A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

PubMed

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

PubMed

Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Unconditional analyses can increase efficiency in assessing gene-environment interaction of the case-combined-control design.

PubMed

Goldstein, Alisa M; Dondon, Marie-Gabrielle; Andrieu, Nadine

2006-08-01

A design combining both related and unrelated controls, named the case-combined-control design, was recently proposed to increase the power for detecting gene-environment (GxE) interaction. Under a conditional analytic approach, the case-combined-control design appeared to be more efficient and feasible than a classical case-control study for detecting interaction involving rare events. We now propose an unconditional analytic strategy to further increase the power for detecting gene-environment (GxE) interactions. This strategy allows the estimation of GxE interaction and exposure (E) main effects under certain assumptions (e.g. no correlation in E between siblings and the same exposure frequency in both control groups). Only the genetic (G) main effect cannot be estimated because it is biased. Using simulations, we show that unconditional logistic regression analysis is often more efficient than conditional analysis for detecting GxE interaction, particularly for a rare gene and strong effects. The unconditional analysis is also at least as efficient as the conditional analysis when the gene is common and the main and joint effects of E and G are small. Under the required assumptions, the unconditional analysis retains more information than does the conditional analysis for which only discordant case-control pairs are informative leading to more precise estimates of the odds ratios.

Identification of a new gene regulatory circuit involving B cell receptor activated signaling using a combined analysis of experimental, clinical and global gene expression data

PubMed Central

Schrader, Alexandra; Meyer, Katharina; Walther, Neele; Stolz, Ailine; Feist, Maren; Hand, Elisabeth; von Bonin, Frederike; Evers, Maurits; Kohler, Christian; Shirneshan, Katayoon; Vockerodt, Martina; Klapper, Wolfram; Szczepanowski, Monika; Murray, Paul G.; Bastians, Holger; Trümper, Lorenz; Spang, Rainer; Kube, Dieter

2016-01-01

To discover new regulatory pathways in B lymphoma cells, we performed a combined analysis of experimental, clinical and global gene expression data. We identified a specific cluster of genes that was coherently expressed in primary lymphoma samples and suppressed by activation of the B cell receptor (BCR) through αIgM treatment of lymphoma cells in vitro. This gene cluster, which we called BCR.1, includes numerous cell cycle regulators. A reduced expression of BCR.1 genes after BCR activation was observed in different cell lines and also in CD10+ germinal center B cells. We found that BCR activation led to a delayed entry to and progression of mitosis and defects in metaphase. Cytogenetic changes were detected upon long-term αIgM treatment. Furthermore, an inverse correlation of BCR.1 genes with c-Myc co-regulated genes in distinct groups of lymphoma patients was observed. Finally, we showed that the BCR.1 index discriminates activated B cell-like and germinal centre B cell-like diffuse large B cell lymphoma supporting the functional relevance of this new regulatory circuit and the power of guided clustering for biomarker discovery. PMID:27166259

Gene expression profiling combined with bioinformatics analysis identify biomarkers for Parkinson disease.

PubMed

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result.

Gene Expression Profiling Combined with Bioinformatics Analysis Identify Biomarkers for Parkinson Disease

PubMed Central

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result. PMID:23284986

Combining mouse mammary gland gene expression and comparative mapping for the identification of candidate genes for QTL of milk production traits in cattle

PubMed Central

Ron, Micha; Israeli, Galit; Seroussi, Eyal; Weller, Joel I; Gregg, Jeffrey P; Shani, Moshe; Medrano, Juan F

2007-01-01

Background Many studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations. However, even for relatively large effects with a saturated marker map the confidence interval for QTL location by linkage analysis spans tens of map units, or hundreds of genes. Combining mapping and arraying has been suggested as an approach to identify candidate genes. Thus, gene expression analysis in the mammary gland of genes positioned in the confidence interval of the QTL can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination. Results We hybridized Affymetrix microarray (MG-U74v2), containing 12,488 murine probes, with RNA derived from mammary gland of virgin, pregnant, lactating and involuting C57BL/6J mice in a total of nine biological replicates. We combined microarray data from two additional studies that used the same design in mice with a total of 75 biological replicates. The same filtering and normalization was applied to each microarray data using GeneSpring software. Analysis of variance identified 249 differentially expressed probe sets common to the three experiments along the four developmental stages of puberty, pregnancy, lactation and involution. 212 genes were assigned to their bovine map positions through comparative mapping, and thus form a list of candidate genes for previously identified QTLs for milk production traits. A total of 82 of the genes showed mammary gland-specific expression with at least 3-fold expression over the median representing all tissues tested in GeneAtlas. Conclusion This work presents a web tool for candidate genes for QTL (cgQTL) that allows navigation between the map of bovine milk production QTL, potential candidate genes and their level of expression in mammary gland arrays and in GeneAtlas. Three out of four confirmed genes that affect QTL in livestock (ABCG2, DGAT1, GDF8, IGF2) were over expressed in the target organ. Thus, cg

Analysis of Gene Expression Profiles of Soft Tissue Sarcoma Using a Combination of Knowledge-Based Filtering with Integration of Multiple Statistics

PubMed Central

Doi, Ayano; Ichinohe, Risa; Ikuyo, Yoriko; Takahashi, Teruyoshi; Marui, Shigetaka; Yasuhara, Koji; Nakamura, Tetsuro; Sugita, Shintaro; Sakamoto, Hiromi; Yoshida, Teruhiko; Hasegawa, Tadashi

2014-01-01

The diagnosis and treatment of soft tissue sarcomas (STS) have been difficult. Of the diverse histological subtypes, undifferentiated pleomorphic sarcoma (UPS) is particularly difficult to diagnose accurately, and its classification per se is still controversial. Recent advances in genomic technologies provide an excellent way to address such problems. However, it is often difficult, if not impossible, to identify definitive disease-associated genes using genome-wide analysis alone, primarily because of multiple testing problems. In the present study, we analyzed microarray data from 88 STS patients using a combination method that used knowledge-based filtering and a simulation based on the integration of multiple statistics to reduce multiple testing problems. We identified 25 genes, including hypoxia-related genes (e.g., MIF, SCD1, P4HA1, ENO1, and STAT1) and cell cycle- and DNA repair-related genes (e.g., TACC3, PRDX1, PRKDC, and H2AFY). These genes showed significant differential expression among histological subtypes, including UPS, and showed associations with overall survival. STAT1 showed a strong association with overall survival in UPS patients (logrank p = 1.84×10−6 and adjusted p value 2.99×10−3 after the permutation test). According to the literature, the 25 genes selected are useful not only as markers of differential diagnosis but also as prognostic/predictive markers and/or therapeutic targets for STS. Our combination method can identify genes that are potential prognostic/predictive factors and/or therapeutic targets in STS and possibly in other cancers. These disease-associated genes deserve further preclinical and clinical validation. PMID:25188299

Detection of doublecortin domain-containing 2 (DCDC2), a new candidate tumor suppressor gene of hepatocellular carcinoma, by triple combination array analysis

PubMed Central

2013-01-01

Background To detect genes correlated with hepatocellular carcinoma (HCC), we developed a triple combination array consisting of methylation array, gene expression array and single nucleotide polymorphism (SNP) array analysis. Methods A surgical specimen obtained from a 68-year-old female HCC patient was analyzed by triple combination array, which identified doublecortin domain-containing 2 (DCDC2) as a candidate tumor suppressor gene of HCC. Subsequently, samples from 48 HCC patients were evaluated for their DCDC2 methylation and expression status using methylation specific PCR (MSP) and semi-quantitative reverse transcriptase (RT) PCR, respectively. Then, we investigated the relationship between clinicopathological factors and methylation status of DCDC2. Results DCDC2 was revealed to be hypermethylated (methylation value 0.846, range 0–1.0) in cancer tissue, compared with adjacent normal tissue (0.212) by methylation array in the 68-year-old female patient. Expression array showed decreased expression of DCDC2 in cancerous tissue. SNP array showed that the copy number of chromosome 6p22.1, in which DCDC2 resides, was normal. MSP revealed hypermethylation of the promoter region of DCDC2 in 41 of the tumor samples. DCDC2 expression was significantly decreased in the cases with methylation (P = 0.048). Furthermore, the methylated cases revealed worse prognosis for overall survival than unmethylated cases (P = 0.048). Conclusions The present study indicates that triple combination array is an effective method to detect novel genes related to HCC. We propose that DCDC2 is a tumor suppressor gene of HCC. PMID:24034596

[Analysis of the frequencies of genotype combinations of 4 polymorphisms of genes acting on the folate cycle in the Spanish population].

PubMed

Martínez-Frías, María Luisa; Bermejo, Eva; Pérez, Belén; Desviat, Lourdes R; Castro, Margarita; Leal, Fátima; Mansilla, Elena; Martínez-Fernández, María Luisa; Rodríguez-Pinilla, Elvira; Rodríguez, Laura; Ugarte, Magdalena

2008-06-21

Studies on different populations have shown a great variability of the frequencies of different polymorphisms in genes acting in the folate cycle. The present study was aimed to analyze the frequency in the Spanish population of each genotype combination of four polymorphisms, one of them -1561C-T of the glutamate carboxypeptidase II (GCPII) gene- being the first time that is studied in Spain. The study included a meta-analysis of the published data. Using the Spanish Collaborative Study of Congenital Malformations (ECEMC) Network, blood samples of 190 mother-child couples with newborns without any congenital defect, were obtained from 15 Spanish autonomous regions. The study polymorphisms were the 677C-T and 1298A-C polymorphisms of the methylenetetrahydrofolate reductase (MTHFR), the 66A-G of the methionine synthase reductase (MTRR), and the 1561C-T polymorphism of the GCPII gene. To estimate the range for the population frequencies, 99% confidence intervals were calculated. The frequencies observed in our country were significantly different from others, being similar to those obtained in countries of the Mediterranean European area. The 1561C-T polymorphism of the GCPII gene has a frequency in Spain of 5.11%, which is also similar to the values observed in France (5%) and in Italy (6%). On the other hand, the frequency of the genotypes CTCC, TTAC is quite few, while the genotype TTCC was not observed in any mother or infants. A meta-analysis was performed for a big sample (23,612 individuals) and the results showed that with a 99% of probability the values for the genotype combinations CTCC, TTAC, and TTCC were within 0.10-0.24; 0.20-0.36; and 0.003-0.05, respectively. Our results are important to further analyze the relationship with some health problems and individual susceptibilities. Indeed, considering the published observations of the structure and function of the MTHFR enzyme, it is understandable that those genotype combinations that are quite little

[Polymorphism of POU1F1 gene and PRL gene and their combined effects on milk performance traits in Chinese Holstein cattle].

PubMed

Jia, Xiang-Jie; Wang, Chang-Fa; Yang, Gui-Wen; Huang, Jin-Ming; Li, Qiu-Ling; Zhong, Ji-Feng

2011-12-01

Three novel SNPs were found by DNA sequencing, PCR-RFLP and CRS-PCR methods were used for genotyping in 979 Chinese Holstein cattle. One SNP, G1178C, was identified in exon 2 of POU1F1 gene. Two novel SNPs, A906G and A1134G, were identified in 5'-flanking regulatory region (5'-UTR) of PRL gene. The association between polymorphisms of the two genes and milk performance traits were analyzed with PROC GLM of SAS. The results showed that GC genotype at 1178 locus of POU1F1 gene was advantageous for milk yield, milk protein yield, and milk fat yield. AG genotype at 906 locus was advantageous for milk yield. There was no significant difference between 1134 locus and milk performance traits of 5'-UTR of PRL gene. Analysis of genotype combination effect on milk production traits showed that the effect of combined genotype was not simple sum of single genotypes and the effects of gene pyramiding seemed to be more important in molecular breeding.

Identification of essential genes and synthetic lethal gene combinations in Escherichia coli K-12.

PubMed

Mori, Hirotada; Baba, Tomoya; Yokoyama, Katsushi; Takeuchi, Rikiya; Nomura, Wataru; Makishi, Kazuichi; Otsuka, Yuta; Dose, Hitomi; Wanner, Barry L

2015-01-01

Here we describe the systematic identification of single genes and gene pairs, whose knockout causes lethality in Escherichia coli K-12. During construction of precise single-gene knockout library of E. coli K-12, we identified 328 essential gene candidates for growth in complex (LB) medium. Upon establishment of the Keio single-gene deletion library, we undertook the development of the ASKA single-gene deletion library carrying a different antibiotic resistance. In addition, we developed tools for identification of synthetic lethal gene combinations by systematic construction of double-gene knockout mutants. We introduce these methods herein.

Clinical omics analysis of colorectal cancer incorporating copy number aberrations and gene expression data.

PubMed

Yoshida, Tsuyoshi; Kobayashi, Takumi; Itoda, Masaya; Muto, Taika; Miyaguchi, Ken; Mogushi, Kaoru; Shoji, Satoshi; Shimokawa, Kazuro; Iida, Satoru; Uetake, Hiroyuki; Ishikawa, Toshiaki; Sugihara, Kenichi; Mizushima, Hiroshi; Tanaka, Hiroshi

2010-07-29

Colorectal cancer (CRC) is one of the most frequently occurring cancers in Japan, and thus a wide range of methods have been deployed to study the molecular mechanisms of CRC. In this study, we performed a comprehensive analysis of CRC, incorporating copy number aberration (CRC) and gene expression data. For the last four years, we have been collecting data from CRC cases and organizing the information as an "omics" study by integrating many kinds of analysis into a single comprehensive investigation. In our previous studies, we had experienced difficulty in finding genes related to CRC, as we observed higher noise levels in the expression data than in the data for other cancers. Because chromosomal aberrations are often observed in CRC, here, we have performed a combination of CNA analysis and expression analysis in order to identify some new genes responsible for CRC. This study was performed as part of the Clinical Omics Database Project at Tokyo Medical and Dental University. The purpose of this study was to investigate the mechanism of genetic instability in CRC by this combination of expression analysis and CNA, and to establish a new method for the diagnosis and treatment of CRC. Comprehensive gene expression analysis was performed on 79 CRC cases using an Affymetrix Gene Chip, and comprehensive CNA analysis was performed using an Affymetrix DNA Sty array. To avoid the contamination of cancer tissue with normal cells, laser micro-dissection was performed before DNA/RNA extraction. Data analysis was performed using original software written in the R language. We observed a high percentage of CNA in colorectal cancer, including copy number gains at 7, 8q, 13 and 20q, and copy number losses at 8p, 17p and 18. Gene expression analysis provided many candidates for CRC-related genes, but their association with CRC did not reach the level of statistical significance. The combination of CNA and gene expression analysis, together with the clinical information

Down-weighting overlapping genes improves gene set analysis

PubMed Central

2012-01-01

Background The identification of gene sets that are significantly impacted in a given condition based on microarray data is a crucial step in current life science research. Most gene set analysis methods treat genes equally, regardless how specific they are to a given gene set. Results In this work we propose a new gene set analysis method that computes a gene set score as the mean of absolute values of weighted moderated gene t-scores. The gene weights are designed to emphasize the genes appearing in few gene sets, versus genes that appear in many gene sets. We demonstrate the usefulness of the method when analyzing gene sets that correspond to the KEGG pathways, and hence we called our method Pathway Analysis with Down-weighting of Overlapping Genes (PADOG). Unlike most gene set analysis methods which are validated through the analysis of 2-3 data sets followed by a human interpretation of the results, the validation employed here uses 24 different data sets and a completely objective assessment scheme that makes minimal assumptions and eliminates the need for possibly biased human assessments of the analysis results. Conclusions PADOG significantly improves gene set ranking and boosts sensitivity of analysis using information already available in the gene expression profiles and the collection of gene sets to be analyzed. The advantages of PADOG over other existing approaches are shown to be stable to changes in the database of gene sets to be analyzed. PADOG was implemented as an R package available at: http://bioinformaticsprb.med.wayne.edu/PADOG/or http://www.bioconductor.org. PMID:22713124

Mitochondrial gene sequences alone or combined with ITS region sequences provide firm molecular criteria for the classification of Lecanicillium species.

PubMed

Kouvelis, Vassili N; Sialakouma, Aphrodite; Typas, Milton A

2008-07-01

The recent revision of Verticillium sect. Prostrata led to the introduction of the genus Lecanicillium, which comprises the majority of the entomopathogenic strains. Sixty-five strains previously classified as Verticillium lecanii or Verticillium sp. from different geographical regions and hosts were examined and their phylogenetic relationships were determined using sequences from three mitochondrial (mt) genes [the small rRNA subunit (rns), the NADH dehydrogenase subunits 1 (nad1) and 3 (nad3)] and the ITS region. In general, single gene phylogenetic trees differentiated and placed the strains examined in well-supported (by BS analysis) groups of L. lecanii, L. longisporum, L. muscarium, and L. nodulosum, although in some cases a few uncertainties still remained. nad1 was the most informative single gene in phylogenetic analyses and was also found to contain group I introns with putative open reading frames (ORFs) encoding for GIY-YIG endonucleases. The combined use of mt gene sequences resolved taxonomic uncertainties arisen from ITS analysis and, alone or in combination with ITS sequences, helped in placing uncharacterised Verticillium lecanii and Verticillium sp. firmly into Lecanicillium species. Combined gene data from all the mt genes and all the mt genes and the ITS region together, were very similar. Furthermore, a relaxed correlation with host specificity -- at least for Homoptera -- was indicated for the rns and the combined mt gene sequences. Thus, the usefulness of mt gene sequences as a convenient molecular tool in phylogenetic studies of entomopathogenic fungi was demonstrated.

Combining Selective Pressures to Enhance the Durability of Disease Resistance Genes.

PubMed

2016-01-01

The efficacy of disease resistance genes in plants decreases over time because of the selection of virulent pathogen genotypes. A key goal of crop protection programs is to increase the durability of the resistance conferred by these genes. The spatial and temporal deployment of plant disease resistance genes is considered to be a major factor determining their durability. In the literature, four principal strategies combining resistance genes over time and space have been considered to delay the evolution of virulent pathogen genotypes. We reviewed this literature with the aim of determining which deployment strategy results in the greatest durability of resistance genes. Although theoretical and empirical studies comparing deployment strategies of more than one resistance gene are very scarce, they suggest that the overall durability of disease resistance genes can be increased by combining their presence in the same plant (pyramiding). Retrospective analyses of field monitoring data also suggest that the pyramiding of disease resistance genes within a plant is the most durable strategy. By extension, we suggest that the combination of disease resistance genes with other practices for pathogen control (pesticides, farming practices) may be a relevant management strategy to slow down the evolution of virulent pathogen genotypes.

The relationship between gene transcription and combinations of histone modifications

NASA Astrophysics Data System (ADS)

Cui, Xiangjun; Li, Hong; Luo, Liaofu

2012-09-01

Histone modification is an important subject of epigenetics which plays an intrinsic role in transcriptional regulation. It is known that multiple histone modifications act in a combinatorial fashion. In this study, we demonstrated that the pathways within constructed Bayesian networks can give an indication for the combinations among 12 histone modifications which have been studied in the TSS+1kb region in S. cerevisiae. After Bayesian networks for the genes with high transcript levels (H-network) and low transcript levels (L-network) were constructed, the combinations of modifications within the two networks were analyzed from the view of transcript level. The results showed that different combinations played dissimilar roles in the regulation of gene transcription when there exist differences for gene expression at transcription level.

Combined analysis of fourteen nuclear genes refines the Ursidae phylogeny.

PubMed

Pagès, Marie; Calvignac, Sébastien; Klein, Catherine; Paris, Mathilde; Hughes, Sandrine; Hänni, Catherine

2008-04-01

Despite numerous studies, questions remain about the evolutionary history of Ursidae and additional independent genetic markers were needed to elucidate these ambiguities. For this purpose, we sequenced ten nuclear genes for all the eight extant bear species. By combining these new sequences with those of four other recently published nuclear markers, we provide new insights into the phylogenetic relationships of the Ursidae family members. The hypothesis that the giant panda was the first species to diverge among ursids is definitively confirmed and the precise branching order within the Ursus genus is clarified for the first time. Moreover, our analyses indicate that the American and the Asiatic black bears do not cluster as sister taxa, as had been previously hypothesised. Sun and sloth bears clearly appear as the most basal ursine species but uncertainties about their exact relationships remain. Since our larger dataset did not enable us to clarify this last question, identifying rare genomic changes in bear genomes could be a promising solution for further studies.

Combining growth-promoting genes leads to positive epistasis in Arabidopsis thaliana

PubMed Central

Vanhaeren, Hannes; Gonzalez, Nathalie; Coppens, Frederik; De Milde, Liesbeth; Van Daele, Twiggy; Vermeersch, Mattias; Eloy, Nubia B; Storme, Veronique; Inzé, Dirk

2014-01-01

Several genes positively influence final leaf size in Arabidopsis when mutated or overexpressed. The connections between these growth regulators are still poorly understood although such knowledge would further contribute to understand the processes driving leaf growth. In this study, we performed a combinatorial screen with 13 transgenic Arabidopsis lines with an increased leaf size. We found that from 61 analyzed combinations, 39% showed an additional increase in leaf size and most resulted from a positive epistasis on growth. Similar to what is found in other organisms in which such an epistasis assay was performed, only few genes were highly connected in synergistic combinations as we observed a positive epistasis in the majority of the combinations with samba, BRI1OE or SAUR19OE. Furthermore, positive epistasis was found with combinations of genes with a similar mode of action, but also with genes which affect distinct processes, such as cell proliferation and cell expansion. DOI: http://dx.doi.org/10.7554/eLife.02252.001 PMID:24843021

Laser-capture micro dissection combined with next-generation sequencing analysis of cell type-specific deafness gene expression in the mouse cochlea.

PubMed

Nishio, Shin-Ya; Takumi, Yutaka; Usami, Shin-Ichi

2017-05-01

Cochlear implantation (CI), which directly stimulates the cochlear nerves, is the most effective and widely used medical intervention for patients with severe to profound sensorineural hearing loss. The etiology of the hearing loss is speculated to have a major influence of CI outcomes, particularly in cases resulting from mutations in genes preferentially expressed in the spiral ganglion region. To elucidate precise gene expression levels in each part of the cochlea, we performed laser-capture micro dissection in combination with next-generation sequencing analysis and determined the expression levels of all known deafness-associated genes in the organ of Corti, spiral ganglion, lateral wall, and spiral limbs. The results were generally consistent with previous reports based on immunocytochemistry or in situ hybridization. As a notable result, the genes associated with many kinds of syndromic hearing loss (such as Clpp, Hars2, Hsd17b4, Lars2 for Perrault syndrome, Polr1c and Polr1d for Treacher Collins syndrome, Ndp for Norrie Disease, Kal for Kallmann syndrome, Edn3 and Snai2 for Waardenburg Syndrome, Col4a3 for Alport syndrome, Sema3e for CHARGE syndrome, Col9a1 for Sticker syndrome, Cdh23, Cib2, Clrn1, Pcdh15, Ush1c, Ush2a, Whrn for Usher syndrome and Wfs1 for Wolfram syndrome) showed higher levels of expression in the spiral ganglion than in other parts of the cochlea. This dataset will provide a base for more detailed analysis in order to clarify gene functions in the cochlea as well as predict CI outcomes based on gene expression data. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Novel strategies to mine alcoholism-related haplotypes and genes by combining existing knowledge framework.

PubMed

Zhang, RuiJie; Li, Xia; Jiang, YongShuai; Liu, GuiYou; Li, ChuanXing; Zhang, Fan; Xiao, Yun; Gong, BinSheng

2009-02-01

High-throughout single nucleotide polymorphism detection technology and the existing knowledge provide strong support for mining the disease-related haplotypes and genes. In this study, first, we apply four kinds of haplotype identification methods (Confidence Intervals, Four Gamete Tests, Solid Spine of LD and fusing method of haplotype block) into high-throughout SNP genotype data to identify blocks, then use cluster analysis to verify the effectiveness of the four methods, and select the alcoholism-related SNP haplotypes through risk analysis. Second, we establish a mapping from haplotypes to alcoholism-related genes. Third, we inquire NCBI SNP and gene databases to locate the blocks and identify the candidate genes. In the end, we make gene function annotation by KEGG, Biocarta, and GO database. We find 159 haplotype blocks, which relate to the alcoholism most possibly on chromosome 1 approximately 22, including 227 haplotypes, of which 102 SNP haplotypes may increase the risk of alcoholism. We get 121 alcoholism-related genes and verify their reliability by the functional annotation of biology. In a word, we not only can handle the SNP data easily, but also can locate the disease-related genes precisely by combining our novel strategies of mining alcoholism-related haplotypes and genes with existing knowledge framework.

Complex regulation of the aflatoxin biosynthesis gene cluster of Aspergillus flavus in relation to various combinations of water activity and temperature.

PubMed

Schmidt-Heydt, Markus; Abdel-Hadi, Ahmed; Magan, Naresh; Geisen, Rolf

2009-11-15

A microarray analysis was performed to study the effect of varying combinations of water activity and temperature on the activation of aflatoxin biosynthesis genes in Aspergillusflavus grown on YES medium. Generally A. flavus showed expression of the aflatoxin biosynthetic genes at all parameter combinations tested. Certain combinations of a(w) and temperature, especially combinations which imposed stress on the fungus resulted in a significant reduction of the growth rate. At these conditions induction of the whole aflatoxin biosynthesis gene cluster occurred, however the produced aflatoxin B(1) was low. At all other combinations (25 degrees C/0.95 and 0.99; 30 degrees C/0.95 and 0.99; 35 degrees C/0.95 and 0.99) a reduced basal level of cluster gene expression occurred. At these combinations a high growth rate was obtained as well as high aflatoxin production. When single genes were compared, two groups with different expression profiles in relation to water activity/temperature combinations occurred. These two groups were co-ordinately localized within the aflatoxin gene cluster. The ratio of aflR/aflJ expression was correlated with increased aflatoxin biosynthesis.

Gene Circuit Analysis of the Terminal Gap Gene huckebein

PubMed Central

Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

2009-01-01

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network. PMID:19876378

Gene circuit analysis of the terminal gap gene huckebein.

PubMed

Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

2009-10-01

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network.

Analysis of the clonal repertoire of gene-corrected cells in gene therapy.

PubMed

Paruzynski, Anna; Glimm, Hanno; Schmidt, Manfred; Kalle, Christof von

2012-01-01

Gene therapy-based clinical phase I/II studies using integrating retroviral vectors could successfully treat different monogenetic inherited diseases. However, with increased efficiency of this therapy, severe side effects occurred in various gene therapy trials. In all cases, integration of the vector close to or within a proto-oncogene contributed substantially to the development of the malignancies. Thus, the in-depth analysis of integration site patterns is of high importance to uncover potential clonal outgrowth and to assess the safety of gene transfer vectors and gene therapy protocols. The standard and nonrestrictive linear amplification-mediated PCR (nrLAM-PCR) in combination with high-throughput sequencing exhibits technologies that allow to comprehensively analyze the clonal repertoire of gene-corrected cells and to assess the safety of the used vector system at an early stage on the molecular level. It enables clarifying the biological consequences of the vector system on the fate of the transduced cell. Furthermore, the downstream performance of real-time PCR allows a quantitative estimation of the clonality of individual cells and their clonal progeny. Here, we present a guideline that should allow researchers to perform comprehensive integration site analysis in preclinical and clinical studies. Copyright © 2012 Elsevier Inc. All rights reserved.

Synergistically combined gene delivery for enhanced VEGF secretion and anti-apoptosis

PubMed Central

Won, Young-Wook; Lee, Minhyung; Kim, Hyun Ah; Nam, Kihoon; Bull, David A.; Kim, Sung Wan

2013-01-01

With current pharmacological treatments, preventing the remodeling of the left ventricle and the progression to heart failure is a difficult task. Gene therapy is considered to provide a direct treatment to the long-term complications of ischemic heart diseases. Although current gene therapies that use single molecular targets seem potentially possible, they have not achieved a success in the treatment of ischemic diseases. With an efficient polymeric gene carrier, PAM-ABP, we designed a synergistically combined gene delivery strategy to enhance vascular endothelial growth factor (VEGF) secretion and prolong anti-apoptotic effects. A hypoxia-inducible plasmid expressing both hypoxia-inducible heme oxygenase-1 (HO-1) and the Src homology domain-2 containing tyrosine phosphatase-1 microRNA (miSHP 1) and a hypoxia-responsive VEGF plasmid were combined in this study. The positive feedback circuit between HO-1 and VEGF, and the negative regulatory role of SHP-1 in angiogenesis enhance VEGF secretion synergistically. The synergy in VEGF secretion as a consequence of the gene combination and the prolonged HO-1 activity was confirmed in hypoxic cardiomyocytes and cardiomyocyte apoptosis under hypoxia, and was decreased synergistically. These results suggest that the synergistic combination of VEGF, HO-1, and miSHP-1 may be promising for the clinical treatment of ischemic diseases. PMID:24007285

Analysis of multiplex gene expression maps obtained by voxelation.

PubMed

An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

2009-04-29

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental

An Integrative Genetics Approach to Identify Candidate Genes Regulating BMD: Combining Linkage, Gene Expression, and Association

PubMed Central

Farber, Charles R; van Nas, Atila; Ghazalpour, Anatole; Aten, Jason E; Doss, Sudheer; Sos, Brandon; Schadt, Eric E; Ingram-Drake, Leslie; Davis, Richard C; Horvath, Steve; Smith, Desmond J; Drake, Thomas A; Lusis, Aldons J

2009-01-01

Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification. PMID:18767929

The human RHOX gene cluster: target genes and functional analysis of gene variants in infertile men.

PubMed

Borgmann, Jennifer; Tüttelmann, Frank; Dworniczak, Bernd; Röpke, Albrecht; Song, Hye-Won; Kliesch, Sabine; Wilkinson, Miles F; Laurentino, Sandra; Gromoll, Jörg

2016-11-15

The X-linked reproductive homeobox (RHOX) gene cluster encodes transcription factors preferentially expressed in reproductive tissues. This gene cluster has important roles in male fertility based on phenotypic defects of Rhox-mutant mice and the finding that aberrant RHOX promoter methylation is strongly associated with abnormal human sperm parameters. However, little is known about the molecular mechanism of RHOX function in humans. Using gene expression profiling, we identified genes regulated by members of the human RHOX gene cluster. Some genes were uniquely regulated by RHOXF1 or RHOXF2/2B, while others were regulated by both of these transcription factors. Several of these regulated genes encode proteins involved in processes relevant to spermatogenesis; e.g. stress protection and cell survival. One of the target genes of RHOXF2/2B is RHOXF1, suggesting cross-regulation to enhance transcriptional responses. The potential role of RHOX in human infertility was addressed by sequencing all RHOX exons in a group of 250 patients with severe oligozoospermia. This revealed two mutations in RHOXF1 (c.515G > A and c.522C > T) and four in RHOXF2/2B (-73C > G, c.202G > A, c.411C > T and c.679G > A), of which only one (c.202G > A) was found in a control group of men with normal sperm concentration. Functional analysis demonstrated that c.202G > A and c.679G > A significantly impaired the ability of RHOXF2/2B to regulate downstream genes. Molecular modelling suggested that these mutations alter RHOXF2/F2B protein conformation. By combining clinical data with in vitro functional analysis, we demonstrate how the X-linked RHOX gene cluster may function in normal human spermatogenesis and we provide evidence that it is impaired in human male fertility.

Bacterial reference genes for gene expression studies by RT-qPCR: survey and analysis.

PubMed

Rocha, Danilo J P; Santos, Carolina S; Pacheco, Luis G C

2015-09-01

The appropriate choice of reference genes is essential for accurate normalization of gene expression data obtained by the method of reverse transcription quantitative real-time PCR (RT-qPCR). In 2009, a guideline called the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) highlighted the importance of the selection and validation of more than one suitable reference gene for obtaining reliable RT-qPCR results. Herein, we searched the recent literature in order to identify the bacterial reference genes that have been most commonly validated in gene expression studies by RT-qPCR (in the first 5 years following publication of the MIQE guidelines). Through a combination of different search parameters with the text mining tool MedlineRanker, we identified 145 unique bacterial genes that were recently tested as candidate reference genes. Of these, 45 genes were experimentally validated and, in most of the cases, their expression stabilities were verified using the software tools geNorm and NormFinder. It is noteworthy that only 10 of these reference genes had been validated in two or more of the studies evaluated. An enrichment analysis using Gene Ontology classifications demonstrated that genes belonging to the functional categories of DNA Replication (GO: 0006260) and Transcription (GO: 0006351) rendered a proportionally higher number of validated reference genes. Three genes in the former functional class were also among the top five most stable genes identified through an analysis of gene expression data obtained from the Pathosystems Resource Integration Center. These results may provide a guideline for the initial selection of candidate reference genes for RT-qPCR studies in several different bacterial species.

Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

PubMed Central

Moretti, Stefano; van Leeuwen, Danitsja; Gmuender, Hans; Bonassi, Stefano; van Delft, Joost; Kleinjans, Jos; Patrone, Fioravante; Merlo, Domenico Franco

2008-01-01

Background In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. Results In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. Conclusion CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between

In vitro therapeutic effect of PDT combined with VEGF-A gene therapy

NASA Astrophysics Data System (ADS)

Lecaros, Rumwald Leo G.; Huang, Leaf; Hsu, Yih-Chih

2014-02-01

Vascular endothelial growth factor A (VEGF-A), commonly known as VEGF, is one of the primary factors that affect tumor angiogenesis. It was found to be expressed in cancer cell lines including oral squamous cell carcinoma. Photodynamic therapy (PDT) is a novel therapeutic modality to treat cancer by using a photosensitizer which is activated by a light source to produce reactive oxygen species and mediates oxygen-independent hypoxic conditions to tumor. Another emerging treatment to cure cancer is the use of interference RNA (e.g. siRNA) to silence a specific mRNA sequence. VEGF-A was found to be expressed in oral squamous cell carcinoma and overexpressed after 24 hour post-PDT by Western blot analysis. Cell viability was found to decrease at 25 nM of transfected VEGF-A siRNA. In vitro combined therapy of PDT and VEGF-A siRNA showed better response as compared with PDT and gene therapy alone. The results suggest that PDT combined with targeted gene therapy has a potential mean to achieve better therapeutic outcome.

Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia.

PubMed

Badea, Liviu; Herlea, Vlad; Dima, Simona Olimpia; Dumitrascu, Traian; Popescu, Irinel

2008-01-01

The precise details of pancreatic ductal adenocarcinoma (PDAC) pathogenesis are still insufficiently known, requiring the use of high-throughput methods. However, PDAC is especially difficult to study using microarrays due to its strong desmoplastic reaction, which involves a hyperproliferating stroma that effectively "masks" the contribution of the minoritary neoplastic epithelial cells. Thus it is not clear which of the genes that have been found differentially expressed between normal and whole tumor tissues are due to the tumor epithelia and which simply reflect the differences in cellular composition. To address this problem, laser microdissection studies have been performed, but these have to deal with much smaller tissue sample quantities and therefore have significantly higher experimental noise. In this paper we combine our own large sample whole-tissue study with a previously published smaller sample microdissection study by Grützmann et al. to identify the genes that are specifically overexpressed in PDAC tumor epithelia. The overlap of this list of genes with other microarray studies of pancreatic cancer as well as with the published literature is impressive. Moreover, we find a number of genes whose over-expression appears to be inversely correlated with patient survival: keratin 7, laminin gamma 2, stratifin, platelet phosphofructokinase, annexin A2, MAP4K4 and OACT2 (MBOAT2), which are all specifically upregulated in the neoplastic epithelia, rather than the tumor stroma. We improve on other microarray studies of PDAC by putting together the higher statistical power due to a larger number of samples with information about cell-type specific expression and patient survival.

Integrated analysis of gene expression and methylation profiles of 48 candidate genes in breast cancer patients.

PubMed

Li, Zibo; Heng, Jianfu; Yan, Jinhua; Guo, Xinwu; Tang, Lili; Chen, Ming; Peng, Limin; Wu, Yepeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Wang, Jun

2016-11-01

Gene-specific methylation and expression have shown biological and clinical importance for breast cancer diagnosis and prognosis. Integrated analysis of gene methylation and gene expression may identify genes associated with biology mechanism and clinical outcome of breast cancer and aid in clinical management. Using high-throughput microfluidic quantitative PCR, we analyzed the expression profiles of 48 candidate genes in 96 Chinese breast cancer patients and investigated their correlation with gene methylation and associations with breast cancer clinical parameters. Breast cancer-specific gene expression alternation was found in 25 genes with significant expression difference between paired tumor and normal tissues. A total of 9 genes (CCND2, EGFR, GSTP1, PGR, PTGS2, RECK, SOX17, TNFRSF10D, and WIF1) showed significant negative correlation between methylation and gene expression, which were validated in the TCGA database. Total 23 genes (ACADL, APC, BRCA2, CADM1, CAV1, CCND2, CST6, EGFR, ESR2, GSTP1, ICAM5, NPY, PGR, PTGS2, RECK, RUNX3, SFRP1, SOX17, SYK, TGFBR2, TNFRSF10D, WIF1, and WRN) annotated with potential TFBSs in the promoter regions showed negative correlation between methylation and expression. In logistics regression analysis, 31 of the 48 genes showed improved performance in disease prediction with combination of methylation and expression coefficient. Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.

Combining Genome-Scale Experimental and Computational Methods To Identify Essential Genes in Rhodobacter sphaeroides

DOE PAGES

Burger, Brian T.; Imam, Saheed; Scarborough, Matthew J.; ...

2017-06-06

Rhodobacter sphaeroides is one of the best-studied alphaproteobacteria from biochemical, genetic, and genomic perspectives. To gain a better systems-level understanding of this organism, we generated a large transposon mutant library and used transposon sequencing (Tn-seq) to identify genes that are essential under several growth conditions. Using newly developed Tn-seq analysis software (TSAS), we identified 493 genes as essential for aerobic growth on a rich medium. We then used the mutant library to identify conditionally essential genes under two laboratory growth conditions, identifying 85 additional genes required for aerobic growth in a minimal medium and 31 additional genes required for photosyntheticmore » growth. In all instances, our analyses confirmed essentiality for many known genes and identified genes not previously considered to be essential. We used the resulting Tn-seq data to refine and improve a genome-scale metabolic network model (GEM) for R. sphaeroides. Together, we demonstrate how genetic, genomic, and computational approaches can be combined to obtain a systems-level understanding of the genetic framework underlying metabolic diversity in bacterial species.« less

Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis.

PubMed

Mei, Hao; Li, Lianna; Liu, Shijian; Jiang, Fan; Griswold, Michael; Mosley, Thomas

2017-01-21

We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.

EGFR Gene Amplification and KRAS Mutation Predict Response to Combination Targeted Therapy in Metastatic Colorectal Cancer.

PubMed

Khan, Sajid A; Zeng, Zhaoshi; Shia, Jinru; Paty, Philip B

2017-07-01

Genetic variability in KRAS and EGFR predicts response to cetuximab in irinotecan refractory colorectal cancer. Whether these markers or others remain predictive in combination biologic therapies including bevacizumab is unknown. We identified predictive biomarkers from patients with irinotecan refractory metastatic colorectal cancer treated with cetuximab plus bevacizumab. Patients who received cetuximab plus bevacizumab for irinotecan refractory colorectal cancer in either of two Phase II trials conducted were identified. Tumor tissue was available for 33 patients. Genomic DNA was extracted and used for mutational analysis of KRAS, BRAF, and p53 genes. Fluorescence in situ hybridization was performed to assess EGFR copy number. The status of single genes and various combinations were tested for association with response. Seven of 33 patients responded to treatment. KRAS mutations were found in 14/33 cases, and 0 responded to treatment (p = 0.01). EGFR gene amplification was seen in 3/33 of tumors and in every case was associated with response to treatment (p < 0.001). TP53 and BRAF mutations were found in 18/33 and 0/33 tumors, respectively, and there were no associations with response to either gene. EGFR gene amplification and KRAS mutations are predictive markers for patients receiving combination biologic therapy of cetuximab plus bevacizumab for metastatic colorectal cancer. One marker or the other is present in the tumor of half of all patients allowing treatment response to be predicted with a high degree of certainty. The role for molecular markers in combination biologic therapy seems promising.

Weighted functional linear regression models for gene-based association analysis.

PubMed

Belonogova, Nadezhda M; Svishcheva, Gulnara R; Wilson, James F; Campbell, Harry; Axenovich, Tatiana I

2018-01-01

Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with P < 0.1 in at least one analysis had lower P values with weighted models. Moreover, we found an association between diastolic blood pressure and the VMP1 gene (P = 8.18×10-6), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had P = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at https://cran.r-project.org/web/packages/FREGAT/index.html.

Systematic analysis of human kinase genes: a large number of genes and alternative splicing events result in functional and structural diversity

PubMed Central

Milanesi, Luciano; Petrillo, Mauro; Sepe, Leandra; Boccia, Angelo; D'Agostino, Nunzio; Passamano, Myriam; Di Nardo, Salvatore; Tasco, Gianluca; Casadio, Rita; Paolella, Giovanni

2005-01-01

Background Protein kinases are a well defined family of proteins, characterized by the presence of a common kinase catalytic domain and playing a significant role in many important cellular processes, such as proliferation, maintenance of cell shape, apoptosys. In many members of the family, additional non-kinase domains contribute further specialization, resulting in subcellular localization, protein binding and regulation of activity, among others. About 500 genes encode members of the kinase family in the human genome, and although many of them represent well known genes, a larger number of genes code for proteins of more recent identification, or for unknown proteins identified as kinase only after computational studies. Results A systematic in silico study performed on the human genome, led to the identification of 5 genes, on chromosome 1, 11, 13, 15 and 16 respectively, and 1 pseudogene on chromosome X; some of these genes are reported as kinases from NCBI but are absent in other databases, such as KinBase. Comparative analysis of 483 gene regions and subsequent computational analysis, aimed at identifying unannotated exons, indicates that a large number of kinase may code for alternately spliced forms or be incorrectly annotated. An InterProScan automated analysis was perfomed to study domain distribution and combination in the various families. At the same time, other structural features were also added to the annotation process, including the putative presence of transmembrane alpha helices, and the cystein propensity to participate into a disulfide bridge. Conclusion The predicted human kinome was extended by identifiying both additional genes and potential splice variants, resulting in a varied panorama where functionality may be searched at the gene and protein level. Structural analysis of kinase proteins domains as defined in multiple sources together with transmembrane alpha helices and signal peptide prediction provides hints to function assignment

[Using exon combined target region capture sequencing chip to detect the disease-causing genes of retinitis pigmentosa].

PubMed

Rong, Weining; Chen, Xuejuan; Li, Huiping; Liu, Yani; Sheng, Xunlun

2014-06-01

To detect the disease-causing genes of 10 retinitis pigmentosa pedigrees by using exon combined target region capture sequencing chip. Pedigree investigation study. From October 2010 to December 2013, 10 RP pedigrees were recruited for this study in Ningxia Eye Hospital. All the patients and family members received complete ophthalmic examinations. DNA was abstracted from patients, family members and controls. Using exon combined target region capture sequencing chip to screen the candidate disease-causing mutations. Polymerase chain reaction (PCR) and direct sequencing were used to confirm the disease-causing mutations. Seventy patients and 23 normal family members were recruited from 10 pedigrees. Among 10 RP pedigrees, 1 was autosomal dominant pedigrees and 9 were autosomal recessive pedigrees. 7 mutations related to 5 genes of 5 pedigrees were detected. A frameshift mutation on BBS7 gene was detected in No.2 pedigree, the patients of this pedigree combined with central obesity, polydactyly and mental handicap. No.2 pedigree was diagnosed as Bardet-Biedl syndrome finally. A missense mutation was detected in No.7 and No.10 pedigrees respectively. Because the patients suffered deafness meanwhile, the final diagnosis was Usher syndrome. A missense mutation on C3 gene related to age-related macular degeneration was also detected in No. 7 pedigrees. A nonsense mutation and a missense mutation on CRB1 gene were detected in No. 1 pedigree and a splicesite mutation on PROM1 gene was detected in No. 5 pedigree. Retinitis pigmentosa is a kind of genetic eye disease with diversity clinical phenotypes. Rapid and effective genetic diagnosis technology combined with clinical characteristics analysis is helpful to improve the level of clinical diagnosis of RP.

Molecular characterization and combined genotype association study of bovine cluster of differentiation 14 gene with clinical mastitis in crossbred dairy cattle.

PubMed

Selvan, A Sakthivel; Gupta, I D; Verma, A; Chaudhari, M V; Magotra, A

2016-07-01

The present study was undertaken with the objectives to characterize and to analyze combined genotypes of cluster of differentiation 14 (CD14) gene to explore its association with clinical mastitis in Karan Fries (KF) cows maintained in the National Dairy Research Institute herd, Karnal. Genomic DNA was extracted using blood of randomly selected 94 KF lactating cattle by phenol-chloroform method. After checking its quality and quantity, polymerase chain reaction (PCR) was carried out using six sets of reported gene-specific primers to amplify complete KF CD14 gene. The forward and reverse sequences for each PCR fragments were assembled to form complete sequence for the respective region of KF CD14 gene. The multiple sequence alignments of the edited sequence with the corresponding reference with reported Bos taurus sequence (EU148610.1) were performed with ClustalW software to identify single nucleotide polymorphisms (SNPs). Basic Local Alignment Search Tool analysis was performed to compare the sequence identity of KF CD14 gene with other species. The restriction fragment length polymorphism (RFLP) analysis was carried out in all KF cows using Helicobacter pylori 188I (Hpy188I) (contig 2) and Haemophilus influenzae I (HinfI) (contig 4) restriction enzyme (RE). Cows were assigned genotypes obtained by PCR-RFLP analysis, and association study was done using Chi-square (χ (2)) test. The genotypes of both contigs (loci) number 2 and 4 were combined with respect to each animal to construct combined genotype patterns. Two types of sequences of KF were obtained: One with 2630 bp having one insertion at 616 nucleotide (nt) position and one deletion at 1117 nt position, and the another sequence was of 2629 bp having only one deletion at 615 nt position. ClustalW, multiple alignments of KF CD14 gene sequence with B. taurus cattle sequence (EU148610.1), revealed 24 nt changes (SNPs). Cows were also screened using PCR-RFLP with Hpy188I (contig 2) and HinfI (contig 4) RE

Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function

PubMed Central

Tian, Weidong; Zhang, Lan V; Taşan, Murat; Gibbons, Francis D; King, Oliver D; Park, Julie; Wunderlich, Zeba; Cherry, J Michael; Roth, Frederick P

2008-01-01

Background: Learning the function of genes is a major goal of computational genomics. Methods for inferring gene function have typically fallen into two categories: 'guilt-by-profiling', which exploits correlation between function and other gene characteristics; and 'guilt-by-association', which transfers function from one gene to another via biological relationships. Results: We have developed a strategy ('Funckenstein') that performs guilt-by-profiling and guilt-by-association and combines the results. Using a benchmark set of functional categories and input data for protein-coding genes in Saccharomyces cerevisiae, Funckenstein was compared with a previous combined strategy. Subsequently, we applied Funckenstein to 2,455 Gene Ontology terms. In the process, we developed 2,455 guilt-by-profiling classifiers based on 8,848 gene characteristics and 12 functional linkage graphs based on 23 biological relationships. Conclusion: Funckenstein outperforms a previous combined strategy using a common benchmark dataset. The combination of 'guilt-by-profiling' and 'guilt-by-association' gave significant improvement over the component classifiers, showing the greatest synergy for the most specific functions. Performance was evaluated by cross-validation and by literature examination of the top-scoring novel predictions. These quantitative predictions should help prioritize experimental study of yeast gene functions. PMID:18613951

A Streamlined Protocol for Molecular Testing of the DMD Gene within a Diagnostic Laboratory: A Combination of Array Comparative Genomic Hybridization and Bidirectional Sequence Analysis

PubMed Central

Marquis-Nicholson, Renate; Lai, Daniel; Love, Jennifer M.; Love, Donald R.

2013-01-01

Purpose. The aim of this study was to develop a streamlined mutation screening protocol for the DMD gene in order to confirm a clinical diagnosis of Duchenne or Becker muscular dystrophy in affected males and to clarify the carrier status of female family members. Methods. Sequence analysis and array comparative genomic hybridization (aCGH) were used to identify mutations in the dystrophin DMD gene. We analysed genomic DNA from six individuals with a range of previously characterised mutations and from eight individuals who had not previously undergone any form of molecular analysis. Results. We successfully identified the known mutations in all six patients. A molecular diagnosis was also made in three of the four patients with a clinical diagnosis who had not undergone prior genetic screening, and testing for familial mutations was successfully completed for the remaining four patients. Conclusion. The mutation screening protocol described here meets best practice guidelines for molecular testing of the DMD gene in a diagnostic laboratory. The aCGH method is a superior alternative to more conventional assays such as multiplex ligation-dependent probe amplification (MLPA). The combination of aCGH and sequence analysis will detect mutations in 98% of patients with the Duchenne or Becker muscular dystrophy. PMID:23476807

Phylogeny of sipunculan worms: A combined analysis of four gene regions and morphology.

PubMed

Schulze, Anja; Cutler, Edward B; Giribet, Gonzalo

2007-01-01

The intra-phyletic relationships of sipunculan worms were analyzed based on DNA sequence data from four gene regions and 58 morphological characters. Initially we analyzed the data under direct optimization using parsimony as optimality criterion. An implied alignment resulting from the direct optimization analysis was subsequently utilized to perform a Bayesian analysis with mixed models for the different data partitions. For this we applied a doublet model for the stem regions of the 18S rRNA. Both analyses support monophyly of Sipuncula and most of the same clades within the phylum. The analyses differ with respect to the relationships among the major groups but whereas the deep nodes in the direct optimization analysis generally show low jackknife support, they are supported by 100% posterior probability in the Bayesian analysis. Direct optimization has been useful for handling sequences of unequal length and generating conservative phylogenetic hypotheses whereas the Bayesian analysis under mixed models provided high resolution in the basal nodes of the tree.

Analysis of Polymorphism of Angiotensin System Genes (ACE, AGTR1, and AGT) and Gene ITGB3 in Patients with Arterial Hypertension in Combination with Metabolic Syndrome.

PubMed

Zotova, T Yu; Kubanova, A P; Azova, M M; Aissa, A Ait; Gigani, O O; Frolov, V A

2016-07-01

Changes in the frequencies of genotypes and mutant alleles of ACE, AGTR1, AGT, and ITGB3 genes were analyzed in patients with arterial hypertension coupled with metabolic syndrome (N=15) and compared with population data and corresponding parameters in patients with isolated hypertension (N=15). Increased frequency of genotype ID of ACE gene (hypertension predictor) was confirmed for both groups. In case of isolated hypertension, M235M genotype (gene AGT) was more frequent, in case of hypertension combined with metabolic syndrome, the frequency of genotypes A1166C and C1166C of the gene AGTR1 was higher in comparison with population data. Comparison of mutant allele frequencies in the two groups showed that at the 90% significance level allele T of the AGT gene was more frequent in hypertension coupled with metabolic syndrome (OR=1.26) and genotype A1166A of the AGTR1 gene was more frequent in the group with isolated hypertension.

Synergistic effects of arsenic trioxide combined with ascorbic acid in human osteosarcoma MG-63 cells: a systems biology analysis.

PubMed

Huang, X C; Maimaiti, X Y M; Huang, C W; Zhang, L; Li, Z B; Chen, Z G; Gao, X; Chen, T Y

2014-01-01

To further understand the synergistic mechanism of As2O3 and asscorbic acid (AA) in human osteosarcoma MG-63 cells by systems biology analysis. Human osteosarcoma MG-63 cells were treated by As2O3 (1 µmol/L), AA (62.5 µmol/L) and combined drugs (1 µmol/L As2O3 plus 62.5 µmol/L AA). Dynamic morphological characteristics were recorded by Cell-IQ system, and growth rate was calculated. Illumina beadchip assay was used to analyze the differential expression genes in different groups. Synergic effects on differential expression genes (DEGs) were analyzed by mixture linear model and singular value decomposition model. KEGG pathway annotations and GO enrichment analysis were performed to figure out the pathways involved in the synergic effects. We captured 1987 differential expression genes in combined therapy MG-63 cells. FAT1 gene was significantly upregulated in all three groups, which is a promising drug target as an important tumor suppressor analogue; meanwhile, HIST1H2BD gene was markedly downregulated in the As2O3 monotherapy group and the combined therapy group, which was found to be upregulated in prostatic cancer. These two genes might play critical roles in synergetic effects of AA and As2O3, although the exact mechanism needs further investigation. KEGG pathway analysis showed many DEGs were related with tight junction, and GO analysis also indicated that DEGs in the combined therapy cells gathered in occluding junction, apical junction complex, cell junction, and tight junction. AA potentiates the efficacy of As2O3 in MG-63 cells. Systems biology analysis showed the synergic effect on the DEGs.

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.

Marker-assisted combination of major genes for pathogen resistance in potato.

PubMed

Gebhardt, C; Bellin, D; Henselewski, H; Lehmann, W; Schwarzfischer, J; Valkonen, J P T

2006-05-01

Closely linked PCR-based markers facilitate the tracing and combining of resistance factors that have been introgressed previously into cultivated potato from different sources. Crosses were performed to combine the Ry ( adg ) gene for extreme resistance to Potato virus Y (PVY) with the Gro1 gene for resistance to the root cyst nematode Globodera rostochiensis and the Rx1 gene for extreme resistance to Potato virus X (PVX), or with resistance to potato wart (Synchytrium endobioticum). Marker-assisted selection (MAS) using four PCR-based diagnostic assays was applied to 110 F1 hybrids resulting from four 2x by 4x cross-combinations. Thirty tetraploid plants having the appropriate marker combinations were selected and tested for presence of the corresponding resistance traits. All plants tested showed the expected resistant phenotype. Unexpectedly, the plants segregated for additional resistance to pathotypes 1, 2 and 6 of S. endobioticum, which was subsequently shown to be inherited from the PVY resistant parents of the crosses. The selected plants can be used as sources of multiple resistance traits in pedigree breeding and are available from a potato germplasm bank.

ExAtlas: An interactive online tool for meta-analysis of gene expression data.

PubMed

Sharov, Alexei A; Schlessinger, David; Ko, Minoru S H

2015-12-01

We have developed ExAtlas, an on-line software tool for meta-analysis and visualization of gene expression data. In contrast to existing software tools, ExAtlas compares multi-component data sets and generates results for all combinations (e.g. all gene expression profiles versus all Gene Ontology annotations). ExAtlas handles both users' own data and data extracted semi-automatically from the public repository (GEO/NCBI database). ExAtlas provides a variety of tools for meta-analyses: (1) standard meta-analysis (fixed effects, random effects, z-score, and Fisher's methods); (2) analyses of global correlations between gene expression data sets; (3) gene set enrichment; (4) gene set overlap; (5) gene association by expression profile; (6) gene specificity; and (7) statistical analysis (ANOVA, pairwise comparison, and PCA). ExAtlas produces graphical outputs, including heatmaps, scatter-plots, bar-charts, and three-dimensional images. Some of the most widely used public data sets (e.g. GNF/BioGPS, Gene Ontology, KEGG, GAD phenotypes, BrainScan, ENCODE ChIP-seq, and protein-protein interaction) are pre-loaded and can be used for functional annotations.

Association analysis of bovine Foxa2 gene single sequence variant and haplotype combinations with growth traits in Chinese cattle.

PubMed

Liu, Mei; Li, Mijie; Wang, Shaoqiang; Xu, Yao; Lan, Xianyong; Li, Zhuanjian; Lei, Chuzhao; Yang, Dongying; Jia, Yutang; Chen, Hong

2014-02-25

Forkhead box A2 (Foxa2) has been recognized as one of the most potent transcriptional activators that is implicated in the control of feeding behavior and energy homeostasis. However, similar researches about the effects of genetic variations of Foxa2 gene on growth traits are lacking. Therefore, this study detected Foxa2 gene polymorphisms by DNA pool sequencing, PCR-RFLP and PCR-ACRS methods in 822 individuals from three Chinese cattle breeds. The results showed that four sequence variants (SVs) were screened, including two mutations (SV1, g. 7005 C>T and SV2, g. 7044 C>G) in intron 4, one mutation (SV3, g. 8449 A>G) in exon 5 and one mutation (SV4, g. 8537 T>C) in the 3'UTR. Notably, association analysis of the single mutations with growth traits in total individuals (at 24months) revealed that significant statistical difference was found in four SVs, and SV4 locus was highly significantly associated with growth traits throughout all three breeds (P<0.05 or P<0.01). Meanwhile, haplotype combination CCCCAGTC also indicated remarkably associated to better chest girth and body weight in Jiaxian Red cattle (P<0.05). We herein described a comprehensive study on the variability of bovine Foxa2 gene that was predictive of molecular markers in cattle breeding for the first time. Copyright © 2013 Elsevier B.V. All rights reserved.

Time-Course Gene Set Analysis for Longitudinal Gene Expression Data

PubMed Central

Hejblum, Boris P.; Skinner, Jason; Thiébaut, Rodolphe

2015-01-01

Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA) introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estimates. It allows to use all available repeated measurements while dealing with unbalanced data due to missing at random (MAR) measurements. TcGSA is a hypothesis driven method that identifies a priori defined gene sets with significant expression variations over time, taking into account the potential heterogeneity of expression within gene sets. When biological conditions are compared, the method indicates if the time patterns of gene sets significantly differ according to these conditions. The interest of the method is illustrated by its application to two real life datasets: an HIV therapeutic vaccine trial (DALIA-1 trial), and data from a recent study on influenza and pneumococcal vaccines. In the DALIA-1 trial TcGSA revealed a significant change in gene expression over time within 69 gene sets during vaccination, while a standard univariate individual gene analysis corrected for multiple testing as well as a standard a Gene Set Enrichment Analysis (GSEA) for time series both failed to detect any significant pattern change over time. When applied to the second illustrative data set, TcGSA allowed the identification of 4 gene sets finally found to be linked with the influenza vaccine too although they were found to be associated to the pneumococcal vaccine only in previous analyses. In our simulation study TcGSA exhibits good statistical properties, and an increased power compared to other approaches for analyzing time-course expression patterns of gene sets. The method is made available for the community through an R package. PMID:26111374

A Comprehensive Analysis of Nuclear-Encoded Mitochondrial Genes in Schizophrenia.

PubMed

Gonçalves, Vanessa F; Cappi, Carolina; Hagen, Christian M; Sequeira, Adolfo; Vawter, Marquis P; Derkach, Andriy; Zai, Clement C; Hedley, Paula L; Bybjerg-Grauholm, Jonas; Pouget, Jennie G; Cuperfain, Ari B; Sullivan, Patrick F; Christiansen, Michael; Kennedy, James L; Sun, Lei

2018-05-01

The genetic risk factors of schizophrenia (SCZ), a severe psychiatric disorder, are not yet fully understood. Multiple lines of evidence suggest that mitochondrial dysfunction may play a role in SCZ, but comprehensive association studies are lacking. We hypothesized that variants in nuclear-encoded mitochondrial genes influence susceptibility to SCZ. We conducted gene-based and gene-set analyses using summary association results from the Psychiatric Genomics Consortium Schizophrenia Phase 2 (PGC-SCZ2) genome-wide association study comprising 35,476 cases and 46,839 control subjects. We applied the MAGMA method to three sets of nuclear-encoded mitochondrial genes: oxidative phosphorylation genes, other nuclear-encoded mitochondrial genes, and genes involved in nucleus-mitochondria crosstalk. Furthermore, we conducted a replication study using the iPSYCH SCZ sample of 2290 cases and 21,621 control subjects. In the PGC-SCZ2 sample, 1186 mitochondrial genes were analyzed, among which 159 had p values < .05 and 19 remained significant after multiple testing correction. A meta-analysis of 818 genes combining the PGC-SCZ2 and iPSYCH samples resulted in 104 nominally significant and nine significant genes, suggesting a polygenic model for the nuclear-encoded mitochondrial genes. Gene-set analysis, however, did not show significant results. In an in silico protein-protein interaction network analysis, 14 mitochondrial genes interacted directly with 158 SCZ risk genes identified in PGC-SCZ2 (permutation p = .02), and aldosterone signaling in epithelial cells and mitochondrial dysfunction pathways appeared to be overrepresented in this network of mitochondrial and SCZ risk genes. This study provides evidence that specific aspects of mitochondrial function may play a role in SCZ, but we did not observe its broad involvement even using a large sample. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Bacterial and Pneumocystis Infections in the Lungs of Gene-Knockout Rabbits with Severe Combined Immunodeficiency

PubMed Central

Song, Jun; Wang, Guoshun; Hoenerhoff, Mark J.; Ruan, Jinxue; Yang, Dongshan; Zhang, Jifeng; Yang, Jibing; Lester, Patrick A.; Sigler, Robert; Bradley, Michael; Eckley, Samantha; Cornelius, Kelsey; Chen, Kong; Kolls, Jay K.; Peng, Li; Ma, Liang; Chen, Yuqing Eugene; Sun, Fei; Xu, Jie

2018-01-01

Using the CRISPR/Cas9 gene-editing technology, we recently produced a number of rabbits with mutations in immune function genes, including FOXN1, PRKDC, RAG1, RAG2, and IL2RG. Seven founder knockout rabbits (F0) and three male IL2RG null (−/y) F1 animals demonstrated severe combined immunodeficiency (SCID), characterized by absence or pronounced hypoplasia of the thymus and splenic white pulp, and absence of immature and mature T and B-lymphocytes in peripheral blood. Complete blood count analysis showed severe leukopenia and lymphocytopenia accompanied by severe neutrophilia. Without prophylactic antibiotics, the SCID rabbits universally succumbed to lung infections following weaning. Pathology examination revealed severe heterophilic bronchopneumonia caused by Bordetella bronchiseptica in several animals, but a consistent feature of lung lesions in all animals was a severe interstitial pneumonia caused by Pneumocystis oryctolagi, as confirmed by histological examination and PCR analysis of Pneumocystis genes. The results of this study suggest that these SCID rabbits could serve as a useful model for human SCID to investigate the disease pathogenesis and the development of gene and drug therapies. PMID:29593714

Molecular characterization and combined genotype association study of bovine cluster of differentiation 14 gene with clinical mastitis in crossbred dairy cattle

PubMed Central

Selvan, A. Sakthivel; Gupta, I. D.; Verma, A.; Chaudhari, M. V.; Magotra, A.

2016-01-01

Aim: The present study was undertaken with the objectives to characterize and to analyze combined genotypes of cluster of differentiation 14 (CD14) gene to explore its association with clinical mastitis in Karan Fries (KF) cows maintained in the National Dairy Research Institute herd, Karnal. Materials and Methods: Genomic DNA was extracted using blood of randomly selected 94 KF lactating cattle by phenol-chloroform method. After checking its quality and quantity, polymerase chain reaction (PCR) was carried out using six sets of reported gene-specific primers to amplify complete KF CD14 gene. The forward and reverse sequences for each PCR fragments were assembled to form complete sequence for the respective region of KF CD14 gene. The multiple sequence alignments of the edited sequence with the corresponding reference with reported Bos taurus sequence (EU148610.1) were performed with ClustalW software to identify single nucleotide polymorphisms (SNPs). Basic Local Alignment Search Tool analysis was performed to compare the sequence identity of KF CD14 gene with other species. The restriction fragment length polymorphism (RFLP) analysis was carried out in all KF cows using Helicobacter pylori 188I (Hpy188I) (contig 2) and Haemophilus influenzae I (HinfI) (contig 4) restriction enzyme (RE). Cows were assigned genotypes obtained by PCR-RFLP analysis, and association study was done using Chi-square (χ2) test. The genotypes of both contigs (loci) number 2 and 4 were combined with respect to each animal to construct combined genotype patterns. Results: Two types of sequences of KF were obtained: One with 2630 bp having one insertion at 616 nucleotide (nt) position and one deletion at 1117 nt position, and the another sequence was of 2629 bp having only one deletion at 615 nt position. ClustalW, multiple alignments of KF CD14 gene sequence with B. taurus cattle sequence (EU148610.1), revealed 24 nt changes (SNPs). Cows were also screened using PCR-RFLP with Hpy188I

Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

PubMed

Feng, Yinling; Wang, Xuefeng

2017-03-01

In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

Gene-Gene Combination Effect and Interactions among ABCA1, APOA1, SR-B1, and CETP Polymorphisms for Serum High-Density Lipoprotein-Cholesterol in the Japanese Population

PubMed Central

Nakamura, Akihiko; Niimura, Hideshi; Kuwabara, Kazuyo; Takezaki, Toshiro; Morita, Emi; Wakai, Kenji; Hamajima, Nobuyuki; Nishida, Yuichiro; Turin, Tanvir Chowdhury; Suzuki, Sadao; Ohnaka, Keizo; Uemura, Hirokazu; Ozaki, Etsuko; Hosono, Satoyo; Mikami, Haruo; Kubo, Michiaki; Tanaka, Hideo

2013-01-01

Background/Objective Gene-gene interactions in the reverse cholesterol transport system for high-density lipoprotein-cholesterol (HDL-C) are poorly understood. The present study observed gene-gene combination effect and interactions between single nucleotide polymorphisms (SNPs) in ABCA1, APOA1, SR-B1, and CETP in serum HDL-C from a cross-sectional study in the Japanese population. Methods The study population comprised 1,535 men and 1,515 women aged 35–69 years who were enrolled in the Japan Multi-Institutional Collaborative Cohort (J-MICC) Study. We selected 13 SNPs in the ABCA1, APOA1, CETP, and SR-B1 genes in the reverse cholesterol transport system. The effects of genetic and environmental factors were assessed using general linear and logistic regression models after adjusting for age, sex, and region. Principal Findings Alcohol consumption and daily activity were positively associated with HDL-C levels, whereas smoking had a negative relationship. The T allele of CETP, rs3764261, was correlated with higher HDL-C levels and had the highest coefficient (2.93 mg/dL/allele) among the 13 SNPs, which was statistically significant after applying the Bonferroni correction (p<0.001). Gene-gene combination analysis revealed that CETP rs3764261 was associated with high HDL-C levels with any combination of SNPs from ABCA1, APOA1, and SR-B1, although no gene-gene interaction was apparent. An increasing trend for serum HDL-C was also observed with an increasing number of alleles (p<0.001). Conclusions The present study identified a multiplier effect from a polymorphism in CETP with ABCA1, APOA1, and SR-B1, as well as a dose-dependence according to the number of alleles present. PMID:24376512

Effect of the absolute statistic on gene-sampling gene-set analysis methods.

PubMed

Nam, Dougu

2017-06-01

Gene-set enrichment analysis and its modified versions have commonly been used for identifying altered functions or pathways in disease from microarray data. In particular, the simple gene-sampling gene-set analysis methods have been heavily used for datasets with only a few sample replicates. The biggest problem with this approach is the highly inflated false-positive rate. In this paper, the effect of absolute gene statistic on gene-sampling gene-set analysis methods is systematically investigated. Thus far, the absolute gene statistic has merely been regarded as a supplementary method for capturing the bidirectional changes in each gene set. Here, it is shown that incorporating the absolute gene statistic in gene-sampling gene-set analysis substantially reduces the false-positive rate and improves the overall discriminatory ability. Its effect was investigated by power, false-positive rate, and receiver operating curve for a number of simulated and real datasets. The performances of gene-set analysis methods in one-tailed (genome-wide association study) and two-tailed (gene expression data) tests were also compared and discussed.

Clinical and multiple gene expression variables in survival analysis of breast cancer: Analysis with the hypertabastic survival model

PubMed Central

2012-01-01

Background We explore the benefits of applying a new proportional hazard model to analyze survival of breast cancer patients. As a parametric model, the hypertabastic survival model offers a closer fit to experimental data than Cox regression, and furthermore provides explicit survival and hazard functions which can be used as additional tools in the survival analysis. In addition, one of our main concerns is utilization of multiple gene expression variables. Our analysis treats the important issue of interaction of different gene signatures in the survival analysis. Methods The hypertabastic proportional hazards model was applied in survival analysis of breast cancer patients. This model was compared, using statistical measures of goodness of fit, with models based on the semi-parametric Cox proportional hazards model and the parametric log-logistic and Weibull models. The explicit functions for hazard and survival were then used to analyze the dynamic behavior of hazard and survival functions. Results The hypertabastic model provided the best fit among all the models considered. Use of multiple gene expression variables also provided a considerable improvement in the goodness of fit of the model, as compared to use of only one. By utilizing the explicit survival and hazard functions provided by the model, we were able to determine the magnitude of the maximum rate of increase in hazard, and the maximum rate of decrease in survival, as well as the times when these occurred. We explore the influence of each gene expression variable on these extrema. Furthermore, in the cases of continuous gene expression variables, represented by a measure of correlation, we were able to investigate the dynamics with respect to changes in gene expression. Conclusions We observed that use of three different gene signatures in the model provided a greater combined effect and allowed us to assess the relative importance of each in determination of outcome in this data set. These

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

The combination of dimethoxycurcumin with DNA methylation inhibitor enhances gene re-expression of promoter-methylated genes and antagonizes their cytotoxic effect

PubMed Central

Hassan, Hazem E.; Keita, Jean-Arnaud; Narayan, Lawrence; Brady, Sean M.; Frederick, Richard; Carlson, Samuel; C. Glass, Karen; Natesan, Senthil; Buttolph, Thomm; Fandy, Tamer E.

2016-01-01

ABSTRACT Curcumin and its analogs exhibited antileukemic activity either as single agent or in combination therapy. Dimethoxycurcumin (DMC) is a more metabolically stable curcumin analog that was shown to induce the expression of promoter-methylated genes without reversing DNA methylation. Accordingly, co-treatment with DMC and DNA methyltransferase (DNMT) inhibitors could hypothetically enhance the re-expression of promoter-methylated tumor suppressor genes. In this study, we investigated the cytotoxic effects and epigenetic changes associated with the combination of DMC and the DNMT inhibitor decitabine (DAC) in primary leukemia samples and cell lines. The combination demonstrated antagonistic cytotoxic effects and was minimally cytotoxic to primary leukemia cells. The combination did not affect the metabolic stability of DMC. Although the combination enhanced the downregulation of nuclear DNMT proteins, the hypomethylating activity of the combination was not increased significantly compared to DAC alone. On the other hand, the combination significantly increased H3K27 acetylation (H3K27Ac) compared to the single agents near the promoter region of promoter-methylated genes. Furthermore, sequential chromatin immunoprecipitation (ChIP) and DNA pyrosequencing of the chromatin-enriched H3K27Ac did not show any significant decrease in DNA methylation compared to other regions. Consequently, the enhanced induction of promoter-methylated genes by the combination compared to DAC alone is mediated by a mechanism that involves increased histone acetylation and not through potentiation of the DNA hypomethylating activity of DAC. Collectively, our results provide the mechanistic basis for further characterization of this combination in leukemia animal models and early phase clinical trials. PMID:27588609

An effective fuzzy kernel clustering analysis approach for gene expression data.

PubMed

Sun, Lin; Xu, Jiucheng; Yin, Jiaojiao

2015-01-01

Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approach to fuzzy kernel clustering analysis (FKCA) that identifies desired cluster number and obtains more steady results for gene expression data. First of all, to optimize characteristic differences and estimate optimal cluster number, Gaussian kernel function is introduced to improve spectrum analysis method (SAM). By combining subtractive clustering with max-min distance mean, maximum distance method (MDM) is proposed to determine cluster centers. Then, the corresponding steps of improved SAM (ISAM) and MDM are given respectively, whose superiority and stability are illustrated through performing experimental comparisons on gene expression data. Finally, by introducing ISAM and MDM into FKCA, an effective improved FKCA algorithm is proposed. Experimental results from public gene expression data and UCI database show that the proposed algorithms are feasible for cluster analysis, and the clustering accuracy is higher than the other related clustering algorithms.

Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations.

PubMed

Leong, Ivone U S; Stuckey, Alexander; Lai, Daniel; Skinner, Jonathan R; Love, Donald R

2015-05-13

Long QT syndrome (LQTS) is an autosomal dominant condition predisposing to sudden death from malignant arrhythmia. Genetic testing identifies many missense single nucleotide variants of uncertain pathogenicity. Establishing genetic pathogenicity is an essential prerequisite to family cascade screening. Many laboratories use in silico prediction tools, either alone or in combination, or metaservers, in order to predict pathogenicity; however, their accuracy in the context of LQTS is unknown. We evaluated the accuracy of five in silico programs and two metaservers in the analysis of LQTS 1-3 gene variants. The in silico tools SIFT, PolyPhen-2, PROVEAN, SNPs&GO and SNAP, either alone or in all possible combinations, and the metaservers Meta-SNP and PredictSNP, were tested on 312 KCNQ1, KCNH2 and SCN5A gene variants that have previously been characterised by either in vitro or co-segregation studies as either "pathogenic" (283) or "benign" (29). The accuracy, sensitivity, specificity and Matthews Correlation Coefficient (MCC) were calculated to determine the best combination of in silico tools for each LQTS gene, and when all genes are combined. The best combination of in silico tools for KCNQ1 is PROVEAN, SNPs&GO and SIFT (accuracy 92.7%, sensitivity 93.1%, specificity 100% and MCC 0.70). The best combination of in silico tools for KCNH2 is SIFT and PROVEAN or PROVEAN, SNPs&GO and SIFT. Both combinations have the same scores for accuracy (91.1%), sensitivity (91.5%), specificity (87.5%) and MCC (0.62). In the case of SCN5A, SNAP and PROVEAN provided the best combination (accuracy 81.4%, sensitivity 86.9%, specificity 50.0%, and MCC 0.32). When all three LQT genes are combined, SIFT, PROVEAN and SNAP is the combination with the best performance (accuracy 82.7%, sensitivity 83.0%, specificity 80.0%, and MCC 0.44). Both metaservers performed better than the single in silico tools; however, they did not perform better than the best performing combination of in silico

Combination Gene Therapy for Liver Metastasis of Colon Carcinoma in vivo

NASA Astrophysics Data System (ADS)

Chen, Shu-Hsai; Chen, X. H. Li; Wang, Yibin; Kosai, Ken-Ichiro; Finegold, Milton J.; Rich, Susan S.

1995-03-01

The efficacy of combination therapy with a "suicide gene" and a cytokine gene to treat metastatic colon carcinoma in the liver was investigated. Tumor in the liver was generated by intrahepatic injection of a colon carcinoma cell line (MCA-26) in syngeneic BALB/c mice. Recombinant adenoviral vectors containing various control and therapeutic genes were injected directly into the solid tumors, followed by treatment with ganciclovir. While the tumors continued to grow in all animals treated with a control vector or a mouse interleukin 2 vector, those treated with a herpes simplex virus thymidine kinase vector, with or without the coadministration of the mouse interleukin 2 vector, exhibited dramatic necrosis and regression. However, only animals treated with both vectors developed an effective systemic antitumoral immunity against challenges of tumorigenic doses of parental tumor cells inoculated at distant sites. The antitumoral immunity was associated with the presence of MCA-26 tumor-specific cytolytic CD8^+ T lymphocytes. The results suggest that combination suicide and cytokine gene therapy in vivo can be a powerful approach for treatment of metastatic colon carcinoma in the liver.

MAGMA: Generalized Gene-Set Analysis of GWAS Data

PubMed Central

de Leeuw, Christiaan A.; Mooij, Joris M.; Heskes, Tom; Posthuma, Danielle

2015-01-01

By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical power for most methods is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard to detect, and the reliance on permutation to compute p-values tends to make the analysis computationally very expensive. To address these issues we have developed MAGMA, a novel tool for gene and gene-set analysis. The gene analysis is based on a multiple regression model, to provide better statistical performance. The gene-set analysis is built as a separate layer around the gene analysis for additional flexibility. This gene-set analysis also uses a regression structure to allow generalization to analysis of continuous properties of genes and simultaneous analysis of multiple gene sets and other gene properties. Simulations and an analysis of Crohn’s Disease data are used to evaluate the performance of MAGMA and to compare it to a number of other gene and gene-set analysis tools. The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohn’s Disease while maintaining a correct type 1 error rate. Moreover, the MAGMA analysis of the Crohn’s Disease data was found to be considerably faster as well. PMID:25885710

MAGMA: generalized gene-set analysis of GWAS data.

PubMed

de Leeuw, Christiaan A; Mooij, Joris M; Heskes, Tom; Posthuma, Danielle

2015-04-01

By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical power for most methods is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard to detect, and the reliance on permutation to compute p-values tends to make the analysis computationally very expensive. To address these issues we have developed MAGMA, a novel tool for gene and gene-set analysis. The gene analysis is based on a multiple regression model, to provide better statistical performance. The gene-set analysis is built as a separate layer around the gene analysis for additional flexibility. This gene-set analysis also uses a regression structure to allow generalization to analysis of continuous properties of genes and simultaneous analysis of multiple gene sets and other gene properties. Simulations and an analysis of Crohn's Disease data are used to evaluate the performance of MAGMA and to compare it to a number of other gene and gene-set analysis tools. The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohn's Disease while maintaining a correct type 1 error rate. Moreover, the MAGMA analysis of the Crohn's Disease data was found to be considerably faster as well.

PRGdb: a bioinformatics platform for plant resistance gene analysis

PubMed Central

Sanseverino, Walter; Roma, Guglielmo; De Simone, Marco; Faino, Luigi; Melito, Sara; Stupka, Elia; Frusciante, Luigi; Ercolano, Maria Raffaella

2010-01-01

PRGdb is a web accessible open-source (http://www.prgdb.org) database that represents the first bioinformatic resource providing a comprehensive overview of resistance genes (R-genes) in plants. PRGdb holds more than 16 000 known and putative R-genes belonging to 192 plant species challenged by 115 different pathogens and linked with useful biological information. The complete database includes a set of 73 manually curated reference R-genes, 6308 putative R-genes collected from NCBI and 10463 computationally predicted putative R-genes. Thanks to a user-friendly interface, data can be examined using different query tools. A home-made prediction pipeline called Disease Resistance Analysis and Gene Orthology (DRAGO), based on reference R-gene sequence data, was developed to search for plant resistance genes in public datasets such as Unigene and Genbank. New putative R-gene classes containing unknown domain combinations were discovered and characterized. The development of the PRG platform represents an important starting point to conduct various experimental tasks. The inferred cross-link between genomic and phenotypic information allows access to a large body of information to find answers to several biological questions. The database structure also permits easy integration with other data types and opens up prospects for future implementations. PMID:19906694

Network Analysis of Human Genes Influencing Susceptibility to Mycobacterial Infections

PubMed Central

Lipner, Ettie M.; Garcia, Benjamin J.; Strong, Michael

2016-01-01

Tuberculosis and nontuberculous mycobacterial infections constitute a high burden of pulmonary disease in humans, resulting in over 1.5 million deaths per year. Building on the premise that genetic factors influence the instance, progression, and defense of infectious disease, we undertook a systems biology approach to investigate relationships among genetic factors that may play a role in increased susceptibility or control of mycobacterial infections. We combined literature and database mining with network analysis and pathway enrichment analysis to examine genes, pathways, and networks, involved in the human response to Mycobacterium tuberculosis and nontuberculous mycobacterial infections. This approach allowed us to examine functional relationships among reported genes, and to identify novel genes and enriched pathways that may play a role in mycobacterial susceptibility or control. Our findings suggest that the primary pathways and genes influencing mycobacterial infection control involve an interplay between innate and adaptive immune proteins and pathways. Signaling pathways involved in autoimmune disease were significantly enriched as revealed in our networks. Mycobacterial disease susceptibility networks were also examined within the context of gene-chemical relationships, in order to identify putative drugs and nutrients with potential beneficial immunomodulatory or anti-mycobacterial effects. PMID:26751573

PCAN: phenotype consensus analysis to support disease-gene association.

PubMed

Godard, Patrice; Page, Matthew

2016-12-07

Bridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy. Approaches that can flexibly and intuitively, integrate known gene-phenotype associations in the context of molecular signaling networks are vital to effectively prioritize and biologically interpret genes underlying disease traits of interest. We describe Phenotype Consensus Analysis (PCAN); a method to assess the consensus semantic similarity of phenotypes in a candidate gene's signaling neighborhood. We demonstrate that significant phenotype consensus (p < 0.05) is observable for ~67% of 4,549 OMIM disease-gene associations, using a combination of high quality String interactions + Metabase pathways and use Joubert Syndrome to demonstrate the ease with which a significant result can be interrogated to highlight discriminatory traits linked to mechanistically related genes. We advocate phenotype consensus as an intuitive and versatile method to aid disease-gene association, which naturally lends itself to the mechanistic deconvolution of diverse phenotypes. We provide PCAN to the community as an R package ( http://bioconductor.org/packages/PCAN/ ) to allow flexible configuration, extension and standalone use or integration to supplement existing gene prioritization workflows.

A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer.

PubMed

Yang, Mary Qu; Li, Dan; Yang, William; Zhang, Yifan; Liu, Jun; Tong, Weida

2017-01-01

Clear cell renal cell carcinoma (ccRCC) is the most common and most aggressive form of renal cell cancer (RCC). The incidence of RCC has increased steadily in recent years. The pathogenesis of renal cell cancer remains poorly understood. Many of the tumor suppressor genes, oncogenes, and dysregulated pathways in ccRCC need to be revealed for improvement of the overall clinical outlook of the disease. Here, we developed a systems biology approach to prioritize the somatic mutated genes that lead to dysregulation of pathways in ccRCC. The method integrated multi-layer information to infer causative mutations and disease genes. First, we identified differential gene modules in ccRCC by coupling transcriptome and protein-protein interactions. Each of these modules consisted of interacting genes that were involved in similar biological processes and their combined expression alterations were significantly associated with disease type. Then, subsequent gene module-based eQTL analysis revealed somatic mutated genes that had driven the expression alterations of differential gene modules. Our study yielded a list of candidate disease genes, including several known ccRCC causative genes such as BAP1 and PBRM1 , as well as novel genes such as NOD2, RRM1, CSRNP1, SLC4A2, TTLL1 and CNTN1. The differential gene modules and their driver genes revealed by our study provided a new perspective for understanding the molecular mechanisms underlying the disease. Moreover, we validated the results in independent ccRCC patient datasets. Our study provided a new method for prioritizing disease genes and pathways.

The limitations of simple gene set enrichment analysis assuming gene independence.

PubMed

Tamayo, Pablo; Steinhardt, George; Liberzon, Arthur; Mesirov, Jill P

2016-02-01

Since its first publication in 2003, the Gene Set Enrichment Analysis method, based on the Kolmogorov-Smirnov statistic, has been heavily used, modified, and also questioned. Recently a simplified approach using a one-sample t-test score to assess enrichment and ignoring gene-gene correlations was proposed by Irizarry et al. 2009 as a serious contender. The argument criticizes Gene Set Enrichment Analysis's nonparametric nature and its use of an empirical null distribution as unnecessary and hard to compute. We refute these claims by careful consideration of the assumptions of the simplified method and its results, including a comparison with Gene Set Enrichment Analysis's on a large benchmark set of 50 datasets. Our results provide strong empirical evidence that gene-gene correlations cannot be ignored due to the significant variance inflation they produced on the enrichment scores and should be taken into account when estimating gene set enrichment significance. In addition, we discuss the challenges that the complex correlation structure and multi-modality of gene sets pose more generally for gene set enrichment methods. © The Author(s) 2012.

Comparative genomic analysis of the PKS genes in five species and expression analysis in upland cotton

PubMed Central

Cheng, Xi; Wang, Yanan; Abdullah, Muhammad; Li, Manli; Li, Dahui; Gao, Junshan

2017-01-01

Plant type III polyketide synthase (PKS) can catalyse the formation of a series of secondary metabolites with different structures and different biological functions; the enzyme plays an important role in plant growth, development and resistance to stress. At present, the PKS gene has been identified and studied in a variety of plants. Here, we identified 11 PKS genes from upland cotton (Gossypium hirsutum) and compared them with 41 PKS genes in Populus tremula, Vitis vinifera, Malus domestica and Arabidopsis thaliana. According to the phylogenetic tree, a total of 52 PKS genes can be divided into four subfamilies (I–IV). The analysis of gene structures and conserved motifs revealed that most of the PKS genes were composed of two exons and one intron and there are two characteristic conserved domains (Chal_sti_synt_N and Chal_sti_synt_C) of the PKS gene family. In our study of the five species, gene duplication was found in addition to Arabidopsis thaliana and we determined that purifying selection has been of great significance in maintaining the function of PKS gene family. From qRT-PCR analysis and a combination of the role of the accumulation of proanthocyanidins (PAs) in brown cotton fibers, we concluded that five PKS genes are candidate genes involved in brown cotton fiber pigment synthesis. These results are important for the further study of brown cotton PKS genes. It not only reveals the relationship between PKS gene family and pigment in brown cotton, but also creates conditions for improving the quality of brown cotton fiber. PMID:29104824

Meta-analysis identifies a MECOM gene as a novel predisposing factor of osteoporotic fracture

PubMed Central

Hwang, Joo-Yeon; Lee, Seung Hun; Go, Min Jin; Kim, Beom-Jun; Kou, Ikuyo; Ikegawa, Shiro; Guo, Yan; Deng, Hong-Wen; Raychaudhuri, Soumya; Kim, Young Jin; Oh, Ji Hee; Kim, Youngdoe; Moon, Sanghoon; Kim, Dong-Joon; Koo, Heejo; Cha, My-Jung; Lee, Min Hye; Yun, Ji Young; Yoo, Hye-Sook; Kang, Young-Ah; Cho, Eun-Hee; Kim, Sang-Wook; Oh, Ki Won; Kang, Moo II; Son, Ho Young; Kim, Shin-Yoon; Kim, Ghi Su; Han, Bok-Ghee; Cho, Yoon Shin; Cho, Myeong-Chan; Lee, Jong-Young; Koh, Jung-Min

2014-01-01

Background Osteoporotic fracture (OF) as a clinical endpoint is a major complication of osteoporosis. To screen for OF susceptibility genes, we performed a genome-wide association study and carried out de novo replication analysis of an East Asian population. Methods Association was tested using a logistic regression analysis. A meta-analysis was performed on the combined results using effect size and standard errors estimated for each study. Results In a combined meta-analysis of a discovery cohort (288 cases and 1139 controls), three hospital based sets in replication stage I (462 cases and 1745 controls), and an independent ethnic group in replication stage II (369 cases and 560 for controls), we identified a new locus associated with OF (rs784288 in the MECOM gene) that showed genome-wide significance (p=3.59×10−8; OR 1.39). RNA interference revealed that a MECOM knockdown suppresses osteoclastogenesis. Conclusions Our findings provide new insights into the genetic architecture underlying OF in East Asians. PMID:23349225

Combined Chromatin and Expression Analysis Reveals Specific Regulatory Mechanisms within Cytokine Genes in the Macrophage Early Immune Response

PubMed Central

Emanuelsson, Olof; Sennblad, Bengt; Pirmoradian Najafabadi, Mohammad; Folkersen, Lasse; Mälarstig, Anders; Lagergren, Jens; Eriksson, Per; Hamsten, Anders; Odeberg, Jacob

2012-01-01

Macrophages play a critical role in innate immunity, and the expression of early response genes orchestrate much of the initial response of the immune system. Macrophages undergo extensive transcriptional reprogramming in response to inflammatory stimuli such as Lipopolysaccharide (LPS). To identify gene transcription regulation patterns involved in early innate immune responses, we used two genome-wide approaches - gene expression profiling and chromatin immunoprecipitation-sequencing (ChIP-seq) analysis. We examined the effect of 2 hrs LPS stimulation on early gene expression and its relation to chromatin remodeling (H3 acetylation; H3Ac) and promoter binding of Sp1 and RNA polymerase II phosphorylated at serine 5 (S5P RNAPII), which is a marker for transcriptional initiation. Our results indicate novel and alternative gene regulatory mechanisms for certain proinflammatory genes. We identified two groups of up-regulated inflammatory genes with respect to chromatin modification and promoter features. One group, including highly up-regulated genes such as tumor necrosis factor (TNF), was characterized by H3Ac, high CpG content and lack of TATA boxes. The second group, containing inflammatory mediators (interleukins and CCL chemokines), was up-regulated upon LPS stimulation despite lacking H3Ac in their annotated promoters, which were low in CpG content but did contain TATA boxes. Genome-wide analysis showed that few H3Ac peaks were unique to either +/−LPS condition. However, within these, an unpacking/expansion of already existing H3Ac peaks was observed upon LPS stimulation. In contrast, a significant proportion of S5P RNAPII peaks (approx 40%) was unique to either condition. Furthermore, data indicated a large portion of previously unannotated TSSs, particularly in LPS-stimulated macrophages, where only 28% of unique S5P RNAPII peaks overlap annotated promoters. The regulation of the inflammatory response appears to occur in a very specific manner at the

Analysis of differential gene expression by bead-based fiber-optic array in nonfunctioning pituitary adenomas.

PubMed

Jiang, Z; Gui, S; Zhang, Y

2011-05-01

Nonfunctioning pituitary adenomas (NFPAs) are relatively common, accounting for 30% of all pituitary adenomas; however, their pathogenesis remains enigmatic. To explore the possible pathogenesis of NFPAs, we used fiber-optic BeadArray to examine gene expression in 5 NFPAs compared with 3 normal pituitaries. 4 differentially expressed genes were chosen randomly for validation by reverse transcriptase-real time quantitative polymerase chain reaction (RT-qPCR). We then analyzed the differentially expressed gene profile with Kyoto Encyclopedia of Genes and Genomes (KEGG). The array analysis indentified significant increases in the expression of 1,402 genes and 383 expressed sequence tags (ESTs), and decreases in 1,697 genes and 113 ESTs in the NFPAs. Bioinformatic and pathway analysis showed that the genes HIGD1B, FAM5C, PMAIP1 and the pathway cell-cycle regulation may play an important role in tumorigenesis and progression of NFPAs. Our data suggest fiber-optic BeadArray combined with pathway analysis of differential gene expression profile appears to be a valid approach for investigating the pathogenesis of tumors. © Georg Thieme Verlag KG Stuttgart · New York.

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.

Bone Metastasis in Advanced Breast Cancer: Analysis of Gene Expression Microarray.

PubMed

Cosphiadi, Irawan; Atmakusumah, Tubagus D; Siregar, Nurjati C; Muthalib, Abdul; Harahap, Alida; Mansyur, Muchtarruddin

2018-03-08

Approximately 30% to 40% of breast cancer recurrences involve bone metastasis (BM). Certain genes have been linked to BM; however, none have been able to predict bone involvement. In this study, we analyzed gene expression profiles in advanced breast cancer patients to elucidate genes that can be used to predict BM. A total of 92 advanced breast cancer patients, including 46 patients with BM and 46 patients without BM, were identified for this study. Immunohistochemistry and gene expression analysis was performed on 81 formalin-fixed paraffin-embedded samples. Data were collected through medical records, and gene expression of 200 selected genes compiled from 6 previous studies was performed using NanoString nCounter. Genetic expression profiles showed that 22 genes were significantly differentially expressed between breast cancer patients with metastasis in bone and other organs (BM+) and non-BM, whereas subjects with only BM showed 17 significantly differentially expressed genes. The following genes were associated with an increasing incidence of BM in the BM+ group: estrogen receptor 1 (ESR1), GATA binding protein 3 (GATA3), and melanophilin with an area under the curve (AUC) of 0.804. In the BM group, the following genes were associated with an increasing incidence of BM: ESR1, progesterone receptor, B-cell lymphoma 2, Rab escort protein, N-acetyltransferase 1, GATA3, annexin A9, and chromosome 9 open reading frame 116. ESR1 and GATA3 showed an increased strength of association with an AUC of 0.928. A combination of the identified 3 genes in BM+ and 8 genes in BM showed better prediction than did each individual gene, and this combination can be used as a training set. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

A central goal of human genetics is to identify and characterize susceptibility genes for common complex human diseases. An important challenge in this endeavor is the modeling of gene-gene interaction or epistasis that can result in non-additivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as machine learning alternative to parametric logistic regression for detecting interactions in absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modeling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fisher’s Exact Test rather than a predetermined threshold. The advantage of this approach is that only those genotype combinations that are determined to be statistically significant are considered in the MDR analysis. We use two simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case-control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene-gene interactions in genotype data from a population-based study of bladder cancer in New Hampshire. PMID:21091664

A Comprehensive Analysis of Transcript-Supported De Novo Genes in Saccharomyces sensu stricto Yeasts

PubMed Central

Lu, Tzu-Chiao; Leu, Jun-Yi; Lin, Wen-Chang

2017-01-01

Abstract Novel genes arising from random DNA sequences (de novo genes) have been suggested to be widespread in the genomes of different organisms. However, our knowledge about the origin and evolution of de novo genes is still limited. To systematically understand the general features of de novo genes, we established a robust pipeline to analyze >20,000 transcript-supported coding sequences (CDSs) from the budding yeast Saccharomyces cerevisiae. Our analysis pipeline combined phylogeny, synteny, and sequence alignment information to identify possible orthologs across 20 Saccharomycetaceae yeasts and discovered 4,340 S. cerevisiae-specific de novo genes and 8,871 S. sensu stricto-specific de novo genes. We further combine information on CDS positions and transcript structures to show that >65% of de novo genes arose from transcript isoforms of ancient genes, especially in the upstream and internal regions of ancient genes. Fourteen identified de novo genes with high transcript levels were chosen to verify their protein expressions. Ten of them, including eight transcript isoform-associated CDSs, showed translation signals and five proteins exhibited specific cytosolic localizations. Our results suggest that de novo genes frequently arise in the S. sensu stricto complex and have the potential to be quickly integrated into ancient cellular network. PMID:28981695

Simultaneous mutation detection of three homoeologous genes in wheat by High Resolution Melting analysis and Mutation Surveyor.

PubMed

Dong, Chongmei; Vincent, Kate; Sharp, Peter

2009-12-04

TILLING (Targeting Induced Local Lesions IN Genomes) is a powerful tool for reverse genetics, combining traditional chemical mutagenesis with high-throughput PCR-based mutation detection to discover induced mutations that alter protein function. The most popular mutation detection method for TILLING is a mismatch cleavage assay using the endonuclease CelI. For this method, locus-specific PCR is essential. Most wheat genes are present as three similar sequences with high homology in exons and low homology in introns. Locus-specific primers can usually be designed in introns. However, it is sometimes difficult to design locus-specific PCR primers in a conserved region with high homology among the three homoeologous genes, or in a gene lacking introns, or if information on introns is not available. Here we describe a mutation detection method which combines High Resolution Melting (HRM) analysis of mixed PCR amplicons containing three homoeologous gene fragments and sequence analysis using Mutation Surveyor software, aimed at simultaneous detection of mutations in three homoeologous genes. We demonstrate that High Resolution Melting (HRM) analysis can be used in mutation scans in mixed PCR amplicons containing three homoeologous gene fragments. Combining HRM scanning with sequence analysis using Mutation Surveyor is sensitive enough to detect a single nucleotide mutation in the heterozygous state in a mixed PCR amplicon containing three homoeoloci. The method was tested and validated in an EMS (ethylmethane sulfonate)-treated wheat TILLING population, screening mutations in the carboxyl terminal domain of the Starch Synthase II (SSII) gene. Selected identified mutations of interest can be further analysed by cloning to confirm the mutation and determine the genomic origin of the mutation. Polyploidy is common in plants. Conserved regions of a gene often represent functional domains and have high sequence similarity between homoeologous loci. The method described here

Genome-wide analysis of YY2 versus YY1 target genes

PubMed Central

Chen, Li; Shioda, Toshi; Coser, Kathryn R.; Lynch, Mary C.; Yang, Chuanwei; Schmidt, Emmett V.

2010-01-01

Yin Yang 1 (YY1) is a critical transcription factor controlling cell proliferation, development and DNA damage responses. Retrotranspositions have independently generated additional YY family members in multiple species. Although Drosophila YY1 [pleiohomeotic (Pho)] and its homolog [pleiohomeotic-like (Phol)] redundantly control homeotic gene expression, the regulatory contributions of YY1-homologs have not yet been examined in other species. Indeed, targets for the mammalian YY1 homolog YY2 are completely unknown. Using gene set enrichment analysis, we found that lentiviral constructs containing short hairpin loop inhibitory RNAs for human YY1 (shYY1) and its homolog YY2 (shYY2) caused significant changes in both shared and distinguishable gene sets in human cells. Ribosomal protein genes were the most significant gene set upregulated by both shYY1 and shYY2, although combined shYY1/2 knock downs were not additive. In contrast, shYY2 reversed the anti-proliferative effects of shYY1, and shYY2 particularly altered UV damage response, platelet-specific and mitochondrial function genes. We found that decreases in YY1 or YY2 caused inverse changes in UV sensitivity, and that their combined loss reversed their respective individual effects. Our studies show that human YY2 is not redundant to YY1, and YY2 is a significant regulator of genes previously identified as uniquely responding to YY1. PMID:20215434

A combined analysis of genome-wide expression profiling of bipolar disorder in human prefrontal cortex.

PubMed

Wang, Jinglu; Qu, Susu; Wang, Weixiao; Guo, Liyuan; Zhang, Kunlin; Chang, Suhua; Wang, Jing

2016-11-01

Numbers of gene expression profiling studies of bipolar disorder have been published. Besides different array chips and tissues, variety of the data processes in different cohorts aggravated the inconsistency of results of these genome-wide gene expression profiling studies. By searching the gene expression databases, we obtained six data sets for prefrontal cortex (PFC) of bipolar disorder with raw data and combinable platforms. We used standardized pre-processing and quality control procedures to analyze each data set separately and then combined them into a large gene expression matrix with 101 bipolar disorder subjects and 106 controls. A standard linear mixed-effects model was used to calculate the differentially expressed genes (DEGs). Multiple levels of sensitivity analyses and cross validation with genetic data were conducted. Functional and network analyses were carried out on basis of the DEGs. In the result, we identified 198 unique differentially expressed genes in the PFC of bipolar disorder and control. Among them, 115 DEGs were robust to at least three leave-one-out tests or different pre-processing methods; 51 DEGs were validated with genetic association signals. Pathway enrichment analysis showed these DEGs were related with regulation of neurological system, cell death and apoptosis, and several basic binding processes. Protein-protein interaction network further identified one key hub gene. We have contributed the most comprehensive integrated analysis of bipolar disorder expression profiling studies in PFC to date. The DEGs, especially those with multiple validations, may denote a common signature of bipolar disorder and contribute to the pathogenesis of disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

Familial aggregation analysis of gene expressions

PubMed Central

Rao, Shao-Qi; Xu, Liang-De; Zhang, Guang-Mei; Li, Xia; Li, Lin; Shen, Gong-Qing; Jiang, Yang; Yang, Yue-Ying; Gong, Bin-Sheng; Jiang, Wei; Zhang, Fan; Xiao, Yun; Wang, Qing K

2007-01-01

Traditional studies of familial aggregation are aimed at defining the genetic (and non-genetic) causes of a disease from physiological or clinical traits. However, there has been little attempt to use genome-wide gene expressions, the direct phenotypic measures of genes, as the traits to investigate several extended issues regarding the distributions of familially aggregated genes on chromosomes or in functions. In this study we conducted a genome-wide familial aggregation analysis by using the in vitro cell gene expressions of 3300 human autosome genes (Problem 1 data provided to Genetic Analysis Workshop 15) in order to answer three basic genetics questions. First, we investigated how gene expressions aggregate among different types (degrees) of relative pairs. Second, we conducted a bioinformatics analysis of highly familially aggregated genes to see how they are distributed on chromosomes. Third, we performed a gene ontology enrichment test of familially aggregated genes to find evidence to support their functional consensus. The results indicated that 1) gene expressions did aggregate in families, especially between sibs. Of 3300 human genes analyzed, there were a total of 1105 genes with one or more significant (empirical p < 0.05) familial correlation; 2) there were several genomic hot spots where highly familially aggregated genes (e.g., the chromosome 6 HLA genes cluster) were clustered; 3) as we expected, gene ontology enrichment tests revealed that the 1105 genes were aggregating not only in families but also in functional categories. PMID:18466548

Combined protein construct and synthetic gene engineering for heterologous protein expression and crystallization using Gene Composer

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

Raymond, Amy; Lovell, Scott; Lorimer, Don

2009-12-01

With the goal of improving yield and success rates of heterologous protein production for structural studies we have developed the database and algorithm software package Gene Composer. This freely available electronic tool facilitates the information-rich design of protein constructs and their engineered synthetic gene sequences, as detailed in the accompanying manuscript. In this report, we compare heterologous protein expression levels from native sequences to that of codon engineered synthetic gene constructs designed by Gene Composer. A test set of proteins including a human kinase (P38{alpha}), viral polymerase (HCV NS5B), and bacterial structural protein (FtsZ) were expressed in both E. colimore » and a cell-free wheat germ translation system. We also compare the protein expression levels in E. coli for a set of 11 different proteins with greatly varied G:C content and codon bias. The results consistently demonstrate that protein yields from codon engineered Gene Composer designs are as good as or better than those achieved from the synonymous native genes. Moreover, structure guided N- and C-terminal deletion constructs designed with the aid of Gene Composer can lead to greater success in gene to structure work as exemplified by the X-ray crystallographic structure determination of FtsZ from Bacillus subtilis. These results validate the Gene Composer algorithms, and suggest that using a combination of synthetic gene and protein construct engineering tools can improve the economics of gene to structure research.« less

Gene delivery systems by the combination of lipid bubbles and ultrasound.

PubMed

Negishi, Yoichi; Endo-Takahashi, Yoko; Maruyama, Kazuo

2016-11-28

Gene therapy is promising for the treatment of many diseases including cancers and genetic diseases. From the viewpoint of safety, ultrasound (US)-mediated gene delivery with nano/ microbubbles was recently developed as a novel non-viral vector system. US-mediated gene delivery using nano/microbubbles are able to produce transient changes in the permeability of the cell membrane after US-induced cavitation while reducing cellular damage and enables the tissue-specific or the site-specific intracellular delivery of gene both in vitro and in vivo. We have recently developed novel lipid nanobubbles (Lipid Bubbles). These nanobubbles can also be used to enhance the efficacy of the US-mediated genes (plasmid DNA, siRNA, and miRNA etc.) delivery. In this review, we describe US-mediated delivery systems combined with nano/microbubbles and discuss their feasibility as non-viral vector systems.

Identification of suitable reference genes for quantitative gene expression analysis in rat adipose stromal cells induced to trilineage differentiation.

PubMed

Santos, Bruno Paiva Dos; da Costa Diesel, Luciana Fraga; da Silva Meirelles, Lindolfo; Nardi, Nance Beyer; Camassola, Melissa

2016-12-15

This study was designed to (i) identify stable reference genes for the analysis of gene expression during in vitro differentiation of rat adipose stromal cells (rASCs), (ii) recommend stable genes for individual treatment conditions, and (iii) validate these genes by comparison with normalization results from stable and unstable reference genes. On the basis of a literature review, eight genes were selected: Actb, B2m, Hprt1, Ppia, Rplp0, Rpl13a, Rpl5, and Ywhaz. Genes were ranked according to their stability under different culture conditions as assessed using GenNorm, NormFinder, and RefFinder algorithms. Although the employed algorithms returned different rankings, the most frequently top-ranked genes were: B2m and/or Ppia for all 28day treatments (ALL28); Ppia and Hprt1 (adipogenic differentiation; A28), B2m (chondrogenic differentiation; C28), Rpl5 (controls maintained in complete culture medium; CCM), Rplp0 (osteogenic differentiation for 3days; O3), Rpl13a and Actb (osteogenic differentiation for 7days; O7), Rplp0 and Ppia (osteogenic differentiation for 14days; O14), Hprt1 and Ppia (osteogenic differentiation for 28days; O28), as well as Actb (all osteogenesis time points combined; ALLOSTEO). The obtained results indicate that the performance of reference genes depends on the differentiation protocol and on the analysis time, thus providing valuable information for the design of RT-PCR experiments. Copyright © 2016. Published by Elsevier B.V.

Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms.

PubMed

Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

2017-12-01

Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric phenotypes and reduces the risk of false-positive findings. We apply this method focusing on the role of perceived parental support, psychological control, and harsh punishment in depressive symptoms in adolescence. Analyses were conducted on 982 adolescents of Caucasian origin (M age (SD) = 13.78 (.94) years) genotyped for 4,947 SNPs in 263 genes, selected based on a literature survey. The Leuven Adolescent Perceived Parenting Scale (LAPPS) and the Parental Behavior Scale (PBS) were used to assess perceived parental psychological control, harsh punishment, and support. The Center for Epidemiologic Studies Depression Scale (CES-D) was the outcome. We used gene-based testing taking into account linkage disequilibrium to identify genes containing SNPs exhibiting an interaction with environmental factors yielding a p-value per single gene. Significant results at the corrected p-value of p < 1.90 × 10 -4 were examined in an independent replication sample of Dutch adolescents (N = 1354). Two genes showed evidence for interaction with perceived support: GABRR1 (p = 4.62 × 10 -5 ) and GABRR2 (p = 9.05 × 10 -6 ). No genes interacted significantly with psychological control or harsh punishment. Gene-based analysis was unable to confirm the interaction of GABRR1 or GABRR2 with support in the replication sample. However, for GABRR2, but not GABRR1, the correlation of the estimates between the two datasets was significant (r (46) = .32; p = .027) and a gene-based analysis of the combined datasets supported GABRR2 × support interaction (p = 1.63 × 10 -4 ). We present a gene-based method for gene-environment interactions in a polygenic context and show that genes

Effect of p27 gene combined with Pientzehuang ([characters: see text]) on tumor growth in osteosarcoma-bearing nude mice.

PubMed

Ren, Shou-song; Yuan, Fang; Liu, Ying-hong; Zhou, Le-tian; Li, Jun

2015-11-01

To observe the effect of p27 gene recombinant adenovirus combined with Chinese medicine Pientzehuang ([characters: see text]) on the growth of xenografted human osteosarcoma in nude mice. Tissue transplantation was used to construct the orthotopic model of human osteosarcoma Saos-2 cell in nude mice. Thirty tumor-bearing nude mice were randomly divided into 5 groups with 6 mice in each group: blank control group (model of osteosarcoma), empty vector group (recombinant adeno-associated virus-multiple cloning site), Pientzehuang group, p27 gene group and combined treatment group (p27 gene combined with Pientzehuang). The effect of combined treatment on human osteosarcoma was analyzed through the tumor formation, tumor volume and inhibition rate of tumor growth. The expression of p27 was measured by immunohistochemical staining and Western blot. The orthotopic model of osteosarcoma in nude mice was successfully constructed. The general appearance of tumor-bearing nude mice in Pientzehuang and p27 gene groups was markedly improved compared with the blank control group; and in the combined treatment group it was significantly improved compared with the Pientzehuang and p27 gene groups. The tumor growth in the Pientzehuang and p27 gene groups was significantly inhibited compared with the blank control group P<0.05); while in the combined treatment group it was markedly inhibited compared with the Pientzehuang and p27 gene groups (P<0.05). The rates of tumor growth inhibition were 34.1%, 56.5% and 63.8% in the Pientzehuang, p27 gene and combined treatment groups, respectively. Meanwhile, the protein expression of p27 gene in the p27 gene group was significantly increased compared with the blank control group (P<0.05); and it was significantly increased in the combined treatment group compared with the p27 gene and Pientzehuang groups (P<0.05). p27 gene introduced by adenovirus combined with Pientzehuang can inhibit the growth of human osteosarcoma cell Saos-2 in nude mice.

Diagnostic value of immunoglobulin κ light chain gene rearrangement analysis in B-cell lymphomas.

PubMed

Kokovic, Ira; Jezersek Novakovic, Barbara; Novakovic, Srdjan

2015-03-01

Analysis of the immunoglobulin κ light chain (IGK) gene is an alternative method for B-cell clonality assessment in the diagnosis of mature B-cell proliferations in which the detection of clonal immunoglobulin heavy chain (IGH) gene rearrangements fails. The aim of the present study was to evaluate the added value of standardized BIOMED-2 assay for the detection of clonal IGK gene rearrangements in the diagnostic setting of suspected B-cell lymphomas. With this purpose, 92 specimens from 80 patients with the final diagnosis of mature B-cell lymphoma (37 specimens), mature T-cell lymphoma (26 specimens) and reactive lymphoid proliferation (29 specimens) were analyzed for B-cell clonality. B-cell clonality analysis was performed using the BIOMED-2 IGH and IGK gene clonality assays. The determined sensitivity of the IGK assay was 67.6%, while the determined sensitivity of the IGH assay was 75.7%. The sensitivity of combined IGH+IGK assay was 81.1%. The determined specificity of the IGK assay was 96.2% in the group of T-cell lymphomas and 96.6% in the group of reactive lesions. The determined specificity of the IGH assay was 84.6% in the group of lymphomas and 86.2% in the group of reactive lesions. The comparison of GeneScan (GS) and heteroduplex pretreatment-polyacrylamide gel electrophoresis (HD-PAGE) methods for the analysis of IGK gene rearrangements showed a higher efficacy of GS analysis in a series of 27 B-cell lymphomas analyzed by both methods. In the present study, we demonstrated that by applying the combined IGH+IGK clonality assay the overall detection rate of B-cell clonality was increased by 5.4%. Thus, we confirmed the added value of the standardized BIOMED-2 IGK assay for assessment of B-cell clonality in suspected B-cell lymphomas with inconclusive clinical and cyto/histological diagnosis.

Bioinformatics analysis of differentially expressed gene profiles associated with systemic lupus erythematosus

PubMed Central

Wu, Chengjiang; Zhao, Yangjing; Lin, Yu; Yang, Xinxin; Yan, Meina; Min, Yujiao; Pan, Zihui; Xia, Sheng; Shao, Qixiang

2018-01-01

DNA microarray and high-throughput sequencing have been widely used to identify the differentially expressed genes (DEGs) in systemic lupus erythematosus (SLE). However, the big data from gene microarrays are also challenging to work with in terms of analysis and processing. The presents study combined data from the microarray expression profile (GSE65391) and bioinformatics analysis to identify the key genes and cellular pathways in SLE. Gene ontology (GO) and cellular pathway enrichment analyses of DEGs were performed to investigate significantly enriched pathways. A protein-protein interaction network was constructed to determine the key genes in the occurrence and development of SLE. A total of 310 DEGs were identified in SLE, including 193 upregulated genes and 117 downregulated genes. GO analysis revealed that the most significant biological process of DEGs was immune system process. Kyoto Encyclopedia of Genes and Genome pathway analysis showed that these DEGs were enriched in signaling pathways associated with the immune system, including the RIG-I-like receptor signaling pathway, intestinal immune network for IgA production, antigen processing and presentation and the toll-like receptor signaling pathway. The current study screened the top 10 genes with higher degrees as hub genes, which included 2′-5′-oligoadenylate synthetase 1, MX dynamin like GTPase 2, interferon induced protein with tetratricopeptide repeats 1, interferon regulatory factor 7, interferon induced with helicase C domain 1, signal transducer and activator of transcription 1, ISG15 ubiquitin-like modifier, DExD/H-box helicase 58, interferon induced protein with tetratricopeptide repeats 3 and 2′-5′-oligoadenylate synthetase 2. Module analysis revealed that these hub genes were also involved in the RIG-I-like receptor signaling, cytosolic DNA-sensing, toll-like receptor signaling and ribosome biogenesis pathways. In addition, these hub genes, from different probe sets, exhibited

Reporter gene bioassays in environmental analysis.

PubMed

Köhler, S; Belkin, S; Schmid, R D

2000-01-01

In parallel to the continuous development of increasingly more sophisticated physical and chemical analytical technologies for the detection of environmental pollutants, there is a progressively more urgent need also for bioassays which report not only on the presence of a chemical but also on its bioavailability and its biological effects. As a partial fulfillment of that need, there has been a rapid development of biosensors based on genetically engineered bacteria. Such microorganisms typically combine a promoter-operator, which acts as the sensing element, with reporter gene(s) coding for easily detectable proteins. These sensors have the ability to detect global parameters such as stress conditions, toxicity or DNA-damaging agents as well as specific organic and inorganic compounds. The systems described in this review, designed to detect different groups of target chemicals, vary greatly in their detection limits, specificity, response times and more. These variations reflect on their potential applicability which, for most of the constructs described, is presently rather limited. Nevertheless, present trends promise that additional improvements will make microbial biosensors an important tool for future environmental analysis.

Avirulence Genes in Cereal Powdery Mildews: The Gene-for-Gene Hypothesis 2.0.

PubMed

Bourras, Salim; McNally, Kaitlin E; Müller, Marion C; Wicker, Thomas; Keller, Beat

2016-01-01

The gene-for-gene hypothesis states that for each gene controlling resistance in the host, there is a corresponding, specific gene controlling avirulence in the pathogen. Allelic series of the cereal mildew resistance genes Pm3 and Mla provide an excellent system for genetic and molecular analysis of resistance specificity. Despite this opportunity for molecular research, avirulence genes in mildews remain underexplored. Earlier work in barley powdery mildew (B.g. hordei) has shown that the reaction to some Mla resistance alleles is controlled by multiple genes. Similarly, several genes are involved in the specific interaction of wheat mildew (B.g. tritici) with the Pm3 allelic series. We found that two mildew genes control avirulence on Pm3f: one gene is involved in recognition by the resistance protein as demonstrated by functional studies in wheat and the heterologous host Nicotiana benthamiana. A second gene is a suppressor, and resistance is only observed in mildew genotypes combining the inactive suppressor and the recognized Avr. We propose that such suppressor/avirulence gene combinations provide the basis of specificity in mildews. Depending on the particular gene combinations in a mildew race, different genes will be genetically identified as the "avirulence" gene. Additionally, the observation of two LINE retrotransposon-encoded avirulence genes in B.g. hordei further suggests that the control of avirulence in mildew is more complex than a canonical gene-for-gene interaction. To fully understand the mildew-cereal interactions, more knowledge on avirulence determinants is needed and we propose ways how this can be achieved based on recent advances in the field.

Comparative modular analysis of gene expression in vertebrate organs.

PubMed

Piasecka, Barbara; Kutalik, Zoltán; Roux, Julien; Bergmann, Sven; Robinson-Rechavi, Marc

2012-03-29

The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

Establishment of Functional Genomics Pipeline in Mouse Epiblast-Like Tissue by Combining Transcriptomic Analysis and Gene Knockdown/Knockin/Knockout, Using RNA Interference and CRISPR/Cas9.

PubMed

Takata, Nozomu; Sakakura, Eriko; Kasukawa, Takeya; Sakuma, Tetsushi; Yamamoto, Takashi; Sasai, Yoshiki

2016-06-01

The epiblast (foremost embryonic ectoderm) generates all three germ layers and therefore has crucial roles in the formation of all mammalian body cells. However, regulation of epiblast gene expression is poorly understood because of the difficulty of manipulating epiblast tissues in vivo. In the present study, using the self-organizing properties of mouse embryonic stem cell (ESC), we generated and characterized epiblast-like tissue in three-dimensional culture. We identified significant genome-wide gene expression changes in this epiblast-like tissue by transcriptomic analysis. In addition, we identified the particular significance of the Erk/Mapk and integrin-linked kinase pathways, and genes related to ectoderm/epithelial formation, using the bioinformatics resources IPA and DAVID. Here, we focused on Fgf5, which ranked in the top 10 among the discovered genes. To develop a functional analysis of Fgf5, we created an efficient method combining CRISPR/Cas9-mediated genome engineering and RNA interference (RNAi). Notably, we show one-step generation of various Fgf5 reporter lines including heterozygous and homozygous knockins (the GET method). For time- and dose-dependent depletion of fgf5 over the course of development, we generated an ESC line harboring Tol2 transposon-mediated integration of an inducible short hairpin RNA interference system (pdiRNAi). Our findings raised the possibility that Fgf/Erk signaling and apicobasal epithelial integrity are important factors in epiblast development. In addition, our methods provide a framework for a broad array of applications in the areas of mammalian genetics and molecular biology to understand development and to improve future therapeutics.

The Rice B-Box Zinc Finger Gene Family: Genomic Identification, Characterization, Expression Profiling and Diurnal Analysis

PubMed Central

Huang, Jianyan; Zhao, Xiaobo; Weng, Xiaoyu; Wang, Lei; Xie, Weibo

2012-01-01

Background The B-box (BBX) -containing proteins are a class of zinc finger proteins that contain one or two B-box domains and play important roles in plant growth and development. The Arabidopsis BBX gene family has recently been re-identified and renamed. However, there has not been a genome-wide survey of the rice BBX (OsBBX) gene family until now. Methodology/Principal Findings In this study, we identified 30 rice BBX genes through a comprehensive bioinformatics analysis. Each gene was assigned a uniform nomenclature. We described the chromosome localizations, gene structures, protein domains, phylogenetic relationship, whole life-cycle expression profile and diurnal expression patterns of the OsBBX family members. Based on the phylogeny and domain constitution, the OsBBX gene family was classified into five subfamilies. The gene duplication analysis revealed that only chromosomal segmental duplication contributed to the expansion of the OsBBX gene family. The expression profile of the OsBBX genes was analyzed by Affymetrix GeneChip microarrays throughout the entire life-cycle of rice cultivar Zhenshan 97 (ZS97). In addition, microarray analysis was performed to obtain the expression patterns of these genes under light/dark conditions and after three phytohormone treatments. This analysis revealed that the expression patterns of the OsBBX genes could be classified into eight groups. Eight genes were regulated under the light/dark treatments, and eleven genes showed differential expression under at least one phytohormone treatment. Moreover, we verified the diurnal expression of the OsBBX genes using the data obtained from the Diurnal Project and qPCR analysis, and the results indicated that many of these genes had a diurnal expression pattern. Conclusions/Significance The combination of the genome-wide identification and the expression and diurnal analysis of the OsBBX gene family should facilitate additional functional studies of the OsBBX genes. PMID:23118960

[The mutation analysis of PAH gene and prenatal diagnosis in classical phenylketonuria family].

PubMed

Yan, Yousheng; Hao, Shengju; Yao, Fengxia; Sun, Qingmei; Zheng, Lei; Zhang, Qinghua; Zhang, Chuan; Yang, Tao; Huang, Shangzhi

2014-12-01

To characterize the mutation spectrum of phenylalanine hydroxylase (PAH) gene and perform prenatal diagnosis for families with classical phenylketonuria. By stratified sequencing, mutations were detected in the exons and flaking introns of PAH gene of 44 families with classical phenylketonuria. 47 fetuses were diagnosed by combined sequencing with linkage analysis of three common short tandem repeats (STR) (PAH-STR, PAH-26 and PAH-32) in the PAH gene. Thirty-one types of mutations were identified. A total of 84 mutations were identified in 88 alleles (95.45%), in which the most common mutation have been R243Q (21.59%), EX6-96A>G (6.82%), IVS4-1G>A (5.86%) and IVS7+2T>A (5.86%). Most mutations were found in exons 3, 5, 6, 7, 11 and 12. The polymorphism information content (PIC) of these three STR markers was 0.71 (PAH-STR), 0.48 (PAH-26) and 0.40 (PAH-32), respectively. Prenatal diagnosis was performed successfully with the combined method in 47 fetuses of 44 classical phenylketonuria families. Among them, 11 (23.4%) were diagnosed as affected, 24 (51.1%) as carriers, and 12 (25.5%) as unaffected. Prenatal diagnosis can be achieved efficiently and accurately by stratified sequencing of PAH gene and linkage analysis of STR for classical phenylketonuria families.

Analysis of differential gene expression by bead-based fiber-optic array in growth-hormone-secreting pituitary adenomas.

PubMed

Jiang, Zhiquan; Gui, Songbo; Zhang, Yazhuo

2010-09-01

Growth-hormone-secreting pituitary adenomas (GHomas) account for approximately 20% of all pituitary neoplasms. However, the pathogenesis of GHomas remains to be elucidated. To explore the possible pathogenesis of GHomas, we used bead-based fiber-optic arrays to examine the gene expression in five GHomas and compared them to three healthy pituitaries. Four differentially expressed genes were chosen randomly for validation by quantitative real-time reverse transcription-polymerase chain reaction. We then performed pathway analysis on the identified differentially expressed genes using the Kyoto Encyclopedia of Genes and Genomes. Array analysis showed significant increases in the expression of 353 genes and 206 expressed sequence tags (ESTs) and decreases in 565 genes and 29 ESTs. Bioinformatic analysis showed that the genes HIGD1B, HOXB2, ANGPT2, HPGD and BTG2 may play an important role in the tumorigenesis and progression of GHomas. Pathway analysis showed that the wingless-type signaling pathway and extracellular-matrix receptor interactions may play a key role in the tumorigenesis and progression of GHomas. Our data suggested that there are numerous aberrantly expressed genes and pathways involved in the pathogenesis of GHomas. Bead-based fiber-optic arrays combined with pathway analysis of differentially expressed genes appear to be a valid method for investigating the pathogenesis of tumors.

Analysis of differential gene expression by bead-based fiber-optic array in growth-hormone-secreting pituitary adenomas

PubMed Central

JIANG, ZHIQUAN; GUI, SONGBO; ZHANG, YAZHUO

2010-01-01

Growth-hormone-secreting pituitary adenomas (GHomas) account for approximately 20% of all pituitary neoplasms. However, the pathogenesis of GHomas remains to be elucidated. To explore the possible pathogenesis of GHomas, we used bead-based fiber-optic arrays to examine the gene expression in five GHomas and compared them to three healthy pituitaries. Four differentially expressed genes were chosen randomly for validation by quantitative real-time reverse transcription-polymerase chain reaction. We then performed pathway analysis on the identified differentially expressed genes using the Kyoto Encyclopedia of Genes and Genomes. Array analysis showed significant increases in the expression of 353 genes and 206 expressed sequence tags (ESTs) and decreases in 565 genes and 29 ESTs. Bioinformatic analysis showed that the genes HIGD1B, HOXB2, ANGPT2, HPGD and BTG2 may play an important role in the tumorigenesis and progression of GHomas. Pathway analysis showed that the wingless-type signaling pathway and extracellular-matrix receptor interactions may play a key role in the tumorigenesis and progression of GHomas. Our data suggested that there are numerous aberrantly expressed genes and pathways involved in the pathogenesis of GHomas. Bead-based fiber-optic arrays combined with pathway analysis of differentially expressed genes appear to be a valid method for investigating the pathogenesis of tumors. PMID:22993617

DEIVA: a web application for interactive visual analysis of differential gene expression profiles.

PubMed

Harshbarger, Jayson; Kratz, Anton; Carninci, Piero

2017-01-07

Differential gene expression (DGE) analysis is a technique to identify statistically significant differences in RNA abundance for genes or arbitrary features between different biological states. The result of a DGE test is typically further analyzed using statistical software, spreadsheets or custom ad hoc algorithms. We identified a need for a web-based system to share DGE statistical test results, and locate and identify genes in DGE statistical test results with a very low barrier of entry. We have developed DEIVA, a free and open source, browser-based single page application (SPA) with a strong emphasis on being user friendly that enables locating and identifying single or multiple genes in an immediate, interactive, and intuitive manner. By design, DEIVA scales with very large numbers of users and datasets. Compared to existing software, DEIVA offers a unique combination of design decisions that enable inspection and analysis of DGE statistical test results with an emphasis on ease of use.

Improved score statistics for meta-analysis in single-variant and gene-level association studies.

PubMed

Yang, Jingjing; Chen, Sai; Abecasis, Gonçalo

2018-06-01

Meta-analysis is now an essential tool for genetic association studies, allowing them to combine large studies and greatly accelerating the pace of genetic discovery. Although the standard meta-analysis methods perform equivalently as the more cumbersome joint analysis under ideal settings, they result in substantial power loss under unbalanced settings with various case-control ratios. Here, we investigate the power loss problem by the standard meta-analysis methods for unbalanced studies, and further propose novel meta-analysis methods performing equivalently to the joint analysis under both balanced and unbalanced settings. We derive improved meta-score-statistics that can accurately approximate the joint-score-statistics with combined individual-level data, for both linear and logistic regression models, with and without covariates. In addition, we propose a novel approach to adjust for population stratification by correcting for known population structures through minor allele frequencies. In the simulated gene-level association studies under unbalanced settings, our method recovered up to 85% power loss caused by the standard methods. We further showed the power gain of our methods in gene-level tests with 26 unbalanced studies of age-related macular degeneration . In addition, we took the meta-analysis of three unbalanced studies of type 2 diabetes as an example to discuss the challenges of meta-analyzing multi-ethnic samples. In summary, our improved meta-score-statistics with corrections for population stratification can be used to construct both single-variant and gene-level association studies, providing a useful framework for ensuring well-powered, convenient, cross-study analyses. © 2018 WILEY PERIODICALS, INC.

Computational Gene Expression Modeling Identifies Salivary Biomarker Analysis that Predict Oral Feeding Readiness in the Newborn

PubMed Central

Maron, Jill L.; Hwang, Jooyeon S.; Pathak, Subash; Ruthazer, Robin; Russell, Ruby L.; Alterovitz, Gil

2014-01-01

Objective To combine mathematical modeling of salivary gene expression microarray data and systems biology annotation with RT-qPCR amplification to identify (phase I) and validate (phase II) salivary biomarker analysis for the prediction of oral feeding readiness in preterm infants. Study design Comparative whole transcriptome microarray analysis from 12 preterm newborns pre- and post-oral feeding success was used for computational modeling and systems biology analysis to identify potential salivary transcripts associated with oral feeding success (phase I). Selected gene expression biomarkers (15 from computational modeling; 6 evidence-based; and 3 reference) were evaluated by RT-qPCR amplification on 400 salivary samples from successful (n=200) and unsuccessful (n=200) oral feeders (phase II). Genes, alone and in combination, were evaluated by a multivariate analysis controlling for sex and post-conceptional age (PCA) to determine the probability that newborns achieved successful oral feeding. Results Advancing post-conceptional age (p < 0.001) and female sex (p = 0.05) positively predicted an infant’s ability to feed orally. A combination of five genes, NPY2R (hunger signaling), AMPK (energy homeostasis), PLXNA1 (olfactory neurogenesis), NPHP4 (visual behavior) and WNT3 (facial development), in addition to PCA and sex, demonstrated good accuracy for determining feeding success (AUROC = 0.78). Conclusions We have identified objective and biologically relevant salivary biomarkers that noninvasively assess a newborn’s developing brain, sensory and facial development as they relate to oral feeding success. Understanding the mechanisms that underlie the development of oral feeding readiness through translational and computational methods may improve clinical decision making while decreasing morbidities and health care costs. PMID:25620512

Combination of gene expression patterns in whole blood discriminate between tuberculosis infection states

PubMed Central

2014-01-01

Background Genetic factors are involved in susceptibility or protection to tuberculosis (TB). Apart from gene polymorphisms and mutations, changes in levels of gene expression, induced by non-genetic factors, may also determine whether individuals progress to active TB. Methods We analysed the expression level of 45 genes in a total of 47 individuals (23 healthy household contacts and 24 new smear-positive pulmonary TB patients) in Addis Ababa using a dual colour multiplex ligation-dependent probe amplification (dcRT-MLPA) technique to assess gene expression profiles that may be used to distinguish TB cases and their contacts and also latently infected (LTBI) and uninfected household contacts. Results The gene expression level of BLR1, Bcl2, IL4d2, IL7R, FCGR1A, MARCO, MMP9, CCL19, and LTF had significant discriminatory power between sputum smear-positive TB cases and household contacts, with AUCs of 0.84, 0.81, 0.79, 0.79, 0.78, 0.76, 0.75, 0.75 and 0.68 respectively. The combination of Bcl2, BLR1, FCGR1A, IL4d2 and MARCO identified 91.66% of active TB cases and 95.65% of household contacts without active TB. The expression of CCL19, TGFB1, and Foxp3 showed significant difference between LTBI and uninfected contacts, with AUCs of 0.85, 0.82, and 0.75, respectively, whereas the combination of BPI, CCL19, FoxP3, FPR1 and TGFB1 identified 90.9% of QFT- and 91.6% of QFT+ household contacts. Conclusions Expression of single and especially combinations of host genes can accurately differentiate between active TB cases and healthy individuals as well as between LTBI and uninfected contacts. PMID:24885723

Avirulence Genes in Cereal Powdery Mildews: The Gene-for-Gene Hypothesis 2.0

PubMed Central

Bourras, Salim; McNally, Kaitlin E.; Müller, Marion C.; Wicker, Thomas; Keller, Beat

2016-01-01

The gene-for-gene hypothesis states that for each gene controlling resistance in the host, there is a corresponding, specific gene controlling avirulence in the pathogen. Allelic series of the cereal mildew resistance genes Pm3 and Mla provide an excellent system for genetic and molecular analysis of resistance specificity. Despite this opportunity for molecular research, avirulence genes in mildews remain underexplored. Earlier work in barley powdery mildew (B.g. hordei) has shown that the reaction to some Mla resistance alleles is controlled by multiple genes. Similarly, several genes are involved in the specific interaction of wheat mildew (B.g. tritici) with the Pm3 allelic series. We found that two mildew genes control avirulence on Pm3f: one gene is involved in recognition by the resistance protein as demonstrated by functional studies in wheat and the heterologous host Nicotiana benthamiana. A second gene is a suppressor, and resistance is only observed in mildew genotypes combining the inactive suppressor and the recognized Avr. We propose that such suppressor/avirulence gene combinations provide the basis of specificity in mildews. Depending on the particular gene combinations in a mildew race, different genes will be genetically identified as the “avirulence” gene. Additionally, the observation of two LINE retrotransposon-encoded avirulence genes in B.g. hordei further suggests that the control of avirulence in mildew is more complex than a canonical gene-for-gene interaction. To fully understand the mildew–cereal interactions, more knowledge on avirulence determinants is needed and we propose ways how this can be achieved based on recent advances in the field. PMID:26973683

Robust extraction of functional signals from gene set analysis using a generalized threshold free scoring function

PubMed Central

2009-01-01

Background A central task in contemporary biosciences is the identification of biological processes showing response in genome-wide differential gene expression experiments. Two types of analysis are common. Either, one generates an ordered list based on the differential expression values of the probed genes and examines the tail areas of the list for over-representation of various functional classes. Alternatively, one monitors the average differential expression level of genes belonging to a given functional class. So far these two types of method have not been combined. Results We introduce a scoring function, Gene Set Z-score (GSZ), for the analysis of functional class over-representation that combines two previous analysis methods. GSZ encompasses popular functions such as correlation, hypergeometric test, Max-Mean and Random Sets as limiting cases. GSZ is stable against changes in class size as well as across different positions of the analysed gene list in tests with randomized data. GSZ shows the best overall performance in a detailed comparison to popular functions using artificial data. Likewise, GSZ stands out in a cross-validation of methods using split real data. A comparison of empirical p-values further shows a strong difference in favour of GSZ, which clearly reports better p-values for top classes than the other methods. Furthermore, GSZ detects relevant biological themes that are missed by the other methods. These observations also hold when comparing GSZ with popular program packages. Conclusion GSZ and improved versions of earlier methods are a useful contribution to the analysis of differential gene expression. The methods and supplementary material are available from the website http://ekhidna.biocenter.helsinki.fi/users/petri/public/GSZ/GSZscore.html. PMID:19775443

Effect of NET-1 siRNA conjugated sub-micron bubble complex combined with low-frequency ultrasound exposure in gene transfection

PubMed Central

Wu, Bolin; Liang, Xitian; Jing, Hui; Han, Xue; Sun, Yixin; Guo, Cunli; Liu, Ying; Cheng, Wen

2018-01-01

The present study evaluated the effect of NET-1 siRNA-conjugated sub-micron bubble (SMB) complexes combined with low-frequency ultrasound exposure in gene transfection. The NET-1 gene was highly expressed level in SMMC-7721 human hepatocellular carcinoma cell line. The cells were divided into seven groups and treated with different conditions. The groups with or without low-frequency ultrasound exposure, groups of adherent cells, and suspension cells were separated. The NET-1 siRNA-conjugated SMB complexes were made in the laboratory and tested by Zetasizer Nano ZS90 analyzer. Flow cytometry was used to estimate the transfection efficiency and cellular apoptosis. Western blot and quantitative real-time polymerase chain reaction (qPCR) were used for the estimation of the protein and mRNA expressions, respectively. Transwell analysis determined the migration and invasion capacities of the tumor cells. The results did not show any difference in the transfection efficiency between adherent and suspension cells. However, the NET-1 siRNA-SMB complexes combined with low-frequency ultrasound exposure could enhance the gene transfection effectively. In summary, the NET-1 siRNA-SMB complexes appeared to be promising gene vehicle. PMID:29423111

Methods to increase reproducibility in differential gene expression via meta-analysis

PubMed Central

Sweeney, Timothy E.; Haynes, Winston A.; Vallania, Francesco; Ioannidis, John P.; Khatri, Purvesh

2017-01-01

Findings from clinical and biological studies are often not reproducible when tested in independent cohorts. Due to the testing of a large number of hypotheses and relatively small sample sizes, results from whole-genome expression studies in particular are often not reproducible. Compared to single-study analysis, gene expression meta-analysis can improve reproducibility by integrating data from multiple studies. However, there are multiple choices in designing and carrying out a meta-analysis. Yet, clear guidelines on best practices are scarce. Here, we hypothesized that studying subsets of very large meta-analyses would allow for systematic identification of best practices to improve reproducibility. We therefore constructed three very large gene expression meta-analyses from clinical samples, and then examined meta-analyses of subsets of the datasets (all combinations of datasets with up to N/2 samples and K/2 datasets) compared to a ‘silver standard’ of differentially expressed genes found in the entire cohort. We tested three random-effects meta-analysis models using this procedure. We showed relatively greater reproducibility with more-stringent effect size thresholds with relaxed significance thresholds; relatively lower reproducibility when imposing extraneous constraints on residual heterogeneity; and an underestimation of actual false positive rate by Benjamini–Hochberg correction. In addition, multivariate regression showed that the accuracy of a meta-analysis increased significantly with more included datasets even when controlling for sample size. PMID:27634930

Literature mining, gene-set enrichment and pathway analysis for target identification in Behçet's disease.

PubMed

Wilson, Paul; Larminie, Christopher; Smith, Rona

2016-01-01

To use literature mining to catalogue Behçet's associated genes, and advanced computational methods to improve the understanding of the pathways and signalling mechanisms that lead to the typical clinical characteristics of Behçet's patients. To extend this technique to identify potential treatment targets for further experimental validation. Text mining methods combined with gene enrichment tools, pathway analysis and causal analysis algorithms. This approach identified 247 human genes associated with Behçet's disease and the resulting disease map, comprising 644 nodes and 19220 edges, captured important details of the relationships between these genes and their associated pathways, as described in diverse data repositories. Pathway analysis has identified how Behçet's associated genes are likely to participate in innate and adaptive immune responses. Causal analysis algorithms have identified a number of potential therapeutic strategies for further investigation. Computational methods have captured pertinent features of the prominent disease characteristics presented in Behçet's disease and have highlighted NOD2, ICOS and IL18 signalling as potential therapeutic strategies.

Abrogation of Microsatellite-instable Tumors Using a Highly Selective Suicide Gene/Prodrug Combination

PubMed Central

Ferrás, Cristina; Oude Vrielink, Joachim AF; Verspuy, Johan WA; te Riele, Hein; Tsaalbi-Shtylik, Anastasia; de Wind, Niels

2009-01-01

A substantial fraction of sporadic and inherited colorectal and endometrial cancers in humans is deficient in DNA mismatch repair (MMR). These cancers are characterized by length alterations in ubiquitous simple sequence repeats, a phenotype called microsatellite instability. Here we have exploited this phenotype by developing a novel approach for the highly selective gene therapy of MMR-deficient tumors. To achieve this selectivity, we mutated the VP22FCU1 suicide gene by inserting an out-of-frame microsatellite within its coding region. We show that in a significant fraction of microsatellite-instable (MSI) cells carrying the mutated suicide gene, full-length protein becomes expressed within a few cell doublings, presumably resulting from a reverting frameshift within the inserted microsatellite. Treatment of these cells with the innocuous prodrug 5-fluorocytosine (5-FC) induces strong cytotoxicity and we demonstrate that this owes to multiple bystander effects conferred by the suicide gene/prodrug combination. In a mouse model, MMR-deficient tumors that contained the out-of-frame VP22FCU1 gene displayed strong remission after treatment with 5-FC, without any obvious adverse systemic effects to the mouse. By virtue of its high selectivity and potency, this conditional enzyme/prodrug combination may hold promise for the treatment or prevention of MMR-deficient cancer in humans. PMID:19471249

Phylogeny Inference of Closely Related Bacterial Genomes: Combining the Features of Both Overlapping Genes and Collinear Genomic Regions

PubMed Central

Zhang, Yan-Cong; Lin, Kui

2015-01-01

Overlapping genes (OGs) represent one type of widespread genomic feature in bacterial genomes and have been used as rare genomic markers in phylogeny inference of closely related bacterial species. However, the inference may experience a decrease in performance for phylogenomic analysis of too closely or too distantly related genomes. Another drawback of OGs as phylogenetic markers is that they usually take little account of the effects of genomic rearrangement on the similarity estimation, such as intra-chromosome/genome translocations, horizontal gene transfer, and gene losses. To explore such effects on the accuracy of phylogeny reconstruction, we combine phylogenetic signals of OGs with collinear genomic regions, here called locally collinear blocks (LCBs). By putting these together, we refine our previous metric of pairwise similarity between two closely related bacterial genomes. As a case study, we used this new method to reconstruct the phylogenies of 88 Enterobacteriale genomes of the class Gammaproteobacteria. Our results demonstrated that the topological accuracy of the inferred phylogeny was improved when both OGs and LCBs were simultaneously considered, suggesting that combining these two phylogenetic markers may reduce, to some extent, the influence of gene loss on phylogeny inference. Such phylogenomic studies, we believe, will help us to explore a more effective approach to increasing the robustness of phylogeny reconstruction of closely related bacterial organisms. PMID:26715828

Rapid detection of pathological mutations and deletions of the haemoglobin beta gene (HBB) by High Resolution Melting (HRM) analysis and Gene Ratio Analysis Copy Enumeration PCR (GRACE-PCR).

PubMed

Turner, Andrew; Sasse, Jurgen; Varadi, Aniko

2016-10-19

Inherited disorders of haemoglobin are the world's most common genetic diseases, resulting in significant morbidity and mortality. The large number of mutations associated with the haemoglobin beta gene (HBB) makes gene scanning by High Resolution Melting (HRM) PCR an attractive diagnostic approach. However, existing HRM-PCR assays are not able to detect all common point mutations and have only a very limited ability to detect larger gene rearrangements. The aim of the current study was to develop a HBB assay, which can be used as a screening test in highly heterogeneous populations, for detection of both point mutations and larger gene rearrangements. The assay is based on a combination of conventional HRM-PCR and a novel Gene Ratio Analysis Copy Enumeration (GRACE) PCR method. HRM-PCR was extensively optimised, which included the use of an unlabelled probe and incorporation of universal bases into primers to prevent interference from common non-pathological polymorphisms. GRACE-PCR was employed to determine HBB gene copy numbers relative to a reference gene using melt curve analysis to detect rearrangements in the HBB gene. The performance of the assay was evaluated by analysing 410 samples. A total of 44 distinct pathological genotypes were detected. In comparison with reference methods, the assay has a sensitivity of 100 % and a specificity of 98 %. We have developed an assay that detects both point mutations and larger rearrangements of the HBB gene. This assay is quick, sensitive, specific and cost effective making it suitable as an initial screening test that can be used for highly heterogeneous cohorts.

Combined sequence and sequence-structure-based methods for analyzing RAAS gene SNPs: a computational approach.

PubMed

Singh, Kh Dhanachandra; Karthikeyan, Muthusamy

2014-12-01

The renin-angiotensin-aldosterone system (RAAS) plays a key role in the regulation of blood pressure (BP). Mutations on the genes that encode components of the RAAS have played a significant role in genetic susceptibility to hypertension and have been intensively scrutinized. The identification of such probably causal mutations not only provides insight into the RAAS but may also serve as antihypertensive therapeutic targets and diagnostic markers. The methods for analyzing the SNPs from the huge dataset of SNPs, containing both functional and neutral SNPs is challenging by the experimental approach on every SNPs to determine their biological significance. To explore the functional significance of genetic mutation (SNPs), we adopted combined sequence and sequence-structure-based SNP analysis algorithm. Out of 3864 SNPs reported in dbSNP, we found 108 missense SNPs in the coding region and remaining in the non-coding region. In this study, we are reporting only those SNPs in coding region to be deleterious when three or more tools are predicted to be deleterious and which have high RMSD from the native structure. Based on these analyses, we have identified two SNPs of REN gene, eight SNPs of AGT gene, three SNPs of ACE gene, two SNPs of AT1R gene, three SNPs of CYP11B2 gene and three SNPs of CMA1 gene in the coding region were found to be deleterious. Further this type of study will be helpful in reducing the cost and time for identification of potential SNP and also helpful in selecting potential SNP for experimental study out of SNP pool.

Isolated and combined dystonia syndromes - an update on new genes and their phenotypes.

PubMed

Balint, B; Bhatia, K P

2015-04-01

Recent consensus on the definition, phenomenology and classification of dystonia centres around phenomenology and guides our diagnostic approach for the heterogeneous group of dystonias. Current terminology classifies conditions where dystonia is the sole motor feature (apart from tremor) as 'isolated dystonia', while 'combined dystonia' refers to dystonias with other accompanying movement disorders. This review highlights recent advances in the genetics of some isolated and combined dystonic syndromes. Some genes, such as ANO3, GNAL and CIZ1, have been discovered for isolated dystonia, but they are probably not a common cause of classic cervical dystonia. Conversely, the phenotype associated with TUBB4A mutations expanded from that of isolated dystonia to a syndrome of hypomyelination with atrophy of the basal ganglia and cerebellum (H-ABC syndrome). Similarly, ATP1A3 mutations cause a wide phenotypic spectrum ranging from rapid-onset dystonia-parkinsonism to alternating hemiplegia of childhood. Other entities entailing dystonia-parkinsonism include dopamine transporter deficiency syndrome (SLC63 mutations); dopa-responsive dystonias; young-onset parkinsonism (PARKIN, PINK1 and DJ-1 mutations); PRKRA mutations; and X-linked TAF1 mutations, which rarely can also manifest in women. Clinical and genetic heterogeneity also characterizes myoclonus-dystonia, which includes not only the classical phenotype associated with epsilon-sarcoglycan mutations but rarely also presentation of ANO3 gene mutations, TITF1 gene mutations typically underlying benign hereditary chorea, and some dopamine synthesis pathway conditions due to GCH1 and TH mutations. Thus, new genes are being recognized for isolated dystonia, and the phenotype of known genes is broadening and now involves different combined dystonia syndromes. © 2015 EAN.

Gene expression profile analysis of Ligon lintless-1 (Li1) mutant reveals important genes and pathways in cotton leaf and fiber development.

PubMed

Ding, Mingquan; Jiang, Yurong; Cao, Yuefen; Lin, Lifeng; He, Shae; Zhou, Wei; Rong, Junkang

2014-02-10

Ligon lintless-1 (Li1) is a monogenic dominant mutant of Gossypium hirsutum (upland cotton) with a phenotype of impaired vegetative growth and short lint fibers. Despite years of research involving genetic mapping and gene expression profile analysis of Li1 mutant ovule tissues, the gene remains uncloned and the underlying pathway of cotton fiber elongation is still unclear. In this study, we report the whole genome-level deep-sequencing analysis of leaf tissues of the Li1 mutant. Differentially expressed genes in leaf tissues of mutant versus wild-type (WT) plants are identified, and the underlying pathways and potential genes that control leaf and fiber development are inferred. The results show that transcription factors AS2, YABBY5, and KANDI-like are significantly differentially expressed in mutant tissues compared with WT ones. Interestingly, several fiber development-related genes are found in the downregulated gene list of the mutant leaf transcriptome. These genes include heat shock protein family, cytoskeleton arrangement, cell wall synthesis, energy, H2O2 metabolism-related genes, and WRKY transcription factors. This finding suggests that the genes are involved in leaf morphology determination and fiber elongation. The expression data are also compared with the previously published microarray data of Li1 ovule tissues. Comparative analysis of the ovule transcriptomes of Li1 and WT reveals that a number of pathways important for fiber elongation are enriched in the downregulated gene list at different fiber development stages (0, 6, 9, 12, 15, 18dpa). Differentially expressed genes identified in both leaf and fiber samples are aligned with cotton whole genome sequences and combined with the genetic fine mapping results to identify a list of candidate genes for Li1. Copyright © 2013 Elsevier B.V. All rights reserved.

Multilevel Regulation of Bacterial Gene Expression with the Combined STAR and Antisense RNA System.

PubMed

Lee, Young Je; Kim, Soo-Jung; Moon, Tae Seok

2018-03-16

Synthetic small RNA regulators have emerged as a versatile tool to predictably control bacterial gene expression. Owing to their simple design principles, small size, and highly orthogonal behavior, these engineered genetic parts have been incorporated into genetic circuits. However, efforts to achieve more sophisticated cellular functions using RNA regulators have been hindered by our limited ability to integrate different RNA regulators into complex circuits. Here, we present a combined RNA regulatory system in Escherichia coli that uses small transcription activating RNA (STAR) and antisense RNA (asRNA) to activate or deactivate target gene expression in a programmable manner. Specifically, we demonstrated that the activated target output by the STAR system can be deactivated by expressing two different types of asRNAs: one binds to and sequesters the STAR regulator, affecting the transcription process, while the other binds to the target mRNA, affecting the translation process. We improved deactivation efficiencies (up to 96%) by optimizing each type of asRNA and then integrating the two optimized asRNAs into a single circuit. Furthermore, we demonstrated that the combined STAR and asRNA system can control gene expression in a reversible way and can regulate expression of a gene in the genome. Lastly, we constructed and simultaneously tested two A AND NOT B logic gates in the same cell to show sophisticated multigene regulation by the combined system. Our approach establishes a methodology for integrating multiple RNA regulators to rationally control multiple genes.

Analysis of bHLH coding genes using gene co-expression network approach.

PubMed

Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

2016-07-01

Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species.

Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

PubMed

Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

2009-10-27

The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a

Random forests-based differential analysis of gene sets for gene expression data.

PubMed

Hsueh, Huey-Miin; Zhou, Da-Wei; Tsai, Chen-An

2013-04-10

In DNA microarray studies, gene-set analysis (GSA) has become the focus of gene expression data analysis. GSA utilizes the gene expression profiles of functionally related gene sets in Gene Ontology (GO) categories or priori-defined biological classes to assess the significance of gene sets associated with clinical outcomes or phenotypes. Many statistical approaches have been proposed to determine whether such functionally related gene sets express differentially (enrichment and/or deletion) in variations of phenotypes. However, little attention has been given to the discriminatory power of gene sets and classification of patients. In this study, we propose a method of gene set analysis, in which gene sets are used to develop classifications of patients based on the Random Forest (RF) algorithm. The corresponding empirical p-value of an observed out-of-bag (OOB) error rate of the classifier is introduced to identify differentially expressed gene sets using an adequate resampling method. In addition, we discuss the impacts and correlations of genes within each gene set based on the measures of variable importance in the RF algorithm. Significant classifications are reported and visualized together with the underlying gene sets and their contribution to the phenotypes of interest. Numerical studies using both synthesized data and a series of publicly available gene expression data sets are conducted to evaluate the performance of the proposed methods. Compared with other hypothesis testing approaches, our proposed methods are reliable and successful in identifying enriched gene sets and in discovering the contributions of genes within a gene set. The classification results of identified gene sets can provide an valuable alternative to gene set testing to reveal the unknown, biologically relevant classes of samples or patients. In summary, our proposed method allows one to simultaneously assess the discriminatory ability of gene sets and the importance of genes for

Large-scale gene function analysis with the PANTHER classification system.

PubMed

Mi, Huaiyu; Muruganujan, Anushya; Casagrande, John T; Thomas, Paul D

2013-08-01

The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.

Unique Physiological and Transcriptional Shifts under Combinations of Salinity, Drought, and Heat.

PubMed

Shaar-Moshe, Lidor; Blumwald, Eduardo; Peleg, Zvi

2017-05-01

Climate-change-driven stresses such as extreme temperatures, water deficit, and ion imbalance are projected to exacerbate and jeopardize global food security. Under field conditions, these stresses usually occur simultaneously and cause damages that exceed single stresses. Here, we investigated the transcriptional patterns and morpho-physiological acclimations of Brachypodium dystachion to single salinity, drought, and heat stresses, as well as their double and triple stress combinations. Hierarchical clustering analysis of morpho-physiological acclimations showed that several traits exhibited a gradually aggravating effect as plants were exposed to combined stresses. On the other hand, other morphological traits were dominated by salinity, while some physiological traits were shaped by heat stress. Response patterns of differentially expressed genes, under single and combined stresses (i.e. common stress genes), were maintained only among 37% of the genes, indicating a limited expression consistency among partially overlapping stresses. A comparison between common stress genes and genes that were uniquely expressed only under combined stresses (i.e. combination unique genes) revealed a significant shift from increased intensity to antagonistic responses, respectively. The different transcriptional signatures imply an alteration in the mode of action under combined stresses and limited ability to predict plant responses as different stresses are combined. Coexpression analysis coupled with enrichment analysis revealed that each gene subset was enriched with different biological processes. Common stress genes were enriched with known stress response pathways, while combination unique-genes were enriched with unique processes and genes with unknown functions that hold the potential to improve stress tolerance and enhance cereal productivity under suboptimal field conditions. © 2017 American Society of Plant Biologists. All Rights Reserved.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

PubMed

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach

PubMed Central

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Introduction Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. Aim The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Methods Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate – adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Results Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. Conclusion To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This

Combining Evidence of Preferential Gene-Tissue Relationships from Multiple Sources

PubMed Central

Guo, Jing; Hammar, Mårten; Öberg, Lisa; Padmanabhuni, Shanmukha S.; Bjäreland, Marcus; Dalevi, Daniel

2013-01-01

An important challenge in drug discovery and disease prognosis is to predict genes that are preferentially expressed in one or a few tissues, i.e. showing a considerably higher expression in one tissue(s) compared to the others. Although several data sources and methods have been published explicitly for this purpose, they often disagree and it is not evident how to retrieve these genes and how to distinguish true biological findings from those that are due to choice-of-method and/or experimental settings. In this work we have developed a computational approach that combines results from multiple methods and datasets with the aim to eliminate method/study-specific biases and to improve the predictability of preferentially expressed human genes. A rule-based score is used to merge and assign support to the results. Five sets of genes with known tissue specificity were used for parameter pruning and cross-validation. In total we identify 3434 tissue-specific genes. We compare the genes of highest scores with the public databases: PaGenBase (microarray), TiGER (EST) and HPA (protein expression data). The results have 85% overlap to PaGenBase, 71% to TiGER and only 28% to HPA. 99% of our predictions have support from at least one of these databases. Our approach also performs better than any of the databases on identifying drug targets and biomarkers with known tissue-specificity. PMID:23950964

Polymorphisms in the methylene tetrahydrofolate reductase gene and their unique combinations are associated with an increased susceptibility to the renal cancers.

PubMed

Ajaz, Sadia; Khaliq, Shagufta; Hashmi, Altaf; Naqvi, Syed Ali Anwar; Rizvi, Syed Adib-ul-Hassan; Mehdi, Syed Qasim

2012-05-01

Two single nucleotide polymorphisms in the methylene tetrahydrofolate reductase (MTHFR) gene, 677C/T and 1298A/C, encode the thermolabile isoforms of the MTHFR enzyme that adversely affect the folic acid metabolic pathway. In the present study, these polymorphisms were investigated for their associations with the risk and prognosis of the renal cell carcinomas (RCCs) in Pakistani patients. The study included 168 RCC patients and 178 controls. The polymorphisms were analyzed by the polymerase chain reaction-restriction fragment length polymorphism method. Statistical analysis revealed that the C-allele and homozygous C genotype of the MTHFR 1298A/C polymorphism were significantly correlated with the risk of RCCs (odds ratio [OR]=1.60; 95% confidence interval [CI]=1.1-2.34 and OR=3.26; 95% CI=1.27-8.37, respectively). The combined genotype analysis showed that the 677CC+1298CC combination greatly increased the susceptibility to RCCs (OR=8.34; 95% CI=2.7-25.7). The 677CT+1298AA and 677CC+1298CA combinations were also associated with an increased risk of RCC (OR=3.21; 95% CI=1.3-7.8 and OR=2.45; 95% CI=1.3-4.6, respectively). The combined genotype effects were also evident in a semiparametric expectation-maximization-based haplotype analysis. The results presented here indicate that the two MTHFR gene polymorphisms are significantly associated with the risk of RCCs in a cohort of Pakistani patients and may be useful as susceptibility markers in other populations of the world as well.

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline

PubMed Central

2013-01-01

Background As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. Results We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS A : DE genes with non-zero effect sizes in all studies, (2) HS B : DE genes with non-zero effect sizes in one or more studies and (3) HS r : DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. Conclusions The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS A , HS B , and HS r ). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline.

PubMed

Chang, Lun-Ching; Lin, Hui-Min; Sibille, Etienne; Tseng, George C

2013-12-21

As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS(A): DE genes with non-zero effect sizes in all studies, (2) HS(B): DE genes with non-zero effect sizes in one or more studies and (3) HS(r): DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS(A), HS(B), and HS(r)). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author's publication website.

Combining suppressive subtractive hybridization and cDNA microarrays to identify dietary phosphorus-responsive genes of the rainbow trout (Oncorhynchus mykiss) kidney.

PubMed

Lake, Jennifer; Gravel, Catherine; Koko, Gabriel Koffi D; Robert, Claude; Vandenberg, Grant W

2010-03-01

Phosphorus (P)-responsive genes and how they regulate renal adaptation to phosphorous-deficient diets in animals, including fish, are not well understood. RNA abundance profiling using cDNA microarrays is an efficient approach to study nutrient-gene interactions and identify these dietary P-responsive genes. To test the hypothesis that dietary P-responsive genes are differentially expressed in fish fed varying P levels, rainbow trout were fed a practical high-P diet (R20: 0.96% P) or a low-P diet (R0: 0.38% P) for 7 weeks. The differentially-expressed genes between dietary groups were identified and compared from the kidney by combining suppressive subtractive hybridization (SSH) with cDNA microarray analysis. A number of genes were confirmed by real-time PCR, and correlated with plasma and bone P concentrations. Approximately 54 genes were identified as potential dietary P-responsive after 7 weeks on a diet deficient in P according to cDNA microarray analysis. Of 18 selected genes, 13 genes were confirmed to be P-responsive at 7 weeks by real-time PCR analysis, including: iNOS, cytochrome b, cytochrome c oxidase subunit II , alpha-globin I, beta-globin, ATP synthase, hyperosmotic protein 21, COL1A3, Nkef, NDPK, glucose phosphate isomerase 1, Na+/H+ exchange protein and GDP dissociation inhibitor 2. Many of these dietary P-responsive genes responded in a moderate way (R0/R20 ratio: <2-3 or >0.5) and in a transient manner to dietary P limitation. In summary, renal adaptation to dietary P deficiency in trout involves changes in the expression of several genes, suggesting a profile of metabolic stress, since many of these differentially-expressed candidates are associated with the cellular adaptative responses. Crown Copyright 2009. Published by Elsevier Inc. All rights reserved.

Principles of gene microarray data analysis.

PubMed

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

Gene-Gene and Gene-Environment Interactions in Ulcerative Colitis

PubMed Central

Wang, Ming-Hsi; Fiocchi, Claudio; Zhu, Xiaofeng; Ripke, Stephan; Kamboh, M. Ilyas; Rebert, Nancy; Duerr, Richard H.; Achkar, Jean-Paul

2014-01-01

Genome-wide association studies (GWAS) have identified at least 133 ulcerative colitis (UC) associated loci. The role of genetic factors in clinical practice is not clearly defined. The relevance of genetic variants to disease pathogenesis is still uncertain because of not characterized gene-gene and gene-environment interactions. We examined the predictive value of combining the 133 UC risk loci with genetic interactions in an ongoing inflammatory bowel disease (IBD) GWAS. The Wellcome Trust Case-Control Consortium (WTCCC) IBD GWAS was used as a replication cohort. We applied logic regression (LR), a novel adaptive regression methodology, to search for high order interactions. Exploratory genotype correlations with UC sub-phenotypes (extent of disease, need of surgery, age of onset, extra-intestinal manifestations and primary sclerosing cholangitis (PSC)) were conducted. The combination of 133 UC loci yielded good UC risk predictability (area under the curve [AUC] of 0.86). A higher cumulative allele score predicted higher UC risk. Through LR, several lines of evidence for genetic interactions were identified and successfully replicated in the WTCCC cohort. The genetic interactions combined with the gene-smoking interaction significantly improved predictability in the model (AUC, from 0.86 to 0.89, P=3.26E-05). Explained UC variance increased from 37% to 42% after adding the interaction terms. A within case analysis found suggested genetic association with PSC. Our study demonstrates that the LR methodology allows the identification and replication of high order genetic interactions in UC GWAS datasets. UC risk can be predicted by a 133 loci and improved by adding gene-gene and gene-environment interactions. PMID:24241240

Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle.

PubMed

Mateescu, Raluca G; Garrick, Dorian J; Reecy, James M

2017-01-01

Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms

Meta-analysis of human gene expression in response to Mycobacterium tuberculosis infection reveals potential therapeutic targets.

PubMed

Wang, Zhang; Arat, Seda; Magid-Slav, Michal; Brown, James R

2018-01-10

With the global emergence of multi-drug resistant strains of Mycobacterium tuberculosis, new strategies to treat tuberculosis are urgently needed such as therapeutics targeting potential human host factors. Here we performed a statistical meta-analysis of human gene expression in response to both latent and active pulmonary tuberculosis infections from nine published datasets. We found 1655 genes that were significantly differentially expressed during active tuberculosis infection. In contrast, no gene was significant for latent tuberculosis. Pathway enrichment analysis identified 90 significant canonical human pathways, including several pathways more commonly related to non-infectious diseases such as the LRRK2 pathway in Parkinson's disease, and PD-1/PD-L1 signaling pathway important for new immuno-oncology therapies. The analysis of human genome-wide association studies datasets revealed tuberculosis-associated genetic variants proximal to several genes in major histocompatibility complex for antigen presentation. We propose several new targets and drug-repurposing opportunities including intravenous immunoglobulin, ion-channel blockers and cancer immuno-therapeutics for development as combination therapeutics with anti-mycobacterial agents. Our meta-analysis provides novel insights into host genes and pathways important for tuberculosis and brings forth potential drug repurposing opportunities for host-directed therapies.

Turning publicly available gene expression data into discoveries using gene set context analysis.

PubMed

Ji, Zhicheng; Vokes, Steven A; Dang, Chi V; Ji, Hongkai

2016-01-08

Gene Set Context Analysis (GSCA) is an open source software package to help researchers use massive amounts of publicly available gene expression data (PED) to make discoveries. Users can interactively visualize and explore gene and gene set activities in 25,000+ consistently normalized human and mouse gene expression samples representing diverse biological contexts (e.g. different cells, tissues and disease types, etc.). By providing one or multiple genes or gene sets as input and specifying a gene set activity pattern of interest, users can query the expression compendium to systematically identify biological contexts associated with the specified gene set activity pattern. In this way, researchers with new gene sets from their own experiments may discover previously unknown contexts of gene set functions and hence increase the value of their experiments. GSCA has a graphical user interface (GUI). The GUI makes the analysis convenient and customizable. Analysis results can be conveniently exported as publication quality figures and tables. GSCA is available at https://github.com/zji90/GSCA. This software significantly lowers the bar for biomedical investigators to use PED in their daily research for generating and screening hypotheses, which was previously difficult because of the complexity, heterogeneity and size of the data. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Haplotype combination of the bovine CFL2 gene sequence variants and association with growth traits in Qinchuan cattle.

PubMed

Sun, Yujia; Lan, Xianyong; Lei, Chuzhao; Zhang, Chunlei; Chen, Hong

2015-06-01

The aim of this study was to examine the association of cofilin2 (CFL2) gene polymorphisms with growth traits in Chinese Qinchuan cattle. Three single nucleotide polymorphisms (SNPs) were identified in the bovine CFL2 gene using DNA sequencing and (forced) PCR-RFLP methods. These polymorphisms included a missense mutation (NC_007319.5: g. C 2213 G) in exon 4, one synonymous mutation (NC_007319.5: g. T 1694 A) in exon 4, and a mutation (NC_007319.5: g. G 1500 A) in intron 2, respectively. In addition, we evaluated the haplotype frequency and linkage disequilibrium coefficient of three sequence variants in 488 individuals in QC cattle. All the three SNPs in QC cattle belonged to an intermediate level of genetic diversity (0.25analysis of three SNPs showed that 8 different haplotypes were identified in all, but only 5 haplotypes were listed except for those with a frequency of <0.03. Hap4 (-GTC-) had the highest haplotype frequencies (34.70%). However in the three SNPs there were no significant associations between the 13 combined genotypes of the CFL2 gene and growth traits. LD analysis showed that the SNP T 1694 A and C 2213 G loci had a strong linkage (r(2)>0.33). Association analysis indicated that SNP G 1500 A, T 1694 A and C 2213 G were significantly associated with growth traits in the QC population. The results of our study suggest that the CFL2 gene may be a strong candidate gene that affects growth traits in the QC cattle breeding program. Copyright © 2015 Elsevier B.V. All rights reserved.

Digital gene expression analysis of gene expression differences within Brassica diploids and allopolyploids.

PubMed

Jiang, Jinjin; Wang, Yue; Zhu, Bao; Fang, Tingting; Fang, Yujie; Wang, Youping

2015-01-27

Brassica includes many successfully cultivated crop species of polyploid origin, either by ancestral genome triplication or by hybridization between two diploid progenitors, displaying complex repetitive sequences and transposons. The U's triangle, which consists of three diploids and three amphidiploids, is optimal for the analysis of complicated genomes after polyploidization. Next-generation sequencing enables the transcriptome profiling of polyploids on a global scale. We examined the gene expression patterns of three diploids (Brassica rapa, B. nigra, and B. oleracea) and three amphidiploids (B. napus, B. juncea, and B. carinata) via digital gene expression analysis. In total, the libraries generated between 5.7 and 6.1 million raw reads, and the clean tags of each library were mapped to 18547-21995 genes of B. rapa genome. The unambiguous tag-mapped genes in the libraries were compared. Moreover, the majority of differentially expressed genes (DEGs) were explored among diploids as well as between diploids and amphidiploids. Gene ontological analysis was performed to functionally categorize these DEGs into different classes. The Kyoto Encyclopedia of Genes and Genomes analysis was performed to assign these DEGs into approximately 120 pathways, among which the metabolic pathway, biosynthesis of secondary metabolites, and peroxisomal pathway were enriched. The non-additive genes in Brassica amphidiploids were analyzed, and the results indicated that orthologous genes in polyploids are frequently expressed in a non-additive pattern. Methyltransferase genes showed differential expression pattern in Brassica species. Our results provided an understanding of the transcriptome complexity of natural Brassica species. The gene expression changes in diploids and allopolyploids may help elucidate the morphological and physiological differences among Brassica species.

GARNET--gene set analysis with exploration of annotation relations.

PubMed

Rho, Kyoohyoung; Kim, Bumjin; Jang, Youngjun; Lee, Sanghyun; Bae, Taejeong; Seo, Jihae; Seo, Chaehwa; Lee, Jihyun; Kang, Hyunjung; Yu, Ungsik; Kim, Sunghoon; Lee, Sanghyuk; Kim, Wan Kyu

2011-02-15

Gene set analysis is a powerful method of deducing biological meaning for an a priori defined set of genes. Numerous tools have been developed to test statistical enrichment or depletion in specific pathways or gene ontology (GO) terms. Major difficulties towards biological interpretation are integrating diverse types of annotation categories and exploring the relationships between annotation terms of similar information. GARNET (Gene Annotation Relationship NEtwork Tools) is an integrative platform for gene set analysis with many novel features. It includes tools for retrieval of genes from annotation database, statistical analysis & visualization of annotation relationships, and managing gene sets. In an effort to allow access to a full spectrum of amassed biological knowledge, we have integrated a variety of annotation data that include the GO, domain, disease, drug, chromosomal location, and custom-defined annotations. Diverse types of molecular networks (pathways, transcription and microRNA regulations, protein-protein interaction) are also included. The pair-wise relationship between annotation gene sets was calculated using kappa statistics. GARNET consists of three modules--gene set manager, gene set analysis and gene set retrieval, which are tightly integrated to provide virtually automatic analysis for gene sets. A dedicated viewer for annotation network has been developed to facilitate exploration of the related annotations. GARNET (gene annotation relationship network tools) is an integrative platform for diverse types of gene set analysis, where complex relationships among gene annotations can be easily explored with an intuitive network visualization tool (http://garnet.isysbio.org/ or http://ercsb.ewha.ac.kr/garnet/).

Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

PubMed Central

Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash

2016-01-01

Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499

Transcriptome analysis of Petunia axillaris flowers reveals genes involved in morphological differentiation and metabolite transport

PubMed Central

Amano, Ikuko; Kitajima, Sakihito; Suzuki, Hideyuki; Koeduka, Takao

2018-01-01

The biosynthesis of plant secondary metabolites is associated with morphological and metabolic differentiation. As a consequence, gene expression profiles can change drastically, and primary and secondary metabolites, including intermediate and end-products, move dynamically within and between cells. However, little is known about the molecular mechanisms underlying differentiation and transport mechanisms. In this study, we performed a transcriptome analysis of Petunia axillaris subsp. parodii, which produces various volatiles in its corolla limbs and emits metabolites to attract pollinators. RNA-sequencing from leaves, buds, and limbs identified 53,243 unigenes. Analysis of differentially expressed genes, combined with gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, showed that many biological processes were highly enriched in limbs. These included catabolic processes and signaling pathways of hormones, such as gibberellins, and metabolic pathways, including phenylpropanoids and fatty acids. Moreover, we identified five transporter genes that showed high expression in limbs, and we performed spatiotemporal expression analyses and homology searches to infer their putative functions. Our systematic analysis provides comprehensive transcriptomic information regarding morphological differentiation and metabolite transport in the Petunia flower and lays the foundation for establishing the specific mechanisms that control secondary metabolite biosynthesis in plants. PMID:29902274

A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence.

PubMed

Hill, W D; Marioni, R E; Maghzian, O; Ritchie, S J; Hagenaars, S P; McIntosh, A M; Gale, C R; Davies, G; Deary, I J

2018-01-11

Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (r g  = 0.70). We used these findings as foundations for our use of a novel approach-multi-trait analysis of genome-wide association studies (MTAG; Turley et al. 2017)-to combine two large genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample. By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based GWAS. We found evidence that neurogenesis and myelination-as well as genes expressed in the synapse, and those involved in the regulation of the nervous system-may explain some of the biological differences in intelligence. The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes.

RAMONA: a Web application for gene set analysis on multilevel omics data.

PubMed

Sass, Steffen; Buettner, Florian; Mueller, Nikola S; Theis, Fabian J

2015-01-01

Decreasing costs of modern high-throughput experiments allow for the simultaneous analysis of altered gene activity on various molecular levels. However, these multi-omics approaches lead to a large amount of data, which is hard to interpret for a non-bioinformatician. Here, we present the remotely accessible multilevel ontology analysis (RAMONA). It offers an easy-to-use interface for the simultaneous gene set analysis of combined omics datasets and is an extension of the previously introduced MONA approach. RAMONA is based on a Bayesian enrichment method for the inference of overrepresented biological processes among given gene sets. Overrepresentation is quantified by interpretable term probabilities. It is able to handle data from various molecular levels, while in parallel coping with redundancies arising from gene set overlaps and related multiple testing problems. The comprehensive output of RAMONA is easy to interpret and thus allows for functional insight into the affected biological processes. With RAMONA, we provide an efficient implementation of the Bayesian inference problem such that ontologies consisting of thousands of terms can be processed in the order of seconds. RAMONA is implemented as ASP.NET Web application and publicly available at http://icb.helmholtz-muenchen.de/ramona. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Identification of gene expression profiles and key genes in subchondral bone of osteoarthritis using weighted gene coexpression network analysis.

PubMed

Guo, Sheng-Min; Wang, Jian-Xiong; Li, Jin; Xu, Fang-Yuan; Wei, Quan; Wang, Hai-Ming; Huang, Hou-Qiang; Zheng, Si-Lin; Xie, Yu-Jie; Zhang, Chi

2018-06-15

Osteoarthritis (OA) significantly influences the quality life of people around the world. It is urgent to find an effective way to understand the genetic etiology of OA. We used weighted gene coexpression network analysis (WGCNA) to explore the key genes involved in the subchondral bone pathological process of OA. Fifty gene expression profiles of GSE51588 were downloaded from the Gene Expression Omnibus database. The OA-associated genes and gene ontologies were acquired from JuniorDoc. Weighted gene coexpression network analysis was used to find disease-related networks based on 21756 gene expression correlation coefficients, hub-genes with the highest connectivity in each module were selected, and the correlation between module eigengene and clinical traits was calculated. The genes in the traits-related gene coexpression modules were subject to functional annotation and pathway enrichment analysis using ClusterProfiler. A total of 73 gene modules were identified, of which, 12 modules were found with high connectivity with clinical traits. Five modules were found with enriched OA-associated genes. Moreover, 310 OA-associated genes were found, and 34 of them were among hub-genes in each module. Consequently, enrichment results indicated some key metabolic pathways, such as extracellular matrix (ECM)-receptor interaction (hsa04512), focal adhesion (hsa04510), the phosphatidylinositol 3'-kinase (PI3K)-Akt signaling pathway (PI3K-AKT) (hsa04151), transforming growth factor beta pathway, and Wnt pathway. We intended to identify some core genes, collagen (COL)6A3, COL6A1, ITGA11, BAMBI, and HCK, which could influence downstream signaling pathways once they were activated. In this study, we identified important genes within key coexpression modules, which associate with a pathological process of subchondral bone in OA. Functional analysis results could provide important information to understand the mechanism of OA. © 2018 Wiley Periodicals, Inc.

Nonviral vectors for cancer gene therapy: prospects for integrating vectors and combination therapies.

PubMed

Ohlfest, John R; Freese, Andrew B; Largaespada, David A

2005-12-01

Gene therapy has the potential to improve the clinical outcome of many cancers by transferring therapeutic genes into tumor cells or normal host tissue. Gene transfer into tumor cells or tumor-associated stroma is being employed to induce tumor cell death, stimulate anti-tumor immune response, inhibit angiogenesis, and control tumor cell growth. Viral vectors have been used to achieve this proof of principle in animal models and, in select cases, in human clinical trials. Nevertheless, there has been considerable interest in developing nonviral vectors for cancer gene therapy. Nonviral vectors are simpler, more amenable to large-scale manufacture, and potentially safer for clinical use. Nonviral vectors were once limited by low gene transfer efficiency and transient or steadily declining gene expression. However, recent improvements in plasmid-based vectors and delivery methods are showing promise in circumventing these obstacles. This article reviews the current status of nonviral cancer gene therapy, with an emphasis on combination strategies, long-term gene transfer using transposons and bacteriophage integrases, and future directions.

MALDI-TOF mass spectrometry for quantitative gene expression analysis of acid responses in Staphylococcus aureus.

PubMed

Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild

2009-07-01

Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions.

Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool.

PubMed

Clark, Neil R; Szymkiewicz, Maciej; Wang, Zichen; Monteiro, Caroline D; Jones, Matthew R; Ma'ayan, Avi

2015-11-01

Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard. In a previously published work we proposed a geometrical approach to differential expression which performed highly in benchmarking tests and compared well to the most popular methods of differential gene expression. As reported, this approach has a natural extension to gene set analysis which we call Principal Angle Enrichment Analysis (PAEA). PAEA employs dimensionality reduction and a multivariate approach for gene set enrichment analysis. However, the performance of this method has not been assessed nor its implementation as a web-based tool. Here we describe new benchmarking protocols for gene set analysis methods and find that PAEA performs highly. The PAEA method is implemented as a user-friendly web-based tool, which contains 70 gene set libraries and is freely available to the community.

Genetic analysis of the ADGF multigene family by homologous recombination and gene conversion in Drosophila.

PubMed

Dolezal, Tomas; Gazi, Michal; Zurovec, Michal; Bryant, Peter J

2003-10-01

Many Drosophila genes exist as members of multigene families and within each family the members can be functionally redundant, making it difficult to identify them by classical mutagenesis techniques based on phenotypic screening. We have addressed this problem in a genetic analysis of a novel family of six adenosine deaminase-related growth factors (ADGFs). We used ends-in targeting to introduce mutations into five of the six ADGF genes, taking advantage of the fact that five of the family members are encoded by a three-gene cluster and a two-gene cluster. We used two targeting constructs to introduce loss-of-function mutations into all five genes, as well as to isolate different combinations of multiple mutations, independent of phenotypic consequences. The results show that (1) it is possible to use ends-in targeting to disrupt gene clusters; (2) gene conversion, which is usually considered a complication in gene targeting, can be used to help recover different mutant combinations in a single screening procedure; (3) the reduction of duplication to a single copy by induction of a double-strand break is better explained by the single-strand annealing mechanism than by simple crossing over between repeats; and (4) loss of function of the most abundantly expressed family member (ADGF-A) leads to disintegration of the fat body and the development of melanotic tumors in mutant larvae.

A single center analysis of nucleophosmin in acute myeloid leukemia: value of combining immunohistochemistry with molecular mutation analysis.

PubMed

Woolthuis, Carolien M; Mulder, André B; Verkaik-Schakel, Rikst Nynke; Rosati, Stefano; Diepstra, Arjan; van den Berg, Eva; Schuringa, Jan Jacob; Vellenga, Edo; Kluin, Philip M; Huls, Gerwin

2013-10-01

Mutations of nucleophosmin 1 are frequently found in acute myeloid leukemia and lead to aberrant cytoplasmic accumulation of nucleophosmin protein. Immunohistochemical staining is therefore recommended as the technique of choice in front-line screening. In this study, we assessed the sensitivity and specificity of immunohistochemistry on formalin-fixed bone marrow biopsies compared with gold standard molecular analysis to predict nucleophosmin 1 mutation status in 119 patients with acute myeloid leukemia. Discrepant cases were further characterized by gene expression analyses and fluorescence in situ hybridization. A large overlap between both methods was observed. Nevertheless, nine patients demonstrated discordant results at initial screening. Five cases demonstrated nuclear staining of nucleophosmin 1 by immunohistochemistry, but a nucleophosmin 1 mutation by molecular analysis. In two cases this could be attributed to technical issues and in three cases minor subpopulations of myeloblasts had not been discovered initially. All tested cases exhibited the characteristic nucleophosmin-mutated gene expression pattern. Four cases had cytoplasmic nucleophosmin 1 staining and a nucleophosmin-mutated gene expression pattern without a detectable nucleophosmin 1 mutation. In two of these cases we found the chromosomal translocation t(3;5)(q25;q35) encoding the NPM-MLF1 fusion protein. In the other discrepant cases the aberrant cytoplasmic nucleophosmin staining and gene expression could not be explained. In total six patients (5%) had true discordant results between immunohistochemistry and mutation analysis. We conclude that cytoplasmic nucleophosmin localization is not always caused by a conventional nucleophosmin 1 mutation and that in the screening for nucleophosmin 1 abnormalities, most information will be obtained by combining immunohistochemistry with molecular analysis.

A single center analysis of nucleophosmin in acute myeloid leukemia: value of combining immunohistochemistry with molecular mutation analysis

PubMed Central

Woolthuis, Carolien M.; Mulder, André B.; Verkaik-Schakel, Rikst Nynke; Rosati, Stefano; Diepstra, Arjan; van den Berg, Eva; Schuringa, Jan Jacob; Vellenga, Edo; Kluin, Philip M.; Huls, Gerwin

2013-01-01

Mutations of nucleophosmin 1 are frequently found in acute myeloid leukemia and lead to aberrant cytoplasmic accumulation of nucleophosmin protein. Immunohistochemical staining is therefore recommended as the technique of choice in front-line screening. In this study, we assessed the sensitivity and specificity of immunohistochemistry on formalin-fixed bone marrow biopsies compared with gold standard molecular analysis to predict nucleophosmin 1 mutation status in 119 patients with acute myeloid leukemia. Discrepant cases were further characterized by gene expression analyses and fluorescence in situ hybridization. A large overlap between both methods was observed. Nevertheless, nine patients demonstrated discordant results at initial screening. Five cases demonstrated nuclear staining of nucleophosmin 1 by immunohistochemistry, but a nucleophosmin 1 mutation by molecular analysis. In two cases this could be attributed to technical issues and in three cases minor subpopulations of myeloblasts had not been discovered initially. All tested cases exhibited the characteristic nucleophosmin-mutated gene expression pattern. Four cases had cytoplasmic nucleophosmin 1 staining and a nucleophosmin-mutated gene expression pattern without a detectable nucleophosmin 1 mutation. In two of these cases we found the chromosomal translocation t(3;5)(q25;q35) encoding the NPM-MLF1 fusion protein. In the other discrepant cases the aberrant cytoplasmic nucleophosmin staining and gene expression could not be explained. In total six patients (5%) had true discordant results between immunohistochemistry and mutation analysis. We conclude that cytoplasmic nucleophosmin localization is not always caused by a conventional nucleophosmin 1 mutation and that in the screening for nucleophosmin 1 abnormalities, most information will be obtained by combining immunohistochemistry with molecular analysis. PMID:23716555

Model-based gene set analysis for Bioconductor.

PubMed

Bauer, Sebastian; Robinson, Peter N; Gagneur, Julien

2011-07-01

Gene Ontology and other forms of gene-category analysis play a major role in the evaluation of high-throughput experiments in molecular biology. Single-category enrichment analysis procedures such as Fisher's exact test tend to flag large numbers of redundant categories as significant, which can complicate interpretation. We have recently developed an approach called model-based gene set analysis (MGSA), that substantially reduces the number of redundant categories returned by the gene-category analysis. In this work, we present the Bioconductor package mgsa, which makes the MGSA algorithm available to users of the R language. Our package provides a simple and flexible application programming interface for applying the approach. The mgsa package has been made available as part of Bioconductor 2.8. It is released under the conditions of the Artistic license 2.0. peter.robinson@charite.de; julien.gagneur@embl.de.

GSCALite: A Web Server for Gene Set Cancer Analysis.

PubMed

Liu, Chun-Jie; Hu, Fei-Fei; Xia, Mengxuan; Han, Leng; Zhang, Qiong; Guo, An-Yuan

2018-05-22

The availability of cancer genomic data makes it possible to analyze genes related to cancer. Cancer is usually the result of a set of genes and the signal of a single gene could be covered by background noise. Here, we present a web server named Gene Set Cancer Analysis (GSCALite) to analyze a set of genes in cancers with the following functional modules. (i) Differential expression in tumor vs normal, and the survival analysis; (ii) Genomic variations and their survival analysis; (iii) Gene expression associated cancer pathway activity; (iv) miRNA regulatory network for genes; (v) Drug sensitivity for genes; (vi) Normal tissue expression and eQTL for genes. GSCALite is a user-friendly web server for dynamic analysis and visualization of gene set in cancer and drug sensitivity correlation, which will be of broad utilities to cancer researchers. GSCALite is available on http://bioinfo.life.hust.edu.cn/web/GSCALite/. guoay@hust.edu.cn or zhangqiong@hust.edu.cn. Supplementary data are available at Bioinformatics online.

Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells

PubMed Central

de Luis Balaguer, Maria Angels; Fisher, Adam P.; Clark, Natalie M.; Fernandez-Espinosa, Maria Guadalupe; Möller, Barbara K.; Weijers, Dolf; Williams, Cranos; Lorenzo, Oscar; Sozzani, Rosangela

2017-01-01

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is essential for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. To accomplish this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network inference algorithm that combines clustering with dynamic Bayesian network inference. We leveraged the topology of our networks to infer potential major regulators. Specifically, through mathematical modeling and experimental validation, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center function. The results presented in this work show that our combination of molecular biology, computational biology, and mathematical modeling is an efficient approach to identify candidate factors that function in the stem cells. PMID:28827319

Combining R gene and quantitative resistance increases effectiveness of cultivar resistance against Leptosphaeria maculans in Brassica napus in different environments

PubMed Central

Mitrousia, Georgia K.; Sidique, Siti Nordahliawate M.; Qi, Aiming; Fitt, Bruce D. L.

2018-01-01

Using cultivar resistance against pathogens is one of the most economical and environmentally friendly methods for control of crop diseases. However, cultivar resistance can be easily rendered ineffective due to changes in pathogen populations or environments. To test the hypothesis that combining R gene-mediated resistance and quantitative resistance (QR) in one cultivar can provide more effective resistance than use of either type of resistance on its own, effectiveness of resistance in eight oilseed rape (Brassica napus) cultivars with different R genes and/or QR against Leptosphaeria maculans (phoma stem canker) was investigated in 13 different environments/sites over three growing seasons (2010/2011, 2011/2012 and 2012/2013). Cultivar Drakkar with no R genes and no QR was used as susceptible control and for sampling L. maculans populations. Isolates of L. maculans were obtained from the 13 sites in 2010/2011 to assess frequencies of avirulent alleles of different effector genes (AvrLm1, AvrLm4 or AvrLm7) corresponding to the resistance genes (Rlm1, Rlm4 or Rlm7) used in the field experiments. Results of field experiments showed that cultivars DK Cabernet (Rlm1 + QR) and Adriana (Rlm4 + QR) had significantly less severe phoma stem canker than cultivars Capitol (Rlm1) and Bilbao (Rlm4), respectively. Results of controlled environment experiments confirmed the presence of Rlm genes and/or QR in these four cultivars. Analysis of L. maculans populations from different sites showed that the mean frequencies of AvrLm1 (10%) and AvrLm4 (41%) were less than that of AvrLm7 (100%), suggesting that Rlm1 and Rlm4 gene-mediated resistances were partially rendered ineffective while Rlm7 resistance was still effective. Cultivar Excel (Rlm7 + QR) had less severe canker than cultivar Roxet (Rlm7), but the difference between them was not significant due to influence of the effective resistance gene Rlm7. For the two cultivars with only QR, Es-Astrid (QR) had less severe stem

Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data.

PubMed

Tintle, Nathan L; Sitarik, Alexandra; Boerema, Benjamin; Young, Kylie; Best, Aaron A; Dejongh, Matthew

2012-08-08

Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

Toxicogenomic analysis in the combined effect of tributyltin and benzo[a]pyrene on the development of zebrafish embryos.

PubMed

Huang, Lixing; Zuo, Zhenghong; Zhang, Youyu; Wang, Chonggang

2015-01-01

There is a growing recognition that the toxic effects of chemical mixtures are been an important issue in toxicological sciences. Tributyltin (TBT) and benzo[a]pyrene (BaP) are widespread pollutants that occur simultaneously in the aquatic environments. This study was designed to examine comprehensively the combined effects of TBT and BaP on zebrafish (Danio rerio) embryos using toxicogenomic approach combined with biochemical detection and morphological analysis, and tried to gain insight into the mechanisms underlying the combined effects of TBT and BaP. The results of toxicogenomic data indicated that: (1) TBT cotreatment rescued the embryos from decreased hatching ratio caused by BaP alone, while the alteration of gene expression (in this article the phrase gene expression is used as a synonym to gene transcription, although in is acknowledged that gene expression can also be regulated by, e.g., translation and mRNA or protein stability) relative to zebrafish hatching in the BaP groups was resumed by the cotreatment with TBT; (2) BaP cotreatment decreased TBT-mediated dorsal curvature, and alleviated the perturbation of Notch pathway caused by TBT alone; (3) cotreatment with TBT decreased BaP-mediated bradycardia, which might be due to that TBT cotreatment alleviated the perturbation in expression of genes related to cardiac muscle cell development and calcium handling caused by BaP alone; 4) TBT cotreatment brought an antagonistic effect on the BaP-mediated oxidative stress and DNA damage. These results suggested that toxicogenomic approach was available for analyzing combined toxicity with high sensitivity and accuracy, which might improve our understanding and predictability for the combined effects of chemicals. Copyright © 2014 Elsevier B.V. All rights reserved.

Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool

PubMed Central

Clark, Neil R.; Szymkiewicz, Maciej; Wang, Zichen; Monteiro, Caroline D.; Jones, Matthew R.; Ma’ayan, Avi

2016-01-01

Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard. In a previously published work we proposed a geometrical approach to differential expression which performed highly in benchmarking tests and compared well to the most popular methods of differential gene expression. As reported, this approach has a natural extension to gene set analysis which we call Principal Angle Enrichment Analysis (PAEA). PAEA employs dimensionality reduction and a multivariate approach for gene set enrichment analysis. However, the performance of this method has not been assessed nor its implementation as a web-based tool. Here we describe new benchmarking protocols for gene set analysis methods and find that PAEA performs highly. The PAEA method is implemented as a user-friendly web-based tool, which contains 70 gene set libraries and is freely available to the community. PMID:26848405

Combining Cytotoxic and Immune-Mediated Gene Therapy to Treat Brain Tumors

PubMed Central

Curtin, James F.; King, Gwendalyn D.; Candolfi, Marianela; Greeno, Remy B.; Kroeger, Kurt M.; Lowenstein, Pedro R.; Castro, Maria G.

2006-01-01

Glioblastoma (GBM) is a type of intracranial brain tumor, for which there is no cure. In spite of advances in surgery, chemotherapy and radiotherapy, patients die within a year of diagnosis. Therefore, there is a critical need to develop novel therapeutic approaches for this disease. Gene therapy, which is the use of genes or other nucleic acids as drugs, is a powerful new treatment strategy which can be developed to treat GBM. Several treatment modalities are amenable for gene therapy implementation, e.g. conditional cytotoxic approaches, targeted delivery of toxins into the tumor mass, immune stimulatory strategies, and these will all be the focus of this review. Both conditional cytotoxicity and targeted toxin mediated tumor death, are aimed at eliminating an established tumor mass and preventing further growth. Tumors employ several defensive strategies that suppress and inhibit anti-tumor immune responses. A better understanding of the mechanisms involved in eliciting anti-tumor immune responses has identified promising targets for immunotherapy. Immunotherapy is designed to aid the immune system to recognize and destroy tumor cells in order to eliminate the tumor burden. Also, immune-therapeutic strategies have the added advantage that an activated immune system has the capability of recognizing tumor cells at distant sites from the primary tumor, therefore targeting metastasis distant from the primary tumor locale. Pre-clinical models and clinical trials have demonstrated that in spite of their location within the central nervous system (CNS), a tissue described as ‘immune privileged’, brain tumors can be effectively targeted by the activated immune system following various immunotherapeutic strategies. This review will highlight recent advances in brain tumor immunotherapy, with particular emphasis on advances made using gene therapy strategies, as well as reviewing other novel therapies that can be used in combination with immunotherapy. Another

Treatment of Diabetic Mice with a Combination of Ketogenic Diet and Aerobic Exercise via Modulations of PPARs Gene Programs

PubMed Central

Xu, Lingyan; Xia, Jie; Wang, Dongmei; Qian, Min

2018-01-01

Type 2 diabetes is a prevalent chronic disease arising as a serious public health problem worldwide. Diet intervention is considered to be a critical strategy in glycemic control of diabetic patients. Recently, the low-carbohydrate ketogenic diet is shown to be effective in glycemic control and weight loss. However, hepatic lipid accumulation could be observed in mice treated with ketogenic diet. On the other hand, exercise is a well-known approach for treating nonalcoholic fatty liver disease. We thus hypothesize that the combination of ketogenic diet and exercise could improve insulin sensitivity, while minimizing adverse effect of hepatic steatosis. In order to test this hypothesis, we established diabetic mice model with streptozotocin (STZ) and divided them into control group, ketogenic diet group, and ketogenic diet with aerobic exercise group. We found that after six weeks of intervention, mice treated with ketogenic diet and ketogenic diet combined with exercise both have lower body weights, HbAlc level, HOMA index, and improvements in insulin sensitivity, compared with diabetes group. In addition, mice in ketogenic diet intervention exhibited hepatic steatosis shown by serum and hepatic parameters, as well as histochemistry staining in the liver, which could be largely relieved by exercise. Furthermore, gene analysis revealed that ketogenic diet in combination with exercise reduced PPARγ and lipid synthetic genes, as well as enhancing PPARα and lipid β-oxidation gene program in the liver compared to those in ketogenic diet without exercise. Overall, the present study demonstrated that the combination of ketogenic diet and a moderate-intensity aerobic exercise intervention improved insulin sensitivity in diabetic mice, while avoiding hepatic steatosis, which provided a novel strategy in the combat of diabetes. PMID:29743883

Treatment of Diabetic Mice with a Combination of Ketogenic Diet and Aerobic Exercise via Modulations of PPARs Gene Programs.

PubMed

Zhang, Qiang; Xu, Lingyan; Xia, Jie; Wang, Dongmei; Qian, Min; Ding, Shuzhe

2018-01-01

Type 2 diabetes is a prevalent chronic disease arising as a serious public health problem worldwide. Diet intervention is considered to be a critical strategy in glycemic control of diabetic patients. Recently, the low-carbohydrate ketogenic diet is shown to be effective in glycemic control and weight loss. However, hepatic lipid accumulation could be observed in mice treated with ketogenic diet. On the other hand, exercise is a well-known approach for treating nonalcoholic fatty liver disease. We thus hypothesize that the combination of ketogenic diet and exercise could improve insulin sensitivity, while minimizing adverse effect of hepatic steatosis. In order to test this hypothesis, we established diabetic mice model with streptozotocin (STZ) and divided them into control group, ketogenic diet group, and ketogenic diet with aerobic exercise group. We found that after six weeks of intervention, mice treated with ketogenic diet and ketogenic diet combined with exercise both have lower body weights, HbAlc level, HOMA index, and improvements in insulin sensitivity, compared with diabetes group. In addition, mice in ketogenic diet intervention exhibited hepatic steatosis shown by serum and hepatic parameters, as well as histochemistry staining in the liver, which could be largely relieved by exercise. Furthermore, gene analysis revealed that ketogenic diet in combination with exercise reduced PPAR γ and lipid synthetic genes, as well as enhancing PPAR α and lipid β -oxidation gene program in the liver compared to those in ketogenic diet without exercise. Overall, the present study demonstrated that the combination of ketogenic diet and a moderate-intensity aerobic exercise intervention improved insulin sensitivity in diabetic mice, while avoiding hepatic steatosis, which provided a novel strategy in the combat of diabetes.

Graphite Web: web tool for gene set analysis exploiting pathway topology

PubMed Central

Sales, Gabriele; Calura, Enrica; Martini, Paolo; Romualdi, Chiara

2013-01-01

Graphite web is a novel web tool for pathway analyses and network visualization for gene expression data of both microarray and RNA-seq experiments. Several pathway analyses have been proposed either in the univariate or in the global and multivariate context to tackle the complexity and the interpretation of expression results. These methods can be further divided into ‘topological’ and ‘non-topological’ methods according to their ability to gain power from pathway topology. Biological pathways are, in fact, not only gene lists but can be represented through a network where genes and connections are, respectively, nodes and edges. To this day, the most used approaches are non-topological and univariate although they miss the relationship among genes. On the contrary, topological and multivariate approaches are more powerful, but difficult to be used by researchers without bioinformatic skills. Here we present Graphite web, the first public web server for pathway analysis on gene expression data that combines topological and multivariate pathway analyses with an efficient system of interactive network visualizations for easy results interpretation. Specifically, Graphite web implements five different gene set analyses on three model organisms and two pathway databases. Graphite Web is freely available at http://graphiteweb.bio.unipd.it/. PMID:23666626

Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application

PubMed Central

Roubelakis, Maria G; Zotos, Pantelis; Papachristoudis, Georgios; Michalopoulos, Ioannis; Pappa, Kalliopi I; Anagnou, Nicholas P; Kossida, Sophia

2009-01-01

Background microRNAs (miRNAs) are single-stranded RNA molecules of about 20–23 nucleotides length found in a wide variety of organisms. miRNAs regulate gene expression, by interacting with target mRNAs at specific sites in order to induce cleavage of the message or inhibit translation. Predicting or verifying mRNA targets of specific miRNAs is a difficult process of great importance. Results GOmir is a novel stand-alone application consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools as well as the experimentally supported targets from TarBase and also providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir represents a new tool incorporating two separate Java applications integrated into one stand-alone Java application. Conclusion GOmir (by using up to five different databases) introduces miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering. Additionally, a reverse search initiated by a potential target can also be conducted. GOmir can freely be downloaded BRFAA. PMID:19534746

Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application.

PubMed

Roubelakis, Maria G; Zotos, Pantelis; Papachristoudis, Georgios; Michalopoulos, Ioannis; Pappa, Kalliopi I; Anagnou, Nicholas P; Kossida, Sophia

2009-06-16

microRNAs (miRNAs) are single-stranded RNA molecules of about 20-23 nucleotides length found in a wide variety of organisms. miRNAs regulate gene expression, by interacting with target mRNAs at specific sites in order to induce cleavage of the message or inhibit translation. Predicting or verifying mRNA targets of specific miRNAs is a difficult process of great importance. GOmir is a novel stand-alone application consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools as well as the experimentally supported targets from TarBase and also providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir represents a new tool incorporating two separate Java applications integrated into one stand-alone Java application. GOmir (by using up to five different databases) introduces miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering. Additionally, a reverse search initiated by a potential target can also be conducted. GOmir can freely be downloaded BRFAA.

MAVTgsa: An R Package for Gene Set (Enrichment) Analysis

DOE PAGES

Chien, Chih-Yi; Chang, Ching-Wei; Tsai, Chen-An; ...

2014-01-01

Gene semore » t analysis methods aim to determine whether an a priori defined set of genes shows statistically significant difference in expression on either categorical or continuous outcomes. Although many methods for gene set analysis have been proposed, a systematic analysis tool for identification of different types of gene set significance modules has not been developed previously. This work presents an R package, called MAVTgsa, which includes three different methods for integrated gene set enrichment analysis. (1) The one-sided OLS (ordinary least squares) test detects coordinated changes of genes in gene set in one direction, either up- or downregulation. (2) The two-sided MANOVA (multivariate analysis variance) detects changes both up- and downregulation for studying two or more experimental conditions. (3) A random forests-based procedure is to identify gene sets that can accurately predict samples from different experimental conditions or are associated with the continuous phenotypes. MAVTgsa computes the P values and FDR (false discovery rate) q -value for all gene sets in the study. Furthermore, MAVTgsa provides several visualization outputs to support and interpret the enrichment results. This package is available online.« less

[Differential gene expression in incompatible interaction between Lilium regale Wilson and Fusarium oxysporum f. sp. lilii revealed by combined SSH and microarray analysis].

PubMed

Rao, J; Liu, D; Zhang, N; He, H; Ge, F; Chen, C

2014-01-01

Fusarium wilt, caused by a soilborne pathogen Fusarium oxysporum f. sp. lilii, is the major disease of lily (Lilium L.). In order to isolate the genes differentially expressed in a resistant reaction to F. oxysporum in L. regale Wilson, a cDNA library was constructed with L. regale root during F. oxysporum infection using the suppression subtractive hybridization (SSH), and a total of 585 unique expressed sequence tags (ESTs) were obtained. Furthermore, the gene expression profiles in the incompatible interaction between L. regale and F. oxysporum were revealed by oligonucleotide microarray analysis of 585 unique ESTs comparison to the compatible interaction between a susceptible Lilium Oriental Hybrid 'Siberia' and F. oxysporum. The result of expression profile analysis indicated that the genes encoding pathogenesis-related proteins (PRs), antioxidative stress enzymes, secondary metabolism enzymes, transcription factors, signal transduction proteins as well as a large number of unknown genes were involved in early defense response of L. regale to F. oxysporum infection. Moreover, the following quantitative reverse transcription PCR (QRT-PCR) analysis confirmed reliability of the oligonucleotide microarray data. In the present study, isolation of differentially expressed genes in L. regale during response to F. oxysporum helped to uncover the molecular mechanism associated with the resistance of L. regale against F. oxysporum.

Separate enrichment analysis of pathways for up- and downregulated genes.

PubMed

Hong, Guini; Zhang, Wenjing; Li, Hongdong; Shen, Xiaopei; Guo, Zheng

2014-03-06

Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.

Genome-wide analysis of the Dof transcription factor gene family reveals soybean-specific duplicable and functional characteristics.

PubMed

Guo, Yong; Qiu, Li-Juan

2013-01-01

The Dof domain protein family is a classic plant-specific zinc-finger transcription factor family involved in a variety of biological processes. There is great diversity in the number of Dof genes in different plants. However, there are only very limited reports on the characterization of Dof transcription factors in soybean (Glycine max). In the present study, 78 putative Dof genes were identified from the whole-genome sequence of soybean. The predicted GmDof genes were non-randomly distributed within and across 19 out of 20 chromosomes and 97.4% (38 pairs) were preferentially retained duplicate paralogous genes located in duplicated regions of the genome. Soybean-specific segmental duplications contributed significantly to the expansion of the soybean Dof gene family. These Dof proteins were phylogenetically clustered into nine distinct subgroups among which the gene structure and motif compositions were considerably conserved. Comparative phylogenetic analysis of these Dof proteins revealed four major groups, similar to those reported for Arabidopsis and rice. Most of the GmDofs showed specific expression patterns based on RNA-seq data analyses. The expression patterns of some duplicate genes were partially redundant while others showed functional diversity, suggesting the occurrence of sub-functionalization during subsequent evolution. Comprehensive expression profile analysis also provided insights into the soybean-specific functional divergence among members of the Dof gene family. Cis-regulatory element analysis of these GmDof genes suggested diverse functions associated with different processes. Taken together, our results provide useful information for the functional characterization of soybean Dof genes by combining phylogenetic analysis with global gene-expression profiling.

Gene-based rare allele analysis identified a risk gene of Alzheimer's disease.

PubMed

Kim, Jong Hun; Song, Pamela; Lim, Hyunsun; Lee, Jae-Hyung; Lee, Jun Hong; Park, Sun Ah

2014-01-01

Alzheimer's disease (AD) has a strong propensity to run in families. However, the known risk genes excluding APOE are not clinically useful. In various complex diseases, gene studies have targeted rare alleles for unsolved heritability. Our study aims to elucidate previously unknown risk genes for AD by targeting rare alleles. We used data from five publicly available genetic studies from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the database of Genotypes and Phenotypes (dbGaP). A total of 4,171 cases and 9,358 controls were included. The genotype information of rare alleles was imputed using 1,000 genomes. We performed gene-based analysis of rare alleles (minor allele frequency≤3%). The genome-wide significance level was defined as meta P<1.8×10(-6) (0.05/number of genes in human genome = 0.05/28,517). ZNF628, which is located at chromosome 19q13.42, showed a genome-wide significant association with AD. The association of ZNF628 with AD was not dependent on APOE ε4. APOE and TREM2 were also significantly associated with AD, although not at genome-wide significance levels. Other genes identified by targeting common alleles could not be replicated in our gene-based rare allele analysis. We identified that rare variants in ZNF628 are associated with AD. The protein encoded by ZNF628 is known as a transcription factor. Furthermore, the associations of APOE and TREM2 with AD were highly significant, even in gene-based rare allele analysis, which implies that further deep sequencing of these genes is required in AD heritability studies.

The Use of a Combined Bioinformatics Approach to Locate Antibiotic Resistance Genes on Plasmids From Whole Genome Sequences of Salmonella enterica Serovars From Humans in Ghana.

PubMed

Kudirkiene, Egle; Andoh, Linda A; Ahmed, Shahana; Herrero-Fresno, Ana; Dalsgaard, Anders; Obiri-Danso, Kwasi; Olsen, John E

2018-01-01

In the current study, we identified plasmids carrying antimicrobial resistance genes in draft whole genome sequences of 16 selected Salmonella enterica isolates representing six different serovars from humans in Ghana. The plasmids and the location of resistance genes in the genomes were predicted using a combination of PlasmidFinder, ResFinder, plasmidSPAdes and BLAST genomic analysis tools. Subsequently, S1-PFGE was employed for analysis of plasmid profiles. Whole genome sequencing confirmed the presence of antimicrobial resistance genes in Salmonella isolates showing multidrug resistance phenotypically. ESBL, either bla TEM52-B or bla CTX-M15 were present in two cephalosporin resistant isolates of S . Virchow and S . Poona, respectively. The systematic genome analysis revealed the presence of different plasmids in different serovars, with or without insertion of antimicrobial resistance genes. In S . Enteritidis, resistance genes were carried predominantly on plasmids of IncN type, in S . Typhimurium on plasmids of IncFII(S)/IncFIB(S)/IncQ1 type. In S . Virchow and in S . Poona, resistance genes were detected on plasmids of IncX1 and TrfA/IncHI2/IncHI2A type, respectively. The latter two plasmids were described for the first time in these serovars. The combination of genomic analytical tools allowed nearly full mapping of the resistance plasmids in all Salmonella strains analyzed. The results suggest that the improved analytical approach used in the current study may be used to identify plasmids that are specifically associated with resistance phenotypes in whole genome sequences. Such knowledge would allow the development of rapid multidrug resistance tracking tools in Salmonella populations using WGS.

[Analysis of horizontal transfer gene of Bombyx mori NPV].

PubMed

Duan, Hai-Rong; Qiu, De-Bin; Gong, Cheng-Liang; Huang, Mo-Li

2011-06-01

For research on genetic characters and evolutionary origin of the genome of baculoviruses, a comprehensive homology search and phylogenetic analysis of the complete genomes of Bombyx mori NPV and Bombyx mori were used. Three horizontally transferred genes (inhibitor of apoptosis, chitinase, and UDP-glucosyltransferase) were identified, and there was evidence that all of these genes were derived from the insect host. The results of analysis showed lots of differences between the features of horizontal transferred genes and the ones of whole genomic genes, such as nucleotide composition, codon usagebias and selection pressure. These results reconfirmed that the horizontally transferred genes are exogenous. The analysis of gene function suggested that horizontally transferred genes acquired from an ancestral host insect can increase the efficiency of baculoviruses transmission.

Combined magnetic and gravity analysis

NASA Technical Reports Server (NTRS)

Hinze, W. J.; Braile, L. W.; Chandler, V. W.; Mazella, F. E.

1975-01-01

Efforts are made to identify methods of decreasing magnetic interpretation ambiguity by combined gravity and magnetic analysis, to evaluate these techniques in a preliminary manner, to consider the geologic and geophysical implications of correlation, and to recommend a course of action to evaluate methods of correlating gravity and magnetic anomalies. The major thrust of the study was a search and review of the literature. The literature of geophysics, geology, geography, and statistics was searched for articles dealing with spatial correlation of independent variables. An annotated bibliography referencing the Germane articles and books is presented. The methods of combined gravity and magnetic analysis techniques are identified and reviewed. A more comprehensive evaluation of two types of techniques is presented. Internal correspondence of anomaly amplitudes is examined and a combined analysis is done utilizing Poisson's theorem. The geologic and geophysical implications of gravity and magnetic correlation based on both theoretical and empirical relationships are discussed.

Combined DNA methylation and gene expression profiling in gastrointestinal stromal tumors reveals hypomethylation of SPP1 as an independent prognostic factor.

PubMed

Haller, Florian; Zhang, Jitao David; Moskalev, Evgeny A; Braun, Alexander; Otto, Claudia; Geddert, Helene; Riazalhosseini, Yasser; Ward, Aoife; Balwierz, Aleksandra; Schaefer, Inga-Marie; Cameron, Silke; Ghadimi, B Michael; Agaimy, Abbas; Fletcher, Jonathan A; Hoheisel, Jörg; Hartmann, Arndt; Werner, Martin; Wiemann, Stefan; Sahin, Ozgür

2015-03-01

Gastrointestinal stromal tumors (GISTs) have distinct gene expression patterns according to localization, genotype and aggressiveness. DNA methylation at CpG dinucleotides is an important mechanism for regulation of gene expression. We performed targeted DNA methylation analysis of 1.505 CpG loci in 807 cancer-related genes in a cohort of 76 GISTs, combined with genome-wide mRNA expression analysis in 22 GISTs, to identify signatures associated with clinicopathological parameters and prognosis. Principal component analysis revealed distinct DNA methylation patterns associated with anatomical localization, genotype, mitotic counts and clinical follow-up. Methylation of a single CpG dinucleotide in the non-CpG island promoter of SPP1 was significantly correlated with shorter disease-free survival. Hypomethylation of this CpG was an independent prognostic parameter in a multivariate analysis compared to anatomical localization, genotype, tumor size and mitotic counts in a cohort of 141 GISTs with clinical follow-up. The epigenetic regulation of SPP1 was confirmed in vitro, and the functional impact of SPP1 protein on tumorigenesis-related signaling pathways was demonstrated. In summary, SPP1 promoter methylation is a novel and independent prognostic parameter in GISTs, and might be helpful in estimating the aggressiveness of GISTs from the intermediate-risk category. © 2014 UICC.

Prioritization of candidate disease genes by combining topological similarity and semantic similarity.

PubMed

Liu, Bin; Jin, Min; Zeng, Pan

2015-10-01

The identification of gene-phenotype relationships is very important for the treatment of human diseases. Studies have shown that genes causing the same or similar phenotypes tend to interact with each other in a protein-protein interaction (PPI) network. Thus, many identification methods based on the PPI network model have achieved good results. However, in the PPI network, some interactions between the proteins encoded by candidate gene and the proteins encoded by known disease genes are very weak. Therefore, some studies have combined the PPI network with other genomic information and reported good predictive performances. However, we believe that the results could be further improved. In this paper, we propose a new method that uses the semantic similarity between the candidate gene and known disease genes to set the initial probability vector of a random walk with a restart algorithm in a human PPI network. The effectiveness of our method was demonstrated by leave-one-out cross-validation, and the experimental results indicated that our method outperformed other methods. Additionally, our method can predict new causative genes of multifactor diseases, including Parkinson's disease, breast cancer and obesity. The top predictions were good and consistent with the findings in the literature, which further illustrates the effectiveness of our method. Copyright © 2015 Elsevier Inc. All rights reserved.

Global gene expression analysis combined with a genomics approach for the identification of signal transduction networks involved in postnatal mouse myocardial proliferation and development.

PubMed

Wang, Ruoxin; Su, Chao; Wang, Xinting; Fu, Qiang; Gao, Xingjie; Zhang, Chunyan; Yang, Jie; Yang, Xi; Wei, Minxin

2018-01-01

Mammalian cardiomyocytes may permanently lose their ability to proliferate after birth. Therefore, studying the proliferation and growth arrest of cardiomyocytes during the postnatal period may enhance the current understanding regarding this molecular mechanism. The present study identified the differentially expressed genes in hearts obtained from 24 h‑old mice, which contain proliferative cardiomyocytes; 7‑day‑old mice, in which the cardiomyocytes are undergoing a proliferative burst; and 10‑week‑old mice, which contain growth‑arrested cardiomyocytes, using global gene expression analysis. Furthermore, myocardial proliferation and growth arrest were analyzed from numerous perspectives, including Gene Ontology annotation, cluster analysis, pathway enrichment and network construction. The results of a Gene Ontology analysis indicated that, with increasing age, enriched gene function was not only associated with cell cycle, cell division and mitosis, but was also associated with metabolic processes and protein synthesis. In the pathway analysis, 'cell cycle', proliferation pathways, such as the 'PI3K‑AKT signaling pathway', and 'metabolic pathways' were well represented. Notably, the cluster analysis revealed that bone morphogenetic protein (BMP)1, BMP10, cyclin E2, E2F transcription factor 1 and insulin like growth factor 1 exhibited increased expression in hearts obtained from 7‑day‑old mice. In addition, the signal transduction pathway associated with the cell cycle was identified. The present study primarily focused on genes with altered expression, including downregulated anaphase promoting complex subunit 1, cell division cycle (CDC20), cyclin dependent kinase 1, MYC proto-oncogene, bHLH transcription factor and CDC25C, and upregulated growth arrest and DNA damage inducible α in 10-week group, which may serve important roles in postnatal myocardial cell cycle arrest. In conclusion, these data may provide important information

Combining evidence, biomedical literature and statistical dependence: new insights for functional annotation of gene sets

PubMed Central

Aubry, Marc; Monnier, Annabelle; Chicault, Celine; de Tayrac, Marie; Galibert, Marie-Dominique; Burgun, Anita; Mosser, Jean

2006-01-01

Background Large-scale genomic studies based on transcriptome technologies provide clusters of genes that need to be functionally annotated. The Gene Ontology (GO) implements a controlled vocabulary organised into three hierarchies: cellular components, molecular functions and biological processes. This terminology allows a coherent and consistent description of the knowledge about gene functions. The GO terms related to genes come primarily from semi-automatic annotations made by trained biologists (annotation based on evidence) or text-mining of the published scientific literature (literature profiling). Results We report an original functional annotation method based on a combination of evidence and literature that overcomes the weaknesses and the limitations of each approach. It relies on the Gene Ontology Annotation database (GOA Human) and the PubGene biomedical literature index. We support these annotations with statistically associated GO terms and retrieve associative relations across the three GO hierarchies to emphasise the major pathways involved by a gene cluster. Both annotation methods and associative relations were quantitatively evaluated with a reference set of 7397 genes and a multi-cluster study of 14 clusters. We also validated the biological appropriateness of our hybrid method with the annotation of a single gene (cdc2) and that of a down-regulated cluster of 37 genes identified by a transcriptome study of an in vitro enterocyte differentiation model (CaCo-2 cells). Conclusion The combination of both approaches is more informative than either separate approach: literature mining can enrich an annotation based only on evidence. Text-mining of the literature can also find valuable associated MEDLINE references that confirm the relevance of the annotation. Eventually, GO terms networks can be built with associative relations in order to highlight cooperative and competitive pathways and their connected molecular functions. PMID:16674810

A fungal phylogeny based on 42 complete genomes derived from supertree and combined gene analysis

PubMed Central

Fitzpatrick, David A; Logue, Mary E; Stajich, Jason E; Butler, Geraldine

2006-01-01

Background To date, most fungal phylogenies have been derived from single gene comparisons, or from concatenated alignments of a small number of genes. The increase in fungal genome sequencing presents an opportunity to reconstruct evolutionary events using entire genomes. As a tool for future comparative, phylogenomic and phylogenetic studies, we used both supertrees and concatenated alignments to infer relationships between 42 species of fungi for which complete genome sequences are available. Results A dataset of 345,829 genes was extracted from 42 publicly available fungal genomes. Supertree methods were employed to derive phylogenies from 4,805 single gene families. We found that the average consensus supertree method may suffer from long-branch attraction artifacts, while matrix representation with parsimony (MRP) appears to be immune from these. A genome phylogeny was also reconstructed from a concatenated alignment of 153 universally distributed orthologs. Our MRP supertree and concatenated phylogeny are highly congruent. Within the Ascomycota, the sub-phyla Pezizomycotina and Saccharomycotina were resolved. Both phylogenies infer that the Leotiomycetes are the closest sister group to the Sordariomycetes. There is some ambiguity regarding the placement of Stagonospora nodurum, the sole member of the class Dothideomycetes present in the dataset. Within the Saccharomycotina, a monophyletic clade containing organisms that translate CTG as serine instead of leucine is evident. There is also strong support for two groups within the CTG clade, one containing the fully sexual species Candida lusitaniae, Candida guilliermondii and Debaryomyces hansenii, and the second group containing Candida albicans, Candida dubliniensis, Candida tropicalis, Candida parapsilosis and Lodderomyces elongisporus. The second major clade within the Saccharomycotina contains species whose genomes have undergone a whole genome duplication (WGD), and their close relatives. We could not

Bacteriophage Mediates Efficient Gene Transfer in Combination with Conventional Transfection Reagents

PubMed Central

Donnelly, Amanda; Yata, Teerapong; Bentayebi, Kaoutar; Suwan, Keittisak; Hajitou, Amin

2015-01-01

The development of commercially available transfection reagents for gene transfer applications has revolutionized the field of molecular biology and scientific research. However, the challenge remains in ensuring that they are efficient, safe, reproducible and cost effective. Bacteriophage (phage)-based viral vectors have the potential to be utilized for general gene transfer applications within research and industry. Yet, they require adaptations in order to enable them to efficiently enter cells and overcome mammalian cellular barriers, as they infect bacteria only; furthermore, limited progress has been made at increasing their efficiency. The production of a novel hybrid nanocomplex system consisting of two different nanomaterial systems, phage vectors and conventional transfection reagents, could overcome these limitations. Here we demonstrate that the combination of cationic lipids, cationic polymers or calcium phosphate with M13 bacteriophage-derived vectors, engineered to carry a mammalian transgene cassette, resulted in increased cellular attachment, entry and improved transgene expression in human cells. Moreover, addition of a targeting ligand into the nanocomplex system, through genetic engineering of the phage capsid further increased gene expression and was effective in a stable cell line generation application. Overall, this new hybrid nanocomplex system (i) provides enhanced phage-mediated gene transfer; (ii) is applicable for laboratory transfection processes and (iii) shows promise within industry for large-scale gene transfer applications. PMID:26670247

Bacteriophage Mediates Efficient Gene Transfer in Combination with Conventional Transfection Reagents.

PubMed

Donnelly, Amanda; Yata, Teerapong; Bentayebi, Kaoutar; Suwan, Keittisak; Hajitou, Amin

2015-12-08

The development of commercially available transfection reagents for gene transfer applications has revolutionized the field of molecular biology and scientific research. However, the challenge remains in ensuring that they are efficient, safe, reproducible and cost effective. Bacteriophage (phage)-based viral vectors have the potential to be utilized for general gene transfer applications within research and industry. Yet, they require adaptations in order to enable them to efficiently enter cells and overcome mammalian cellular barriers, as they infect bacteria only; furthermore, limited progress has been made at increasing their efficiency. The production of a novel hybrid nanocomplex system consisting of two different nanomaterial systems, phage vectors and conventional transfection reagents, could overcome these limitations. Here we demonstrate that the combination of cationic lipids, cationic polymers or calcium phosphate with M13 bacteriophage-derived vectors, engineered to carry a mammalian transgene cassette, resulted in increased cellular attachment, entry and improved transgene expression in human cells. Moreover, addition of a targeting ligand into the nanocomplex system, through genetic engineering of the phage capsid further increased gene expression and was effective in a stable cell line generation application. Overall, this new hybrid nanocomplex system (i) provides enhanced phage-mediated gene transfer; (ii) is applicable for laboratory transfection processes and (iii) shows promise within industry for large-scale gene transfer applications.

Rapid Communication: MiR-92a as a housekeeping gene for analysis of bovine mastitis-related microRNA in milk.

PubMed

Lai, Y C; Fujikawa, T; Ando, T; Kitahara, G; Koiwa, M; Kubota, C; Miura, N

2017-06-01

Our aim was to identify a suitable microRNA housekeeping gene for real-time PCR analysis of bovine mastitis-related microRNA in milk. We identified , , and as housekeeping gene candidates on the basis of previous Solexa sequencing results. Threshold cycle (CT) values for , , and did not differ between milk from control cows and milk from mastitis-affected cows. NormFinder software identified as the most stable single housekeeping gene. We evaluated the suitability of the housekeeping gene candidates by using them to assess expression levels of the inflammation-related gene . Regardless of the housekeeping gene candidates used for normalization, relative expression levels of were significantly higher in mastitis-affected samples than in control samples. However, of all the housekeeping genes and gene combinations investigated, normalization with alone generated the difference in relative expression between mastitis-affected and control samples with the highest significance. These results suggest that is suitable for use as a housekeeping gene for analysis of bovine mastitis-related microRNA in milk.

Microbubble-assisted p53, RB, and p130 gene transfer in combination with radiation therapy in prostate cancer.

PubMed

Nande, Rounak; Greco, Adelaide; Gossman, Michael S; Lopez, Jeffrey P; Claudio, Luigi; Salvatore, Marco; Brunetti, Arturo; Denvir, James; Howard, Candace M; Claudio, Pier Paolo

2013-06-01

Combining radiation therapy and direct intratumoral (IT) injection of adenoviral vectors has been explored as a means to enhance the therapeutic potential of gene transfer. A major challenge for gene transfer is systemic delivery of nucleic acids directly into an affected tissue. Ultrasound (US) contrast agents (microbubbles) are viable candidates to enhance targeted delivery of systemically administered genes. Here we show that p53, pRB, and p130 gene transfer mediated by US cavitation of microbubbles at the tumor site resulted in targeted gene transduction and increased reduction in tumor growth compared to DU-145 prostate cancer cell xenografts treated intratumorally with adenovirus (Ad) or radiation alone. Microbubble-assisted/US-mediated Ad.p53 and Ad.RB treated tumors showed significant reduction in tumor volume compared to Ad.p130 treated tumors (p<0.05). Additionally, US mediated microbubble delivery of p53 and RB combined with external beam radiation resulted in the most profound tumor reduction in DU-145 xenografted nude mice (p<0.05) compared to radiation alone. These findings highlight the potential therapeutic applications of this novel image-guided gene transfer technology in combination with external beam radiation for prostate cancer patients with therapy resistant disease.

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

PubMed

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

2014-06-01

In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both

Dynamic association rules for gene expression data analysis.

PubMed

Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

2015-10-14

The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed

[Familial male-limited precocious puberty due to Asp578His mutations in the LHCGR gene: clinical characteristics and gene analysis in an infant].

PubMed

Wang, Min; Li, Min; Liu, Yue-Sheng; Lei, Si-Min; Xiao, Yan-Feng

2017-11-01

The aim of the study was to provide a descriptive analysis of familial male-limited precocious puberty (FMPP), which is a rare inherited disease caused by heterozygous constitutively activating mutations of the luteinizing hormone/choriogonadotropin receptor gene (LHCGR). The patient was a ten-month-old boy, presenting with penile enlargement, pubic hair formation, and spontaneous erections. Based on the clinical manifestations and laboratory data, including sexual characteristics, serum testosterone levels, GnRH stimulation test, and bone age, this boy was diagnosed with peripheral precocious puberty. Subsequently the precocious puberty-related genes were analyzed by direct DNA sequencing of amplified PCR products from the patient and his parents. Genetic analysis revealed a novel heterozygous missense mutation c.1732G>C (Asp578His) of the LHCGR gene exon11 in the patient, which had never been reported. His parents had no mutations. After combined treatment with aromatase inhibitor letrozole and anti-androgen spironolactone for six months, the patient's symptoms were controlled. The findings in this study expand the mutation spectrum of the LHCGR gene, and provide molecular evidence for the etiologic diagnosis as well as for the genetic counseling and prenatal diagnosis in the family.

Programmable control of bacterial gene expression with the combined CRISPR and antisense RNA system

PubMed Central

Lee, Young Je; Hoynes-O'Connor, Allison; Leong, Matthew C.; Moon, Tae Seok

2016-01-01

A central goal of synthetic biology is to implement diverse cellular functions by predictably controlling gene expression. Though research has focused more on protein regulators than RNA regulators, recent advances in our understanding of RNA folding and functions have motivated the use of RNA regulators. RNA regulators provide an advantage because they are easier to design and engineer than protein regulators, potentially have a lower burden on the cell and are highly orthogonal. Here, we combine the CRISPR system from Streptococcus pyogenes and synthetic antisense RNAs (asRNAs) in Escherichia coli strains to repress or derepress a target gene in a programmable manner. Specifically, we demonstrate for the first time that the gene target repressed by the CRISPR system can be derepressed by expressing an asRNA that sequesters a small guide RNA (sgRNA). Furthermore, we demonstrate that tunable levels of derepression can be achieved (up to 95%) by designing asRNAs that target different regions of a sgRNA and by altering the hybridization free energy of the sgRNA–asRNA complex. This new system, which we call the combined CRISPR and asRNA system, can be used to reversibly repress or derepress multiple target genes simultaneously, allowing for rational reprogramming of cellular functions. PMID:26837577

Biochemical and molecular characterization of thyroid tissue by micro-Raman spectroscopy and gene expression analysis

NASA Astrophysics Data System (ADS)

Neto, Lázaro P. M.; Martin, Aírton A.; Soto, Claudio A. T.; Santos, André B. O.; Mello, Evandro S.; Pereira, Marina A.; Cernea, Cláudio R.; Brandão, Lenine G.; Canevari, Renata A.

2016-02-01

Thyroid carcinomas represent the main endocrine malignancy and their diagnosis may produce inconclusive results. Raman spectroscopy and gene expression analysis have shown excellent results on the differentiation of carcinomas. This study aimed to improve the discrimination between different thyroid pathologies combining of both analyses. A total of 35 thyroid tissues samples including normal tissue (n=10), goiter (n=10), papillary (n=10) and follicular carcinomas (n=5) were analyzed. Confocal Raman spectra was obtain by using a Rivers Diagnostic System, 785 nm laser excitation and CCD detector. The data was processed by the software Labspec5 and Origin 8.5 and analyzed by Minitab® program. The gene expression analysis was performed by qRT-PCR technique for TG, TPO, PDGFB, SERPINA1, LGALS3 and TFF3 genes and statistically analyzed by Mann-Whitney test. The confocal Raman spectroscopy allowed a maximum discrimination of 91.1% between normal and tumor tissues, 84.8% between benign and malignant pathologies and 84.6% among carcinomas analyzed. Significant differences was observed for TG, LGALS3, SERPINA1 and TFF3 genes between benign lesions and carcinomas, and SERPINA1 and TFF3 genes between papillary and follicular carcinomas. Principal component analysis was performed using PC1 and PC2 in the papillary carcinoma samples that showed over gene expression when compared with normal sample, where 90% of discrimination was observed at the Amide 1 (1655 cm-1), and at the tyrosine spectra region (856 cm-1). The discrimination of tissues thyroid carried out by confocal Raman spectroscopy and gene expression analysis indicate that these techniques are promising tools to be used in the diagnosis of thyroid lesions.

Construction and analysis of gene-gene dynamics influence networks based on a Boolean model.

PubMed

Mazaya, Maulida; Trinh, Hung-Cuong; Kwon, Yung-Keun

2017-12-21

Identification of novel gene-gene relations is a crucial issue to understand system-level biological phenomena. To this end, many methods based on a correlation analysis of gene expressions or structural analysis of molecular interaction networks have been proposed. They have a limitation in identifying more complicated gene-gene dynamical relations, though. To overcome this limitation, we proposed a measure to quantify a gene-gene dynamical influence (GDI) using a Boolean network model and constructed a GDI network to indicate existence of a dynamical influence for every ordered pair of genes. It represents how much a state trajectory of a target gene is changed by a knockout mutation subject to a source gene in a gene-gene molecular interaction (GMI) network. Through a topological comparison between GDI and GMI networks, we observed that the former network is denser than the latter network, which implies that there exist many gene pairs of dynamically influencing but molecularly non-interacting relations. In addition, a larger number of hub genes were generated in the GDI network. On the other hand, there was a correlation between these networks such that the degree value of a node was positively correlated to each other. We further investigated the relationships of the GDI value with structural properties and found that there are negative and positive correlations with the length of a shortest path and the number of paths, respectively. In addition, a GDI network could predict a set of genes whose steady-state expression is affected in E. coli gene-knockout experiments. More interestingly, we found that the drug-targets with side-effects have a larger number of outgoing links than the other genes in the GDI network, which implies that they are more likely to influence the dynamics of other genes. Finally, we found biological evidences showing that the gene pairs which are not molecularly interacting but dynamically influential can be considered for novel gene-gene

Combined Bisulfite Restriction Analysis for brain tissue identification.

PubMed

Samsuwan, Jarunya; Muangsub, Tachapol; Yanatatsaneejit, Pattamawadee; Mutirangura, Apiwat; Kitkumthorn, Nakarin

2018-05-01

According to the tissue-specific methylation database (doi: 10.1016/j.gene.2014.09.060), methylation at CpG locus cg03096975 in EML2 has been preliminarily proven to be specific to brain tissue. In this study, we enlarged sample size and developed a technique for identifying brain tissue in aged samples. Combined Bisulfite Restriction Analysis-for EML2 (COBRA-EML2) technique was established and validated in various organ samples obtained from 108 autopsies. In addition, this technique was also tested for its reliability, minimal DNA concentration detected, and use in aged samples and in samples obtained from specific brain compartments and spinal cord. COBRA-EML2 displayed 100% sensitivity and specificity for distinguishing brain tissue from other tissues, showed high reliability, was capable of detecting minimal DNA concentration (0.015ng/μl), could be used for identifying brain tissue in aged samples. In summary, COBRA-EML2 is a technique to identify brain tissue. This analysis is useful in criminal cases since it can identify the vital organ tissues from small samples acquired from criminal scenes. The results from this analysis can be counted as a medical and forensic marker supporting criminal investigations, and as one of the evidences in court rulings. Copyright © 2018 Elsevier B.V. All rights reserved.

RNA-Seq analysis of yak ovary: improving yak gene structure information and mining reproduction-related genes.

PubMed

Lan, DaoLiang; Xiong, XianRong; Wei, YanLi; Xu, Tong; Zhong, JinCheng; Zhi, XiangDong; Wang, Yong; Li, Jian

2014-09-01

RNA-Seq, a high-throughput (HT) sequencing technique, has been used effectively in large-scale transcriptomic studies, and is particularly useful for improving gene structure information and mining of new genes. In this study, RNA-Seq HT technology was employed to analyze the transcriptome of yak ovary. After Illumina-Solexa deep sequencing, 26826516 clean reads with a total of 4828772880 bp were obtained from the ovary library. Alignment analysis showed that 16992 yak genes mapped to the yak genome and 3734 of these genes were involved in alternative splicing. Gene structure refinement analysis showed that 7340 genes that were annotated in the yak genome could be extended at the 5' or 3' ends based on the alignments been the transcripts and the genome sequence. Novel transcript prediction analysis identified 6321 new transcripts with lengths ranging from 180 to 14884 bp, and 2267 of them were predicted to code proteins. BLAST analysis of the new transcripts showed that 1200?4933 mapped to the non-redundant (nr), nucleotide (nt) and/or SwissProt sequence databases. Comparative statistical analysis of the new mapped transcripts showed that the majority of them were similar to genes in Bos taurus (41.4%), Bos grunniens mutus (33.0%), Ovis aries (6.3%), Homo sapiens (2.8%), Mus musculus (1.6%) and other species. Functional analysis showed that these expressed genes were involved in various Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes pathways. GO analysis of the new transcripts found that the largest proportion of them was associated with reproduction. The results of this study will provide a basis for describing the normal transcriptome map of yak ovary and for future studies on yak breeding performance. Moreover, the results confirmed that RNA-Seq HT technology is highly advantageous in improving gene structure information and mining of new genes, as well as in providing valuable data to expand the yak genome information.

Meta-type analysis of dopaminergic effects on gene expression in the neuroendocrine brain of female goldfish.

PubMed

Popesku, Jason T; Martyniuk, Christopher J; Trudeau, Vance L

2012-01-01

Dopamine (DA) is a major neurotransmitter important for neuroendocrine control and recent studies have described genomic signaling pathways activated and inhibited by DA agonists and antagonists in the goldfish brain. Here we perform a meta-type analysis using microarray datasets from experiments conducted with female goldfish to characterize the gene expression responses that underlie dopaminergic signaling. Sexually mature, pre-spawning [gonadosomatic index (GSI) = 4.5 ± 1.3%] or sexually regressing (GSI = 3 ± 0.4%) female goldfish (15-40 g) injected intraperitoneally with either SKF 38393, LY 171555, SCH 23390, sulpiride, or a combination of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine and α-methyl-p-tyrosine. Microarray meta-type analysis identified 268 genes in the telencephalon and hypothalamus as having reciprocal (i.e., opposite between agonism and antagonism/depletion) fold change responses, suggesting that these transcripts are likely targets for DA-mediated regulation. Noteworthy genes included ependymin, vimentin, and aromatase, genes that support the significance of DA in neuronal plasticity and tissue remodeling. Sub-network enrichment analysis (SNEA) was used to identify common gene regulators and binding proteins associated with the differentially expressed genes mediated by DA. SNEA analysis identified gene expression targets that were related to three major categories that included cell signaling (STAT3, SP1, SMAD, Jun/Fos), immune response (IL-6, IL-1β, TNFs, cytokine, NF-κB), and cell proliferation and growth (IGF1, TGFβ1). These gene networks are also known to be associated with neurodegenerative disorders such as Parkinsons' disease, well-known to be associated with loss of dopaminergic neurons. This study identifies genes and networks that underlie DA signaling in the vertebrate CNS and provides targets that may be key neuroendocrine regulators. The results provide a foundation for future work on dopaminergic

T-cell lymphomas associated gene expression signature: Bioinformatics analysis based on gene expression Omnibus.

PubMed

Zhou, Lei-Lei; Xu, Xiao-Yue; Ni, Jie; Zhao, Xia; Zhou, Jian-Wei; Feng, Ji-Feng

2018-06-01

Due to the low incidence and the heterogeneity of subtypes, the biological process of T-cell lymphomas is largely unknown. Although many genes have been detected in T-cell lymphomas, the role of these genes in biological process of T-cell lymphomas was not further analyzed. Two qualified datasets were downloaded from Gene Expression Omnibus database. The biological functions of differentially expressed genes were evaluated by gene ontology enrichment and KEGG pathway analysis. The network for intersection genes was constructed by the cytoscape v3.0 software. Kaplan-Meier survival curves and log-rank test were employed to assess the association between differentially expressed genes and clinical characters. The intersection mRNAs were proved to be associated with fundamental processes of T-cell lymphoma cells. These intersection mRNAs were involved in the activation of some cancer-related pathways, including PI3K/AKT, Ras, JAK-STAT, and NF-kappa B signaling pathway. PDGFRA, CXCL12, and CCL19 were the most significant central genes in the signal-net analysis. The results of survival analysis are not entirely credible. Our findings uncovered aberrantly expressed genes and a complex RNA signal network in T-cell lymphomas and indicated cancer-related pathways involved in disease initiation and progression, providing a new insight for biotargeted therapy in T-cell lymphomas. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Comparative genome analysis of PHB gene family reveals deep evolutionary origins and diverse gene function.

PubMed

Di, Chao; Xu, Wenying; Su, Zhen; Yuan, Joshua S

2010-10-07

PHB (Prohibitin) gene family is involved in a variety of functions important for different biological processes. PHB genes are ubiquitously present in divergent species from prokaryotes to eukaryotes. Human PHB genes have been found to be associated with various diseases. Recent studies by our group and others have shown diverse function of PHB genes in plants for development, senescence, defence, and others. Despite the importance of the PHB gene family, no comprehensive gene family analysis has been carried to evaluate the relatedness of PHB genes across different species. In order to better guide the gene function analysis and understand the evolution of the PHB gene family, we therefore carried out the comparative genome analysis of the PHB genes across different kingdoms. The relatedness, motif distribution, and intron/exon distribution all indicated that PHB genes is a relatively conserved gene family. The PHB genes can be classified into 5 classes and each class have a very deep evolutionary origin. The PHB genes within the class maintained the same motif patterns during the evolution. With Arabidopsis as the model species, we found that PHB gene intron/exon structure and domains are also conserved during the evolution. Despite being a conserved gene family, various gene duplication events led to the expansion of the PHB genes. Both segmental and tandem gene duplication were involved in Arabidopsis PHB gene family expansion. However, segmental duplication is predominant in Arabidopsis. Moreover, most of the duplicated genes experienced neofunctionalization. The results highlighted that PHB genes might be involved in important functions so that the duplicated genes are under the evolutionary pressure to derive new function. PHB gene family is a conserved gene family and accounts for diverse but important biological functions based on the similar molecular mechanisms. The highly diverse biological function indicated that more research needs to be carried out

Gene set analysis using variance component tests.

PubMed

Huang, Yen-Tsung; Lin, Xihong

2013-06-28

Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

PubMed

Hu, Yi-Juan; Berndt, Sonja I; Gustafsson, Stefan; Ganna, Andrea; Hirschhorn, Joel; North, Kari E; Ingelsson, Erik; Lin, Dan-Yu

2013-08-08

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Genome-wide methylation analysis identifies genes silenced in non-seminoma cell lines

PubMed Central

Noor, Dzul Azri Mohamed; Jeyapalan, Jennie N; Alhazmi, Safiah; Carr, Matthew; Squibb, Benjamin; Wallace, Claire; Tan, Christopher; Cusack, Martin; Hughes, Jaime; Reader, Tom; Shipley, Janet; Sheer, Denise; Scotting, Paul J

2016-01-01

Silencing of genes by DNA methylation is a common phenomenon in many types of cancer. However, the genome-wide effect of DNA methylation on gene expression has been analysed in relatively few cancers. Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. Previous analyses have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. The genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumours’ biology have not yet been established. In this study, genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data from primary tumours to address this question. Genome methylation was analysed using the Illumina infinium HumanMethylome450 bead chip system and gene expression was analysed using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Regulation by methylation was confirmed by demethylation using 5-aza-2-deoxycytidine and reverse transcription–quantitative PCR. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested played a role in their silencing in yolk sac tumour cells and many of these genes were also differentially expressed in primary tumours. Genes silenced by methylation in the various GCT cell lines were identified. Several pluripotency-associated genes were identified as a major functional group of silenced genes. PMID:29263807

Genome-wide methylation analysis identifies genes silenced in non-seminoma cell lines.

PubMed

Noor, Dzul Azri Mohamed; Jeyapalan, Jennie N; Alhazmi, Safiah; Carr, Matthew; Squibb, Benjamin; Wallace, Claire; Tan, Christopher; Cusack, Martin; Hughes, Jaime; Reader, Tom; Shipley, Janet; Sheer, Denise; Scotting, Paul J

2016-01-01

Silencing of genes by DNA methylation is a common phenomenon in many types of cancer. However, the genome-wide effect of DNA methylation on gene expression has been analysed in relatively few cancers. Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. Previous analyses have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. The genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumours' biology have not yet been established. In this study, genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data from primary tumours to address this question. Genome methylation was analysed using the Illumina infinium HumanMethylome450 bead chip system and gene expression was analysed using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Regulation by methylation was confirmed by demethylation using 5-aza-2-deoxycytidine and reverse transcription-quantitative PCR. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested played a role in their silencing in yolk sac tumour cells and many of these genes were also differentially expressed in primary tumours. Genes silenced by methylation in the various GCT cell lines were identified. Several pluripotency-associated genes were identified as a major functional group of silenced genes.

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.

Comprehensive detection of genes causing a phenotype using phenotype sequencing and pathway analysis.

PubMed

Harper, Marc; Gronenberg, Luisa; Liao, James; Lee, Christopher

2014-01-01

Discovering all the genetic causes of a phenotype is an important goal in functional genomics. We combine an experimental design for detecting independent genetic causes of a phenotype with a high-throughput sequencing analysis that maximizes sensitivity for comprehensively identifying them. Testing this approach on a set of 24 mutant strains generated for a metabolic phenotype with many known genetic causes, we show that this pathway-based phenotype sequencing analysis greatly improves sensitivity of detection compared with previous methods, and reveals a wide range of pathways that can cause this phenotype. We demonstrate our approach on a metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli, which is crucial to a substantial number of metabolic pathways and under renewed interest for biofuel research. Out of 2157 mutations in these strains, pathway-phenoseq discriminated just five gene groups (12 genes) as statistically significant causes of the phenotype. Experimentally, these five gene groups, and the next two high-scoring pathway-phenoseq groups, either have a clear connection to the PEP metabolite level or offer an alternative path of producing oxaloacetate (OAA), and thus clearly explain the phenotype. These high-scoring gene groups also show strong evidence of positive selection pressure, compared with strictly neutral selection in the rest of the genome.

Genome-wide identification and analysis of the MADS-box gene family in bread wheat (Triticum aestivum L.)

PubMed Central

Yang, Congcong; Ding, Puyang; Liu, Yaxi; Qiao, Linyi; Chang, Zhijian; Geng, Hongwei; Wang, Penghao; Jiang, Qiantao; Wang, Jirui; Chen, Guoyue; Wei, Yuming; Zheng, Youliang; Lan, Xiujin

2017-01-01

The MADS-box genes encode transcription factors with key roles in plant growth and development. A comprehensive analysis of the MADS-box gene family in bread wheat (Triticum aestivum) has not yet been conducted, and our understanding of their roles in stress is rather limited. Here, we report the identification and characterization of the MADS-box gene family in wheat. A total of 180 MADS-box genes classified as 32 Mα, 5 Mγ, 5 Mδ, and 138 MIKC types were identified. Evolutionary analysis of the orthologs among T. urartu, Aegilops tauschii and wheat as well as homeologous sequences analysis among the three sub-genomes in wheat revealed that gene loss and chromosomal rearrangements occurred during and/or after the origin of bread wheat. Forty wheat MADS-box genes that were expressed throughout the investigated tissues and development stages were identified. The genes that were regulated in response to both abiotic stresses (i.e., phosphorus deficiency, drought, heat, and combined drought and heat) and biotic stresses (i.e., Fusarium graminearum, Septoria tritici, stripe rust and powdery mildew) were detected as well. A few notable MADS-box genes were specifically expressed in a single tissue and those showed relatively higher expression differences between the stress and control treatment. The expression patterns of considerable MADS-box genes differed from those of their orthologs in Brachypodium, rice, and Arabidopsis. Collectively, the present study provides new insights into the possible roles of MADS-box genes in response to stresses and will be valuable for further functional studies of important candidate MADS-box genes. PMID:28742823

Genome-wide identification and analysis of the MADS-box gene family in bread wheat (Triticum aestivum L.).

PubMed

Ma, Jian; Yang, Yujie; Luo, Wei; Yang, Congcong; Ding, Puyang; Liu, Yaxi; Qiao, Linyi; Chang, Zhijian; Geng, Hongwei; Wang, Penghao; Jiang, Qiantao; Wang, Jirui; Chen, Guoyue; Wei, Yuming; Zheng, Youliang; Lan, Xiujin

2017-01-01

The MADS-box genes encode transcription factors with key roles in plant growth and development. A comprehensive analysis of the MADS-box gene family in bread wheat (Triticum aestivum) has not yet been conducted, and our understanding of their roles in stress is rather limited. Here, we report the identification and characterization of the MADS-box gene family in wheat. A total of 180 MADS-box genes classified as 32 Mα, 5 Mγ, 5 Mδ, and 138 MIKC types were identified. Evolutionary analysis of the orthologs among T. urartu, Aegilops tauschii and wheat as well as homeologous sequences analysis among the three sub-genomes in wheat revealed that gene loss and chromosomal rearrangements occurred during and/or after the origin of bread wheat. Forty wheat MADS-box genes that were expressed throughout the investigated tissues and development stages were identified. The genes that were regulated in response to both abiotic stresses (i.e., phosphorus deficiency, drought, heat, and combined drought and heat) and biotic stresses (i.e., Fusarium graminearum, Septoria tritici, stripe rust and powdery mildew) were detected as well. A few notable MADS-box genes were specifically expressed in a single tissue and those showed relatively higher expression differences between the stress and control treatment. The expression patterns of considerable MADS-box genes differed from those of their orthologs in Brachypodium, rice, and Arabidopsis. Collectively, the present study provides new insights into the possible roles of MADS-box genes in response to stresses and will be valuable for further functional studies of important candidate MADS-box genes.

Association analysis of nine candidate gene polymorphisms in Indian patients with type 2 diabetic retinopathy.

PubMed

Balasubbu, Suganthalakshmi; Sundaresan, Periasamy; Rajendran, Anand; Ramasamy, Kim; Govindarajan, Gowthaman; Perumalsamy, Namperumalsamy; Hejtmancik, J Fielding

2010-11-10

Diabetic retinopathy (DR) is classically defined as a microvasculopathy that primarily affects the small blood vessels of the inner retina as a complication of diabetes mellitus (DM).It is a multifactorial disease with a strong genetic component. The aim of this study is to investigate the association of a set of nine candidate genes with the development of diabetic retinopathy in a South Indian cohort who have type 2 diabetes mellitus (T2DM). Seven candidate genes (RAGE, PEDF, AKR1B1, EPO, HTRA1, ICAM and HFE) were chosen based on reported association with DR in the literature. Two more, CFH and ARMS2, were chosen based on their roles in biological pathways previously implicated in DR. Fourteen single nucleotide polymorphisms (SNPs) and one dinucleotide repeat polymorphism, previously reported to show association with DR or other related diseases, were genotyped in 345 DR and 356 diabetic patients without retinopathy (DNR). The genes which showed positive association in this screening set were tested further in additional sets of 100 DR and 90 DNR additional patients from the Aravind Eye Hospital. Those which showed association in the secondary screen were subjected to a combined analysis with the 100 DR and 100 DNR subjects previously recruited and genotyped through the Sankara Nethralaya Hospital, India. Genotypes were evaluated using a combination of direct sequencing, TaqMan SNP genotyping, RFLP analysis, and SNaPshot PCR assays. Chi-square and Fisher exact tests were used to analyze the genotype and allele frequencies. Among the nine loci (15 polymorphisms) screened, SNP rs2070600 (G82S) in the RAGE gene, showed significant association with DR (allelic P = 0.016, dominant model P = 0.012), compared to DNR. SNP rs2070600 further showed significant association with DR in the confirmation cohort (P = 0.035, dominant model P = 0.032). Combining the two cohorts gave an allelic P < 0.003 and dominant P = 0.0013). Combined analysis with the Sankara Nethralaya cohort

Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

PubMed

Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

2017-08-01

This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

A Novel Combination of Homeobox Genes Is Expressed in Mesenchymal Chorionic Stem/Stromal Cells in First Trimester and Term Pregnancies

PubMed Central

Liu, Haiying; Murthi, Padma; Qin, Sharon; Kusuma, Gina D.; Borg, Anthony J.; Knöfler, Martin; Haslinger, Peter; Manuelpillai, Ursula; Pertile, Mark D.; Abumaree, Mohamed

2014-01-01

Human chorionic mesenchymal stem/stromal cells (CMSCs) derived from the placenta are similar to adult tissue-derived MSCs. The aim of this study was to investigate the role of these cells in normal placental development. Transcription factors, particularly members of the homeobox gene family, play crucial roles in maintaining stem cell proliferation and lineage specification in embryonic tissues. In adult tissues and organs, stem cells proliferate at low levels in their niche until they receive cues from the microenvironment to differentiate. The homeobox genes that are expressed in the CMSC niche in placental tissues have not been identified. We used the novel strategy of laser capture microdissection to isolate the stromal component of first trimester villi and excluded the cytotrophoblast and syncytiotrophoblast layers that comprise the outer layer of the chorionic villi. Microarray analysis was then used to screen for homeobox genes in the microdissected tissue. Candidate homeobox genes were selected for further RNA analysis. Immunohistochemistry of candidate genes in first trimester placental villous stromal tissue revealed homeobox genes Meis1, myeloid ectropic viral integration site 1 homolog 2 (MEIS2), H2.0-like Drosophila (HLX), transforming growth factor β-induced factor (TGIF), and distal-less homeobox 5 (DLX5) were expressed in the vascular niche where CMSCs have been shown to reside. Expression of MEIS2, HLX, TGIF, and DLX5 was also detected in scattered stromal cells. Real-time polymerase chain reaction and immunocytochemistry verified expression of MEIS2, HLX, TGIF, and DLX5 homeobox genes in first trimester and term CMSCs. These data suggest a combination of regulatory homeobox genes is expressed in CMSCs from early placental development to term, which may be required for stem cell proliferation and differentiation. PMID:24692208

The link between the microbial ecology, gene expression, and biokinetics of denitrifying polyphosphate-accumulating systems under different electron acceptor combinations.

PubMed

Vieira, A; Ribera-Guardia, A; Marques, R; Barreto Crespo, M T; Oehmen, A; Carvalho, G

2018-06-02

The emission of the greenhouse gas nitrous oxide (N 2 O) can occur during biological nutrient removal. Denitrifying enhanced biological phosphorus removal (d-EBPR) systems are an efficient means of removing phosphate and nitrogen, performed by denitrifying polyphosphate-accumulating organisms (d-PAOs). The aim of this work was to study the effect of various combinations of electron acceptors, nitrate (NO 3 - ), nitrite (NO 2 - ), and N 2 O, on the denitrification pathway of a d-EBPR system. Batch tests were performed with different electron acceptor combinations, to explore the denitrification pathway. Reverse transcriptase-qPCR (RT-qPCR) and high-throughput sequencing, combined with chemical analysis, were used to study gene expression, microbial diversity, and denitrification kinetics. The potential for N 2 O production was greater than the potential for its reduction in most tests. A strong correlation was observed between the N 2 O reduction rate and the relative gene expression of nitrous oxide reductase per nitrite reductase (nosZ/(nirS + nirK)), suggesting that the expression of denitrifying marker genes is a strong predictor of the N 2 O reduction rate. The d-EBPR community maintained a core population with low variations throughout the study. Furthermore, phylogenetic analyses of the studied marker genes revealed that the organisms actively involved in denitrification were closely related to Thauera sp., Candidatus Accumulibacter phosphatis, and Candidatus Competibacter denitrificans. Moreover, Competibacter-related OTUs seem to be important contributors to the N 2 O reduction capacity of the system, likely scavenging the N 2 O produced by other organisms. Overall, this study contributes to a better understanding of the microbial biochemistry and the genetics involving biological denitrification removal, important to minimize N 2 O emissions in wastewater treatment plants.

Citrate Accumulation-Related Gene Expression and/or Enzyme Activity Analysis Combined With Metabolomics Provide a Novel Insight for an Orange Mutant

PubMed Central

Guo, Ling-Xia; Shi, Cai-Yun; Liu, Xiao; Ning, Dong-Yuan; Jing, Long-Fei; Yang, Huan; Liu, Yong-Zhong

2016-01-01

‘Hong Anliu’ (HAL, Citrus sinensis cv. Hong Anliu) is a bud mutant of ‘Anliu’ (AL), characterized by a comprehensive metabolite alteration, such as lower accumulation of citrate, high accumulation of lycopene and soluble sugars in fruit juice sacs. Due to carboxylic acid metabolism connects other metabolite biosynthesis and/or catabolism networks, we therefore focused analyzing citrate accumulation-related gene expression profiles and/or enzyme activities, along with metabolic fingerprinting between ‘HAL’ and ‘AL’. Compared with ‘AL’, the transcript levels of citrate biosynthesis- and utilization-related genes and/or the activities of their respective enzymes such as citrate synthase, cytosol aconitase and ATP-citrate lyase were significantly higher in ‘HAL’. Nevertheless, the mitochondrial aconitase activity, the gene transcript levels of proton pumps, including vacuolar H+-ATPase, vacuolar H+-PPase, and the juice sac-predominant p-type proton pump gene (CsPH8) were significantly lower in ‘HAL’. These results implied that ‘HAL’ has higher abilities for citrate biosynthesis and utilization, but lower ability for the citrate uptake into vacuole compared with ‘AL’. Combined with the metabolites-analyzing results, a model was then established and suggested that the reduction in proton pump activity is the key factor for the low citrate accumulation and the comprehensive metabolite alterations as well in ‘HAL’. PMID:27385485

ADAGE signature analysis: differential expression analysis with data-defined gene sets.

PubMed

Tan, Jie; Huyck, Matthew; Hu, Dongbo; Zelaya, René A; Hogan, Deborah A; Greene, Casey S

2017-11-22

Gene set enrichment analysis and overrepresentation analyses are commonly used methods to determine the biological processes affected by a differential expression experiment. This approach requires biologically relevant gene sets, which are currently curated manually, limiting their availability and accuracy in many organisms without extensively curated resources. New feature learning approaches can now be paired with existing data collections to directly extract functional gene sets from big data. Here we introduce a method to identify perturbed processes. In contrast with methods that use curated gene sets, this approach uses signatures extracted from public expression data. We first extract expression signatures from public data using ADAGE, a neural network-based feature extraction approach. We next identify signatures that are differentially active under a given treatment. Our results demonstrate that these signatures represent biological processes that are perturbed by the experiment. Because these signatures are directly learned from data without supervision, they can identify uncurated or novel biological processes. We implemented ADAGE signature analysis for the bacterial pathogen Pseudomonas aeruginosa. For the convenience of different user groups, we implemented both an R package (ADAGEpath) and a web server ( http://adage.greenelab.com ) to run these analyses. Both are open-source to allow easy expansion to other organisms or signature generation methods. We applied ADAGE signature analysis to an example dataset in which wild-type and ∆anr mutant cells were grown as biofilms on the Cystic Fibrosis genotype bronchial epithelial cells. We mapped active signatures in the dataset to KEGG pathways and compared with pathways identified using GSEA. The two approaches generally return consistent results; however, ADAGE signature analysis also identified a signature that revealed the molecularly supported link between the MexT regulon and Anr. We designed

SigEMD: A powerful method for differential gene expression analysis in single-cell RNA sequencing data.

PubMed

Wang, Tianyu; Nabavi, Sheida

2018-04-24

Differential gene expression analysis is one of the significant efforts in single cell RNA sequencing (scRNAseq) analysis to discover the specific changes in expression levels of individual cell types. Since scRNAseq exhibits multimodality, large amounts of zero counts, and sparsity, it is different from the traditional bulk RNA sequencing (RNAseq) data. The new challenges of scRNAseq data promote the development of new methods for identifying differentially expressed (DE) genes. In this study, we proposed a new method, SigEMD, that combines a data imputation approach, a logistic regression model and a nonparametric method based on the Earth Mover's Distance, to precisely and efficiently identify DE genes in scRNAseq data. The regression model and data imputation are used to reduce the impact of large amounts of zero counts, and the nonparametric method is used to improve the sensitivity of detecting DE genes from multimodal scRNAseq data. By additionally employing gene interaction network information to adjust the final states of DE genes, we further reduce the false positives of calling DE genes. We used simulated datasets and real datasets to evaluate the detection accuracy of the proposed method and to compare its performance with those of other differential expression analysis methods. Results indicate that the proposed method has an overall powerful performance in terms of precision in detection, sensitivity, and specificity. Copyright © 2018 Elsevier Inc. All rights reserved.

Transcriptome analysis of Brassica napus pod using RNA-Seq and identification of lipid-related candidate genes.

PubMed

Xu, Hai-Ming; Kong, Xiang-Dong; Chen, Fei; Huang, Ji-Xiang; Lou, Xiang-Yang; Zhao, Jian-Yi

2015-10-24

Brassica napus is an important oilseed crop. Dissection of the genetic architecture underlying oil-related biological processes will greatly facilitates the genetic improvement of rapeseed. The differential gene expression during pod development offers a snapshot on the genes responsible for oil accumulation in. To identify candidate genes in the linkage peaks reported previously, we used RNA sequencing (RNA-Seq) technology to analyze the pod transcriptomes of German cultivar Sollux and Chinese inbred line Gaoyou. The RNA samples were collected for RNA-Seq at 5-7, 15-17 and 25-27 days after flowering (DAF). Bioinformatics analysis was performed to investigate differentially expressed genes (DEGs). Gene annotation analysis was integrated with QTL mapping and Brassica napus pod transcriptome profiling to detect potential candidate genes in oilseed. Four hundred sixty five and two thousand, one hundred fourteen candidate DEGs were identified, respectively, between two varieties at the same stages and across different periods of each variety. Then, 33 DEGs between Sollux and Gaoyou were identified as the candidate genes affecting seed oil content by combining those DEGs with the quantitative trait locus (QTL) mapping results, of which, one was found to be homologous to Arabidopsis thaliana lipid-related genes. Intervarietal DEGs of lipid pathways in QTL regions represent important candidate genes for oil-related traits. Integrated analysis of transcriptome profiling, QTL mapping and comparative genomics with other relative species leads to efficient identification of most plausible functional genes underlying oil-content related characters, offering valuable resources for bettering breeding program of Brassica napus. This study provided a comprehensive overview on the pod transcriptomes of two varieties with different oil-contents at the three developmental stages.

Identification of candidate genes involved in neuroblastoma progression by combining genomic and expression microarrays with survival data.

PubMed

Łastowska, M; Viprey, V; Santibanez-Koref, M; Wappler, I; Peters, H; Cullinane, C; Roberts, P; Hall, A G; Tweddle, D A; Pearson, A D J; Lewis, I; Burchill, S A; Jackson, M S

2007-11-22

Identifying genes, whose expression is consistently altered by chromosomal gains or losses, is an important step in defining genes of biological relevance in a wide variety of tumour types. However, additional criteria are needed to discriminate further among the large number of candidate genes identified. This is particularly true for neuroblastoma, where multiple genomic copy number changes of proven prognostic value exist. We have used Affymetrix microarrays and a combination of fluorescent in situ hybridization and single nucleotide polymorphism (SNP) microarrays to establish expression profiles and delineate copy number alterations in 30 primary neuroblastomas. Correlation of microarray data with patient survival and analysis of expression within rodent neuroblastoma cell lines were then used to define further genes likely to be involved in the disease process. Using this approach, we identify >1000 genes within eight recurrent genomic alterations (loss of 1p, 3p, 4p, 10q and 11q, 2p gain, 17q gain, and the MYCN amplicon) whose expression is consistently altered by copy number change. Of these, 84 correlate with patient survival, with the minimal regions of 17q gain and 4p loss being enriched significantly for such genes. These include genes involved in RNA and DNA metabolism, and apoptosis. Orthologues of all but one of these genes on 17q are overexpressed in rodent neuroblastoma cell lines. A significant excess of SNPs whose copy number correlates with survival is also observed on proximal 4p in stage 4 tumours, and we find that deletion of 4p is associated with improved outcome in an extended cohort of tumours. These results define the major impact of genomic copy number alterations upon transcription within neuroblastoma, and highlight genes on distal 17q and proximal 4p for downstream analyses. They also suggest that integration of discriminators, such as survival and comparative gene expression, with microarray data may be useful in the identification of

Identification of functional enolase genes of the silkworm Bombyx mori from public databases with a combination of dry and wet bench processes.

PubMed

Kikuchi, Akira; Nakazato, Takeru; Ito, Katsuhiko; Nojima, Yosui; Yokoyama, Takeshi; Iwabuchi, Kikuo; Bono, Hidemasa; Toyoda, Atsushi; Fujiyama, Asao; Sato, Ryoichi; Tabunoki, Hiroko

2017-01-13

Various insect species have been added to genomic databases over the years. Thus, researchers can easily obtain online genomic information on invertebrates and insects. However, many incorrectly annotated genes are included in these databases, which can prevent the correct interpretation of subsequent functional analyses. To address this problem, we used a combination of dry and wet bench processes to select functional genes from public databases. Enolase is an important glycolytic enzyme in all organisms. We used a combination of dry and wet bench processes to identify functional enolases in the silkworm Bombyx mori (BmEno). First, we detected five annotated enolases from public databases using a Hidden Markov Model (HMM) search, and then through cDNA cloning, Northern blotting, and RNA-seq analysis, we revealed three functional enolases in B. mori: BmEno1, BmEno2, and BmEnoC. BmEno1 contained a conserved key amino acid residue for metal binding and substrate binding in other species. However, BmEno2 and BmEnoC showed a change in this key amino acid. Phylogenetic analysis showed that BmEno2 and BmEnoC were distinct from BmEno1 and other enolases, and were distributed only in lepidopteran clusters. BmEno1 was expressed in all of the tissues used in our study. In contrast, BmEno2 was mainly expressed in the testis with some expression in the ovary and suboesophageal ganglion. BmEnoC was weakly expressed in the testis. Quantitative RT-PCR showed that the mRNA expression of BmEno2 and BmEnoC correlated with testis development; thus, BmEno2 and BmEnoC may be related to lepidopteran-specific spermiogenesis. We identified and characterized three functional enolases from public databases with a combination of dry and wet bench processes in the silkworm B. mori. In addition, we determined that BmEno2 and BmEnoC had species-specific functions. Our strategy could be helpful for the detection of minor genes and functional genes in non-model organisms from public databases.

GeneSigDB: a manually curated database and resource for analysis of gene expression signatures

PubMed Central

Culhane, Aedín C.; Schröder, Markus S.; Sultana, Razvan; Picard, Shaita C.; Martinelli, Enzo N.; Kelly, Caroline; Haibe-Kains, Benjamin; Kapushesky, Misha; St Pierre, Anne-Alyssa; Flahive, William; Picard, Kermshlise C.; Gusenleitner, Daniel; Papenhausen, Gerald; O'Connor, Niall; Correll, Mick; Quackenbush, John

2012-01-01

GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a ‘basket’ feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org. PMID:22110038

MINER: exploratory analysis of gene interaction networks by machine learning from expression data.

PubMed

Kadupitige, Sidath Randeni; Leung, Kin Chun; Sellmeier, Julia; Sivieng, Jane; Catchpoole, Daniel R; Bain, Michael E; Gaëta, Bruno A

2009-12-03

The reconstruction of gene regulatory networks from high-throughput "omics" data has become a major goal in the modelling of living systems. Numerous approaches have been proposed, most of which attempt only "one-shot" reconstruction of the whole network with no intervention from the user, or offer only simple correlation analysis to infer gene dependencies. We have developed MINER (Microarray Interactive Network Exploration and Representation), an application that combines multivariate non-linear tree learning of individual gene regulatory dependencies, visualisation of these dependencies as both trees and networks, and representation of known biological relationships based on common Gene Ontology annotations. MINER allows biologists to explore the dependencies influencing the expression of individual genes in a gene expression data set in the form of decision, model or regression trees, using their domain knowledge to guide the exploration and formulate hypotheses. Multiple trees can then be summarised in the form of a gene network diagram. MINER is being adopted by several of our collaborators and has already led to the discovery of a new significant regulatory relationship with subsequent experimental validation. Unlike most gene regulatory network inference methods, MINER allows the user to start from genes of interest and build the network gene-by-gene, incorporating domain expertise in the process. This approach has been used successfully with RNA microarray data but is applicable to other quantitative data produced by high-throughput technologies such as proteomics and "next generation" DNA sequencing.

Lentiviral gene ontology (LeGO) vectors equipped with novel drug-selectable fluorescent proteins: new building blocks for cell marking and multi-gene analysis.

PubMed

Weber, K; Mock, U; Petrowitz, B; Bartsch, U; Fehse, B

2010-04-01

Vector-encoded fluorescent proteins (FPs) facilitate unambiguous identification or sorting of gene-modified cells by fluorescence-activated cell sorting (FACS). Exploiting this feature, we have recently developed lentiviral gene ontology (LeGO) vectors (www.LentiGO-Vectors.de) for multi-gene analysis in different target cells. In this study, we extend the LeGO principle by introducing 10 different drug-selectable FPs created by fusing one of the five selection marker (protecting against blasticidin, hygromycin, neomycin, puromycin and zeocin) and one of the five FP genes (Cerulean, eGFP, Venus, dTomato and mCherry). All tested fusion proteins allowed both fluorescence-mediated detection and drug-mediated selection of LeGO-transduced cells. Newly generated codon-optimized hygromycin- and neomycin-resistance genes showed improved expression as compared with their ancestors. New LeGO constructs were produced at titers >10(6) per ml (for non-concentrated supernatants). We show efficient combinatorial marking and selection of various cells, including mesenchymal stem cells, simultaneously transduced with different LeGO constructs. Inclusion of the cytomegalovirus early enhancer/chicken beta-actin promoter into LeGO vectors facilitated robust transgene expression in and selection of neural stem cells and their differentiated progeny. We suppose that the new drug-selectable markers combining advantages of FACS and drug selection are well suited for numerous applications and vector systems. Their inclusion into LeGO vectors opens new possibilities for (stem) cell tracking and functional multi-gene analysis.

Thermal tolerance in the keystone species Daphnia magna-a candidate gene and an outlier analysis approach.

PubMed

Jansen, M; Geerts, A N; Rago, A; Spanier, K I; Denis, C; De Meester, L; Orsini, L

2017-04-01

Changes in temperature have occurred throughout Earth's history. However, current warming trends exacerbated by human activities impose severe and rapid loss of biodiversity. Although understanding the mechanisms orchestrating organismal response to climate change is important, remarkably few studies document their role in nature. This is because only few systems enable the combined analysis of genetic and plastic responses to environmental change over long time spans. Here, we characterize genetic and plastic responses to temperature increase in the aquatic keystone grazer Daphnia magna combining a candidate gene and an outlier analysis approach. We capitalize on the short generation time of our species, facilitating experimental evolution, and the production of dormant eggs enabling the analysis of long-term response to environmental change through a resurrection ecology approach. We quantify plasticity in the expression of 35 candidate genes in D. magna populations resurrected from a lake that experienced changes in average temperature over the past century and from experimental populations differing in thermal tolerance isolated from a selection experiment. By measuring expression in multiple genotypes from each of these populations in control and heat treatments, we assess plastic responses to extreme temperature events. By measuring evolutionary changes in gene expression between warm- and cold-adapted populations, we assess evolutionary response to temperature changes. Evolutionary response to temperature increase is also assessed via an outlier analysis using EST-linked microsatellite loci. This study provides the first insights into the role of plasticity and genetic adaptation in orchestrating adaptive responses to environmental change in D. magna. © 2017 John Wiley & Sons Ltd.

Programmable control of bacterial gene expression with the combined CRISPR and antisense RNA system.

PubMed

Lee, Young Je; Hoynes-O'Connor, Allison; Leong, Matthew C; Moon, Tae Seok

2016-03-18

A central goal of synthetic biology is to implement diverse cellular functions by predictably controlling gene expression. Though research has focused more on protein regulators than RNA regulators, recent advances in our understanding of RNA folding and functions have motivated the use of RNA regulators. RNA regulators provide an advantage because they are easier to design and engineer than protein regulators, potentially have a lower burden on the cell and are highly orthogonal. Here, we combine the CRISPR system from Streptococcus pyogenes and synthetic antisense RNAs (asRNAs) in Escherichia coli strains to repress or derepress a target gene in a programmable manner. Specifically, we demonstrate for the first time that the gene target repressed by the CRISPR system can be derepressed by expressing an asRNA that sequesters a small guide RNA (sgRNA). Furthermore, we demonstrate that tunable levels of derepression can be achieved (up to 95%) by designing asRNAs that target different regions of a sgRNA and by altering the hybridization free energy of the sgRNA-asRNA complex. This new system, which we call the combined CRISPR and asRNA system, can be used to reversibly repress or derepress multiple target genes simultaneously, allowing for rational reprogramming of cellular functions. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Gene expression meta-analysis identifies chromosomal regions and candidate genes involved in breast cancer metastasis.

PubMed

Thomassen, Mads; Tan, Qihua; Kruse, Torben A

2009-01-01

Breast cancer cells exhibit complex karyotypic alterations causing deregulation of numerous genes. Some of these genes are probably causal for cancer formation and local growth whereas others are causal for the various steps of metastasis. In a fraction of tumors deregulation of the same genes might be caused by epigenetic modulations, point mutations or the influence of other genes. We have investigated the relation of gene expression and chromosomal position, using eight datasets including more than 1200 breast tumors, to identify chromosomal regions and candidate genes possibly causal for breast cancer metastasis. By use of "Gene Set Enrichment Analysis" we have ranked chromosomal regions according to their relation to metastasis. Overrepresentation analysis identified regions with increased expression for chromosome 1q41-42, 8q24, 12q14, 16q22, 16q24, 17q12-21.2, 17q21-23, 17q25, 20q11, and 20q13 among metastasizing tumors and reduced gene expression at 1p31-21, 8p22-21, and 14q24. By analysis of genes with extremely imbalanced expression in these regions we identified DIRAS3 at 1p31, PSD3, LPL, EPHX2 at 8p21-22, and FOS at 14q24 as candidate metastasis suppressor genes. Potential metastasis promoting genes includes RECQL4 at 8q24, PRMT7 at 16q22, GINS2 at 16q24, and AURKA at 20q13.

Genes for seed longevity in barley identified by genomic analysis on Near Isogenic Lines.

PubMed

Wozny, Dorothee; Kramer, Katharina; Finkemeier, Iris; Acosta, Ivan F; Koornneef, Maarten

2018-05-09

Genes controlling differences in seed longevity between two barley (Hordeum vulgare) accessions were identified by combining quantitative genetics 'omics' technologies in Near Isogenic Lines (NILs). The NILs were derived from crosses between the spring barley landraces L94 from Ethiopia and Cebada Capa from Argentina. A combined transcriptome and proteome analysis on mature, non-aged seeds of the two parental lines and the L94 NILs by RNA-sequencing and total seed proteomic profiling identified the UDP-glycosyltransferase MLOC_11661.1 as candidate gene for the QTL on 2H, and the NADP-dependent malic enzyme (NADP-ME) MLOC_35785.1 as possible downstream target gene. To validate these candidates, they were expressed in Arabidopsis under the control of constitutive promoters to attempt complementing the T-DNA knock-out line nadp-me1. Both the NADP-ME MLOC_35785.1 and the UDP-glycosyltransferase MLOC_11661.1 were able to rescue the nadp-me1 seed longevity phenotype. In the case of the UDP-glycosyltransferase, with high accumulation in NILs, only the coding sequence of Cebada Capa had a rescue effect. This article is protected by copyright. All rights reserved.

Mapping autosomal recessive intellectual disability: combined microarray and exome sequencing identifies 26 novel candidate genes in 192 consanguineous families.

PubMed

Harripaul, R; Vasli, N; Mikhailov, A; Rafiq, M A; Mittal, K; Windpassinger, C; Sheikh, T I; Noor, A; Mahmood, H; Downey, S; Johnson, M; Vleuten, K; Bell, L; Ilyas, M; Khan, F S; Khan, V; Moradi, M; Ayaz, M; Naeem, F; Heidari, A; Ahmed, I; Ghadami, S; Agha, Z; Zeinali, S; Qamar, R; Mozhdehipanah, H; John, P; Mir, A; Ansar, M; French, L; Ayub, M; Vincent, J B

2018-04-01

Approximately 1% of the global population is affected by intellectual disability (ID), and the majority receive no molecular diagnosis. Previous studies have indicated high levels of genetic heterogeneity, with estimates of more than 2500 autosomal ID genes, the majority of which are autosomal recessive (AR). Here, we combined microarray genotyping, homozygosity-by-descent (HBD) mapping, copy number variation (CNV) analysis, and whole exome sequencing (WES) to identify disease genes/mutations in 192 multiplex Pakistani and Iranian consanguineous families with non-syndromic ID. We identified definite or candidate mutations (or CNVs) in 51% of families in 72 different genes, including 26 not previously reported for ARID. The new ARID genes include nine with loss-of-function mutations (ABI2, MAPK8, MPDZ, PIDD1, SLAIN1, TBC1D23, TRAPPC6B, UBA7 and USP44), and missense mutations include the first reports of variants in BDNF or TET1 associated with ID. The genes identified also showed overlap with de novo gene sets for other neuropsychiatric disorders. Transcriptional studies showed prominent expression in the prenatal brain. The high yield of AR mutations for ID indicated that this approach has excellent clinical potential and should inform clinical diagnostics, including clinical whole exome and genome sequencing, for populations in which consanguinity is common. As with other AR disorders, the relevance will also apply to outbred populations.

VIZARD: analysis of Affymetrix Arabidopsis GeneChip data

NASA Technical Reports Server (NTRS)

Moseyko, Nick; Feldman, Lewis J.

2002-01-01

SUMMARY: The Affymetrix GeneChip Arabidopsis genome array has proved to be a very powerful tool for the analysis of gene expression in Arabidopsis thaliana, the most commonly studied plant model organism. VIZARD is a Java program created at the University of California, Berkeley, to facilitate analysis of Arabidopsis GeneChip data. It includes several integrated tools for filtering, sorting, clustering and visualization of gene expression data as well as tools for the discovery of regulatory motifs in upstream sequences. VIZARD also includes annotation and upstream sequence databases for the majority of genes represented on the Affymetrix Arabidopsis GeneChip array. AVAILABILITY: VIZARD is available free of charge for educational, research, and not-for-profit purposes, and can be downloaded at http://www.anm.f2s.com/research/vizard/ CONTACT: moseyko@uclink4.berkeley.edu.

In silico analysis of miRNA-mediated gene regulation in OCA and OA genes.

PubMed

Kamaraj, Balu; Gopalakrishnan, Chandrasekhar; Purohit, Rituraj

2014-12-01

Albinism is an autosomal recessive genetic disorder due to low secretion of melanin. The oculocutaneous albinism (OCA) and ocular albinism (OA) genes are responsible for melanin production and also act as a potential targets for miRNAs. The role of miRNA is to inhibit the protein synthesis partially or completely by binding with the 3'UTR of the mRNA thus regulating gene expression. In this analysis, we predicted the genetic variation that occurred in 3'UTR of the transcript which can be a reason for low melanin production thus causing albinism. The single nucleotide polymorphisms (SNPs) in 3'UTR cause more new binding sites for miRNA which binds with mRNA which leads to inhibit the translation process either partially or completely. The SNPs in the mRNA of OCA and OA genes can create new binding sites for miRNA which may control the gene expression and lead to hypopigmentation. We have developed a computational procedure to determine the SNPs in the 3'UTR region of mRNA of OCA (TYR, OCA2, TYRP1 and SLC45A2) and OA (GPR143) genes which will be a potential cause for albinism. We identified 37 SNPs in five genes that are predicted to create 87 new binding sites on mRNA, which may lead to abrogation of the translation process. Expression analysis confirms that these genes are highly expressed in skin and eye regions. It is well supported by enrichment analysis that these genes are mainly involved in eye pigmentation and melanin biosynthesis process. The network analysis also shows how the genes are interacting and expressing in a complex network. This insight provides clue to wet-lab researches to understand the expression pattern of OCA and OA genes and binding phenomenon of mRNA and miRNA upon mutation, which is responsible for inhibition of translation process at genomic levels.

Molecular characterization and expression analysis of Triticum aestivum squamosa-promoter binding protein-box genes involved in ear development.

PubMed

Zhang, Bin; Liu, Xia; Zhao, Guangyao; Mao, Xinguo; Li, Ang; Jing, Ruilian

2014-06-01

Wheat (Triticum aestivum L.) is one of the most important crops in the world. Squamosa-promoter binding protein (SBP)-box genes play a critical role in regulating flower and fruit development. In this study, 10 novel SBP-box genes (TaSPL genes) were isolated from wheat ((Triticum aestivum L.) cultivar Yanzhan 4110). Phylogenetic analysis classified the TaSPL genes into five groups (G1-G5). The motif combinations and expression patterns of the TaSPL genes varied among the five groups with each having own distinctive characteristics: TaSPL20/21 in G1 and TaSPL17 in G2 mainly expressed in the shoot apical meristem and the young ear, and their expression levels responded to development of the ear; TaSPL6/15 belonging to G3 were upregulated and TaSPL1/23 in G4 were downregulated during grain development; the gene in G5 (TaSPL3) expressed constitutively. Thus, the consistency of the phylogenetic analysis, motif compositions, and expression patterns of the TaSPL genes revealed specific gene structures and functions. On the other hand, the diverse gene structures and different expression patterns suggested that wheat SBP-box genes have a wide range of functions. The results also suggest a potential role for wheat SBP-box genes in ear development. This study provides a significant beginning of functional analysis of SBP-box genes in wheat. © 2014 The Authors. Journal of Integrative Plant Biology Published by Wiley Publishing Asia Pty Ltd on behalf of Institute of Botany, Chinese Academy of Sciences.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis

Combining lipophilic dye, in situ hybridization, immunohistochemistry, and histology.

PubMed

Duncan, Jeremy; Kersigo, Jennifer; Gray, Brian; Fritzsch, Bernd

2011-03-17

Going beyond single gene function to cut deeper into gene regulatory networks requires multiple mutations combined in a single animal. Such analysis of two or more genes needs to be complemented with in situ hybridization of other genes, or immunohistochemistry of their proteins, both in whole mounted developing organs or sections for detailed resolution of the cellular and tissue expression alterations. Combining multiple gene alterations requires the use of cre or flipase to conditionally delete genes and avoid embryonic lethality. Required breeding schemes dramatically enhance effort and cost proportional to the number of genes mutated, with an outcome of very few animals with the full repertoire of genetic modifications desired. Amortizing the vast amount of effort and time to obtain these few precious specimens that are carrying multiple mutations necessitates tissue optimization. Moreover, investigating a single animal with multiple techniques makes it easier to correlate gene deletion defects with expression profiles. We have developed a technique to obtain a more thorough analysis of a given animal; with the ability to analyze several different histologically recognizable structures as well as gene and protein expression all from the same specimen in both whole mounted organs and sections. Although mice have been utilized to demonstrate the effectiveness of this technique it can be applied to a wide array of animals. To do this we combine lipophilic dye tracing, whole mount in situ hybridization, immunohistochemistry, and histology to extract the maximal possible amount of data.

Combining Lipophilic dye, in situ Hybridization, Immunohistochemistry, and Histology

PubMed Central

Duncan, Jeremy; Kersigo, Jennifer; Gray, Brian; Fritzsch, Bernd

2011-01-01

Going beyond single gene function to cut deeper into gene regulatory networks requires multiple mutations combined in a single animal. Such analysis of two or more genes needs to be complemented with in situ hybridization of other genes, or immunohistochemistry of their proteins, both in whole mounted developing organs or sections for detailed resolution of the cellular and tissue expression alterations. Combining multiple gene alterations requires the use of cre or flipase to conditionally delete genes and avoid embryonic lethality. Required breeding schemes dramatically enhance effort and cost proportional to the number of genes mutated, with an outcome of very few animals with the full repertoire of genetic modifications desired. Amortizing the vast amount of effort and time to obtain these few precious specimens that are carrying multiple mutations necessitates tissue optimization. Moreover, investigating a single animal with multiple techniques makes it easier to correlate gene deletion defects with expression profiles. We have developed a technique to obtain a more thorough analysis of a given animal; with the ability to analyze several different histologically recognizable structures as well as gene and protein expression all from the same specimen in both whole mounted organs and sections. Although mice have been utilized to demonstrate the effectiveness of this technique it can be applied to a wide array of animals. To do this we combine lipophilic dye tracing, whole mount in situ hybridization, immunohistochemistry, and histology to extract the maximal possible amount of data. PMID:21445047

Genome-wide analysis of the WRKY gene family in cotton.

PubMed

Dou, Lingling; Zhang, Xiaohong; Pang, Chaoyou; Song, Meizhen; Wei, Hengling; Fan, Shuli; Yu, Shuxun

2014-12-01

WRKY proteins are major transcription factors involved in regulating plant growth and development. Although many studies have focused on the functional identification of WRKY genes, our knowledge concerning many areas of WRKY gene biology is limited. For example, in cotton, the phylogenetic characteristics, global expression patterns, molecular mechanisms regulating expression, and target genes/pathways of WRKY genes are poorly characterized. Therefore, in this study, we present a genome-wide analysis of the WRKY gene family in cotton (Gossypium raimondii and Gossypium hirsutum). We identified 116 WRKY genes in G. raimondii from the completed genome sequence, and we cloned 102 WRKY genes in G. hirsutum. Chromosomal location analysis indicated that WRKY genes in G. raimondii evolved mainly from segmental duplication followed by tandem amplifications. Phylogenetic analysis of alga, bryophyte, lycophyta, monocot and eudicot WRKY domains revealed family member expansion with increasing complexity of the plant body. Microarray, expression profiling and qRT-PCR data revealed that WRKY genes in G. hirsutum may regulate the development of fibers, anthers, tissues (roots, stems, leaves and embryos), and are involved in the response to stresses. Expression analysis showed that most group II and III GhWRKY genes are highly expressed under diverse stresses. Group I members, representing the ancestral form, seem to be insensitive to abiotic stress, with low expression divergence. Our results indicate that cotton WRKY genes might have evolved by adaptive duplication, leading to sensitivity to diverse stresses. This study provides fundamental information to inform further analysis and understanding of WRKY gene functions in cotton species.

Peptide micelle-mediated delivery of tissue-specific suicide gene and combined therapy with avastin in a glioblastoma model.

PubMed

Oh, Binna; Han, Jaesik; Choi, Eunji; Tan, Xiaonan; Lee, Minhyung

2015-04-01

Bevacizumab (Avastin) is an angiogenesis inhibitor used as a treatment for various cancers. In this study, the combination therapy of Avastin and glioblastoma-specific thymidine kinase gene [pEpo-NI2-SV-herpes simplex virus thymidine kinase(HSVtk)] was evaluated in a glioblastoma animal model. The R7L10 peptide was used as a gene carrier of pEpo-NI2-SV-HSVtk. Gel retardation assays confirmed that R7L10 formed stable complexes with pEpo-NI2-SV-HSVtk. R7L10 protected DNA from nuclease digestion. R7L10 had lower transfection efficiency than polyethylenimine (PEI; 25 kDa). However, the in vitro and in vivo toxicity assays showed that R7L10 had lower cytotoxicity than PEI, suggesting that R7L10 is safer than PEI. For the combination therapy, Avastin was injected intravenously and the pEpo-NI2-SV-HSVtk/R7L10 complexes were injected intratumorally in the glioblastoma animal model. Tumor growth was most effectively inhibited by the combination therapy of Avastin and the gene. The immunostaining results confirmed that the HSVtk genes were expressed in the groups with the pEpo-NI2-SV-HSVtk/R7L10 complex. The terminal deoxynucleotidyl transferase dUTP nick end labeling assay showed a higher level of apoptotic cells in the combination group than the pEpo-NI2-SV-HSVtk/R7L10 complex or Avastin group. In conclusion, the combination of Avastin and the glioblastoma-specific HSVtk gene has a higher antitumor effect than single therapy of Avastin or HSVtk after intratumoral administration in glioblastoma animal model. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Phylogenetic analysis at deep timescales: unreliable gene trees, bypassed hidden support, and the coalescence/concatalescence conundrum.

PubMed

Gatesy, John; Springer, Mark S

2014-11-01

Large datasets are required to solve difficult phylogenetic problems that are deep in the Tree of Life. Currently, two divergent systematic methods are commonly applied to such datasets: the traditional supermatrix approach (= concatenation) and "shortcut" coalescence (= coalescence methods wherein gene trees and the species tree are not co-estimated). When applied to ancient clades, these contrasting frameworks often produce congruent results, but in recent phylogenetic analyses of Placentalia (placental mammals), this is not the case. A recent series of papers has alternatively disputed and defended the utility of shortcut coalescence methods at deep phylogenetic scales. Here, we examine this exchange in the context of published phylogenomic data from Mammalia; in particular we explore two critical issues - the delimitation of data partitions ("genes") in coalescence analysis and hidden support that emerges with the combination of such partitions in phylogenetic studies. Hidden support - increased support for a clade in combined analysis of all data partitions relative to the support evident in separate analyses of the various data partitions, is a hallmark of the supermatrix approach and a primary rationale for concatenating all characters into a single matrix. In the most extreme cases of hidden support, relationships that are contradicted by all gene trees are supported when all of the genes are analyzed together. A valid fear is that shortcut coalescence methods might bypass or distort character support that is hidden in individual loci because small gene fragments are analyzed in isolation. Given the extensive systematic database for Mammalia, the assumptions and applicability of shortcut coalescence methods can be assessed with rigor to complement a small but growing body of simulation work that has directly compared these methods to concatenation. We document several remarkable cases of hidden support in both supermatrix and coalescence paradigms and argue

GenePattern | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

GenePattern is a genomic analysis platform that provides access to hundreds of tools for the analysis and visualization of multiple data types. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research. A new GenePattern Notebook environment allows users to combine GenePattern analyses with text, graphics, and code to create complete reproducible research narratives.

Microarray Meta-Analysis Focused on the Response of Genes Involved in Redox Homeostasis to Diverse Abiotic Stresses in Rice

PubMed Central

de Abreu Neto, Joao B.; Frei, Michael

2016-01-01

Plants are exposed to a wide range of abiotic stresses (AS), which often occur in combination. Because physiological investigations typically focus on one stress, our understanding of unspecific stress responses remains limited. The plant redox homeostasis, i.e., the production and removal of reactive oxygen species (ROS), may be involved in many environmental stress conditions. Therefore, this study intended to identify genes, which are activated in diverse AS, focusing on ROS-related pathways. We conducted a meta-analysis (MA) of microarray experiments, focusing on rice. Transcriptome data were mined from public databases and fellow researchers, which represented 36 different experiments and investigated diverse AS, including ozone stress, drought, heat, cold, salinity, and mineral deficiencies/toxicities. To overcome the inherent artifacts of different MA methods, data were processed using Fisher, rOP, REM, and product of rank (GeneSelector), and genes identified by most approaches were considered as shared differentially expressed genes (DEGs). Two MA strategies were adopted: first, datasets were separated into shoot, root, and seedling experiments, and these tissues were analyzed separately to identify shared DEGs. Second, shoot and seedling experiments were classed into oxidative stress (OS), i.e., ozone and hydrogen peroxide treatments directly producing ROS in plant tissue, and other AS, in which ROS production is indirect. In all tissues and stress conditions, genes a priori considered as ROS-related were overrepresented among the DEGs, as they represented 4% of all expressed genes but 7–10% of the DEGs. The combined MA approach was substantially more conservative than individual MA methods and identified 1001 shared DEGs in shoots, 837 shared DEGs in root, and 1172 shared DEGs in seedlings. Within the OS and AS groups, 990 and 1727 shared DEGs were identified, respectively. In total, 311 genes were shared between OS and AS, including many regulatory

Assessing the utility of gene co-expression stability in combination with correlation in the analysis of protein-protein interaction networks

PubMed Central

2011-01-01

Background Gene co-expression, in the form of a correlation coefficient, has been valuable in the analysis, classification and prediction of protein-protein interactions. However, it is susceptible to bias from a few samples having a large effect on the correlation coefficient. Gene co-expression stability is a means of quantifying this bias, with high stability indicating robust, unbiased co-expression correlation coefficients. We assess the utility of gene co-expression stability as an additional measure to support the co-expression correlation in the analysis of protein-protein interaction networks. Results We studied the patterns of co-expression correlation and stability in interacting proteins with respect to their interaction promiscuity, levels of intrinsic disorder, and essentiality or disease-relatedness. Co-expression stability, along with co-expression correlation, acts as a better classifier of hub proteins in interaction networks, than co-expression correlation alone, enabling the identification of a class of hubs that are functionally distinct from the widely accepted transient (date) and obligate (party) hubs. Proteins with high levels of intrinsic disorder have low co-expression correlation and high stability with their interaction partners suggesting their involvement in transient interactions, except for a small group that have high co-expression correlation and are typically subunits of stable complexes. Similar behavior was seen for disease-related and essential genes. Interacting proteins that are both disordered have higher co-expression stability than ordered protein pairs. Using co-expression correlation and stability, we found that transient interactions are more likely to occur between an ordered and a disordered protein while obligate interactions primarily occur between proteins that are either both ordered, or disordered. Conclusions We observe that co-expression stability shows distinct patterns in structurally and functionally

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

[From gene cloning to expressional analysis--practice and experience from educational reform of experimental gene engineering].

PubMed

Wu, Yan-Hua; Guo, Bin; Lou, Hui-Ling; Cui, Yu-Liang; Gu, Hui-Juan; Qiao, Shou-Yi

2012-02-01

Experimental gene engineering is a laboratory course focusing on the molecular structure, expression pattern and biological function of genes. Providing our students with a solid knowledge base and correct ways to conduct research is very important for high-quality education of genetic engineering. Inspired by recent progresses in this field, we improved the experimental gene engineering course by adding more updated knowledge and technologies and emphasizing on the combination of teaching and research, with the aim of offering our students a good start in their scientific careers.

Derivation of an artificial gene to improve classification accuracy upon gene selection.

PubMed

Seo, Minseok; Oh, Sejong

2012-02-01

Classification analysis has been developed continuously since 1936. This research field has advanced as a result of development of classifiers such as KNN, ANN, and SVM, as well as through data preprocessing areas. Feature (gene) selection is required for very high dimensional data such as microarray before classification work. The goal of feature selection is to choose a subset of informative features that reduces processing time and provides higher classification accuracy. In this study, we devised a method of artificial gene making (AGM) for microarray data to improve classification accuracy. Our artificial gene was derived from a whole microarray dataset, and combined with a result of gene selection for classification analysis. We experimentally confirmed a clear improvement of classification accuracy after inserting artificial gene. Our artificial gene worked well for popular feature (gene) selection algorithms and classifiers. The proposed approach can be applied to any type of high dimensional dataset. Copyright © 2011 Elsevier Ltd. All rights reserved.

Gene expression analysis of rheumatoid arthritis synovial lining regions by cDNA microarray combined with laser microdissection: up-regulation of inflammation-associated STAT1, IRF1, CXCL9, CXCL10, and CCL5

PubMed Central

Yoshida, S; Arakawa, F; Higuchi, F; Ishibashi, Y; Goto, M; Sugita, Y; Nomura, Y; Niino, D; Shimizu, K; Aoki, R; Hashikawa, K; Kimura, Y; Yasuda, K; Tashiro, K; Kuhara, S; Nagata, K; Ohshima, K

2012-01-01

Objectives The main histological change in rheumatoid arthritis (RA) is the villous proliferation of synovial lining cells, an important source of cytokines and chemokines, which are associated with inflammation. The aim of this study was to evaluate gene expression in the microdissected synovial lining cells of RA patients, using those of osteoarthritis (OA) patients as the control. Methods Samples were obtained during total joint replacement from 11 RA and five OA patients. Total RNA from the synovial lining cells was derived from selected specimens by laser microdissection (LMD) for subsequent cDNA microarray analysis. In addition, the expression of significant genes was confirmed immunohistochemically. Results The 14 519 genes detected by cDNA microarray were used to compare gene expression levels in synovial lining cells from RA with those from OA patients. Cluster analysis indicated that RA cells, including low- and high-expression subgroups, and OA cells were stored in two main clusters. The molecular activity of RA was statistically consistent with its clinical and histological activity. Expression levels of signal transducer and activator of transcription 1 (STAT1), interferon regulatory factor 1 (IRF1), and the chemokines CXCL9, CXCL10, and CCL5 were statistically significantly higher in the synovium of RA than in that of OA. Immunohistochemically, the lining synovium of RA, but not that of OA, clearly expressed STAT1, IRF1, and chemokines, as was seen in microarray analysis combined with LMD. Conclusions Our findings indicate an important role for lining synovial cells in the inflammatory and proliferative processes of RA. Further understanding of the local signalling in structural components is important in rheumatology. PMID:22401175

Combinations of mutant FAD2 and FAD3 genes to produce high oleic acid and low linolenic acid soybean oil.

PubMed

Pham, Anh-Tung; Shannon, J Grover; Bilyeu, Kristin D

2012-08-01

High oleic acid soybeans were produced by combining mutant FAD2-1A and FAD2-1B genes. Despite having a high oleic acid content, the linolenic acid content of these soybeans was in the range of 4-6 %, which may be high enough to cause oxidative instability of the oil. Therefore, a study was conducted to incorporate one or two mutant FAD3 genes into the high oleic acid background to further reduce the linolenic acid content. As a result, soybean lines with high oleic acid and low linolenic acid (HOLL) content were produced using different sources of mutant FAD2-1A genes. While oleic acid content of these HOLL lines was stable across two testing environments, the reduction of linolenic acid content varied depending on the number of mutant FAD3 genes combined with mutant FAD2-1 genes, on the severity of mutation in the FAD2-1A gene, and on the testing environment. Combination of two mutant FAD2-1 genes and one mutant FAD3 gene resulted in less than 2 % linolenic acid content in Portageville, Missouri (MO) while four mutant genes were needed to achieve the same linolenic acid in Columbia, MO. This study generated non-transgenic soybeans with the highest oleic acid content and lowest linolenic acid content reported to date, offering a unique alternative to produce a fatty acid profile similar to olive oil.

Gene Ontology-Based Analysis of Zebrafish Omics Data Using the Web Tool Comparative Gene Ontology.

PubMed

Ebrahimie, Esmaeil; Fruzangohar, Mario; Moussavi Nik, Seyyed Hani; Newman, Morgan

2017-10-01

Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in revealing functional mechanisms underlying observed patterns in transcriptomic, genomic, and proteomic data. The already extensive and increasing use of zebrafish for modeling genetic and other diseases highlights the need to develop a GO analytical tool for this organism. The web tool Comparative GO was originally developed for GO analysis of bacterial data in 2013 ( www.comparativego.com ). We have now upgraded and elaborated this web tool for analysis of zebrafish genetic data using GOs and annotations from the Gene Ontology Consortium.

Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

PubMed

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-03-09

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

Pathway-Based Factor Analysis of Gene Expression Data Produces Highly Heritable Phenotypes That Associate with Age

PubMed Central

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-01-01

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 “pathway phenotypes” that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold (P<5.38×10−5). These phenotypes are more heritable (h2=0.32) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. PMID:25758824

Meta-Type Analysis of Dopaminergic Effects on Gene Expression in the Neuroendocrine Brain of Female Goldfish

PubMed Central

Popesku, Jason T.; Martyniuk, Christopher J.; Trudeau, Vance L.

2012-01-01

Dopamine (DA) is a major neurotransmitter important for neuroendocrine control and recent studies have described genomic signaling pathways activated and inhibited by DA agonists and antagonists in the goldfish brain. Here we perform a meta-type analysis using microarray datasets from experiments conducted with female goldfish to characterize the gene expression responses that underlie dopaminergic signaling. Sexually mature, pre-spawning [gonadosomatic index (GSI) = 4.5 ± 1.3%] or sexually regressing (GSI = 3 ± 0.4%) female goldfish (15–40 g) injected intraperitoneally with either SKF 38393, LY 171555, SCH 23390, sulpiride, or a combination of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine and α-methyl-p-tyrosine. Microarray meta-type analysis identified 268 genes in the telencephalon and hypothalamus as having reciprocal (i.e., opposite between agonism and antagonism/depletion) fold change responses, suggesting that these transcripts are likely targets for DA-mediated regulation. Noteworthy genes included ependymin, vimentin, and aromatase, genes that support the significance of DA in neuronal plasticity and tissue remodeling. Sub-network enrichment analysis (SNEA) was used to identify common gene regulators and binding proteins associated with the differentially expressed genes mediated by DA. SNEA analysis identified gene expression targets that were related to three major categories that included cell signaling (STAT3, SP1, SMAD, Jun/Fos), immune response (IL-6, IL-1β, TNFs, cytokine, NF-κB), and cell proliferation and growth (IGF1, TGFβ1). These gene networks are also known to be associated with neurodegenerative disorders such as Parkinsons’ disease, well-known to be associated with loss of dopaminergic neurons. This study identifies genes and networks that underlie DA signaling in the vertebrate CNS and provides targets that may be key neuroendocrine regulators. The results provide a foundation for future work on dopaminergic

Identification of pathogenic genes related to rheumatoid arthritis through integrated analysis of DNA methylation and gene expression profiling.

PubMed

Zhang, Lei; Ma, Shiyun; Wang, Huailiang; Su, Hang; Su, Ke; Li, Longjie

2017-11-15

The purpose of our study was to identify new pathogenic genes used for exploring the pathogenesis of rheumatoid arthritis (RA). To screen pathogenic genes of RA, an integrated analysis was performed by using the microarray datasets in RA derived from the Gene Expression Omnibus (GEO) database. The functional annotation and potential pathways of differentially expressed genes (DEGs) were further discovered by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Afterwards, the integrated analysis of DNA methylation and gene expression profiling was used to screen crucial genes. In addition, we used RT-PCR and MSP to verify the expression levels and methylation status of these crucial genes in 20 synovial biopsy samples obtained from 10 RA model mice and 10 normal mice. BCL11B, CCDC88C, FCRLA and APOL6 were both up-regulated and hypomethylated in RA according to integrated analysis, RT-PCR and MSP verification. Four crucial genes (BCL11B, CCDC88C, FCRLA and APOL6) identified and analyzed in this study might be closely connected with the pathogenesis of RA. Copyright © 2017. Published by Elsevier B.V.

Genome-Wide Comparative Analysis of the Phospholipase D Gene Families among Allotetraploid Cotton and Its Diploid Progenitors

PubMed Central

Tang, Kai; Dong, Chun-Juan; Liu, Jin-Yuan

2016-01-01

In this study, 40 phospholipase D (PLD) genes were identified from allotetraploid cotton Gossypium hirsutum, and 20 PLD genes were examined in diploid cotton Gossypium raimondii. Combining with 19 previously identified Gossypium arboreum PLD genes, a comparative analysis was performed among the PLD gene families among allotetraploid and two diploid cottons. Based on the orthologous relationships, we found that almost each G. hirsutum PLD had a corresponding homolog in the G. arboreum and G. raimondii genomes, except for GhPLDβ3A, whose homolog GaPLDβ3 may have been lost during the evolution of G. arboreum after the interspecific hybridization. Phylogenetic analysis showed that all of the cotton PLDs were unevenly classified into six numbered subgroups: α, β/γ, δ, ε, ζ and φ. An N-terminal C2 domain was found in the α, β/γ, δ and ε subgroups, while phox homology (PX) and pleckstrin homology (PH) domains were identified in the ζ subgroup. The subgroup φ possessed a single peptide instead of a functional domain. In each phylogenetic subgroup, the PLDs showed high conservation in gene structure and amino acid sequences in functional domains. The expansion of GhPLD and GrPLD gene families were mainly attributed to segmental duplication and partly attributed to tandem duplication. Furthermore, purifying selection played a critical role in the evolution of PLD genes in cotton. Quantitative RT-PCR documented that allotetraploid cotton PLD genes were broadly expressed and each had a unique spatial and developmental expression pattern, indicating their functional diversification in cotton growth and development. Further analysis of cis-regulatory elements elucidated transcriptional regulations and potential functions. Our comparative analysis provided valuable information for understanding the putative functions of the PLD genes in cotton fiber. PMID:27213891

A combination test for detection of gene-environment interaction in cohort studies.

PubMed

Coombes, Brandon; Basu, Saonli; McGue, Matt

2017-07-01

Identifying gene-environment (G-E) interactions can contribute to a better understanding of disease etiology, which may help researchers develop disease prevention strategies and interventions. One big criticism of studying G-E interaction is the lack of power due to sample size. Studies often restrict the interaction search to the top few hundred hits from a genome-wide association study or focus on potential candidate genes. In this paper, we test interactions between a candidate gene and an environmental factor to improve power by analyzing multiple variants within a gene. We extend recently developed score statistic based genetic association testing approaches to the G-E interaction testing problem. We also propose tests for interaction using gene-based summary measures that pool variants together. Although it has recently been shown that these summary measures can be biased and may lead to inflated type I error, we show that under several realistic scenarios, we can still provide valid tests of interaction. These tests use significantly less degrees of freedom and thus can have much higher power to detect interaction. Additionally, we demonstrate that the iSeq-aSum-min test, which combines a gene-based summary measure test, iSeq-aSum-G, and an interaction-based summary measure test, iSeq-aSum-I, provides a powerful alternative to test G-E interaction. We demonstrate the performance of these approaches using simulation studies and illustrate their performance to study interaction between the SNPs in several candidate genes and family climate environment on alcohol consumption using the Minnesota Center for Twin and Family Research dataset. © 2017 WILEY PERIODICALS, INC.

Comprehensive Analysis of the Soybean (Glycine max) GmLAX Auxin Transporter Gene Family

PubMed Central

Chai, Chenglin; Wang, Yongqin; Valliyodan, Babu; Nguyen, Henry T.

2016-01-01

The phytohormone auxin plays a critical role in regulation of plant growth and development as well as plant responses to abiotic stresses. This is mainly achieved through its uneven distribution in plant via a polar auxin transport process. Auxin transporters are major players in polar auxin transport. The AUXIN RESISTENT 1/LIKE AUX1 (AUX/LAX) auxin influx carriers belong to the amino acid permease family of proton-driven transporters and function in the uptake of indole-3-acetic acid (IAA). In this study, genome-wide comprehensive analysis of the soybean AUX/LAX (GmLAX) gene family, including phylogenic relationships, chromosome localization, and gene structure, was carried out. A total of 15 GmLAX genes, including seven duplicated gene pairs, were identified in the soybean genome. They were distributed on 10 chromosomes. Despite their higher percentage identities at the protein level, GmLAXs exhibited versatile tissue-specific expression patterns, indicating coordinated functioning during plant growth and development. Most GmLAXs were responsive to drought and dehydration stresses and auxin and abscisic acid (ABA) stimuli, in a tissue- and/or time point- sensitive mode. Several GmLAX members were involved in responding to salt stress. Sequence analysis revealed that promoters of GmLAXs contained different combinations of stress-related cis-regulatory elements. These studies suggest that the soybean GmLAXs were under control of a very complex regulatory network, responding to various internal and external signals. This study helps to identity candidate GmLAXs for further analysis of their roles in soybean development and adaption to adverse environments. PMID:27014306

Analysis of MHC class I genes across horse MHC haplotypes

PubMed Central

Tallmadge, Rebecca L.; Campbell, Julie A.; Miller, Donald C.; Antczak, Douglas F.

2010-01-01

The genomic sequences of 15 horse Major Histocompatibility Complex (MHC) class I genes and a collection of MHC class I homozygous horses of five different haplotypes were used to investigate the genomic structure and polymorphism of the equine MHC. A combination of conserved and locus-specific primers was used to amplify horse MHC class I genes with classical and non-classical characteristics. Multiple clones from each haplotype identified three to five classical sequences per homozygous animal, and two to three non-classical sequences. Phylogenetic analysis was applied to these sequences and groups were identified which appear to be allelic series, but some sequences were left ungrouped. Sequences determined from MHC class I heterozygous horses and previously described MHC class I sequences were then added, representing a total of ten horse MHC haplotypes. These results were consistent with those obtained from the MHC homozygous horses alone, and 30 classical sequences were assigned to four previously confirmed loci and three new provisional loci. The non-classical genes had few alleles and the classical genes had higher levels of allelic polymorphism. Alleles for two classical loci with the expected pattern of polymorphism were found in the majority of haplotypes tested, but alleles at two other commonly detected loci had more variation outside of the hypervariable region than within. Our data indicate that the equine Major Histocompatibility Complex is characterized by variation in the complement of class I genes expressed in different haplotypes in addition to the expected allelic polymorphism within loci. PMID:20099063

Warehousing re-annotated cancer genes for biomarker meta-analysis.

PubMed

Orsini, M; Travaglione, A; Capobianco, E

2013-07-01

Translational research in cancer genomics assigns a fundamental role to bioinformatics in support of candidate gene prioritization with regard to both biomarker discovery and target identification for drug development. Efforts in both such directions rely on the existence and constant update of large repositories of gene expression data and omics records obtained from a variety of experiments. Users who interactively interrogate such repositories may have problems in retrieving sample fields that present limited associated information, due for instance to incomplete entries or sometimes unusable files. Cancer-specific data sources present similar problems. Given that source integration usually improves data quality, one of the objectives is keeping the computational complexity sufficiently low to allow an optimal assimilation and mining of all the information. In particular, the scope of integrating intraomics data can be to improve the exploration of gene co-expression landscapes, while the scope of integrating interomics sources can be that of establishing genotype-phenotype associations. Both integrations are relevant to cancer biomarker meta-analysis, as the proposed study demonstrates. Our approach is based on re-annotating cancer-specific data available at the EBI's ArrayExpress repository and building a data warehouse aimed to biomarker discovery and validation studies. Cancer genes are organized by tissue with biomedical and clinical evidences combined to increase reproducibility and consistency of results. For better comparative evaluation, multiple queries have been designed to efficiently address all types of experiments and platforms, and allow for retrieval of sample-related information, such as cell line, disease state and clinical aspects. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Multiscale Embedded Gene Co-expression Network Analysis

PubMed Central

Song, Won-Min; Zhang, Bin

2015-01-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma. PMID:26618778

Multiscale Embedded Gene Co-expression Network Analysis.

PubMed

Song, Won-Min; Zhang, Bin

2015-11-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

Genome-Wide Detection and Analysis of Multifunctional Genes

PubMed Central

Pritykin, Yuri; Ghersi, Dario; Singh, Mona

2015-01-01

Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, D. melanogaster, and S. cerevisiae—and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality. PMID:26436655

Phylogenic analysis of the M genes of influenza viruses isolated from free-flying water birds from their Northern Territory to Hokkaido, Japan.

PubMed

Manzoor, Rashid; Sakoda, Yoshihiro; Mweene, Aaron; Tsuda, Yoshimi; Kishida, Noriko; Bai, Gui-Rong; Kameyama, Ken-Ichiro; Isoda, Norikazu; Soda, Kosuke; Naito, Michiko; Kida, Hiroshi

2008-10-01

During 2000-2007, 218 influenza viruses of 28 different combinations of HA (H1-H13) and NA (N1-N9) subtypes were isolated from fecal samples of free-flying water birds at two distant lakes in Hokkaido, Japan. Phylogenic analysis of the matrix (M) genes of 67 strains, selected on the basis of their subtype combinations, revealed that A/duck/Hokkaido/W95/2006 (H10N8) was a reassortant whose M and NA genes [corrected] belonged to North American non-gull-avian and the other six [corrected] genes to Eurasian non-gull-avian lineages. The M genes of other 65 strains belonged to Eurasian non-gull-avian and the one to Eurasian-gull lineages. The M genes of 65 strains were grouped into three different sublineages, indicating that influenza viruses circulating in different populations of free-flying water birds have evolved independently in nature.

Gene therapy for adenosine deaminase-deficient severe combined immune deficiency: clinical comparison of retroviral vectors and treatment plans.

PubMed

Candotti, Fabio; Shaw, Kit L; Muul, Linda; Carbonaro, Denise; Sokolic, Robert; Choi, Christopher; Schurman, Shepherd H; Garabedian, Elizabeth; Kesserwan, Chimene; Jagadeesh, G Jayashree; Fu, Pei-Yu; Gschweng, Eric; Cooper, Aaron; Tisdale, John F; Weinberg, Kenneth I; Crooks, Gay M; Kapoor, Neena; Shah, Ami; Abdel-Azim, Hisham; Yu, Xiao-Jin; Smogorzewska, Monika; Wayne, Alan S; Rosenblatt, Howard M; Davis, Carla M; Hanson, Celine; Rishi, Radha G; Wang, Xiaoyan; Gjertson, David; Yang, Otto O; Balamurugan, Arumugam; Bauer, Gerhard; Ireland, Joanna A; Engel, Barbara C; Podsakoff, Gregory M; Hershfield, Michael S; Blaese, R Michael; Parkman, Robertson; Kohn, Donald B

2012-11-01

We conducted a gene therapy trial in 10 patients with adenosine deaminase (ADA)-deficient severe combined immunodeficiency using 2 slightly different retroviral vectors for the transduction of patients' bone marrow CD34(+) cells. Four subjects were treated without pretransplantation cytoreduction and remained on ADA enzyme-replacement therapy (ERT) throughout the procedure. Only transient (months), low-level (< 0.01%) gene marking was observed in PBMCs of 2 older subjects (15 and 20 years of age), whereas some gene marking of PBMC has persisted for the past 9 years in 2 younger subjects (4 and 6 years). Six additional subjects were treated using the same gene transfer protocol, but after withdrawal of ERT and administration of low-dose busulfan (65-90 mg/m(2)). Three of these remain well, off ERT (5, 4, and 3 years postprocedure), with gene marking in PBMC of 1%-10%, and ADA enzyme expression in PBMC near or in the normal range. Two subjects were restarted on ERT because of poor gene marking and immune recovery, and one had a subsequent allogeneic hematopoietic stem cell transplantation. These studies directly demonstrate the importance of providing nonmyeloablative pretransplantation conditioning to achieve therapeutic benefits with gene therapy for ADA-deficient severe combined immunodeficiency.

Gene therapy for adenosine deaminase–deficient severe combined immune deficiency: clinical comparison of retroviral vectors and treatment plans

PubMed Central

Candotti, Fabio; Shaw, Kit L.; Muul, Linda; Carbonaro, Denise; Sokolic, Robert; Choi, Christopher; Schurman, Shepherd H.; Garabedian, Elizabeth; Kesserwan, Chimene; Jagadeesh, G. Jayashree; Fu, Pei-Yu; Gschweng, Eric; Cooper, Aaron; Tisdale, John F.; Weinberg, Kenneth I.; Crooks, Gay M.; Kapoor, Neena; Shah, Ami; Abdel-Azim, Hisham; Yu, Xiao-Jin; Smogorzewska, Monika; Wayne, Alan S.; Rosenblatt, Howard M.; Davis, Carla M.; Hanson, Celine; Rishi, Radha G.; Wang, Xiaoyan; Gjertson, David; Yang, Otto O.; Balamurugan, Arumugam; Bauer, Gerhard; Ireland, Joanna A.; Engel, Barbara C.; Podsakoff, Gregory M.; Hershfield, Michael S.; Blaese, R. Michael; Parkman, Robertson

2012-01-01

We conducted a gene therapy trial in 10 patients with adenosine deaminase (ADA)–deficient severe combined immunodeficiency using 2 slightly different retroviral vectors for the transduction of patients' bone marrow CD34+ cells. Four subjects were treated without pretransplantation cytoreduction and remained on ADA enzyme-replacement therapy (ERT) throughout the procedure. Only transient (months), low-level (< 0.01%) gene marking was observed in PBMCs of 2 older subjects (15 and 20 years of age), whereas some gene marking of PBMC has persisted for the past 9 years in 2 younger subjects (4 and 6 years). Six additional subjects were treated using the same gene transfer protocol, but after withdrawal of ERT and administration of low-dose busulfan (65-90 mg/m2). Three of these remain well, off ERT (5, 4, and 3 years postprocedure), with gene marking in PBMC of 1%-10%, and ADA enzyme expression in PBMC near or in the normal range. Two subjects were restarted on ERT because of poor gene marking and immune recovery, and one had a subsequent allogeneic hematopoietic stem cell transplantation. These studies directly demonstrate the importance of providing nonmyeloablative pretransplantation conditioning to achieve therapeutic benefits with gene therapy for ADA-deficient severe combined immunodeficiency. PMID:22968453

Evaluation and selection of reliable reference genes for gene expression under abiotic stress in cotton (Gossypium hirsutum L.).

PubMed

Wang, Min; Wang, Qinglian; Zhang, Baohong

2013-11-01

Reference genes are critical for normalization of the gene expression level of target genes. The widely used housekeeping genes may change their expression levels at different tissue under different treatment or stress conditions. Therefore, systematical evaluation on the housekeeping genes is required for gene expression analysis. Up to date, no work was performed to evaluate the housekeeping genes in cotton under stress treatment. In this study, we chose 10 housekeeping genes to systematically assess their expression levels at two different tissues (leaves and roots) under two different abiotic stresses (salt and drought) with three different concentrations. Our results show that there is no best reference gene for all tissues at all stress conditions. The reliable reference gene should be selected based on a specific condition. For example, under salt stress, UBQ7, GAPDH and EF1A8 are better reference genes in leaves; TUA10, UBQ7, CYP1, GAPDH and EF1A8 were better in roots. Under drought stress, UBQ7, EF1A8, TUA10, and GAPDH showed less variety of expression level in leaves and roots. Thus, it is better to identify reliable reference genes first before performing any gene expression analysis. However, using a combination of housekeeping genes as reference gene may provide a new strategy for normalization of gene expression. In this study, we found that combination of four housekeeping genes worked well as reference genes under all the stress conditions. © 2013.

GeneBuilder: interactive in silico prediction of gene structure.

PubMed

Milanesi, L; D'Angelo, D; Rogozin, I B

1999-01-01

Prediction of gene structure in newly sequenced DNA becomes very important in large genome sequencing projects. This problem is complicated due to the exon-intron structure of eukaryotic genes and because gene expression is regulated by many different short nucleotide domains. In order to be able to analyse the full gene structure in different organisms, it is necessary to combine information about potential functional signals (promoter region, splice sites, start and stop codons, 3' untranslated region) together with the statistical properties of coding sequences (coding potential), information about homologous proteins, ESTs and repeated elements. We have developed the GeneBuilder system which is based on prediction of functional signals and coding regions by different approaches in combination with similarity searches in proteins and EST databases. The potential gene structure models are obtained by using a dynamic programming method. The program permits the use of several parameters for gene structure prediction and refinement. During gene model construction, selecting different exon homology levels with a protein sequence selected from a list of homologous proteins can improve the accuracy of the gene structure prediction. In the case of low homology, GeneBuilder is still able to predict the gene structure. The GeneBuilder system has been tested by using the standard set (Burset and Guigo, Genomics, 34, 353-367, 1996) and the performances are: 0.89 sensitivity and 0.91 specificity at the nucleotide level. The total correlation coefficient is 0.88. The GeneBuilder system is implemented as a part of the WebGene a the URL: http://www.itba.mi. cnr.it/webgene and TRADAT (TRAncription Database and Analysis Tools) launcher URL: http://www.itba.mi.cnr.it/tradat.

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.

Breast cancer prognosis by combinatorial analysis of gene expression data.

PubMed

Alexe, Gabriela; Alexe, Sorin; Axelrod, David E; Bonates, Tibérius O; Lozina, Irina I; Reiss, Michael; Hammer, Peter L

2006-01-01

The potential of applying data analysis tools to microarray data for diagnosis and prognosis is illustrated on the recent breast cancer dataset of van 't Veer and coworkers. We re-examine that dataset using the novel technique of logical analysis of data (LAD), with the double objective of discovering patterns characteristic for cases with good or poor outcome, using them for accurate and justifiable predictions; and deriving novel information about the role of genes, the existence of special classes of cases, and other factors. Data were analyzed using the combinatorics and optimization-based method of LAD, recently shown to provide highly accurate diagnostic and prognostic systems in cardiology, cancer proteomics, hematology, pulmonology, and other disciplines. LAD identified a subset of 17 of the 25,000 genes, capable of fully distinguishing between patients with poor, respectively good prognoses. An extensive list of 'patterns' or 'combinatorial biomarkers' (that is, combinations of genes and limitations on their expression levels) was generated, and 40 patterns were used to create a prognostic system, shown to have 100% and 92.9% weighted accuracy on the training and test sets, respectively. The prognostic system uses fewer genes than other methods, and has similar or better accuracy than those reported in other studies. Out of the 17 genes identified by LAD, three (respectively, five) were shown to play a significant role in determining poor (respectively, good) prognosis. Two new classes of patients (described by similar sets of covering patterns, gene expression ranges, and clinical features) were discovered. As a by-product of the study, it is shown that the training and the test sets of van 't Veer have differing characteristics. The study shows that LAD provides an accurate and fully explanatory prognostic system for breast cancer using genomic data (that is, a system that, in addition to predicting good or poor prognosis, provides an individualized

GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms.

PubMed

Jani, Saurin D; Argraves, Gary L; Barth, Jeremy L; Argraves, W Scott

2010-04-01

An important objective of DNA microarray-based gene expression experimentation is determining inter-relationships that exist between differentially expressed genes and biological processes, molecular functions, cellular components, signaling pathways, physiologic processes and diseases. Here we describe GeneMesh, a web-based program that facilitates analysis of DNA microarray gene expression data. GeneMesh relates genes in a query set to categories available in the Medical Subject Headings (MeSH) hierarchical index. The interface enables hypothesis driven relational analysis to a specific MeSH subcategory (e.g., Cardiovascular System, Genetic Processes, Immune System Diseases etc.) or unbiased relational analysis to broader MeSH categories (e.g., Anatomy, Biological Sciences, Disease etc.). Genes found associated with a given MeSH category are dynamically linked to facilitate tabular and graphical depiction of Entrez Gene information, Gene Ontology information, KEGG metabolic pathway diagrams and intermolecular interaction information. Expression intensity values of groups of genes that cluster in relation to a given MeSH category, gene ontology or pathway can be displayed as heat maps of Z score-normalized values. GeneMesh operates on gene expression data derived from a number of commercial microarray platforms including Affymetrix, Agilent and Illumina. GeneMesh is a versatile web-based tool for testing and developing new hypotheses through relating genes in a query set (e.g., differentially expressed genes from a DNA microarray experiment) to descriptors making up the hierarchical structure of the National Library of Medicine controlled vocabulary thesaurus, MeSH. The system further enhances the discovery process by providing links between sets of genes associated with a given MeSH category to a rich set of html linked tabular and graphic information including Entrez Gene summaries, gene ontologies, intermolecular interactions, overlays of genes onto KEGG

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.

Functional Analysis of the Arabidopsis TETRASPANIN Gene Family in Plant Growth and Development.

PubMed

Wang, Feng; Muto, Antonella; Van de Velde, Jan; Neyt, Pia; Himanen, Kristiina; Vandepoele, Klaas; Van Lijsebettens, Mieke

2015-11-01

TETRASPANIN (TET) genes encode conserved integral membrane proteins that are known in animals to function in cellular communication during gamete fusion, immunity reaction, and pathogen recognition. In plants, functional information is limited to one of the 17 members of the Arabidopsis (Arabidopsis thaliana) TET gene family and to expression data in reproductive stages. Here, the promoter activity of all 17 Arabidopsis TET genes was investigated by pAtTET::NUCLEAR LOCALIZATION SIGNAL-GREEN FLUORESCENT PROTEIN/β-GLUCURONIDASE reporter lines throughout the life cycle, which predicted functional divergence in the paralogous genes per clade. However, partial overlap was observed for many TET genes across the clades, correlating with few phenotypes in single mutants and, therefore, requiring double mutant combinations for functional investigation. Mutational analysis showed a role for TET13 in primary root growth and lateral root development and redundant roles for TET5 and TET6 in leaf and root growth through negative regulation of cell proliferation. Strikingly, a number of TET genes were expressed in embryonic and seedling progenitor cells and remained expressed until the differentiation state in the mature plant, suggesting a dynamic function over developmental stages. The cis-regulatory elements together with transcription factor-binding data provided molecular insight into the sites, conditions, and perturbations that affect TET gene expression and positioned the TET genes in different molecular pathways; the data represent a hypothesis-generating resource for further functional analyses. © 2015 American Society of Plant Biologists. All Rights Reserved.

Multi-membership gene regulation in pathway based microarray analysis

PubMed Central

2011-01-01

Background Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. Results We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. Conclusions We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes. PMID:21939531

Multi-membership gene regulation in pathway based microarray analysis.

PubMed

Pavlidis, Stelios P; Payne, Annette M; Swift, Stephen M

2011-09-22

Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes.

A gene network bioinformatics analysis for pemphigoid autoimmune blistering diseases.

PubMed

Barone, Antonio; Toti, Paolo; Giuca, Maria Rita; Derchi, Giacomo; Covani, Ugo

2015-07-01

In this theoretical study, a text mining search and clustering analysis of data related to genes potentially involved in human pemphigoid autoimmune blistering diseases (PAIBD) was performed using web tools to create a gene/protein interaction network. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was employed to identify a final set of PAIBD-involved genes and to calculate the overall significant interactions among genes: for each gene, the weighted number of links, or WNL, was registered and a clustering procedure was performed using the WNL analysis. Genes were ranked in class (leader, B, C, D and so on, up to orphans). An ontological analysis was performed for the set of 'leader' genes. Using the above-mentioned data network, 115 genes represented the final set; leader genes numbered 7 (intercellular adhesion molecule 1 (ICAM-1), interferon gamma (IFNG), interleukin (IL)-2, IL-4, IL-6, IL-8 and tumour necrosis factor (TNF)), class B genes were 13, whereas the orphans were 24. The ontological analysis attested that the molecular action was focused on extracellular space and cell surface, whereas the activation and regulation of the immunity system was widely involved. Despite the limited knowledge of the present pathologic phenomenon, attested by the presence of 24 genes revealing no protein-protein direct or indirect interactions, the network showed significant pathways gathered in several subgroups: cellular components, molecular functions, biological processes and the pathologic phenomenon obtained from the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database. The molecular basis for PAIBD was summarised and expanded, which will perhaps give researchers promising directions for the identification of new therapeutic targets.

Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping

PubMed Central

Chen, Lin; An, Yixin; Li, Yong-xiang; Li, Chunhui; Shi, Yunsu; Song, Yanchun; Zhang, Dengfeng; Wang, Tianyu; Li, Yu

2017-01-01

Maize grain yield and related traits are complex and are controlled by a large number of genes of small effect or quantitative trait loci (QTL). Over the years, a large number of yield-related QTLs have been identified in maize and deposited in public databases. However, integrating and re-analyzing these data and mining candidate loci for yield-related traits has become a major issue in maize. In this study, we collected information on QTLs conferring maize yield-related traits from 33 published studies. Then, 999 of these QTLs were iteratively projected and subjected to meta-analysis to obtain metaQTLs (MQTLs). A total of 76 MQTLs were found across the maize genome. Based on a comparative genomics strategy, several maize orthologs of rice yield-related genes were identified in these MQTL regions. Furthermore, three potential candidate genes (Gene ID: GRMZM2G359974, GRMZM2G301884, and GRMZM2G083894) associated with kernel size and weight within three MQTL regions were identified using regional association mapping, based on the results of the meta-analysis. This strategy, combining MQTL analysis and regional association mapping, is helpful for functional marker development and rapid identification of candidate genes or loci. PMID:29312420

Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies.

PubMed

Martini, Paolo; Risso, Davide; Sales, Gabriele; Romualdi, Chiara; Lanfranchi, Gerolamo; Cagnin, Stefano

2011-04-11

In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focused on the identification of significant differentially expressed genes. Later, researchers moved toward the systematic integration of gene expression profiles with additional biological information, such as chromosomal location, ontological annotations or sequence features. The analysis of gene expression linked to physical location of genes on chromosomes allows the identification of transcriptionally imbalanced regions, while, Gene Set Analysis focuses on the detection of coordinated changes in transcriptional levels among sets of biologically related genes. In this field, meta-analysis offers the possibility to compare different studies, addressing the same biological question to fully exploit public gene expression datasets. We describe STEPath, a method that starts from gene expression profiles and integrates the analysis of imbalanced region as an a priori step before performing gene set analysis. The application of STEPath in individual studies produced gene set scores weighted by chromosomal activation. As a final step, we propose a way to compare these scores across different studies (meta-analysis) on related biological issues. One complication with meta-analysis is batch effects, which occur because molecular measurements are affected by laboratory conditions, reagent lots and personnel differences. Major problems occur when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. We evaluated the power of combining chromosome mapping and gene set enrichment analysis, performing the analysis on a dataset of leukaemia (example of individual study) and on a dataset of skeletal muscle diseases (meta-analysis approach). In leukaemia, we identified the Hox gene set, a gene set closely related to the pathology that other algorithms of gene set analysis do not

Genome-Wide Identification and Evaluation of Reference Genes for Quantitative RT-PCR Analysis during Tomato Fruit Development.

PubMed

Cheng, Yuan; Bian, Wuying; Pang, Xin; Yu, Jiahong; Ahammed, Golam J; Zhou, Guozhi; Wang, Rongqing; Ruan, Meiying; Li, Zhimiao; Ye, Qingjing; Yao, Zhuping; Yang, Yuejian; Wan, Hongjian

2017-01-01

Gene expression analysis in tomato fruit has drawn increasing attention nowadays. Quantitative real-time PCR (qPCR) is a routine technique for gene expression analysis. In qPCR operation, reliability of results largely depends on the choice of appropriate reference genes (RGs). Although tomato is a model for fruit biology study, few RGs for qPCR analysis in tomato fruit had yet been developed. In this study, we initially identified 38 most stably expressed genes based on tomato transcriptome data set, and their expression stabilities were further determined in a set of tomato fruit samples of four different fruit developmental stages (Immature, mature green, breaker, mature red) using qPCR analysis. Two statistical algorithms, geNorm and Normfinder, concordantly determined the superiority of these identified putative RGs. Notably, SlFRG05 (Solyc01g104170), SlFRG12 (Solyc04g009770), SlFRG16 (Solyc10g081190), SlFRG27 (Solyc06g007510), and SlFRG37 (Solyc11g005330) were proved to be suitable RGs for tomato fruit development study. Further analysis using geNorm indicate that the combined use of SlFRG03 (Solyc02g063070) and SlFRG27 would provide more reliable normalization results in qPCR experiments. The identified RGs in this study will be beneficial for future qPCR analysis of tomato fruit developmental study, as well as for the potential identification of optimal normalization controls in other plant species.

Genome-Wide Identification and Evaluation of Reference Genes for Quantitative RT-PCR Analysis during Tomato Fruit Development

PubMed Central

Cheng, Yuan; Bian, Wuying; Pang, Xin; Yu, Jiahong; Ahammed, Golam J.; Zhou, Guozhi; Wang, Rongqing; Ruan, Meiying; Li, Zhimiao; Ye, Qingjing; Yao, Zhuping; Yang, Yuejian; Wan, Hongjian

2017-01-01

Gene expression analysis in tomato fruit has drawn increasing attention nowadays. Quantitative real-time PCR (qPCR) is a routine technique for gene expression analysis. In qPCR operation, reliability of results largely depends on the choice of appropriate reference genes (RGs). Although tomato is a model for fruit biology study, few RGs for qPCR analysis in tomato fruit had yet been developed. In this study, we initially identified 38 most stably expressed genes based on tomato transcriptome data set, and their expression stabilities were further determined in a set of tomato fruit samples of four different fruit developmental stages (Immature, mature green, breaker, mature red) using qPCR analysis. Two statistical algorithms, geNorm and Normfinder, concordantly determined the superiority of these identified putative RGs. Notably, SlFRG05 (Solyc01g104170), SlFRG12 (Solyc04g009770), SlFRG16 (Solyc10g081190), SlFRG27 (Solyc06g007510), and SlFRG37 (Solyc11g005330) were proved to be suitable RGs for tomato fruit development study. Further analysis using geNorm indicate that the combined use of SlFRG03 (Solyc02g063070) and SlFRG27 would provide more reliable normalization results in qPCR experiments. The identified RGs in this study will be beneficial for future qPCR analysis of tomato fruit developmental study, as well as for the potential identification of optimal normalization controls in other plant species. PMID:28900431

In vivo genome-wide analysis of multiple tissues identifies gene regulatory networks, novel functions and downstream regulatory genes for Bapx1 and its co-regulation with Sox9 in the mammalian vertebral column.

PubMed

Chatterjee, Sumantra; Sivakamasundari, V; Yap, Sook Peng; Kraus, Petra; Kumar, Vibhor; Xing, Xing; Lim, Siew Lan; Sng, Joel; Prabhakar, Shyam; Lufkin, Thomas

2014-12-05

Vertebrate organogenesis is a highly complex process involving sequential cascades of transcription factor activation or repression. Interestingly a single developmental control gene can occasionally be essential for the morphogenesis and differentiation of tissues and organs arising from vastly disparate embryological lineages. Here we elucidated the role of the mammalian homeobox gene Bapx1 during the embryogenesis of five distinct organs at E12.5 - vertebral column, spleen, gut, forelimb and hindlimb - using expression profiling of sorted wildtype and mutant cells combined with genome wide binding site analysis. Furthermore we analyzed the development of the vertebral column at the molecular level by combining transcriptional profiling and genome wide binding data for Bapx1 with similarly generated data sets for Sox9 to assemble a detailed gene regulatory network revealing genes previously not reported to be controlled by either of these two transcription factors. The gene regulatory network appears to control cell fate decisions and morphogenesis in the vertebral column along with the prevention of premature chondrocyte differentiation thus providing a detailed molecular view of vertebral column development.

Identification and analysis of novel genes involved in gravitropism of Arabidopsis thaliana.

NASA Astrophysics Data System (ADS)

Morita, Miyo T.; Tasaka, Masao; Masatoshi Taniguchi, .

2012-07-01

Gravitropism is a continuous control with regard to the orientation and juxtaposition of the various parts of the plant body in response to gravity. In higher plants, the relative directional change of gravity is mainly suscepted in specialized cells called statocytes, followed by signal conversion from physical information into physiological information within the statocytes. We have studied the early process of shoot gravitropism, gravity sensing and signaling process, mainly by molecular genetic approach. In Arabidopsis shoot, statocytes are the endodermal cells. sgr1/scarcrow (scr) and sgr7/short-root (shr) mutants fail to form the endodermis and to respond to gravity in their inflorescence stems. Since both SGR1/SCR and SGR7/SHR are transcriptional factors, at least a subset of their downstream genes can be expected to be involved in gravitropism. In addition, eal1 (endodermal-amyloplast less 1), which exhibits no gravitropism in inflorescence stem but retains ability to form endodermis, is a hypomorphic allele of sgr7/shr. Take advantage of these mutants, we performed DNA microarray analysis and compared gene expression profiles between wild type and the mutants. We found that approx. 40 genes were commonly down-regulated in these mutants and termed them DGE (DOWN-REGULATED GENE IN EAL1) genes. DGE1 has sequence similarity to Oryza sativa LAZY1 that is involved in shoot gravitropism of rice. DGE2 has a short region homologous to DGE1. DTL (DGE TWO-LIKE}) that has 54% identity to DGE2 is found in Arabidopsis genome. All three genes are conserved in angiosperm but have no known functional domains or motifs. We analyzed T-DNA insertion for these genes in single or multiple combinations. In dge1 dge2 dtl triple mutant, gravitropic response of shoot, hypocotyl and root dramatically reduced. Now we are carrying out further physiological and molecular genetic analysis of the triple mutant.

Identification of candidate genes in osteoporosis by integrated microarray analysis.

PubMed

Li, J J; Wang, B Q; Fei, Q; Yang, Y; Li, D

2016-12-01

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.Cite this article: J. J

LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights

PubMed Central

Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

2016-01-01

Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher’s exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO’s usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher. PMID:26750448

LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights.

PubMed

Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

2016-01-11

Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher's exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO's usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher.

A combination of PhP typing and β-d-glucuronidase gene sequence variation analysis for differentiation of Escherichia coli from humans and animals.

PubMed

Masters, N; Christie, M; Katouli, M; Stratton, H

2015-06-01

We investigated the usefulness of the β-d-glucuronidase gene variance in Escherichia coli as a microbial source tracking tool using a novel algorithm for comparison of sequences from a prescreened set of host-specific isolates using a high-resolution PhP typing method. A total of 65 common biochemical phenotypes belonging to 318 E. coli strains isolated from humans and domestic and wild animals were analysed for nucleotide variations at 10 loci along a 518 bp fragment of the 1812 bp β-d-glucuronidase gene. Neighbour-joining analysis of loci variations revealed 86 (76.8%) human isolates and 91.2% of animal isolates were correctly identified. Pairwise hierarchical clustering improved assignment; where 92 (82.1%) human and 204 (99%) animal strains were assigned to their respective cluster. Our data show that initial typing of isolates and selection of common types from different hosts prior to analysis of the β-d-glucuronidase gene sequence improves source identification. We also concluded that numerical profiling of the nucleotide variations can be used as a valuable approach to differentiate human from animal E. coli. This study signifies the usefulness of the β-d-glucuronidase gene as a marker for differentiating human faecal pollution from animal sources.

Expression analysis in response to drought stress in soybean: Shedding light on the regulation of metabolic pathway genes.

PubMed

Guimarães-Dias, Fábia; Neves-Borges, Anna Cristina; Viana, Antonio Americo Barbosa; Mesquita, Rosilene Oliveira; Romano, Eduardo; de Fátima Grossi-de-Sá, Maria; Nepomuceno, Alexandre Lima; Loureiro, Marcelo Ehlers; Alves-Ferreira, Márcio

2012-06-01

Metabolomics analysis of wild type Arabidopsis thaliana plants, under control and drought stress conditions revealed several metabolic pathways that are induced under water deficit. The metabolic response to drought stress is also associated with ABA dependent and independent pathways, allowing a better understanding of the molecular mechanisms in this model plant. Through combining an in silico approach and gene expression analysis by quantitative real-time PCR, the present work aims at identifying genes of soybean metabolic pathways potentially associated with water deficit. Digital expression patterns of Arabidopsis genes, which were selected based on the basis of literature reports, were evaluated under drought stress condition by Genevestigator. Genes that showed strong induction under drought stress were selected and used as bait to identify orthologs in the soybean genome. This allowed us to select 354 genes of putative soybean orthologs of 79 Arabidopsis genes belonging to 38 distinct metabolic pathways. The expression pattern of the selected genes was verified in the subtractive libraries available in the GENOSOJA project. Subsequently, 13 genes from different metabolic pathways were selected for validation by qPCR experiments. The expression of six genes was validated in plants undergoing drought stress in both pot-based and hydroponic cultivation systems. The results suggest that the metabolic response to drought stress is conserved in Arabidopsis and soybean plants.

Effects of blood-activating and stasis-removing drugs combined with VEGF gene transfer on angiogenesis in ischemic necrosis of the femoral head.

PubMed

Li, Jun-Hui; Wu, Ya-Ling; Ye, Jian-Hong; Ning, Ya-Gong; Yu, Hai-Ying; Peng, Zhong-Jie; Luan, Xiao-Wen

2009-09-01

To observe the promoting effects of blood-activating and stasis-removing Chinese drugs combined with vascular endothelial growth factor (VEGF) gene transfer on angiogenesis in ischemic necrosis of the femoral head. Forty Japanese giant-ear rabbits were randomly divided into a control group, a model group, a Chinese drug group, a gene group, and a combined group. After 8 weeks of treatment, the rate of VEGF positive cell expression in the synovium of the femoral head was measured using the immunohistochemical method, and the number of blood vessels in the femoral head was measured by digital subtraction angiography. The rate of VEGF positive cell expression in the model group was significantly lower than that in the Chinese drug group (P < 0.05) and very significantly lower than those in other groups (P < 0.01); but in the combined group it was significantly higher than in the Chinese drug group (P < 0.05). The differences in the number of blood vessels in area A between the model group and other groups were not statistically significant. However, in area B, the number of blood vessels significantly increased in the control group, the gene group and the combined group as compared with the model group (P < 0.05), and in the combined group the number of blood vessels was significantly more than in the gene group (P < 0.05); but in the Chinese drug group it was not significantly different than the model group (P > 0.05). Either the blood-activating and stasis-removing Chinese drugs or VEGF gene transfer can promote the angiogenesis and building of collateral circulation for femoral head ischemic necrosis, and the combined therapy with Chinese drugs or VEGF gene transfer may show a better therapeutic effect. The present study provides an experimental basis for clinical application of the combined therapy with the blood-activating and stasis-removing Chinese drugs and VEGF gene transfer.

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

PubMed

Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

2014-01-01

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

Functional Analysis With a Barcoder Yeast Gene Overexpression System

PubMed Central

Douglas, Alison C.; Smith, Andrew M.; Sharifpoor, Sara; Yan, Zhun; Durbic, Tanja; Heisler, Lawrence E.; Lee, Anna Y.; Ryan, Owen; Göttert, Hendrikje; Surendra, Anu; van Dyk, Dewald; Giaever, Guri; Boone, Charles; Nislow, Corey; Andrews, Brenda J.

2012-01-01

Systematic analysis of gene overexpression phenotypes provides an insight into gene function, enzyme targets, and biological pathways. Here, we describe a novel functional genomics platform that enables a highly parallel and systematic assessment of overexpression phenotypes in pooled cultures. First, we constructed a genome-level collection of ~5100 yeast barcoder strains, each of which carries a unique barcode, enabling pooled fitness assays with a barcode microarray or sequencing readout. Second, we constructed a yeast open reading frame (ORF) galactose-induced overexpression array by generating a genome-wide set of yeast transformants, each of which carries an individual plasmid-born and sequence-verified ORF derived from the Saccharomyces cerevisiae full-length EXpression-ready (FLEX) collection. We combined these collections genetically using synthetic genetic array methodology, generating ~5100 strains, each of which is barcoded and overexpresses a specific ORF, a set we termed “barFLEX.” Additional synthetic genetic array allows the barFLEX collection to be moved into different genetic backgrounds. As a proof-of-principle, we describe the properties of the barFLEX overexpression collection and its application in synthetic dosage lethality studies under different environmental conditions. PMID:23050238

A Method for Gene-Based Pathway Analysis Using Genomewide Association Study Summary Statistics Reveals Nine New Type 1 Diabetes Associations

PubMed Central

Evangelou, Marina; Smyth, Deborah J; Fortune, Mary D; Burren, Oliver S; Walker, Neil M; Guo, Hui; Onengut-Gumuscu, Suna; Chen, Wei-Min; Concannon, Patrick; Rich, Stephen S; Todd, John A; Wallace, Chris

2014-01-01

Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed () with 12 of the 22 SNPs showing . Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, ), NRP1 (rs722988, ), BAD (rs694739, ), CTSB (rs1296023, ), FYN (rs11964650, ), UBE2G1 (rs9906760, ), MAP3K14 (rs17759555, ), ITGB1 (rs1557150, ), and IL7R (rs1445898, ). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available. PMID:25371288

The drug target genes show higher evolutionary conservation than non-target genes.

PubMed

Lv, Wenhua; Xu, Yongdeng; Guo, Yiying; Yu, Ziqi; Feng, Guanglong; Liu, Panpan; Luan, Meiwei; Zhu, Hongjie; Liu, Guiyou; Zhang, Mingming; Lv, Hongchao; Duan, Lian; Shang, Zhenwei; Li, Jin; Jiang, Yongshuai; Zhang, Ruijie

2016-01-26

Although evidence indicates that drug target genes share some common evolutionary features, there have been few studies analyzing evolutionary features of drug targets from an overall level. Therefore, we conducted an analysis which aimed to investigate the evolutionary characteristics of drug target genes. We compared the evolutionary conservation between human drug target genes and non-target genes by combining both the evolutionary features and network topological properties in human protein-protein interaction network. The evolution rate, conservation score and the percentage of orthologous genes of 21 species were included in our study. Meanwhile, four topological features including the average shortest path length, betweenness centrality, clustering coefficient and degree were considered for comparison analysis. Then we got four results as following: compared with non-drug target genes, 1) drug target genes had lower evolutionary rates; 2) drug target genes had higher conservation scores; 3) drug target genes had higher percentages of orthologous genes and 4) drug target genes had a tighter network structure including higher degrees, betweenness centrality, clustering coefficients and lower average shortest path lengths. These results demonstrate that drug target genes are more evolutionarily conserved than non-drug target genes. We hope that our study will provide valuable information for other researchers who are interested in evolutionary conservation of drug targets.

Exome Sequencing and Linkage Analysis Identified Novel Candidate Genes in Recessive Intellectual Disability Associated with Ataxia.

PubMed

Jazayeri, Roshanak; Hu, Hao; Fattahi, Zohreh; Musante, Luciana; Abedini, Seyedeh Sedigheh; Hosseini, Masoumeh; Wienker, Thomas F; Ropers, Hans Hilger; Najmabadi, Hossein; Kahrizi, Kimia

2015-10-01

Intellectual disability (ID) is a neuro-developmental disorder which causes considerable socio-economic problems. Some ID individuals are also affected by ataxia, and the condition includes different mutations affecting several genes. We used whole exome sequencing (WES) in combination with homozygosity mapping (HM) to identify the genetic defects in five consanguineous families among our cohort study, with two affected children with ID and ataxia as major clinical symptoms. We identified three novel candidate genes, RIPPLY1, MRPL10, SNX14, and a new mutation in known gene SURF1. All are autosomal genes, except RIPPLY1, which is located on the X chromosome. Two are housekeeping genes, implicated in transcription and translation regulation and intracellular trafficking, and two encode mitochondrial proteins. The pathogenesis of these variants was evaluated by mutation classification, bioinformatic methods, review of medical and biological relevance, co-segregation studies in the particular family, and a normal population study. Linkage analysis and exome sequencing of a small number of affected family members is a powerful new technique which can be used to decrease the number of candidate genes in heterogenic disorders such as ID, and may even identify the responsible gene(s).

Comparative and evolutionary analysis of the HES/HEY gene family reveal exon/intron loss and teleost specific duplication events.

PubMed

Zhou, Mi; Yan, Jun; Ma, Zhaowu; Zhou, Yang; Abbood, Nibras Najm; Liu, Jianfeng; Su, Li; Jia, Haibo; Guo, An-Yuan

2012-01-01

HES/HEY genes encode a family of basic helix-loop-helix (bHLH) transcription factors with both bHLH and Orange domain. HES/HEY proteins are direct targets of the Notch signaling pathway and play an essential role in developmental decisions, such as the developments of nervous system, somitogenesis, blood vessel and heart. Despite their important functions, the origin and evolution of this HES/HEY gene family has yet to be elucidated. In this study, we identified genes of the HES/HEY family in representative species and performed evolutionary analysis to elucidate their origin and evolutionary process. Our results showed that the HES/HEY genes only existed in metazoans and may originate from the common ancestor of metazoans. We identified HES/HEY genes in more than 10 species representing the main lineages. Combining the bHLH and Orange domain sequences, we constructed the phylogenetic trees by different methods (Bayesian, ML, NJ and ME) and classified the HES/HEY gene family into four groups. Our results indicated that this gene family had undergone three expansions, which were along with the origins of Eumetazoa, vertebrate, and teleost. Gene structure analysis revealed that the HES/HEY genes were involved in exon and/or intron loss in different species lineages. Genes of this family were duplicated in bony fishes and doubled than other vertebrates. Furthermore, we studied the teleost-specific duplications in zebrafish and investigated the expression pattern of duplicated genes in different tissues by RT-PCR. Finally, we proposed a model to show the evolution of this gene family with processes of expansion, exon/intron loss, and motif loss. Our study revealed the evolution of HES/HEY gene family, the expression and function divergence of duplicated genes, which also provide clues for the research of Notch function in development. This study shows a model of gene family analysis with gene structure evolution and duplication.

Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders

PubMed Central

Jha, Prabhash Kumar; Vijay, Aatira; Sahu, Anita; Ashraf, Mohammad Zahid

2016-01-01

Thrombosis is a leading cause of morbidity and mortality in patients with myeloproliferative disorders (MPDs), particularly polycythemia vera (PV) and essential thrombocythemia (ET). Despite the attempts to establish a link between them, the shared biological mechanisms are yet to be characterized. An integrated gene expression meta-analysis of five independent publicly available microarray data of the three diseases was conducted to identify shared gene expression signatures and overlapping biological processes. Using INMEX bioinformatic tool, based on combined Effect Size (ES) approaches, we identified a total of 1,157 differentially expressed genes (DEGs) (697 overexpressed and 460 underexpressed genes) shared between the three diseases. EnrichR tool’s rich library was used for comprehensive functional enrichment and pathway analysis which revealed “mRNA Splicing” and “SUMO E3 ligases SUMOylate target proteins” among the most enriched terms. Network based meta-analysis identified MYC and FN1 to be the most highly ranked hub genes. Our results reveal that the alterations in biomarkers of the coagulation cascade like F2R, PROS1, SELPLG and ITGB2 were common between the three diseases. Interestingly, the study has generated a novel database of candidate genetic markers, pathways and transcription factors shared between thrombosis and MPDs, which might aid in the development of prognostic therapeutic biomarkers. PMID:27892526

ribB and ribBA genes from Acidithiobacillus ferrooxidans: expression levels under different growth conditions and phylogenetic analysis.

PubMed

Knegt, Fábio H P; Mello, Luciane V; Reis, Fernanda C; Santos, Marcos T; Vicentini, Renato; Ferraz, Lúcio F C; Ottoboni, Laura M M

2008-01-01

Acidithiobacillus ferrooxidans is a Gram-negative, chemolithoautotrophic bacterium involved in metal bioleaching. Using the RNA arbitrarily primed polymerase chain reaction (RAP-PCR), we have identified several cDNAs that were differentially expressed when A. ferrooxidans LR was submitted to potassium- and phosphate-limiting conditions. One of these cDNAs showed similarity with ribB. An analysis of the A. ferrooxidans ATCC 23270 genome, made available by The Institute for Genomic Research, showed that the ribB gene was not located in the rib operon, but a ribBA gene was present in this operon instead. The ribBA gene was isolated from A. ferrooxidans LR and expression of both ribB and ribBA was investigated. Transcript levels of both genes were enhanced in cells grown in the absence of K2HPO4, in the presence of zinc and copper sulfate and in different pHs. Transcript levels decreased upon exposure to a temperature higher than the ideal 30 degrees C and at pH 1.2. A comparative genomic analysis using the A. ferrooxidans ATCC 23270 genome revealed similar putative regulatory elements for both genes. Moreover, an RFN element was identified upstream from the ribB gene. Phylogenetic analysis of the distribution of RibB and RibBA in bacteria showed six different combinations. We suggest that the presence of duplicated riboflavin synthesis genes in bacteria must provide their host with some benefit in certain stressful situations.

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

A pathway-based network analysis of hypertension-related genes

NASA Astrophysics Data System (ADS)

Wang, Huan; Hu, Jing-Bo; Xu, Chuan-Yun; Zhang, De-Hai; Yan, Qian; Xu, Ming; Cao, Ke-Fei; Zhang, Xu-Sheng

2016-02-01

Complex network approach has become an effective way to describe interrelationships among large amounts of biological data, which is especially useful in finding core functions and global behavior of biological systems. Hypertension is a complex disease caused by many reasons including genetic, physiological, psychological and even social factors. In this paper, based on the information of biological pathways, we construct a network model of hypertension-related genes of the salt-sensitive rat to explore the interrelationship between genes. Statistical and topological characteristics show that the network has the small-world but not scale-free property, and exhibits a modular structure, revealing compact and complex connections among these genes. By the threshold of integrated centrality larger than 0.71, seven key hub genes are found: Jun, Rps6kb1, Cycs, Creb312, Cdk4, Actg1 and RT1-Da. These genes should play an important role in hypertension, suggesting that the treatment of hypertension should focus on the combination of drugs on multiple genes.

Pan- and core- network analysis of co-expression genes in a model plant

DOE PAGES

He, Fei; Maslov, Sergei

2016-12-16

Genome-wide gene expression experiments have been performed using the model plant Arabidopsis during the last decade. Some studies involved construction of coexpression networks, a popular technique used to identify groups of co-regulated genes, to infer unknown gene functions. One approach is to construct a single coexpression network by combining multiple expression datasets generated in different labs. We advocate a complementary approach in which we construct a large collection of 134 coexpression networks based on expression datasets reported in individual publications. To this end we reanalyzed public expression data. To describe this collection of networks we introduced concepts of ‘pan-network’ andmore » ‘core-network’ representing union and intersection between a sizeable fractions of individual networks, respectively. Here, we showed that these two types of networks are different both in terms of their topology and biological function of interacting genes. For example, the modules of the pan-network are enriched in regulatory and signaling functions, while the modules of the core-network tend to include components of large macromolecular complexes such as ribosomes and photosynthetic machinery. Our analysis is aimed to help the plant research community to better explore the information contained within the existing vast collection of gene expression data in Arabidopsis.« less

Pan- and core- network analysis of co-expression genes in a model plant

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

He, Fei; Maslov, Sergei

Genome-wide gene expression experiments have been performed using the model plant Arabidopsis during the last decade. Some studies involved construction of coexpression networks, a popular technique used to identify groups of co-regulated genes, to infer unknown gene functions. One approach is to construct a single coexpression network by combining multiple expression datasets generated in different labs. We advocate a complementary approach in which we construct a large collection of 134 coexpression networks based on expression datasets reported in individual publications. To this end we reanalyzed public expression data. To describe this collection of networks we introduced concepts of ‘pan-network’ andmore » ‘core-network’ representing union and intersection between a sizeable fractions of individual networks, respectively. Here, we showed that these two types of networks are different both in terms of their topology and biological function of interacting genes. For example, the modules of the pan-network are enriched in regulatory and signaling functions, while the modules of the core-network tend to include components of large macromolecular complexes such as ribosomes and photosynthetic machinery. Our analysis is aimed to help the plant research community to better explore the information contained within the existing vast collection of gene expression data in Arabidopsis.« less

Multifunctional Poly(L-lactide)-Polyethylene Glycol-Grafted Graphene Quantum Dots for Intracellular MicroRNA Imaging and Combined Specific-Gene-Targeting Agents Delivery for Improved Therapeutics.

PubMed

Dong, Haifeng; Dai, Wenhao; Ju, Huangxian; Lu, Huiting; Wang, Shiyan; Xu, Liping; Zhou, Shu-Feng; Zhang, Yue; Zhang, Xueji

2015-05-27

Photoluminescent (PL) graphene quantum dots (GQDs) with large surface area and superior mechanical flexibility exhibit fascinating optical and electronic properties and possess great promising applications in biomedical engineering. Here, a multifunctional nanocomposite of poly(l-lactide) (PLA) and polyethylene glycol (PEG)-grafted GQDs (f-GQDs) was proposed for simultaneous intracellular microRNAs (miRNAs) imaging analysis and combined gene delivery for enhanced therapeutic efficiency. The functionalization of GQDs with PEG and PLA imparts the nanocomposite with super physiological stability and stable photoluminescence over a broad pH range, which is vital for cell imaging. Cell experiments demonstrate the f-GQDs excellent biocompatibility, lower cytotoxicity, and protective properties. Using the HeLa cell as a model, we found the f-GQDs effectively delivered a miRNA probe for intracellular miRNA imaging analysis and regulation. Notably, the large surface of GQDs was capable of simultaneous adsorption of agents targeting miRNA-21 and survivin, respectively. The combined conjugation of miRNA-21-targeting and survivin-targeting agents induced better inhibition of cancer cell growth and more apoptosis of cancer cells, compared with conjugation of agents targeting miRNA-21 or survivin alone. These findings highlight the promise of the highly versatile multifunctional nanocomposite in biomedical application of intracellular molecules analysis and clinical gene therapeutics.

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.

Cloning, characterization, and physical mapping of the canine Prop-1 gene (PROP1): exclusion as a candidate for combined pituitary hormone deficiency in German shepherd dogs.

PubMed

Lantinga-van Leeuwen, I S; Kooistra, H S; Mol, J A; Renier, C; Breen, M; van Oost, B A

2000-01-01

Abnormalities in the genes encoding Pit-1 and Prop-1 have been reported to cause combined pituitary hormone deficiency (CPHD) in mice and humans. In dogs, a similar phenotype has been described in the German shepherd breed. We have previously reported that the Pit-1 gene (POU1F1) is not mutated in affected German shepherd dogs. In this study, we report the isolation and mapping of the canine Prop-1 gene (PROP1), and we assessed the involvement of PROP1 in German shepherd dog dwarfism. The canine PROP1 gene was found to contain three exons, encoding a 226 amino acid protein. The deduced amino acid sequence was 79% and 84% homologous with the mouse and human Prop-1 protein, respectively. Using fluorescence in situ hybridization, PROP1 was mapped to canine chromosome 11. Further mapping with a canine radiation hybrid panel showed co-localization with the polymorphic DNA marker AHT137. Sequence analysis of genomic DNA from dwarf German shepherd dogs revealed no alterations in the PROP1 gene. Moreover, linkage analysis of AHT137 revealed no co-segregation between the PROP1 locus and the CPHD phenotype, excluding this gene as candidate for canine CPHD and providing a new spontaneous model of hypopituitarism. Copyright 2000 S. Karger AG, Basel

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.

Gene expression profiles analysis identifies key genes for acute lung injury in patients with sepsis.

PubMed

Guo, Zhiqiang; Zhao, Chuncheng; Wang, Zheng

2014-09-26

To identify critical genes and biological pathways in acute lung injury (ALI), a comparative analysis of gene expression profiles of patients with ALI + sepsis compared with patients with sepsis alone were performed with bioinformatic tools. GSE10474 was downloaded from Gene Expression Omnibus, including a collective of 13 whole blood samples with ALI + sepsis and 21 whole blood samples with sepsis alone. After pre-treatment with robust multichip averaging (RMA) method, differential analysis was conducted using simpleaffy package based upon t-test and fold change. Hierarchical clustering was also performed using function hclust from package stats. Beisides, functional enrichment analysis was conducted using iGepros. Moreover, the gene regulatory network was constructed with information from Kyoto Encyclopedia of Genes and Genomes (KEGG) and then visualized by Cytoscape. A total of 128 differentially expressed genes (DEGs) were identified, including 47 up- and 81 down-regulated genes. The significantly enriched functions included negative regulation of cell proliferation, regulation of response to stimulus and cellular component morphogenesis. A total of 27 DEGs were significantly enriched in 16 KEGG pathways, such as protein digestion and absorption, fatty acid metabolism, amoebiasis, etc. Furthermore, the regulatory network of these 27 DEGs was constructed, which involved several key genes, including protein tyrosine kinase 2 (PTK2), v-src avian sarcoma (SRC) and Caveolin 2 (CAV2). PTK2, SRC and CAV2 may be potential markers for diagnosis and treatment of ALI. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5865162912987143.

The de novo Q167K mutation in the POU1F1 gene leads to combined pituitary hormone deficiency in an Italian patient.

PubMed

Malvagia, Sabrina; Poggi, Giovanni Maria; Pasquini, Elisabetta; Donati, Maria Alice; Pela, Ivana; Morrone, Amelia; Zammarchi, Enrico

2003-11-01

The POU1F1 gene encodes a transcription factor that is important for the development and differentiation of the cells producing GH, prolactin, and TSH in the anterior pituitary gland. Patients with POU1F1 mutations show a combined pituitary hormone deficiency with low or absent levels of GH, prolactin, and TSH. Fourteen mutations have been reported in the POU1F1 gene up to now. These genetic lesions can be inherited either in an autosomal dominant or an autosomal recessive mode. We report on the first Italian patient, a girl, affected by combined pituitary hormone deficiency. The patient was found to be positive for congenital hypothyroidism (with low TSH levels) at neonatal screening. Substitutive therapy was started, but subsequent growth was very poor, although psychomotor development was substantially normal. Hospitalized at 10 mo she showed hypotonic crises, growth retardation, delayed bone age, and facial dysmorphism. In addition to congenital hypothyroidism, GH and prolactin deficiencies were found. Mutation DNA analysis of the patient's POU1F1 gene identified the novel Q167K amino acid change at the heterozygous level. The highly conserved Q167 residue is located in the POU-specific domain. No mutation was detected in the other allele. DNA analysis in the proband's parents did not identify this amino acid substitution, suggesting a de novo genetic lesion. From these data it can be hypothesized that the Q167K mutation has a dominant negative effect.

Oligoamine analogues in combination with 2-difluoromethylornithine synergistically induce re-expression of aberrantly silenced tumour-suppressor genes

PubMed Central

Wu, Yu; Steinbergs, Nora; Murray-Stewart, Tracy; Marton, Laurence J.; Casero, Robert A.

2011-01-01

Epigenetic gene silencing is an important mechanism in the initiation and progression of cancer. Abnormal DNA CpG island hypermethylation and histone modifications are involved in aberrant silencing of tumour-suppressor genes. LSD1 (lysine-specific demethylase 1) was the first enzyme identified to specifically demethylate H3K4 (Lys4 of histone H3). Methylated H3K4 is an important mark associated with transcriptional activation. The flavin adenine dinucleotide-binding amine oxidase domain of LSD1 is homologous with two polyamine oxidases, SMO (spermine oxidase) and APAO (N1-acetylpolyamine oxidase). We have demonstrated previously that long-chain polyamine analogues, the oligoamines, are inhibitors of LSD1. In the present paper we report the synergistic effects of specific oligoamines in combination with DFMO (2-difluoromethylornithine), an inhibitor of ornithine decarboxylase, in human colorectal cancer cells. DFMO treatment depletes natural polyamines and increases the uptake of exogenous polyamines. The combination of oligoamines and DFMO results in a synergistic re-expression of aberrantly silenced tumour-suppressor genes, including SFRP2 (secreted frizzled-related protein 2), which encodes a Wnt signalling pathway antagonist and plays an anti-tumorigenic role in colorectal cancer. The treatment-induced re-expression of SFRP2 is associated with increased H3K4me2 (di-methyl H3K4) in the gene promoter. The combination of LSD1-inhibiting oligoamines and DFMO represents a novel approach to epigenetic therapy of cancer. PMID:22132744

Validation of Reference Genes for Robust qRT-PCR Gene Expression Analysis in the Rice Blast Fungus Magnaporthe oryzae.

PubMed

Che Omar, Sarena; Bentley, Michael A; Morieri, Giulia; Preston, Gail M; Gurr, Sarah J

2016-01-01

The rice blast fungus causes significant annual harvest losses. It also serves as a genetically-tractable model to study fungal ingress. Whilst pathogenicity determinants have been unmasked and changes in global gene expression described, we know little about Magnaporthe oryzae cell wall remodelling. Our interests, in wall remodelling genes expressed during infection, vegetative growth and under exogenous wall stress, demand robust choice of reference genes for quantitative Real Time-PCR (qRT-PCR) data normalisation. We describe the expression stability of nine candidate reference genes profiled by qRT-PCR with cDNAs derived during asexual germling development, from sexual stage perithecia and from vegetative mycelium grown under various exogenous stressors. Our Minimum Information for Publication of qRT-PCR Experiments (MIQE) compliant analysis reveals a set of robust reference genes used to track changes in the expression of the cell wall remodelling gene MGG_Crh2 (MGG_00592). We ranked nine candidate reference genes by their expression stability (M) and report the best gene combination needed for reliable gene expression normalisation, when assayed in three tissue groups (Infective, Vegetative, and Global) frequently used in M. oryzae expression studies. We found that MGG_Actin (MGG_03982) and the 40S 27a ribosomal subunit MGG_40s (MGG_02872) proved to be robust reference genes for the Infection group and MGG_40s and MGG_Ef1 (Elongation Factor1-α) for both Vegetative and Global groups. Using the above validated reference genes, M. oryzae MGG_Crh2 expression was found to be significantly (p<0.05) elevated three-fold during vegetative growth as compared with dormant spores and two fold higher under cell wall stress (Congo Red) compared to growth under optimal conditions. We recommend the combinatorial use of two reference genes, belonging to the cytoskeleton and ribosomal synthesis functional groups, MGG_Actin, MGG_40s, MGG_S8 (Ribosomal subunit 40S S8) or MGG

Effects of single and combined low frequency electromagnetic fields and simulated microgravity on gene expression of human mesenchymal stem cells during chondrogenesis

PubMed Central

Hammerschmid, Florian; Blum, Helmut; Krebs, Stefan; Redeker, Julia I.; Holzapfel, Boris M.; Jansson, Volkmar; Müller, Peter E.

2016-01-01

Introduction Low frequency electromagnetic fields (LF-EMF) and simulated microgravity (SMG) have been observed to affect chondrogenesis. A controlled bioreactor system was developed to apply LF-EMF and SMG singly or combined during chondrogenic differentiation of human mesenchymal stem cells (hMSCs) in 3D culture. Material and methods An external motor gear SMG bioreactor was combined with magnetic Helmholtz coils for EMF (5 mT; 15 Hz). Pellets of hMSCs (±TGF-β3) were cultured (P5) under SMG, LF-EMF, LF-EMF/SMG and control (1 g) conditions for 3 weeks. Sections were stained with safranin-O and collagen type II. Gene expression was evaluated by microarray and real-time polymerase chain reaction analysis. Results Simulated microgravity application significantly changed gene expression; specifically, COLXA1 but also COL2A1, which represents the chondrogenic potential, were reduced (p < 0.05). Low frequency electromagnetic fields application showed no gene expression changes on a microarray basis. LF-EMF/SMG application obtained significant different expression values from cultures obtained under SMG conditions with a re-increase of COL2A1, therefore rescuing the chondrogenic potential, which had been lowered by SMG. Conclusions Simulated microgravity lowered hypertrophy but also the chondrogenic potential of hMSCs. Combined LF-EMF/SMG provided a rescue effect of the chondrogenic potential of hMSCs although no LF-EMF effect was observed under optimal conditions. The study provides new insights into how LF-EMF and SMG affect chondrogenesis of hMSCs and how they generate interdependent effects. PMID:29765449

[Key effect genes responding to nerve injury identified by gene ontology and computer pattern recognition].

PubMed

Pan, Qian; Peng, Jin; Zhou, Xue; Yang, Hao; Zhang, Wei

2012-07-01

In order to screen out important genes from large gene data of gene microarray after nerve injury, we combine gene ontology (GO) method and computer pattern recognition technology to find key genes responding to nerve injury, and then verify one of these screened-out genes. Data mining and gene ontology analysis of gene chip data GSE26350 was carried out through MATLAB software. Cd44 was selected from screened-out key gene molecular spectrum by comparing genes' different GO terms and positions on score map of principal component. Function interferences were employed to influence the normal binding of Cd44 and one of its ligands, chondroitin sulfate C (CSC), to observe neurite extension. Gene ontology analysis showed that the first genes on score map (marked by red *) mainly distributed in molecular transducer activity, receptor activity, protein binding et al molecular function GO terms. Cd44 is one of six effector protein genes, and attracted us with its function diversity. After adding different reagents into the medium to interfere the normal binding of CSC and Cd44, varying-degree remissions of CSC's inhibition on neurite extension were observed. CSC can inhibit neurite extension through binding Cd44 on the neuron membrane. This verifies that important genes in given physiological processes can be identified by gene ontology analysis of gene chip data.

Gene-centric Meta-analysis in 87,736 Individuals of European Ancestry Identifies Multiple Blood-Pressure-Related Loci

PubMed Central

Tragante, Vinicius; Barnes, Michael R.; Ganesh, Santhi K.; Lanktree, Matthew B.; Guo, Wei; Franceschini, Nora; Smith, Erin N.; Johnson, Toby; Holmes, Michael V.; Padmanabhan, Sandosh; Karczewski, Konrad J.; Almoguera, Berta; Barnard, John; Baumert, Jens; Chang, Yen-Pei Christy; Elbers, Clara C.; Farrall, Martin; Fischer, Mary E.; Gaunt, Tom R.; Gho, Johannes M.I.H.; Gieger, Christian; Goel, Anuj; Gong, Yan; Isaacs, Aaron; Kleber, Marcus E.; Leach, Irene Mateo; McDonough, Caitrin W.; Meijs, Matthijs F.L.; Melander, Olle; Nelson, Christopher P.; Nolte, Ilja M.; Pankratz, Nathan; Price, Tom S.; Shaffer, Jonathan; Shah, Sonia; Tomaszewski, Maciej; van der Most, Peter J.; Van Iperen, Erik P.A.; Vonk, Judith M.; Witkowska, Kate; Wong, Caroline O.L.; Zhang, Li; Beitelshees, Amber L.; Berenson, Gerald S.; Bhatt, Deepak L.; Brown, Morris; Burt, Amber; Cooper-DeHoff, Rhonda M.; Connell, John M.; Cruickshanks, Karen J.; Curtis, Sean P.; Davey-Smith, George; Delles, Christian; Gansevoort, Ron T.; Guo, Xiuqing; Haiqing, Shen; Hastie, Claire E.; Hofker, Marten H.; Hovingh, G. Kees; Kim, Daniel S.; Kirkland, Susan A.; Klein, Barbara E.; Klein, Ronald; Li, Yun R.; Maiwald, Steffi; Newton-Cheh, Christopher; O’Brien, Eoin T.; Onland-Moret, N. Charlotte; Palmas, Walter; Parsa, Afshin; Penninx, Brenda W.; Pettinger, Mary; Vasan, Ramachandran S.; Ranchalis, Jane E.; M Ridker, Paul; Rose, Lynda M.; Sever, Peter; Shimbo, Daichi; Steele, Laura; Stolk, Ronald P.; Thorand, Barbara; Trip, Mieke D.; van Duijn, Cornelia M.; Verschuren, W. Monique; Wijmenga, Cisca; Wyatt, Sharon; Young, J. Hunter; Zwinderman, Aeilko H.; Bezzina, Connie R.; Boerwinkle, Eric; Casas, Juan P.; Caulfield, Mark J.; Chakravarti, Aravinda; Chasman, Daniel I.; Davidson, Karina W.; Doevendans, Pieter A.; Dominiczak, Anna F.; FitzGerald, Garret A.; Gums, John G.; Fornage, Myriam; Hakonarson, Hakon; Halder, Indrani; Hillege, Hans L.; Illig, Thomas; Jarvik, Gail P.; Johnson, Julie A.; Kastelein, John J.P.; Koenig, Wolfgang; Kumari, Meena; März, Winfried; Murray, Sarah S.; O’Connell, Jeffery R.; Oldehinkel, Albertine J.; Pankow, James S.; Rader, Daniel J.; Redline, Susan; Reilly, Muredach P.; Schadt, Eric E.; Kottke-Marchant, Kandice; Snieder, Harold; Snyder, Michael; Stanton, Alice V.; Tobin, Martin D.; Uitterlinden, André G.; van der Harst, Pim; van der Schouw, Yvonne T.; Samani, Nilesh J.; Watkins, Hugh; Johnson, Andrew D.; Reiner, Alex P.; Zhu, Xiaofeng; de Bakker, Paul I.W.; Levy, Daniel; Asselbergs, Folkert W.; Munroe, Patricia B.; Keating, Brendan J.

2014-01-01

Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ∼50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10−7) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification. PMID:24560520

GenePublisher: Automated analysis of DNA microarray data.

PubMed

Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, Thomas; Friis, Carsten

2003-07-01

GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with a specification of the data. The server performs normalization, statistical analysis and visualization of the data. The results are run against databases of signal transduction pathways, metabolic pathways and promoter sequences in order to extract more information. The results of the entire analysis are summarized in report form and returned to the user.

Functional analysis of neuronal microRNAs in Caenorhabditis elegans dauer formation by combinational genetics and Neuronal miRISC immunoprecipitation.

PubMed

Than, Minh T; Kudlow, Brian A; Han, Min

2013-06-01

Identifying the physiological functions of microRNAs (miRNAs) is often challenging because miRNAs commonly impact gene expression under specific physiological conditions through complex miRNA::mRNA interaction networks and in coordination with other means of gene regulation, such as transcriptional regulation and protein degradation. Such complexity creates difficulties in dissecting miRNA functions through traditional genetic methods using individual miRNA mutations. To investigate the physiological functions of miRNAs in neurons, we combined a genetic "enhancer" approach complemented by biochemical analysis of neuronal miRNA-induced silencing complexes (miRISCs) in C. elegans. Total miRNA function can be compromised by mutating one of the two GW182 proteins (AIN-1), an important component of miRISC. We found that combining an ain-1 mutation with a mutation in unc-3, a neuronal transcription factor, resulted in an inappropriate entrance into the stress-induced, alternative larval stage known as dauer, indicating a role of miRNAs in preventing aberrant dauer formation. Analysis of this genetic interaction suggests that neuronal miRNAs perform such a role partly by regulating endogenous cyclic guanosine monophosphate (cGMP) signaling, potentially influencing two other dauer-regulating pathways. Through tissue-specific immunoprecipitations of miRISC, we identified miRNAs and their likely target mRNAs within neuronal tissue. We verified the biological relevance of several of these miRNAs and found that many miRNAs likely regulate dauer formation through multiple dauer-related targets. Further analysis of target mRNAs suggests potential miRNA involvement in various neuronal processes, but the importance of these miRNA::mRNA interactions remains unclear. Finally, we found that neuronal genes may be more highly regulated by miRNAs than intestinal genes. Overall, our study identifies miRNAs and their targets, and a physiological function of these miRNAs in neurons. It

RefEx, a reference gene expression dataset as a web tool for the functional analysis of genes.

PubMed

Ono, Hiromasa; Ogasawara, Osamu; Okubo, Kosaku; Bono, Hidemasa

2017-08-29

Gene expression data are exponentially accumulating; thus, the functional annotation of such sequence data from metadata is urgently required. However, life scientists have difficulty utilizing the available data due to its sheer magnitude and complicated access. We have developed a web tool for browsing reference gene expression pattern of mammalian tissues and cell lines measured using different methods, which should facilitate the reuse of the precious data archived in several public databases. The web tool is called Reference Expression dataset (RefEx), and RefEx allows users to search by the gene name, various types of IDs, chromosomal regions in genetic maps, gene family based on InterPro, gene expression patterns, or biological categories based on Gene Ontology. RefEx also provides information about genes with tissue-specific expression, and the relative gene expression values are shown as choropleth maps on 3D human body images from BodyParts3D. Combined with the newly incorporated Functional Annotation of Mammals (FANTOM) dataset, RefEx provides insight regarding the functional interpretation of unfamiliar genes. RefEx is publicly available at http://refex.dbcls.jp/.

Combined radiation and p53 gene therapy of malignant glioma cells.

PubMed

Badie, B; Goh, C S; Klaver, J; Herweijer, H; Boothman, D A

1999-01-01

More than half of malignant gliomas reportedly have alterations in the p53 tumor suppressor gene. Because p53 plays a key role in the cellular response to DNA-damaging agents, we investigated the role of p53 gene therapy before ionizing radiation in cultured human glioma cells containing normal or mutated p53. Three established human glioma cell lines expressing the wild-type (U87 MG, p53wt) or mutant (A172 and U373 MG, p53mut) p53 gene were transduced by recombinant adenoviral vectors bearing human p53 (Adp53) and Escherichia coli beta-galactosidase genes (AdLacZ, control virus) before radiation (0-20 Gy). Changes in p53, p21, and Bax expression were studied by Western immunoblotting, whereas cell cycle alterations and apoptosis were investigated by flow cytometry and nuclear staining. Survival was assessed by clonogenic assays. Within 48 hours of Adp53 exposure, all three cell lines demonstrated p53 expression at a viral multiplicity of infection of 100. p21, which is a p53-inducible downstream effector gene, was overexpressed, and cells were arrested in the G1 phase. Bax expression, which is thought to play a role in p53-induced apoptosis, did not change with either radiation or Adp53. Apoptosis and survival after p53 gene therapy varied. U87 MG (p53wt) cells showed minimal apoptosis after Adp53, irradiation, or combined treatments. U373 MG (p53mut) cells underwent massive apoptosis and died within 48 hours of Adp53 treatment, independent of irradiation. Surprisingly, A172 (p53mut) cells demonstrated minimal apoptosis after Adp53 exposure; however, unlike U373 MG cells, apoptosis increased with radiation dose. Survival of all three cell lines was reduced dramatically after >10 Gy. Although Adp53 transduction significantly reduced the survival of U373 MG cells and inhibited A172 growth, it had no effect on the U87 MG cell line. Transduction with AdLacZ did not affect apoptosis or cell cycle progression and only minimally affected survival in all cell lines. We

Comprehensive analysis of the codon usage patterns in the envelope glycoprotein E2 gene of the classical swine fever virus

PubMed Central

Chi, Xiaojuan; Wang, Song; Ma, Yanmei; Chen, Jilong

2017-01-01

The classical swine fever virus (CSFV), circulating worldwide, is a highly contagious virus. Since the emergence of CSFV, it has caused great economic loss in swine industry. The envelope glycoprotein E2 gene of the CSFV is an immunoprotective antigen that induces the immune system to produce neutralizing antibodies. Therefore, it is essential to study the codon usage of the E2 gene of the CSFV. In this study, 140 coding sequences of the E2 gene were analyzed. The value of effective number of codons (ENC) showed low codon usage bias in the E2 gene. Our study showed that codon usage could be described mainly by mutation pressure ENC plot analysis combined with principal component analysis (PCA) and translational selection-correlation analysis between the general average hydropathicity (Gravy) and aromaticity (Aroma), and nucleotides at the third position of codons (A3s, T3s, G3s, C3s and GC3s). Furthermore, the neutrality analysis, which explained the relationship between GC12s and GC3s, revealed that natural selection had a key role compared with mutational bias during the evolution of the E2 gene. These results lay a foundation for further research on the molecular evolution of CSFV. PMID:28880881

Comprehensive analysis of the codon usage patterns in the envelope glycoprotein E2 gene of the classical swine fever virus.

PubMed

Chen, Ye; Li, Xinxin; Chi, Xiaojuan; Wang, Song; Ma, Yanmei; Chen, Jilong

2017-01-01

The classical swine fever virus (CSFV), circulating worldwide, is a highly contagious virus. Since the emergence of CSFV, it has caused great economic loss in swine industry. The envelope glycoprotein E2 gene of the CSFV is an immunoprotective antigen that induces the immune system to produce neutralizing antibodies. Therefore, it is essential to study the codon usage of the E2 gene of the CSFV. In this study, 140 coding sequences of the E2 gene were analyzed. The value of effective number of codons (ENC) showed low codon usage bias in the E2 gene. Our study showed that codon usage could be described mainly by mutation pressure ENC plot analysis combined with principal component analysis (PCA) and translational selection-correlation analysis between the general average hydropathicity (Gravy) and aromaticity (Aroma), and nucleotides at the third position of codons (A3s, T3s, G3s, C3s and GC3s). Furthermore, the neutrality analysis, which explained the relationship between GC12s and GC3s, revealed that natural selection had a key role compared with mutational bias during the evolution of the E2 gene. These results lay a foundation for further research on the molecular evolution of CSFV.

Combined serial analysis of gene expression and transcription factor binding site prediction identifies novel-candidate-target genes of Nr2e1 in neocortex development.

PubMed

Schmouth, Jean-François; Arenillas, David; Corso-Díaz, Ximena; Xie, Yuan-Yun; Bohacec, Slavita; Banks, Kathleen G; Bonaguro, Russell J; Wong, Siaw H; Jones, Steven J M; Marra, Marco A; Simpson, Elizabeth M; Wasserman, Wyeth W

2015-07-24

Nr2e1 (nuclear receptor subfamily 2, group e, member 1) encodes a transcription factor important in neocortex development. Previous work has shown that nuclear receptors can have hundreds of target genes, and bind more than 300 co-interacting proteins. However, recognition of the critical role of Nr2e1 in neural stem cells and neocortex development is relatively recent, thus the molecular mechanisms involved for this nuclear receptor are only beginning to be understood. Serial analysis of gene expression (SAGE), has given researchers both qualitative and quantitative information pertaining to biological processes. Thus, in this work, six LongSAGE mouse libraries were generated from laser microdissected tissue samples of dorsal VZ/SVZ (ventricular zone and subventricular zone) from the telencephalon of wild-type (Wt) and Nr2e1-null embryos at the critical development ages E13.5, E15.5, and E17.5. We then used a novel approach, implementing multiple computational methods followed by biological validation to further our understanding of Nr2e1 in neocortex development. In this work, we have generated a list of 1279 genes that are differentially expressed in response to altered Nr2e1 expression during in vivo neocortex development. We have refined this list to 64 candidate direct-targets of NR2E1. Our data suggested distinct roles for Nr2e1 during different neocortex developmental stages. Most importantly, our results suggest a possible novel pathway by which Nr2e1 regulates neurogenesis, which includes Lhx2 as one of the candidate direct-target genes, and SOX9 as a co-interactor. In conclusion, we have provided new candidate interacting partners and numerous well-developed testable hypotheses for understanding the pathways by which Nr2e1 functions to regulate neocortex development.

Rare Frequency of Mutations in Pituitary Transcription Factor Genes in Combined Pituitary Hormone or Isolated Growth Hormone Deficiencies in Korea.

PubMed

Choi, Jin Ho; Jung, Chang Woo; Kang, Eungu; Kim, Yoon Myung; Heo, Sun Hee; Lee, Beom Hee; Kim, Gu Hwan; Yoo, Han Wook

2017-05-01

Congenital hypopituitarism is caused by mutations in pituitary transcription factors involved in the development of the hypothalamic-pituitary axis. Mutation frequencies of genes involved in congenital hypopituitarism are extremely low and vary substantially between ethnicities. This study was undertaken to compare the clinical, endocrinological, and radiological features of patients with an isolated growth hormone deficiency (IGHD) or combined pituitary hormone deficiency (CPHD). This study included 27 patients with sporadic IGHD and CPHD. A mutation analysis of the POU1F1, PROP1, LHX3, LHX4, and HESX1 genes was performed using genomic DNA from peripheral blood leukocytes. IGHD and CPHD were observed in 4 and 23 patients, respectively. Mean age at diagnosis was 8.28±7.25 years for IGHD and 13.48±10.46 years for CPHD (p=0.37). Serum insulin-like growth factor-1 and peak growth hormone (GH) levels following GH stimulation tests were significantly lower in patients with CPHD than in those with IGHD (p<0.05). Sellar MRI findings revealed structural abnormalities in 3 patients with IGHD (75%) and 21 patients with CPHD (91.3%) (p=0.62). A mutation analysis identified homozygous p.R109Q mutations in HESX1 in a patient with CPHD. Patients with CPHD had more severe GHD than those with IGHD. The frequency of defects in the genes encoding pituitary transcription factors was extremely low in Korean patients with congenital hypopituitarism. Environmental factors and the impact of other causative genes may contribute to this clinical phenotype. © Copyright: Yonsei University College of Medicine 2017

Rare Frequency of Mutations in Pituitary Transcription Factor Genes in Combined Pituitary Hormone or Isolated Growth Hormone Deficiencies in Korea

PubMed Central

Choi, Jin-Ho; Jung, Chang-Woo; Kang, Eungu; Kim, Yoon-Myung; Heo, Sun Hee; Lee, Beom Hee; Kim, Gu-Hwan

2017-01-01

Purpose Congenital hypopituitarism is caused by mutations in pituitary transcription factors involved in the development of the hypothalamic-pituitary axis. Mutation frequencies of genes involved in congenital hypopituitarism are extremely low and vary substantially between ethnicities. This study was undertaken to compare the clinical, endocrinological, and radiological features of patients with an isolated growth hormone deficiency (IGHD) or combined pituitary hormone deficiency (CPHD). Materials and Methods This study included 27 patients with sporadic IGHD and CPHD. A mutation analysis of the POU1F1, PROP1, LHX3, LHX4, and HESX1 genes was performed using genomic DNA from peripheral blood leukocytes. Results IGHD and CPHD were observed in 4 and 23 patients, respectively. Mean age at diagnosis was 8.28±7.25 years for IGHD and 13.48±10.46 years for CPHD (p=0.37). Serum insulin-like growth factor-1 and peak growth hormone (GH) levels following GH stimulation tests were significantly lower in patients with CPHD than in those with IGHD (p<0.05). Sellar MRI findings revealed structural abnormalities in 3 patients with IGHD (75%) and 21 patients with CPHD (91.3%) (p=0.62). A mutation analysis identified homozygous p.R109Q mutations in HESX1 in a patient with CPHD. Patients with CPHD had more severe GHD than those with IGHD. Conclusion The frequency of defects in the genes encoding pituitary transcription factors was extremely low in Korean patients with congenital hypopituitarism. Environmental factors and the impact of other causative genes may contribute to this clinical phenotype. PMID:28332357

Gene expression analysis of a Helicobacter pylori-infected and high-salt diet-treated mouse gastric tumor model: identification of CD177 as a novel prognostic factor in patients with gastric cancer