme allows lactose digestion in fresh milk. Its activity strongly decreases after the weaning phase in most humans, but persists at a high frequency in Europe and some nomadic populations. Two hypotheses are usually proposed to explain the particular distribution of the lactase persistence phenotype. The gene-culture coevolution hypothesis supposes a nutritional advantage of lactose digestion in pastoral populations. The calcium assimilation hypothesis suggests that carriers of the lactase persistence allele(s) (LCT*P) are favoured in high-latitude regions, where sunshine is insufficient to allow accurate vitamin-D synthesis. In this work, we test the validity of these two hypotheses on a large worldwide dataset of lactase persistence frequencies by using several complementary approaches. We first analyse the distribution of lactase persistence in various continents in relation to geographic variation, pastoralism levels, and the genetic patterns observed for other independent polymorphisms. Then we use computer simulations and a large database of archaeological dates for the introduction of domestication to explore the evolution of these frequencies in Europe according to different demographic scenarios and selection intensities. Our results show that gene-culture coevolution is a likely hypothesis in Africa as high LCT*P frequencies are preferentially found in pastoral populations. In Europe, we show that population history played an important role in the diffusion of lactase persistence over the continent. Moreover, selection pressure on lactase persistence has been very high in the North-western part of the continent, by contrast to the South-eastern part where genetic drift alone can explain the observed frequencies. This selection pressure increasing with latitude is highly compatible with the calcium assimilation hypothesis while the gene-culture coevolution hypothesis cannot be ruled out if a positively selected lactase gene was carried at the front of the expansion wave during the Neolithic transition in Europe.

Bone-related gene profiles in developing calvaria.

PubMed

Cho, Je-Yoel; Lee, Won-Bong; Kim, Hyun-Jung; Mi Woo, Kyung; Baek, Jeong-Hwa; Choi, Je-Yong; Hur, Cheol-Gu; Ryoo, Hyun-Mo

2006-05-10

Generating a comprehensive understanding of osteogenesis-related gene profiles is very important in the development of new treatments for osteopenic conditions. Developing calvaria undergoes a typical intramembranous bone-forming process. To identify genes associated with osteoblast differentiation, we isolated total RNAs from parietal bones, that represent active osteoblasts, and sutural mesenchyme, that represents osteoprogenitor cells, and comprehensively analyzed their gene expression profiles using an oligo-based Affymetrix microarray chip containing 22,690 probes. About 2100 genes with "Present" calls had more than 2-fold higher expression in bone compared to sutures while 73 of these genes had more than 8-fold expression. Some of these genes are already known to be bone-related biomarkers: VitD receptor, bone sialoprotein, osteocalcin, osteopontin, MMP13, etc. Eight genes were selected and subjected to confirmation by quantitative real-time RT-PCR analyses. All the genes tested showed higher expression in bones, ranging from 5- to 140-fold. Several of these genes are ESTs while others are already known but their functions in osteogenesis were not previously known. Most genes of the BMP and FGF families probed in the Genechip analysis were more highly expressed in bone tissues compared to suture. All differentially-expressed Runx and Dlx family genes also showed higher expression in bone. These results imply that our data is valid and can be used as a good standard for the mining of osteogenesis-related genes.

A high-density transcript linkage map with 1,845 expressed genes positioned by microarray-based Single Feature Polymorphisms (SFP) in Eucalyptus

PubMed Central

2011-01-01

Background Technological advances are progressively increasing the application of genomics to a wider array of economically and ecologically important species. High-density maps enriched for transcribed genes facilitate the discovery of connections between genes and phenotypes. We report the construction of a high-density linkage map of expressed genes for the heterozygous genome of Eucalyptus using Single Feature Polymorphism (SFP) markers. Results SFP discovery and mapping was achieved using pseudo-testcross screening and selective mapping to simultaneously optimize linkage mapping and microarray costs. SFP genotyping was carried out by hybridizing complementary RNA prepared from 4.5 year-old trees xylem to an SFP array containing 103,000 25-mer oligonucleotide probes representing 20,726 unigenes derived from a modest size expressed sequence tags collection. An SFP-mapping microarray with 43,777 selected candidate SFP probes representing 15,698 genes was subsequently designed and used to genotype SFPs in a larger subset of the segregating population drawn by selective mapping. A total of 1,845 genes were mapped, with 884 of them ordered with high likelihood support on a framework map anchored to 180 microsatellites with average density of 1.2 cM. Using more probes per unigene increased by two-fold the likelihood of detecting segregating SFPs eventually resulting in more genes mapped. In silico validation showed that 87% of the SFPs map to the expected location on the 4.5X draft sequence of the Eucalyptus grandis genome. Conclusions The Eucalyptus 1,845 gene map is the most highly enriched map for transcriptional information for any forest tree species to date. It represents a major improvement on the number of genes previously positioned on Eucalyptus maps and provides an initial glimpse at the gene space for this global tree genome. A general protocol is proposed to build high-density transcript linkage maps in less characterized plant species by SFP genotyping with a concurrent objective of reducing microarray costs. HIgh-density gene-rich maps represent a powerful resource to assist gene discovery endeavors when used in combination with QTL and association mapping and should be especially valuable to assist the assembly of reference genome sequences soon to come for several plant and animal species. PMID:21492453

Current and future developments in patents for quantitative trait loci in dairy cattle.

PubMed

Weller, Joel I

2007-01-01

Many studies have proposed that rates of genetic gain in dairy cattle can be increased by direct selection on the individual quantitative loci responsible for the genetic variation in these traits, or selection on linked genetic markers. The development of DNA-level genetic markers has made detection of QTL nearly routine in all major livestock species. The studies that attempted to detect genes affecting quantitative traits can be divided into two categories: analysis of candidate genes, and genome scans based on within-family genetic linkage. To date, 12 patent cooperative treaty (PCT) and US patents have been registered for DNA sequences claimed to be associated with effects on economic traits in dairy cattle. All claim effects on milk production, but other traits are also included in some of the claims. Most of the sequences found by the candidate gene approach are of dubious validity, and have been repeated in only very few independent studies. The two missense mutations on chromosomes 6 and 14 affecting milk concentration derived from genome scans are more solidly based, but the claims are also disputed. A few PCT in dairy cattle are commercialized as genetic tests where commercial dairy farmers are the target market.

Selection and testing of reference genes for accurate RT-qPCR in rice seedlings under iron toxicity.

PubMed

Santos, Fabiane Igansi de Castro Dos; Marini, Naciele; Santos, Railson Schreinert Dos; Hoffman, Bianca Silva Fernandes; Alves-Ferreira, Marcio; de Oliveira, Antonio Costa

2018-01-01

Reverse Transcription quantitative PCR (RT-qPCR) is a technique for gene expression profiling with high sensibility and reproducibility. However, to obtain accurate results, it depends on data normalization by using endogenous reference genes whose expression is constitutive or invariable. Although the technique is widely used in plant stress analyzes, the stability of reference genes for iron toxicity in rice (Oryza sativa L.) has not been thoroughly investigated. Here, we tested a set of candidate reference genes for use in rice under this stressful condition. The test was performed using four distinct methods: NormFinder, BestKeeper, geNorm and the comparative ΔCt. To achieve reproducible and reliable results, Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines were followed. Valid reference genes were found for shoot (P2, OsGAPDH and OsNABP), root (OsEF-1a, P8 and OsGAPDH) and root+shoot (OsNABP, OsGAPDH and P8) enabling us to perform further reliable studies for iron toxicity in both indica and japonica subspecies. The importance of the study of other than the traditional endogenous genes for use as normalizers is also shown here.

Selection and testing of reference genes for accurate RT-qPCR in rice seedlings under iron toxicity

PubMed Central

dos Santos, Fabiane Igansi de Castro; Marini, Naciele; dos Santos, Railson Schreinert; Hoffman, Bianca Silva Fernandes; Alves-Ferreira, Marcio

2018-01-01

Reverse Transcription quantitative PCR (RT-qPCR) is a technique for gene expression profiling with high sensibility and reproducibility. However, to obtain accurate results, it depends on data normalization by using endogenous reference genes whose expression is constitutive or invariable. Although the technique is widely used in plant stress analyzes, the stability of reference genes for iron toxicity in rice (Oryza sativa L.) has not been thoroughly investigated. Here, we tested a set of candidate reference genes for use in rice under this stressful condition. The test was performed using four distinct methods: NormFinder, BestKeeper, geNorm and the comparative ΔCt. To achieve reproducible and reliable results, Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines were followed. Valid reference genes were found for shoot (P2, OsGAPDH and OsNABP), root (OsEF-1a, P8 and OsGAPDH) and root+shoot (OsNABP, OsGAPDH and P8) enabling us to perform further reliable studies for iron toxicity in both indica and japonica subspecies. The importance of the study of other than the traditional endogenous genes for use as normalizers is also shown here. PMID:29494624

Use of a 17-Gene Prognostic Assay in Contemporary Urologic Practice: Results of an Interim Analysis in an Observational Cohort.

PubMed

Eure, Gregg; Germany, Raymond; Given, Robert; Lu, Ruixiao; Shindel, Alan W; Rothney, Megan; Glowacki, Richard; Henderson, Jonathan; Richardson, Tim; Goldfischer, Evan; Febbo, Phillip G; Denes, Bela S

2017-09-01

To study the impact of genomic testing in shared decision making for men with clinically low-risk prostate cancer (PCa). Patients with clinically low-risk PCa were enrolled in a prospective, multi-institutional study of a validated 17-gene tissue-based reverse transcription polymerase chain reaction assay (Genomic Prostate Score [GPS]). In this paper we report on outcomes in the first 297 patients enrolled in the study with valid 17-gene assay results and decision-change data. The primary end points were shared decision on initial management and persistence on active surveillance (AS) at 1 year post diagnosis. AS utilization and persistence were compared with similar end points in a group of patients who did not have genomic testing (baseline cohort). Secondary end points included perceived utility of the assay and patient decisional conflict before and after testing. One-year results were available on 258 patients. Shift between initial recommendation and shared decision occurred in 23% of patients. Utilization of AS was higher in the GPS-tested cohort than in the untested baseline cohort (62% vs 40%). The proportion of men who selected and persisted on AS at 1 year was 55% and 34% in the GPS and baseline cohorts, respectively. Physicians reported that GPS was useful in 90% of cases. Mean decisional conflict scores declined in patients after GPS testing. Patients who received GPS testing were more likely to select and persist on AS for initial management compared with a matched baseline group. These data indicate that GPS help guide shared decisions in clinically low-risk PCa. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

De Novo Assembly and Transcriptome Analysis of the Rubber Tree (Hevea brasiliensis) and SNP Markers Development for Rubber Biosynthesis Pathways

PubMed Central

Mantello, Camila Campos; Cardoso-Silva, Claudio Benicio; da Silva, Carla Cristina; de Souza, Livia Moura; Scaloppi Junior, Erivaldo José; de Souza Gonçalves, Paulo; Vicentini, Renato; de Souza, Anete Pereira

2014-01-01

Hevea brasiliensis (Willd. Ex Adr. Juss.) Muell.-Arg. is the primary source of natural rubber that is native to the Amazon rainforest. The singular properties of natural rubber make it superior to and competitive with synthetic rubber for use in several applications. Here, we performed RNA sequencing (RNA-seq) of H. brasiliensis bark on the Illumina GAIIx platform, which generated 179,326,804 raw reads on the Illumina GAIIx platform. A total of 50,384 contigs that were over 400 bp in size were obtained and subjected to further analyses. A similarity search against the non-redundant (nr) protein database returned 32,018 (63%) positive BLASTx hits. The transcriptome analysis was annotated using the clusters of orthologous groups (COG), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam databases. A search for putative molecular marker was performed to identify simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). In total, 17,927 SSRs and 404,114 SNPs were detected. Finally, we selected sequences that were identified as belonging to the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, which are involved in rubber biosynthesis, to validate the SNP markers. A total of 78 SNPs were validated in 36 genotypes of H. brasiliensis. This new dataset represents a powerful information source for rubber tree bark genes and will be an important tool for the development of microsatellites and SNP markers for use in future genetic analyses such as genetic linkage mapping, quantitative trait loci identification, investigations of linkage disequilibrium and marker-assisted selection. PMID:25048025

Molecular tools for the selective detection of nine diatom species biomarkers of various water quality levels.

PubMed

Cimarelli, Lucia; Singh, Kumar Saurabh; Mai, Nguyen Thi Nhu; Dhar, Bidhan Chandra; Brandi, Anna; Brandi, Letizia; Spurio, Roberto

2015-05-22

Our understanding of the composition of diatom communities and their response to environmental changes is currently limited by laborious taxonomic identification procedures. Advances in molecular technologies are expected to contribute more efficient, robust and sensitive tools for the detection of these ecologically relevant microorganisms. There is a need to explore and test phylogenetic markers as an alternative to the use of rRNA genes, whose limited sequence divergence does not allow the accurate discrimination of diatoms at the species level. In this work, nine diatom species belonging to eight genera, isolated from epylithic environmental samples collected in central Italy, were chosen to implement a panel of diatoms covering the full range of ecological status of freshwaters. The procedure described in this work relies on the PCR amplification of specific regions in two conserved diatom genes, elongation factor 1-a (eEF1-a) and silicic acid transporter (SIT), as a first step to narrow down the complexity of the targets, followed by microarray hybridization experiments. Oligonucleotide probes with the potential to discriminate closely related species were designed taking into account the genetic polymorphisms found in target genes. These probes were tested, refined and validated on a small-scale prototype DNA chip. Overall, we obtained 17 highly specific probes targeting eEF1-a and SIT, along with 19 probes having lower discriminatory power recognizing at the same time two or three species. This basic array was validated in a laboratory setting and is ready for tests with crude environmental samples eventually to be scaled-up to include a larger panel of diatoms. Its possible use for the simultaneous detection of diatoms selected from the classes of water quality identified by the European Water Framework Directive is discussed.

DNA methylation array analysis identifies breast cancer associated RPTOR, MGRN1 and RAPSN hypomethylation in peripheral blood DNA.

PubMed

Tang, Qiuqiong; Holland-Letz, Tim; Slynko, Alla; Cuk, Katarina; Marme, Frederik; Schott, Sarah; Heil, Jörg; Qu, Bin; Golatta, Michael; Bewerunge-Hudler, Melanie; Sutter, Christian; Surowy, Harald; Wappenschmidt, Barbara; Schmutzler, Rita; Hoth, Markus; Bugert, Peter; Bartram, Claus R; Sohn, Christof; Schneeweiss, Andreas; Yang, Rongxi; Burwinkel, Barbara

2016-09-27

DNA methylation changes in peripheral blood DNA have been shown to be associated with solid tumors. We sought to identify methylation alterations in whole blood DNA that are associated with breast cancer (BC). Epigenome-wide DNA methylation profiling on blood DNA from BC cases and healthy controls was performed by applying Infinium HumanMethylation450K BeadChips. Promising CpG sites were selected and validated in three independent larger sample cohorts via MassARRAY EpiTyper assays. CpG sites located in three genes (cg06418238 in RPTOR, cg00736299 in MGRN1 and cg27466532 in RAPSN), which showed significant hypomethylation in BC patients compared to healthy controls in the discovery cohort (p < 1.00 x 10-6) were selected and successfully validated in three independent cohorts (validation I, n =211; validation II, n=378; validation III, n=520). The observed methylation differences are likely not cell-type specific, as the differences were only seen in whole blood, but not in specific sub cell-types of leucocytes. Moreover, we observed in quartile analysis that women in the lower methylation quartiles of these three loci had higher ORs than women in the higher quartiles. The combined AUC of three loci was 0.79 (95%CI 0.73-0.85) in validation cohort I, and was 0.60 (95%CI 0.54-0.66) and 0.62 (95%CI 0.57-0.67) in validation cohort II and III, respectively. Our study suggests that hypomethylation of CpG sites in RPTOR, MGRN1 and RAPSN in blood is associated with BC and might serve as blood-based marker supplements for BC if these could be verified in prospective studies.

RNA sequencing to predict response to TNF-α inhibitors reveals possible mechanism for nonresponse in smokers.

PubMed

Cuppen, Bart V J; Rossato, Marzia; Fritsch-Stork, Ruth D E; Concepcion, Arno N; Linn-Rasker, Suzanne P; Bijlsma, Johannes W J; van Laar, Jacob M; Lafeber, Floris P J G; Radstake, Timothy R

2018-06-06

Several studies have employed microarray-based profiling to predict response to tumor necrosis factor-alpha inhibitors (TNFi) in rheumatoid arthritis (RA); yet efforts to validate these targets have failed to show predictive abilities acceptable for clinical practice. The eighty most extreme responders and nonresponders to TNFi therapy were selected from the observational BiOCURA cohort. RNA sequencing was performed on mRNA from peripheral blood mononuclear cells (PBMCs) collected before initiation of treatment. The expression of pathways as well as individual gene transcripts between responders and nonresponders was investigated. Promising targets were technically replicated and validated in n = 40 new patients using qPCR assays. Before therapy initiation, nonresponders had lower expression of pathways related to interferon and cytokine signaling, while also showing higher levels of two genes, GPR15 and SEMA6B (p = 0.02). The two targets could be validated, however, additional analyses revealed that GPR15 and SEMA6B did not independently predict response, but were rather dose-dependent markers of smoking (p < 0.0001). The study did not identify new transcripts ready to use in clinical practice, yet GPR15 and SEMA6B were recognized as candidate explanatory markers for the reduced treatment success in RA smokers.

Gene Editing in Human Lymphoid Cells: Role for Donor DNA, Type of Genomic Nuclease and Cell Selection Method.

PubMed

Zotova, Anastasia; Lopatukhina, Elena; Filatov, Alexander; Khaitov, Musa; Mazurov, Dmitriy

2017-11-02

Programmable endonucleases introduce DNA breaks at specific sites, which are repaired by non-homologous end joining (NHEJ) or homology recombination (HDR). Genome editing in human lymphoid cells is challenging as these difficult-to-transfect cells may also inefficiently repair DNA by HDR. Here, we estimated efficiencies and dynamics of knockout (KO) and knockin (KI) generation in human T and B cell lines depending on repair template, target loci and types of genomic endonucleases. Using zinc finger nuclease (ZFN), we have engineered Jurkat and CEM cells with the 8.2 kb human immunodeficiency virus type 1 (HIV-1) ∆Env genome integrated at the adeno-associated virus integration site 1 (AAVS1) locus that stably produce virus particles and mediate infection upon transfection with helper vectors. Knockouts generated by ZFN or clustered regularly interspaced short palindromic repeats (CRISPR/Cas9) double nicking techniques were comparably efficient in lymphoid cells. However, unlike polyclonal sorted cells, gene-edited cells selected by cloning exerted tremendous deviations in functionality as estimated by replication of HIV-1 and human T cell leukemia virus type 1 (HTLV-1) in these cells. Notably, the recently reported high-fidelity eCas9 1.1 when combined to the nickase mutation displayed gene-dependent decrease in on-target activity. Thus, the balance between off-target effects and on-target efficiency of nucleases, as well as choice of the optimal method of edited cell selection should be taken into account for proper gene function validation in lymphoid cells.

Intricate interplay between astrocytes and motor neurons in ALS

PubMed Central

Phatnani, Hemali P.; Guarnieri, Paolo; Friedman, Brad A.; Carrasco, Monica A.; Muratet, Michael; O’Keeffe, Sean; Nwakeze, Chiamaka; Pauli-Behn, Florencia; Newberry, Kimberly M.; Meadows, Sarah K.; Tapia, Juan Carlos; Myers, Richard M.; Maniatis, Tom

2013-01-01

ALS results from the selective and progressive degeneration of motor neurons. Although the underlying disease mechanisms remain unknown, glial cells have been implicated in ALS disease progression. Here, we examine the effects of glial cell/motor neuron interactions on gene expression using the hSOD1G93A (the G93A allele of the human superoxide dismutase gene) mouse model of ALS. We detect striking cell autonomous and nonautonomous changes in gene expression in cocultured motor neurons and glia, revealing that the two cell types profoundly affect each other. In addition, we found a remarkable concordance between the cell culture data and expression profiles of whole spinal cords and acutely isolated spinal cord cells during disease progression in the G93A mouse model, providing validation of the cell culture approach. Bioinformatics analyses identified changes in the expression of specific genes and signaling pathways that may contribute to motor neuron degeneration in ALS, among which are TGF-β signaling pathways. PMID:23388633

A Synthetic DNA-Binding Domain Guides Distinct Chromatin-Modifying Small Molecules to Activate an Identical Gene Network.

PubMed

Han, Le; Pandian, Ganesh N; Chandran, Anandhakumar; Sato, Shinsuke; Taniguchi, Junichi; Kashiwazaki, Gengo; Sawatani, Yoshito; Hashiya, Kaori; Bando, Toshikazu; Xu, Yufang; Qian, Xuhong; Sugiyama, Hiroshi

2015-07-20

Synthetic dual-function ligands targeting specific DNA sequences and histone-modifying enzymes were applied to achieve regulatory control over multi-gene networks in living cells. Unlike the broad array of targeting small molecules for histone deacetylases (HDACs), few modulators are known for histone acetyltransferases (HATs), which play a central role in transcriptional control. As a novel chemical approach to induce selective HAT-regulated genes, we conjugated a DNA-binding domain (DBD) "I" to N-(4-chloro-3-trifluoromethyl-phenyl)-2-ethoxy-benzamide (CTB), an artificial HAT activator. In vitro enzyme activity assays and microarray studies were used to demonstrate that distinct functional small molecules could be transformed to have identical bioactivity when conjugated with a targeting DBD. This proof-of-concept synthetic strategy validates the switchable functions of HDACs and HATs in gene regulation and provides a molecular basis for developing versatile bioactive ligands. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

PubMed

Gruel, Jérémy; LeBorgne, Michel; LeMeur, Nolwenn; Théret, Nathalie

2011-09-12

Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns

PubMed Central

2011-01-01

Background Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Results Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Conclusions Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks. PMID:21910886

A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning

PubMed Central

2018-01-01

Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma based on gene coexpression network. Using multiple microarray, gene coexpression network analysis was performed to identify survival-related networks. A deep learning based risk stratification model was constructed with representative genes of these networks. The model was validated in two test sets. Survival analysis was performed using the output of the model to evaluate whether it could predict patients' survival independent of clinicopathological variables. Five networks were significantly associated with patients' survival. Considering prognostic significance and representativeness, genes of the two survival-related networks were selected for input of the model. The output of the model was significantly associated with patients' survival in two test sets and training set (p < 0.00001, p < 0.0001 and p = 0.02 for training and test sets 1 and 2, resp.). In multivariate analyses, the model was associated with patients' prognosis independent of other clinicopathological features. Our study presents a new perspective on incorporating gene coexpression networks into the gene expression signature and clinical application of deep learning in genomic data science for prognosis prediction. PMID:29581968

Validation of the β-amy1 transcription profiling assay and selection of reference genes suited for a RT-qPCR assay in developing barley caryopsis.

PubMed

Ovesná, Jaroslava; Kučera, Ladislav; Vaculová, Kateřina; Štrymplová, Kamila; Svobodová, Ilona; Milella, Luigi

2012-01-01

Reverse transcription coupled with real-time quantitative PCR (RT-qPCR) is a frequently used method for gene expression profiling. Reference genes (RGs) are commonly employed to normalize gene expression data. A limited information exist on the gene expression and profiling in developing barley caryopsis. Expression stability was assessed by measuring the cycle threshold (Ct) range and applying both the GeNorm (pair-wise comparison of geometric means) and Normfinder (model-based approach) principles for the calculation. Here, we have identified a set of four RGs suitable for studying gene expression in the developing barley caryopsis. These encode the proteins GAPDH, HSP90, HSP70 and ubiquitin. We found a correlation between the frequency of occurrence of a transcript in silico and its suitability as an RG. This set of RGs was tested by comparing the normalized level of β-amylase (β-amy1) transcript with directly measured quantities of the BMY1 gene product in the developing barley caryopsis. This panel of genes could be used for other gene expression studies, as well as to optimize β-amy1 analysis for study of the impact of β-amy1 expression upon barley end-use quality.

Image-guided genomic analysis of tissue response to laser-induced thermal stress

NASA Astrophysics Data System (ADS)

Mackanos, Mark A.; Helms, Mike; Kalish, Flora; Contag, Christopher H.

2011-05-01

The cytoprotective response to thermal injury is characterized by transcriptional activation of ``heat shock proteins'' (hsp) and proinflammatory proteins. Expression of these proteins may predict cellular survival. Microarray analyses were performed to identify spatially distinct gene expression patterns responding to thermal injury. Laser injury zones were identified by expression of a transgene reporter comprised of the 70 kD hsp gene and the firefly luciferase coding sequence. Zones included the laser spot, the surrounding region where hsp70-luc expression was increased, and a region adjacent to the surrounding region. A total of 145 genes were up-regulated in the laser irradiated region, while 69 were up-regulated in the adjacent region. At 7 hours the chemokine Cxcl3 was the highest expressed gene in the laser spot (24 fold) and adjacent region (32 fold). Chemokines were the most common up-regulated genes identified. Microarray gene expression was successfully validated using qRT- polymerase chain reaction for selected genes of interest. The early response genes are likely involved in cytoprotection and initiation of the healing response. Their regulatory elements will benefit creating the next generation reporter mice and controlling expression of therapeutic proteins. The identified genes serve as drug development targets that may prevent acute tissue damage and accelerate healing.

Evaluation of artificial selection in Standard Poodles using whole-genome sequencing.

PubMed

Friedenberg, Steven G; Meurs, Kathryn M; Mackay, Trudy F C

2016-12-01

Identifying regions of artificial selection within dog breeds may provide insights into genetic variation that underlies breed-specific traits or diseases-particularly if these traits or disease predispositions are fixed within a breed. In this study, we searched for runs of homozygosity (ROH) and calculated the d i statistic (which is based upon F ST ) to identify regions of artificial selection in Standard Poodles using high-coverage, whole-genome sequencing data of 15 Standard Poodles and 49 dogs across seven other breeds. We identified consensus ROH regions ≥1 Mb in length and common to at least ten Standard Poodles covering 0.6 % of the genome, and d i regions that most distinguish Standard Poodles from other breeds covering 3.7 % of the genome. Within these regions, we identified enriched gene pathways related to olfaction, digestion, and taste, as well as pathways related to adrenal hormone biosynthesis, T cell function, and protein ubiquitination that could contribute to the pathogenesis of some Poodle-prevalent autoimmune diseases. We also validated variants related to hair coat and skull morphology that have previously been identified as being under selective pressure in Poodles, and flagged additional polymorphisms in genes such as ITGA2B, CBX4, and TNXB that may represent strong candidates for other common Poodle disorders.

Direct expression and validation of phage-selected peptide variants in mammalian cells.

PubMed

Quinlan, Brian D; Gardner, Matthew R; Joshi, Vinita R; Chiang, Jessica J; Farzan, Michael

2013-06-28

Phage display is a key technology for the identification and maturation of high affinity peptides, antibodies, and other proteins. However, limitations of bacterial expression restrict the range and sensitivity of assays that can be used to evaluate phage-selected variants. To address this problem, selected genes are typically transferred to mammalian expression vectors, a major rate-limiting step in the iterative improvement of peptides and proteins. Here we describe a system that combines phage display and efficient mammalian expression in a single vector, pDQ1. This system permits immediate expression of phage-selected genes as IgG1-Fc fusions in mammalian cells, facilitating the rapid, sensitive characterization of a large number of library outputs for their biochemical and functional properties. We demonstrate the utility of this system by improving the ability of a CD4-mimetic peptide to bind the HIV-1 envelope glycoprotein and neutralize HIV-1 entry. We further improved the potency of the resulting peptide, CD4mim6, by limiting its ability to induce the CD4-bound conformation of the envelope glycoprotein. Thus, CD4mim6 and its variants can be used to investigate the properties of the HIV-1 envelope glycoprotein, and pDQ1 can accelerate the discovery of new peptides and proteins through phage display.

A candidate gene based approach validates Md-PG1 as the main responsible for a QTL impacting fruit texture in apple (Malus x domestica Borkh).

PubMed

Longhi, Sara; Hamblin, Martha T; Trainotti, Livio; Peace, Cameron P; Velasco, Riccardo; Costa, Fabrizio

2013-03-04

Apple is a widely cultivated fruit crop for its quality properties and extended storability. Among the several quality factors, texture is the most important and appreciated, and within the apple variety panorama the cortex texture shows a broad range of variability. Anatomically these variations depend on degradation events occurring in both fruit primary cell wall and middle lamella. This physiological process is regulated by an enzymatic network generally encoded by large gene families, among which polygalacturonase is devoted to the depolymerization of pectin. In apple, Md-PG1, a key gene belonging to the polygalacturonase gene family, was mapped on chromosome 10 and co-localized within the statistical interval of a major hot spot QTL associated to several fruit texture sub-phenotypes. In this work, a QTL corresponding to the position of Md-PG1 was validated and new functional alleles associated to the fruit texture properties in 77 apple cultivars were discovered. 38 SNPs genotyped by gene full length resequencing and 2 SSR markers ad hoc targeted in the gene metacontig were employed. Out of this SNP set, eleven were used to define three significant haplotypes statistically associated to several texture components. The impact of Md-PG1 in the fruit cell wall disassembly was further confirmed by the cortex structure electron microscope scanning in two apple varieties characterized by opposite texture performance, such as 'Golden Delicious' and 'Granny Smith'. The results here presented step forward into the genetic dissection of fruit texture in apple. This new set of haplotypes, and microsatellite alleles, can represent a valuable toolbox for a more efficient parental selection as well as the identification of new apple accessions distinguished by superior fruit quality features.

In silico pathway analysis in cervical carcinoma reveals potential new targets for treatment

PubMed Central

van Dam, Peter A.; van Dam, Pieter-Jan H. H.; Rolfo, Christian; Giallombardo, Marco; van Berckelaer, Christophe; Trinh, Xuan Bich; Altintas, Sevilay; Huizing, Manon; Papadimitriou, Kostas; Tjalma, Wiebren A. A.; van Laere, Steven

2016-01-01

An in silico pathway analysis was performed in order to improve current knowledge on the molecular drivers of cervical cancer and detect potential targets for treatment. Three publicly available Affymetrix gene expression data-sets (GSE5787, GSE7803, GSE9750) were retrieved, vouching for a total of 9 cervical cancer cell lines (CCCLs), 39 normal cervical samples, 7 CIN3 samples and 111 cervical cancer samples (CCSs). Predication analysis of microarrays was performed in the Affymetrix sets to identify cervical cancer biomarkers. To select cancer cell-specific genes the CCSs were compared to the CCCLs. Validated genes were submitted to a gene set enrichment analysis (GSEA) and Expression2Kinases (E2K). In the CCSs a total of 1,547 probe sets were identified that were overexpressed (FDR < 0.1). Comparing to CCCLs 560 probe sets (481 unique genes) had a cancer cell-specific expression profile, and 315 of these genes (65%) were validated. GSEA identified 5 cancer hallmarks enriched in CCSs (P < 0.01 and FDR < 0.25) showing that deregulation of the cell cycle is a major component of cervical cancer biology. E2K identified a protein-protein interaction (PPI) network of 162 nodes (including 20 drugable kinases) and 1626 edges. This PPI-network consists of 5 signaling modules associated with MYC signaling (Module 1), cell cycle deregulation (Module 2), TGFβ-signaling (Module 3), MAPK signaling (Module 4) and chromatin modeling (Module 5). Potential targets for treatment which could be identified were CDK1, CDK2, ABL1, ATM, AKT1, MAPK1, MAPK3 among others. The present study identified important driver pathways in cervical carcinogenesis which should be assessed for their potential therapeutic drugability. PMID:26701206

Evaluation of the mature grain phytase candidate HvPAPhy_a gene in barley (Hordeum vulgare L.) using CRISPR/Cas9 and TALENs.

PubMed

Holme, Inger B; Wendt, Toni; Gil-Humanes, Javier; Deleuran, Lise C; Starker, Colby G; Voytas, Daniel F; Brinch-Pedersen, Henrik

2017-09-01

In the present study, we utilized TALEN- and CRISPR/Cas9-induced mutations to analyze the promoter of the barley phytase gene HvPAPhy_a. The purpose of the study was dual, validation of the PAPhy_a enzyme as the main contributor of the mature grain phytase activity (MGPA), as well as validating the importance of a specific promoter region of the PAPhy_a gene which contains three overlapping cis-acting regulatory elements (GCN4, Skn1 and the RY-element) known to be involved in gene expression during grain filling. The results confirm that the barley PAPhy_a enzyme is the main contributor to the MGPA as grains of knock-out lines show very low MGPA. Additionally, the analysis of the HvPAPhy_a promoter region containing the GCN4/Skn1/RY motif highlights its importance for HvPAPhy_a expression as the MGPA in grains of plant lines with mutations within this motif is significantly reduced. Interestingly, lines with deletions located downstream of the motif show even lower MGPA levels, indicating that the GCN4/SKn1/RY motif is not the only element responsible for the level of PAPhy_a expression during grain maturation. Mutant grains with very low MPGA showed delayed germination as compared to grains of wild type barley. As grains with high levels of preformed phytases would provide more readily available phosphorous needed for a fast germination, this indicates that faster germination may be implicated in the positive selection of the ancient PAPhy gene duplication that lead to the creation of the PAPhy_a gene.

Regulation of Isoflavone Biosynthesis by miRNAs in Two Contrasting Soybean Genotypes at Different Seed Developmental Stages

PubMed Central

Gupta, Om P.; Nigam, Deepti; Dahuja, Anil; Kumar, Sanjeev; Vinutha, T.; Sachdev, Archana; Praveen, Shelly

2017-01-01

Owing to the presence of nutritionally important, health-promoting bioactive compounds, especially isoflavones, soybean has acquired the status of a functional food. miRNAs are tiny riboregulator of gene expression by either decreasing and/or increasing the expression of their corresponding target genes. Despite several works on identification and functional characterization of plant miRNAs, the role of miRNAs in the regulation of isoflavones metabolism is still a virgin field. In the present study, we identified a total of 31 new miRNAs along with their 245 putative target genes from soybean seed-specific ESTs using computational approach. The Kyoto Encyclopedia of Genes and Genomes pathway analyses indicated that miRNA putatively regulates metabolism and genetic information processing. Out of that, a total of 5 miRNAs (Gma-miRNA12, Gma-miRNA24, Gma-miRNA26, Gma-miRNA28, and Gma-miRNA29) were predicted and validated for their probable role during isoflavone biosynthesis. We also validated their five target genes using RA-PCR, which is as good as 5'RLM-RACE. Temporal regulation [35 days after flowering, 45, 55, and 65 DAF] of miRNAs and their targets showed differential expression schema. Differential expression of Gma-miR26 and Gma-miRNA28 along with their corresponding target genes (Glyma.10G197900 and Glyma.09G127200) showed a direct relationship with the total isoflavone content. Therefore, understanding the miRNA-based genetic regulation of isoflavone pathway would assist in selection and manipulation to get high-performing soybean genotypes with better isoflavone yield. PMID:28450878

Insight into the expression variation of metal-responsive genes in the seedling of date palm (Phoenix dactylifera).

PubMed

Chaâbene, Zayneb; Rorat, Agnieszka; Rekik Hakim, Imen; Bernard, Fabien; Douglas, Grubb C; Elleuch, Amine; Vandenbulcke, Franck; Mejdoub, Hafedh

2018-04-01

Phytochelatin synthase and metallothionein gene expressions were monitored via qPCR in order to investigate the molecular mechanisms involved in Cd and Cr detoxification in date palm (Phoenix dactylifera). A specific reference gene validation procedure using BestKeeper, NormFinder and geNorm programs allowed selection of the three most stable reference genes in a context of Cd or Cr contamination among six reference gene candidates, namely elongation factor α1, actin, aldehyde dehydrogenase, SAND family, tubulin 6 and TaTa box binding protein. Phytochelatin synthase (pcs) and metallothionein (mt) encoding gene expression were induced from the first days of exposure. At low Cd stress (0.02 mM), genes were still up-regulated until 60th day of exposure. At the highest metal concentrations, however, pcs and mt gene expressions decreased. pcs encoding gene was significantly up-regulated under Cr exposure, and was more responsive to increasing Cr concentration than mt encoding gene. Moreover, exposure to Cd or Cr influenced clearly seed germination and hypocotyls elongation. Thus, the results have proved that both analyzed genes participate in metal detoxification and their expression is regulated at transcriptional level in date palm subjected to Cr and Cd stress. Consequently, variations of expression of mt and pcs genes may serve as early-warning biomarkers of metal stress in this species. Copyright © 2018 Elsevier Ltd. All rights reserved.

Identification and validation of single nucleotide polymorphic markers linked to Ug99 stem rust resistance in spring wheat

PubMed Central

Chao, Shiaoman; Singh, Ravi P.; Sorrells, Mark E.

2017-01-01

Wheat stem rust (Puccinia graminis f. sp. tritici Eriks. and E. Henn.) is one of the most destructive diseases world-wide. Races belonging to Ug99 (or TTKSK) continue to cause crop losses in East Africa and threaten global wheat production. Developing and deploying wheat varieties with multiple race-specific genes or complex adult plant resistance is necessary to achieve durability. In the present study, we applied genome-wide association studies (GWAS) for identifying loci associated with the Ug99 stem rust resistance (SR) in a panel of wheat lines developed at the International Maize and Wheat Improvement Center (CIMMYT). Genotyping was carried out using the wheat 9K iSelect single nucleotide polymorphism (SNP) chip. Phenotyping was done in the field in Kenya by infection of Puccinia graminis f. sp. tritici race TTKST, the Sr24-virulent variant of Ug99. Marker-trait association identified 12 SNP markers significantly associated with resistance. Among them, 7 were mapped on five chromosomes. Markers located on chromosomes 4A and 4B overlapped with the location of the Ug99 resistance genes SrND643 and Sr37, respectively. Markers identified on 7DL were collocated with Sr25. Additional significant markers were located in the regions where no Sr gene has been reported. The chromosome location for five of the SNP markers was unknown. A BLASTN search of the NCBI database using the flanking sequences of the SNPs associated with Ug99 resistance revealed that several markers were linked to plant disease resistance analogues, while others were linked to regulatory factors or metabolic enzymes. A KASP (Kompetitive Allele Specific PCR) assay was used for validating six marker loci linked to genes with resistance to Ug99. Of those, four co-segregated with the Sr25-pathotypes while the rest identified unknown resistance genes. With further investigation, these markers can be used for marker-assisted selection in breeding for Ug99 stem rust resistance in wheat. PMID:28241006

Novel Rhizosphere Soil Alleles for the Enzyme 1-Aminocyclopropane-1-Carboxylate Deaminase Queried for Function with an In Vivo Competition Assay

PubMed Central

Jin, Zhao; Di Rienzi, Sara C.; Janzon, Anders; Werner, Jeff J.; Angenent, Largus T.; Dangl, Jeffrey L.; Fowler, Douglas M.

2015-01-01

Metagenomes derived from environmental microbiota encode a vast diversity of protein homologs. How this diversity impacts protein function can be explored through selection assays aimed to optimize function. While artificially generated gene sequence pools are typically used in selection assays, their usage may be limited because of technical or ethical reasons. Here, we investigate an alternative strategy, the use of soil microbial DNA as a starting point. We demonstrate this approach by optimizing the function of a widely occurring soil bacterial enzyme, 1-aminocyclopropane-1-carboxylate (ACC) deaminase. We identified a specific ACC deaminase domain region (ACCD-DR) that, when PCR amplified from the soil, produced a variant pool that we could swap into functional plasmids carrying ACC deaminase-encoding genes. Functional clones of ACC deaminase were selected for in a competition assay based on their capacity to provide nitrogen to Escherichia coli in vitro. The most successful ACCD-DR variants were identified after multiple rounds of selection by sequence analysis. We observed that previously identified essential active-site residues were fixed in the original unselected library and that additional residues went to fixation after selection. We identified a divergent essential residue whose presence hints at the possible use of alternative substrates and a cluster of neutral residues that did not influence ACCD performance. Using an artificial ACCD-DR variant library generated by DNA oligomer synthesis, we validated the same fixation patterns. Our study demonstrates that soil metagenomes are useful starting pools of protein-coding-gene diversity that can be utilized for protein optimization and functional characterization when synthetic libraries are not appropriate. PMID:26637602

Integrative Bayesian variable selection with gene-based informative priors for genome-wide association studies.

PubMed

Zhang, Xiaoshuai; Xue, Fuzhong; Liu, Hong; Zhu, Dianwen; Peng, Bin; Wiemels, Joseph L; Yang, Xiaowei

2014-12-10

Genome-wide Association Studies (GWAS) are typically designed to identify phenotype-associated single nucleotide polymorphisms (SNPs) individually using univariate analysis methods. Though providing valuable insights into genetic risks of common diseases, the genetic variants identified by GWAS generally account for only a small proportion of the total heritability for complex diseases. To solve this "missing heritability" problem, we implemented a strategy called integrative Bayesian Variable Selection (iBVS), which is based on a hierarchical model that incorporates an informative prior by considering the gene interrelationship as a network. It was applied here to both simulated and real data sets. Simulation studies indicated that the iBVS method was advantageous in its performance with highest AUC in both variable selection and outcome prediction, when compared to Stepwise and LASSO based strategies. In an analysis of a leprosy case-control study, iBVS selected 94 SNPs as predictors, while LASSO selected 100 SNPs. The Stepwise regression yielded a more parsimonious model with only 3 SNPs. The prediction results demonstrated that the iBVS method had comparable performance with that of LASSO, but better than Stepwise strategies. The proposed iBVS strategy is a novel and valid method for Genome-wide Association Studies, with the additional advantage in that it produces more interpretable posterior probabilities for each variable unlike LASSO and other penalized regression methods.

A predictive signature gene set for discriminating active from latent tuberculosis in Warao Amerindian children.

PubMed

Verhagen, Lilly M; Zomer, Aldert; Maes, Mailis; Villalba, Julian A; Del Nogal, Berenice; Eleveld, Marc; van Hijum, Sacha Aft; de Waard, Jacobus H; Hermans, Peter Wm

2013-02-01

Tuberculosis (TB) continues to cause a high toll of disease and death among children worldwide. The diagnosis of childhood TB is challenged by the paucibacillary nature of the disease and the difficulties in obtaining specimens. Whereas scientific and clinical research efforts to develop novel diagnostic tools have focused on TB in adults, childhood TB has been relatively neglected. Blood transcriptional profiling has improved our understanding of disease pathogenesis of adult TB and may offer future leads for diagnosis and treatment. No studies applying gene expression profiling of children with TB have been published so far. We identified a 116-gene signature set that showed an average prediction error of 11% for TB vs. latent TB infection (LTBI) and for TB vs. LTBI vs. healthy controls (HC) in our dataset. A minimal gene set of only 9 genes showed the same prediction error of 11% for TB vs. LTBI in our dataset. Furthermore, this minimal set showed a significant discriminatory value for TB vs. LTBI for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. In order to identify a robust representative gene set that would perform well in populations of different genetic backgrounds, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to classify 78% of the TB cases correctly with no LTBI subjects wrongly classified as TB (100% specificity). Our data justify the further exploration of our signature set as biomarkers for potential childhood TB diagnosis. We show that, as the identification of different biomarkers in ethnically distinct cohorts is apparent, it is important to cross-validate newly identified markers in all available cohorts.

A predictive signature gene set for discriminating active from latent tuberculosis in Warao Amerindian children

PubMed Central

2013-01-01

Background Tuberculosis (TB) continues to cause a high toll of disease and death among children worldwide. The diagnosis of childhood TB is challenged by the paucibacillary nature of the disease and the difficulties in obtaining specimens. Whereas scientific and clinical research efforts to develop novel diagnostic tools have focused on TB in adults, childhood TB has been relatively neglected. Blood transcriptional profiling has improved our understanding of disease pathogenesis of adult TB and may offer future leads for diagnosis and treatment. No studies applying gene expression profiling of children with TB have been published so far. Results We identified a 116-gene signature set that showed an average prediction error of 11% for TB vs. latent TB infection (LTBI) and for TB vs. LTBI vs. healthy controls (HC) in our dataset. A minimal gene set of only 9 genes showed the same prediction error of 11% for TB vs. LTBI in our dataset. Furthermore, this minimal set showed a significant discriminatory value for TB vs. LTBI for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. In order to identify a robust representative gene set that would perform well in populations of different genetic backgrounds, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to classify 78% of the TB cases correctly with no LTBI subjects wrongly classified as TB (100% specificity). Conclusions Our data justify the further exploration of our signature set as biomarkers for potential childhood TB diagnosis. We show that, as the identification of different biomarkers in ethnically distinct cohorts is apparent, it is important to cross-validate newly identified markers in all available cohorts. PMID:23375113

The validity and value of inclusive fitness theory

PubMed Central

Bourke, Andrew F. G.

2011-01-01

Social evolution is a central topic in evolutionary biology, with the evolution of eusociality (societies with altruistic, non-reproductive helpers) representing a long-standing evolutionary conundrum. Recent critiques have questioned the validity of the leading theory for explaining social evolution and eusociality, namely inclusive fitness (kin selection) theory. I review recent and past literature to argue that these critiques do not succeed. Inclusive fitness theory has added fundamental insights to natural selection theory. These are the realization that selection on a gene for social behaviour depends on its effects on co-bearers, the explanation of social behaviours as unalike as altruism and selfishness using the same underlying parameters, and the explanation of within-group conflict in terms of non-coinciding inclusive fitness optima. A proposed alternative theory for eusocial evolution assumes mistakenly that workers' interests are subordinate to the queen's, contains no new elements and fails to make novel predictions. The haplodiploidy hypothesis has yet to be rigorously tested and positive relatedness within diploid eusocial societies supports inclusive fitness theory. The theory has made unique, falsifiable predictions that have been confirmed, and its evidence base is extensive and robust. Hence, inclusive fitness theory deserves to keep its position as the leading theory for social evolution. PMID:21920980

The validity and value of inclusive fitness theory.

PubMed

Bourke, Andrew F G

2011-11-22

Social evolution is a central topic in evolutionary biology, with the evolution of eusociality (societies with altruistic, non-reproductive helpers) representing a long-standing evolutionary conundrum. Recent critiques have questioned the validity of the leading theory for explaining social evolution and eusociality, namely inclusive fitness (kin selection) theory. I review recent and past literature to argue that these critiques do not succeed. Inclusive fitness theory has added fundamental insights to natural selection theory. These are the realization that selection on a gene for social behaviour depends on its effects on co-bearers, the explanation of social behaviours as unalike as altruism and selfishness using the same underlying parameters, and the explanation of within-group conflict in terms of non-coinciding inclusive fitness optima. A proposed alternative theory for eusocial evolution assumes mistakenly that workers' interests are subordinate to the queen's, contains no new elements and fails to make novel predictions. The haplodiploidy hypothesis has yet to be rigorously tested and positive relatedness within diploid eusocial societies supports inclusive fitness theory. The theory has made unique, falsifiable predictions that have been confirmed, and its evidence base is extensive and robust. Hence, inclusive fitness theory deserves to keep its position as the leading theory for social evolution.

Evaluating the Detection of Hydrocarbon-Degrading Bacteria in 16S rRNA Gene Sequencing Surveys

PubMed Central

Berry, David; Gutierrez, Tony

2017-01-01

Hydrocarbonoclastic bacteria (HCB) play a key role in the biodegradation of oil hydrocarbons in marine and other environments. A small number of taxa have been identified as obligate HCB, notably the Gammaproteobacterial genera Alcanivorax, Cycloclasticus, Marinobacter, Neptumonas, Oleiphilus, Oleispira, and Thalassolituus, as well as the Alphaproteobacterial genus Thalassospira. Detection of HCB in amplicon-based sequencing surveys relies on high coverage by PCR primers and accurate taxonomic classification. In this study, we performed a phylogenetic analysis to identify 16S rRNA gene sequence regions that represent the breadth of sequence diversity within these taxa. Using validated sequences, we evaluated 449 universal 16S rRNA gene-targeted bacterial PCR primer pairs for their coverage of these taxa. The results of this analysis provide a practical framework for selection of suitable primer sets for optimal detection of HCB in sequencing surveys. PMID:28567035

Evaluating the Detection of Hydrocarbon-Degrading Bacteria in 16S rRNA Gene Sequencing Surveys.

PubMed

Berry, David; Gutierrez, Tony

2017-01-01

Hydrocarbonoclastic bacteria (HCB) play a key role in the biodegradation of oil hydrocarbons in marine and other environments. A small number of taxa have been identified as obligate HCB, notably the Gammaproteobacterial genera Alcanivorax, Cycloclasticus, Marinobacter, Neptumonas, Oleiphilus, Oleispira , and Thalassolituus , as well as the Alphaproteobacterial genus Thalassospira . Detection of HCB in amplicon-based sequencing surveys relies on high coverage by PCR primers and accurate taxonomic classification. In this study, we performed a phylogenetic analysis to identify 16S rRNA gene sequence regions that represent the breadth of sequence diversity within these taxa. Using validated sequences, we evaluated 449 universal 16S rRNA gene-targeted bacterial PCR primer pairs for their coverage of these taxa. The results of this analysis provide a practical framework for selection of suitable primer sets for optimal detection of HCB in sequencing surveys.

Segregation of genes from donor strain during the production of recombinant congenic strains.

PubMed

van Zutphen, L F; Den Bieman, M; Lankhorst, A; Demant, P

1991-07-01

Recombinant congenic strains (RCS) constitute a set of inbred strains which are designed to dissect the genetic control of multigenic traits, such as tumour susceptibility or disease resistance. Each RCS contains a small fraction of the genome of a common donor strain, while the majority of genes stem from a common background strain. We tested at two stages of the inbreeding process in 20 RCS, derived from BALB/cHeA and STS/A, to see whether alleles from the STS/A donor strain are distributed over the RCS in a ratio as would theoretically be expected. Four marker genes (Pep-3; Pgm-1; Gpi-1 and Es-3) located at 4 different chromosomes were selected and the allelic distribution was tested after 3-4 and after 12 generations of inbreeding. The data obtained do not significantly deviate from the expected pattern, thus supporting the validity of the concept of RCS.

Diversity and population-genetic properties of copy number variations and multicopy genes in cattle

PubMed Central

Bickhart, Derek M.; Xu, Lingyang; Hutchison, Jana L.; Cole, John B.; Null, Daniel J.; Schroeder, Steven G.; Song, Jiuzhou; Garcia, Jose Fernando; Sonstegard, Tad S.; Van Tassell, Curtis P.; Schnabel, Robert D.; Taylor, Jeremy F.; Lewin, Harris A.; Liu, George E.

2016-01-01

The diversity and population genetics of copy number variation (CNV) in domesticated animals are not well understood. In this study, we analysed 75 genomes of major taurine and indicine cattle breeds (including Angus, Brahman, Gir, Holstein, Jersey, Limousin, Nelore, and Romagnola), sequenced to 11-fold coverage to identify 1,853 non-redundant CNV regions. Supported by high validation rates in array comparative genomic hybridization (CGH) and qPCR experiments, these CNV regions accounted for 3.1% (87.5 Mb) of the cattle reference genome, representing a significant increase over previous estimates of the area of the genome that is copy number variable (∼2%). Further population genetics and evolutionary genomics analyses based on these CNVs revealed the population structures of the cattle taurine and indicine breeds and uncovered potential diversely selected CNVs near important functional genes, including AOX1, ASZ1, GAT, GLYAT, and KRTAP9-1. Additionally, 121 CNV gene regions were found to be either breed specific or differentially variable across breeds, such as RICTOR in dairy breeds and PNPLA3 in beef breeds. In contrast, clusters of the PRP and PAG genes were found to be duplicated in all sequenced animals, suggesting that subfunctionalization, neofunctionalization, or overdominance play roles in diversifying those fertility-related genes. These CNV results provide a new glimpse into the diverse selection histories of cattle breeds and a basis for correlating structural variation with complex traits in the future. PMID:27085184

Identification of host transcriptional networks showing concentration-dependent regulation by HPV16 E6 and E7 proteins in basal cervical squamous epithelial cells

PubMed Central

Smith, Stephen P.; Scarpini, Cinzia G.; Groves, Ian J.; Odle, Richard I.; Coleman, Nicholas

2016-01-01

Development of cervical squamous cell carcinoma requires increased expression of the major high-risk human-papillomavirus (HPV) oncogenes E6 and E7 in basal cervical epithelial cells. We used a systems biology approach to identify host transcriptional networks in such cells and study the concentration-dependent changes produced by HPV16-E6 and -E7 oncoproteins. We investigated sample sets derived from the W12 model of cervical neoplastic progression, for which high quality phenotype/genotype data were available. We defined a gene co-expression matrix containing a small number of highly-connected hub nodes that controlled large numbers of downstream genes (regulons), indicating the scale-free nature of host gene co-expression in W12. We identified a small number of ‘master regulators’ for which downstream effector genes were significantly associated with protein levels of HPV16 E6 (n = 7) or HPV16 E7 (n = 5). We validated our data by depleting E6/E7 in relevant cells and by functional analysis of selected genes in vitro. We conclude that the network of transcriptional interactions in HPV16-infected basal-type cervical epithelium is regulated in a concentration-dependent manner by E6/E7, via a limited number of central master-regulators. These effects are likely to be significant in cervical carcinogenesis, where there is competitive selection of cells with elevated expression of virus oncoproteins. PMID:27457222

A Genome-wide Combinatorial Strategy Dissects Complex Genetic Architecture of Seed Coat Color in Chickpea

PubMed Central

Bajaj, Deepak; Das, Shouvik; Upadhyaya, Hari D.; Ranjan, Rajeev; Badoni, Saurabh; Kumar, Vinod; Tripathi, Shailesh; Gowda, C. L. Laxmipathi; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K.; Parida, Swarup K.

2015-01-01

The study identified 9045 high-quality SNPs employing both genome-wide GBS- and candidate gene-based SNP genotyping assays in 172, including 93 cultivated (desi and kabuli) and 79 wild chickpea accessions. The GWAS in a structured population of 93 sequenced accessions detected 15 major genomic loci exhibiting significant association with seed coat color. Five seed color-associated major genomic loci underlying robust QTLs mapped on a high-density intra-specific genetic linkage map were validated by QTL mapping. The integration of association and QTL mapping with gene haplotype-specific LD mapping and transcript profiling identified novel allelic variants (non-synonymous SNPs) and haplotypes in a MATE secondary transporter gene regulating light/yellow brown and beige seed coat color differentiation in chickpea. The down-regulation and decreased transcript expression of beige seed coat color-associated MATE gene haplotype was correlated with reduced proanthocyanidins accumulation in the mature seed coats of beige than light/yellow brown seed colored desi and kabuli accessions for their coloration/pigmentation. This seed color-regulating MATE gene revealed strong purifying selection pressure primarily in LB/YB seed colored desi and wild Cicer reticulatum accessions compared with the BE seed colored kabuli accessions. The functionally relevant molecular tags identified have potential to decipher the complex transcriptional regulatory gene function of seed coat coloration and for understanding the selective sweep-based seed color trait evolutionary pattern in cultivated and wild accessions during chickpea domestication. The genome-wide integrated approach employed will expedite marker-assisted genetic enhancement for developing cultivars with desirable seed coat color types in chickpea. PMID:26635822

Major carcinogenic pathways identified by gene expression analysis of peritoneal mesotheliomas following chemical treatment in F344 rats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Yongbaek; Thai-Vu Ton; De Angelo, Anthony B.

2006-07-15

This study was performed to characterize the gene expression profile and to identify the major carcinogenic pathways involved in rat peritoneal mesothelioma (RPM) formation following treatment of Fischer 344 rats with o-nitrotoluene (o-NT) or bromochloracetic acid (BCA). Oligo arrays, with over 20,000 target genes, were used to evaluate o-NT- and BCA-induced RPMs, when compared to a non-transformed mesothelial cell line (Fred-PE). Analysis using Ingenuity Pathway Analysis software revealed 169 cancer-related genes that were categorized into binding activity, growth and proliferation, cell cycle progression, apoptosis, and invasion and metastasis. The microarray data were validated by positive correlation with quantitative real-time RT-PCRmore » on 16 selected genes including igf1, tgfb3 and nov. Important carcinogenic pathways involved in RPM formation included insulin-like growth factor 1 (IGF-1), p38 MAPkinase, Wnt/{beta}-catenin and integrin signaling pathways. This study demonstrated that mesotheliomas in rats exposed to o-NT- and BCA were similar to mesotheliomas in humans, at least at the cellular and molecular level.« less

Critical roles of mucin-1 in sensitivity of lung cancer cells to tumor necrosis factor-alpha and dexamethasone.

PubMed

Xu, Menglin; Wang, Xiangdong

2017-08-01

Lung cancer is the leading cause of death from cancer. Mucins are glycoproteins with high molecular weight, responsible for cell growth, differentiation, and signaling, and were proposed to be correlated with gene heterogeneity of lung cancer. Here, we report aberrant expression of mucin genes and tumor necrosis factor receptors in lung adenocarcinoma tissues compared with normal tissues in GEO datasets. Mucin-1 (MUC1) gene was selected and considered as the target gene; furthermore, the expression pattern of adenocarcinomic cells (A549, H1650, or H1299 cells) was validated under the stimulation with tumor necrosis factor-alpha (TNFα) or dexamethasone (DEX), separately. MUC1 gene interference was done to A549 cells to show its role in sensitivity of lung cancer cells to TNFα and DEX. Results of our experiments indicate that MUC1 may regulate the influence of inflammatory mediators in effects of glucocorticoids (GCs), as a regulatory target to improve therapeutics. It shows the potential effect of MUC1 and GCs in lung adenocarcinoma (LADC), which may help in LADC treatment in the future.

Identification and Evaluation of Reliable Reference Genes for Quantitative Real-Time PCR Analysis in Tea Plant (Camellia sinensis (L.) O. Kuntze)

PubMed Central

Hao, Xinyuan; Horvath, David P.; Chao, Wun S.; Yang, Yajun; Wang, Xinchao; Xiao, Bin

2014-01-01

Reliable reference selection for the accurate quantification of gene expression under various experimental conditions is a crucial step in qRT-PCR normalization. To date, only a few housekeeping genes have been identified and used as reference genes in tea plant. The validity of those reference genes are not clear since their expression stabilities have not been rigorously examined. To identify more appropriate reference genes for qRT-PCR studies on tea plant, we examined the expression stability of 11 candidate reference genes from three different sources: the orthologs of Arabidopsis traditional reference genes and stably expressed genes identified from whole-genome GeneChip studies, together with three housekeeping gene commonly used in tea plant research. We evaluated the transcript levels of these genes in 94 experimental samples. The expression stabilities of these 11 genes were ranked using four different computation programs including geNorm, Normfinder, BestKeeper, and the comparative ∆CT method. Results showed that the three commonly used housekeeping genes of CsTUBULIN1, CsACINT1 and Cs18S rRNA1 together with CsUBQ1 were the most unstable genes in all sample ranking order. However, CsPTB1, CsEF1, CsSAND1, CsCLATHRIN1 and CsUBC1 were the top five appropriate reference genes for qRT-PCR analysis in complex experimental conditions. PMID:25474086

Validation of reference genes for quantifying changes in gene expression in virus-infected tobacco.

PubMed

Baek, Eseul; Yoon, Ju-Yeon; Palukaitis, Peter

2017-10-01

To facilitate quantification of gene expression changes in virus-infected tobacco plants, eight housekeeping genes were evaluated for their stability of expression during infection by one of three systemically-infecting viruses (cucumber mosaic virus, potato virus X, potato virus Y) or a hypersensitive-response-inducing virus (tobacco mosaic virus; TMV) limited to the inoculated leaf. Five reference-gene validation programs were used to establish the order of the most stable genes for the systemically-infecting viruses as ribosomal protein L25 > β-Tubulin > Actin, and the least stable genes Ubiquitin-conjugating enzyme (UCE) < PP2A < GAPDH. For local infection by TMV, the most stable genes were EF1α > Cysteine protease > Actin, and the least stable genes were GAPDH < PP2A < UCE. Using two of the most stable and the two least stable validated reference genes, three defense responsive genes were examined to compare their relative changes in gene expression caused by each virus. Copyright © 2017 Elsevier Inc. All rights reserved.

Host genetics of response to porcine reproductive and respiratory syndrome in nursery pigs.

PubMed

Dekkers, Jack; Rowland, Raymond R R; Lunney, Joan K; Plastow, Graham

2017-09-01

PRRS is the most costly disease in the US pig industry. While vaccination, biosecurity and eradication effort have had some success, the variability and infectiousness of PRRS virus strains have hampered the effectiveness of these measures. We propose the use of genetic selection of pigs as an additional and complementary effort. Several studies have shown that host response to PRRS infection has a sizeable genetic component and recent advances in genomics provide opportunities to capitalize on these genetic differences and improve our understanding of host response to PRRS. While work is also ongoing to understand the genetic basis of host response to reproductive PRRS, the focus of this review is on research conducted on host response to PRRS in the nursery and grow-finish phase as part of the PRRS Host Genetics Consortium. Using experimental infection of large numbers of commercial nursery pigs, combined with deep phenotyping and genomics, this research has identified a major gene that is associated with host response to PRRS. Further functional genomics work identified the GBP5 gene as harboring the putative causative mutation. GBP5 is associated with innate immune response. Subsequent work has validated the effect of this genomic region on host response to a second PRRSV strain and to PRRS vaccination and co-infection of nursery pigs with PRRSV and PCV2b. A genetic marker near GBP5 is available to the industry for use in selection. Genetic differences in host response beyond GBP5 appear to be highly polygenic, i.e. controlled by many genes across the genome, each with a small effect. Such effects can by capitalized on in a selection program using genomic prediction on large numbers of genetic markers across the genome. Additional work has also identified the genetic basis of antibody response to PRRS, which could lead to the use of vaccine response as an indicator trait to select for host response to PRRS. Other genomic analyses, including gene expression analyses, have identified genes and modules of genes that are associated with differences in host response to PRRS and can be used to further understand and utilize differences in host response. Together, these results demonstrate that genetic selection can be an additional and complementary tool to combat PRRS in the swine industry. Copyright © 2017 Elsevier B.V. All rights reserved.

The transcriptome of corona radiata cells from individual MІІ oocytes that after ICSI developed to embryos selected for transfer: PCOS women compared to healthy women.

PubMed

Wissing, Marie Louise; Sonne, Si Brask; Westergaard, David; Nguyen, Kho do; Belling, Kirstine; Høst, Thomas; Mikkelsen, Anne Lis

2014-11-29

Corona radiata cells (CRCs) refer to the fraction of cumulus cells just adjacent to the oocyte. The CRCs are closely connected to the oocyte throughout maturation and their gene expression profiles might reflect oocyte quality. Polycystic ovary syndrome (PCOS) is a common cause of infertility. It is controversial whether PCOS associate with diminished oocyte quality. The purpose of this study was to compare individual human CRC samples between PCOS patients and controls. All patients were stimulated by the long gonadotropin-releasing hormone (GnRH) agonist protocol. The CRC samples originated from individual oocytes developing into embryos selected for transfer. CRCs were isolated in a two-step denudation procedure, separating outer cumulus cells from the inner CRCs. Extracted RNA was amplified and transcriptome profiling was performed with Human Agilent® arrays. The transcriptomes of CRCs showed no individual genes with significant differential expression between PCOS and controls, but gene set enrichment analysis identified several cell cycle- and DNA replication pathways overexpressed in PCOS CRCs (FDR < 0.05). Five of the genes contributing to the up-regulated cell cycle pathways in the PCOS CRCs were selected for qRT-PCR validation in ten PCOS and ten control CRC samples. qRT-PCR confirmed significant up-regulation in PCOS CRCs of cell cycle progression genes HIST1H4C (FC = 2.7), UBE2C (FC = 2.6) and cell cycle related transcription factor E2F4 (FC = 2.5). The overexpression of cell cycle-related genes and cell cycle pathways in PCOS CRCs could indicate a disturbed or delayed final maturation and differentiation of the CRCs in response to the human chorionic gonadotropin (hCG) surge. However, this had no effect on the in vitro development of the corresponding embryos. Future studies are needed to clarify whether the up-regulated cell cycle pathways in PCOS CRCs have any clinical implications.

Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing.

PubMed

Liang, Chen; Sun, Jingchun; Tao, Cui

2015-01-01

There remain significant difficulties selecting probable candidate drugs from existing databases. We describe an ontology-oriented approach to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. We also report a case study in which we attempted to explore candidate drugs effective for bipolar disorder and epilepsy. We constructed an ontology incorporating knowledge between the two diseases and performed semantic reasoning tasks with the ontology. The results suggested 48 candidate drugs that hold promise for further breakthrough. The evaluation demonstrated the validity our approach. Our approach prioritizes the candidate drugs that have potential associations among genes, phenotypes and symptoms, and thus facilitates the data integration and drug repurposing in psychiatric disorders.

Identification and Comparative Study of Chemosensory Genes Related to Host Selection by Legs Transcriptome Analysis in the Tea Geometrid Ectropis obliqua

PubMed Central

Bian, Lei; Cai, Xiao-Ming; Luo, Zong-Xiu; Zhang, Yong-Jun; Chen, Zong-Mao

2016-01-01

Host selection by female moths is fundamental to the survival of their larvae. Detecting and perceiving the non-volatile chemicals of the plant surface involved in gustatory detection determine the host preference. In many lepidopteran species, tarsal chemosensilla are sensitive to non-volatile chemicals and responsible for taste detection. The tea geometrid Ectropis obliqua is one devastating chewing pest selectively feeding on limited plants, requiring the specialized sensors to forage certain host for oviposition. In present study, we revealed the distribution of chemosensilla in the ventral side of female fifth tarsomere in E. obliqua. To investigate its molecular mechanism of gustatory perception, we performed HiSeq 2500 sequencing of the male- and female- legs transcriptome and identified 24 candidate odorant binding proteins (OBPs), 21 chemosensory proteins (CSPs), 2 sensory neuron membrane proteins (SNMPs), 3 gustatory receptors (GRs) and 4 odorant receptors (ORs). Several leg-specific or enriched chemosensory genes were screened by tissue expression analysis, and clustered with functionally validated genes from other moths, suggesting the potential involvement in taste sensation or other physiological processes. The RPKM value analysis revealed that 9 EoblOBPs showed sex discrepancy in the leg expression, 8 being up-regulated in female and only 1 being over expressed in male. These female-biased EoblOBPs indicated an ecological adaption related with host-seeking and oviposition behaviors. Our work will provide basic knowledge for further studies on the molecular mechanism of gustatory perception, and enlighten a host-selection-based control strategy of insect pests. PMID:26930056

MeSH key terms for validation and annotation of gene expression clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rechtsteiner, A.; Rocha, L. M.

2004-01-01

Integration of different sources of information is a great challenge for the analysis of gene expression data, and for the field of Functional Genomics in general. As the availability of numerical data from high-throughput methods increases, so does the need for technologies that assist in the validation and evaluation of the biological significance of results extracted from these data. In mRNA assaying with microarrays, for example, numerical analysis often attempts to identify clusters of co-expressed genes. The important task to find the biological significance of the results and validate them has so far mostly fallen to the biological expert whomore » had to perform this task manually. One of the most promising avenues to develop automated and integrative technology for such tasks lies in the application of modern Information Retrieval (IR) and Knowledge Management (KM) algorithms to databases with biomedical publications and data. Examples of databases available for the field are bibliographic databases c ntaining scientific publications (e.g. MEDLINE/PUBMED), databases containing sequence data (e.g. GenBank) and databases of semantic annotations (e.g. the Gene Ontology Consortium and Medical Subject Headings (MeSH)). We present here an approach that uses the MeSH terms and their concept hierarchies to validate and obtain functional information for gene expression clusters. The controlled and hierarchical MeSH vocabulary is used by the National Library of Medicine (NLM) to index all the articles cited in MEDLINE. Such indexing with a controlled vocabulary eliminates some of the ambiguity due to polysemy (terms that have multiple meanings) and synonymy (multiple terms have similar meaning) that would be encountered if terms would be extracted directly from the articles due to differing article contexts or author preferences and background. Further, the hierarchical organization of the MeSH terms can illustrate the conceptuallfunctional relationships of genes associated with MeSH terms. MeSH terms can be associated with genes through co-occurrence of these in MEDLINE citations, i.e. the genes occur in titles or abstracts and the MeSH terms are assigned by experts. To identify MeSH terms associated with a group of genes we used the tool MESHGENE developed at the Information Dynamics Lab at HP Labs (http://www-idl.hpl.hp.com/meshgene/). When presented with a list of human genes, MESHGENE uses some sophisticated techniques to search for these gene symbols in the titles and abstracts of all MEDLINE citations. MeSH terms and the number of co-occurrences can be retrieved. Gene symbols that are aliases of each other are pooled from several databases. This addresses the problem of synonymy, the fact that several symbols can refer to the same gene. MESHGENE employs some sophisticated algorithms that disregards symbols that are likely to be acronyms for other concepts than a gene. This addresses the problem of polysemy, i.e. possible multiple meanings of a gene symbol. We applied our approach to gene expression data from herpes virus infected human fibroblast cells. The data contains 12 time-points, between 1/2 hrs and 48 hrs after infection. Singular Value Decomposition was used to identify the dominant modes of expression. 75% of the variance in the expression data was captured by the first two modes, the first exhibiting a monotonly increasing expression pattern and the second a more transient pattern. Projection of the gene expression vectors onto this first two modes identified 3 statistically significant clusters of co-expressed genes. 500 genes from cluster 1 and 300 genes from clusters 2 and 3 each were uploaded to MESHGENE and the MeSH terms and co-occurrence values were retrieved. MeSH terms were also obtained for 5 groups of randomly selected genes with similar numbers of genes. The log was taken of the co-occurrence values and for each MeSH term these log co-occurrence values were summed for each group over the genes in that group. A matrix with 8 columns for the 8 groups of genes and with 14,000 rows with the MeSH terms was obtained. To analyze this association matrix we used a Latent Semantic Analysis (LSA) approach. We applied SVD to this gene-group vs. MeSH term association matrix. The first 2 modes that capture most of the variation (and therefore most times also information) in the association matrix were highly associated with MeSH terms that occurred uniquely or disproportionally in the 3 gene clusters. MeSH terms highly associated with the 5 groups of randomly selected genes were associated with the lower modes. These modes seem to just capture 'noise' in the association matrix. This result by itself is of great interest for gene expression analysis. We were able to show that the 3 clusters of genes not only separated in 'expression space' but also in the MeSH term space with which they are associated through the literature.« less

Active oligonucleotides incorporating alkylating an agent as potential sequence- and base selective modifier of gene expression.

PubMed

Sasaki, S

2001-04-01

A number of cross-linking (alkylating) agents have been developed and incorporated into the oligonulceotides for sequence selective control of gene expression. Recently, potential application of such active oligonucleotides has been expanding from use for improvement of inhibition efficiency to new biotechnology that may enable chemical alteration of genetic information. These interests in active oligonucleotides have encouraged the generation of new cross-linking agents that exhibit high efficiency for application of either in vitro or in vivo. This mini review summarizes structures of alkylating agents, in particular, a new basic skeleton for cross-linking, a 2'-deoxyribose derivative of 2-amino-6-vinylpurine that has been recently developed by the author's group. The 2-amino-6-vinylpurine has been shown to form a complex with cytidine under acidic conditions, and brings the vinyl and the amino reactive groups into proximity to achieve efficient alkylation. A new strategy was designed so that the reactivity of 2-amino-6-vinylpurine can be induced from the corresponding phenylsulfoxide derivative within a duplex with the complementary strand. The validity of the new strategy has been proven by achievement of cytidine-selective cross-linking with remarkably efficiency.

Molecular cloning of Brevundimonas diminuta for efficacy assessment of reverse osmosis devices.

PubMed

Donofrio, Robert; Saha, Ratul; Bestervelt, Lori; Bagley, Susan

2012-06-01

Brevundimonas diminuta is the test organism specified in the United States Environmental Protection Agency's (USEPA) reverse osmosis (RO) treatment device verification protocol. As non-selective growth medium is employed, enumeration of B. diminuta may be impaired due to interference by indigenous heterotrophic bacteria. Thus the microbial removal capability of the filtration system may be incorrectly assessed. As these treatment devices are used in emergency situations, the health of the public could be compromised. The objective of this study was to develop selective approaches for enumerating viable B. diminuta in test water. Two molecular approaches were investigated: expression of a kanamycin resistance gene and expression of a fluorescent protein gene. The USEPA protocol specifies a 0.3 μm cell size, so the expression of the selective markers were assessed following growth on media designed to induce this small cell diameter. The kan(R) strain was demonstrated to be equivalent to the wild type in cell dimension and survival following exposure to the test water. The kan(R) strain showed equivalent performance to the wild type in the RO protocol indicating that it is a viable alternative surrogate. By utilizing this strain, a more accurate validation of the RO system can be achieved.

Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages.

PubMed

Reddy, Anupama; Growney, Joseph D; Wilson, Nick S; Emery, Caroline M; Johnson, Jennifer A; Ward, Rebecca; Monaco, Kelli A; Korn, Joshua; Monahan, John E; Stump, Mark D; Mapa, Felipa A; Wilson, Christopher J; Steiger, Janine; Ledell, Jebediah; Rickles, Richard J; Myer, Vic E; Ettenberg, Seth A; Schlegel, Robert; Sellers, William R; Huet, Heather A; Lehár, Joseph

2015-01-01

Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response.

Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages

PubMed Central

Reddy, Anupama; Growney, Joseph D.; Wilson, Nick S.; Emery, Caroline M.; Johnson, Jennifer A.; Ward, Rebecca; Monaco, Kelli A.; Korn, Joshua; Monahan, John E.; Stump, Mark D.; Mapa, Felipa A.; Wilson, Christopher J.; Steiger, Janine; Ledell, Jebediah; Rickles, Richard J.; Myer, Vic E.; Ettenberg, Seth A.; Schlegel, Robert; Sellers, William R.

2015-01-01

Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response. PMID:26378449

Differential Gene Expression in Gonadotropin-Releasing Hormone Neurons of Male and Metestrous Female Mice.

PubMed

Vastagh, Csaba; Rodolosse, Annie; Solymosi, Norbert; Farkas, Imre; Auer, Herbert; Sárvári, Miklós; Liposits, Zsolt

2015-01-01

Gonadotropin-releasing hormone (GnRH) neurons play a pivotal role in the regulation of the hypothalamic-pituitary gonadal axis in a sex-specific manner. We hypothesized that the differences seen in reproductive functions of males and females are associated with a sexually dimorphic gene expression profile of GnRH neurons. We compared the transcriptome of GnRH neurons obtained from intact metestrous female and male GnRH-green fluorescent protein transgenic mice. About 1,500 individual GnRH neurons from each sex were sampled with laser capture microdissection followed by whole-transcriptome amplification for gene expression profiling. Under stringent selection criteria (fold change >1.6, adjusted p value 0.01), Affymetrix Mouse Genome 430 PM array analysis identified 543 differentially expressed genes. Sexual dimorphism was most apparent in gene clusters associated with synaptic communication, signal transduction, cell adhesion, vesicular transport and cell metabolism. To validate microarray results, 57 genes were selected, and 91% of their differential expression was confirmed by real-time PCR. Similarly, 88% of microarray results were confirmed with PCR from independent samples obtained by patch pipette harvesting and pooling of 30 GnRH neurons from each sex. We found significant differences in the expression of genes involved in vesicle priming and docking (Syt1, Cplx1), GABAergic (Gabra3, Gabrb3, Gabrg2) and glutamatergic (Gria1, Grin1, Slc17a6) neurotransmission, peptide signaling (Sstr3, Npr2, Cxcr4) and the regulation of intracellular ion homeostasis (Cacna1, Cacnb1, Cacng5, Kcnq2, Kcnc1). The striking sexual dimorphism of the GnRH neuron transcriptome we report here contributes to a better understanding of the differences in cellular mechanisms of GnRH neurons in the two sexes. © 2015 S. Karger AG, Basel.

Exploratory Investigation of Bacteroides fragilis Transcriptional Response during In vitro Exposure to Subinhibitory Concentration of Metronidazole.

PubMed

de Freitas, Michele C R; Resende, Juliana A; Ferreira-Machado, Alessandra B; Saji, Guadalupe D R Q; de Vasconcelos, Ana T R; da Silva, Vânia L; Nicolás, Marisa F; Diniz, Cláudio G

2016-01-01

Bacteroides fragilis , member from commensal gut microbiota, is an important pathogen associated to endogenous infections and metronidazole remains a valuable antibiotic for the treatment of these infections, although bacterial resistance is widely reported. Considering the need of a better understanding on the global mechanisms by which B. fragilis survive upon metronidazole exposure, we performed a RNA-seq transcriptomic approach with validation of gene expression results by qPCR. Bacteria strains were selected after in vitro subcultures with subinhibitory concentration (SIC) of the drug. From a wild type B. fragilis ATCC 43859 four derivative strains were selected: first and fourth subcultures under metronidazole exposure and first and fourth subcultures after drug removal. According to global gene expression analysis, 2,146 protein coding genes were identified, of which a total of 1,618 (77%) were assigned to a Gene Ontology term (GO), indicating that most known cellular functions were taken. Among these 2,146 protein coding genes, 377 were shared among all strains, suggesting that they are critical for B. fragilis survival. In order to identify distinct expression patterns, we also performed a K-means clustering analysis set to 15 groups. This analysis allowed us to detect the major activated or repressed genes encoding for enzymes which act in several metabolic pathways involved in metronidazole response such as drug activation, defense mechanisms against superoxide ions, high expression level of multidrug efflux pumps, and DNA repair. The strains collected after metronidazole removal were functionally more similar to those cultured under drug pressure, reinforcing that drug-exposure lead to drastic persistent changes in the B. fragilis gene expression patterns. These results may help to elucidate B. fragilis response during metronidazole exposure, mainly at SIC, contributing with information about bacterial survival strategies under stress conditions in their environment.

Transcriptome database resource and gene expression atlas for the rose

PubMed Central

2012-01-01

Background For centuries roses have been selected based on a number of traits. Little information exists on the genetic and molecular basis that contributes to these traits, mainly because information on expressed genes for this economically important ornamental plant is scarce. Results Here, we used a combination of Illumina and 454 sequencing technologies to generate information on Rosa sp. transcripts using RNA from various tissues and in response to biotic and abiotic stresses. A total of 80714 transcript clusters were identified and 76611 peptides have been predicted among which 20997 have been clustered into 13900 protein families. BLASTp hits in closely related Rosaceae species revealed that about half of the predicted peptides in the strawberry and peach genomes have orthologs in Rosa dataset. Digital expression was obtained using RNA samples from organs at different development stages and under different stress conditions. qPCR validated the digital expression data for a selection of 23 genes with high or low expression levels. Comparative gene expression analyses between the different tissues and organs allowed the identification of clusters that are highly enriched in given tissues or under particular conditions, demonstrating the usefulness of the digital gene expression analysis. A web interface ROSAseq was created that allows data interrogation by BLAST, subsequent analysis of DNA clusters and access to thorough transcript annotation including best BLAST matches on Fragaria vesca, Prunus persica and Arabidopsis. The rose peptides dataset was used to create the ROSAcyc resource pathway database that allows access to the putative genes and enzymatic pathways. Conclusions The study provides useful information on Rosa expressed genes, with thorough annotation and an overview of expression patterns for transcripts with good accuracy. PMID:23164410

Comparative Transcriptome Analysis Reveals the Genetic Basis of Skin Color Variation in Common Carp

PubMed Central

Jiang, Yanliang; Zhang, Songhao; Xu, Jian; Feng, Jianxin; Mahboob, Shahid; Al-Ghanim, Khalid A.; Sun, Xiaowen; Xu, Peng

2014-01-01

Background The common carp is an important aquaculture species that is widely distributed across the world. During the long history of carp domestication, numerous carp strains with diverse skin colors have been established. Skin color is used as a visual criterion to determine the market value of carp. However, the genetic basis of common carp skin color has not been extensively studied. Methodology/Principal Findings In this study, we performed Illumina sequencing on two common carp strains: the reddish Xingguo red carp and the brownish-black Yellow River carp. A total of 435,348,868 reads were generated, resulting in 198,781 assembled contigs that were used as reference sequences. Comparisons of skin transcriptome files revealed 2,012 unigenes with significantly different expression in the two common carp strains, including 874 genes that were up-regulated in Xingguo red carp and 1,138 genes that were up-regulated in Yellow River carp. The expression patterns of 20 randomly selected differentially expressed genes were validated using quantitative RT-PCR. Gene pathway analysis of the differentially expressed genes indicated that melanin biosynthesis, along with the Wnt and MAPK signaling pathways, is highly likely to affect the skin pigmentation process. Several key genes involved in the skin pigmentation process, including TYRP1, SILV, ASIP and xCT, showed significant differences in their expression patterns between the two strains. Conclusions In this study, we conducted a comparative transcriptome analysis of Xingguo red carp and Yellow River carp skins, and we detected key genes involved in the common carp skin pigmentation process. We propose that common carp skin pigmentation depends upon at least three pathways. Understanding fish skin color genetics will facilitate future molecular selection of the fish skin colors with high market values. PMID:25255374

Comparative transcriptome analysis reveals the genetic basis of skin color variation in common carp.

PubMed

Jiang, Yanliang; Zhang, Songhao; Xu, Jian; Feng, Jianxin; Mahboob, Shahid; Al-Ghanim, Khalid A; Sun, Xiaowen; Xu, Peng

2014-01-01

The common carp is an important aquaculture species that is widely distributed across the world. During the long history of carp domestication, numerous carp strains with diverse skin colors have been established. Skin color is used as a visual criterion to determine the market value of carp. However, the genetic basis of common carp skin color has not been extensively studied. In this study, we performed Illumina sequencing on two common carp strains: the reddish Xingguo red carp and the brownish-black Yellow River carp. A total of 435,348,868 reads were generated, resulting in 198,781 assembled contigs that were used as reference sequences. Comparisons of skin transcriptome files revealed 2,012 unigenes with significantly different expression in the two common carp strains, including 874 genes that were up-regulated in Xingguo red carp and 1,138 genes that were up-regulated in Yellow River carp. The expression patterns of 20 randomly selected differentially expressed genes were validated using quantitative RT-PCR. Gene pathway analysis of the differentially expressed genes indicated that melanin biosynthesis, along with the Wnt and MAPK signaling pathways, is highly likely to affect the skin pigmentation process. Several key genes involved in the skin pigmentation process, including TYRP1, SILV, ASIP and xCT, showed significant differences in their expression patterns between the two strains. In this study, we conducted a comparative transcriptome analysis of Xingguo red carp and Yellow River carp skins, and we detected key genes involved in the common carp skin pigmentation process. We propose that common carp skin pigmentation depends upon at least three pathways. Understanding fish skin color genetics will facilitate future molecular selection of the fish skin colors with high market values.

Selection and Validation of Reference Genes for qRT-PCR Expression Analysis of Candidate Genes Involved in Olfactory Communication in the Butterfly Bicyclus anynana

PubMed Central

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M.

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes. PMID:25793735

Selection and validation of reference genes for qRT-PCR expression analysis of candidate genes involved in olfactory communication in the butterfly Bicyclus anynana.

PubMed

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes.

Comprehensive interactome of Otx2 in the adult mouse neural retina.

PubMed

Fant, Bruno; Samuel, Alexander; Audebert, Stéphane; Couzon, Agnès; El Nagar, Salsabiel; Billon, Nathalie; Lamonerie, Thomas

2015-11-01

The Otx2 homeodomain transcription factor exerts multiple functions in specific developmental contexts, probably through the regulation of different sets of genes. Protein partners of Otx2 have been shown to modulate its activity. Therefore, the Otx2 interactome may play a key role in selecting a precise target-gene repertoire, hence determining its function in a specific tissue. To address the nature of Otx2 interactome, we generated a new recombinant Otx2(CTAP-tag) mouse line, designed for protein complexes purification. We validated this mouse line by establishing the Otx2 interactome in the adult neural retina. In this tissue, Otx2 is thought to have overlapping function with its paralog Crx. Our analysis revealed that, in contrary to Crx, Otx2 did not develop interactions with proteins that are known to regulate phototransduction genes but showed specific partnership with factors associated with retinal development. The relationship between Otx2 and Crx in the neural retina should therefore be considered as complementarity rather than redundancy. Furthermore, study of the Otx2 interactome revealed strong associations with RNA processing and translation machineries, suggesting unexpected roles for Otx2 in the regulation of selected target genes all along the transcription/translation pathway. The Otx2(CTAP-tag) line, therefore, appears suitable for a systematic approach to Otx2 protein-protein interactions. genesis 53:685-694, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Resistance-breaking population of Meloidogyne incognita utilizes plant peroxidase to scavenge reactive oxygen species, thereby promoting parasitism on tomato carrying Mi-1 gene.

PubMed

Guan, Tinglong; Shen, Jinhua; Fa, Yang; Su, Yishi; Wang, Xuan; Li, Hongmei

2017-01-01

Resistance conferred by the Mi-1 gene from Solanum peruvianum is effective and widely used for controlling root-knot nematodes (RKNs, Meloidogyne spp.). However, breakdown of resistance by RKNs seriously threatens the durable application of the resistance resource. Here, a resistance-breaking population of M. incognita was selected from an avirulent population by continuously inoculating on Mi-1-carrying tomato. Histological observations showed the resistance-breaking population would not induce hypersensitive response (HR) when infecting Mi-1-carrying tomato, while avirulent population did. A total of 308 differentially expressed genes (DEGs) were identified from Mi-1-carrying tomato upon infection with resistance-breaking versus avirulent populations by RNA-seq. The expression patterns of 23 selected DEGs were validated by quantitative real-time PCR (qRT-PCR). Subsequently, seven out of nine highly up-regulated DEGs were successfully knocked down in Mi-1-carrying tomato by tobacco rattle virus (TRV) mediated RNAi. The TRV line targeting a peroxidase gene showed a much higher magnitude of reactive oxygen species (ROS) and distinct reduction of pathogenicity upon infection of the resistance-breaking population compared with that of TRV::gfp line. Our results suggested that plant peroxidase might be exploited by resistance-breaking population of M. incognita to scavenge ROS, so as to overcome Mi-1-mediated resistance. Copyright © 2016 Elsevier Inc. All rights reserved.

Multimarker analysis suggests the involvement of BDNF signaling and microRNA biosynthesis in suicidal behavior.

PubMed

Pulay, Attila J; Réthelyi, János M

2016-09-01

Despite moderate heritability estimates the genetics of suicidal behavior remains unclear, genome-wide association and candidate gene studies focusing on single nucleotide associations reported inconsistent findings. Our study explored biologically informed, multimarker candidate gene associations with suicidal behavior in mood disorders. We analyzed the GAIN Whole Genome Association Study of Bipolar Disorder version 3 (n = 999, suicidal n = 358) and the GAIN Major Depression: Stage 1 Genomewide Association in Population-Based Samples (n = 1,753, suicidal n = 245) datasets. Suicidal behavior was defined as severe suicidal ideation or attempt. Candidate genes were selected based on literature search (Geneset1, n = 35), gene expression data of microRNA genes, (Geneset2, n = 68) and their target genes (Geneset3, n = 11,259). Quality control, dosage analyses were carried out with PLINK. Gene-based associations of Geneset1 were analyzed with KGG. Polygenic profile scores of suicidal behavior were computed in the major depression dataset both with PRSice and LDpred and validated in the bipolar disorder data. Several nominally significant gene-based associations were detected, but only DICER1 associated with suicidal behavior in both samples, while only the associations of NTRK2 in the depression sample reached family wise and experiment wise significance. Polygenic profile scores negatively predicted suicidal behavior in the bipolar sample for only Geneset2, with the strongest prediction by PRSice at Pt  < 0.03 (Nagelkerke R(2)  = 0.01, P < 0.007). Gene-based association results confirmed the potential involvement of the BDNF-NTRK2-CREB pathway in the pathogenesis of suicide and the cross-disorder association of DICER1. Polygenic risk prediction of the selected miRNA genes indicates that the miRNA system may play a mediating role, but with considerable pleiotropy. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Large-scale mapping of mutations affecting zebrafish development.

PubMed

Geisler, Robert; Rauch, Gerd-Jörg; Geiger-Rudolph, Silke; Albrecht, Andrea; van Bebber, Frauke; Berger, Andrea; Busch-Nentwich, Elisabeth; Dahm, Ralf; Dekens, Marcus P S; Dooley, Christopher; Elli, Alexandra F; Gehring, Ines; Geiger, Horst; Geisler, Maria; Glaser, Stefanie; Holley, Scott; Huber, Matthias; Kerr, Andy; Kirn, Anette; Knirsch, Martina; Konantz, Martina; Küchler, Axel M; Maderspacher, Florian; Neuhauss, Stephan C; Nicolson, Teresa; Ober, Elke A; Praeg, Elke; Ray, Russell; Rentzsch, Brit; Rick, Jens M; Rief, Eva; Schauerte, Heike E; Schepp, Carsten P; Schönberger, Ulrike; Schonthaler, Helia B; Seiler, Christoph; Sidi, Samuel; Söllner, Christian; Wehner, Anja; Weiler, Christian; Nüsslein-Volhard, Christiane

2007-01-09

Large-scale mutagenesis screens in the zebrafish employing the mutagen ENU have isolated several hundred mutant loci that represent putative developmental control genes. In order to realize the potential of such screens, systematic genetic mapping of the mutations is necessary. Here we report on a large-scale effort to map the mutations generated in mutagenesis screening at the Max Planck Institute for Developmental Biology by genome scanning with microsatellite markers. We have selected a set of microsatellite markers and developed methods and scoring criteria suitable for efficient, high-throughput genome scanning. We have used these methods to successfully obtain a rough map position for 319 mutant loci from the Tübingen I mutagenesis screen and subsequent screening of the mutant collection. For 277 of these the corresponding gene is not yet identified. Mapping was successful for 80 % of the tested loci. By comparing 21 mutation and gene positions of cloned mutations we have validated the correctness of our linkage group assignments and estimated the standard error of our map positions to be approximately 6 cM. By obtaining rough map positions for over 300 zebrafish loci with developmental phenotypes, we have generated a dataset that will be useful not only for cloning of the affected genes, but also to suggest allelism of mutations with similar phenotypes that will be identified in future screens. Furthermore this work validates the usefulness of our methodology for rapid, systematic and inexpensive microsatellite mapping of zebrafish mutations.

Alkylation sensitivity screens reveal a conserved cross-species functionome

PubMed Central

Svilar, David; Dyavaiah, Madhu; Brown, Ashley R.; Tang, Jiang-bo; Li, Jianfeng; McDonald, Peter R.; Shun, Tong Ying; Braganza, Andrea; Wang, Xiao-hong; Maniar, Salony; St Croix, Claudette M.; Lazo, John S.; Pollack, Ian F.; Begley, Thomas J.; Sobol, Robert W.

2013-01-01

To identify genes that contribute to chemotherapy resistance in glioblastoma, we conducted a synthetic lethal screen in a chemotherapy-resistant glioblastoma derived cell line with the clinical alkylator temozolomide (TMZ) and an siRNA library tailored towards “druggable” targets. Select DNA repair genes in the screen were validated independently, confirming the DNA glycosylases UNG and MYH as well as MPG to be involved in the response to high dose TMZ. The involvement of UNG and MYH is likely the result of a TMZ-induced burst of reactive oxygen species. We then compared the human TMZ sensitizing genes identified in our screen with those previously identified from alkylator screens conducted in E. coli and S. cerevisiae. The conserved biological processes across all three species composes an Alkylation Functionome that includes many novel proteins not previously thought to impact alkylator resistance. This high-throughput screen, validation and cross-species analysis was then followed by a mechanistic analysis of two essential nodes: base excision repair (BER) DNA glycosylases (UNG, human and mag1, S. cerevisiae) and protein modification systems, including UBE3B and ICMT in human cells or pby1, lip22, stp22 and aim22 in S. cerevisiae. The conserved processes of BER and protein modification were dual targeted and yielded additive sensitization to alkylators in S. cerevisiae. In contrast, dual targeting of BER and protein modification genes in human cells did not increase sensitivity, suggesting an epistatic relationship. Importantly, these studies provide potential new targets to overcome alkylating agent resistance. PMID:23038810

ICG: a wiki-driven knowledgebase of internal control genes for RT-qPCR normalization.

PubMed

Sang, Jian; Wang, Zhennan; Li, Man; Cao, Jiabao; Niu, Guangyi; Xia, Lin; Zou, Dong; Wang, Fan; Xu, Xingjian; Han, Xiaojiao; Fan, Jinqi; Yang, Ye; Zuo, Wanzhu; Zhang, Yang; Zhao, Wenming; Bao, Yiming; Xiao, Jingfa; Hu, Songnian; Hao, Lili; Zhang, Zhang

2018-01-04

Real-time quantitative PCR (RT-qPCR) has become a widely used method for accurate expression profiling of targeted mRNA and ncRNA. Selection of appropriate internal control genes for RT-qPCR normalization is an elementary prerequisite for reliable expression measurement. Here, we present ICG (http://icg.big.ac.cn), a wiki-driven knowledgebase for community curation of experimentally validated internal control genes as well as their associated experimental conditions. Unlike extant related databases that focus on qPCR primers in model organisms (mainly human and mouse), ICG features harnessing collective intelligence in community integration of internal control genes for a variety of species. Specifically, it integrates a comprehensive collection of more than 750 internal control genes for 73 animals, 115 plants, 12 fungi and 9 bacteria, and incorporates detailed information on recommended application scenarios corresponding to specific experimental conditions, which, collectively, are of great help for researchers to adopt appropriate internal control genes for their own experiments. Taken together, ICG serves as a publicly editable and open-content encyclopaedia of internal control genes and accordingly bears broad utility for reliable RT-qPCR normalization and gene expression characterization in both model and non-model organisms. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of genes differentially expressed in ectomycorrhizal roots during the Pinus pinaster-Laccaria bicolor interaction.

PubMed

Flores-Monterroso, Aranzazu; Canales, Javier; de la Torre, Fernando; Ávila, Concepción; Cánovas, Francisco M

2013-06-01

Ectomycorrhizal associations are of major ecological importance in temperate and boreal forests. The development of a functional ectomycorrhiza requires many genetic and biochemical changes. In this study, suppressive subtraction hybridization was used to identify differentially expressed genes in the roots of maritime pine (Pinus pinaster Aiton) inoculated with Laccaria bicolor, a mycorrhizal fungus. A total number of 200 unigenes were identified as being differentially regulated in maritime pine roots during the development of mycorrhiza. These unigenes were classified into 10 categories according to the function of their homologues in the GenBank database. Approximately, 40 % of the differentially expressed transcripts were genes that coded for unknown proteins in the databases or that had no homology to known genes. A group of these differentially expressed genes was selected to validate the results using quantitative real-time PCR. The transcript levels of the representative genes were compared between the non-inoculated and inoculated plants at 1, 5, 15 and 30 days after inoculation. The observed expression patterns indicate (1) changes in the composition of the wall cell, (2) tight regulation of defence genes during the development of mycorrhiza and (3) changes in carbon and nitrogen metabolism. Ammonium excess or deficiency dramatically affected the stability of ectomycorrhiza and altered gene expression in maritime pine roots.

Global monitoring of autumn gene expression within and among phenotypically divergent populations of Sitka spruce (Picea sitchensis).

PubMed

Holliday, Jason A; Ralph, Steven G; White, Richard; Bohlmann, Jörg; Aitken, Sally N

2008-01-01

Cold acclimation in conifers is a complex process, the timing and extent of which reflects local adaptation and varies widely along latitudinal gradients for many temperate and boreal tree species. Despite their ecological and economic importance, little is known about the global changes in gene expression that accompany autumn cold acclimation in conifers. Using three populations of Sitka spruce (Picea sitchensis) spanning the species range, and a Picea cDNA microarray with 21,840 unique elements, within- and among-population gene expression was monitored during the autumn. Microarray data were validated for selected genes using real-time PCR. Similar numbers of genes were significantly twofold upregulated (1257) and downregulated (967) between late summer and early winter. Among those upregulated were dehydrins, pathogenesis-related/antifreeze genes, carbohydrate and lipid metabolism genes, and genes involved in signal transduction and transcriptional regulation. Among-population microarray hybridizations at early and late autumn time points revealed substantial variation in the autumn transcriptome, some of which may reflect local adaptation. These results demonstrate the complexity of cold acclimation in conifers, highlight similarities and differences to cold tolerance in annual plants, and provide a solid foundation for functional and genetic studies of this important adaptive process.

Data Mining of Gene Arrays for Biomarkers of Survival in Ovarian Cancer

PubMed Central

Coveney, Clare; Boocock, David J.; Rees, Robert C.; Deen, Suha; Ball, Graham R.

2015-01-01

The expected five-year survival rate from a stage III ovarian cancer diagnosis is a mere 22%; this applies to the 7000 new cases diagnosed yearly in the UK. Stratification of patients with this heterogeneous disease, based on active molecular pathways, would aid a targeted treatment improving the prognosis for many cases. While hundreds of genes have been associated with ovarian cancer, few have yet been verified by peer research for clinical significance. Here, a meta-analysis approach was applied to two carefully selected gene expression microarray datasets. Artificial neural networks, Cox univariate survival analyses and T-tests identified genes whose expression was consistently and significantly associated with patient survival. The rigor of this experimental design increases confidence in the genes found to be of interest. A list of 56 genes were distilled from a potential 37,000 to be significantly related to survival in both datasets with a FDR of 1.39859 × 10−11, the identities of which both verify genes already implicated with this disease and provide novel genes and pathways to pursue. Further investigation and validation of these may lead to clinical insights and have potential to predict a patient’s response to treatment or be used as a novel target for therapy. PMID:27600227

Whole-genome resequencing of Bacillus cereus and expression of genes functioning in sodium chloride stress.

PubMed

Xu, Zhenbo; Xie, Jinhong; Liu, Junyan; Ji, Lili; Soteyome, Thanapop; Peters, Brian M; Chen, Dingqiang; Li, Bing; Li, Lin; Shirtliff, Mark E

2017-03-01

Bacillus cereus is one of the most common opportunistic pathogens responsible for various foodborn diseases. To investigate the regulatory mechanism of B. cereus under high osmotic pressure, two B. cereus strains B25 and B26 were isolated from the industrial soy sauce residue containing high-salt concentration. Resequencing was performed by Illumina/Solexa platform and 13,646 SNPs and 434 InDels were identified as common variants between B25 and B26 against reference genome, followed by COG, GO, and KEGG enrichment analysis. Furthermore, 49 key genes involving in Na + /H + ,K + transporter, dipeptide or tripeptide transporter, stress response were selected and classified into 27 groups. Further validation was performed by qRT-PCR, and 4 candidate genes were found most associated with osmotic response. Gene expression of the 4 candidate genes was then analyzed accordingly, and down regulation was obtained for gene BC0669 and BC0754 associated with K + transport system. However, dramatic up regulation was detected for gene BC2114 involving in glutathione peroxidase, indicating the activation of antioxidant responses by osmotic stress via genetic regulation. As concluded, bioinformatic analysis and gene expression profile represented the basis of further investigation on the genetic and regulatory mechanism of bacterial salt tolerance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploiting the full power of temporal gene expression profiling through a new statistical test: application to the analysis of muscular dystrophy data.

PubMed

Vinciotti, Veronica; Liu, Xiaohui; Turk, Rolf; de Meijer, Emile J; 't Hoen, Peter A C

2006-04-03

The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Most statistical methods used in the literature do not fully exploit the temporal ordering in the dataset and are not suited to the case where temporal profiles are measured for a number of different biological conditions. We present a statistical test that makes explicit use of the temporal order in the data by fitting polynomial functions to the temporal profile of each gene and for each biological condition. A Hotelling T2-statistic is derived to detect the genes for which the parameters of these polynomials are significantly different from each other. We validate the temporal Hotelling T2-test on muscular gene expression data from four mouse strains which were profiled at different ages: dystrophin-, beta-sarcoglycan and gamma-sarcoglycan deficient mice, and wild-type mice. The first three are animal models for different muscular dystrophies. Extensive biological validation shows that the method is capable of finding genes with temporal profiles significantly different across the four strains, as well as identifying potential biomarkers for each form of the disease. The added value of the temporal test compared to an identical test which does not make use of temporal ordering is demonstrated via a simulation study, and through confirmation of the expression profiles from selected genes by quantitative PCR experiments. The proposed method maximises the detection of the biologically interesting genes, whilst minimising false detections. The temporal Hotelling T2-test is capable of finding relatively small and robust sets of genes that display different temporal profiles between the conditions of interest. The test is simple, it can be used on gene expression data generated from any experimental design and for any number of conditions, and it allows fast interpretation of the temporal behaviour of genes. The R code is available from V.V. The microarray data have been submitted to GEO under series GSE1574 and GSE3523.

Exploiting the full power of temporal gene expression profiling through a new statistical test: Application to the analysis of muscular dystrophy data

PubMed Central

Vinciotti, Veronica; Liu, Xiaohui; Turk, Rolf; de Meijer, Emile J; 't Hoen, Peter AC

2006-01-01

Background The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Most statistical methods used in the literature do not fully exploit the temporal ordering in the dataset and are not suited to the case where temporal profiles are measured for a number of different biological conditions. We present a statistical test that makes explicit use of the temporal order in the data by fitting polynomial functions to the temporal profile of each gene and for each biological condition. A Hotelling T2-statistic is derived to detect the genes for which the parameters of these polynomials are significantly different from each other. Results We validate the temporal Hotelling T2-test on muscular gene expression data from four mouse strains which were profiled at different ages: dystrophin-, beta-sarcoglycan and gamma-sarcoglycan deficient mice, and wild-type mice. The first three are animal models for different muscular dystrophies. Extensive biological validation shows that the method is capable of finding genes with temporal profiles significantly different across the four strains, as well as identifying potential biomarkers for each form of the disease. The added value of the temporal test compared to an identical test which does not make use of temporal ordering is demonstrated via a simulation study, and through confirmation of the expression profiles from selected genes by quantitative PCR experiments. The proposed method maximises the detection of the biologically interesting genes, whilst minimising false detections. Conclusion The temporal Hotelling T2-test is capable of finding relatively small and robust sets of genes that display different temporal profiles between the conditions of interest. The test is simple, it can be used on gene expression data generated from any experimental design and for any number of conditions, and it allows fast interpretation of the temporal behaviour of genes. The R code is available from V.V. The microarray data have been submitted to GEO under series GSE1574 and GSE3523. PMID:16584545