dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

PubMed Central

Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

2009-01-01

Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156

Comparative genome analysis in the integrated microbial genomes (IMG) system.

PubMed

Markowitz, Victor M; Kyrpides, Nikos C

2007-01-01

Comparative genome analysis is critical for the effective exploration of a rapidly growing number of complete and draft sequences for microbial genomes. The Integrated Microbial Genomes (IMG) system (img.jgi.doe.gov) has been developed as a community resource that provides support for comparative analysis of microbial genomes in an integrated context. IMG allows users to navigate the multidimensional microbial genome data space and focus their analysis on a subset of genes, genomes, and functions of interest. IMG provides graphical viewers, summaries, and occurrence profile tools for comparing genes, pathways, and functions (terms) across specific genomes. Genes can be further examined using gene neighborhoods and compared with sequence alignment tools.

Exploring internal features of 16S rRNA gene for identification of clinically relevant species of the genus Streptococcus

PubMed Central

2011-01-01

Background Streptococcus is an economically important genus as a number of species belonging to this genus are human and animal pathogens. The genus has been divided into different groups based on 16S rRNA gene sequence similarity. The variability observed among the members of these groups is low and it is difficult to distinguish them. The present study was taken up to explore 16S rRNA gene sequence to develop methods that can be used for preliminary identification and can supplement the existing methods for identification of clinically-relevant isolates of the genus Streptococcus. Methods 16S rRNA gene sequences belonging to the isolates of S. dysgalactiae, S. equi, S. pyogenes, S. agalactiae, S. bovis, S. gallolyticus, S. mutans, S. sobrinus, S. mitis, S. pneumoniae, S. thermophilus and S. anginosus were analyzed with the purpose to define genetic variability within each species to generate a phylogenetic framework, to identify species-specific signatures and in-silico restriction enzyme analysis. Results The framework based analysis was used to segregate Streptococcus spp. previously identified upto genus level. This segregation was validated using species-specific signatures and in-silico restriction enzyme analysis. 43 uncharacterized Streptococcus spp. could be identified using this approach. Conclusions The markers generated exploring 16S rRNA gene sequences provided useful tool that can be further used for identification of different species of the genus Streptococcus. PMID:21702978

Computational exploration of cis-regulatory modules in rhythmic expression data using the "Exploration of Distinctive CREs and CRMs" (EDCC) and "CRM Network Generator" (CNG) programs.

PubMed

Bekiaris, Pavlos Stephanos; Tekath, Tobias; Staiger, Dorothee; Danisman, Selahattin

2018-01-01

Understanding the effect of cis-regulatory elements (CRE) and clusters of CREs, which are called cis-regulatory modules (CRM), in eukaryotic gene expression is a challenge of computational biology. We developed two programs that allow simple, fast and reliable analysis of candidate CREs and CRMs that may affect specific gene expression and that determine positional features between individual CREs within a CRM. The first program, "Exploration of Distinctive CREs and CRMs" (EDCC), correlates candidate CREs and CRMs with specific gene expression patterns. For pairs of CREs, EDCC also determines positional preferences of the single CREs in relation to each other and to the transcriptional start site. The second program, "CRM Network Generator" (CNG), prioritizes these positional preferences using a neural network and thus allows unbiased rating of the positional preferences that were determined by EDCC. We tested these programs with data from a microarray study of circadian gene expression in Arabidopsis thaliana. Analyzing more than 1.5 million pairwise CRE combinations, we found 22 candidate combinations, of which several contained known clock promoter elements together with elements that had not been identified as relevant to circadian gene expression before. CNG analysis further identified positional preferences of these CRE pairs, hinting at positional information that may be relevant for circadian gene expression. Future wet lab experiments will have to determine which of these combinations confer daytime specific circadian gene expression.

Computational exploration of cis-regulatory modules in rhythmic expression data using the “Exploration of Distinctive CREs and CRMs” (EDCC) and “CRM Network Generator” (CNG) programs

PubMed Central

Staiger, Dorothee

2018-01-01

Understanding the effect of cis-regulatory elements (CRE) and clusters of CREs, which are called cis-regulatory modules (CRM), in eukaryotic gene expression is a challenge of computational biology. We developed two programs that allow simple, fast and reliable analysis of candidate CREs and CRMs that may affect specific gene expression and that determine positional features between individual CREs within a CRM. The first program, “Exploration of Distinctive CREs and CRMs” (EDCC), correlates candidate CREs and CRMs with specific gene expression patterns. For pairs of CREs, EDCC also determines positional preferences of the single CREs in relation to each other and to the transcriptional start site. The second program, “CRM Network Generator” (CNG), prioritizes these positional preferences using a neural network and thus allows unbiased rating of the positional preferences that were determined by EDCC. We tested these programs with data from a microarray study of circadian gene expression in Arabidopsis thaliana. Analyzing more than 1.5 million pairwise CRE combinations, we found 22 candidate combinations, of which several contained known clock promoter elements together with elements that had not been identified as relevant to circadian gene expression before. CNG analysis further identified positional preferences of these CRE pairs, hinting at positional information that may be relevant for circadian gene expression. Future wet lab experiments will have to determine which of these combinations confer daytime specific circadian gene expression. PMID:29298348

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.

ACE I/D Gene Polymorphism Can't Predict the Steroid Responsiveness in Asian Children with Idiopathic Nephrotic Syndrome: A Meta-Analysis

PubMed Central

Su, Li-Na; Lei, Feng-Ying; Huang, Wei-Fang; Zhao, Yan-Jun

2011-01-01

Background The results from the published studies on the association between angiotensin-converting enzyme (ACE) insertion/deletion (I/D) gene polymorphism and the treatment response to steroid in Asian children with idiopathic nephrotic syndrome (INS) is still conflicting. This meta-analysis was performed to evaluate the relation between ACE I/D gene polymorphism and treatment response to steroid in Asian children and to explore whether ACE D allele or DD genotype could become a predictive marker for steroid responsiveness. Methodology/Principal Findings Association studies were identified from the databases of PubMed, Embase, Cochrane Library and CBM-disc (China Biological Medicine Database) as of September 1, 2010, and eligible investigations were synthesized using meta-analysis method. Five investigations were identified for the analysis of association between ACE I/D gene polymorphism and steroid-resistant nephrotic syndrome (SRNS) risk in Asian children and seven studies were included to explore the relationship between ACE I/D gene polymorphism and steroid-sensitive nephrotic syndrome (SSNS) susceptibility. Five investigations were recruited to explore the difference of ACE I/D gene distribution between SRNS and SSNS. There was no a markedly association between D allele or DD genotype and SRNS susceptibility or SSNS risk, and the gene distribution differences of ACE between SRNS and SSNS were not statistically significant. II genotype might play a positive role against SRNS onset but not for SSNS (OR = 0.51, P = 0.02; OR = 0.95, P = 0.85; respectively), however, the result for the association of II genotype with SRNS risk was not stable. Conclusions/Significance Our results indicate that D allele or DD homozygous can't become a significant genetic molecular marker to predict the treatment response to steroid in Asian children with INS. PMID:21611163

Genome-wide analysis of miRNAs in the ovaries of Jining Grey and Laiwu Black goats to explore the regulation of fecundity.

PubMed

Miao, Xiangyang; Luo, Qingmiao; Zhao, Huijing; Qin, Xiaoyu

2016-11-29

Goat fecundity is important for agriculture and varies depending on the genetic background of the goat. Two excellent domestic breeds in China, the Jining Grey and Laiwu Black goats, have different fecundity and prolificacies. To explore the potential miRNAs that regulate the expression of the genes involved in these prolific differences and to potentially discover new miRNAs, we performed a genome-wide analysis of the miRNAs in the ovaries from these two goats using RNA-Seq technology. Thirty miRNAs were differentially expressed between the Jining Grey and Laiwu Black goats. Gene Ontology and KEGG pathway analyses revealed that the target genes of the differentially expressed miRNAs were significantly enriched in several biological processes and pathways. A protein-protein interaction analysis indicated that the miRNAs and their target genes were related to the reproduction complex regulation network. The differential miRNA expression profiles found in the ovaries between the two distinctive breeds of goats studied here provide a unique resource for addressing fecundity differences in goats.

Analysis of vascular endothelial dysfunction genes and related pathways in obesity through systematic bioinformatics.

PubMed

Zhang, Hui; Wang, Jing; Sun, Ling; Xu, Qiuqin; Hou, Miao; Ding, Yueyue; Huang, Jie; Chen, Ye; Cao, Lei; Zhang, Jianmin; Qian, Weiguo; Lv, Haitao

2015-01-01

Obesity has become an increasingly serious health problem and popular research topic. It is associated with many diseases, especially cardiovascular disease (CVD)-related endothelial dysfunction. This study analyzed genes related to endothelial dysfunction and obesity and then summarized their most significant signaling pathways. Genes related to vascular endothelial dysfunction and obesity were extracted from a PubMed database, and analyzed by STRING, DAVID, and Gene-Go Meta-Core software. 142 genes associated with obesity were found to play a role in endothelial dysfunction in PubMed. A significant pathway (Angiotensin system maturation in protein folding and maturation) associated with obesity and endothelial dysfunction was explored. The genes and the pathway explored may play an important role in obesity. Further studies about preventing vascular endothelial dysfunction obesity should be conducted through targeting these loci and pathways.

Reverse genetics: Its origins and prospects

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

Berg, P.

1991-04-01

The nucleotide sequence of a gene and its flanking segments alone will not tell us how its expression is regulated during development and differentiation, or in response to environmental changes. To comprehend the physiological significance of the molecular details requires biological analysis. Recombinant DNA techniques provide a powerful experimental approach. A strategy termed reverse genetics' utilizes the analysis of the activities of mutant and normal genes and experimentally constructed mutants to explore the relationship between gene structure and function thereby helping elucidate the relationship between genotype and phenotype.

IMG-ABC. A knowledge base to fuel discovery of biosynthetic gene clusters and novel secondary metabolites

DOE PAGES

Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; ...

2015-07-14

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG’s comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve asmore » the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC’s focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in lphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG’s extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.« less

WHAM!: a web-based visualization suite for user-defined analysis of metagenomic shotgun sequencing data.

PubMed

Devlin, Joseph C; Battaglia, Thomas; Blaser, Martin J; Ruggles, Kelly V

2018-06-25

Exploration of large data sets, such as shotgun metagenomic sequence or expression data, by biomedical experts and medical professionals remains as a major bottleneck in the scientific discovery process. Although tools for this purpose exist for 16S ribosomal RNA sequencing analysis, there is a growing but still insufficient number of user-friendly interactive visualization workflows for easy data exploration and figure generation. The development of such platforms for this purpose is necessary to accelerate and streamline microbiome laboratory research. We developed the Workflow Hub for Automated Metagenomic Exploration (WHAM!) as a web-based interactive tool capable of user-directed data visualization and statistical analysis of annotated shotgun metagenomic and metatranscriptomic data sets. WHAM! includes exploratory and hypothesis-based gene and taxa search modules for visualizing differences in microbial taxa and gene family expression across experimental groups, and for creating publication quality figures without the need for command line interface or in-house bioinformatics. WHAM! is an interactive and customizable tool for downstream metagenomic and metatranscriptomic analysis providing a user-friendly interface allowing for easy data exploration by microbiome and ecological experts to facilitate discovery in multi-dimensional and large-scale data sets.

Systematic analysis of molecular mechanisms for HCC metastasis via text mining approach.

PubMed

Zhen, Cheng; Zhu, Caizhong; Chen, Haoyang; Xiong, Yiru; Tan, Junyuan; Chen, Dong; Li, Jin

2017-02-21

To systematically explore the molecular mechanism for hepatocellular carcinoma (HCC) metastasis and identify regulatory genes with text mining methods. Genes with highest frequencies and significant pathways related to HCC metastasis were listed. A handful of proteins such as EGFR, MDM2, TP53 and APP, were identified as hub nodes in PPI (protein-protein interaction) network. Compared with unique genes for HBV-HCCs, genes particular to HCV-HCCs were less, but may participate in more extensive signaling processes. VEGFA, PI3KCA, MAPK1, MMP9 and other genes may play important roles in multiple phenotypes of metastasis. Genes in abstracts of HCC-metastasis literatures were identified. Word frequency analysis, KEGG pathway and PPI network analysis were performed. Then co-occurrence analysis between genes and metastasis-related phenotypes were carried out. Text mining is effective for revealing potential regulators or pathways, but the purpose of it should be specific, and the combination of various methods will be more useful.

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

PubMed Central

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

2013-01-01

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

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.

Network-based co-expression analysis for exploring the potential diagnostic biomarkers of metastatic melanoma.

PubMed

Wang, Li-Xin; Li, Yang; Chen, Guan-Zhi

2018-01-01

Metastatic melanoma is an aggressive skin cancer and is one of the global malignancies with high mortality and morbidity. It is essential to identify and verify diagnostic biomarkers of early metastatic melanoma. Previous studies have systematically assessed protein biomarkers and mRNA-based expression characteristics. However, molecular markers for the early diagnosis of metastatic melanoma have not been identified. To explore potential regulatory targets, we have analyzed the gene microarray expression profiles of malignant melanoma samples by co-expression analysis based on the network approach. The differentially expressed genes (DEGs) were screened by the EdgeR package of R software. A weighted gene co-expression network analysis (WGCNA) was used for the identification of DEGs in the special gene modules and hub genes. Subsequently, a protein-protein interaction network was constructed to extract hub genes associated with gene modules. Finally, twenty-four important hub genes (RASGRP2, IKZF1, CXCR5, LTB, BLK, LINGO3, CCR6, P2RY10, RHOH, JUP, KRT14, PLA2G3, SPRR1A, KRT78, SFN, CLDN4, IL1RN, PKP3, CBLC, KRT16, TMEM79, KLK8, LYPD3 and LYPD5) were treated as valuable factors involved in the immune response and tumor cell development in tumorigenesis. In addition, a transcriptional regulatory network was constructed for these specific modules or hub genes, and a few core transcriptional regulators were found to be mostly associated with our hub genes, including GATA1, STAT1, SP1, and PSG1. In summary, our findings enhance our understanding of the biological process of malignant melanoma metastasis, enabling us to identify specific genes to use for diagnostic and prognostic markers and possibly for targeted therapy.

A Canonical Correlation Analysis of AIDS Restriction Genes and Metabolic Pathways Identifies Purine Metabolism as a Key Cooperator.

PubMed

Ye, Hanhui; Yuan, Jinjin; Wang, Zhengwu; Huang, Aiqiong; Liu, Xiaolong; Han, Xiao; Chen, Yahong

2016-01-01

Human immunodeficiency virus causes a severe disease in humans, referred to as immune deficiency syndrome. Studies on the interaction between host genetic factors and the virus have revealed dozens of genes that impact diverse processes in the AIDS disease. To resolve more genetic factors related to AIDS, a canonical correlation analysis was used to determine the correlation between AIDS restriction and metabolic pathway gene expression. The results show that HIV-1 postentry cellular viral cofactors from AIDS restriction genes are coexpressed in human transcriptome microarray datasets. Further, the purine metabolism pathway comprises novel host factors that are coexpressed with AIDS restriction genes. Using a canonical correlation analysis for expression is a reliable approach to exploring the mechanism underlying AIDS.

Comprehensive analysis of the flowering genes in Chinese cabbage and examination of evolutionary pattern of CO-like genes in plant kingdom

NASA Astrophysics Data System (ADS)

Song, Xiaoming; Duan, Weike; Huang, Zhinan; Liu, Gaofeng; Wu, Peng; Liu, Tongkun; Li, Ying; Hou, Xilin

2015-09-01

In plants, flowering is the most important transition from vegetative to reproductive growth. The flowering patterns of monocots and eudicots are distinctly different, but few studies have described the evolutionary patterns of the flowering genes in them. In this study, we analysed the evolutionary pattern, duplication and expression level of these genes. The main results were as follows: (i) characterization of flowering genes in monocots and eudicots, including the identification of family-specific, orthologous and collinear genes; (ii) full characterization of CONSTANS-like genes in Brassica rapa (BraCOL genes), the key flowering genes; (iii) exploration of the evolution of COL genes in plant kingdom and construction of the evolutionary pattern of COL genes; (iv) comparative analysis of CO and FT genes between Brassicaceae and Grass, which identified several family-specific amino acids, and revealed that CO and FT protein structures were similar in B. rapa and Arabidopsis but different in rice; and (v) expression analysis of photoperiod pathway-related genes in B. rapa under different photoperiod treatments by RT-qPCR. This analysis will provide resources for understanding the flowering mechanisms and evolutionary pattern of COL genes. In addition, this genome-wide comparative study of COL genes may also provide clues for evolution of other flowering genes.

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

PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space.

PubMed

Ma, Chihua; Luciani, Timothy; Terebus, Anna; Liang, Jie; Marai, G Elisabeta

2017-02-15

Visualizing the complex probability landscape of stochastic gene regulatory networks can further biologists' understanding of phenotypic behavior associated with specific genes. We present PRODIGEN (PRObability DIstribution of GEne Networks), a web-based visual analysis tool for the systematic exploration of probability distributions over simulation time and state space in such networks. PRODIGEN was designed in collaboration with bioinformaticians who research stochastic gene networks. The analysis tool combines in a novel way existing, expanded, and new visual encodings to capture the time-varying characteristics of probability distributions: spaghetti plots over one dimensional projection, heatmaps of distributions over 2D projections, enhanced with overlaid time curves to display temporal changes, and novel individual glyphs of state information corresponding to particular peaks. We demonstrate the effectiveness of the tool through two case studies on the computed probabilistic landscape of a gene regulatory network and of a toggle-switch network. Domain expert feedback indicates that our visual approach can help biologists: 1) visualize probabilities of stable states, 2) explore the temporal probability distributions, and 3) discover small peaks in the probability landscape that have potential relation to specific diseases.

Transcriptomic analysis in the developing zebrafish embryo after compound exposure: Individual gene expression and pathway regulation

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

Hermsen, Sanne A.B., E-mail: Sanne.Hermsen@rivm.nl; Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht; Institute for Risk Assessment Sciences

2013-10-01

The zebrafish embryotoxicity test is a promising alternative assay for developmental toxicity. Classically, morphological assessment of the embryos is applied to evaluate the effects of compound exposure. However, by applying differential gene expression analysis the sensitivity and predictability of the test may be increased. For defining gene expression signatures of developmental toxicity, we explored the possibility of using gene expression signatures of compound exposures based on commonly expressed individual genes as well as based on regulated gene pathways. Four developmental toxic compounds were tested in concentration-response design, caffeine, carbamazepine, retinoic acid and valproic acid, and two non-embryotoxic compounds, D-mannitol andmore » saccharin, were included. With transcriptomic analyses we were able to identify commonly expressed genes, which were mostly development related, after exposure to the embryotoxicants. We also identified gene pathways regulated by the embryotoxicants, suggestive of their modes of action. Furthermore, whereas pathways may be regulated by all compounds, individual gene expression within these pathways can differ for each compound. Overall, the present study suggests that the use of individual gene expression signatures as well as pathway regulation may be useful starting points for defining gene biomarkers for predicting embryotoxicity. - Highlights: • The zebrafish embryotoxicity test in combination with transcriptomics was used. • We explored two approaches of defining gene biomarkers for developmental toxicity. • Four compounds in concentration-response design were tested. • We identified commonly expressed individual genes as well as regulated gene pathways. • Both approaches seem suitable starting points for defining gene biomarkers.« less

DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures.

PubMed

Mazandu, Gaston K; Mulder, Nicola J

2013-09-25

The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis.

Multiple correlation analyses revealed complex relationship between DNA methylation and mRNA expression in human peripheral blood mononuclear cells.

PubMed

Xie, Fang-Fei; Deng, Fei-Yan; Wu, Long-Fei; Mo, Xing-Bo; Zhu, Hong; Wu, Jian; Guo, Yu-Fan; Zeng, Ke-Qin; Wang, Ming-Jun; Zhu, Xiao-Wei; Xia, Wei; Wang, Lan; He, Pei; Bing, Peng-Fei; Lu, Xin; Zhang, Yong-Hong; Lei, Shu-Feng

2018-01-01

DNA methylation is an important regulator on the mRNA expression. However, a genome-wide correlation pattern between DNA methylation and mRNA expression in human peripheral blood mononuclear cells (PBMCs) is largely unknown. The comprehensive relationship between mRNA and DNA methylation was explored by using four types of correlation analyses and a genome-wide methylation-mRNA expression quantitative trait locus (eQTL) analysis in PBMCs in 46 unrelated female subjects. An enrichment analysis was performed to detect biological function for the detected genes. Single pair correlation coefficient (r T1 ) between methylation level and mRNA is moderate (-0.63-0.62) in intensity, and the negative and positive correlations are nearly equal in quantity. Correlation analysis on each gene (T4) found 60.1% genes showed correlations between mRNA and gene-based methylation at P < 0.05 and more than 5.96% genes presented very strong correlation (R T4  > 0.8). Methylation sites have regulation effects on mRNA expression in eQTL analysis, with more often observations in region of transcription start site (TSS). The genes under significant methylation regulation both in correlation analysis and eQTL analysis tend to cluster to the categories (e.g., transcription, translation, regulation of transcription) that are essential for maintaining the basic life activities of cells. Our findings indicated that DNA methylation has predictive regulation effect on mRNA with a very complex pattern in PBMCs. The results increased our understanding on correlation of methylation and mRNA and also provided useful clues for future epigenetic studies in exploring biological and disease-related regulatory mechanisms in PBMC.

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

PubMed

Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

2017-04-27

Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes.

PubMed

Hadjithomas, Michalis; Chen, I-Min A; Chu, Ken; Huang, Jinghua; Ratner, Anna; Palaniappan, Krishna; Andersen, Evan; Markowitz, Victor; Kyrpides, Nikos C; Ivanova, Natalia N

2017-01-04

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic gene clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Omics Dashboard for interactive exploration of gene-expression data.

PubMed

Paley, Suzanne; Parker, Karen; Spaulding, Aaron; Tomb, Jean-Francois; O'Maille, Paul; Karp, Peter D

2017-12-01

The Omics Dashboard is a software tool for interactive exploration and analysis of gene-expression datasets. The Omics Dashboard is organized as a hierarchy of cellular systems. At the highest level of the hierarchy the Dashboard contains graphical panels depicting systems such as biosynthesis, energy metabolism, regulation and central dogma. Each of those panels contains a series of X-Y plots depicting expression levels of subsystems of that panel, e.g. subsystems within the central dogma panel include transcription, translation and protein maturation and folding. The Dashboard presents a visual read-out of the expression status of cellular systems to facilitate a rapid top-down user survey of how all cellular systems are responding to a given stimulus, and to enable the user to quickly view the responses of genes within specific systems of interest. Although the Dashboard is complementary to traditional statistical methods for analysis of gene-expression data, we show how it can detect changes in gene expression that statistical techniques may overlook. We present the capabilities of the Dashboard using two case studies: the analysis of lipid production for the marine alga Thalassiosira pseudonana, and an investigation of a shift from anaerobic to aerobic growth for the bacterium Escherichia coli. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Omics Dashboard for interactive exploration of gene-expression data

PubMed Central

Paley, Suzanne; Parker, Karen; Spaulding, Aaron; Tomb, Jean-Francois; O’Maille, Paul

2017-01-01

Abstract The Omics Dashboard is a software tool for interactive exploration and analysis of gene-expression datasets. The Omics Dashboard is organized as a hierarchy of cellular systems. At the highest level of the hierarchy the Dashboard contains graphical panels depicting systems such as biosynthesis, energy metabolism, regulation and central dogma. Each of those panels contains a series of X–Y plots depicting expression levels of subsystems of that panel, e.g. subsystems within the central dogma panel include transcription, translation and protein maturation and folding. The Dashboard presents a visual read-out of the expression status of cellular systems to facilitate a rapid top-down user survey of how all cellular systems are responding to a given stimulus, and to enable the user to quickly view the responses of genes within specific systems of interest. Although the Dashboard is complementary to traditional statistical methods for analysis of gene-expression data, we show how it can detect changes in gene expression that statistical techniques may overlook. We present the capabilities of the Dashboard using two case studies: the analysis of lipid production for the marine alga Thalassiosira pseudonana, and an investigation of a shift from anaerobic to aerobic growth for the bacterium Escherichia coli. PMID:29040755

Transcriptome profile and unique genetic evolution of positively selected genes in yak lungs.

PubMed

Lan, DaoLiang; Xiong, XianRong; Ji, WenHui; Li, Jian; Mipam, Tserang-Donko; Ai, Yi; Chai, ZhiXin

2018-04-01

The yak (Bos grunniens), which is a unique bovine breed that is distributed mainly in the Qinghai-Tibetan Plateau, is considered a good model for studying plateau adaptability in mammals. The lungs are important functional organs that enable animals to adapt to their external environment. However, the genetic mechanism underlying the adaptability of yak lungs to harsh plateau environments remains unknown. To explore the unique evolutionary process and genetic mechanism of yak adaptation to plateau environments, we performed transcriptome sequencing of yak and cattle (Bos taurus) lungs using RNA-Seq technology and a subsequent comparison analysis to identify the positively selected genes in the yak. After deep sequencing, a normal transcriptome profile of yak lung that containing a total of 16,815 expressed genes was obtained, and the characteristics of yak lungs transcriptome was described by functional analysis. Furthermore, Ka/Ks comparison statistics result showed that 39 strong positively selected genes are identified from yak lungs. Further GO and KEGG analysis was conducted for the functional annotation of these genes. The results of this study provide valuable data for further explorations of the unique evolutionary process of high-altitude hypoxia adaptation in yaks in the Tibetan Plateau and the genetic mechanism at the molecular level.

Interaction of methylation-related genetic variants with circulating fatty acids on plasma lipids: a meta-analysis of 7 studies & methylation analysis of 3 studies in the Cohorts for Heart & Aging Research

USDA-ARS?s Scientific Manuscript database

Background: DNA methylation is influenced by diet and single nucleotide polymorphisms (SNPs), and methylation modulates gene expression. Objective: We aimed to explore whether the gene-by-diet interactions on blood lipids act through DNA methylation. Design: We selected 7 SNPs on the basis of predic...

[FANCA gene mutation analysis in Fanconi anemia patients].

PubMed

Chen, Fei; Peng, Guang-Jie; Zhang, Kejian; Hu, Qun; Zhang, Liu-Qing; Liu, Ai-Guo

2005-10-01

To screen the FANCA gene mutation and explore the FANCA protein function in Fanconi anemia (FA) patients. FANCA protein expression and its interaction with FANCF were analyzed using Western blot and immunoprecipitation in 3 cases of FA-A. Genomic DNA was used for MLPA analysis followed by sequencing. FANCA protein was undetectable and FANCA and FANCF protein interaction was impaired in these 3 cases of FA-A. Each case of FA-A contained biallelic pathogenic mutations in FANCA gene. No functional FANCA protein was found in these 3 cases of FA-A, and intragenic deletion, frame shift and splice site mutation were the major pathogenic mutations found in FANCA gene.

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes

DOE PAGES

Hadjithomas, Michalis; Chen, I-Min A.; Chu, Ken; ...

2016-11-29

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic genemore » clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery.« less

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes

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

Hadjithomas, Michalis; Chen, I-Min A.; Chu, Ken

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic genemore » clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery.« less

Partial least squares based gene expression analysis in estrogen receptor positive and negative breast tumors.

PubMed

Ma, W; Zhang, T-F; Lu, P; Lu, S H

2014-01-01

Breast cancer is categorized into two broad groups: estrogen receptor positive (ER+) and ER negative (ER-) groups. Previous study proposed that under trastuzumab-based neoadjuvant chemotherapy, tumor initiating cell (TIC) featured ER- tumors response better than ER+ tumors. Exploration of the molecular difference of these two groups may help developing new therapeutic strategies, especially for ER- patients. With gene expression profile from the Gene Expression Omnibus (GEO) database, we performed partial least squares (PLS) based analysis, which is more sensitive than common variance/regression analysis. We acquired 512 differentially expressed genes. Four pathways were found to be enriched with differentially expressed genes, involving immune system, metabolism and genetic information processing process. Network analysis identified five hub genes with degrees higher than 10, including APP, ESR1, SMAD3, HDAC2, and PRKAA1. Our findings provide new understanding for the molecular difference between TIC featured ER- and ER+ breast tumors with the hope offer supports for therapeutic studies.

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.

Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

USDA-ARS?s Scientific Manuscript database

The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

Identification and Characterization of the MADS-Box Genes and Their Contribution to Flower Organ in Carnation (Dianthus caryophyllus L.)

PubMed Central

Zhang, Xiaoni; Wang, Qijian; Yang, Shaozong; Lin, Shengnan; Bao, Manzhu; Wu, Quanshu; Wang, Caiyun; Fu, Xiaopeng

2018-01-01

Dianthus is a large genus containing many species with high ornamental economic value. Extensive breeding strategies permitted an exploration of an improvement in the quality of cultivated carnation, particularly in flowers. However, little is known on the molecular mechanisms of flower development in carnation. Here, we report the identification and description of MADS-box genes in carnation (DcaMADS) with a focus on those involved in flower development and organ identity determination. In this study, 39 MADS-box genes were identified from the carnation genome and transcriptome by the phylogenetic analysis. These genes were categorized into four subgroups (30 MIKCc, two MIKC*, two Mα, and five Mγ). The MADS-box domain, gene structure, and conserved motif compositions of the carnation MADS genes were analysed. Meanwhile, the expression of DcaMADS genes were significantly different in stems, leaves, and flower buds. Further studies were carried out for exploring the expression of DcaMADS genes in individual flower organs, and some crucial DcaMADS genes correlated with their putative function were validated. Finally, a new expression pattern of DcaMADS genes in flower organs of carnation was provided: sepal (three class E genes and two class A genes), petal (two class B genes, two class E genes, and one SHORT VEGETATIVE PHASE (SVP)), stamen (two class B genes, two class E genes, and two class C), styles (two class E genes and two class C), and ovary (two class E genes, two class C, one AGAMOUS-LIKE 6 (AGL6), one SEEDSTICK (STK), one B sister, one SVP, and one Mα). This result proposes a model in floral organ identity of carnation and it may be helpful to further explore the molecular mechanism of flower organ identity in carnation. PMID:29617274

Identification and Characterization of the MADS-Box Genes and Their Contribution to Flower Organ in Carnation (Dianthus caryophyllus L.).

PubMed

Zhang, Xiaoni; Wang, Qijian; Yang, Shaozong; Lin, Shengnan; Bao, Manzhu; Bendahmane, Mohammed; Wu, Quanshu; Wang, Caiyun; Fu, Xiaopeng

2018-04-04

Dianthus is a large genus containing many species with high ornamental economic value. Extensive breeding strategies permitted an exploration of an improvement in the quality of cultivated carnation, particularly in flowers. However, little is known on the molecular mechanisms of flower development in carnation. Here, we report the identification and description of MADS-box genes in carnation ( DcaMADS ) with a focus on those involved in flower development and organ identity determination. In this study, 39 MADS-box genes were identified from the carnation genome and transcriptome by the phylogenetic analysis. These genes were categorized into four subgroups (30 MIKC c , two MIKC*, two Mα, and five Mγ). The MADS-box domain, gene structure, and conserved motif compositions of the carnation MADS genes were analysed. Meanwhile, the expression of DcaMADS genes were significantly different in stems, leaves, and flower buds. Further studies were carried out for exploring the expression of DcaMADS genes in individual flower organs, and some crucial DcaMADS genes correlated with their putative function were validated. Finally, a new expression pattern of DcaMADS genes in flower organs of carnation was provided: sepal (three class E genes and two class A genes), petal (two class B genes, two class E genes, and one SHORT VEGETATIVE PHASE ( SVP )), stamen (two class B genes, two class E genes, and two class C), styles (two class E genes and two class C), and ovary (two class E genes, two class C, one AGAMOUS-LIKE 6 ( AGL6 ), one SEEDSTICK ( STK ), one B sister , one SVP , and one Mα ). This result proposes a model in floral organ identity of carnation and it may be helpful to further explore the molecular mechanism of flower organ identity in carnation.

Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis

PubMed Central

Yang, Fang; Wang, Yumei

2018-01-01

Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis. PMID:29805480

Exploring candidate biomarkers for lung and prostate cancers using gene expression and flux variability analysis.

PubMed

Asgari, Yazdan; Khosravi, Pegah; Zabihinpour, Zahra; Habibi, Mahnaz

2018-02-19

Genome-scale metabolic models have provided valuable resources for exploring changes in metabolism under normal and cancer conditions. However, metabolism itself is strongly linked to gene expression, so integration of gene expression data into metabolic models might improve the detection of genes involved in the control of tumor progression. Herein, we considered gene expression data as extra constraints to enhance the predictive powers of metabolic models. We reconstructed genome-scale metabolic models for lung and prostate, under normal and cancer conditions to detect the major genes associated with critical subsystems during tumor development. Furthermore, we utilized gene expression data in combination with an information theory-based approach to reconstruct co-expression networks of the human lung and prostate in both cohorts. Our results revealed 19 genes as candidate biomarkers for lung and prostate cancer cells. This study also revealed that the development of a complementary approach (integration of gene expression and metabolic profiles) could lead to proposing novel biomarkers and suggesting renovated cancer treatment strategies which have not been possible to detect using either of the methods alone.

Functional Genomic Analysis of Cotton Genes with Agrobacterium-Mediated Virus-Induced Gene Silencing

PubMed Central

Gao, Xiquan; Shan, Libo

2015-01-01

Cotton (Gossypium spp.) is one of the most agronomically important crops worldwide for its unique textile fiber production and serving as food and feed stock. Molecular breeding and genetic engineering of useful genes into cotton have emerged as advanced approaches to improve cotton yield, fiber quality, and resistance to various stresses. However, the understanding of gene functions and regulations in cotton is largely hindered by the limited molecular and biochemical tools. Here, we describe the method of an Agrobacterium infiltration-based virus-induced gene silencing (VIGS) assay to transiently silence endogenous genes in cotton at 2-week-old seedling stage. The genes of interest could be readily silenced with a consistently high efficiency. To monitor gene silencing efficiency, we have cloned cotton GrCla1 from G. raimondii, a homolog gene of Arabidopsis Cloroplastos alterados 1 (AtCla1) involved in chloroplast development, and inserted into a tobacco rattle virus (TRV) binary vector pYL156. Silencing of GrCla1 results in albino phenotype on the newly emerging leaves, serving as a visual marker for silencing efficiency. To further explore the possibility of using VIGS assay to reveal the essential genes mediating disease resistance to Verticillium dahliae, a fungal pathogen causing severe Verticillium wilt in cotton, we developed a seedling infection assay to inoculate cotton seedlings when the genes of interest are silenced by VIGS. The method we describe here could be further explored for functional genomic analysis of cotton genes involved in development and various biotic and abiotic stresses. PMID:23386302

Functional genomic analysis of cotton genes with agrobacterium-mediated virus-induced gene silencing.

PubMed

Gao, Xiquan; Shan, Libo

2013-01-01

Cotton (Gossypium spp.) is one of the most agronomically important crops worldwide for its unique textile fiber production and serving as food and feed stock. Molecular breeding and genetic engineering of useful genes into cotton have emerged as advanced approaches to improve cotton yield, fiber quality, and resistance to various stresses. However, the understanding of gene functions and regulations in cotton is largely hindered by the limited molecular and biochemical tools. Here, we describe the method of an Agrobacterium infiltration-based virus-induced gene silencing (VIGS) assay to transiently silence endogenous genes in cotton at 2-week-old seedling stage. The genes of interest could be readily silenced with a consistently high efficiency. To monitor gene silencing efficiency, we have cloned cotton GrCla1 from G. raimondii, a homolog gene of Arabidopsis Cloroplastos alterados 1 (AtCla1) involved in chloroplast development, and inserted into a tobacco rattle virus (TRV) binary vector pYL156. Silencing of GrCla1 results in albino phenotype on the newly emerging leaves, serving as a visual marker for silencing efficiency. To further explore the possibility of using VIGS assay to reveal the essential genes mediating disease resistance to Verticillium dahliae, a fungal pathogen causing severe Verticillium wilt in cotton, we developed a seedling infection assay to inoculate cotton seedlings when the genes of interest are silenced by VIGS. The method we describe here could be further explored for functional genomic analysis of cotton genes involved in development and various biotic and abiotic stresses.

Nucleotide variability of protamine genes influencing bull sperm motility variables.

PubMed

H M, Yathish; Kumar, Subodh; Chaudhary, Rajni; Mishra, Chinmoy; A, Sivakumar; Kumar, Amit; Chauhan, Anuj; Ghosh, S K; Mitra, Abhijit

2018-06-01

Protamines (PRMs), important proteins of chromatin condensation in spermiogenesis, are promising candidate genes to explore markers of sperm motility. The coding and in-silico predicted promoter regions of these genes were investigated in 102 crossbred and 32 purebred cattle. Also, mRNA quantification was done to explore its possibility as diagnostic tool of infertility. The PCR-SSCP analysis indicated there were two band patterns only in fragment I of the PRM1 and fragment II of the PRM2 gene. The sequence analysis revealed A152G and G179A transitions in the PRM1 gene. Similarly, G35A, A49G and A64G transitions were identified in the PRM2 gene which resulted in altered amino acid sequences from arginine (R) to glutamine (Q), from arginine (R) to glycine (G) and from arginine (R) to glycine (G), respectively. This caused the reduction in molecular weight of PRM2 from 2157.66 to 1931.33 Da due to reduction in the number of basic amino acids. These altered properties of the PRM2 protein led to the reduction in Mass Motility (MM: P < 0.01), Initial Progressive Motility (IPM; P < 0.05) and Post Thaw Motility (PTM; P < 0.05) in crossbred bulls. The least squares analysis of variance indicated there was an effect of PRM2 haplotypes on MM (P = 0.0069), IPM (P = 0.0306) and PTM (P = 0.0500) in crossbred cattle and on PTM (P = 0.0408) in the overall cattle population. Based on the RT-qPCR analysis, however, there was not any significant variation of PRM1 and PRM2 gene expression among sperm of Vrindavani bulls with relatively lesser and greater sperm motility. Copyright © 2018 Elsevier B.V. All rights reserved.

ISAAC - InterSpecies Analysing Application using Containers.

PubMed

Baier, Herbert; Schultz, Jörg

2014-01-15

Information about genes, transcripts and proteins is spread over a wide variety of databases. Different tools have been developed using these databases to identify biological signals in gene lists from large scale analysis. Mostly, they search for enrichments of specific features. But, these tools do not allow an explorative walk through different views and to change the gene lists according to newly upcoming stories. To fill this niche, we have developed ISAAC, the InterSpecies Analysing Application using Containers. The central idea of this web based tool is to enable the analysis of sets of genes, transcripts and proteins under different biological viewpoints and to interactively modify these sets at any point of the analysis. Detailed history and snapshot information allows tracing each action. Furthermore, one can easily switch back to previous states and perform new analyses. Currently, sets can be viewed in the context of genomes, protein functions, protein interactions, pathways, regulation, diseases and drugs. Additionally, users can switch between species with an automatic, orthology based translation of existing gene sets. As todays research usually is performed in larger teams and consortia, ISAAC provides group based functionalities. Here, sets as well as results of analyses can be exchanged between members of groups. ISAAC fills the gap between primary databases and tools for the analysis of large gene lists. With its highly modular, JavaEE based design, the implementation of new modules is straight forward. Furthermore, ISAAC comes with an extensive web-based administration interface including tools for the integration of third party data. Thus, a local installation is easily feasible. In summary, ISAAC is tailor made for highly explorative interactive analyses of gene, transcript and protein sets in a collaborative environment.

EviNet: a web platform for network enrichment analysis with flexible definition of gene sets.

PubMed

Jeggari, Ashwini; Alekseenko, Zhanna; Petrov, Iurii; Dias, José M; Ericson, Johan; Alexeyenko, Andrey

2018-06-09

The new web resource EviNet provides an easily run interface to network enrichment analysis for exploration of novel, experimentally defined gene sets. The major advantages of this analysis are (i) applicability to any genes found in the global network rather than only to those with pathway/ontology term annotations, (ii) ability to connect genes via different molecular mechanisms rather than within one high-throughput platform, and (iii) statistical power sufficient to detect enrichment of very small sets, down to individual genes. The users' gene sets are either defined prior to upload or derived interactively from an uploaded file by differential expression criteria. The pathways and networks used in the analysis can be chosen from the collection menu. The calculation is typically done within seconds or minutes and the stable URL is provided immediately. The results are presented in both visual (network graphs) and tabular formats using jQuery libraries. Uploaded data and analysis results are kept in separated project directories not accessible by other users. EviNet is available at https://www.evinet.org/.

Using scale and feather traits for module construction provides a functional approach to chicken epidermal development.

PubMed

Bao, Weier; Greenwold, Matthew J; Sawyer, Roger H

2017-11-01

Gene co-expression network analysis has been a research method widely used in systematically exploring gene function and interaction. Using the Weighted Gene Co-expression Network Analysis (WGCNA) approach to construct a gene co-expression network using data from a customized 44K microarray transcriptome of chicken epidermal embryogenesis, we have identified two distinct modules that are highly correlated with scale or feather development traits. Signaling pathways related to feather development were enriched in the traditional KEGG pathway analysis and functional terms relating specifically to embryonic epidermal development were also enriched in the Gene Ontology analysis. Significant enrichment annotations were discovered from customized enrichment tools such as Modular Single-Set Enrichment Test (MSET) and Medical Subject Headings (MeSH). Hub genes in both trait-correlated modules showed strong specific functional enrichment toward epidermal development. Also, regulatory elements, such as transcription factors and miRNAs, were targeted in the significant enrichment result. This work highlights the advantage of this methodology for functional prediction of genes not previously associated with scale- and feather trait-related modules.

A Systematic Analysis of Candidate Genes Associated with Nicotine Addiction

PubMed Central

Liu, Meng; Li, Xia; Fan, Rui; Liu, Xinhua; Wang, Ju

2015-01-01

Nicotine, as the major psychoactive component of tobacco, has broad physiological effects within the central nervous system, but our understanding of the molecular mechanism underlying its neuronal effects remains incomplete. In this study, we performed a systematic analysis on a set of nicotine addiction-related genes to explore their characteristics at network levels. We found that NAGenes tended to have a more moderate degree and weaker clustering coefficient and to be less central in the network compared to alcohol addiction-related genes or cancer genes. Further, clustering of these genes resulted in six clusters with themes in synaptic transmission, signal transduction, metabolic process, and apoptosis, which provided an intuitional view on the major molecular functions of the genes. Moreover, functional enrichment analysis revealed that neurodevelopment, neurotransmission activity, and metabolism related biological processes were involved in nicotine addiction. In summary, by analyzing the overall characteristics of the nicotine addiction related genes, this study provided valuable information for understanding the molecular mechanisms underlying nicotine addiction. PMID:26097843

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 results point to the potential to combine gene signatures to a greater effect in cases where each gene signature represents some distinct aspect of the cancer biology. Furthermore we conclude that the hypertabastic survival models can be an effective survival analysis tool for breast cancer patients. PMID:23241496

DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures

PubMed Central

2013-01-01

Background The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. Results We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. Conclusions The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis. PMID:24067102

Key genes and pathways in measles and their interaction with environmental chemicals.

PubMed

Zhang, Rongqiang; Jiang, Hualin; Li, Fengying; Su, Ning; Ding, Yi; Mao, Xiang; Ren, Dan; Wang, Jing

2018-06-01

The aim of the present study was to explore key genes that may have a role in the pathology of measles virus infection and to clarify the interaction networks between environmental factors and differentially expressed genes (DEGs). After screening the database of the Gene Expression Omnibus of the National Center for Biotechnology Information, the dataset GSE5808 was downloaded and analyzed. A global normalization method was performed to minimize data inconsistencies and heterogeneity. DEGs during different stages of measles virus infection were explored using R software (v3.4.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using Cytoscape 3.4.0 software. A protein-protein interaction (PPI) network of the DEGs was obtained from the STRING database v9.05. A total of 43 DEGs were obtained from four analyzed sample groups, including 10 highly expressed genes and 33 genes with decreased expression. The most enriched pathways based on KEGG analysis were fatty acid elongation, cytokine-cytokine receptor interaction and RNA degradation. The genes mentioned in the PPI network were mainly associated with protein binding and chemokine activity. A total of 219 chemicals were identified that may, jointly or on their own, interact with the 6 DEGs between the control group and patients with measles (at hospital entry), including benzo(a)pyrene (BaP) and tetrachlorodibenzodioxin (TCDD). In conclusion, the present study revealed that chemokines and environmental chemicals, e.g. BaP and TCDD, may affect the development of measles.

Genome-Wide Analysis of NBS-LRR Genes in Sorghum Genome Revealed Several Events Contributing to NBS-LRR Gene Evolution in Grass Species

PubMed Central

Yang, Xiping; Wang, Jianping

2016-01-01

The nucleotide-binding site (NBS)–leucine-rich repeat (LRR) gene family is crucially important for offering resistance to pathogens. To explore evolutionary conservation and variability of NBS-LRR genes across grass species, we identified 88, 107, 24, and 44 full-length NBS-LRR genes in sorghum, rice, maize, and Brachypodium, respectively. A comprehensive analysis was performed on classification, genome organization, evolution, expression, and regulation of these NBS-LRR genes using sorghum as a representative of grass species. In general, the full-length NBS-LRR genes are highly clustered and duplicated in sorghum genome mainly due to local duplications. NBS-LRR genes have basal expression levels and are highly potentially targeted by miRNA. The number of NBS-LRR genes in the four grass species is positively correlated with the gene clustering rate. The results provided a valuable genomic resource and insights for functional and evolutionary studies of NBS-LRR genes in grass species. PMID:26792976

pico-PLAZA, a genome database of microbial photosynthetic eukaryotes.

PubMed

Vandepoele, Klaas; Van Bel, Michiel; Richard, Guilhem; Van Landeghem, Sofie; Verhelst, Bram; Moreau, Hervé; Van de Peer, Yves; Grimsley, Nigel; Piganeau, Gwenael

2013-08-01

With the advent of next generation genome sequencing, the number of sequenced algal genomes and transcriptomes is rapidly growing. Although a few genome portals exist to browse individual genome sequences, exploring complete genome information from multiple species for the analysis of user-defined sequences or gene lists remains a major challenge. pico-PLAZA is a web-based resource (http://bioinformatics.psb.ugent.be/pico-plaza/) for algal genomics that combines different data types with intuitive tools to explore genomic diversity, perform integrative evolutionary sequence analysis and study gene functions. Apart from homologous gene families, multiple sequence alignments, phylogenetic trees, Gene Ontology, InterPro and text-mining functional annotations, different interactive viewers are available to study genome organization using gene collinearity and synteny information. Different search functions, documentation pages, export functions and an extensive glossary are available to guide non-expert scientists. To illustrate the versatility of the platform, different case studies are presented demonstrating how pico-PLAZA can be used to functionally characterize large-scale EST/RNA-Seq data sets and to perform environmental genomics. Functional enrichments analysis of 16 Phaeodactylum tricornutum transcriptome libraries offers a molecular view on diatom adaptation to different environments of ecological relevance. Furthermore, we show how complementary genomic data sources can easily be combined to identify marker genes to study the diversity and distribution of algal species, for example in metagenomes, or to quantify intraspecific diversity from environmental strains. © 2013 John Wiley & Sons Ltd and Society for Applied Microbiology.

Genome-wide characterization of the Pectate Lyase-like (PLL) genes in Brassica rapa.

PubMed

Jiang, Jingjing; Yao, Lina; Miao, Ying; Cao, Jiashu

2013-11-01

Pectate lyases (PL) depolymerize demethylated pectin (pectate, EC 4.2.2.2) by catalyzing the eliminative cleavage of α-1,4-glycosidic linked galacturonan. Pectate Lyase-like (PLL) genes are one of the largest and most complex families in plants. However, studies on the phylogeny, gene structure, and expression of PLL genes are limited. To understand the potential functions of PLL genes in plants, we characterized their intron-exon structure, phylogenetic relationships, and protein structures, and measured their expression patterns in various tissues, specifically the reproductive tissues in Brassica rapa. Sequence alignments revealed two characteristic motifs in PLL genes. The chromosome location analysis indicated that 18 of the 46 PLL genes were located in the least fractionated sub-genome (LF) of B. rapa, while 16 were located in the medium fractionated sub-genome (MF1) and 12 in the more fractionated sub-genome (MF2). Quantitative RT-PCR analysis showed that BrPLL genes were expressed in various tissues, with most of them being expressed in flowers. Detailed qRT-PCR analysis identified 11 pollen specific PLL genes and several other genes with unique spatial expression patterns. In addition, some duplicated genes showed similar expression patterns. The phylogenetic analysis identified three PLL gene subfamilies in plants, among which subfamily II might have evolved from gene neofunctionalization or subfunctionalization. Therefore, this study opens the possibility for exploring the roles of PLL genes during plant development.

Genomic evidence of gene duplication and adaptive evolution of Toll like receptors (TLR2 and TLR4) in reptiles.

PubMed

Shang, Shuai; Zhong, Huaming; Wu, Xiaoyang; Wei, Qinguo; Zhang, Huanxin; Chen, Jun; Chen, Yao; Tang, Xuexi; Zhang, Honghai

2018-04-01

Toll-like receptors (TLRs) encoded by the TLR multigene family play an important role in initial pathogen recognition in vertebrates. Among the TLRs, TLR2 and TLR4 may be of particular importance to reptiles. In order to study the evolutionary patterns and structural characteristics of TLRs, we explored the available genomes of several representative members of reptiles. 25 TLR2 genes and 19 TLR4 genes from reptiles were obtained in this study. Phylogenetic results showed that the TLR2 gene duplication occurred in several species. Evolutionary analysis by at least two methods identified 30 and 13 common positively selected codons in TLR2 and TLR4, respectively. Most positively selected sites of TLR2 and TLR4 were located in the Leucine-rich repeat (LRRs). Branch model analysis showed that TLR2 genes were under different evolutionary forces in reptiles, while the TLR4 genes showed no significant selection pressure. The different evolutionary adaptation of TLR2 and TLR4 among the reptiles might be due to their different function in recognizing bacteria. Overall, we explored the structure and evolution of TLR2 and TLR4 genes in reptiles for the first time. Our study revealed valuable information regarding TLR2 and TLR4 in reptiles, and provided novel insights into the conservation concern of natural populations. Copyright © 2017 Elsevier B.V. All rights reserved.

A Meta-Analysis of Multiple Matched Copy Number and Transcriptomics Data Sets for Inferring Gene Regulatory Relationships

PubMed Central

Newton, Richard; Wernisch, Lorenz

2014-01-01

Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments. PMID:25148247

Acclimation of Antarctic Chlamydomonas to the sea-ice environment: a transcriptomic analysis.

PubMed

Liu, Chenlin; Wang, Xiuliang; Wang, Xingna; Sun, Chengjun

2016-07-01

The Antarctic green alga Chlamydomonas sp. ICE-L was isolated from sea ice. As a psychrophilic microalga, it can tolerate the environmental stress in the sea-ice brine, such as freezing temperature and high salinity. We performed a transcriptome analysis to identify freezing stress responding genes and explore the extreme environmental acclimation-related strategies. Here, we show that many genes in ICE-L transcriptome that encoding PUFA synthesis enzymes, molecular chaperon proteins, and cell membrane transport proteins have high similarity to the gens from Antarctic bacteria. These ICE-L genes are supposed to be acquired through horizontal gene transfer from its symbiotic microbes in the sea-ice brine. The presence of these genes in both sea-ice microalgae and bacteria indicated the biological processes they involved in are possibly contributing to ICE-L success in sea ice. In addition, the biological pathways were compared between ICE-L and its closely related sister species, Chlamydomonas reinhardtii and Volvox carteri. In ICE-L transcripome, many sequences homologous to the plant or bacteria proteins in the post-transcriptional, post-translational modification, and signal-transduction KEGG pathways, are absent in the nonpsychrophilic green algae. These complex structural components might imply enhanced stress adaptation capacity. At last, differential gene expression analysis at the transcriptome level of ICE-L indicated that genes that associated with post-translational modification, lipid metabolism, and nitrogen metabolism are responding to the freezing treatment. In conclusion, the transcriptome of Chlamydomonas sp. ICE-L is very useful for exploring the mutualistic interaction between microalgae and bacteria in sea ice; and discovering the specific genes and metabolism pathways responding to the freezing acclimation in psychrophilic microalgae.

Data Analysis of Sequences and qPCR for Microbial Communities during Algal Blooms

EPA Pesticide Factsheets

A training opportunity is open to a highly microbial-research-motivated student to conduct sequence analysis, explore novel genes and metabolic pathways, validate resultant findings using qPCR/RT-qPCR and summarize the findings

From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.

PubMed

Chen, Yunshun; Lun, Aaron T L; Smyth, Gordon K

2016-01-01

In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims of RNA-seq profiling is to identify genes or molecular pathways that are differentially expressed (DE) between two or more biological conditions. This article demonstrates a computational workflow for the detection of DE genes and pathways from RNA-seq data by providing a complete analysis of an RNA-seq experiment profiling epithelial cell subsets in the mouse mammary gland. The workflow uses R software packages from the open-source Bioconductor project and covers all steps of the analysis pipeline, including alignment of read sequences, data exploration, differential expression analysis, visualization and pathway analysis. Read alignment and count quantification is conducted using the Rsubread package and the statistical analyses are performed using the edgeR package. The differential expression analysis uses the quasi-likelihood functionality of edgeR.

Gene expression patterns combined with bioinformatics analysis identify genes associated with cholangiocarcinoma.

PubMed

Li, Chen; Shen, Weixing; Shen, Sheng; Ai, Zhilong

2013-12-01

To explore the molecular mechanisms of cholangiocarcinoma (CC), microarray technology was used to find biomarkers for early detection and diagnosis. The gene expression profiles from 6 patients with CC and 5 normal controls were downloaded from Gene Expression Omnibus and compared. As a result, 204 differentially co-expressed genes (DCGs) in CC patients compared to normal controls were identified using a computational bioinformatics analysis. These genes were mainly involved in coenzyme metabolic process, peptidase activity and oxidation reduction. A regulatory network was constructed by mapping the DCGs to known regulation data. Four transcription factors, FOXC1, ZIC2, NKX2-2 and GCGR, were hub nodes in the network. In conclusion, this study provides a set of targets useful for future investigations into molecular biomarker studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

PubMed

Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

2014-12-01

Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

Systematic exploration of essential yeast gene function with temperature-sensitive mutants

PubMed Central

Li, Zhijian; Vizeacoumar, Franco J; Bahr, Sondra; Li, Jingjing; Warringer, Jonas; Vizeacoumar, Frederick S; Min, Renqiang; VanderSluis, Benjamin; Bellay, Jeremy; DeVit, Michael; Fleming, James A; Stephens, Andrew; Haase, Julian; Lin, Zhen-Yuan; Baryshnikova, Anastasia; Lu, Hong; Yan, Zhun; Jin, Ke; Barker, Sarah; Datti, Alessandro; Giaever, Guri; Nislow, Corey; Bulawa, Chris; Myers, Chad L; Costanzo, Michael; Gingras, Anne-Claude; Zhang, Zhaolei; Blomberg, Anders; Bloom, Kerry; Andrews, Brenda; Boone, Charles

2012-01-01

Conditional temperature-sensitive (ts) mutations are valuable reagents for studying essential genes in the yeast Saccharomyces cerevisiae. We constructed 787 ts strains, covering 497 (~45%) of the 1,101 essential yeast genes, with ~30% of the genes represented by multiple alleles. All of the alleles are integrated into their native genomic locus in the S288C common reference strain and are linked to a kanMX selectable marker, allowing further genetic manipulation by synthetic genetic array (SGA)–based, high-throughput methods. We show two such manipulations: barcoding of 440 strains, which enables chemical-genetic suppression analysis, and the construction of arrays of strains carrying different fluorescent markers of subcellular structure, which enables quantitative analysis of phenotypes using high-content screening. Quantitative analysis of a GFP-tubulin marker identified roles for cohesin and condensin genes in spindle disassembly. This mutant collection should facilitate a wide range of systematic studies aimed at understanding the functions of essential genes. PMID:21441928

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

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

Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less

Computation and application of tissue-specific gene set weights.

PubMed

Frost, H Robert

2018-04-06

Gene set testing, or pathway analysis, has become a critical tool for the analysis of highdimensional genomic data. Although the function and activity of many genes and higher-level processes is tissue-specific, gene set testing is typically performed in a tissue agnostic fashion, which impacts statistical power and the interpretation and replication of results. To address this challenge, we have developed a bioinformatics approach to compute tissuespecific weights for individual gene sets using information on tissue-specific gene activity from the Human Protein Atlas (HPA). We used this approach to create a public repository of tissue-specific gene set weights for 37 different human tissue types from the HPA and all collections in the Molecular Signatures Database (MSigDB). To demonstrate the validity and utility of these weights, we explored three different applications: the functional characterization of human tissues, multi-tissue analysis for systemic diseases and tissue-specific gene set testing. All data used in the reported analyses is publicly available. An R implementation of the method and tissue-specific weights for MSigDB gene set collections can be downloaded at http://www.dartmouth.edu/∼hrfrost/TissueSpecificGeneSets. rob.frost@dartmouth.edu.

DNetDB: The human disease network database based on dysfunctional regulation mechanism.

PubMed

Yang, Jing; Wu, Su-Juan; Yang, Shao-You; Peng, Jia-Wei; Wang, Shi-Nuo; Wang, Fu-Yan; Song, Yu-Xing; Qi, Ting; Li, Yi-Xue; Li, Yuan-Yuan

2016-05-21

Disease similarity study provides new insights into disease taxonomy, pathogenesis, which plays a guiding role in diagnosis and treatment. The early studies were limited to estimate disease similarities based on clinical manifestations, disease-related genes, medical vocabulary concepts or registry data, which were inevitably biased to well-studied diseases and offered small chance of discovering novel findings in disease relationships. In other words, genome-scale expression data give us another angle to address this problem since simultaneous measurement of the expression of thousands of genes allows for the exploration of gene transcriptional regulation, which is believed to be crucial to biological functions. Although differential expression analysis based methods have the potential to explore new disease relationships, it is difficult to unravel the upstream dysregulation mechanisms of diseases. We therefore estimated disease similarities based on gene expression data by using differential coexpression analysis, a recently emerging method, which has been proved to be more potential to capture dysfunctional regulation mechanisms than differential expression analysis. A total of 1,326 disease relationships among 108 diseases were identified, and the relevant information constituted the human disease network database (DNetDB). Benefiting from the use of differential coexpression analysis, the potential common dysfunctional regulation mechanisms shared by disease pairs (i.e. disease relationships) were extracted and presented. Statistical indicators, common disease-related genes and drugs shared by disease pairs were also included in DNetDB. In total, 1,326 disease relationships among 108 diseases, 5,598 pathways, 7,357 disease-related genes and 342 disease drugs are recorded in DNetDB, among which 3,762 genes and 148 drugs are shared by at least two diseases. DNetDB is the first database focusing on disease similarity from the viewpoint of gene regulation mechanism. It provides an easy-to-use web interface to search and browse the disease relationships and thus helps to systematically investigate etiology and pathogenesis, perform drug repositioning, and design novel therapeutic interventions.Database URL: http://app.scbit.org/DNetDB/ #.

ITEP: an integrated toolkit for exploration of microbial pan-genomes.

PubMed

Benedict, Matthew N; Henriksen, James R; Metcalf, William W; Whitaker, Rachel J; Price, Nathan D

2014-01-03

Comparative genomics is a powerful approach for studying variation in physiological traits as well as the evolution and ecology of microorganisms. Recent technological advances have enabled sequencing large numbers of related genomes in a single project, requiring computational tools for their integrated analysis. In particular, accurate annotations and identification of gene presence and absence are critical for understanding and modeling the cellular physiology of newly sequenced genomes. Although many tools are available to compare the gene contents of related genomes, new tools are necessary to enable close examination and curation of protein families from large numbers of closely related organisms, to integrate curation with the analysis of gain and loss, and to generate metabolic networks linking the annotations to observed phenotypes. We have developed ITEP, an Integrated Toolkit for Exploration of microbial Pan-genomes, to curate protein families, compute similarities to externally-defined domains, analyze gene gain and loss, and generate draft metabolic networks from one or more curated reference network reconstructions in groups of related microbial species among which the combination of core and variable genes constitute the their "pan-genomes". The ITEP toolkit consists of: (1) a series of modular command-line scripts for identification, comparison, curation, and analysis of protein families and their distribution across many genomes; (2) a set of Python libraries for programmatic access to the same data; and (3) pre-packaged scripts to perform common analysis workflows on a collection of genomes. ITEP's capabilities include de novo protein family prediction, ortholog detection, analysis of functional domains, identification of core and variable genes and gene regions, sequence alignments and tree generation, annotation curation, and the integration of cross-genome analysis and metabolic networks for study of metabolic network evolution. ITEP is a powerful, flexible toolkit for generation and curation of protein families. ITEP's modular design allows for straightforward extension as analysis methods and tools evolve. By integrating comparative genomics with the development of draft metabolic networks, ITEP harnesses the power of comparative genomics to build confidence in links between genotype and phenotype and helps disambiguate gene annotations when they are evaluated in both evolutionary and metabolic network contexts.

Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer.

PubMed

Gao, Xue-Xin; Gao, Lei; Wang, Jiu-Qiang; Qu, Su-Su; Qu, Yue; Sun, Hong-Lei; Liu, Si-Dang; Shang, Ying-Li

2016-07-12

Recent genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with risk of esophageal cancer (EC). However, investigation of genetic basis from the perspective of systematic biology and integrative genomics remains scarce.In this study, we explored genetic basis of EC based on GWAS data and implemented a series of bioinformatics methods including functional annotation, expression quantitative trait loci (eQTL) analysis, pathway enrichment analysis and pathway grouped network analysis.Two hundred and thirteen risk SNPs were identified, in which 44 SNPs were found to have significantly differential gene expression in esophageal tissues by eQTL analysis. By pathway enrichment analysis, 170 risk genes mapped by risk SNPs were enriched into 38 significant GO terms and 17 significant KEGG pathways, which were significantly grouped into 9 sub-networks by pathway grouped network analysis. The 9 groups of interconnected pathways were mainly involved with muscle cell proliferation, cellular response to interleukin-6, cell adhesion molecules, and ethanol oxidation, which might participate in the development of EC.Our findings provide genetic evidence and new insight for exploring the molecular mechanisms of EC.

MARQ: an online tool to mine GEO for experiments with similar or opposite gene expression signatures.

PubMed

Vazquez, Miguel; Nogales-Cadenas, Ruben; Arroyo, Javier; Botías, Pedro; García, Raul; Carazo, Jose M; Tirado, Francisco; Pascual-Montano, Alberto; Carmona-Saez, Pedro

2010-07-01

The enormous amount of data available in public gene expression repositories such as Gene Expression Omnibus (GEO) offers an inestimable resource to explore gene expression programs across several organisms and conditions. This information can be used to discover experiments that induce similar or opposite gene expression patterns to a given query, which in turn may lead to the discovery of new relationships among diseases, drugs or pathways, as well as the generation of new hypotheses. In this work, we present MARQ, a web-based application that allows researchers to compare a query set of genes, e.g. a set of over- and under-expressed genes, against a signature database built from GEO datasets for different organisms and platforms. MARQ offers an easy-to-use and integrated environment to mine GEO, in order to identify conditions that induce similar or opposite gene expression patterns to a given experimental condition. MARQ also includes additional functionalities for the exploration of the results, including a meta-analysis pipeline to find genes that are differentially expressed across different experiments. The application is freely available at http://marq.dacya.ucm.es.

Gene expression analysis of wood decay fungus Fibroporia Radiculosa grown In ACQ-treated wood

Treesearch

Ayfer Akgul; Ali Akgul; Juliet D. Diehl Tang

2018-01-01

Copper-tolerant brown-rot fungi are able todegrade wood treated with copper or copper-based wood preservatives. This research used quantitative reverse transcriptase polymerase chain reaction to explore what genes of the brown-rot fungus, Fibroporia radiculosa, were expressed when the fungus was overcoming the wood preservatives and decaying the...

The effects of omega-3 polyunsaturated fatty acids and genetic variants on methylation levels of the interleukin-6 gene promoter

USDA-ARS?s Scientific Manuscript database

Scope: Omega-3 PUFAs (n-3 PUFAs) reduce IL-6 gene expression, but their effects on transcription regulatory mechanisms are unknown. We aimed to conduct an integrated analysis with both population and in vitro studies to systematically explore the relationships among n-3 PUFA, DNA methylation, single...

Characterization and comparative analyses of transcriptomes for in vivo and in vitro produced peri-implantation conceptuses and endometria from sheep

PubMed Central

WEI, Xia; XIAOLING, Zhang; KAI, Miao; RUI, Wang; JING, Xu; MIN, Guo; ZHONGHONG, Wu; JIANHUI, Tian; XINYU, Zhang; LEI, An

2016-01-01

An increasing number of reports indicate that in vitro fertilization (IVF) is highly associated with long‑term side effects on embryonic and postnatal development, and can sometimes result in embryonic implant failure. While high‑throughput gene expression analysis has been used to explore the mechanisms underlying IVF-induced side effects on embryonic development, little is known about the effects of IVF on conceptus–endometrial interactions during the peri-implantation period. Using sheep as a model, we performed a comparative transcriptome analysis between in vivo (IVO; in vivo fertilized followed by further development in the uterus) and in vitro produced (IVP; IVF with further culture in the incubator) conceptuses, and the caruncular and intercaruncular areas of the ovine endometrium. We identified several genes that were differentially expressed between the IVO and IVP groups on day 17, when adhesion between the trophoblast and the uterine luminal epithelium begins in sheep. By performing Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, we found that, in the conceptus, differentially expressed genes (DEGs) were associated mainly with functions relating to cell binding and the cell cycle. In the endometrial caruncular area, DEGs were involved in cell adhesion/migration and apoptosis, and in the intercaruncular area, they were significantly enriched in pathways of signal transduction and transport. Thus, these DEGs are potential candidates for further exploring the mechanism underlying IVF/IVP-induced embryonic implant failure that occurs due to a loss of interaction between the conceptus and endometrium during the peri-implantation period. PMID:26946921

A comparative molecular analysis of water-filled limestone sinkholes in north-eastern Mexico.

PubMed

Sahl, Jason W; Gary, Marcus O; Harris, J Kirk; Spear, John R

2011-01-01

Sistema Zacatón in north-eastern Mexico is host to several deep, water-filled, anoxic, karstic sinkholes (cenotes). These cenotes were explored, mapped, and geochemically and microbiologically sampled by the autonomous underwater vehicle deep phreatic thermal explorer (DEPTHX). The community structure of the filterable fraction of the water column and extensive microbial mats that coat the cenote walls was investigated by comparative analysis of small-subunit (SSU) 16S rRNA gene sequences. Full-length Sanger gene sequence analysis revealed novel microbial diversity that included three putative bacterial candidate phyla and three additional groups that showed high intra-clade distance with poorly characterized bacterial candidate phyla. Limited functional gene sequence analysis in these anoxic environments identified genes associated with methanogenesis, sulfate reduction and anaerobic ammonium oxidation. A directed, barcoded amplicon, multiplex pyrosequencing approach was employed to compare ∼100,000 bacterial SSU gene sequences from water column and wall microbial mat samples from five cenotes in Sistema Zacatón. A new, high-resolution sequence distribution profile (SDP) method identified changes in specific phylogenetic types (phylotypes) in microbial mats at varied depths; Mantel tests showed a correlation of the genetic distances between mat communities in two cenotes and the geographic location of each cenote. Community structure profiles from the water column of three neighbouring cenotes showed distinct variation; statistically significant differences in the concentration of geochemical constituents suggest that the variation observed in microbial communities between neighbouring cenotes are due to geochemical variation. © 2010 Society for Applied Microbiology and Blackwell Publishing Ltd.

Key genes and pathways in measles and their interaction with environmental chemicals

PubMed Central

Zhang, Rongqiang; Jiang, Hualin; Li, Fengying; Su, Ning; Ding, Yi; Mao, Xiang; Ren, Dan; Wang, Jing

2018-01-01

The aim of the present study was to explore key genes that may have a role in the pathology of measles virus infection and to clarify the interaction networks between environmental factors and differentially expressed genes (DEGs). After screening the database of the Gene Expression Omnibus of the National Center for Biotechnology Information, the dataset GSE5808 was downloaded and analyzed. A global normalization method was performed to minimize data inconsistencies and heterogeneity. DEGs during different stages of measles virus infection were explored using R software (v3.4.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using Cytoscape 3.4.0 software. A protein-protein interaction (PPI) network of the DEGs was obtained from the STRING database v9.05. A total of 43 DEGs were obtained from four analyzed sample groups, including 10 highly expressed genes and 33 genes with decreased expression. The most enriched pathways based on KEGG analysis were fatty acid elongation, cytokine-cytokine receptor interaction and RNA degradation. The genes mentioned in the PPI network were mainly associated with protein binding and chemokine activity. A total of 219 chemicals were identified that may, jointly or on their own, interact with the 6 DEGs between the control group and patients with measles (at hospital entry), including benzo(a)pyrene (BaP) and tetrachlorodibenzodioxin (TCDD). In conclusion, the present study revealed that chemokines and environmental chemicals, e.g. BaP and TCDD, may affect the development of measles. PMID:29805511

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.

Interactive knowledge discovery and data mining on genomic expression data with numeric formal concept analysis.

PubMed

González-Calabozo, Jose M; Valverde-Albacete, Francisco J; Peláez-Moreno, Carmen

2016-09-15

Gene Expression Data (GED) analysis poses a great challenge to the scientific community that can be framed into the Knowledge Discovery in Databases (KDD) and Data Mining (DM) paradigm. Biclustering has emerged as the machine learning method of choice to solve this task, but its unsupervised nature makes result assessment problematic. This is often addressed by means of Gene Set Enrichment Analysis (GSEA). We put forward a framework in which GED analysis is understood as an Exploratory Data Analysis (EDA) process where we provide support for continuous human interaction with data aiming at improving the step of hypothesis abduction and assessment. We focus on the adaptation to human cognition of data interpretation and visualization of the output of EDA. First, we give a proper theoretical background to bi-clustering using Lattice Theory and provide a set of analysis tools revolving around [Formula: see text]-Formal Concept Analysis ([Formula: see text]-FCA), a lattice-theoretic unsupervised learning technique for real-valued matrices. By using different kinds of cost structures to quantify expression we obtain different sequences of hierarchical bi-clusterings for gene under- and over-expression using thresholds. Consequently, we provide a method with interleaved analysis steps and visualization devices so that the sequences of lattices for a particular experiment summarize the researcher's vision of the data. This also allows us to define measures of persistence and robustness of biclusters to assess them. Second, the resulting biclusters are used to index external omics databases-for instance, Gene Ontology (GO)-thus offering a new way of accessing publicly available resources. This provides different flavors of gene set enrichment against which to assess the biclusters, by obtaining their p-values according to the terminology of those resources. We illustrate the exploration procedure on a real data example confirming results previously published. The GED analysis problem gets transformed into the exploration of a sequence of lattices enabling the visualization of the hierarchical structure of the biclusters with a certain degree of granularity. The ability of FCA-based bi-clustering methods to index external databases such as GO allows us to obtain a quality measure of the biclusters, to observe the evolution of a gene throughout the different biclusters it appears in, to look for relevant biclusters-by observing their genes and what their persistence is-to infer, for instance, hypotheses on their function.

Text mining and network analysis to find functional associations of genes in high altitude diseases.

PubMed

Bhasuran, Balu; Subramanian, Devika; Natarajan, Jeyakumar

2018-05-02

Travel to elevations above 2500 m is associated with the risk of developing one or more forms of acute altitude illness such as acute mountain sickness (AMS), high altitude cerebral edema (HACE) or high altitude pulmonary edema (HAPE). Our work aims to identify the functional association of genes involved in high altitude diseases. In this work we identified the gene networks responsible for high altitude diseases by using the principle of gene co-occurrence statistics from literature and network analysis. First, we mined the literature data from PubMed on high-altitude diseases, and extracted the co-occurring gene pairs. Next, based on their co-occurrence frequency, gene pairs were ranked. Finally, a gene association network was created using statistical measures to explore potential relationships. Network analysis results revealed that EPO, ACE, IL6 and TNF are the top five genes that were found to co-occur with 20 or more genes, while the association between EPAS1 and EGLN1 genes is strongly substantiated. The network constructed from this study proposes a large number of genes that work in-toto in high altitude conditions. Overall, the result provides a good reference for further study of the genetic relationships in high altitude diseases. Copyright © 2018 Elsevier Ltd. All rights reserved.

Ortholog-based screening and identification of genes related to intracellular survival.

PubMed

Yang, Xiaowen; Wang, Jiawei; Bing, Guoxia; Bie, Pengfei; De, Yanyan; Lyu, Yanli; Wu, Qingmin

2018-04-20

Bioinformatics and comparative genomics analysis methods were used to predict unknown pathogen genes based on homology with identified or functionally clustered genes. In this study, the genes of common pathogens were analyzed to screen and identify genes associated with intracellular survival through sequence similarity, phylogenetic tree analysis and the λ-Red recombination system test method. The total 38,952 protein-coding genes of common pathogens were divided into 19,775 clusters. As demonstrated through a COG analysis, information storage and processing genes might play an important role intracellular survival. Only 19 clusters were present in facultative intracellular pathogens, and not all were present in extracellular pathogens. Construction of a phylogenetic tree selected 18 of these 19 clusters. Comparisons with the DEG database and previous research revealed that seven other clusters are considered essential gene clusters and that seven other clusters are associated with intracellular survival. Moreover, this study confirmed that clusters screened by orthologs with similar function could be replaced with an approved uvrY gene and its orthologs, and the results revealed that the usg gene is associated with intracellular survival. The study improves the current understanding of intracellular pathogens characteristics and allows further exploration of the intracellular survival-related gene modules in these pathogens. Copyright © 2018. Published by Elsevier B.V.

Systematic Analysis of the 4-Coumarate:Coenzyme A Ligase (4CL) Related Genes and Expression Profiling during Fruit Development in the Chinese Pear

PubMed Central

Cao, Yunpeng; Han, Yahui; Li, Dahui; Lin, Yi; Cai, Yongping

2016-01-01

In plants, 4-coumarate:coenzyme A ligases (4CLs), comprising some of the adenylate-forming enzymes, are key enzymes involved in regulating lignin metabolism and the biosynthesis of flavonoids and other secondary metabolites. Although several 4CL-related proteins were shown to play roles in secondary metabolism, no comprehensive study on 4CL-related genes in the pear and other Rosaceae species has been reported. In this study, we identified 4CL-related genes in the apple, peach, yangmei, and pear genomes using DNATOOLS software and inferred their evolutionary relationships using phylogenetic analysis, collinearity analysis, conserved motif analysis, and structure analysis. A total of 149 4CL-related genes in four Rosaceous species (pear, apple, peach, and yangmei) were identified, with 30 members in the pear. We explored the functions of several 4CL and acyl-coenzyme A synthetase (ACS) genes during the development of pear fruit by quantitative real-time PCR (qRT-PCR). We found that duplication events had occurred in the 30 4CL-related genes in the pear. These duplicated 4CL-related genes are distributed unevenly across all pear chromosomes except chromosomes 4, 8, 11, and 12. The results of this study provide a basis for further investigation of both the functions and evolutionary history of 4CL-related genes. PMID:27775579

Systematic Analysis of the 4-Coumarate:Coenzyme A Ligase (4CL) Related Genes and Expression Profiling during Fruit Development in the Chinese Pear.

PubMed

Cao, Yunpeng; Han, Yahui; Li, Dahui; Lin, Yi; Cai, Yongping

2016-10-19

In plants, 4-coumarate:coenzyme A ligases (4CLs), comprising some of the adenylate-forming enzymes, are key enzymes involved in regulating lignin metabolism and the biosynthesis of flavonoids and other secondary metabolites. Although several 4CL-related proteins were shown to play roles in secondary metabolism, no comprehensive study on 4CL-related genes in the pear and other Rosaceae species has been reported. In this study, we identified 4CL-related genes in the apple, peach, yangmei, and pear genomes using DNATOOLS software and inferred their evolutionary relationships using phylogenetic analysis, collinearity analysis, conserved motif analysis, and structure analysis. A total of 149 4CL-related genes in four Rosaceous species (pear, apple, peach, and yangmei) were identified, with 30 members in the pear. We explored the functions of several 4CL and acyl-coenzyme A synthetase (ACS) genes during the development of pear fruit by quantitative real-time PCR (qRT-PCR). We found that duplication events had occurred in the 30 4CL-related genes in the pear. These duplicated 4CL-related genes are distributed unevenly across all pear chromosomes except chromosomes 4, 8, 11, and 12. The results of this study provide a basis for further investigation of both the functions and evolutionary history of 4CL-related genes.

Synergistic Effect of Combinatorial Treatment with Curcumin and Mitomycin C on the Induction of Apoptosis of Breast Cancer Cells: A cDNA Microarray Analysis

PubMed Central

Zhou, Qian-Mei; Chen, Qi-Long; Du, Jia; Wang, Xiu-Feng; Lu, Yi-Yu; Zhang, Hui; Su, Shi-Bing

2014-01-01

In order to explore the synergistic mechanisms of combinatorial treatment using curcumin and mitomycin C (MMC) for breast cancer, MCF-7 breast cancer xenografts were conducted to observe the synergistic effect of combinatorial treatment using curcumin and MMC at various dosages. The synergistic mechanisms of combinatorial treatment using curcumin and MMC on the inhibition of tumor growth were explored by differential gene expression profile, gene ontology (GO), ingenuity pathway analysis (IPA) and Signal–Net network analysis. The expression levels of selected genes identified by cDNA microarray expression profiling were validated by quantitative RT-PCR (qRT-PCR) and Western blot analysis. Effect of combinatorial treatment on the inhibition of cell growth was observed by MTT assay. Apoptosis was detected by flow cytometric analysis and Hoechst 33258 staining. The combinatorial treatment of 100 mg/kg curcumin and 1.5 mg/kg MMC revealed synergistic inhibition on tumor growth. Among 1501 differentially expressed genes, the expression of 25 genes exhibited an obvious change and a significant difference in 27 signal pathways was observed (p < 0.05). In addition, Mapk1 (ERK) and Mapk14 (MAPK p38) had more cross-interactions with other genes and revealed an increase in expression by 8.14- and 11.84-fold, respectively during the combinatorial treatment by curcumin and MMC when compared with the control. Moreover, curcumin can synergistically improve tumoricidal effect of MMC in another human breast cancer MDA-MB-231 cells. Apoptosis was significantly induced by the combinatorial treatment (p < 0.05) and significantly inhibited by ERK inhibitor (PD98059) in MCF-7 cells (p < 0.05). The synergistic effect of combinatorial treatment by curcumin and MMC on the induction of apoptosis in breast cancer cells may be via the ERK pathway. PMID:25226537

Exploring the Yeast Acetylome Using Functional Genomics

PubMed Central

Duffy, Supipi Kaluarachchi; Friesen, Helena; Baryshnikova, Anastasia; Lambert, Jean-Philippe; Chong, Yolanda T.; Figeys, Daniel; Andrews, Brenda

2014-01-01

SUMMARY Lysine acetylation is a dynamic posttranslational modification with a well-defined role in regulating histones. The impact of acetylation on other cellular functions remains relatively uncharacterized. We explored the budding yeast acetylome with a functional genomics approach, assessing the effects of gene overexpression in the absence of lysine deacetylases (KDACs). We generated a network of 463 synthetic dosage lethal (SDL) interactions involving class I and II KDACs, revealing many cellular pathways regulated by different KDACs. A biochemical survey of genes interacting with the KDAC RPD3 identified 72 proteins acetylated in vivo. In-depth analysis of one of these proteins, Swi4, revealed a role for acetylation in G1-specific gene expression. Acetylation of Swi4 regulates interaction with its partner Swi6, both components of the SBF transcription factor. This study expands our view of the yeast acetylome, demonstrates the utility of functional genomic screens for exploring enzymatic pathways, and provides functional information that can be mined for future studies. PMID:22579291

The Reconstruction and Analysis of Gene Regulatory Networks.

PubMed

Zheng, Guangyong; Huang, Tao

2018-01-01

In post-genomic era, an important task is to explore the function of individual biological molecules (i.e., gene, noncoding RNA, protein, metabolite) and their organization in living cells. For this end, gene regulatory networks (GRNs) are constructed to show relationship between biological molecules, in which the vertices of network denote biological molecules and the edges of network present connection between nodes (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). Biologists can understand not only the function of biological molecules but also the organization of components of living cells through interpreting the GRNs, since a gene regulatory network is a comprehensively physiological map of living cells and reflects influence of genetic and epigenetic factors (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). In this paper, we will review the inference methods of GRN reconstruction and analysis approaches of network structure. As a powerful tool for studying complex diseases and biological processes, the applications of the network method in pathway analysis and disease gene identification will be introduced.

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes

PubMed Central

McKay, James D.; Hung, Rayjean J.; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C.; Caporaso, Neil E.; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A.; Qian, David C.; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N.; Bojesen, Stig E.; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C.; Bush, William S.; Tardon, Adonina; Rennert, Gad; Teare, M. Dawn; Field, John K.; Kiemeney, Lambertus A.; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B.; Andrew, Angeline S.; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C.; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S.; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A.; Wilkens, Lynne R.; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F.M.; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael PA; Marcus, Michael W.; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C.; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A.; Barnett, Matt P.; Chen, Chu; Goodman, Gary E.; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H.-Erich; Manz, Judith; Muley, Thomas R.; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A.; Tsao, Ming-Sound; Arnold, Susanne M.; Haura, Eric B.; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M.; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J.; Butler, Lesley M.; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S.; McLaughlin, John; Stevens, Victoria L.; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C.; Obeidat, Ma’en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D.; Wain, Louise V.; Rafnar, Thorunn; Thorgeirsson, Thorgeir E.; Reginsson, Gunnar W.; Stefansson, Kari; Hancock, Dana B.; Bierut, Laura J.; Spitz, Margaret R.; Gaddis, Nathan C.; Lutz, Sharon M.; Gu, Fangyi; Johnson, Eric O.; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F.; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I.

2017-01-01

Summary While several lung cancer susceptibility loci have been identified, much of lung cancer heritability remains unexplained. Here, 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated GWAS analysis of lung cancer on 29,266 patients and 56,450 controls. We identified 18 susceptibility loci achieving genome wide significance, including 10 novel loci. The novel loci highlighted the striking heterogeneity in genetic susceptibility across lung cancer histological subtypes, with four loci associated with lung cancer overall and six with lung adenocarcinoma. Gene expression quantitative trait analysis (eQTL) in 1,425 normal lung tissues highlighted RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes, OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer. PMID:28604730

Identification of key candidate genes and pathways in hepatitis B virus-associated acute liver failure by bioinformatical analysis

PubMed Central

Lin, Huapeng; Zhang, Qian; Li, Xiaocheng; Wu, Yushen; Liu, Ye; Hu, Yingchun

2018-01-01

Abstract Hepatitis B virus-associated acute liver failure (HBV-ALF) is a rare but life-threatening syndrome that carried a high morbidity and mortality. Our study aimed to explore the possible molecular mechanisms of HBV-ALF by means of bioinformatics analysis. In this study, genes expression microarray datasets of HBV-ALF from Gene Expression Omnibus were collected, and then we identified differentially expressed genes (DEGs) by the limma package in R. After functional enrichment analysis, we constructed the protein–protein interaction (PPI) network by the Search Tool for the Retrieval of Interacting Genes online database and weighted genes coexpression network by the WGCNA package in R. Subsequently, we picked out the hub genes among the DEGs. A total of 423 DEGs with 198 upregulated genes and 225 downregulated genes were identified between HBV-ALF and normal samples. The upregulated genes were mainly enriched in immune response, and the downregulated genes were mainly enriched in complement and coagulation cascades. Orosomucoid 1 (ORM1), orosomucoid 2 (ORM2), plasminogen (PLG), and aldehyde oxidase 1 (AOX1) were picked out as the hub genes that with a high degree in both PPI network and weighted genes coexpression network. The weighted genes coexpression network analysis found out 3 of the 5 modules that upregulated genes enriched in were closely related to immune system. The downregulated genes enriched in only one module, and the genes in this module majorly enriched in the complement and coagulation cascades pathway. In conclusion, 4 genes (ORM1, ORM2, PLG, and AOX1) with immune response and the complement and coagulation cascades pathway may take part in the pathogenesis of HBV-ALF, and these candidate genes and pathways could be therapeutic targets for HBV-ALF. PMID:29384847

Analysis of the Human Prostate-Specific Proteome Defined by Transcriptomics and Antibody-Based Profiling Identifies TMEM79 and ACOXL as Two Putative, Diagnostic Markers in Prostate Cancer

PubMed Central

O'Hurley, Gillian; Busch, Christer; Fagerberg, Linn; Hallström, Björn M.; Stadler, Charlotte; Tolf, Anna; Lundberg, Emma; Schwenk, Jochen M.; Jirström, Karin; Bjartell, Anders; Gallagher, William M.; Uhlén, Mathias; Pontén, Fredrik

2015-01-01

To better understand prostate function and disease, it is important to define and explore the molecular constituents that signify the prostate gland. The aim of this study was to define the prostate specific transcriptome and proteome, in comparison to 26 other human tissues. Deep sequencing of mRNA (RNA-seq) and immunohistochemistry-based protein profiling were combined to identify prostate specific gene expression patterns and to explore tissue biomarkers for potential clinical use in prostate cancer diagnostics. We identified 203 genes with elevated expression in the prostate, 22 of which showed more than five-fold higher expression levels compared to all other tissue types. In addition to previously well-known proteins we identified two poorly characterized proteins, TMEM79 and ACOXL, with potential to differentiate between benign and cancerous prostatic glands in tissue biopsies. In conclusion, we have applied a genome-wide analysis to identify the prostate specific proteome using transcriptomics and antibody-based protein profiling to identify genes with elevated expression in the prostate. Our data provides a starting point for further functional studies to explore the molecular repertoire of normal and diseased prostate including potential prostate cancer markers such as TMEM79 and ACOXL. PMID:26237329

NetGen: a novel network-based probabilistic generative model for gene set functional enrichment analysis.

PubMed

Sun, Duanchen; Liu, Yinliang; Zhang, Xiang-Sun; Wu, Ling-Yun

2017-09-21

High-throughput experimental techniques have been dramatically improved and widely applied in the past decades. However, biological interpretation of the high-throughput experimental results, such as differential expression gene sets derived from microarray or RNA-seq experiments, is still a challenging task. Gene Ontology (GO) is commonly used in the functional enrichment studies. The GO terms identified via current functional enrichment analysis tools often contain direct parent or descendant terms in the GO hierarchical structure. Highly redundant terms make users difficult to analyze the underlying biological processes. In this paper, a novel network-based probabilistic generative model, NetGen, was proposed to perform the functional enrichment analysis. An additional protein-protein interaction (PPI) network was explicitly used to assist the identification of significantly enriched GO terms. NetGen achieved a superior performance than the existing methods in the simulation studies. The effectiveness of NetGen was explored further on four real datasets. Notably, several GO terms which were not directly linked with the active gene list for each disease were identified. These terms were closely related to the corresponding diseases when accessed to the curated literatures. NetGen has been implemented in the R package CopTea publicly available at GitHub ( http://github.com/wulingyun/CopTea/ ). Our procedure leads to a more reasonable and interpretable result of the functional enrichment analysis. As a novel term combination-based functional enrichment analysis method, NetGen is complementary to current individual term-based methods, and can help to explore the underlying pathogenesis of complex diseases.

Longitudinal Analysis of Whole Blood Transcriptomes to Explore Molecular Signatures Associated With Acute Renal Allograft Rejection

PubMed Central

Shin, Heesun; Günther, Oliver; Hollander, Zsuzsanna; Wilson-McManus, Janet E.; Ng, Raymond T.; Balshaw, Robert; Keown, Paul A.; McMaster, Robert; McManus, Bruce M.; Isbel, Nicole M.; Knoll, Greg; Tebbutt, Scott J.

2014-01-01

In this study, we explored a time course of peripheral whole blood transcriptomes from kidney transplantation patients who either experienced an acute rejection episode or did not in order to better delineate the immunological and biological processes measureable in blood leukocytes that are associated with acute renal allograft rejection. Using microarrays, we generated gene expression data from 24 acute rejectors and 24 nonrejectors. We filtered the data to obtain the most unambiguous and robustly expressing probe sets and selected a subset of patients with the clearest phenotype. We then performed a data-driven exploratory analysis using data reduction and differential gene expression analysis tools in order to reveal gene expression signatures associated with acute allograft rejection. Using a template-matching algorithm, we then expanded our analysis to include time course data, identifying genes whose expression is modulated leading up to acute rejection. We have identified molecular phenotypes associated with acute renal allograft rejection, including a significantly upregulated signature of neutrophil activation and accumulation following transplant surgery that is common to both acute rejectors and nonrejectors. Our analysis shows that this expression signature appears to stabilize over time in nonrejectors but persists in patients who go on to reject the transplanted organ. In addition, we describe an expression signature characteristic of lymphocyte activity and proliferation. This lymphocyte signature is significantly downregulated in both acute rejectors and nonrejectors following surgery; however, patients who go on to reject the organ show a persistent downregulation of this signature relative to the neutrophil signature. PMID:24526836

Systematic analysis of gene expression pattern in has-miR-197 over-expressed human uterine leiomyoma cells.

PubMed

Ling, Jing; Wu, Xiaoli; Fu, Ziyi; Tan, Jie; Xu, Qing

2015-10-01

Our previous study showed that the expression of miR-197 in leiomyoma was down-regulated compared with myometrium. Further, miR-197 has been identified to affect uterine leiomyoma cell proliferation, apoptosis, and metastasis ability, though the responsible molecular mechanism has not been well elucidated. In this study, we sought to determine the expression patterns of miR-197 targeted genes and to explore their potential functions, participating Pathways and the networks that are involved in the biological behavior of human uterine leiomyoma. After transfection of human uterine leiomyoma cells with miR-197, we confirmed the expression level of miR-197 using quantitative real-time PCR (qRT-PCR), and we detected the gene expression profiles after miR-197 over-expression through DNA microarray analysis. Further, we performed GO and Pathway analysis. The dominantly dys-regulated genes, which were up- or down-regulated by more than 10-fold, compared with parental cells, were confirmed using qRT-PCR technology. Compared with the control group, miR-197 was up-regulated by 30-fold after miR-197 lentiviral transfection. The microarray data showed that 872 genes were dys-regulated by more than 2-fold in human uterine leiomyoma cells after miR-197 overexpression, including 537 up-regulated and 335 down-regulated genes. The GO analysis indicated that the dys-regulated genes were primarily involved in response to stimuli, multicellular organ processes, and the signaling of biological progression. Further, Pathway analysis data showed that these genes participated in regulating several signaling Pathways, including the JAK/STAT signaling Pathway, the Toll-like receptor signaling Pathway, and cytokine-cytokine receptor interaction. The qRT-PCR results confirmed that 17 of the 66 selected genes, which were up- or down-regulated more than 10-fold by miR-197, were consistent with the microarray results, including tumorigenesis-related genes, such as DRT7, SLC549, SFMBT2, FLJ37956, FBLN2, C10orf35, HOXD12, CACNG7, and LOC100134279. Our study explored gene expression patterns after miR-197 overexpression and confirmed 17 dominantly dys-regulated genes, which could expand the insights into the function of miR-197 and the molecular mechanisms during the development and progression of uterine leiomyomas. This study might afford new clues for understanding the pathogenesis of uterine leiomyomas, and it could likely provide a unique method for diagnosing or predicting prognosis in the clinical treatment of leiomyoma. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Transcriptome analysis of PCOS arrested 2-cell embryos.

PubMed

Lu, Cuiling; Chi, Hongbin; Wang, Yapeng; Feng, Xue; Wang, Lina; Huang, Shuo; Yan, Liying; Lin, Shengli; Liu, Ping; Qiao, Jie

2018-06-18

In an attempt to explore the early developmental arrest in embryos from polycystic ovarian syndrome (PCOS) patients, we sequenced the transcriptome profiles of PCOS arrested 2-cell embryos, non-PCOS arrested 2-cell embryos and non-arrested 2-cell embryos using single-cell RNA-Seq technique. Differential expression analysis was performed using the DEGSeq R package. Gene Ontology (GO) enrichment was analyzed using the GOseq R package. Data revealed 62 differentially expressed genes between non-PCOS arrested and PCOS arrested embryos and 2217 differentially expressed genes between PCOS arrested and non-arrested 2-cell embryos. A total of 49 differently expressed genes (DEGs) were annotated with GO terms in the up-regulated genes between PCOS arrested and non-PCOS arrested embryos after GO enrichment. A total of 29 DEGs were annotated with GO terms in the down-regulated genes between PCOS arrested and non-arrested 2-cell embryos after GO enrichment. These data can provide a reference for screening specific genes involved in the arrest of PCOS embryos.

Analysis of the Metabolic Pathways Affected by Poly(γ-glutamic Acid) in Arabidopsis thaliana Based on GeneChip Microarray.

PubMed

Xu, Zongqi; Lei, Peng; Feng, Xiaohai; Li, Sha; Xu, Hong

2016-08-17

Plant growth is promoted by poly(γ-glutamic acid) (γ-PGA). However, the molecular mechanism underlying such promotion is not yet well understood. Therefore, we used GeneChip microarrays to explore the effects of γ-PGA on gene transcription in Arabidopsis thaliana. Our results revealed 299 genes significantly regulated by γ-PGA. These differently expressed genes participate mainly in metabolic and cellular processes and in stimuli responses. The metabolic pathways linked to these differently expressed genes were also investigated. A total of 64 of the 299 differently expressed genes were shown to be directly involved in 24 pathways such as brassinosteroid biosynthesis, α-linolenic acid metabolism, phenylpropanoid biosynthesis, and nitrogen metabolism, all of which were influenced by γ-PGA. The analysis demonstrated that γ-PGA promoted nitrogen assimilation and biosynthesis of brassinosteroids, jasmonic acid, and lignins, providing a better explanation for why γ-PGA promotes growth and enhances stress tolerance in plants.

Gene Ranking of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization.

PubMed

Jia, Zhilong; Zhang, Xiang; Guan, Naiyang; Bo, Xiaochen; Barnes, Michael R; Luo, Zhigang

2015-01-01

RNA-sequencing is rapidly becoming the method of choice for studying the full complexity of transcriptomes, however with increasing dimensionality, accurate gene ranking is becoming increasingly challenging. This paper proposes an accurate and sensitive gene ranking method that implements discriminant non-negative matrix factorization (DNMF) for RNA-seq data. To the best of our knowledge, this is the first work to explore the utility of DNMF for gene ranking. When incorporating Fisher's discriminant criteria and setting the reduced dimension as two, DNMF learns two factors to approximate the original gene expression data, abstracting the up-regulated or down-regulated metagene by using the sample label information. The first factor denotes all the genes' weights of two metagenes as the additive combination of all genes, while the second learned factor represents the expression values of two metagenes. In the gene ranking stage, all the genes are ranked as a descending sequence according to the differential values of the metagene weights. Leveraging the nature of NMF and Fisher's criterion, DNMF can robustly boost the gene ranking performance. The Area Under the Curve analysis of differential expression analysis on two benchmarking tests of four RNA-seq data sets with similar phenotypes showed that our proposed DNMF-based gene ranking method outperforms other widely used methods. Moreover, the Gene Set Enrichment Analysis also showed DNMF outweighs others. DNMF is also computationally efficient, substantially outperforming all other benchmarked methods. Consequently, we suggest DNMF is an effective method for the analysis of differential gene expression and gene ranking for RNA-seq data.

A Parallel Genetic Algorithm to Discover Patterns in Genetic Markers that Indicate Predisposition to Multifactorial Disease

PubMed Central

Rausch, Tobias; Thomas, Alun; Camp, Nicola J.; Cannon-Albright, Lisa A.; Facelli, Julio C.

2008-01-01

This paper describes a novel algorithm to analyze genetic linkage data using pattern recognition techniques and genetic algorithms (GA). The method allows a search for regions of the chromosome that may contain genetic variations that jointly predispose individuals for a particular disease. The method uses correlation analysis, filtering theory and genetic algorithms (GA) to achieve this goal. Because current genome scans use from hundreds to hundreds of thousands of markers, two versions of the method have been implemented. The first is an exhaustive analysis version that can be used to visualize, explore, and analyze small genetic data sets for two marker correlations; the second is a GA version, which uses a parallel implementation allowing searches of higher-order correlations in large data sets. Results on simulated data sets indicate that the method can be informative in the identification of major disease loci and gene-gene interactions in genome-wide linkage data and that further exploration of these techniques is justified. The results presented for both variants of the method show that it can help genetic epidemiologists to identify promising combinations of genetic factors that might predispose to complex disorders. In particular, the correlation analysis of IBD expression patterns might hint to possible gene-gene interactions and the filtering might be a fruitful approach to distinguish true correlation signals from noise. PMID:18547558

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma

PubMed Central

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-01-01

Objective This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Methods Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Results Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification (P=0.009) or deletion (P=0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly (P=1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Conclusion Chromosomal CNVs may contribute to their transcript expression in cervical cancer. PMID:29312578

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma.

PubMed

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-12-12

This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification ( P =0.009) or deletion ( P =0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly ( P =1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Chromosomal CNVs may contribute to their transcript expression in cervical cancer.

Mining microarray data at NCBI's Gene Expression Omnibus (GEO)*.

PubMed

Barrett, Tanya; Edgar, Ron

2006-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data

PubMed Central

Yi, Ming; Horton, Jay D; Cohen, Jonathan C; Hobbs, Helen H; Stephens, Robert M

2006-01-01

Background Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data. Result WPS extracts gene lists with shared biological themes through color cue templates. WPS statistically evaluates global functional category enrichment of gene lists and pathway-level pattern enrichment of data. WPS incorporates well-known biological pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes) and Biocarta, GO (Gene Ontology) terms as well as user-defined pathways or relevant gene clusters or groups, and explores gene-term relationships within the derived gene-term association networks (GTANs). WPS simultaneously compares multiple datasets within biological contexts either as pathways or as association networks. WPS also integrates Genetic Association Database and Partial MedGene Database for disease-association information. We have used this program to analyze and compare microarray and proteomics datasets derived from a variety of biological systems. Application examples demonstrated the capacity of WPS to significantly facilitate the analysis of HTP data for integrative discovery. Conclusion This tool represents a pathway-based platform for discovery integration to maximize analysis power. The tool is freely available at . PMID:16423281

Dynamic gene expression analysis in a H1N1 influenza virus mouse pneumonia model.

PubMed

Bao, Yanyan; Gao, Yingjie; Shi, Yujing; Cui, Xiaolan

2017-06-01

H1N1, a major pathogenic subtype of influenza A virus, causes a respiratory infection in humans and livestock that can range from a mild infection to more severe pneumonia associated with acute respiratory distress syndrome. Understanding the dynamic changes in the genome and the related functional changes induced by H1N1 influenza virus infection is essential to elucidating the pathogenesis of this virus and thereby determining strategies to prevent future outbreaks. In this study, we filtered the significantly expressed genes in mouse pneumonia using mRNA microarray analysis. Using STC analysis, seven significant gene clusters were revealed, and using STC-GO analysis, we explored the significant functions of these seven gene clusters. The results revealed GOs related to H1N1 virus-induced inflammatory and immune functions, including innate immune response, inflammatory response, specific immune response, and cellular response to interferon-beta. Furthermore, the dynamic regulation relationships of the key genes in mouse pneumonia were revealed by dynamic gene network analysis, and the most important genes were filtered, including Dhx58, Cxcl10, Cxcl11, Zbp1, Ifit1, Ifih1, Trim25, Mx2, Oas2, Cd274, Irgm1, and Irf7. These results suggested that during mouse pneumonia, changes in the expression of gene clusters and the complex interactions among genes lead to significant changes in function. Dynamic gene expression analysis revealed key genes that performed important functions. These results are a prelude to advancements in mouse H1N1 influenza virus infection biology, as well as the use of mice as a model organism for human H1N1 influenza virus infection studies.

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.

Insights into the Ecology and Evolution of Polyploid Plants through Network Analysis.

PubMed

Gallagher, Joseph P; Grover, Corrinne E; Hu, Guanjing; Wendel, Jonathan F

2016-06-01

Polyploidy is a widespread phenomenon throughout eukaryotes, with important ecological and evolutionary consequences. Although genes operate as components of complex pathways and networks, polyploid changes in genes and gene expression have typically been evaluated as either individual genes or as a part of broad-scale analyses. Network analysis has been fruitful in associating genomic and other 'omic'-based changes with phenotype for many systems. In polyploid species, network analysis has the potential not only to facilitate a better understanding of the complex 'omic' underpinnings of phenotypic and ecological traits common to polyploidy, but also to provide novel insight into the interaction among duplicated genes and genomes. This adds perspective to the global patterns of expression (and other 'omic') change that accompany polyploidy and to the patterns of recruitment and/or loss of genes following polyploidization. While network analysis in polyploid species faces challenges common to other analyses of duplicated genomes, present technologies combined with thoughtful experimental design provide a powerful system to explore polyploid evolution. Here, we demonstrate the utility and potential of network analysis to questions pertaining to polyploidy with an example involving evolution of the transgressively superior cotton fibres found in polyploid Gossypium hirsutum. By combining network analysis with prior knowledge, we provide further insights into the role of profilins in fibre domestication and exemplify the potential for network analysis in polyploid species. © 2016 John Wiley & Sons Ltd.

Gene Expression Profiling of Lung Tissue of Rats Exposed to Lunar Dust Particles

NASA Technical Reports Server (NTRS)

Zhang, Ye; Feiveson, Alan H.; Lam, Chiu-Wing; Kidane, Yared H.; Ploutz-Snyder Robert; Yeshitla, Samrawit; Zalesak, Selina M.; Scully, Robert R.; Wu, Honglu; James, John T.

2014-01-01

The purpose of the study is to analyze the dynamics of global gene expression changes in the lung tissue of rats exposed to lunar dust particles. Multiple pathways and transcription factors were identified using the Ingenuity Pathway Analysis tool, showing the potential networks of these signaling regulations involved in lunar dust-induced prolonged proflammatory response and toxicity. The data presented in this study, for the first time, explores the molecular mechanisms of lunar dust induced toxicity. This work contributes not only to the risk assessment for future space exploration, but also to the understanding of the dust-induced toxicity to humans on earth.

Analysis of the Prefoldin Gene Family in 14 Plant Species

PubMed Central

Cao, Jun

2016-01-01

Prefoldin is a hexameric molecular chaperone complex present in all eukaryotes and archaea. The evolution of this gene family in plants is unknown. Here, I identified 140 prefoldin genes in 14 plant species. These prefoldin proteins were divided into nine groups through phylogenetic analysis. Highly conserved gene organization and motif distribution exist in each prefoldin group, implying their functional conservation. I also observed the segmental duplication of maize prefoldin gene family. Moreover, a few functional divergence sites were identified within each group pairs. Functional network analyses identified 78 co-expressed genes, and most of them were involved in carrying, binding and kinase activity. Divergent expression profiles of the maize prefoldin genes were further investigated in different tissues and development periods and under auxin and some abiotic stresses. I also found a few cis-elements responding to abiotic stress and phytohormone in the upstream sequences of the maize prefoldin genes. The results provided a foundation for exploring the characterization of the prefoldin genes in plants and will offer insights for additional functional studies. PMID:27014333

Joint mapping of genes and conditions via multidimensional unfolding analysis

PubMed Central

Van Deun, Katrijn; Marchal, Kathleen; Heiser, Willem J; Engelen, Kristof; Van Mechelen, Iven

2007-01-01

Background Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding. Results We present a novel algorithm for multidimensional unfolding that overcomes both general problems and problems that are specific for the analysis of gene expression data sets. Applying the algorithm to two publicly available microarray compendia illustrates its power as a tool for exploratory data analysis: The unfolding analysis of a first data set resulted in a two-dimensional representation which clearly reveals temporal regulation patterns for the genes and a meaningful structure for the time points, while the analysis of a second data set showed the algorithm's ability to go beyond a mere identification of those genes that discriminate between different patient or tissue types. Conclusion Multidimensional unfolding offers a useful tool for preliminary explorations of microarray data: By relying on an easy-to-grasp low-dimensional geometric framework, relations among genes, among conditions and between genes and conditions are simultaneously represented in an accessible way which may reveal interesting patterns in the data. An additional advantage of the method is that it can be applied to the raw data without necessitating the choice of suitable genewise transformations of the data. PMID:17550582

Evolutionary analysis of the jacalin-related lectin family genes in 11 fishes.

PubMed

Cao, Jun; Lv, Yueqing

2016-09-01

Jacalin-related lectins are a type of carbohydrate-binding proteins, which are distributed across a wide variety of organisms and involved in some important biological processes. The evolution of this gene family in fishes is unknown. Here, 47 putative jacalin genes in 11 fish species were identified and divided into 4 groups through phylogenetic analysis. Conserved gene organization and motif distribution existed in each group, suggesting their functional conservation. Some fishes have eleven jacalin genes, while others have only one or zero gene in their genomes, suggesting dynamic changes in the number of jacalin genes during the evolution of fishes. Intragenic recombination played a key role in the evolution of jacalin genes. Synteny analyses of jacalin genes in some fishes implied conserved and dynamic evolution characteristics of this gene family and related genome segments. Moreover, a few functional divergence sites were identified within each group pairs. Divergent expression profiles of the zebra fish jacalin genes were further investigated in different stresses. The results provided a foundation for exploring the characterization of the jacalin genes in fishes and will offer insights for additional functional studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparative genomic analysis of the WRKY III gene family in populus, grape, arabidopsis and rice.

PubMed

Wang, Yiyi; Feng, Lin; Zhu, Yuxin; Li, Yuan; Yan, Hanwei; Xiang, Yan

2015-09-08

WRKY III genes have significant functions in regulating plant development and resistance. In plant, WRKY gene family has been studied in many species, however, there still lack a comprehensive analysis of WRKY III genes in the woody plant species poplar, three representative lineages of flowering plant species are incorporated in most analyses: Arabidopsis (a model plant for annual herbaceous dicots), grape (one model plant for perennial dicots) and Oryza sativa (a model plant for monocots). In this study, we identified 10, 6, 13 and 28 WRKY III genes in the genomes of Populus trichocarpa, grape (Vitis vinifera), Arabidopsis thaliana and rice (Oryza sativa), respectively. Phylogenetic analysis revealed that the WRKY III proteins could be divided into four clades. By microsynteny analysis, we found that the duplicated regions were more conserved between poplar and grape than Arabidopsis or rice. We dated their duplications by Ks analysis of Populus WRKY III genes and demonstrated that all the blocks were formed after the divergence of monocots and dicots. Strong purifying selection has played a key role in the maintenance of WRKY III genes in Populus. Tissue expression analysis of the WRKY III genes in Populus revealed that five were most highly expressed in the xylem. We also performed quantitative real-time reverse transcription PCR analysis of WRKY III genes in Populus treated with salicylic acid, abscisic acid and polyethylene glycol to explore their stress-related expression patterns. This study highlighted the duplication and diversification of the WRKY III gene family in Populus and provided a comprehensive analysis of this gene family in the Populus genome. Our results indicated that the majority of WRKY III genes of Populus was expanded by large-scale gene duplication. The expression pattern of PtrWRKYIII gene identified that these genes play important roles in the xylem during poplar growth and development, and may play crucial role in defense to drought stress. Our results presented here may aid in the selection of appropriate candidate genes for further characterization of their biological functions in poplar.

Comprehensive Exploration of Novel Chimeric Transcripts in Clear Cell Renal Cell Carcinomas Using Whole Transcriptome Analysis

PubMed Central

Gotoh, Masahiro; Ichikawa, Hitoshi; Arai, Eri; Chiku, Suenori; Sakamoto, Hiromi; Fujimoto, Hiroyuki; Hiramoto, Masaki; Nammo, Takao; Yasuda, Kazuki; Yoshida, Teruhiko; Kanai, Yae

2014-01-01

The aim of this study was to clarify the participation of expression of chimeric transcripts in renal carcinogenesis. Whole transcriptome analysis (RNA sequencing) and exploration of candidate chimeric transcripts using the deFuse program were performed on 68 specimens of cancerous tissue (T) and 11 specimens of non-cancerous renal cortex tissue (N) obtained from 68 patients with clear cell renal cell carcinomas (RCCs) in an initial cohort. As positive controls, two RCCs associated with Xp11.2 translocation were analyzed. After verification by reverse transcription (RT)-PCR and Sanger sequencing, 26 novel chimeric transcripts were identified in 17 (25%) of the 68 clear cell RCCs. Genomic breakpoints were determined in five of the chimeric transcripts. Quantitative RT-PCR analysis revealed that the mRNA expression levels for the MMACHC, PTER, EPC2, ATXN7, FHIT, KIFAP3, CPEB1, MINPP1, TEX264, FAM107A, UPF3A, CDC16, MCCC1, CPSF3, and ASAP2 genes, being partner genes involved in the chimeric transcripts in the initial cohort, were significantly reduced in 26 T samples relative to the corresponding 26 N samples in the second cohort. Moreover, the mRNA expression levels for the above partner genes in T samples were significantly correlated with tumor aggressiveness and poorer patient outcome, indicating that reduced expression of these genes may participate in malignant progression of RCCs. As is the case when their levels of expression are reduced, these partner genes also may not fully function when involved in chimeric transcripts. These data suggest that generation of chimeric transcripts may participate in renal carcinogenesis by inducing dysfunction of tumor-related genes. PMID:25230976

Targeted exploration and analysis of large cross-platform human transcriptomic compendia

PubMed Central

Zhu, Qian; Wong, Aaron K; Krishnan, Arjun; Aure, Miriam R; Tadych, Alicja; Zhang, Ran; Corney, David C; Greene, Casey S; Bongo, Lars A; Kristensen, Vessela N; Charikar, Moses; Li, Kai; Troyanskaya, Olga G.

2016-01-01

We present SEEK (http://seek.princeton.edu), a query-based search engine across very large transcriptomic data collections, including thousands of human data sets from almost 50 microarray and next-generation sequencing platforms. SEEK uses a novel query-level cross-validation-based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify query-coregulated genes, pathways, and processes. SEEK provides cross-platform handling, multi-gene query search, iterative metadata-based search refinement, and extensive visualization-based analysis options. PMID:25581801

An eQTL Analysis of Partial Resistance to Puccinia hordei in Barley

PubMed Central

Chen, Xinwei; Hackett, Christine A.; Niks, Rients E.; Hedley, Peter E.; Booth, Clare; Druka, Arnis; Marcel, Thierry C.; Vels, Anton; Bayer, Micha; Milne, Iain; Morris, Jenny; Ramsay, Luke; Marshall, David; Cardle, Linda; Waugh, Robbie

2010-01-01

Background Genetic resistance to barley leaf rust caused by Puccinia hordei involves both R genes and quantitative trait loci. The R genes provide higher but less durable resistance than the quantitative trait loci. Consequently, exploring quantitative or partial resistance has become a favorable alternative for controlling disease. Four quantitative trait loci for partial resistance to leaf rust have been identified in the doubled haploid Steptoe (St)/Morex (Mx) mapping population. Further investigations are required to study the molecular mechanisms underpinning partial resistance and ultimately identify the causal genes. Methodology/Principal Findings We explored partial resistance to barley leaf rust using a genetical genomics approach. We recorded RNA transcript abundance corresponding to each probe on a 15K Agilent custom barley microarray in seedlings from St and Mx and 144 doubled haploid lines of the St/Mx population. A total of 1154 and 1037 genes were, respectively, identified as being P. hordei-responsive among the St and Mx and differentially expressed between P. hordei-infected St and Mx. Normalized ratios from 72 distant-pair hybridisations were used to map the genetic determinants of variation in transcript abundance by expression quantitative trait locus (eQTL) mapping generating 15685 eQTL from 9557 genes. Correlation analysis identified 128 genes that were correlated with resistance, of which 89 had eQTL co-locating with the phenotypic quantitative trait loci (pQTL). Transcript abundance in the parents and conservation of synteny with rice allowed us to prioritise six genes as candidates for Rphq11, the pQTL of largest effect, and highlight one, a phospholipid hydroperoxide glutathione peroxidase (HvPHGPx) for detailed analysis. Conclusions/Significance The eQTL approach yielded information that led to the identification of strong candidate genes underlying pQTL for resistance to leaf rust in barley and on the general pathogen response pathway. The dataset will facilitate a systems appraisal of this host-pathogen interaction and, potentially, for other traits measured in this population. PMID:20066049

Genome-guided exploration of metabolic features of Streptomyces peucetius ATCC 27952: past, current, and prospect.

PubMed

Thuan, Nguyen Huy; Dhakal, Dipesh; Pokhrel, Anaya Raj; Chu, Luan Luong; Van Pham, Thi Thuy; Shrestha, Anil; Sohng, Jae Kyung

2018-05-01

Streptomyces peucetius ATCC 27952 produces two major anthracyclines, doxorubicin (DXR) and daunorubicin (DNR), which are potent chemotherapeutic agents for the treatment of several cancers. In order to gain detailed insight on genetics and biochemistry of the strain, the complete genome was determined and analyzed. The result showed that its complete sequence contains 7187 protein coding genes in a total of 8,023,114 bp, whereas 87% of the genome contributed to the protein coding region. The genomic sequence included 18 rRNA, 66 tRNAs, and 3 non-coding RNAs. In silico studies predicted ~ 68 biosynthetic gene clusters (BCGs) encoding diverse classes of secondary metabolites, including non-ribosomal polyketide synthase (NRPS), polyketide synthase (PKS I, II, and III), terpenes, and others. Detailed analysis of the genome sequence revealed versatile biocatalytic enzymes such as cytochrome P450 (CYP), electron transfer systems (ETS) genes, methyltransferase (MT), glycosyltransferase (GT). In addition, numerous functional genes (transporter gene, SOD, etc.) and regulatory genes (afsR-sp, metK-sp, etc.) involved in the regulation of secondary metabolites were found. This minireview summarizes the genome-based genome mining (GM) of diverse BCGs and genome exploration (GE) of versatile biocatalytic enzymes, and other enzymes involved in maintenance and regulation of metabolism of S. peucetius. The detailed analysis of genome sequence provides critically important knowledge useful in the bioengineering of the strain or harboring catalytically efficient enzymes for biotechnological applications.

Proteomic and transcriptomic analysis of lung tissue in OVA-challenged mice.

PubMed

Lee, Yongjin; Hwang, Yun-Ho; Kim, Kwang-Jin; Park, Ae-Kyung; Paik, Man-Jeong; Kim, Seong Hwan; Lee, Su Ui; Yee, Sung-Tae; Son, Young-Jin

2018-01-01

Asthma is a long term inflammatory disease of the airway of lungs characterized by variable airflow obstruction and bronchospasm. Asthma is caused by a complex combination of environmental and genetic interactions. In this study, we conducted proteomic analysis of samples derived from control and OVA challenged mice for environmental respiratory disease by using 2-D gel electrophoresis. In addition, we explored the genes associated with the environmental substances that cause respiratory disease and conducted RNA-seq by next-generation sequencing. Proteomic analysis revealed 7 up-regulated (keratin KB40, CRP, HSP27, chaperonin containing TCP-1, TCP-10, keratin, and albumin) and 3 down-regulated proteins (PLC-α, PLA2, and precursor ApoA-1). The expression diversity of many genes was found in the lung tissue of OVA challenged moue by RNA-seq. 146 genes were identified as significantly differentially expressed by OVA treatment, and 118 genes of the 146 differentially expressed genes were up-regulated and 28 genes were downregulated. These genes were related to inflammation, mucin production, and airway remodeling. The results presented herein enable diagnosis and the identification of quantitative markers to monitor the progression of environmental respiratory disease using proteomics and genomic approaches.

Transcriptomic analysis of differentially expressed genes in flower-buds of genetic male sterile and wild type cucumber by RNA sequencing.

PubMed

Han, Yike; Wang, Xianyun; Zhao, Fengyue; Gao, Shang; Wei, Aimin; Chen, Zhengwu; Liu, Nan; Zhang, Zhenxian; Du, Shengli

2018-05-01

Cucumber ( Cucumis sativus L. ) pollen development involves a diverse range of gene interactions between sporophytic and gametophytic tissues. Previous studies in our laboratory showed that male sterility was controlled by a single recessive nuclear gene, and occurred in pollen mother cell meiophase. To fully explore the global gene expression and identify genes related to male sterility, a RNA-seq analysis was adopted in this study. Young male flower-buds (1-2 mm in length) from genetic male sterility (GMS) mutant and homozygous fertile cucumber (WT) were collected for two sequencing libraries. Total 545 differentially expressed genes (DEGs), including 142 up-regulated DEGs and 403 down-regulated DEGs, were detected in two libraries (Fold Change ≥ 2, FDR < 0.01). These genes were involved in a variety of metabolic pathways, like ethylene-activated signaling pathway, sporopollenin biosynthetic pathway, cell cycle and DNA damage repair pathway. qRT-PCR analysis was performed and showed that the correlation between RNA-Seq and qRT-PCR was 0.876. These findings contribute to a better understanding of the mechanism that leads to GMS in cucumber.

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

Pathway-based analysis of GWAs data identifies association of sex determination genes with susceptibility to testicular germ cell tumors.

PubMed

Koster, Roelof; Mitra, Nandita; D'Andrea, Kurt; Vardhanabhuti, Saran; Chung, Charles C; Wang, Zhaoming; Loren Erickson, R; Vaughn, David J; Litchfield, Kevin; Rahman, Nazneen; Greene, Mark H; McGlynn, Katherine A; Turnbull, Clare; Chanock, Stephen J; Nathanson, Katherine L; Kanetsky, Peter A

2014-11-15

Genome-wide association (GWA) studies of testicular germ cell tumor (TGCT) have identified 18 susceptibility loci, some containing genes encoding proteins important in male germ cell development. Deletions of one of these genes, DMRT1, lead to male-to-female sex reversal and are associated with development of gonadoblastoma. To further explore genetic association with TGCT, we undertook a pathway-based analysis of SNP marker associations in the Penn GWAs (349 TGCT cases and 919 controls). We analyzed a custom-built sex determination gene set consisting of 32 genes using three different methods of pathway-based analysis. The sex determination gene set ranked highly compared with canonical gene sets, and it was associated with TGCT (FDRG = 2.28 × 10(-5), FDRM = 0.014 and FDRI = 0.008 for Gene Set Analysis-SNP (GSA-SNP), Meta-Analysis Gene Set Enrichment of Variant Associations (MAGENTA) and Improved Gene Set Enrichment Analysis for Genome-wide Association Study (i-GSEA4GWAS) analysis, respectively). The association remained after removal of DMRT1 from the gene set (FDRG = 0.0002, FDRM = 0.055 and FDRI = 0.009). Using data from the NCI GWA scan (582 TGCT cases and 1056 controls) and UK scan (986 TGCT cases and 4946 controls), we replicated these findings (NCI: FDRG = 0.006, FDRM = 0.014, FDRI = 0.033, and UK: FDRG = 1.04 × 10(-6), FDRM = 0.016, FDRI = 0.025). After removal of DMRT1 from the gene set, the sex determination gene set remains associated with TGCT in the NCI (FDRG = 0.039, FDRM = 0.050 and FDRI = 0.055) and UK scans (FDRG = 3.00 × 10(-5), FDRM = 0.056 and FDRI = 0.044). With the exception of DMRT1, genes in the sex determination gene set have not previously been identified as TGCT susceptibility loci in these GWA scans, demonstrating the complementary nature of a pathway-based approach for genome-wide analysis of TGCT. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Alteration of peripheral blood monocyte gene expression in humans following diesel exhaust inhalation

PubMed Central

Pettit, Ashley P.; Brooks, Andrew; Laumbach, Robert; Fiedler, Nancy; Wang, Qi; Strickland, Pamela Ohman; Madura, Kiran; Zhang, Junfeng; Kipen, Howard M.

2013-01-01

Context Epidemiologic associations between acutely increased cardiorespiratory morbidity and mortality and particulate air pollution are well established, but the effects of acute pollution exposure on human gene expression changes are not well understood. Objective In order to identify potential mechanisms underlying epidemiologic associations between air pollution and morbidity, we explored changes in gene expression in humans following inhalation of fresh diesel exhaust (DE), a model for particulate air pollution. Materials and methods Fourteen ethnically homogeneous (white males), young, healthy subjects underwent 60-min inhalation exposures on 2 separate days with clean filtered air (CA) or freshly generated and diluted DE at a concentration of 300 μg/m3 PM2.5. Prior to and 24 h following each session, whole blood was sampled and fractionated for peripheral blood mononuclear cell (PBMC) isolation, RNA extraction, and generation of cDNA, followed by hybridization with Agilent Whole Human Genome (4X44K) arrays. Results Oxidative stress and the ubiquitin proteasome pathway, as well as the coagulation system, were among hypothesized pathways identified by analysis of differentially expressed genes. Nine genes from these pathways were validated using real-time polymerase chain reaction (PCR) to compare fold change in expression between DE exposed and CA days. Quantitative gene fold changes generated by real-time PCR were directionally consistent with the fold changes from the microarray analysis. Discussion and conclusion Changes in gene expression connected with key oxidative stress, protein degradation, and coagulation pathways are likely to underlie observed physiologic and clinical outcomes and suggest specific avenues and sensitive time points for further physiologic exploration. PMID:22369193

In silico analysis of a novel MKRN3 missense mutation in familial central precocious puberty.

PubMed

Neocleous, Vassos; Shammas, Christos; Phelan, Marie M; Nicolaou, Stella; Phylactou, Leonidas A; Skordis, Nicos

2016-01-01

The onset of puberty is influenced by the interplay of stimulating and restraining factors, many of which have a genetic origin. Premature activation of the GnRH secretion in central precocious puberty (CPP) may arise either from gain-of-function mutations of the KISS1 and KISS1R genes or from loss-of-function manner mutations of the MKRN3 gene leading to MKRN3 deficiency. To explore the genetic causes responsible for CPP and the potential role of the RING finger protein 3 (MKRN3) gene. We investigated potential sequence variations in the intronless MKRN3 gene by Sanger sequencing of the entire 507 amino acid coding region of exon 1 in a family with two affected girls presented with CPP at the age of 6 and 5·7 years, respectively. A novel heterozygous g.Gly312Asp missense mutation in the MKRN3 gene was identified in these siblings. The imprinted MKRN3 missense mutation was also identified as expected in the unaffected father and followed as expected an imprinted mode of inheritance. In silico analysis of the altered missense variant using the computational algorithms Polyphen2, SIFT and Mutation Taster predicted a damage and pathogenic alteration causing CPP. The pathogenicity of the alteration at the protein level via an in silico structural model is also explored. A novel mutation in the MKRN3 gene in two sisters with CPP was identified, supporting the fundamental role of this gene in the suppression of the hypothalamic GnRH neurons. © 2015 John Wiley & Sons Ltd.

Inter- and Intraspecies Phylogenetic Analyses Reveal Extensive X–Y Gene Conversion in the Evolution of Gametologous Sequences of Human Sex Chromosomes

PubMed Central

Trombetta, Beniamino; Sellitto, Daniele; Scozzari, Rosaria; Cruciani, Fulvio

2014-01-01

It has long been believed that the male-specific region of the human Y chromosome (MSY) is genetically independent from the X chromosome. This idea has been recently dismissed due to the discovery that X–Y gametologous gene conversion may occur. However, the pervasiveness of this molecular process in the evolution of sex chromosomes has yet to be exhaustively analyzed. In this study, we explored how pervasive X–Y gene conversion has been during the evolution of the youngest stratum of the human sex chromosomes. By comparing about 0.5 Mb of human–chimpanzee gametologous sequences, we identified 19 regions in which extensive gene conversion has occurred. From our analysis, two major features of these emerged: 1) Several of them are evolutionarily conserved between the two species and 2) almost all of the 19 hotspots overlap with regions where X–Y crossing-over has been previously reported to be involved in sex reversal. Furthermore, in order to explore the dynamics of X–Y gametologous conversion in recent human evolution, we resequenced these 19 hotspots in 68 widely divergent Y haplogroups and used publicly available single nucleotide polymorphism data for the X chromosome. We found that at least ten hotspots are still active in humans. Hence, the results of the interspecific analysis are consistent with the hypothesis of widespread reticulate evolution within gametologous sequences in the differentiation of hominini sex chromosomes. In turn, intraspecific analysis demonstrates that X–Y gene conversion may modulate human sex-chromosome-sequence evolution to a greater extent than previously thought. PMID:24817545

The epigenetic promise for prostate cancer diagnosis.

PubMed

Van Neste, Leander; Herman, James G; Otto, Gaëtan; Bigley, Joseph W; Epstein, Jonathan I; Van Criekinge, Wim

2012-08-01

Prostate cancer is the most common cancer diagnosis in men and a leading cause of death. Improvements in disease management would have a significant impact and could be facilitated by the development of biomarkers, whether for diagnostic, prognostic, or predictive purposes. The blood-based prostate biomarker PSA has been part of clinical practice for over two decades, although it is surrounded by controversy. While debates of usefulness are ongoing, alternatives should be explored. Particularly with recent recommendations against routine PSA-testing, the time is ripe to explore promising biomarkers to yield a more efficient and accurate screening for detection and management of prostate cancer. Epigenetic changes, more specifically DNA methylation, are amongst the most common alterations in human cancer. These changes are associated with transcriptional silencing of genes, leading to an altered cellular biology. One gene in particular, GSTP1, has been widely studied in prostate cancer. Therefore a meta-analysis has been conducted to examine the role of this and other genes and the potential contribution to prostate cancer management and screening refinement. More than 30 independent, peer reviewed studies have reported a consistently high sensitivity and specificity of GSTP1 hypermethylation in prostatectomy or biopsy tissue. The meta-analysis combined and compared these results. GSTP1 methylation detection can serve an important role in prostate cancer managment. The meta-analysis clearly confirmed a link between tissue DNA hypermethylation of this and other genes and prostate cancer. Detection of DNA methylation in genes, including GSTP1, could serve an important role in clinical practice. Copyright © 2011 Wiley Periodicals, Inc.

Use of the Aspergillus oryzae actin gene promoter in a novel reporter system for exploring antifungal compounds and their target genes.

PubMed

Marui, Junichiro; Yoshimi, Akira; Hagiwara, Daisuke; Fujii-Watanabe, Yoshimi; Oda, Ken; Koike, Hideaki; Tamano, Koichi; Ishii, Tomoko; Sano, Motoaki; Machida, Masayuki; Abe, Keietsu

2010-08-01

Demand for novel antifungal drugs for medical and agricultural uses has been increasing because of the diversity of pathogenic fungi and the emergence of drug-resistant strains. Genomic resources for various living species, including pathogenic fungi, can be utilized to develop novel and effective antifungal compounds. We used Aspergillus oryzae as a model to construct a reporter system for exploring novel antifungal compounds and their target genes. The comprehensive gene expression analysis showed that the actin-encoding actB gene was transcriptionally highly induced by benomyl treatment. We therefore used the actB gene to construct a novel reporter system for monitoring responses to cytoskeletal stress in A. oryzae by introducing the actB promoter::EGFP fusion gene. Distinct fluorescence was observed in the reporter strain with minimum background noise in response to not only benomyl but also compounds inhibiting lipid metabolism that is closely related to cell membrane integrity. The fluorescent responses indicated that the reporter strain can be used to screen for lead compounds affecting fungal microtubule and cell membrane integrity, both of which are attractive antifungal targets. Furthermore, the reporter strain was shown to be technically applicable for identifying novel target genes of antifungal drugs triggering perturbation of fungal microtubules or membrane integrity.

Genetic analysis of the pedigrees and molecular defects of the GH-receptor gene in the Israeli cohort of patients with Laron syndrome.

PubMed

Shevah, Orit; Laron, Zvi

2006-08-01

Out of the 63 patients with Laron Syndrome ( LS) followed in our clinic we were able to perform a genetic analysis on 43 patients belonging to 28 families. Twenty-seven patients were Jews, eight were Arabs, one was Druze, and six were Caucasians from countries other then Israel. Consanguinity was found in 11 families. Molecular analysis of the growth hormone receptor gene was performed in 32 patients and 32 family members. From the study of the pedigrees, as well as the GH receptor gene analysis, we confirmed an earlier report from our group that LS is a recessively inherited disease. One patient with a classical phenotype of LS had a non-classical pattern of inheritance: R43X heterozygosity together with a heterozygous polymorphism G168G; a condition which needs further exploration.

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

PubMed

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

Analytical workflow profiling gene expression in murine macrophages

PubMed Central

Nixon, Scott E.; González-Peña, Dianelys; Lawson, Marcus A.; McCusker, Robert H.; Hernandez, Alvaro G.; O’Connor, Jason C.; Dantzer, Robert; Kelley, Keith W.

2015-01-01

Comprehensive and simultaneous analysis of all genes in a biological sample is a capability of RNA-Seq technology. Analysis of the entire transcriptome benefits from summarization of genes at the functional level. As a cellular response of interest not previously explored with RNA-Seq, peritoneal macrophages from mice under two conditions (control and immunologically challenged) were analyzed for gene expression differences. Quantification of individual transcripts modeled RNA-Seq read distribution and uncertainty (using a Beta Negative Binomial distribution), then tested for differential transcript expression (False Discovery Rate-adjusted p-value < 0.05). Enrichment of functional categories utilized the list of differentially expressed genes. A total of 2079 differentially expressed transcripts representing 1884 genes were detected. Enrichment of 92 categories from Gene Ontology Biological Processes and Molecular Functions, and KEGG pathways were grouped into 6 clusters. Clusters included defense and inflammatory response (Enrichment Score = 11.24) and ribosomal activity (Enrichment Score = 17.89). Our work provides a context to the fine detail of individual gene expression differences in murine peritoneal macrophages during immunological challenge with high throughput RNA-Seq. PMID:25708305

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features.

PubMed

Haakensen, Vilde D; Lingjaerde, Ole Christian; Lüders, Torben; Riis, Margit; Prat, Aleix; Troester, Melissa A; Holmen, Marit M; Frantzen, Jan Ole; Romundstad, Linda; Navjord, Dina; Bukholm, Ida K; Johannesen, Tom B; Perou, Charles M; Ursin, Giske; Kristensen, Vessela N; Børresen-Dale, Anne-Lise; Helland, Aslaug

2011-11-01

Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer.

Expression of fox-related genes in the skin follicles of Inner Mongolia cashmere goat.

PubMed

Han, Wenjing; Li, Xiaoyan; Wang, Lele; Wang, Honghao; Yang, Kun; Wang, Zhixin; Wang, Ruijun; Su, Rui; Liu, Zhihong; Zhao, Yanhong; Zhang, Yanjun; Li, Jinquan

2018-03-01

This study investigated the expression of genes in cashmere goats at different periods of their fetal development. Bioinformatics analysis was used to evaluate data obtained by transcriptome sequencing of fetus skin samples collected from Inner Mongolia cashmere goats on days 45, 55, and 65 of fetal age. We found that FoxN1 , FoxE1 , and FoxI3 genes of the Fox gene family were probably involved in the growth and development of the follicle and the formation of hair, which is consistent with previous findings. Real-time quantitative polymerase chain reaction detecting system and Western blot analysis were employed to study the relative differentially expressed genes FoxN1 , FoxE1 , and FoxI3 in the body skin of cashmere goat fetuses and adult individuals. This study provided new fundamental information for further investigation of the genes related to follicle development and exploration of their roles in hair follicle initiation, growth, and development.

iCanPlot: Visual Exploration of High-Throughput Omics Data Using Interactive Canvas Plotting

PubMed Central

Sinha, Amit U.; Armstrong, Scott A.

2012-01-01

Increasing use of high throughput genomic scale assays requires effective visualization and analysis techniques to facilitate data interpretation. Moreover, existing tools often require programming skills, which discourages bench scientists from examining their own data. We have created iCanPlot, a compelling platform for visual data exploration based on the latest technologies. Using the recently adopted HTML5 Canvas element, we have developed a highly interactive tool to visualize tabular data and identify interesting patterns in an intuitive fashion without the need of any specialized computing skills. A module for geneset overlap analysis has been implemented on the Google App Engine platform: when the user selects a region of interest in the plot, the genes in the region are analyzed on the fly. The visualization and analysis are amalgamated for a seamless experience. Further, users can easily upload their data for analysis—which also makes it simple to share the analysis with collaborators. We illustrate the power of iCanPlot by showing an example of how it can be used to interpret histone modifications in the context of gene expression. PMID:22393367

Identifying arsenic trioxide (ATO) functions in leukemia cells by using time series gene expression profiles.

PubMed

Yang, Hong; Lin, Shan; Cui, Jingru

2014-02-10

Arsenic trioxide (ATO) is presently the most active single agent in the treatment of acute promyelocytic leukemia (APL). In order to explore the molecular mechanism of ATO in leukemia cells with time series, we adopted bioinformatics strategy to analyze expression changing patterns and changes in transcription regulation modules of time series genes filtered from Gene Expression Omnibus database (GSE24946). We totally screened out 1847 time series genes for subsequent analysis. The KEGG (Kyoto encyclopedia of genes and genomes) pathways enrichment analysis of these genes showed that oxidative phosphorylation and ribosome were the top 2 significantly enriched pathways. STEM software was employed to compare changing patterns of gene expression with assigned 50 expression patterns. We screened out 7 significantly enriched patterns and 4 tendency charts of time series genes. The result of Gene Ontology showed that functions of times series genes mainly distributed in profiles 41, 40, 39 and 38. Seven genes with positive regulation of cell adhesion function were enriched in profile 40, and presented the same first increased model then decreased model as profile 40. The transcription module analysis showed that they mainly involved in oxidative phosphorylation pathway and ribosome pathway. Overall, our data summarized the gene expression changes in ATO treated K562-r cell lines with time and suggested that time series genes mainly regulated cell adhesive. Furthermore, our result may provide theoretical basis of molecular biology in treating acute promyelocytic leukemia. Copyright © 2013 Elsevier B.V. All rights reserved.

Identification of Transcriptional Modules and Key Genes in Chickens Infected with Salmonella enterica Serovar Pullorum Using Integrated Coexpression Analyses.

PubMed

Liu, Bao-Hong; Cai, Jian-Ping

2017-01-01

Salmonella enterica Pullorum is one of the leading causes of mortality in poultry. Understanding the molecular response in chickens in response to the infection by S. enterica is important in revealing the mechanisms of pathogenesis and disease progress. There have been studies on identifying genes associated with Salmonella infection by differential expression analysis, but the relationships among regulated genes have not been investigated. In this study, we employed weighted gene coexpression network analysis (WGCNA) and differential coexpression analysis (DCEA) to identify coexpression modules by exploring microarray data derived from chicken splenic tissues in response to the S. enterica infection. A total of 19 modules from 13,538 genes were associated with the Jak-STAT signaling pathway, the extracellular matrix, cytoskeleton organization, the regulation of the actin cytoskeleton, G-protein coupled receptor activity, Toll-like receptor signaling pathways, and immune system processes; among them, 14 differentially coexpressed modules (DCMs) and 2,856 differentially coexpressed genes (DCGs) were identified. The global expression of module genes between infected and uninfected chickens showed slight differences but considerable changes for global coexpression. Furthermore, DCGs were consistently linked to the hubs of the modules. These results will help prioritize candidate genes for future studies of Salmonella infection.

Comparisons between Arabidopsis thaliana and Drosophila melanogaster in relation to Coding and Noncoding Sequence Length and Gene Expression

PubMed Central

Caldwell, Rachel; Lin, Yan-Xia; Zhang, Ren

2015-01-01

There is a continuing interest in the analysis of gene architecture and gene expression to determine the relationship that may exist. Advances in high-quality sequencing technologies and large-scale resource datasets have increased the understanding of relationships and cross-referencing of expression data to the large genome data. Although a negative correlation between expression level and gene (especially transcript) length has been generally accepted, there have been some conflicting results arising from the literature concerning the impacts of different regions of genes, and the underlying reason is not well understood. The research aims to apply quantile regression techniques for statistical analysis of coding and noncoding sequence length and gene expression data in the plant, Arabidopsis thaliana, and fruit fly, Drosophila melanogaster, to determine if a relationship exists and if there is any variation or similarities between these species. The quantile regression analysis found that the coding sequence length and gene expression correlations varied, and similarities emerged for the noncoding sequence length (5′ and 3′ UTRs) between animal and plant species. In conclusion, the information described in this study provides the basis for further exploration into gene regulation with regard to coding and noncoding sequence length. PMID:26114098

Identification of Transcriptional Modules and Key Genes in Chickens Infected with Salmonella enterica Serovar Pullorum Using Integrated Coexpression Analyses

PubMed Central

2017-01-01

Salmonella enterica Pullorum is one of the leading causes of mortality in poultry. Understanding the molecular response in chickens in response to the infection by S. enterica is important in revealing the mechanisms of pathogenesis and disease progress. There have been studies on identifying genes associated with Salmonella infection by differential expression analysis, but the relationships among regulated genes have not been investigated. In this study, we employed weighted gene coexpression network analysis (WGCNA) and differential coexpression analysis (DCEA) to identify coexpression modules by exploring microarray data derived from chicken splenic tissues in response to the S. enterica infection. A total of 19 modules from 13,538 genes were associated with the Jak-STAT signaling pathway, the extracellular matrix, cytoskeleton organization, the regulation of the actin cytoskeleton, G-protein coupled receptor activity, Toll-like receptor signaling pathways, and immune system processes; among them, 14 differentially coexpressed modules (DCMs) and 2,856 differentially coexpressed genes (DCGs) were identified. The global expression of module genes between infected and uninfected chickens showed slight differences but considerable changes for global coexpression. Furthermore, DCGs were consistently linked to the hubs of the modules. These results will help prioritize candidate genes for future studies of Salmonella infection. PMID:28529955

dbCPG: A web resource for cancer predisposition genes.

PubMed

Wei, Ran; Yao, Yao; Yang, Wu; Zheng, Chun-Hou; Zhao, Min; Xia, Junfeng

2016-06-21

Cancer predisposition genes (CPGs) are genes in which inherited mutations confer highly or moderately increased risks of developing cancer. Identification of these genes and understanding the biological mechanisms that underlie them is crucial for the prevention, early diagnosis, and optimized management of cancer. Over the past decades, great efforts have been made to identify CPGs through multiple strategies. However, information on these CPGs and their molecular functions is scattered. To address this issue and provide a comprehensive resource for researchers, we developed the Cancer Predisposition Gene Database (dbCPG, Database URL: http://bioinfo.ahu.edu.cn:8080/dbCPG/index.jsp), the first literature-based gene resource for exploring human CPGs. It contains 827 human (724 protein-coding, 23 non-coding, and 80 unknown type genes), 637 rats, and 658 mouse CPGs. Furthermore, data mining was performed to gain insights into the understanding of the CPGs data, including functional annotation, gene prioritization, network analysis of prioritized genes and overlap analysis across multiple cancer types. A user-friendly web interface with multiple browse, search, and upload functions was also developed to facilitate access to the latest information on CPGs. Taken together, the dbCPG database provides a comprehensive data resource for further studies of cancer predisposition genes.

PIGD: a database for intronless genes in the Poaceae.

PubMed

Yan, Hanwei; Jiang, Cuiping; Li, Xiaoyu; Sheng, Lei; Dong, Qing; Peng, Xiaojian; Li, Qian; Zhao, Yang; Jiang, Haiyang; Cheng, Beijiu

2014-10-01

Intronless genes are a feature of prokaryotes; however, they are widespread and unequally distributed among eukaryotes and represent an important resource to study the evolution of gene architecture. Although many databases on exons and introns exist, there is currently no cohesive database that collects intronless genes in plants into a single database. In this study, we present the Poaceae Intronless Genes Database (PIGD), a user-friendly web interface to explore information on intronless genes from different plants. Five Poaceae species, Sorghum bicolor, Zea mays, Setaria italica, Panicum virgatum and Brachypodium distachyon, are included in the current release of PIGD. Gene annotations and sequence data were collected and integrated from different databases. The primary focus of this study was to provide gene descriptions and gene product records. In addition, functional annotations, subcellular localization prediction and taxonomic distribution are reported. PIGD allows users to readily browse, search and download data. BLAST and comparative analyses are also provided through this online database, which is available at http://pigd.ahau.edu.cn/. PIGD provides a solid platform for the collection, integration and analysis of intronless genes in the Poaceae. As such, this database will be useful for subsequent bio-computational analysis in comparative genomics and evolutionary studies.

Mining Microarray Data at NCBI’s Gene Expression Omnibus (GEO)*

PubMed Central

Barrett, Tanya; Edgar, Ron

2006-01-01

Summary The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo. PMID:16888359

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering.

PubMed

Ji, Shuiwang

2013-07-11

The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development. In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space. Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship.

New Statistics for Testing Differential Expression of Pathways from Microarray Data

NASA Astrophysics Data System (ADS)

Siu, Hoicheong; Dong, Hua; Jin, Li; Xiong, Momiao

Exploring biological meaning from microarray data is very important but remains a great challenge. Here, we developed three new statistics: linear combination test, quadratic test and de-correlation test to identify differentially expressed pathways from gene expression profile. We apply our statistics to two rheumatoid arthritis datasets. Notably, our results reveal three significant pathways and 275 genes in common in two datasets. The pathways we found are meaningful to uncover the disease mechanisms of rheumatoid arthritis, which implies that our statistics are a powerful tool in functional analysis of gene expression data.

What's that gene (or protein)? Online resources for exploring functions of genes, transcripts, and proteins

PubMed Central

Hutchins, James R. A.

2014-01-01

The genomic era has enabled research projects that use approaches including genome-scale screens, microarray analysis, next-generation sequencing, and mass spectrometry–based proteomics to discover genes and proteins involved in biological processes. Such methods generate data sets of gene, transcript, or protein hits that researchers wish to explore to understand their properties and functions and thus their possible roles in biological systems of interest. Recent years have seen a profusion of Internet-based resources to aid this process. This review takes the viewpoint of the curious biologist wishing to explore the properties of protein-coding genes and their products, identified using genome-based technologies. Ten key questions are asked about each hit, addressing functions, phenotypes, expression, evolutionary conservation, disease association, protein structure, interactors, posttranslational modifications, and inhibitors. Answers are provided by presenting the latest publicly available resources, together with methods for hit-specific and data set–wide information retrieval, suited to any genome-based analytical technique and experimental species. The utility of these resources is demonstrated for 20 factors regulating cell proliferation. Results obtained using some of these are discussed in more depth using the p53 tumor suppressor as an example. This flexible and universally applicable approach for characterizing experimental hits helps researchers to maximize the potential of their projects for biological discovery. PMID:24723265

Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

PubMed Central

Reif, David M.; Israel, Mark A.; Moore, Jason H.

2007-01-01

The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occuring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org. PMID:19390666

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

PubMed

McKay, James D; Hung, Rayjean J; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C; Caporaso, Neil E; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A; Qian, David C; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N; Bojesen, Stig E; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C; Bush, William S; Tardon, Adonina; Rennert, Gad; Teare, M Dawn; Field, John K; Kiemeney, Lambertus A; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B; Andrew, Angeline S; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A; Wilkens, Lynne R; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F M; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael P A; Marcus, Michael W; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A; Barnett, Matt P; Chen, Chu; Goodman, Gary E; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H-Erich; Manz, Judith; Muley, Thomas R; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A; Tsao, Ming-Sound; Arnold, Susanne M; Haura, Eric B; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J; Butler, Lesley M; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S; McLaughlin, John; Stevens, Victoria L; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C; Obeidat, Ma'en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D; Wain, Louise V; Rafnar, Thorunn; Thorgeirsson, Thorgeir E; Reginsson, Gunnar W; Stefansson, Kari; Hancock, Dana B; Bierut, Laura J; Spitz, Margaret R; Gaddis, Nathan C; Lutz, Sharon M; Gu, Fangyi; Johnson, Eric O; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I

2017-07-01

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.

Ketide Synthase (KS) Domain Prediction and Analysis of Iterative Type II PKS Gene in Marine Sponge-Associated Actinobacteria Producing Biosurfactants and Antimicrobial Agents

PubMed Central

Selvin, Joseph; Sathiyanarayanan, Ganesan; Lipton, Anuj N.; Al-Dhabi, Naif Abdullah; Valan Arasu, Mariadhas; Kiran, George S.

2016-01-01

The important biological macromolecules, such as lipopeptide and glycolipid biosurfactant producing marine actinobacteria were analyzed and their potential linkage between type II polyketide synthase (PKS) genes was explored. A unique feature of type II PKS genes is their high amino acid (AA) sequence homology and conserved gene organization. These enzymes mediate the biosynthesis of polyketide natural products with enormous structural complexity and chemical nature by combinatorial use of various domains. Therefore, deciphering the order of AA sequence encoded by PKS domains tailored the chemical structure of polyketide analogs still remains a great challenge. The present work deals with an in vitro and in silico analysis of PKS type II genes from five actinobacterial species to correlate KS domain architecture and structural features. Our present analysis reveals the unique protein domain organization of iterative type II PKS and KS domain of marine actinobacteria. The findings of this study would have implications in metabolic pathway reconstruction and design of semi-synthetic genomes to achieve rational design of novel natural products. PMID:26903957

Evaluation of differentially expressed immune-related genes in intestine of Pelodiscus sinensis after intragastric challenge with lipopolysaccharide based on transcriptome analysis.

PubMed

Xu, Jiehao; Zhao, Jing; Li, Yiqun; Zou, Yiyi; Lu, Binjie; Chen, Yuyin; Ma, Youzhi; Xu, Haisheng

2016-09-01

Pelodiscus sinensis is the most common turtle species that has been raised in East and Southeast Asia. However, there are still limited studies about the immune defense mechanisms in its small intestine until now. In the present research, histological analysis and transcriptome analysis was performed on the small intestine of P. sinensis after intragastric challenge with LPS to explore its mechanisms of immune responses to pathogens. The result showed the number of intraepithelial lymphocytes (IELs) and goblet cells (GCs) in its intestine increased significantly at 48 h post-challenge with LPS by intragastrical route, indicating clearly the intestinal immune response was induced. Compared with the control, a total of 748 differentially expressed genes (DEGs) were identified, including 361 up-regulated genes and 387 down-regulated genes. Based on the Gene Ontology (GO) annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG), 48 immune-related DEGs were identified, which were classified into 82 GO terms and 14 pathways. Finally, 18 DEGs, which were randomly selected, were confirmed by quantitative real-time PCR (qRT-PCR). Our results provide valuable information for further analysis of the immune defense mechanisms against pathogens in the small intestine of P. sinensis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Seeking unique and common biological themes in multiple gene lists or datasets: pathway pattern extraction pipeline for pathway-level comparative analysis.

PubMed

Yi, Ming; Mudunuri, Uma; Che, Anney; Stephens, Robert M

2009-06-29

One of the challenges in the analysis of microarray data is to integrate and compare the selected (e.g., differential) gene lists from multiple experiments for common or unique underlying biological themes. A common way to approach this problem is to extract common genes from these gene lists and then subject these genes to enrichment analysis to reveal the underlying biology. However, the capacity of this approach is largely restricted by the limited number of common genes shared by datasets from multiple experiments, which could be caused by the complexity of the biological system itself. We now introduce a new Pathway Pattern Extraction Pipeline (PPEP), which extends the existing WPS application by providing a new pathway-level comparative analysis scheme. To facilitate comparing and correlating results from different studies and sources, PPEP contains new interfaces that allow evaluation of the pathway-level enrichment patterns across multiple gene lists. As an exploratory tool, this analysis pipeline may help reveal the underlying biological themes at both the pathway and gene levels. The analysis scheme provided by PPEP begins with multiple gene lists, which may be derived from different studies in terms of the biological contexts, applied technologies, or methodologies. These lists are then subjected to pathway-level comparative analysis for extraction of pathway-level patterns. This analysis pipeline helps to explore the commonality or uniqueness of these lists at the level of pathways or biological processes from different but relevant biological systems using a combination of statistical enrichment measurements, pathway-level pattern extraction, and graphical display of the relationships of genes and their associated pathways as Gene-Term Association Networks (GTANs) within the WPS platform. As a proof of concept, we have used the new method to analyze many datasets from our collaborators as well as some public microarray datasets. This tool provides a new pathway-level analysis scheme for integrative and comparative analysis of data derived from different but relevant systems. The tool is freely available as a Pathway Pattern Extraction Pipeline implemented in our existing software package WPS, which can be obtained at http://www.abcc.ncifcrf.gov/wps/wps_index.php.

DNA Microarray Analysis of the Expression Profile of Escherichia coli in Response to Treatment with 4,5-Dihydroxy-2-Cyclopenten-1-One

PubMed Central

Phadtare, Sangita; Kato, Ikunoshin; Inouye, Masayori

2002-01-01

We carried out DNA microarray-based global transcript profiling of Escherichia coli in response to 4,5-dihydroxy-2-cyclopenten-1-one to explore the manifestation of its antibacterial activity. We show that it has widespread effects in E. coli affecting genes encoding proteins involved in cell metabolism and membrane synthesis and functions. Genes belonging to the regulon involved in synthesis of Cys are upregulated. In addition, rpoS and RpoS-regulated genes responding to various stresses and a number of genes responding to oxidative stress are upregulated. PMID:12426362

Use of transcriptome sequencing to understand the pistillate flowering in hickory (Carya cathayensis Sarg.).

PubMed

Huang, You-Jun; Liu, Li-Li; Huang, Jian-Qin; Wang, Zheng-Jia; Chen, Fang-Fang; Zhang, Qi-Xiang; Zheng, Bing-Song; Chen, Ming

2013-10-10

Different from herbaceous plants, the woody plants undergo a long-period vegetative stage to achieve floral transition. They then turn into seasonal plants, flowering annually. In this study, a preliminary model of gene regulations for seasonal pistillate flowering in hickory (Carya cathayensis) was proposed. The genome-wide dynamic transcriptome was characterized via the joint-approach of RNA sequencing and microarray analysis. Differential transcript abundance analysis uncovered the dynamic transcript abundance patterns of flowering correlated genes and their major functions based on Gene Ontology (GO) analysis. To explore pistillate flowering mechanism in hickory, a comprehensive flowering gene regulatory network based on Arabidopsis thaliana was constructed by additional literature mining. A total of 114 putative flowering or floral genes including 31 with differential transcript abundance were identified in hickory. The locations, functions and dynamic transcript abundances were analyzed in the gene regulatory networks. A genome-wide co-expression network for the putative flowering or floral genes shows three flowering regulatory modules corresponding to response to light abiotic stimulus, cold stress, and reproductive development process, respectively. Totally 27 potential flowering or floral genes were recruited which are meaningful to understand the hickory specific seasonal flowering mechanism better. Flowering event of pistillate flower bud in hickory is triggered by several pathways synchronously including the photoperiod, autonomous, vernalization, gibberellin, and sucrose pathway. Totally 27 potential flowering or floral genes were recruited from the genome-wide co-expression network function module analysis. Moreover, the analysis provides a potential FLC-like gene based vernalization pathway and an 'AC' model for pistillate flower development in hickory. This work provides an available framework for pistillate flower development in hickory, which is significant for insight into regulation of flowering and floral development of woody plants.

Use of transcriptome sequencing to understand the pistillate flowering in hickory (Carya cathayensis Sarg.)

PubMed Central

2013-01-01

Background Different from herbaceous plants, the woody plants undergo a long-period vegetative stage to achieve floral transition. They then turn into seasonal plants, flowering annually. In this study, a preliminary model of gene regulations for seasonal pistillate flowering in hickory (Carya cathayensis) was proposed. The genome-wide dynamic transcriptome was characterized via the joint-approach of RNA sequencing and microarray analysis. Results Differential transcript abundance analysis uncovered the dynamic transcript abundance patterns of flowering correlated genes and their major functions based on Gene Ontology (GO) analysis. To explore pistillate flowering mechanism in hickory, a comprehensive flowering gene regulatory network based on Arabidopsis thaliana was constructed by additional literature mining. A total of 114 putative flowering or floral genes including 31 with differential transcript abundance were identified in hickory. The locations, functions and dynamic transcript abundances were analyzed in the gene regulatory networks. A genome-wide co-expression network for the putative flowering or floral genes shows three flowering regulatory modules corresponding to response to light abiotic stimulus, cold stress, and reproductive development process, respectively. Totally 27 potential flowering or floral genes were recruited which are meaningful to understand the hickory specific seasonal flowering mechanism better. Conclusions Flowering event of pistillate flower bud in hickory is triggered by several pathways synchronously including the photoperiod, autonomous, vernalization, gibberellin, and sucrose pathway. Totally 27 potential flowering or floral genes were recruited from the genome-wide co-expression network function module analysis. Moreover, the analysis provides a potential FLC-like gene based vernalization pathway and an 'AC’ model for pistillate flower development in hickory. This work provides an available framework for pistillate flower development in hickory, which is significant for insight into regulation of flowering and floral development of woody plants. PMID:24106755

Systematic Association of Genes to Phenotypes by Genome and Literature Mining

PubMed Central

Jensen, Lars J; Perez-Iratxeta, Carolina; Kaczanowski, Szymon; Hooper, Sean D; Andrade, Miguel A

2005-01-01

One of the major challenges of functional genomics is to unravel the connection between genotype and phenotype. So far no global analysis has attempted to explore those connections in the light of the large phenotypic variability seen in nature. Here, we use an unsupervised, systematic approach for associating genes and phenotypic characteristics that combines literature mining with comparative genome analysis. We first mine the MEDLINE literature database for terms that reflect phenotypic similarities of species. Subsequently we predict the likely genomic determinants: genes specifically present in the respective genomes. In a global analysis involving 92 prokaryotic genomes we retrieve 323 clusters containing a total of 2,700 significant gene–phenotype associations. Some clusters contain mostly known relationships, such as genes involved in motility or plant degradation, often with additional hypothetical proteins associated with those phenotypes. Other clusters comprise unexpected associations; for example, a group of terms related to food and spoilage is linked to genes predicted to be involved in bacterial food poisoning. Among the clusters, we observe an enrichment of pathogenicity-related associations, suggesting that the approach reveals many novel genes likely to play a role in infectious diseases. PMID:15799710

Xylella fastidiosa gene expression analysis by DNA microarrays.

PubMed

Travensolo, Regiane F; Carareto-Alves, Lucia M; Costa, Maria V C G; Lopes, Tiago J S; Carrilho, Emanuel; Lemos, Eliana G M

2009-04-01

Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM(2) and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements.

PubMed

Mi, Huaiyu; Huang, Xiaosong; Muruganujan, Anushya; Tang, Haiming; Mills, Caitlin; Kang, Diane; Thomas, Paul D

2017-01-04

The PANTHER database (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org) contains comprehensive information on the evolution and function of protein-coding genes from 104 completely sequenced genomes. PANTHER software tools allow users to classify new protein sequences, and to analyze gene lists obtained from large-scale genomics experiments. In the past year, major improvements include a large expansion of classification information available in PANTHER, as well as significant enhancements to the analysis tools. Protein subfamily functional classifications have more than doubled due to progress of the Gene Ontology Phylogenetic Annotation Project. For human genes (as well as a few other organisms), PANTHER now also supports enrichment analysis using pathway classifications from the Reactome resource. The gene list enrichment tools include a new 'hierarchical view' of results, enabling users to leverage the structure of the classifications/ontologies; the tools also allow users to upload genetic variant data directly, rather than requiring prior conversion to a gene list. The updated coding single-nucleotide polymorphisms (SNP) scoring tool uses an improved algorithm. The hidden Markov model (HMM) search tools now use HMMER3, dramatically reducing search times and improving accuracy of E-value statistics. Finally, the PANTHER Tree-Attribute Viewer has been implemented in JavaScript, with new views for exploring protein sequence evolution. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comparative evolutionary genomics of Corynebacterium with special reference to codon and amino acid usage diversities.

PubMed

Pal, Shilpee; Sarkar, Indrani; Roy, Ayan; Mohapatra, Pradeep K Das; Mondal, Keshab C; Sen, Arnab

2018-02-01

The present study has been aimed to the comparative analysis of high GC composition containing Corynebacterium genomes and their evolutionary study by exploring codon and amino acid usage patterns. Phylogenetic study by MLSA approach, indel analysis and BLAST matrix differentiated Corynebacterium species in pathogenic and non-pathogenic clusters. Correspondence analysis on synonymous codon usage reveals that, gene length, optimal codon frequencies and tRNA abundance affect the gene expression of Corynebacterium. Most of the optimal codons as well as translationally optimal codons are C ending i.e. RNY (R-purine, N-any nucleotide base, and Y-pyrimidine) and reveal translational selection pressure on codon bias of Corynebacterium. Amino acid usage is affected by hydrophobicity, aromaticity, protein energy cost, etc. Highly expressed genes followed the cost minimization hypothesis and are less diverged at their synonymous positions of codons. Functional analysis of core genes shows significant difference in pathogenic and non-pathogenic Corynebacterium. The study reveals close relationship between non-pathogenic and opportunistic pathogenic Corynebaterium as well as between molecular evolution and survival niches of the organism.

Integrative Analysis Reveals Regulatory Programs in Endometriosis

PubMed Central

Yang, Huan; Kang, Kai; Cheng, Chao; Mamillapalli, Ramanaiah; Taylor, Hugh S.

2015-01-01

Endometriosis is a common gynecological disease found in approximately 10% of reproductive-age women. Gene expression analysis has been performed to explore alterations in gene expression associated with endometriosis; however, the underlying transcription factors (TFs) governing such expression changes have not been investigated in a systematic way. In this study, we propose a method to integrate gene expression with TF binding data and protein–protein interactions to construct an integrated regulatory network (IRN) for endometriosis. The IRN has shown that the most regulated gene in endometriosis is RUNX1, which is targeted by 14 of 26 TFs also involved in endometriosis. Using 2 published cohorts, GSE7305 (Hover, n = 20) and GSE7307 (Roth, n = 36) from the Gene Expression Omnibus database, we identified a network of TFs, which bind to target genes that are differentially expressed in endometriosis. Enrichment analysis based on the hypergeometric distribution allowed us to predict the TFs involved in endometriosis (n = 40). This included known TFs such as androgen receptor (AR) and critical factors in the pathology of endometriosis, estrogen receptor α, and estrogen receptor β. We also identified several new ones from which we selected FOXA2 and TFAP2C, and their regulation was confirmed by quantitative real-time polymerase chain reaction and immunohistochemistry (IHC). Further, our analysis revealed that the function of AR and p53 in endometriosis is regulated by posttranscriptional changes and not by differential gene expression. Our integrative analysis provides new insights into the regulatory programs involved in endometriosis. PMID:26134036

Genomic evidence of bitter taste in snakes and phylogenetic analysis of bitter taste receptor genes in reptiles

PubMed Central

Zhong, Huaming; Shang, Shuai; Wu, Xiaoyang; Chen, Jun; Zhu, Wanchao; Yan, Jiakuo; Li, Haotian

2017-01-01

As nontraditional model organisms with extreme physiological and morphological phenotypes, snakes are believed to possess an inferior taste system. However, the bitter taste sensation is essential to distinguish the nutritious and poisonous food resources and the genomic evidence of bitter taste in snakes is largely scarce. To explore the genetic basis of the bitter taste of snakes and characterize the evolution of bitter taste receptor genes (Tas2rs) in reptiles, we identified Tas2r genes in 19 genomes (species) corresponding to three orders of non-avian reptiles. Our results indicated contractions of Tas2r gene repertoires in snakes, however dramatic gene expansions have occurred in lizards. Phylogenetic analysis of the Tas2rs with NJ and BI methods revealed that Tas2r genes of snake species formed two clades, whereas in lizards the Tas2r genes clustered into two monophyletic clades and four large clades. Evolutionary changes (birth and death) of intact Tas2r genes in reptiles were determined by reconciliation analysis. Additionally, the taste signaling pathway calcium homeostasis modulator 1 (Calhm1) gene of snakes was putatively functional, suggesting that snakes still possess bitter taste sensation. Furthermore, Phylogenetically Independent Contrasts (PIC) analyses reviewed a significant correlation between the number of Tas2r genes and the amount of potential toxins in reptilian diets, suggesting that insectivores such as some lizards may require more Tas2rs genes than omnivorous and carnivorous reptiles. PMID:28828281

Lessons learned from whole exome sequencing in multiplex families affected by a complex genetic disorder, intracranial aneurysm.

PubMed

Farlow, Janice L; Lin, Hai; Sauerbeck, Laura; Lai, Dongbing; Koller, Daniel L; Pugh, Elizabeth; Hetrick, Kurt; Ling, Hua; Kleinloog, Rachel; van der Vlies, Pieter; Deelen, Patrick; Swertz, Morris A; Verweij, Bon H; Regli, Luca; Rinkel, Gabriel J E; Ruigrok, Ynte M; Doheny, Kimberly; Liu, Yunlong; Broderick, Joseph; Foroud, Tatiana

2015-01-01

Genetic risk factors for intracranial aneurysm (IA) are not yet fully understood. Genomewide association studies have been successful at identifying common variants; however, the role of rare variation in IA susceptibility has not been fully explored. In this study, we report the use of whole exome sequencing (WES) in seven densely-affected families (45 individuals) recruited as part of the Familial Intracranial Aneurysm study. WES variants were prioritized by functional prediction, frequency, predicted pathogenicity, and segregation within families. Using these criteria, 68 variants in 68 genes were prioritized across the seven families. Of the genes that were expressed in IA tissue, one gene (TMEM132B) was differentially expressed in aneurysmal samples (n=44) as compared to control samples (n=16) (false discovery rate adjusted p-value=0.023). We demonstrate that sequencing of densely affected families permits exploration of the role of rare variants in a relatively common disease such as IA, although there are important study design considerations for applying sequencing to complex disorders. In this study, we explore methods of WES variant prioritization, including the incorporation of unaffected individuals, multipoint linkage analysis, biological pathway information, and transcriptome profiling. Further studies are needed to validate and characterize the set of variants and genes identified in this study.

Evolution of Sulfobacillus thermosulfidooxidans secreting alginate during bioleaching of chalcopyrite concentrate.

PubMed

Yu, R-L; Liu, A; Liu, Y; Yu, Z; Peng, T; Wu, X; Shen, L; Liu, Y; Li, J; Liu, X; Qiu, G; Chen, M; Zeng, W

2017-06-01

To explore the distribution disciplinarian of alginate on the chalcopyrite concentrate surface during bioleaching. The evolution of Sulfobacillus thermosulfidooxidans secreting alginate during bioleaching of chalcopyrite concentrate was investigated through gas chromatography coupled with mass spectrometry (GC-MS) and confocal laser scanning microscope (CLSM), and the critical synthetic genes (algA, algC, algD) of alginate were analysed by real-time polymerase chain reaction (RT-PCR). The GC-MS analysis results indicated that there was a little amount of alginate formed on the mineral surface at the early stage, while increasing largely to the maximum value at the intermediate stage, and then kept a stable value at the end stage. The CLSM analysis of chalcopyrite slice showed the same variation trend of alginate content on the mineral surface. Furthermore, the RT-PCR results showed that during the early stage of bioleaching, the expressions of the algA, algC and the algD genes were all overexpressed. However, at the final stage, the algD gene expression decreased in a large scale, and the algA and algC decreased slightly. This expression pattern was attributed to the fact that algA and algC genes were involved in several biosynthesis reactions, but the algD gene only participated in the alginate biosynthesis and this was considered as the key gene to control alginate synthesis. The content of alginate on the mineral surface increased largely at the beginning of bioleaching, and remained stable at the end of bioleaching due to the restriction of algD gene expression. Our findings provide valuable information to explore the relationship between alginate formation and bioleaching of chalcopyrite. © 2017 The Society for Applied Microbiology.

Molecular Phylogenetic and Expression Analysis of the Complete WRKY Transcription Factor Family in Maize

PubMed Central

Wei, Kai-Fa; Chen, Juan; Chen, Yan-Feng; Wu, Ling-Juan; Xie, Dao-Xin

2012-01-01

The WRKY transcription factors function in plant growth and development, and response to the biotic and abiotic stresses. Although many studies have focused on the functional identification of the WRKY transcription factors, much less is known about molecular phylogenetic and global expression analysis of the complete WRKY family in maize. In this study, we identified 136 WRKY proteins coded by 119 genes in the B73 inbred line from the complete genome and named them in an orderly manner. Then, a comprehensive phylogenetic analysis of five species was performed to explore the origin and evolutionary patterns of these WRKY genes, and the result showed that gene duplication is the major driving force for the origin of new groups and subgroups and functional divergence during evolution. Chromosomal location analysis of maize WRKY genes indicated that 20 gene clusters are distributed unevenly in the genome. Microarray-based expression analysis has revealed that 131 WRKY transcripts encoded by 116 genes may participate in the regulation of maize growth and development. Among them, 102 transcripts are stably expressed with a coefficient of variation (CV) value of <15%. The remaining 29 transcripts produced by 25 WRKY genes with the CV value of >15% are further analysed to discover new organ- or tissue-specific genes. In addition, microarray analyses of transcriptional responses to drought stress and fungal infection showed that maize WRKY proteins are involved in stress responses. All these results contribute to a deep probing into the roles of WRKY transcription factors in maize growth and development and stress tolerance. PMID:22279089

Molecular phylogenetic and expression analysis of the complete WRKY transcription factor family in maize.

PubMed

Wei, Kai-Fa; Chen, Juan; Chen, Yan-Feng; Wu, Ling-Juan; Xie, Dao-Xin

2012-04-01

The WRKY transcription factors function in plant growth and development, and response to the biotic and abiotic stresses. Although many studies have focused on the functional identification of the WRKY transcription factors, much less is known about molecular phylogenetic and global expression analysis of the complete WRKY family in maize. In this study, we identified 136 WRKY proteins coded by 119 genes in the B73 inbred line from the complete genome and named them in an orderly manner. Then, a comprehensive phylogenetic analysis of five species was performed to explore the origin and evolutionary patterns of these WRKY genes, and the result showed that gene duplication is the major driving force for the origin of new groups and subgroups and functional divergence during evolution. Chromosomal location analysis of maize WRKY genes indicated that 20 gene clusters are distributed unevenly in the genome. Microarray-based expression analysis has revealed that 131 WRKY transcripts encoded by 116 genes may participate in the regulation of maize growth and development. Among them, 102 transcripts are stably expressed with a coefficient of variation (CV) value of <15%. The remaining 29 transcripts produced by 25 WRKY genes with the CV value of >15% are further analysed to discover new organ- or tissue-specific genes. In addition, microarray analyses of transcriptional responses to drought stress and fungal infection showed that maize WRKY proteins are involved in stress responses. All these results contribute to a deep probing into the roles of WRKY transcription factors in maize growth and development and stress tolerance.

Transcriptome Analysis and Discovery of Genes Involved in Immune Pathways from Coelomocytes of Sea Cucumber (Apostichopus japonicus) after Vibrio splendidus Challenge.

PubMed

Gao, Qiong; Liao, Meijie; Wang, Yingeng; Li, Bin; Zhang, Zheng; Rong, Xiaojun; Chen, Guiping; Wang, Lan

2015-07-17

Vibrio splendidus is identified as one of the major pathogenic factors for the skin ulceration syndrome in sea cucumber (Apostichopus japonicus), which has vastly limited the development of the sea cucumber culture industry. In order to screen the immune genes involving Vibrio splendidus challenge in sea cucumber and explore the molecular mechanism of this process, the related transcriptome and gene expression profiling of resistant and susceptible biotypes of sea cucumber with Vibrio splendidus challenge were collected for analysis. A total of 319,455,942 trimmed reads were obtained, which were assembled into 186,658 contigs. After that, 89,891 representative contigs (without isoform) were clustered. The analysis of the gene expression profiling identified 358 differentially expression genes (DEGs) in the bacterial-resistant group, and 102 DEGs in the bacterial-susceptible group, compared with that in control group. According to the reported references and annotation information from BLAST, GO and KEGG, 30 putative bacterial-resistant genes and 19 putative bacterial-susceptible genes were identified from DEGs. The qRT-PCR results were consistent with the RNA-Seq results. Furthermore, many DGEs were involved in immune signaling related pathways, such as Endocytosis, Lysosome, MAPK, Chemokine and the ERBB signaling pathway.

Transcriptome Analysis and Discovery of Genes Involved in Immune Pathways from Coelomocytes of Sea Cucumber (Apostichopus japonicus) after Vibrio splendidus Challenge

PubMed Central

Gao, Qiong; Liao, Meijie; Wang, Yingeng; Li, Bin; Zhang, Zheng; Rong, Xiaojun; Chen, Guiping; Wang, Lan

2015-01-01

Vibrio splendidus is identified as one of the major pathogenic factors for the skin ulceration syndrome in sea cucumber (Apostichopus japonicus), which has vastly limited the development of the sea cucumber culture industry. In order to screen the immune genes involving Vibrio splendidus challenge in sea cucumber and explore the molecular mechanism of this process, the related transcriptome and gene expression profiling of resistant and susceptible biotypes of sea cucumber with Vibrio splendidus challenge were collected for analysis. A total of 319,455,942 trimmed reads were obtained, which were assembled into 186,658 contigs. After that, 89,891 representative contigs (without isoform) were clustered. The analysis of the gene expression profiling identified 358 differentially expression genes (DEGs) in the bacterial-resistant group, and 102 DEGs in the bacterial-susceptible group, compared with that in control group. According to the reported references and annotation information from BLAST, GO and KEGG, 30 putative bacterial-resistant genes and 19 putative bacterial-susceptible genes were identified from DEGs. The qRT-PCR results were consistent with the RNA-Seq results. Furthermore, many DGEs were involved in immune signaling related pathways, such as Endocytosis, Lysosome, MAPK, Chemokine and the ERBB signaling pathway. PMID:26193268

[Association between the canine monoamine oxidase B (MAOB) gene polymorphisms and behavior of puppies in open-field test].

PubMed

Li, Xiao-Hui; Xu, Han-Kun; Mao, Da-Gan; Ma, Da-Jun; Chen, Peng; Yang, Li-Guo

2006-11-01

Excitability, activity and exploration behavior of puppies in a novel open-field were tested in a total of 204 two-month-old German shepherd dog, labrador retriever or English springer spaniel puppies. The polymorphisms of monoamine oxidase B gene (MAOB) were detected by PCR-RFLP. Statistics analysis indicated that genotype and allele frequencies of the polymorphisms were significantly different among three breeds (P < 0.01). With GLM analysis of SAS software, association analysis was conducted between MAOB gene polymorphisms and locomotion and vocalization behavior parameters in the open-field test. The results showed that MAOB gene polymorphisms had a significant effect on walking time, squares crossed, lying time, the times of standing up against walls(P < 0.01 or P < 0.05) and were associated with the times of posture change (P=0.064). Walking time and squares crossed were higher in TT genotype puppies than those in TC and CC puppies (P < 0.05) and the times of posture change and standing up against walls were also higher than those in CC (P < 0.05). In addition, lying time in CC genotype puppies were higher than that in TT (P < 0.05). MAOB had a positive effect on walking time, lying time, squares crossed, the times of posture change, the times of standing up against walls in the three dog breeds that was highly statistically significant (P < 0.01 or P < 0.05). Our results imply that MAOB gene significantly affects the excitability, activity and exploration behavior of puppies in open-field test and TT genotype has favorable effects in these behavior traits.

Genome-Wide Screening and Characterization of the Dof Gene Family in Physic Nut (Jatropha curcas L.).

PubMed

Wang, Peipei; Li, Jing; Gao, Xiaoyang; Zhang, Di; Li, Anlin; Liu, Changning

2018-05-29

Physic nut ( Jatropha curcas L.) is a species of flowering plant with great potential for biofuel production and as an emerging model organism for functional genomic analysis, particularly in the Euphorbiaceae family. DNA binding with one finger (Dof) transcription factors play critical roles in numerous biological processes in plants. Nevertheless, the knowledge about members, and the evolutionary and functional characteristics of the Dof gene family in physic nut is insufficient. Therefore, we performed a genome-wide screening and characterization of the Dof gene family within the physic nut draft genome. In total, 24 JcDof genes (encoding 33 JcDof proteins) were identified. All the JcDof genes were divided into three major groups based on phylogenetic inference, which was further validated by the subsequent gene structure and motif analysis. Genome comparison revealed that segmental duplication may have played crucial roles in the expansion of the JcDof gene family, and gene expansion was mainly subjected to positive selection. The expression profile demonstrated the broad involvement of JcDof genes in response to various abiotic stresses, hormonal treatments and functional divergence. This study provides valuable information for better understanding the evolution of JcDof genes, and lays a foundation for future functional exploration of JcDof genes.

Oligonucleotide microarray analysis of apoptosis induced by 15-methoxypinusolidic acid in microglial BV2 cells

PubMed Central

Choi, Y; Lim, SY; Jeong, HS; Koo, KA; Sung, SH; Kim, YC

2009-01-01

Background and purpose: We conducted a genome wide gene expression analysis to explore the biological aspects of 15-methoxypinusolidic acid (15-MPA) isolated from Biota orientalis and tried to confirm the suitability of 15-MPA as a therapeutic candidate for CNS injuries focusing on microglia. Experimental approach: Murine microglial BV2 cells were treated with 15-MPA, and their transcriptome was analysed by using oligonucleotide microarrays. Genes differentially expressed upon 15-MPA treatment were selected for RT-PCR (reverse transcription-polymerase chain reaction) analysis to confirm the gene expression. Inhibition of cell proliferation and induction of apoptosis by 15-MPA were examined by bromodeoxyuridine assay, Western blot analysis of poly-ADP-ribose polymerase and flow cytometry. Key results: A total of 514 genes were differentially expressed by 15-MPA treatment. Biological pathway analysis revealed that 15-MPA induced significant changes in expression of genes in the cell cycle pathway. Genes involved in growth arrest and DNA damage [gadd45α, gadd45γ and ddit3 (DNA damage-inducible transcript 3)] and cyclin-dependent kinase inhibitor (cdkn2b) were up-regulated, whereas genes involved in cell cycle progression (ccnd1, ccnd3 and ccne1), DNA replication (mcm4, orc1l and cdc6) and cell proliferation (fos and jun) were down-regulated. RT-PCR analysis for representative genes confirmed the expression levels. 15-MPA significantly reduced bromodeoxyuridine incorporation, increased poly-ADP-ribose polymerase cleavage and the number of apoptotic cells, indicating that 15-MPA induces apoptosis in BV2 cells. Conclusion and implications: 15-MPA induced apoptosis in murine microglial cells, presumably via inhibition of the cell cycle progression. As microglial activation is detrimental in CNS injuries, these data suggest a strong therapeutic potential of 15-MPA. PMID:19466985

Exploring Wound-Healing Genomic Machinery with a Network-Based Approach

PubMed Central

Vitali, Francesca; Marini, Simone; Balli, Martina; Grosemans, Hanne; Sampaolesi, Maurilio; Lussier, Yves A.; Cusella De Angelis, Maria Gabriella; Bellazzi, Riccardo

2017-01-01

The molecular mechanisms underlying tissue regeneration and wound healing are still poorly understood despite their importance. In this paper we develop a bioinformatics approach, combining biology and network theory to drive experiments for better understanding the genetic underpinnings of wound healing mechanisms and for selecting potential drug targets. We start by selecting literature-relevant genes in murine wound healing, and inferring from them a Protein-Protein Interaction (PPI) network. Then, we analyze the network to rank wound healing-related genes according to their topological properties. Lastly, we perform a procedure for in-silico simulation of a treatment action in a biological pathway. The findings obtained by applying the developed pipeline, including gene expression analysis, confirms how a network-based bioinformatics method is able to prioritize candidate genes for in vitro analysis, thus speeding up the understanding of molecular mechanisms and supporting the discovery of potential drug targets. PMID:28635674

Mapping the malaria parasite druggable genome by using in vitro evolution and chemogenomics.

PubMed

Cowell, Annie N; Istvan, Eva S; Lukens, Amanda K; Gomez-Lorenzo, Maria G; Vanaerschot, Manu; Sakata-Kato, Tomoyo; Flannery, Erika L; Magistrado, Pamela; Owen, Edward; Abraham, Matthew; LaMonte, Gregory; Painter, Heather J; Williams, Roy M; Franco, Virginia; Linares, Maria; Arriaga, Ignacio; Bopp, Selina; Corey, Victoria C; Gnädig, Nina F; Coburn-Flynn, Olivia; Reimer, Christin; Gupta, Purva; Murithi, James M; Moura, Pedro A; Fuchs, Olivia; Sasaki, Erika; Kim, Sang W; Teng, Christine H; Wang, Lawrence T; Akidil, Aslı; Adjalley, Sophie; Willis, Paul A; Siegel, Dionicio; Tanaseichuk, Olga; Zhong, Yang; Zhou, Yingyao; Llinás, Manuel; Ottilie, Sabine; Gamo, Francisco-Javier; Lee, Marcus C S; Goldberg, Daniel E; Fidock, David A; Wirth, Dyann F; Winzeler, Elizabeth A

2018-01-12

Chemogenetic characterization through in vitro evolution combined with whole-genome analysis can identify antimalarial drug targets and drug-resistance genes. We performed a genome analysis of 262 Plasmodium falciparum parasites resistant to 37 diverse compounds. We found 159 gene amplifications and 148 nonsynonymous changes in 83 genes associated with drug-resistance acquisition, where gene amplifications contributed to one-third of resistance acquisition events. Beyond confirming previously identified multidrug-resistance mechanisms, we discovered hitherto unrecognized drug target-inhibitor pairs, including thymidylate synthase and a benzoquinazolinone, farnesyltransferase and a pyrimidinedione, and a dipeptidylpeptidase and an arylurea. This exploration of the P. falciparum resistome and druggable genome will likely guide drug discovery and structural biology efforts, while also advancing our understanding of resistance mechanisms available to the malaria parasite. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Nitrogen Cycle Evaluation (NiCE) Chip for the Simultaneous Analysis of Multiple N-Cycle Associated Genes.

PubMed

Oshiki, Mamoru; Segawa, Takahiro; Ishii, Satoshi

2018-02-02

Various microorganisms play key roles in the Nitrogen (N) cycle. Quantitative PCR (qPCR) and PCR-amplicon sequencing of the N cycle functional genes allow us to analyze the abundance and diversity of microbes responsible in the N transforming reactions in various environmental samples. However, analysis of multiple target genes can be cumbersome and expensive. PCR-independent analysis, such as metagenomics and metatranscriptomics, is useful but expensive especially when we analyze multiple samples and try to detect N cycle functional genes present at relatively low abundance. Here, we present the application of microfluidic qPCR chip technology to simultaneously quantify and prepare amplicon sequence libraries for multiple N cycle functional genes as well as taxon-specific 16S rRNA gene markers for many samples. This approach, named as N cycle evaluation (NiCE) chip, was evaluated by using DNA from pure and artificially mixed bacterial cultures and by comparing the results with those obtained by conventional qPCR and amplicon sequencing methods. Quantitative results obtained by the NiCE chip were comparable to those obtained by conventional qPCR. In addition, the NiCE chip was successfully applied to examine abundance and diversity of N cycle functional genes in wastewater samples. Although non-specific amplification was detected on the NiCE chip, this could be overcome by optimizing the primer sequences in the future. As the NiCE chip can provide high-throughput format to quantify and prepare sequence libraries for multiple N cycle functional genes, this tool should advance our ability to explore N cycling in various samples. Importance. We report a novel approach, namely Nitrogen Cycle Evaluation (NiCE) chip by using microfluidic qPCR chip technology. By sequencing the amplicons recovered from the NiCE chip, we can assess diversities of the N cycle functional genes. The NiCE chip technology is applicable to analyze the temporal dynamics of the N cycle gene transcriptions in wastewater treatment bioreactors. The NiCE chip can provide high-throughput format to quantify and prepare sequence libraries for multiple N cycle functional genes. While there is a room for future improvement, this tool should significantly advance our ability to explore the N cycle in various environmental samples. Copyright © 2018 American Society for Microbiology.

Inferring molecular interactions pathways from eQTL data

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

Rashid, Imran; McDermott, Jason E.; Samudrala, Ram

Analysis of expression quantitative trait loci (eQTL) helps elucidate the connection between genotype, gene expression levels, and phenotype. However, standard statistical genetics can only attribute changes in expression levels to loci on the genome, not specific genes. Each locus can contain many genes, making it very difficult to discover which gene is controlling the expression levels of other genes. Furthermore, it is even more difficult to find a pathway of molecular interactions responsible for controlling the expression levels. Here we describe a series of techniques for finding explanatory pathways by exploring graphs of molecular interactions. We show several simple methodsmore » can find complete pathways the explain the mechanism of differential expression in eQTL data.« less

DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis.

PubMed

Yu, Guangchuang; Wang, Li-Gen; Yan, Guang-Rong; He, Qing-Yu

2015-02-15

Disease ontology (DO) annotates human genes in the context of disease. DO is important annotation in translating molecular findings from high-throughput data to clinical relevance. DOSE is an R package providing semantic similarity computations among DO terms and genes which allows biologists to explore the similarities of diseases and of gene functions in disease perspective. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented to support discovering disease associations of high-throughput biological data. This allows biologists to verify disease relevance in a biological experiment and identify unexpected disease associations. Comparison among gene clusters is also supported. DOSE is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (http://www.bioconductor.org/packages/release/bioc/html/DOSE.html). Supplementary data are available at Bioinformatics online. gcyu@connect.hku.hk or tqyhe@jnu.edu.cn. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Descent graphs in pedigree analysis: applications to haplotyping, location scores, and marker-sharing statistics.

PubMed Central

Sobel, E.; Lange, K.

1996-01-01

The introduction of stochastic methods in pedigree analysis has enabled geneticists to tackle computations intractable by standard deterministic methods. Until now these stochastic techniques have worked by running a Markov chain on the set of genetic descent states of a pedigree. Each descent state specifies the paths of gene flow in the pedigree and the founder alleles dropped down each path. The current paper follows up on a suggestion by Elizabeth Thompson that genetic descent graphs offer a more appropriate space for executing a Markov chain. A descent graph specifies the paths of gene flow but not the particular founder alleles traveling down the paths. This paper explores algorithms for implementing Thompson's suggestion for codominant markers in the context of automatic haplotyping, estimating location scores, and computing gene-clustering statistics for robust linkage analysis. Realistic numerical examples demonstrate the feasibility of the algorithms. PMID:8651310

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 highly adaptable, integrative, yet flexible tool which can be used for automated quality control, analysis, annotation and visualization of microarray data, constituting a starting point for further data interpretation and integration with numerous other tools.

Emerging Use of Gene Expression Microarrays in Plant Physiology

DOE PAGES

Wullschleger, Stan D.; Difazio, Stephen P.

2003-01-01

Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology weremore » selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.« less

A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae

PubMed Central

Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol; Scalcinati, Gionata; Fagerberg, Linn; Uhlén, Matthias; Nielsen, Jens

2012-01-01

RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the Illumina platform, and to perform a cross-platform comparison based on the results obtained through Affymetrix microarray. As a case study for our work we, used the Saccharomyces cerevisiae strain CEN.PK 113-7D, grown under two different conditions (batch and chemostat). Here, we asses the influence of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays) for gene expression analysis and addresses the contribution of the different steps involved in the analysis of RNA-seq data. PMID:22965124

Exploring Transcription Factors-microRNAs Co-regulation Networks in Schizophrenia.

PubMed

Xu, Yong; Yue, Weihua; Yao Shugart, Yin; Li, Sheng; Cai, Lei; Li, Qiang; Cheng, Zaohuo; Wang, Guoqiang; Zhou, Zhenhe; Jin, Chunhui; Yuan, Jianmin; Tian, Lin; Wang, Jun; Zhang, Kai; Zhang, Kerang; Liu, Sha; Song, Yuqing; Zhang, Fuquan

2016-07-01

Transcriptional factors (TFs) and microRNAs (miRNAs) have been recognized as 2 classes of principal gene regulators that may be responsible for genome coexpression changes observed in schizophrenia (SZ). This study aims to (1) identify differentially coexpressed genes (DCGs) in 3 mRNA expression microarray datasets; (2) explore potential interactions among the DCGs, and differentially expressed miRNAs identified in our dataset composed of early-onset SZ patients and healthy controls; (3) validate expression levels of some key transcripts; and (4) explore the druggability of DCGs using the curated database. We detected a differential coexpression network associated with SZ and found that 9 out of the 12 regulators were replicated in either of the 2 other datasets. Leveraging the differentially expressed miRNAs identified in our previous dataset, we constructed a miRNA-TF-gene network relevant to SZ, including an EGR1-miR-124-3p-SKIL feed-forward loop. Our real-time quantitative PCR analysis indicated the overexpression of miR-124-3p, the under expression of SKIL and EGR1 in the blood of SZ patients compared with controls, and the direction of change of miR-124-3p and SKIL mRNA levels in SZ cases were reversed after a 12-week treatment cycle. Our druggability analysis revealed that many of these genes have the potential to be drug targets. Together, our results suggest that coexpression network abnormalities driven by combinatorial and interactive action from TFs and miRNAs may contribute to the development of SZ and be relevant to the clinical treatment of the disease. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Exploring Transcription Factors-microRNAs Co-regulation Networks in Schizophrenia

PubMed Central

Xu, Yong; Yue, Weihua; Yao Shugart, Yin; Li, Sheng; Cai, Lei; Li, Qiang; Cheng, Zaohuo; Wang, Guoqiang; Zhou, Zhenhe; Jin, Chunhui; Yuan, Jianmin; Tian, Lin; Wang, Jun; Zhang, Kai; Zhang, Kerang; Liu, Sha; Song, Yuqing; Zhang, Fuquan

2016-01-01

Background: Transcriptional factors (TFs) and microRNAs (miRNAs) have been recognized as 2 classes of principal gene regulators that may be responsible for genome coexpression changes observed in schizophrenia (SZ). Methods: This study aims to (1) identify differentially coexpressed genes (DCGs) in 3 mRNA expression microarray datasets; (2) explore potential interactions among the DCGs, and differentially expressed miRNAs identified in our dataset composed of early-onset SZ patients and healthy controls; (3) validate expression levels of some key transcripts; and (4) explore the druggability of DCGs using the curated database. Results: We detected a differential coexpression network associated with SZ and found that 9 out of the 12 regulators were replicated in either of the 2 other datasets. Leveraging the differentially expressed miRNAs identified in our previous dataset, we constructed a miRNA–TF–gene network relevant to SZ, including an EGR1–miR-124-3p–SKIL feed-forward loop. Our real-time quantitative PCR analysis indicated the overexpression of miR-124-3p, the under expression of SKIL and EGR1 in the blood of SZ patients compared with controls, and the direction of change of miR-124-3p and SKIL mRNA levels in SZ cases were reversed after a 12-week treatment cycle. Our druggability analysis revealed that many of these genes have the potential to be drug targets. Conclusions: Together, our results suggest that coexpression network abnormalities driven by combinatorial and interactive action from TFs and miRNAs may contribute to the development of SZ and be relevant to the clinical treatment of the disease. PMID:26609121

dbCPG: A web resource for cancer predisposition genes

PubMed Central

Wei, Ran; Yao, Yao; Yang, Wu; Zheng, Chun-Hou; Zhao, Min; Xia, Junfeng

2016-01-01

Cancer predisposition genes (CPGs) are genes in which inherited mutations confer highly or moderately increased risks of developing cancer. Identification of these genes and understanding the biological mechanisms that underlie them is crucial for the prevention, early diagnosis, and optimized management of cancer. Over the past decades, great efforts have been made to identify CPGs through multiple strategies. However, information on these CPGs and their molecular functions is scattered. To address this issue and provide a comprehensive resource for researchers, we developed the Cancer Predisposition Gene Database (dbCPG, Database URL: http://bioinfo.ahu.edu.cn:8080/dbCPG/index.jsp), the first literature-based gene resource for exploring human CPGs. It contains 827 human (724 protein-coding, 23 non-coding, and 80 unknown type genes), 637 rats, and 658 mouse CPGs. Furthermore, data mining was performed to gain insights into the understanding of the CPGs data, including functional annotation, gene prioritization, network analysis of prioritized genes and overlap analysis across multiple cancer types. A user-friendly web interface with multiple browse, search, and upload functions was also developed to facilitate access to the latest information on CPGs. Taken together, the dbCPG database provides a comprehensive data resource for further studies of cancer predisposition genes. PMID:27192119

Characterization of potential driver mutations involved in human breast cancer by computational approaches

PubMed Central

Rajendran, Barani Kumar; Deng, Chu-Xia

2017-01-01

Breast cancer is the second most frequently occurring form of cancer and is also the second most lethal cancer in women worldwide. A genetic mutation is one of the key factors that alter multiple cellular regulatory pathways and drive breast cancer initiation and progression yet nature of these cancer drivers remains elusive. In this article, we have reviewed various computational perspectives and algorithms for exploring breast cancer driver mutation genes. Using both frequency based and mutational exclusivity based approaches, we identified 195 driver genes and shortlisted 63 of them as candidate drivers for breast cancer using various computational approaches. Finally, we conducted network and pathway analysis to explore their functions in breast tumorigenesis including tumor initiation, progression, and metastasis. PMID:28477017

DOSim: an R package for similarity between diseases based on Disease Ontology.

PubMed

Li, Jiang; Gong, Binsheng; Chen, Xi; Liu, Tao; Wu, Chao; Zhang, Fan; Li, Chunquan; Li, Xiang; Rao, Shaoqi; Li, Xia

2011-06-29

The construction of the Disease Ontology (DO) has helped promote the investigation of diseases and disease risk factors. DO enables researchers to analyse disease similarity by adopting semantic similarity measures, and has expanded our understanding of the relationships between different diseases and to classify them. Simultaneously, similarities between genes can also be analysed by their associations with similar diseases. As a result, disease heterogeneity is better understood and insights into the molecular pathogenesis of similar diseases have been gained. However, bioinformatics tools that provide easy and straight forward ways to use DO to study disease and gene similarity simultaneously are required. We have developed an R-based software package (DOSim) to compute the similarity between diseases and to measure the similarity between human genes in terms of diseases. DOSim incorporates a DO-based enrichment analysis function that can be used to explore the disease feature of an independent gene set. A multilayered enrichment analysis (GO and KEGG annotation) annotation function that helps users explore the biological meaning implied in a newly detected gene module is also part of the DOSim package. We used the disease similarity application to demonstrate the relationship between 128 different DO cancer terms. The hierarchical clustering of these 128 different cancers showed modular characteristics. In another case study, we used the gene similarity application on 361 obesity-related genes. The results revealed the complex pathogenesis of obesity. In addition, the gene module detection and gene module multilayered annotation functions in DOSim when applied on these 361 obesity-related genes helped extend our understanding of the complex pathogenesis of obesity risk phenotypes and the heterogeneity of obesity-related diseases. DOSim can be used to detect disease-driven gene modules, and to annotate the modules for functions and pathways. The DOSim package can also be used to visualise DO structure. DOSim can reflect the modular characteristic of disease related genes and promote our understanding of the complex pathogenesis of diseases. DOSim is available on the Comprehensive R Archive Network (CRAN) or http://bioinfo.hrbmu.edu.cn/dosim.

Analyzing Immunoglobulin Repertoires

PubMed Central

Chaudhary, Neha; Wesemann, Duane R.

2018-01-01

Somatic assembly of T cell receptor and B cell receptor (BCR) genes produces a vast diversity of lymphocyte antigen recognition capacity. The advent of efficient high-throughput sequencing of lymphocyte antigen receptor genes has recently generated unprecedented opportunities for exploration of adaptive immune responses. With these opportunities have come significant challenges in understanding the analysis techniques that most accurately reflect underlying biological phenomena. In this regard, sample preparation and sequence analysis techniques, which have largely been borrowed and adapted from other fields, continue to evolve. Here, we review current methods and challenges of library preparation, sequencing and statistical analysis of lymphocyte receptor repertoire studies. We discuss the general steps in the process of immune repertoire generation including sample preparation, platforms available for sequencing, processing of sequencing data, measurable features of the immune repertoire, and the statistical tools that can be used for analysis and interpretation of the data. Because BCR analysis harbors additional complexities, such as immunoglobulin (Ig) (i.e., antibody) gene somatic hypermutation and class switch recombination, the emphasis of this review is on Ig/BCR sequence analysis. PMID:29593723

A microarray whole-genome gene expression dataset in a rat model of inflammatory corneal angiogenesis.

PubMed

Mukwaya, Anthony; Lindvall, Jessica M; Xeroudaki, Maria; Peebo, Beatrice; Ali, Zaheer; Lennikov, Anton; Jensen, Lasse Dahl Ejby; Lagali, Neil

2016-11-22

In angiogenesis with concurrent inflammation, many pathways are activated, some linked to VEGF and others largely VEGF-independent. Pathways involving inflammatory mediators, chemokines, and micro-RNAs may play important roles in maintaining a pro-angiogenic environment or mediating angiogenic regression. Here, we describe a gene expression dataset to facilitate exploration of pro-angiogenic, pro-inflammatory, and remodelling/normalization-associated genes during both an active capillary sprouting phase, and in the restoration of an avascular phenotype. The dataset was generated by microarray analysis of the whole transcriptome in a rat model of suture-induced inflammatory corneal neovascularisation. Regions of active capillary sprout growth or regression in the cornea were harvested and total RNA extracted from four biological replicates per group. High quality RNA was obtained for gene expression analysis using microarrays. Fold change of selected genes was validated by qPCR, and protein expression was evaluated by immunohistochemistry. We provide a gene expression dataset that may be re-used to investigate corneal neovascularisation, and may also have implications in other contexts of inflammation-mediated angiogenesis.

Analysis, annotation, and profiling of the oat seed transcriptome

USDA-ARS?s Scientific Manuscript database

Novel high-throughput next generation sequencing (NGS) technologies are providing opportunities to explore genomes and transcriptomes in a cost-effective manner. To construct a gene expression atlas of developing oat (Avena sativa) seeds, two software packages specifically designed for RNA-seq (Trin...

PRAPI: post-transcriptional regulation analysis pipeline for Iso-Seq.

PubMed

Gao, Yubang; Wang, Huiyuan; Zhang, Hangxiao; Wang, Yongsheng; Chen, Jinfeng; Gu, Lianfeng

2018-05-01

The single-molecule real-time (SMRT) isoform sequencing (Iso-Seq) based on Pacific Bioscience (PacBio) platform has received increasing attention for its ability to explore full-length isoforms. Thus, comprehensive tools for Iso-Seq bioinformatics analysis are extremely useful. Here, we present a one-stop solution for Iso-Seq analysis, called PRAPI to analyze alternative transcription initiation (ATI), alternative splicing (AS), alternative cleavage and polyadenylation (APA), natural antisense transcripts (NAT), and circular RNAs (circRNAs) comprehensively. PRAPI is capable of combining Iso-Seq full-length isoforms with short read data, such as RNA-Seq or polyadenylation site sequencing (PAS-seq) for differential expression analysis of NAT, AS, APA and circRNAs. Furthermore, PRAPI can annotate new genes and correct mis-annotated genes when gene annotation is available. Finally, PRAPI generates high-quality vector graphics to visualize and highlight the Iso-Seq results. The Dockerfile of PRAPI is available at http://www.bioinfor.org/tool/PRAPI. lfgu@fafu.edu.cn.

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering

PubMed Central

2013-01-01

Background The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development. Results In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space. Conclusions Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship. PMID:23845024

Transcriptome profiling analysis reveals the role of silique in controlling seed oil content in Brassica napus.

PubMed

Huang, Ke-Lin; Zhang, Mei-Li; Ma, Guang-Jing; Wu, Huan; Wu, Xiao-Ming; Ren, Feng; Li, Xue-Bao

2017-01-01

Seed oil content is an important agronomic trait in oilseed rape. However, the molecular mechanism of oil accumulation in rapeseeds is unclear so far. In this report, RNA sequencing technique (RNA-Seq) was performed to explore differentially expressed genes in siliques of two Brassica napus lines (HFA and LFA which contain high and low oil contents in seeds, respectively) at 15 and 25 days after pollination (DAP). The RNA-Seq results showed that 65746 and 66033 genes were detected in siliques of low oil content line at 15 and 25 DAP, and 65236 and 65211 genes were detected in siliques of high oil content line at 15 and 25 DAP, respectively. By comparative analysis, the differentially expressed genes (DEGs) were identified in siliques of these lines. The DEGs were involved in multiple pathways, including metabolic pathways, biosynthesis of secondary metabolic, photosynthesis, pyruvate metabolism, fatty metabolism, glycophospholipid metabolism, and DNA binding. Also, DEGs were related to photosynthesis, starch and sugar metabolism, pyruvate metabolism, and lipid metabolism at different developmental stage, resulting in the differential oil accumulation in seeds. Furthermore, RNA-Seq and qRT-PCR data revealed that some transcription factors positively regulate seed oil content. Thus, our data provide the valuable information for further exploring the molecular mechanism of lipid biosynthesis and oil accumulation in B. nupus.

Transcriptome profiling analysis reveals the role of silique in controlling seed oil content in Brassica napus

PubMed Central

Huang, Ke-Lin; Zhang, Mei-Li; Ma, Guang-Jing; Wu, Huan; Wu, Xiao-Ming; Ren, Feng

2017-01-01

Seed oil content is an important agronomic trait in oilseed rape. However, the molecular mechanism of oil accumulation in rapeseeds is unclear so far. In this report, RNA sequencing technique (RNA-Seq) was performed to explore differentially expressed genes in siliques of two Brassica napus lines (HFA and LFA which contain high and low oil contents in seeds, respectively) at 15 and 25 days after pollination (DAP). The RNA-Seq results showed that 65746 and 66033 genes were detected in siliques of low oil content line at 15 and 25 DAP, and 65236 and 65211 genes were detected in siliques of high oil content line at 15 and 25 DAP, respectively. By comparative analysis, the differentially expressed genes (DEGs) were identified in siliques of these lines. The DEGs were involved in multiple pathways, including metabolic pathways, biosynthesis of secondary metabolic, photosynthesis, pyruvate metabolism, fatty metabolism, glycophospholipid metabolism, and DNA binding. Also, DEGs were related to photosynthesis, starch and sugar metabolism, pyruvate metabolism, and lipid metabolism at different developmental stage, resulting in the differential oil accumulation in seeds. Furthermore, RNA-Seq and qRT-PCR data revealed that some transcription factors positively regulate seed oil content. Thus, our data provide the valuable information for further exploring the molecular mechanism of lipid biosynthesis and oil accumulation in B. nupus. PMID:28594951

Region Evolution eXplorer - A tool for discovering evolution trends in ontology regions.

PubMed

Christen, Victor; Hartung, Michael; Groß, Anika

2015-01-01

A large number of life science ontologies has been developed to support different application scenarios such as gene annotation or functional analysis. The continuous accumulation of new insights and knowledge affects specific portions in ontologies and thus leads to their adaptation. Therefore, it is valuable to study which ontology parts have been extensively modified or remained unchanged. Users can monitor the evolution of an ontology to improve its further development or apply the knowledge in their applications. Here we present REX (Region Evolution eXplorer) a web-based system for exploring the evolution of ontology parts (regions). REX provides an analysis platform for currently about 1,000 versions of 16 well-known life science ontologies. Interactive workflows allow an explorative analysis of changing ontology regions and can be used to study evolution trends for long-term periods. REX is a web application providing an interactive and user-friendly interface to identify (un)stable regions in large life science ontologies. It is available at http://www.izbi.de/rex.

Functional relevance for type 1 diabetes mellitus-associated genetic variants by using integrative analyses.

PubMed

Qiu, Ying-Hua; Deng, Fei-Yan; Tang, Zai-Xiang; Jiang, Zhen-Huan; Lei, Shu-Feng

2015-10-01

Type 1 diabetes mellitus (type 1 DM) is an autoimmune disease. Although genome-wide association studies (GWAS) and meta-analyses have successfully identified numerous type 1 DM-associated susceptibility loci, the underlying mechanisms for these susceptibility loci are currently largely unclear. Based on publicly available datasets, we performed integrative analyses (i.e., integrated gene relationships among implicated loci, differential gene expression analysis, functional prediction and functional annotation clustering analysis) and combined with expression quantitative trait loci (eQTL) results to further explore function mechanisms underlying the associations between genetic variants and type 1 DM. Among a total of 183 type 1 DM-associated SNPs, eQTL analysis showed that 17 SNPs with cis-regulated eQTL effects on 9 genes. All the 9 eQTL genes enrich in immune-related pathways or Gene Ontology (GO) terms. Functional prediction analysis identified 5 SNPs located in transcription factor (TF) binding sites. Of the 9 eQTL genes, 6 (TAP2, HLA-DOB, HLA-DQB1, HLA-DQA1, HLA-DRB5 and CTSH) were differentially expressed in type 1 DM-associated related cells. Especially, rs3825932 in CTSH has integrative functional evidence supporting the association with type 1 DM. These findings indicated that integrative analyses can yield important functional information to link genetic variants and type 1 DM. Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis

PubMed Central

Gadelha, Luiz; Ribeiro-Alves, Marcelo; Porto, Fábio

2017-01-01

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet. PMID:28695067

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis.

PubMed

Costa, Raquel L; Gadelha, Luiz; Ribeiro-Alves, Marcelo; Porto, Fábio

2017-01-01

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet.

Genome-Wide Identification, Characterization and Expression Analysis of the TCP Gene Family in Prunus mume

PubMed Central

Zhou, Yuzhen; Xu, Zongda; Zhao, Kai; Yang, Weiru; Cheng, Tangren; Wang, Jia; Zhang, Qixiang

2016-01-01

TCP proteins, belonging to a plant-specific transcription factors family, are known to have great functions in plant development, especially flower and leaf development. However, there is little information about this gene family in Prunus mume, which is widely cultivated in China as an ornamental and fruit tree. Here a genome-wide analysis of TCP genes was performed to explore their evolution in P. mume. Nineteen PmTCPs were identified and three of them contained putative miR319 target sites. Phylogenetic and comprehensive bioinformatics analyses of these genes revealed that different types of TCP genes had undergone different evolutionary processes and the genes in the same clade had similar chromosomal location, gene structure, and conserved domains. Expression analysis of these PmTCPs indicated that there were diverse expression patterns among different clades. Most TCP genes were predominantly expressed in flower, leaf, and stem, and showed high expression levels in the different stages of flower bud differentiation, especially in petal formation stage and gametophyte development. Genes in TCP-P subfamily had main roles in both flower development and gametophyte development. The CIN genes in double petal cultivars might have key roles in the formation of petal, while they were correlated with gametophyte development in the single petal cultivar. The CYC/TB1 type genes were highly detected in the formation of petal and pistil. The less-complex flower types of P. mume might result from the fact that there were only two CYC type genes present in P. mume and a lack of CYC2 genes to control the identity of flower types. These results lay the foundation for further study on the functions of TCP genes during flower development. PMID:27630648

Genome-Wide Identification, Characterization and Expression Analysis of the TCP Gene Family in Prunus mume.

PubMed

Zhou, Yuzhen; Xu, Zongda; Zhao, Kai; Yang, Weiru; Cheng, Tangren; Wang, Jia; Zhang, Qixiang

2016-01-01

TCP proteins, belonging to a plant-specific transcription factors family, are known to have great functions in plant development, especially flower and leaf development. However, there is little information about this gene family in Prunus mume, which is widely cultivated in China as an ornamental and fruit tree. Here a genome-wide analysis of TCP genes was performed to explore their evolution in P. mume. Nineteen PmTCPs were identified and three of them contained putative miR319 target sites. Phylogenetic and comprehensive bioinformatics analyses of these genes revealed that different types of TCP genes had undergone different evolutionary processes and the genes in the same clade had similar chromosomal location, gene structure, and conserved domains. Expression analysis of these PmTCPs indicated that there were diverse expression patterns among different clades. Most TCP genes were predominantly expressed in flower, leaf, and stem, and showed high expression levels in the different stages of flower bud differentiation, especially in petal formation stage and gametophyte development. Genes in TCP-P subfamily had main roles in both flower development and gametophyte development. The CIN genes in double petal cultivars might have key roles in the formation of petal, while they were correlated with gametophyte development in the single petal cultivar. The CYC/TB1 type genes were highly detected in the formation of petal and pistil. The less-complex flower types of P. mume might result from the fact that there were only two CYC type genes present in P. mume and a lack of CYC2 genes to control the identity of flower types. These results lay the foundation for further study on the functions of TCP genes during flower development.

Prediction of target genes for miR-140-5p in pulmonary arterial hypertension using bioinformatics methods.

PubMed

Li, Fangwei; Shi, Wenhua; Wan, Yixin; Wang, Qingting; Feng, Wei; Yan, Xin; Wang, Jian; Chai, Limin; Zhang, Qianqian; Li, Manxiang

2017-12-01

The expression of microRNA (miR)-140-5p is known to be reduced in both pulmonary arterial hypertension (PAH) patients and monocrotaline-induced PAH models in rat. Identification of target genes for miR-140-5p with bioinformatics analysis may reveal new pathways and connections in PAH. This study aimed to explore downstream target genes and relevant signaling pathways regulated by miR-140-5p to provide theoretical evidences for further researches on role of miR-140-5p in PAH. Multiple downstream target genes and upstream transcription factors (TFs) of miR-140-5p were predicted in the analysis. Gene ontology (GO) enrichment analysis indicated that downstream target genes of miR-140-5p were enriched in many biological processes, such as biological regulation, signal transduction, response to chemical stimulus, stem cell proliferation, cell surface receptor signaling pathways. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis found that downstream target genes were mainly located in Notch, TGF-beta, PI3K/Akt, and Hippo signaling pathway. According to TF-miRNA-mRNA network, the important downstream target genes of miR-140-5p were PPI, TGF-betaR1, smad4, JAG1, ADAM10, FGF9, PDGFRA, VEGFA, LAMC1, TLR4, and CREB. After thoroughly reviewing published literature, we found that 23 target genes and seven signaling pathways were truly inhibited by miR-140-5p in various tissues or cells; most of these verified targets were in accordance with our present prediction. Other predicted targets still need further verification in vivo and in vitro .

Identification of Biological Targets of Therapeutic Intervention for Hepatocellular Carcinoma by Integrated Bioinformatical Analysis.

PubMed

Hu, Wei Qi; Wang, Wei; Fang, Di Long; Yin, Xue Feng

2018-05-24

BACKGROUND We screened the potential molecular targets and investigated the molecular mechanisms of hepatocellular carcinoma (HCC). MATERIAL AND METHODS Microarray data of GSE47786, including the 40 μM berberine-treated HepG2 human hepatoma cell line and 0.08% DMSO-treated as control cells samples, was downloaded from the GEO database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed; the protein-protein interaction (PPI) networks were constructed using STRING database and Cytoscape; the genetic alteration, neighboring genes networks, and survival analysis of hub genes were explored by cBio portal; and the expression of mRNA level of hub genes was obtained from the Oncomine databases. RESULTS A total of 56 upregulated and 8 downregulated DEGs were identified. The GO analysis results were significantly enriched in cell-cycle arrest, regulation of transcription, DNA-dependent, protein amino acid phosphorylation, cell cycle, and apoptosis. The KEGG pathway analysis showed that DEGs were enriched in MAPK signaling pathway, ErbB signaling pathway, and p53 signaling pathway. JUN, EGR1, MYC, and CDKN1A were identified as hub genes in PPI networks. The genetic alteration of hub genes was mainly concentrated in amplification. TP53, NDRG1, and MAPK15 were found in neighboring genes networks. Altered genes had worse overall survival and disease-free survival than unaltered genes. The expressions of EGR1, MYC, and CDKN1A were significantly increased, but expression of JUN was not, in the Roessler Liver datasets. CONCLUSIONS We found that JUN, EGR1, MYC, and CDKN1A might be used as diagnostic and therapeutic molecular biomarkers and broaden our understanding of the molecular mechanisms of HCC.

GENEASE: Real time bioinformatics tool for multi-omics and disease ontology exploration, analysis and visualization.

PubMed

Ghandikota, Sudhir; Hershey, Gurjit K Khurana; Mersha, Tesfaye B

2018-03-24

Advances in high-throughput sequencing technologies have made it possible to generate multiple omics data at an unprecedented rate and scale. The accumulation of these omics data far outpaces the rate at which biologists can mine and generate new hypothesis to test experimentally. There is an urgent need to develop a myriad of powerful tools to efficiently and effectively search and filter these resources to address specific post-GWAS functional genomics questions. However, to date, these resources are scattered across several databases and often lack a unified portal for data annotation and analytics. In addition, existing tools to analyze and visualize these databases are highly fragmented, resulting researchers to access multiple applications and manual interventions for each gene or variant in an ad hoc fashion until all the questions are answered. In this study, we present GENEASE, a web-based one-stop bioinformatics tool designed to not only query and explore multi-omics and phenotype databases (e.g., GTEx, ClinVar, dbGaP, GWAS Catalog, ENCODE, Roadmap Epigenomics, KEGG, Reactome, Gene and Phenotype Ontology) in a single web interface but also to perform seamless post genome-wide association downstream functional and overlap analysis for non-coding regulatory variants. GENEASE accesses over 50 different databases in public domain including model organism-specific databases to facilitate gene/variant and disease exploration, enrichment and overlap analysis in real time. It is a user-friendly tool with point-and-click interface containing links for support information including user manual and examples. GENEASE can be accessed freely at http://research.cchmc.org/mershalab/genease_new/login.html. Tesfaye.Mersha@cchmc.org, Sudhir.Ghandikota@cchmc.org. Supplementary data are available at Bioinformatics online.

Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

PubMed Central

Li, Dapeng; Heiling, Sven; Baldwin, Ian T.

2016-01-01

Secondary metabolite diversity is considered an important fitness determinant for plants’ biotic and abiotic interactions in nature. This diversity can be examined in two dimensions. The first one considers metabolite diversity across plant species. A second way of looking at this diversity is by considering the tissue-specific localization of pathways underlying secondary metabolism within a plant. Although these cross-tissue metabolite variations are increasingly regarded as important readouts of tissue-level gene function and regulatory processes, they have rarely been comprehensively explored by nontargeted metabolomics. As such, important questions have remained superficially addressed. For instance, which tissues exhibit prevalent signatures of metabolic specialization? Reciprocally, which metabolites contribute most to this tissue specialization in contrast to those metabolites exhibiting housekeeping characteristics? Here, we explore tissue-level metabolic specialization in Nicotiana attenuata, an ecological model with rich secondary metabolism, by combining tissue-wide nontargeted mass spectral data acquisition, information theory analysis, and tandem MS (MS/MS) molecular networks. This analysis was conducted for two different methanolic extracts of 14 tissues and deconvoluted 895 nonredundant MS/MS spectra. Using information theory analysis, anthers were found to harbor the most specialized metabolome, and most unique metabolites of anthers and other tissues were annotated through MS/MS molecular networks. Tissue–metabolite association maps were used to predict tissue-specific gene functions. Predictions for the function of two UDP-glycosyltransferases in flavonoid metabolism were confirmed by virus-induced gene silencing. The present workflow allows biologists to amortize the vast amount of data produced by modern MS instrumentation in their quest to understand gene function. PMID:27821729

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

PubMed

Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

2011-01-01

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

Ossification of the posterior longitudinal ligament related genes identification using microarray gene expression profiling and bioinformatics analysis.

PubMed

He, Hailong; Mao, Lingzhou; Xu, Peng; Xi, Yanhai; Xu, Ning; Xue, Mingtao; Yu, Jiangming; Ye, Xiaojian

2014-01-10

Ossification of the posterior longitudinal ligament (OPLL) is a kind of disease with physical barriers and neurological disorders. The objective of this study was to explore the differentially expressed genes (DEGs) in OPLL patient ligament cells and identify the target sites for the prevention and treatment of OPLL in clinic. Gene expression data GSE5464 was downloaded from Gene Expression Omnibus; then DEGs were screened by limma package in R language, and changed functions and pathways of OPLL cells compared to normal cells were identified by DAVID (The Database for Annotation, Visualization and Integrated Discovery); finally, an interaction network of DEGs was constructed by string. A total of 1536 DEGs were screened, with 31 down-regulated and 1505 up-regulated genes. Response to wounding function and Toll-like receptor signaling pathway may involve in the development of OPLL. Genes, such as PDGFB, PRDX2 may involve in OPLL through response to wounding function. Toll-like receptor signaling pathway enriched genes such as TLR1, TLR5, and TLR7 may involve in spine cord injury in OPLL. PIK3R1 was the hub gene in the network of DEGs with the highest degree; INSR was one of the most closely related genes of it. OPLL related genes screened by microarray gene expression profiling and bioinformatics analysis may be helpful for elucidating the mechanism of OPLL. © 2013.

Target gene screening and evaluation of prognostic values in non-small cell lung cancers by bioinformatics analysis.

PubMed

Piao, Junjie; Sun, Jie; Yang, Yang; Jin, Tiefeng; Chen, Liyan; Lin, Zhenhua

2018-03-20

Non-small cell lung cancer (NSCLC) is the major leading cause of cancer-related deaths worldwide. This study aims to explore molecular mechanism of NSCLC. Microarray dataset was obtained from the Gene Expression Omnibus (GEO) database, and analyzed by using GEO2R. Functional and pathway enrichment analysis were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Then, STRING, Cytoscape and MCODE were applied to construct the Protein-protein interaction (PPI) network and screen hub genes. Following, overall survival (OS) analysis of hub genes was performed by using the Kaplan-Meier plotter online tool. Moreover, miRecords was also applied to predict the targets of the differentially expressed microRNAs (DEMs). A total of 228 DEGs were identified, and they were mainly enriched in the terms of cell adhesion molecules, leukocyte transendothelial migration and ECM-receptor interaction. A PPI network was constructed, and 16 hub genes were identified, including TEK, ANGPT1, MMP9, VWF, CDH5, EDN1, ESAM, CCNE1, CDC45, PRC1, CCNB2, AURKA, MELK, CDC20, TOP2A and PTTG1. Among the genes, expressions of 14 hub genes were associated with prognosis of NSCLC patients. Additionally, a total of 11 DEMs were also identified. Our results provide some potential underlying biomarkers for NSCLC. Further studies are required to elucidate the pathogenesis of NSCLC. Copyright © 2018 Elsevier B.V. All rights reserved.

Integrative omics analysis. A study based on Plasmodium falciparum mRNA and protein data.

PubMed

Tomescu, Oana A; Mattanovich, Diethard; Thallinger, Gerhard G

2014-01-01

Technological improvements have shifted the focus from data generation to data analysis. The availability of large amounts of data from transcriptomics, protemics and metabolomics experiments raise new questions concerning suitable integrative analysis methods. We compare three integrative analysis techniques (co-inertia analysis, generalized singular value decomposition and integrative biclustering) by applying them to gene and protein abundance data from the six life cycle stages of Plasmodium falciparum. Co-inertia analysis is an analysis method used to visualize and explore gene and protein data. The generalized singular value decomposition has shown its potential in the analysis of two transcriptome data sets. Integrative Biclustering applies biclustering to gene and protein data. Using CIA, we visualize the six life cycle stages of Plasmodium falciparum, as well as GO terms in a 2D plane and interpret the spatial configuration. With GSVD, we decompose the transcriptomic and proteomic data sets into matrices with biologically meaningful interpretations and explore the processes captured by the data sets. IBC identifies groups of genes, proteins, GO Terms and life cycle stages of Plasmodium falciparum. We show method-specific results as well as a network view of the life cycle stages based on the results common to all three methods. Additionally, by combining the results of the three methods, we create a three-fold validated network of life cycle stage specific GO terms: Sporozoites are associated with transcription and transport; merozoites with entry into host cell as well as biosynthetic and metabolic processes; rings with oxidation-reduction processes; trophozoites with glycolysis and energy production; schizonts with antigenic variation and immune response; gametocyctes with DNA packaging and mitochondrial transport. Furthermore, the network connectivity underlines the separation of the intraerythrocytic cycle from the gametocyte and sporozoite stages. Using integrative analysis techniques, we can integrate knowledge from different levels and obtain a wider view of the system under study. The overlap between method-specific and common results is considerable, even if the basic mathematical assumptions are very different. The three-fold validated network of life cycle stage characteristics of Plasmodium falciparum could identify a large amount of the known associations from literature in only one study.

Integrative omics analysis. A study based on Plasmodium falciparum mRNA and protein data

PubMed Central

2014-01-01

Background Technological improvements have shifted the focus from data generation to data analysis. The availability of large amounts of data from transcriptomics, protemics and metabolomics experiments raise new questions concerning suitable integrative analysis methods. We compare three integrative analysis techniques (co-inertia analysis, generalized singular value decomposition and integrative biclustering) by applying them to gene and protein abundance data from the six life cycle stages of Plasmodium falciparum. Co-inertia analysis is an analysis method used to visualize and explore gene and protein data. The generalized singular value decomposition has shown its potential in the analysis of two transcriptome data sets. Integrative Biclustering applies biclustering to gene and protein data. Results Using CIA, we visualize the six life cycle stages of Plasmodium falciparum, as well as GO terms in a 2D plane and interpret the spatial configuration. With GSVD, we decompose the transcriptomic and proteomic data sets into matrices with biologically meaningful interpretations and explore the processes captured by the data sets. IBC identifies groups of genes, proteins, GO Terms and life cycle stages of Plasmodium falciparum. We show method-specific results as well as a network view of the life cycle stages based on the results common to all three methods. Additionally, by combining the results of the three methods, we create a three-fold validated network of life cycle stage specific GO terms: Sporozoites are associated with transcription and transport; merozoites with entry into host cell as well as biosynthetic and metabolic processes; rings with oxidation-reduction processes; trophozoites with glycolysis and energy production; schizonts with antigenic variation and immune response; gametocyctes with DNA packaging and mitochondrial transport. Furthermore, the network connectivity underlines the separation of the intraerythrocytic cycle from the gametocyte and sporozoite stages. Conclusion Using integrative analysis techniques, we can integrate knowledge from different levels and obtain a wider view of the system under study. The overlap between method-specific and common results is considerable, even if the basic mathematical assumptions are very different. The three-fold validated network of life cycle stage characteristics of Plasmodium falciparum could identify a large amount of the known associations from literature in only one study. PMID:25033389

At what scale should microarray data be analyzed?

PubMed

Huang, Shuguang; Yeo, Adeline A; Gelbert, Lawrence; Lin, Xi; Nisenbaum, Laura; Bemis, Kerry G

2004-01-01

The hybridization intensities derived from microarray experiments, for example Affymetrix's MAS5 signals, are very often transformed in one way or another before statistical models are fitted. The motivation for performing transformation is usually to satisfy the model assumptions such as normality and homogeneity in variance. Generally speaking, two types of strategies are often applied to microarray data depending on the analysis need: correlation analysis where all the gene intensities on the array are considered simultaneously, and gene-by-gene ANOVA where each gene is analyzed individually. We investigate the distributional properties of the Affymetrix GeneChip signal data under the two scenarios, focusing on the impact of analyzing the data at an inappropriate scale. The Box-Cox type of transformation is first investigated for the strategy of pooling genes. The commonly used log-transformation is particularly applied for comparison purposes. For the scenario where analysis is on a gene-by-gene basis, the model assumptions such as normality are explored. The impact of using a wrong scale is illustrated by log-transformation and quartic-root transformation. When all the genes on the array are considered together, the dependent relationship between the expression and its variation level can be satisfactorily removed by Box-Cox transformation. When genes are analyzed individually, the distributional properties of the intensities are shown to be gene dependent. Derivation and simulation show that some loss of power is incurred when a wrong scale is used, but due to the robustness of the t-test, the loss is acceptable when the fold-change is not very large.

Integrated analysis of HPV-mediated immune alterations in cervical cancer.

PubMed

Chen, Long; Luan, Shaohong; Xia, Baoguo; Liu, Yansheng; Gao, Yuan; Yu, Hongyan; Mu, Qingling; Zhang, Ping; Zhang, Weina; Zhang, Shengmiao; Wei, Guopeng; Yang, Min; Li, Ke

2018-05-01

Human papillomavirus (HPV) infection is the primary cause of cervical cancer. HPV-mediated immune alterations are known to play crucial roles in determining viral persistence and host cell transformation. We sought to thoroughly understand HPV-directed immune alterations in cervical cancer by exploring publically available datasets. 130 HPV positive and 7 HPV negative cervical cancer cases from The Cancer Genome Atlas were compared for differences in gene expression levels and functional enrichment. Analyses for copy number variation (CNV) and genetic mutation were conducted for differentially expressed immune genes. Kaplan-Meier analysis was performed to assess survival and relapse differences across cases with or without alterations of the identified immune signature genes. Genes up-regulated in HPV positive cervical cancer were enriched for various gene ontology terms of immune processes (P=1.05E-14~1.00E-05). Integrated analysis of the differentially expressed immune genes identified 9 genes that displayed either CNV, genetic mutation and/or gene expression changes in at least 10% of the cases of HPV positive cervical cancer. Genomic amplification may cause elevated levels of these genes in some HPV positive cases. Finally, patients with alterations in at least one of the nine signature genes overall had earlier relapse compared to those without any alterations. The altered expression of either TFRC or MMP13 may indicate poor survival for a subset of cervical cancer patients (P=1.07E-07). We identified a novel immune gene signature for HPV positive cervical cancer that is potentially associated with early relapse of cervical cancer. Copyright © 2018. Published by Elsevier Inc.

The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.

PubMed

Zhang, Chaoyang; Peng, Li; Zhang, Yaqin; Liu, Zhaoyang; Li, Wenling; Chen, Shilian; Li, Guancheng

2017-06-01

Liver cancer is a serious threat to public health and has fairly complicated pathogenesis. Therefore, the identification of key genes and pathways is of much importance for clarifying molecular mechanism of hepatocellular carcinoma (HCC) initiation and progression. HCC-associated gene expression dataset was downloaded from Gene Expression Omnibus database. Statistical software R was used for significance analysis of differentially expressed genes (DEGs) between liver cancer samples and normal samples. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, based on R software, were applied for the identification of pathways in which DEGs significantly enriched. Cytoscape software was for the construction of protein-protein interaction (PPI) network and module analysis to find the hub genes and key pathways. Finally, weighted correlation network analysis (WGCNA) was conducted to further screen critical gene modules with similar expression pattern and explore their biological significance. Significance analysis identified 1230 DEGs with fold change >2, including 632 significantly down-regulated DEGs and 598 significantly up-regulated DEGs. GO term enrichment analysis suggested that up-regulated DEG significantly enriched in immune response, cell adhesion, cell migration, type I interferon signaling pathway, and cell proliferation, and the down-regulated DEG mainly enriched in response to endoplasmic reticulum stress and endoplasmic reticulum unfolded protein response. KEGG pathway analysis found DEGs significantly enriched in five pathways including complement and coagulation cascades, focal adhesion, ECM-receptor interaction, antigen processing and presentation, and protein processing in endoplasmic reticulum. The top 10 hub genes in HCC were separately GMPS, ACACA, ALB, TGFB1, KRAS, ERBB2, BCL2, EGFR, STAT3, and CD8A, which resulted from PPI network. The top 3 gene interaction modules in PPI network enriched in immune response, organ development, and response to other organism, respectively. WGCNA revealed that the confirmed eight gene modules significantly enriched in monooxygenase and oxidoreductase activity, response to endoplasmic reticulum stress, type I interferon signaling pathway, processing, presentation and binding of peptide antigen, cellular response to cadmium and zinc ion, cell locomotion and differentiation, ribonucleoprotein complex and RNA processing, and immune system process, respectively. In conclusion, we identified some key genes and pathways closely related with HCC initiation and progression by a series of bioinformatics analysis on DEGs. These screened genes and pathways provided for a more detailed molecular mechanism underlying HCC occurrence and progression, holding promise for acting as biomarkers and potential therapeutic targets.

Genomic and transcriptomic analyses reveal differential regulation of diverse terpenoid and polyketides secondary metabolites in Hericium erinaceus.

PubMed

Chen, Juan; Zeng, Xu; Yang, Yan Long; Xing, Yong Mei; Zhang, Qi; Li, Jia Mei; Ma, Ke; Liu, Hong Wei; Guo, Shun Xing

2017-08-31

The lion's mane mushroom Hericium erinaceus is a famous traditional medicinal fungus credited with anti-dementia activity and a producer of cyathane diterpenoid natural products (erinacines) useful against nervous system diseases. To date, few studies have explored the biosynthesis of these compounds, although their chemical synthesis is known. Here, we report the first genome and tanscriptome sequence of the medicinal fungus H. erinaceus. The size of the genome is 39.35 Mb, containing 9895 gene models. The genome of H. erinaceus reveals diverse enzymes and a large family of cytochrome P450 (CYP) proteins involved in the biosynthesis of terpenoid backbones, diterpenoids, sesquiterpenes and polyketides. Three gene clusters related to terpene biosynthesis and one gene cluster for polyketides biosynthesis (PKS) were predicted. Genes involved in terpenoid biosynthesis were generally upregulated in mycelia, while the PKS gene was upregulated in the fruiting body. Comparative genome analysis of 42 fungal species of Basidiomycota revealed that most edible and medicinal mushroom show many more gene clusters involved in terpenoid and polyketide biosynthesis compared to the pathogenic fungi. None of the gene clusters for terpenoid or polyketide biosynthesis were predicted in the poisonous mushroom Amanita muscaria. Our findings may facilitate future discovery and biosynthesis of bioactive secondary metabolites from H. erinaceus and provide fundamental information for exploring the secondary metabolites in other Basidiomycetes.

Transcriptional profiling by DDRT-PCR analysis reveals gene expression during seed development in Carya cathayensis Sarg.

PubMed

Huang, You-Jun; Zhou, Qin; Huang, Jian-Qin; Zeng, Yan-Ru; Wang, Zheng-Jia; Zhang, Qi-Xiang; Zhu, Yi-Hang; Shen, Chen; Zheng, Bing-Song

2015-06-01

Hickory (Carya cathayensis Sarg.) seed has one of the highest oil content and is rich in polyunsaturated fatty acids (PUFAs), which kernel is helpful to human health, particularly to human brain function. A better elucidation of lipid accumulation mechanism would help to improve hickory production and seed quality. DDRT-PCR analysis was used to examine gene expression in hickory at thirteen time points during seed development process. A total of 67 unique genes involved in seed development were obtained, and those expression patterns were further confirmed by semi-quantitative RT-PCR and real time RT-PCR analysis. Of them, the genes with known functions were involved in signal transduction, amino acid metabolism, nuclear metabolism, fatty acid metabolism, protein metabolism, carbon metabolism, secondary metabolism, oxidation of fatty acids and stress response, suggesting that hickory underwent a complex metabolism process in seed development. Furthermore, 6 genes related to fatty acid synthesis were explored, and their functions in seed development process were further discussed. The data obtained here would provide the first clues for guiding further functional studies of fatty acid synthesis in hickory. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Comprehensive Genomic Analysis and Expression Profiling of Phospholipase C Gene Family during Abiotic Stresses and Development in Rice

PubMed Central

Singh, Amarjeet; Kanwar, Poonam; Pandey, Amita; Tyagi, Akhilesh K.; Sopory, Sudhir K.; Kapoor, Sanjay; Pandey, Girdhar K.

2013-01-01

Background Phospholipase C (PLC) is one of the major lipid hydrolysing enzymes, implicated in lipid mediated signaling. PLCs have been found to play a significant role in abiotic stress triggered signaling and developmental processes in various plant species. Genome wide identification and expression analysis have been carried out for this gene family in Arabidopsis, yet not much has been accomplished in crop plant rice. Methodology/Principal Findings An exhaustive in-silico exploration of rice genome using various online databases and tools resulted in the identification of nine PLC encoding genes. Based on sequence, motif and phylogenetic analysis rice PLC gene family could be divided into phosphatidylinositol-specific PLCs (PI-PLCs) and phosphatidylcholine- PLCs (PC-PLC or NPC) classes with four and five members, respectively. A comparative analysis revealed that PLCs are conserved in Arabidopsis (dicots) and rice (monocot) at gene structure and protein level but they might have evolved through a separate evolutionary path. Transcript profiling using gene chip microarray and quantitative RT-PCR showed that most of the PLC members expressed significantly and differentially under abiotic stresses (salt, cold and drought) and during various developmental stages with condition/stage specific and overlapping expression. This finding suggested an important role of different rice PLC members in abiotic stress triggered signaling and plant development, which was also supported by the presence of relevant cis-regulatory elements in their promoters. Sub-cellular localization of few selected PLC members in Nicotiana benthamiana and onion epidermal cells has provided a clue about their site of action and functional behaviour. Conclusion/Significance The genome wide identification, structural and expression analysis and knowledge of sub-cellular localization of PLC gene family envisage the functional characterization of these genes in crop plants in near future. PMID:23638098

Comprehensive genomic analysis and expression profiling of phospholipase C gene family during abiotic stresses and development in rice.

PubMed

Singh, Amarjeet; Kanwar, Poonam; Pandey, Amita; Tyagi, Akhilesh K; Sopory, Sudhir K; Kapoor, Sanjay; Pandey, Girdhar K

2013-01-01

Phospholipase C (PLC) is one of the major lipid hydrolysing enzymes, implicated in lipid mediated signaling. PLCs have been found to play a significant role in abiotic stress triggered signaling and developmental processes in various plant species. Genome wide identification and expression analysis have been carried out for this gene family in Arabidopsis, yet not much has been accomplished in crop plant rice. An exhaustive in-silico exploration of rice genome using various online databases and tools resulted in the identification of nine PLC encoding genes. Based on sequence, motif and phylogenetic analysis rice PLC gene family could be divided into phosphatidylinositol-specific PLCs (PI-PLCs) and phosphatidylcholine- PLCs (PC-PLC or NPC) classes with four and five members, respectively. A comparative analysis revealed that PLCs are conserved in Arabidopsis (dicots) and rice (monocot) at gene structure and protein level but they might have evolved through a separate evolutionary path. Transcript profiling using gene chip microarray and quantitative RT-PCR showed that most of the PLC members expressed significantly and differentially under abiotic stresses (salt, cold and drought) and during various developmental stages with condition/stage specific and overlapping expression. This finding suggested an important role of different rice PLC members in abiotic stress triggered signaling and plant development, which was also supported by the presence of relevant cis-regulatory elements in their promoters. Sub-cellular localization of few selected PLC members in Nicotiana benthamiana and onion epidermal cells has provided a clue about their site of action and functional behaviour. The genome wide identification, structural and expression analysis and knowledge of sub-cellular localization of PLC gene family envisage the functional characterization of these genes in crop plants in near future.

Comprehensive evaluation of gene expression signatures in response to electroacupuncture stimulation at Zusanli (ST36) acupoint by transcriptomic analysis.

PubMed

Wu, Jing-Shan; Lo, Hsin-Yi; Li, Chia-Cheng; Chen, Feng-Yuan; Hsiang, Chien-Yun; Ho, Tin-Yun

2017-08-15

Electroacupuncture (EA) has been applied to treat and prevent diseases for years. However, molecular events happened in both the acupunctured site and the internal organs after EA stimulation have not been clarified. Here we applied transcriptomic analysis to explore the gene expression signatures after EA stimulation. Mice were applied EA stimulation at ST36 for 15 min and nine tissues were collected three hours later for microarray analysis. We found that EA affected the expression of genes not only in the acupunctured site but also in the internal organs. EA commonly affected biological networks involved in cytoskeleton and cell adhesion, and also regulated unique process networks in specific organs, such as γ-aminobutyric acid-ergic neurotransmission in brain and inflammation process in lung. In addition, EA affected the expression of genes related to various diseases, such as neurodegenerative diseases in brain and obstructive pulmonary diseases in lung. This report applied, for the first time, a global comprehensive genome-wide approach to analyze the gene expression profiling of acupunctured site and internal organs after EA stimulation. The connection between gene expression signatures, biological processes, and diseases might provide a basis for prediction and explanation on the therapeutic potentials of acupuncture in organs.

Characterization of Soybean WRKY Gene Family and Identification of Soybean WRKY Genes that Promote Resistance to Soybean Cyst Nematode.

PubMed

Yang, Yan; Zhou, Yuan; Chi, Yingjun; Fan, Baofang; Chen, Zhixiang

2017-12-19

WRKY proteins are a superfamily of plant transcription factors with important roles in plants. WRKY proteins have been extensively analyzed in plant species including Arabidopsis and rice. Here we report characterization of soybean WRKY gene family and their functional analysis in resistance to soybean cyst nematode (SCN), the most important soybean pathogen. Through search of the soybean genome, we identified 174 genes encoding WRKY proteins that can be classified into seven groups as established in other plants. WRKY variants including a WRKY-related protein unique to legumes have also been identified. Expression analysis reveals both diverse expression patterns in different soybean tissues and preferential expression of specific WRKY groups in certain tissues. Furthermore, a large number of soybean WRKY genes were responsive to salicylic acid. To identify soybean WRKY genes that promote soybean resistance to SCN, we first screened soybean WRKY genes for enhancing SCN resistance when over-expressed in transgenic soybean hairy roots. To confirm the results, we transformed five WRKY genes into a SCN-susceptible soybean cultivar and generated transgenic soybean lines. Transgenic soybean lines overexpressing three WRKY transgenes displayed increased resistance to SCN. Thus, WRKY genes could be explored to develop new soybean cultivars with enhanced resistance to SCN.

Genome-Wide Evolutionary Characterization and Expression Analyses of WRKY Family Genes in Brachypodium distachyon

PubMed Central

Wen, Feng; Zhu, Hong; Li, Peng; Jiang, Min; Mao, Wenqing; Ong, Chermaine; Chu, Zhaoqing

2014-01-01

Members of plant WRKY gene family are ancient transcription factors that function in plant growth and development and respond to biotic and abiotic stresses. In our present study, we have investigated WRKY family genes in Brachypodium distachyon, a new model plant of family Poaceae. We identified a total of 86 WRKY genes from B. distachyon and explored their chromosomal distribution and evolution, domain alignment, promoter cis-elements, and expression profiles. Combining the analysis of phylogenetic tree of BdWRKY genes and the result of expression profiling, results showed that most of clustered gene pairs had higher similarities in the WRKY domain, suggesting that they might be functionally redundant. Neighbour-joining analysis of 301 WRKY domains from Oryza sativa, Arabidopsis thaliana, and B. distachyon suggested that BdWRKY domains are evolutionarily more closely related to O. sativa WRKY domains than those of A. thaliana. Moreover, tissue-specific expression profile of BdWRKY genes and their responses to phytohormones and several biotic or abiotic stresses were analysed by quantitative real-time PCR. The results showed that the expression of BdWRKY genes was rapidly regulated by stresses and phytohormones, and there was a strong correlation between promoter cis-elements and the phytohormones-induced BdWRKY gene expression. PMID:24453041

Exploring Regulatory Mechanisms of Atrial Myocyte Hypertrophy of Mitral Regurgitation through Gene Expression Profiling Analysis: Role of NFAT in Cardiac Hypertrophy

PubMed Central

Chang, Tzu-Hao; Chen, Mien-Cheng; Chang, Jen-Ping; Huang, Hsien-Da; Ho, Wan-Chun; Lin, Yu-Sheng; Pan, Kuo-Li; Huang, Yao-Kuang; Liu, Wen-Hao; Wu, Chia-Chen

2016-01-01

Background Left atrial enlargement in mitral regurgitation (MR) predicts a poor prognosis. The regulatory mechanisms of atrial myocyte hypertrophy of MR patients remain unknown. Methods and Results This study comprised 14 patients with MR, 7 patients with aortic valve disease (AVD), and 6 purchased samples from normal subjects (NC). We used microarrays, enrichment analysis and quantitative RT-PCR to study the gene expression profiles in the left atria. Microarray results showed that 112 genes were differentially up-regulated and 132 genes were differentially down-regulated in the left atria between MR patients and NC. Enrichment analysis of differentially expressed genes demonstrated that “NFAT in cardiac hypertrophy” pathway was not only one of the significant associated canonical pathways, but also the only one predicted with a non-zero score of 1.34 (i.e. activated) through Ingenuity Pathway Analysis molecule activity predictor. Ingenuity Pathway Analysis Global Molecular Network analysis exhibited that the highest score network also showed high association with cardiac related pathways and functions. Therefore, 5 NFAT associated genes (PPP3R1, PPP3CB, CAMK1, MEF2C, PLCE1) were studies for validation. The mRNA expressions of PPP3CB and MEF2C were significantly up-regulated, and CAMK1 and PPP3R1 were significantly down-regulated in MR patients compared to NC. Moreover, MR patients had significantly increased mRNA levels of PPP3CB, MEF2C and PLCE1 compared to AVD patients. The atrial myocyte size of MR patients significantly exceeded that of the AVD patients and NC. Conclusions Differentially expressed genes in the “NFAT in cardiac hypertrophy” pathway may play a critical role in the atrial myocyte hypertrophy of MR patients. PMID:27907007

Hierarchy in gene expression is predictive of risk, progression, and outcome in adult acute myeloid leukemia

NASA Astrophysics Data System (ADS)

Tripathi, Shubham; Deem, Michael W.

2015-02-01

Cancer progresses with a change in the structure of the gene network in normal cells. We define a measure of organizational hierarchy in gene networks of affected cells in adult acute myeloid leukemia (AML) patients. With a retrospective cohort analysis based on the gene expression profiles of 116 AML patients, we find that the likelihood of future cancer relapse and the level of clinical risk are directly correlated with the level of organization in the cancer related gene network. We also explore the variation of the level of organization in the gene network with cancer progression. We find that this variation is non-monotonic, which implies the fitness landscape in the evolution of AML cancer cells is non-trivial. We further find that the hierarchy in gene expression at the time of diagnosis may be a useful biomarker in AML prognosis.

Exploration of the Esophageal Mucosal Barrier in Non-Erosive Reflux Disease

PubMed Central

Rinsma, Nicolaas F.; Farré, Ricard; Troost, Fred J.; Elizalde, Montserrat; Keszthelyi, Daniel; Helyes, Zsuzsanna; Masclee, Ad A.; Conchillo, José M.

2017-01-01

In the absence of visible mucosal damage, it is hypothesized that the esophageal mucosal barrier is functionally impaired in patients with non-erosive reflux disease (NERD). The aim of the present study was to perform an exploratory analysis of the mucosal barrier in NERD compared to erosive esophagitis (EE) and controls. A second aim was to explore TRPV1 gene transcription in relation to the mucosal barrier function and heartburn symptoms. In this prospective study, 10 NERD patients, 11 patients with active erosive esophagitis and 10 healthy volunteers were included. Biopsies from non-eroded mucosa were obtained for (1) ex vivo analyses (Ussing chamber) of transepithelial electrical resistance (TEER) and permeability (2) gene transcription of tight-junction proteins and transient receptor potential vanilloid subfamily member 1 (TRPV1). No differences in TEER or permeability were found between NERD and healthy volunteers, whereas TEER was lower in patients with erosive esophagitis. TRPV1 gene transcription was not significantly different between EE, NERD and controls. Conclusions: esophageal mucosal barrier function and TRPV1 transcription is not significantly altered in NERD patients. Future research is needed to explore other potential mechanisms that may account for the high symptom burden in these patients. PMID:28534850

Short and long-term genome stability analysis of prokaryotic genomes.

PubMed

Brilli, Matteo; Liò, Pietro; Lacroix, Vincent; Sagot, Marie-France

2013-05-08

Gene organization dynamics is actively studied because it provides useful evolutionary information, makes functional annotation easier and often enables to characterize pathogens. There is therefore a strong interest in understanding the variability of this trait and the possible correlations with life-style. Two kinds of events affect genome organization: on one hand translocations and recombinations change the relative position of genes shared by two genomes (i.e. the backbone gene order); on the other, insertions and deletions leave the backbone gene order unchanged but they alter the gene neighborhoods by breaking the syntenic regions. A complete picture about genome organization evolution therefore requires to account for both kinds of events. We developed an approach where we model chromosomes as graphs on which we compute different stability estimators; we consider genome rearrangements as well as the effect of gene insertions and deletions. In a first part of the paper, we fit a measure of backbone gene order conservation (hereinafter called backbone stability) against phylogenetic distance for over 3000 genome comparisons, improving existing models for the divergence in time of backbone stability. Intra- and inter-specific comparisons were treated separately to focus on different time-scales. The use of multiple genomes of a same species allowed to identify genomes with diverging gene order with respect to their conspecific. The inter-species analysis indicates that pathogens are more often unstable with respect to non-pathogens. In a second part of the text, we show that in pathogens, gene content dynamics (insertions and deletions) have a much more dramatic effect on genome organization stability than backbone rearrangements. In this work, we studied genome organization divergence taking into account the contribution of both genome order rearrangements and genome content dynamics. By studying species with multiple sequenced genomes available, we were able to explore genome organization stability at different time-scales and to find significant differences for pathogen and non-pathogen species. The output of our framework also allows to identify the conserved gene clusters and/or partial occurrences thereof, making possible to explore how gene clusters assembled during evolution.

Novel candidate genes of the PARK7 interactome as mediators of apoptosis and acetylation in multiple sclerosis: An in silico analysis.

PubMed

Vavougios, George D; Zarogiannis, Sotirios G; Krogfelt, Karen Angeliki; Gourgoulianis, Konstantinos; Mitsikostas, Dimos Dimitrios; Hadjigeorgiou, Georgios

2018-01-01

currently only 4 studies have explored the potential role of PARK7's dysregulation in MS pathophysiology Currently, no study has evaluated the potential role of the PARK7 interactome in MS. The aim of our study was to assess the differential expression of PARK7 mRNA in peripheral blood mononuclears (PBMCs) donated from MS versus healthy patients using data mining techniques. The PARK7 interactome data from the GDS3920 profile were scrutinized for differentially expressed genes (DEGs); Gene Enrichment Analysis (GEA) was used to detect significantly enriched biological functions. 27 differentially expressed genes in the MS dataset were detected; 12 of these (NDUFA4, UBA2, TDP2, NPM1, NDUFS3, SUMO1, PIAS2, KIAA0101, RBBP4, NONO, RBBP7 AND HSPA4) are reported for the first time in MS. Stepwise Linear Discriminant Function Analysis constructed a predictive model (Wilk's λ = 0.176, χ 2 = 45.204, p = 1.5275e -10 ) with 2 variables (TIDP2, RBBP4) that achieved 96.6% accuracy when discriminating between patients and controls. Gene Enrichment Analysis revealed that induction and regulation of programmed / intrinsic cell death represented the most salient Gene Ontology annotations. Cross-validation on systemic lupus erythematosus and ischemic stroke datasets revealed that these functions are unique to the MS dataset. Based on our results, novel potential target genes are revealed; these differentially expressed genes regulate epigenetic and apoptotic pathways that may further elucidate underlying mechanisms of autorreactivity in MS. Copyright © 2017 Elsevier B.V. All rights reserved.

Data science approaches to pharmacogenetics.

PubMed

Penrod, N M; Moore, J H

2014-01-01

Pharmacogenetic studies rely on applied statistics to evaluate genetic data describing natural variation in response to pharmacotherapeutics such as drugs and vaccines. In the beginning, these studies were based on candidate gene approaches that specifically focused on efficacy or adverse events correlated with variants of single genes. This hypothesis driven method required the researcher to have a priori knowledge of which genes or gene sets to investigate. According to rational design, the focus of these studies has been on drug metabolizing enzymes, drug transporters, and drug targets. As technology has progressed, these studies have transitioned to hypothesis-free explorations where markers across the entire genome can be measured in large scale, population based, genome-wide association studies (GWAS). This enables identification of novel genetic biomarkers, therapeutic targets, and analysis of gene-gene interactions, which may reveal molecular mechanisms of drug activities. Ultimately, the challenge is to utilize gene-drug associations to create dosing algorithms based individual genotypes, which will guide physicians and ensure they prescribe the correct dose of the correct drug the first time eliminating trial-and-error and adverse events. We review here basic concepts and applications of data science to the genetic analysis of pharmacologic outcomes.

Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma

PubMed Central

Kaushik, Abhinav; Bhatia, Yashuma; Ali, Shakir; Gupta, Dinesh

2015-01-01

Metastatic melanoma patients have a poor prognosis, mainly attributable to the underlying heterogeneity in melanoma driver genes and altered gene expression profiles. These characteristics of melanoma also make the development of drugs and identification of novel drug targets for metastatic melanoma a daunting task. Systems biology offers an alternative approach to re-explore the genes or gene sets that display dysregulated behaviour without being differentially expressed. In this study, we have performed systems biology studies to enhance our knowledge about the conserved property of disease genes or gene sets among mutually exclusive datasets representing melanoma progression. We meta-analysed 642 microarray samples to generate melanoma reconstructed networks representing four different stages of melanoma progression to extract genes with altered molecular circuitry wiring as compared to a normal cellular state. Intriguingly, a majority of the melanoma network-rewired genes are not differentially expressed and the disease genes involved in melanoma progression consistently modulate its activity by rewiring network connections. We found that the shortlisted disease genes in the study show strong and abnormal network connectivity, which enhances with the disease progression. Moreover, the deviated network properties of the disease gene sets allow ranking/prioritization of different enriched, dysregulated and conserved pathway terms in metastatic melanoma, in agreement with previous findings. Our analysis also reveals presence of distinct network hubs in different stages of metastasizing tumor for the same set of pathways in the statistically conserved gene sets. The study results are also presented as a freely available database at http://bioinfo.icgeb.res.in/m3db/. The web-based database resource consists of results from the analysis presented here, integrated with cytoscape web and user-friendly tools for visualization, retrieval and further analysis. PMID:26558755

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features

PubMed Central

2011-01-01

Background Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Methods Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Results Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. Conclusion This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer. PMID:22044755

Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages.

PubMed

Taminau, Jonatan; Meganck, Stijn; Lazar, Cosmin; Steenhoff, David; Coletta, Alain; Molter, Colin; Duque, Robin; de Schaetzen, Virginie; Weiss Solís, David Y; Bersini, Hugues; Nowé, Ann

2012-12-24

With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].

Identification of a Fungal 1,8-Cineole Synthase from Hypoxylon sp. with Specificity Determinants in Common with the Plant Synthases*

PubMed Central

Shaw, Jeffrey J.; Berbasova, Tetyana; Sasaki, Tomoaki; Jefferson-George, Kyra; Spakowicz, Daniel J.; Dunican, Brian F.; Portero, Carolina E.; Narváez-Trujillo, Alexandra; Strobel, Scott A.

2015-01-01

Terpenes are an important and diverse class of secondary metabolites widely produced by fungi. Volatile compound screening of a fungal endophyte collection revealed a number of isolates in the family Xylariaceae, producing a series of terpene molecules, including 1,8-cineole. This compound is a commercially important component of eucalyptus oil used in pharmaceutical applications and has been explored as a potential biofuel additive. The genes that produce terpene molecules, such as 1,8-cineole, have been little explored in fungi, providing an opportunity to explore the biosynthetic origin of these compounds. Through genome sequencing of cineole-producing isolate E7406B, we were able to identify 11 new terpene synthase genes. Expressing a subset of these genes in Escherichia coli allowed identification of the hyp3 gene, responsible for 1,8-cineole biosynthesis, the first monoterpene synthase discovered in fungi. In a striking example of convergent evolution, mutational analysis of this terpene synthase revealed an active site asparagine critical for water capture and specificity during cineole synthesis, the same mechanism used in an unrelated plant homologue. These studies have provided insight into the evolutionary relationship of fungal terpene synthases to those in plants and bacteria and further established fungi as a relatively untapped source of this important and diverse class of compounds. PMID:25648891

Genome-wide identification and expression analysis of the apple ASR gene family in response to Alternaria alternata f. sp. mali.

PubMed

Huang, Kaihui; Zhong, Yan; Li, Yingjun; Zheng, Dan; Cheng, Zong-Ming

2016-10-01

The ABA/water stress/ripening-induced (ASR) gene family exists universally in higher plants, and many ASR genes are up-regulated during periods of environmental stress and fruit ripening. Although a considerable amount of research has been performed investigating ASR gene response to abiotic stresses, relatively little is known about their roles in response to biotic stresses. In this report, we identified five ASR genes in apple (Malus × domestica) and explored their phylogenetic relationship, duplication events, and selective pressure. Five apple ASR genes (Md-ASR) were divided into two clades based on phylogenetic analysis. Species-specific duplication was detected in M. domestica ASR genes. Leaves of 'Golden delicious' and 'Starking' were infected with Alternaria alternata f. sp. mali, which causes apple blotch disease, and examined for the expression of the ASR genes in lesion areas during the first 72 h after inoculation. Md-ASR genes showed different expression patterns at different sampling times in 'Golden delicious' and 'Starking'. The activities of stress-related enzymes, peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), phenylalanine ammonia lyase (PAL), and polyphenoloxidase (PPO), and the content of malondialdehyde (MDA) were also measured in different stages of disease development in two cultivars. The ASR gene expression patterns and theses physiological indexes for disease resistance suggested that Md-ASR genes are involved in biotic stress responses in apple.

Massive sequencing of 70 genes reveals a myriad of missing genes or mechanisms to be uncovered in hereditary spastic paraplegias

PubMed Central

Morais, Sara; Raymond, Laure; Mairey, Mathilde; Coutinho, Paula; Brandão, Eva; Ribeiro, Paula; Loureiro, José Leal; Sequeiros, Jorge; Brice, Alexis; Alonso, Isabel; Stevanin, Giovanni

2017-01-01

Hereditary spastic paraplegias (HSP) are neurodegenerative disorders characterized by lower limb spasticity and weakness that can be complicated by other neurological or non-neurological signs. Despite a high genetic heterogeneity (>60 causative genes), 40–70% of the families remain without a molecular diagnosis. Analysis of one of the pioneer cohorts of 193 HSP families generated in the early 1990s in Portugal highlighted that SPAST and SPG11 are the most frequent diagnoses. We have now explored 98 unsolved families from this series using custom next generation sequencing panels analyzing up to 70 candidate HSP genes. We identified the likely disease-causing variant in 20 of the 98 families with KIF5A being the most frequently mutated gene. We also found 52 variants of unknown significance (VUS) in 38% of the cases. These new diagnoses resulted in 42% of solved cases in the full Portuguese cohort (81/193). Segregation of the variants was not always compatible with the presumed inheritance, indicating that the analysis of all HSP genes regardless of the inheritance mode can help to explain some cases. Our results show that there is still a large set of unknown genes responsible for HSP and most likely novel mechanisms or inheritance modes leading to the disease to be uncovered, but this will require international collaborative efforts, particularly for the analysis of VUS. PMID:28832565

Global analysis of human duplicated genes reveals the relative importance of whole-genome duplicates originated in the early vertebrate evolution.

PubMed

Acharya, Debarun; Ghosh, Tapash C

2016-01-22

Gene duplication is a genetic mutation that creates functionally redundant gene copies that are initially relieved from selective pressures and may adapt themselves to new functions with time. The levels of gene duplication may vary from small-scale duplication (SSD) to whole genome duplication (WGD). Studies with yeast revealed ample differences between these duplicates: Yeast WGD pairs were functionally more similar, less divergent in subcellular localization and contained a lesser proportion of essential genes. In this study, we explored the differences in evolutionary genomic properties of human SSD and WGD genes, with the identifiable human duplicates coming from the two rounds of whole genome duplication occurred early in vertebrate evolution. We observed that these two groups of duplicates were also dissimilar in terms of their evolutionary and genomic properties. But interestingly, this is not like the same observed in yeast. The human WGDs were found to be functionally less similar, diverge more in subcellular level and contain a higher proportion of essential genes than the SSDs, all of which are opposite from yeast. Additionally, we explored that human WGDs were more divergent in their gene expression profile, have higher multifunctionality and are more often associated with disease, and are evolutionarily more conserved than human SSDs. Our study suggests that human WGD duplicates are more divergent and entails the adaptation of WGDs to novel and important functions that consequently lead to their evolutionary conservation in the course of evolution.

RNA-Seq analysis of salinity stress-responsive transcriptome in the liver of spotted sea bass (Lateolabrax maculatus).

PubMed

Zhang, Xiaoyan; Wen, Haishen; Wang, Hailiang; Ren, Yuanyuan; Zhao, Ji; Li, Yun

2017-01-01

Salinity is one of the most prominent abiotic factors, which greatly influence reproduction, development, growth, physiological and metabolic activities of fishes. Spotted sea bass (Lateolabrax maculatus), as a euryhaline marine teleost, has extraordinary ability to deal with a wide range of salinity changes. However, this species is devoid of genomic resources, and no study has been conducted at the transcriptomic level to determine genes responsible for salinity regulation, which impedes the understanding of the fundamental mechanism conferring tolerance to salinity fluctuations. Liver, as the major metabolic organ, is the key source supplying energy for iono- and osmoregulation in fish, however, little attention has been paid to its salinity-related functions but which should not be ignored. In this study, we perform RNA-Seq analysis to identify genes involved in salinity adaptation and osmoregulation in liver of spotted sea bass, generating from the fishes exposed to low and high salinity water (5 vs 30ppt). After de novo assembly, annotation and differential gene expression analysis, a total of 455 genes were differentially expressed, including 184 up-regulated and 271 down-regulated transcripts in low salinity-acclimated fish group compared with that in high salinity-acclimated group. A number of genes with a potential role in salinity adaptation for spotted sea bass were classified into five functional categories based on the gene ontology (GO) and enrichment analysis, which include genes involved in metabolites and ion transporters, energy metabolism, signal transduction, immune response and structure reorganization. The candidate genes identified in L. maculates liver provide valuable information to explore new pathways related to fish salinity and osmotic regulation. Besides, the transcriptomic sequencing data supplies significant resources for identification of novel genes and further studying biological questions in spotted sea bass.

RNA-Seq analysis of salinity stress–responsive transcriptome in the liver of spotted sea bass (Lateolabrax maculatus)

PubMed Central

Zhang, Xiaoyan; Wen, Haishen; Wang, Hailiang; Ren, Yuanyuan; Zhao, Ji; Li, Yun

2017-01-01

Salinity is one of the most prominent abiotic factors, which greatly influence reproduction, development, growth, physiological and metabolic activities of fishes. Spotted sea bass (Lateolabrax maculatus), as a euryhaline marine teleost, has extraordinary ability to deal with a wide range of salinity changes. However, this species is devoid of genomic resources, and no study has been conducted at the transcriptomic level to determine genes responsible for salinity regulation, which impedes the understanding of the fundamental mechanism conferring tolerance to salinity fluctuations. Liver, as the major metabolic organ, is the key source supplying energy for iono- and osmoregulation in fish, however, little attention has been paid to its salinity-related functions but which should not be ignored. In this study, we perform RNA-Seq analysis to identify genes involved in salinity adaptation and osmoregulation in liver of spotted sea bass, generating from the fishes exposed to low and high salinity water (5 vs 30ppt). After de novo assembly, annotation and differential gene expression analysis, a total of 455 genes were differentially expressed, including 184 up-regulated and 271 down-regulated transcripts in low salinity-acclimated fish group compared with that in high salinity-acclimated group. A number of genes with a potential role in salinity adaptation for spotted sea bass were classified into five functional categories based on the gene ontology (GO) and enrichment analysis, which include genes involved in metabolites and ion transporters, energy metabolism, signal transduction, immune response and structure reorganization. The candidate genes identified in L. maculates liver provide valuable information to explore new pathways related to fish salinity and osmotic regulation. Besides, the transcriptomic sequencing data supplies significant resources for identification of novel genes and further studying biological questions in spotted sea bass. PMID:28253338

DNA methylome signature in rheumatoid arthritis.

PubMed

Nakano, Kazuhisa; Whitaker, John W; Boyle, David L; Wang, Wei; Firestein, Gary S

2013-01-01

Epigenetics can influence disease susceptibility and severity. While DNA methylation of individual genes has been explored in autoimmunity, no unbiased systematic analyses have been reported. Therefore, a genome-wide evaluation of DNA methylation loci in fibroblast-like synoviocytes (FLS) isolated from the site of disease in rheumatoid arthritis (RA) was performed. Genomic DNA was isolated from six RA and five osteoarthritis (OA) FLS lines and evaluated using the Illumina HumanMethylation450 chip. Cluster analysis of data was performed and corrected using Benjamini-Hochberg adjustment for multiple comparisons. Methylation was confirmed by pyrosequencing and gene expression was determined by qPCR. Pathway analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. RA and control FLS segregated based on DNA methylation, with 1859 differentially methylated loci. Hypomethylated loci were identified in key genes relevant to RA, such as CHI3L1, CASP1, STAT3, MAP3K5, MEFV and WISP3. Hypermethylation was also observed, including TGFBR2 and FOXO1. Hypomethylation of individual genes was associated with increased gene expression. Grouped analysis identified 207 hypermethylated or hypomethylated genes with multiple differentially methylated loci, including COL1A1, MEFV and TNF. Hypomethylation was increased in multiple pathways related to cell migration, including focal adhesion, cell adhesion, transendothelial migration and extracellular matrix interactions. Confirmatory studies with OA and normal FLS also demonstrated segregation of RA from control FLS based on methylation pattern. Differentially methylated genes could alter FLS gene expression and contribute to the pathogenesis of RA. DNA methylation of critical genes suggests that RA FLS are imprinted and implicate epigenetic contributions to inflammatory arthritis.

Partitioning of functional gene expression data using principal points.

PubMed

Kim, Jaehee; Kim, Haseong

2017-10-12

DNA microarrays offer motivation and hope for the simultaneous study of variations in multiple genes. Gene expression is a temporal process that allows variations in expression levels with a characterized gene function over a period of time. Temporal gene expression curves can be treated as functional data since they are considered as independent realizations of a stochastic process. This process requires appropriate models to identify patterns of gene functions. The partitioning of the functional data can find homogeneous subgroups of entities for the massive genes within the inherent biological networks. Therefor it can be a useful technique for the analysis of time-course gene expression data. We propose a new self-consistent partitioning method of functional coefficients for individual expression profiles based on the orthonormal basis system. A principal points based functional partitioning method is proposed for time-course gene expression data. The method explores the relationship between genes using Legendre coefficients as principal points to extract the features of gene functions. Our proposed method provides high connectivity in connectedness after clustering for simulated data and finds a significant subsets of genes with the increased connectivity. Our approach has comparative advantages that fewer coefficients are used from the functional data and self-consistency of principal points for partitioning. As real data applications, we are able to find partitioned genes through the gene expressions found in budding yeast data and Escherichia coli data. The proposed method benefitted from the use of principal points, dimension reduction, and choice of orthogonal basis system as well as provides appropriately connected genes in the resulting subsets. We illustrate our method by applying with each set of cell-cycle-regulated time-course yeast genes and E. coli genes. The proposed method is able to identify highly connected genes and to explore the complex dynamics of biological systems in functional genomics.

[Differentially expressed genes of cell signal transduction associated with benzene poisoning by cDNA microarray].

PubMed

Wang, Hong; Bi, Yongyi; Tao, Ning; Wang, Chunhong

2005-08-01

To detect the differential expression of cell signal transduction genes associated with benzene poisoning, and to explore the pathogenic mechanisms of blood system damage induced by benzene. Peripheral white blood cell gene expression profile of 7 benzene poisoning patients, including one aplastic anemia, was determined by cDNA microarray. Seven chips from normal workers were served as controls. Cluster analysis of gene expression profile was performed. Among the 4265 target genes, 176 genes associated with cell signal transduction were differentially expressed. 35 up-regulated genes including PTPRC, STAT4, IFITM1 etc were found in at least 6 pieces of microarray; 45 down-regulated genes including ARHB, PPP3CB, CDC37 etc were found in at least 5 pieces of microarray. cDNA microarray technology is an effective technique for screening the differentially expressed genes of cell signal transduction. Disorder in cell signal transduction may play certain role in the pathogenic mechanism of benzene poisoning.

Genome-wide identification and expression analysis of glutathione S-transferase gene family in tomato: Gaining an insight to their physiological and stress-specific roles

PubMed Central

Islam, Shiful; Rahman, Iffat Ara; Islam, Tahmina

2017-01-01

Glutathione S-transferase (GST) refers to one of the major detoxifying enzymes that plays an important role in different abiotic and biotic stress modulation pathways of plant. The present study aimed to a comprehensive genome-wide functional characterization of GST genes and proteins in tomato (Solanum lycopersicum L.). The whole genome sequence analysis revealed the presence of 90 GST genes in tomato, the largest GST gene family reported till date. Eight segmental duplicated gene pairs might contribute significantly to the expansion of SlGST gene family. Based on phylogenetic analysis of tomato, rice, and Arabidopsis GST proteins, GST family members could be further divided into ten classes. Members of each orthologous class showed high conservancy among themselves. Tau and lambda are the major classes of tomato; while tau and phi are the major classes for rice and Arabidopsis. Chromosomal localization revealed highly uneven distribution of SlGST genes in 13 different chromosomes, where chromosome 9 possessed the highest number of genes. Based on publicly available microarray data, expression analysis of 30 available SlGST genes exhibited a differential pattern in all the analyzed tissues and developmental stages. Moreover, most of the members showed highly induced expression in response to multiple biotic and abiotic stress inducers that could be harmonized with the increase in total GST enzyme activity under several stress conditions. Activity of tomato GST could be enhanced further by using some positive modulators (safeners) that have been predicted through molecular docking of SlGSTU5 and ligands. Moreover, tomato GST proteins are predicted to interact with a lot of other glutathione synthesizing and utilizing enzymes such as glutathione peroxidase, glutathione reductase, glutathione synthetase and γ-glutamyltransferase. This comprehensive genome-wide analysis and expression profiling would provide a rational platform and possibility to explore the versatile role of GST genes in crop engineering. PMID:29095889

Transcriptomic insights into citrus segment membrane's cell wall components relating to fruit sensory texture.

PubMed

Wang, Xun; Lin, Lijin; Tang, Yi; Xia, Hui; Zhang, Xiancong; Yue, Maolan; Qiu, Xia; Xu, Ke; Wang, Zhihui

2018-04-23

During fresh fruit consumption, sensory texture is one factor that affects the organoleptic qualities. Chemical components of plant cell walls, including pectin, cellulose, hemicellulose and lignin, play central roles in determining the textural qualities. To explore the genes and regulatory pathways involved in fresh citrus' perceived sensory texture, we performed mRNA-seq analyses of the segment membranes of two citrus cultivars, Shiranui and Kiyomi, with different organoleptic textures. Segment membranes were sampled at two developmental stages of citrus fruit, the beginning and end of the expansion period. More than 3000 differentially expressed genes were identified. The gene ontology analysis revealed that more categories were significantly enriched in 'Shiranui' than in 'Kiyomi' at both developmental stages. In total, 108 significantly enriched pathways were obtained, with most belonging to metabolism. A detailed transcriptomic analysis revealed potential critical genes involved in the metabolism of cell wall structures, for example, GAUT4 in pectin synthesis, CESA1, 3 and 6, and SUS4 in cellulose synthesis, CSLC5, XXT1 and XXT2 in hemicellulose synthesis, and CSE in lignin synthesis. Low levels, or no expression, of genes involved in cellulose and hemicellulose, such as CESA4, CESA7, CESA8, IRX9 and IRX14, confirmed that secondary cell walls were negligible or absent in citrus segment membranes. A chemical component analysis of the segment membranes from mature fruit revealed that the pectin, cellulose and lignin contents, and the segment membrane's weight (% of segment) were greater in 'Kiyomi'. Organoleptic quality of citrus is easily overlooked. It is mainly determined by sensory texture perceived in citrus segment membrane properties. We performed mRNA-seq analyses of citrus segment membranes to explore the genes and regulatory pathways involved in fresh citrus' perceived sensory texture. Transcriptomic data showed high repeatability between two independent biological replicates. The expression levels of genes involved in cell wall structure metabolism, including pectin, cellulose, hemicellulose and lignin, were investigated. Meanwhile, chemical component contents of the segment membranes from mature fruit were analyzed. This study provided detailed transcriptional regulatory profiles of different organoleptic citrus qualities and integrated insights into the mechanisms affecting citrus' sensory texture.

Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci

USDA-ARS?s Scientific Manuscript database

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholest...

A comprehensive and quantitative exploration of thousands of viral genomes

PubMed Central

Mahmoudabadi, Gita

2018-01-01

The complete assembly of viral genomes from metagenomic datasets (short genomic sequences gathered from environmental samples) has proven to be challenging, so there are significant blind spots when we view viral genomes through the lens of metagenomics. One approach to overcoming this problem is to leverage the thousands of complete viral genomes that are publicly available. Here we describe our efforts to assemble a comprehensive resource that provides a quantitative snapshot of viral genomic trends – such as gene density, noncoding percentage, and abundances of functional gene categories – across thousands of viral genomes. We have also developed a coarse-grained method for visualizing viral genome organization for hundreds of genomes at once, and have explored the extent of the overlap between bacterial and bacteriophage gene pools. Existing viral classification systems were developed prior to the sequencing era, so we present our analysis in a way that allows us to assess the utility of the different classification systems for capturing genomic trends. PMID:29624169

A comprehensive and quantitative exploration of thousands of viral genomes.

PubMed

Mahmoudabadi, Gita; Phillips, Rob

2018-04-19

The complete assembly of viral genomes from metagenomic datasets (short genomic sequences gathered from environmental samples) has proven to be challenging, so there are significant blind spots when we view viral genomes through the lens of metagenomics. One approach to overcoming this problem is to leverage the thousands of complete viral genomes that are publicly available. Here we describe our efforts to assemble a comprehensive resource that provides a quantitative snapshot of viral genomic trends - such as gene density, noncoding percentage, and abundances of functional gene categories - across thousands of viral genomes. We have also developed a coarse-grained method for visualizing viral genome organization for hundreds of genomes at once, and have explored the extent of the overlap between bacterial and bacteriophage gene pools. Existing viral classification systems were developed prior to the sequencing era, so we present our analysis in a way that allows us to assess the utility of the different classification systems for capturing genomic trends. © 2018, Mahmoudabadi et al.

Characterization of a Crabs Claw Gene in basal eudicot species Epimedium sagittatum (Berberidaceae).

PubMed

Sun, Wei; Huang, Wenjun; Li, Zhineng; Lv, Haiyan; Huang, Hongwen; Wang, Ying

2013-01-08

The Crabs Claw (CRC) YABBY gene is required for regulating carpel development in angiosperms and has played an important role in nectary evolution during core eudicot speciation. The function or expression of CRC-like genes has been explored in two basal eudicots, Eschscholzia californica and Aquilegia formosa. To further investigate the function of CRC orthologous genes related to evolution of carpel and nectary development in basal eudicots, a CRC ortholog, EsCRC, was isolated and characterized from Epimedium sagittatum (Sieb. and Zucc.) Maxim. A phylogenetic analysis of EsCRC and previously identified CRC-like genes placed EsCRC within the basal eudicot lineage. Gene expression results suggest that EsCRC is involved in the development of sepals and carpels, but not nectaries. Phenotypic complementation of the Arabidopsis mutant crc-1 was achieved by constitutive expression of EsCRC. In addition, over-expression of EsCRC in Arabidopsis and tobacco gave rise to abaxially curled leaves. Transgenic results together with the gene expression analysis suggest that EsCRC may maintain a conserved function in carpel development and also play a novel role related to sepal formation. Absence of EsCRC and ElCRC expression in nectaries further indicates that nectary development in non-core eudicots is unrelated to expression of CRC-like genes.

Characterization of a Crabs Claw Gene in Basal Eudicot Species Epimedium sagittatum (Berberidaceae)

PubMed Central

Sun, Wei; Huang, Wenjun; Li, Zhineng; Lv, Haiyan; Huang, Hongwen; Wang, Ying

2013-01-01

The Crabs Claw (CRC) YABBY gene is required for regulating carpel development in angiosperms and has played an important role in nectary evolution during core eudicot speciation. The function or expression of CRC-like genes has been explored in two basal eudicots, Eschscholzia californica and Aquilegia formosa. To further investigate the function of CRC orthologous genes related to evolution of carpel and nectary development in basal eudicots, a CRC ortholog, EsCRC, was isolated and characterized from Epimedium sagittatum (Sieb. and Zucc.) Maxim. A phylogenetic analysis of EsCRC and previously identified CRC-like genes placed EsCRC within the basal eudicot lineage. Gene expression results suggest that EsCRC is involved in the development of sepals and carpels, but not nectaries. Phenotypic complementation of the Arabidopsis mutant crc-1 was achieved by constitutive expression of EsCRC. In addition, over-expression of EsCRC in Arabidopsis and tobacco gave rise to abaxially curled leaves. Transgenic results together with the gene expression analysis suggest that EsCRC may maintain a conserved function in carpel development and also play a novel role related to sepal formation. Absence of EsCRC and ElCRC expression in nectaries further indicates that nectary development in non-core eudicots is unrelated to expression of CRC-like genes. PMID:23299438

Down-Regulation of Gene Expression by RNA-Induced Gene Silencing

NASA Astrophysics Data System (ADS)

Travella, Silvia; Keller, Beat

Down-regulation of endogenous genes via post-transcriptional gene silencing (PTGS) is a key to the characterization of gene function in plants. Many RNA-based silencing mechanisms such as post-transcriptional gene silencing, co-suppression, quelling, and RNA interference (RNAi) have been discovered among species of different kingdoms (plants, fungi, and animals). One of the most interesting discoveries was RNAi, a sequence-specific gene-silencing mechanism initiated by the introduction of double-stranded RNA (dsRNA), homologous in sequence to the silenced gene, which triggers degradation of mRNA. Infection of plants with modified viruses can also induce RNA silencing and is referred to as virus-induced gene silencing (VIGS). In contrast to insertional mutagenesis, these emerging new reverse genetic approaches represent a powerful tool for exploring gene function and for manipulating gene expression experimentally in cereal species such as barley and wheat. We examined how RNAi and VIGS have been used to assess gene function in barley and wheat, including molecular mechanisms involved in the process and available methodological elements, such as vectors, inoculation procedures, and analysis of silenced phenotypes.

Evolutionary Approach for Relative Gene Expression Algorithms

PubMed Central

Czajkowski, Marcin

2014-01-01

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

Comparing Mycobacterium tuberculosis genomes using genome topology networks.

PubMed

Jiang, Jianping; Gu, Jianlei; Zhang, Liang; Zhang, Chenyi; Deng, Xiao; Dou, Tonghai; Zhao, Guoping; Zhou, Yan

2015-02-14

Over the last decade, emerging research methods, such as comparative genomic analysis and phylogenetic study, have yielded new insights into genotypes and phenotypes of closely related bacterial strains. Several findings have revealed that genomic structural variations (SVs), including gene gain/loss, gene duplication and genome rearrangement, can lead to different phenotypes among strains, and an investigation of genes affected by SVs may extend our knowledge of the relationships between SVs and phenotypes in microbes, especially in pathogenic bacteria. In this work, we introduce a 'Genome Topology Network' (GTN) method based on gene homology and gene locations to analyze genomic SVs and perform phylogenetic analysis. Furthermore, the concept of 'unfixed ortholog' has been proposed, whose members are affected by SVs in genome topology among close species. To improve the precision of 'unfixed ortholog' recognition, a strategy to detect annotation differences and complete gene annotation was applied. To assess the GTN method, a set of thirteen complete M. tuberculosis genomes was analyzed as a case study. GTNs with two different gene homology-assigning methods were built, the Clusters of Orthologous Groups (COG) method and the orthoMCL clustering method, and two phylogenetic trees were constructed accordingly, which may provide additional insights into whole genome-based phylogenetic analysis. We obtained 24 unfixable COG groups, of which most members were related to immunogenicity and drug resistance, such as PPE-repeat proteins (COG5651) and transcriptional regulator TetR gene family members (COG1309). The GTN method has been implemented in PERL and released on our website. The tool can be downloaded from http://homepage.fudan.edu.cn/zhouyan/gtn/ , and allows re-annotating the 'lost' genes among closely related genomes, analyzing genes affected by SVs, and performing phylogenetic analysis. With this tool, many immunogenic-related and drug resistance-related genes were found to be affected by SVs in M. tuberculosis genomes. We believe that the GTN method will be suitable for the exploration of genomic SVs in connection with biological features of bacterial strains, and that GTN-based phylogenetic analysis will provide additional insights into whole genome-based phylogenetic analysis.

Evolution and structural diversification of Nictaba-like lectin genes in food crops with a focus on soybean (Glycine max).

PubMed

Van Holle, Sofie; Rougé, Pierre; Van Damme, Els J M

2017-03-01

The Nictaba family groups all proteins that show homology to Nictaba, the tobacco lectin. So far, Nictaba and an Arabidopsis thaliana homologue have been shown to be implicated in the plant stress response. The availability of more than 50 sequenced plant genomes provided the opportunity for a genome-wide identification of Nictaba -like genes in 15 species, representing members of the Fabaceae, Poaceae, Solanaceae, Musaceae, Arecaceae, Malvaceae and Rubiaceae. Additionally, phylogenetic relationships between the different species were explored. Furthermore, this study included domain organization analysis, searching for orthologous genes in the legume family and transcript profiling of the Nictaba -like lectin genes in soybean. Using a combination of BLASTp, InterPro analysis and hidden Markov models, the genomes of Medicago truncatula , Cicer arietinum , Lotus japonicus , Glycine max , Cajanus cajan , Phaseolus vulgaris , Theobroma cacao , Solanum lycopersicum , Solanum tuberosum , Coffea canephora , Oryza sativa , Zea mays, Sorghum bicolor , Musa acuminata and Elaeis guineensis were searched for Nictaba -like genes. Phylogenetic analysis was performed using RAxML and additional protein domains in the Nictaba-like sequences were identified using InterPro. Expression analysis of the soybean Nictaba -like genes was investigated using microarray data. Nictaba -like genes were identified in all studied species and analysis of the duplication events demonstrated that both tandem and segmental duplication contributed to the expansion of the Nictaba gene family in angiosperms. The single-domain Nictaba protein and the multi-domain F-box Nictaba architectures are ubiquitous among all analysed species and microarray analysis revealed differential expression patterns for all soybean Nictaba-like genes. Taken together, the comparative genomics data contributes to our understanding of the Nictaba -like gene family in species for which the occurrence of Nictaba domains had not yet been investigated. Given the ubiquitous nature of these genes, they have probably acquired new functions over time and are expected to take on various roles in plant development and defence. © The Author 2017. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Exploring Population Admixture Dynamics via Empirical and Simulated Genome-wide Distribution of Ancestral Chromosomal Segments

PubMed Central

Jin, Wenfei; Wang, Sijia; Wang, Haifeng; Jin, Li; Xu, Shuhua

2012-01-01

The processes of genetic admixture determine the haplotype structure and linkage disequilibrium patterns of the admixed population, which is important for medical and evolutionary studies. However, most previous studies do not consider the inherent complexity of admixture processes. Here we proposed two approaches to explore population admixture dynamics, and we demonstrated, by analyzing genome-wide empirical and simulated data, that the approach based on the distribution of chromosomal segments of distinct ancestry (CSDAs) was more powerful than that based on the distribution of individual ancestry proportions. Analysis of 1,890 African Americans showed that a continuous gene flow model, in which the African American population continuously received gene flow from European populations over about 14 generations, best explained the admixture dynamics of African Americans among several putative models. Interestingly, we observed that some African Americans had much more European ancestry than the simulated samples, indicating substructures of local ancestries in African Americans that could have been caused by individuals from some particular lineages having repeatedly admixed with people of European ancestry. In contrast, the admixture dynamics of Mexicans could be explained by a gradual admixture model in which the Mexican population continuously received gene flow from both European and Amerindian populations over about 24 generations. Our results also indicated that recent gene flows from Sub-Saharan Africans have contributed to the gene pool of Middle Eastern populations such as Mozabite, Bedouin, and Palestinian. In summary, this study not only provides approaches to explore population admixture dynamics, but also advances our understanding on population history of African Americans, Mexicans, and Middle Eastern populations. PMID:23103229

GIANT 2.0: genome-scale integrated analysis of gene networks in tissues.

PubMed

Wong, Aaron K; Krishnan, Arjun; Troyanskaya, Olga G

2018-05-25

GIANT2 (Genome-wide Integrated Analysis of gene Networks in Tissues) is an interactive web server that enables biomedical researchers to analyze their proteins and pathways of interest and generate hypotheses in the context of genome-scale functional maps of human tissues. The precise actions of genes are frequently dependent on their tissue context, yet direct assay of tissue-specific protein function and interactions remains infeasible in many normal human tissues and cell-types. With GIANT2, researchers can explore predicted tissue-specific functional roles of genes and reveal changes in those roles across tissues, all through interactive multi-network visualizations and analyses. Additionally, the NetWAS approach available through the server uses tissue-specific/cell-type networks predicted by GIANT2 to re-prioritize statistical associations from GWAS studies and identify disease-associated genes. GIANT2 predicts tissue-specific interactions by integrating diverse functional genomics data from now over 61 400 experiments for 283 diverse tissues and cell-types. GIANT2 does not require any registration or installation and is freely available for use at http://giant-v2.princeton.edu.

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

PubMed Central

Rioualen, Claire; Da Costa, Quentin; Chetrit, Bernard; Charafe-Jauffret, Emmanuelle; Ginestier, Christophe

2017-01-01

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2). PMID:28949986

ZikaBase: An integrated ZIKV- Human Interactome Map database.

PubMed

Gurumayum, Sanathoi; Brahma, Rahul; Naorem, Leimarembi Devi; Muthaiyan, Mathavan; Gopal, Jeyakodi; Venkatesan, Amouda

2018-01-15

Re-emergence of ZIKV has caused infections in more than 1.5 million people. The molecular mechanism and pathogenesis of ZIKV is not well explored due to unavailability of adequate model and lack of publically accessible resources to provide information of ZIKV-Human protein interactome map till today. This study made an attempt to curate the ZIKV-Human interaction proteins from published literatures and RNA-Seq data. 11 direct interaction, 12 associated genes are retrieved from literatures and 3742 Differentially Expressed Genes (DEGs) are obtained from RNA-Seq analysis. The genes have been analyzed to construct the ZIKV-Human Interactome Map. The importance of the study has been illustrated by the enrichment analysis and observed that direct interaction and associated genes are enriched in viral entry into host cell. Also, ZIKV infection modulates 32% signal and 27% immune system pathways. The integrated database, ZikaBase has been developed to help the virology research community and accessible at https://test5.bicpu.edu.in. Copyright © 2017 Elsevier Inc. All rights reserved.

Evolution of the chalcone synthase gene family in the genus Ipomoea.

PubMed Central

Durbin, M L; Learn, G H; Huttley, G A; Clegg, M T

1995-01-01

The evolution of the chalcone synthase [CHS; malonyl-CoA:4-coumaroyl-CoA malonyltransferase (cyclizing), EC 2.3.1.74] multigene family in the genus Ipomoea is explored. Thirteen CHS genes from seven Ipomoea species (family Convolvulaceae) were sequenced--three from genomic clones and the remainder from PCR amplification with primers designed from the 5' flanking region and the end of the 3' coding region of Ipomoea purpurea Roth. Analysis of the data indicates a duplication of CHS that predates the divergence of the Ipomoea species in this study. The Ipomoea CHS genes are among the most rapidly evolving of the CHS genes sequenced to date. The CHS genes in this study are most closely related to the Petunia CHS-B gene, which is also rapidly evolving and highly divergent from the rest of the Petunia CHS sequences. PMID:7724563

Integrative pathway analysis of a genome-wide association study of V̇o2max response to exercise training

PubMed Central

Vivar, Juan C.; Sarzynski, Mark A.; Sung, Yun Ju; Timmons, James A.; Bouchard, Claude; Rankinen, Tuomo

2013-01-01

We previously reported the findings from a genome-wide association study of the response of maximal oxygen uptake (V̇o2max) to an exercise program. Here we follow up on these results to generate hypotheses on genes, pathways, and systems involved in the ability to respond to exercise training. A systems biology approach can help us better establish a comprehensive physiological description of what underlies V̇o2maxtrainability. The primary material for this exploration was the individual single-nucleotide polymorphism (SNP), SNP-gene mapping, and statistical significance levels. We aimed to generate novel hypotheses through analyses that go beyond statistical association of single-locus markers. This was accomplished through three complementary approaches: 1) building de novo evidence of gene candidacy through informatics-driven literature mining; 2) aggregating evidence from statistical associations to link variant enrichment in biological pathways to V̇o2max trainability; and 3) predicting possible consequences of variants residing in the pathways of interest. We started with candidate gene prioritization followed by pathway analysis focused on overrepresentation analysis and gene set enrichment analysis. Subsequently, leads were followed using in silico analysis of predicted SNP functions. Pathways related to cellular energetics (pantothenate and CoA biosynthesis; PPAR signaling) and immune functions (complement and coagulation cascades) had the highest levels of SNP burden. In particular, long-chain fatty acid transport and fatty acid oxidation genes and sequence variants were found to influence differences in V̇o2max trainability. Together, these methods allow for the hypothesis-driven ranking and prioritization of genes and pathways for future experimental testing and validation. PMID:23990238

Global gene expression associated with hepatocarcinogenesis in adult male mice induced by in utero arsenic exposure.

PubMed

Liu, Jie; Xie, Yaxiong; Ducharme, Danica M K; Shen, Jun; Diwan, Bhalchandra A; Merrick, B Alex; Grissom, Sherry F; Tucker, Charles J; Paules, Richard S; Tennant, Raymond; Waalkes, Michael P

2006-03-01

Our previous work has shown that exposure to inorganic arsenic in utero produces hepatocellular carcinoma (HCC) in adult male mice. To explore further the molecular mechanisms of transplacental arsenic hepatocarcinogenesis, we conducted a second arsenic transplacental carcinogenesis study and used a genomewide microarray to profile arsenic-induced aberrant gene expression more extensively. Briefly, pregnant C3H mice were given drinking water containing 85 ppm arsenic as sodium arsenite or unaltered water from days 8 to 18 of gestation. The incidence of HCC in adult male offspring was increased 4-fold and tumor multiplicity 3-fold after transplacental arsenic exposure. Samples of normal liver and liver tumors were taken at autopsy for genomic analysis. Arsenic exposure in utero resulted in significant alterations (p < 0.001) in the expression of 2,010 genes in arsenic-exposed liver samples and in the expression of 2,540 genes in arsenic-induced HCC. Ingenuity Pathway Analysis revealed that significant alterations in gene expression occurred in a number of biological networks, and Myc plays a critical role in one of the primary networks. Real-time reverse transcriptase-polymerase chain reaction and Western blot analysis of selected genes/proteins showed > 90% concordance. Arsenic-altered gene expression included activation of oncogenes and HCC biomarkers, and increased expression of cell proliferation-related genes, stress proteins, and insulin-like growth factors and genes involved in cell-cell communications. Liver feminization was evidenced by increased expression of estrogen-linked genes and altered expression of genes that encode gender-related metabolic enzymes. These novel findings are in agreement with the biology and histology of arsenic-induced HCC, thereby indicating that multiple genetic events are associated with transplacental arsenic hepatocarcinogenesis.

Differential Effect of Active Smoking on Gene Expression in Male and Female Smokers

PubMed Central

Paul, Sunirmal; Amundson, Sally A

2015-01-01

Smoking is the second leading cause of preventable death in the United States. Cohort epidemiological studies have demonstrated that women are more vulnerable to cigarette-smoking induced diseases than their male counterparts, however, the molecular basis of these differences has remained unknown. In this study, we explored if there were differences in the gene expression patterns between male and female smokers, and how these patterns might reflect different sex-specific responses to the stress of smoking. Using whole genome microarray gene expression profiling, we found that a substantial number of oxidant related genes were expressed in both male and female smokers, however, smoking-responsive genes did indeed differ greatly between male and female smokers. Gene set enrichment analysis (GSEA) against reference oncogenic signature gene sets identified a large number of oncogenic pathway gene-sets that were significantly altered in female smokers compared to male smokers. In addition, functional annotation with Ingenuity Pathway Analysis (IPA) identified smoking-correlated genes associated with biological functions in male and female smokers that are directly relevant to well-known smoking related pathologies. However, these relevant biological functions were strikingly overrepresented in female smokers compared to male smokers. IPA network analysis with the functional categories of immune and inflammatory response gene products suggested potential interactions between smoking response and female hormones. Our results demonstrate a striking dichotomy between male and female gene expression responses to smoking. This is the first genome-wide expression study to compare the sex-specific impacts of smoking at a molecular level and suggests a novel potential connection between sex hormone signaling and smoking-induced diseases in female smokers. PMID:25621181

Identification of Reference Genes for Quantitative Gene Expression Studies in a Non-Model Tree Pistachio (Pistacia vera L.)

PubMed Central

Moazzam Jazi, Maryam; Ghadirzadeh Khorzoghi, Effat; Botanga, Christopher; Seyedi, Seyed Mahdi

2016-01-01

The tree species, Pistacia vera (P. vera) is an important commercial product that is salt-tolerant and long-lived, with a possible lifespan of over one thousand years. Gene expression analysis is an efficient method to explore the possible regulatory mechanisms underlying these characteristics. Therefore, having the most suitable set of reference genes is required for transcript level normalization under different conditions in P. vera. In the present study, we selected eight widely used reference genes, ACT, EF1α, α-TUB, β-TUB, GAPDH, CYP2, UBQ10, and 18S rRNA. Using qRT-PCR their expression was assessed in 54 different samples of three cultivars of P. vera. The samples were collected from different organs under various abiotic treatments (cold, drought, and salt) across three time points. Several statistical programs (geNorm, NormFinder, and BestKeeper) were applied to estimate the expression stability of candidate reference genes. Results obtained from the statistical analysis were then exposed to Rank aggregation package to generate a consensus gene rank. Based on our results, EF1α was found to be the superior reference gene in all samples under all abiotic treatments. In addition to EF1α, ACT and β-TUB were the second best reference genes for gene expression analysis in leaf and root. We recommended β-TUB as the second most stable gene for samples under the cold and drought treatments, while ACT holds the same position in samples analyzed under salt treatment. This report will benefit future research on the expression profiling of P. vera and other members of the Anacardiaceae family. PMID:27308855

Identification of Reference Genes for Quantitative Gene Expression Studies in a Non-Model Tree Pistachio (Pistacia vera L.).

PubMed

Moazzam Jazi, Maryam; Ghadirzadeh Khorzoghi, Effat; Botanga, Christopher; Seyedi, Seyed Mahdi

2016-01-01

The tree species, Pistacia vera (P. vera) is an important commercial product that is salt-tolerant and long-lived, with a possible lifespan of over one thousand years. Gene expression analysis is an efficient method to explore the possible regulatory mechanisms underlying these characteristics. Therefore, having the most suitable set of reference genes is required for transcript level normalization under different conditions in P. vera. In the present study, we selected eight widely used reference genes, ACT, EF1α, α-TUB, β-TUB, GAPDH, CYP2, UBQ10, and 18S rRNA. Using qRT-PCR their expression was assessed in 54 different samples of three cultivars of P. vera. The samples were collected from different organs under various abiotic treatments (cold, drought, and salt) across three time points. Several statistical programs (geNorm, NormFinder, and BestKeeper) were applied to estimate the expression stability of candidate reference genes. Results obtained from the statistical analysis were then exposed to Rank aggregation package to generate a consensus gene rank. Based on our results, EF1α was found to be the superior reference gene in all samples under all abiotic treatments. In addition to EF1α, ACT and β-TUB were the second best reference genes for gene expression analysis in leaf and root. We recommended β-TUB as the second most stable gene for samples under the cold and drought treatments, while ACT holds the same position in samples analyzed under salt treatment. This report will benefit future research on the expression profiling of P. vera and other members of the Anacardiaceae family.

[Association between patatin-like phospholipase domain-containing protein 3 gene rs738409 polymorphism and non-alcoholic fatty liver disease susceptibility: a meta-analysis].

PubMed

Wu, Pengbo; Shu, Yongxiang; Guo, Fang; Luo, Hesheng; Zhang, Guo; Tan, Shiyun

2015-01-01

To explore the association between patatin-like phospholipase domain-containing protein 3(PNPLA3) gene rs738409 polymorphism and the susceptibility of non-alcoholic fatty liver disease(NAFLD). Data bases were comprehensively searched to retrace all the related studies on the association between PNPLA3 gene rs738409 polymorphism and susceptibility. Of NAFLD, the pooled OR with 95% CI of the association between PNPLA3 gene rs738409 polymorphism and NAFLD susceptibility were performed using different genetic models. Subgroup analysis based on the source of population and sensitivity analysis was performed to detect the stability of results. 28 original studies with 6 216 patients and 8 218 controls were involved in the final combination of data. Findings from the meta-analyses showed that there were strong associations between PNPLA3 gene rs738409 polymorphism and the susceptibility of NAFLD, under different genetic model comparisons[GG vs. CC:OR = 2.42, 95%CI:1.83-3.21, P < 0.001;CG vs. CC:OR = 1.28, 95%CI:1.15-1.43, P < 0.001;CG+GG vs. CC:OR = 1.31, 95%CI:1.17-1.46, P < 0.001; GG vs. CC+GC:OR = 2.26, 95%CI:1.76-2.90, P < 0.001]. Similar results were found in both Asian and Caucasian populations. Results from the Meta-analysis strongly suggested that there appeared significant association between PNPLA3 gene rs738409 polymorphism and the susceptibility of NAFLD.

Prognostic factors and genes associated with endometrial cancer based on gene expression profiling by bioinformatics analysis.

PubMed

Zhang, Ying; Zhang, Wei; Li, Xinglan; Li, Dapeng; Zhang, Xiaoling; Yin, Yajie; Deng, Xiangyun; Sheng, Xiugui

2016-06-01

Endometrial cancer (EC) is the most prevalent malignancy worldwide. Although several efforts had been made to explore the molecular mechanism responsible for EC progression, it is still not fully understood. To evaluate the clinical characteristics and prognostic factors of patients with EC, and further to search for novel genes associated with EC progression. We recruited 328 patients with EC and analyzed prognostic factors using Cox proportional hazard regression model. Further, a gene expression profile of EC was used to identify the differentially expressed genes (DEGs) between normal samples and tumor samples. Subsequently, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis ( http://www.genome.jp/kegg/ ) for DEGs were performed, and then protein-protein interaction (PPI) network of DEGs as well as the subnetwork of PPI were constructed with plug-in, MCODE by mapping DEGs into the Search Tool for the Retrieval of Interacting Genes database. Our results showed that body mass index (BMI), hypertension, myometrial invasion, pathological type, and Glut4 positive expression were prognostic factors in EC (P < 0.05). Bioinformatics analysis showed that upregulated DEGs were associated with cell cycle, and downregulated DEGs were related to MAPK pathway. Meanwhile, PPI network analysis revealed that upregulated CDK1 and CCNA2 as well as downregulated JUN and FOS were listed in top two nodes with high degrees. Patients with EC should be given more focused attentions in respect of pathological type, BMI, hypertension, and Glut4-positive expression. In addition, CDK1, CCNA2, JUN, and FOS might play important roles in EC development.

Single cell sequencing reveals heterogeneity within ovarian cancer epithelium and cancer associated stromal cells.

PubMed

Winterhoff, Boris J; Maile, Makayla; Mitra, Amit Kumar; Sebe, Attila; Bazzaro, Martina; Geller, Melissa A; Abrahante, Juan E; Klein, Molly; Hellweg, Raffaele; Mullany, Sally A; Beckman, Kenneth; Daniel, Jerry; Starr, Timothy K

2017-03-01

The purpose of this study was to determine the level of heterogeneity in high grade serous ovarian cancer (HGSOC) by analyzing RNA expression in single epithelial and cancer associated stromal cells. In addition, we explored the possibility of identifying subgroups based on pathway activation and pre-defined signatures from cancer stem cells and chemo-resistant cells. A fresh, HGSOC tumor specimen derived from ovary was enzymatically digested and depleted of immune infiltrating cells. RNA sequencing was performed on 92 single cells and 66 of these single cell datasets passed quality control checks. Sequences were analyzed using multiple bioinformatics tools, including clustering, principle components analysis, and geneset enrichment analysis to identify subgroups and activated pathways. Immunohistochemistry for ovarian cancer, stem cell and stromal markers was performed on adjacent tumor sections. Analysis of the gene expression patterns identified two major subsets of cells characterized by epithelial and stromal gene expression patterns. The epithelial group was characterized by proliferative genes including genes associated with oxidative phosphorylation and MYC activity, while the stromal group was characterized by increased expression of extracellular matrix (ECM) genes and genes associated with epithelial-to-mesenchymal transition (EMT). Neither group expressed a signature correlating with published chemo-resistant gene signatures, but many cells, predominantly in the stromal subgroup, expressed markers associated with cancer stem cells. Single cell sequencing provides a means of identifying subpopulations of cancer cells within a single patient. Single cell sequence analysis may prove to be critical for understanding the etiology, progression and drug resistance in ovarian cancer. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of Key Pathways and Genes in L4 Dorsal Root Ganglion (DRG) After Sciatic Nerve Injury via Microarray Analysis.

PubMed

Zhao, He; Duan, Li-Jun; Sun, Qing-Ling; Gao, Yu-Shan; Yang, Yong-Dong; Tang, Xiang-Sheng; Zhao, Ding-Yan; Xiong, Yang; Hu, Zhen-Guo; Li, Chuan-Hong; Chen, Si-Xue; Liu, Tao; Yu, Xing

2018-04-19

Peripheral nerve injury (PNI) has devastating consequences. Dorsal root ganglion as a pivotal locus participates in the process of neuropathic pain and nerve regeneration. In recent years, gene sequencing technology has seen rapid rise in the biomedicine field. So, we attempt to gain insight into in the mechanism of neuropathic pain and nerve regeneration in the transcriptional level and to explore novel genes through bioinformatics analysis. The gene expression profiles of GSE96051 were downloaded from GEO database. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and protein-protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed by Cytoscape software. Our results showed that both IL-6 and Jun genes and the signaling pathway of MAPK, apoptosis, P53 present their vital modulatory role in nerve regeneration and neuropathic pain. Noteworthy, 13 hub genes associated with neuropathic pain and nerve regeneration, including Ccl12, Ppp1r15a, Cdkn1a, Atf3, Nts, Dusp1, Ccl7, Csf, Gadd45a, Serpine1, Timp1 were rarely reported in PubMed database, these genes may provide us the new orientation in experimental research and clinical study. Our results may provide more deep insight into the mechanism and a promising therapeutic target. The next step is to put our emphasis on an experiment level and to verify the novel genes from 13 hub genes.

The ergot alkaloid gene cluster in Claviceps purpurea: extension of the cluster sequence and intra species evolution.

PubMed

Haarmann, Thomas; Machado, Caroline; Lübbe, Yvonne; Correia, Telmo; Schardl, Christopher L; Panaccione, Daniel G; Tudzynski, Paul

2005-06-01

The genomic region of Claviceps purpurea strain P1 containing the ergot alkaloid gene cluster [Tudzynski, P., Hölter, K., Correia, T., Arntz, C., Grammel, N., Keller, U., 1999. Evidence for an ergot alkaloid gene cluster in Claviceps purpurea. Mol. Gen. Genet. 261, 133-141] was explored by chromosome walking, and additional genes probably involved in the ergot alkaloid biosynthesis have been identified. The putative cluster sequence (extending over 68.5kb) contains 4 different nonribosomal peptide synthetase (NRPS) genes and several putative oxidases. Northern analysis showed that most of the genes were co-regulated (repressed by high phosphate), and identified probable flanking genes by lack of co-regulation. Comparison of the cluster sequences of strain P1, an ergotamine producer, with that of strain ECC93, an ergocristine producer, showed high conservation of most of the cluster genes, but significant variation in the NRPS modules, strongly suggesting that evolution of these chemical races of C. purpurea is determined by evolution of NRPS module specificity.

GreenPhylDB v2.0: comparative and functional genomics in plants.

PubMed

Rouard, Mathieu; Guignon, Valentin; Aluome, Christelle; Laporte, Marie-Angélique; Droc, Gaëtan; Walde, Christian; Zmasek, Christian M; Périn, Christophe; Conte, Matthieu G

2011-01-01

GreenPhylDB is a database designed for comparative and functional genomics based on complete genomes. Version 2 now contains sixteen full genomes of members of the plantae kingdom, ranging from algae to angiosperms, automatically clustered into gene families. Gene families are manually annotated and then analyzed phylogenetically in order to elucidate orthologous and paralogous relationships. The database offers various lists of gene families including plant, phylum and species specific gene families. For each gene cluster or gene family, easy access to gene composition, protein domains, publications, external links and orthologous gene predictions is provided. Web interfaces have been further developed to improve the navigation through information related to gene families. New analysis tools are also available, such as a gene family ontology browser that facilitates exploration. GreenPhylDB is a component of the South Green Bioinformatics Platform (http://southgreen.cirad.fr/) and is accessible at http://greenphyl.cirad.fr. It enables comparative genomics in a broad taxonomy context to enhance the understanding of evolutionary processes and thus tends to speed up gene discovery.

[Progress in porky genes and transcriptome and discussion of relative issues].

PubMed

Zhu, Meng-Jin; Liu, Bang; Li, Kui

2005-01-01

To date, research on molecular base of porky molecular development was mainly involved in muscle growth and meat quality. Some functional genes including Hal gene and RN gene and some QTLs controlling or associated with porky growth and quality were detected through candidate gene approach and genome-wide scanning. Genic transcriptome pertinent to porcine muscle and adipose also came into study. At the same time, these researches have befallen some shortcomings to some extent. Research from molecular quantitative genetics showed shortcomings that single gene was devilishly emphasized and co-expression pattern of multi-genes was ignored. Research applying transcriptome analysis tool also met two of limitations, one was the singleness of type of molecular experimental techniques, and another was that genes of muscle and adipose were artificially divided into unattached two parts. Thus, porky genes were explored by parallel genetics based on systemic views and techniques to specially reveal the interactional mechanism of porky genes respectively controlling muscle and adipose, which would be important issues of genes and genome researches on porky development in the near future.

Altered retinal microRNA expression profiles in early diabetic retinopathy: an in silico analysis.

PubMed

Xiong, Fen; Du, Xinhua; Hu, Jianyan; Li, Tingting; Du, Shanshan; Wu, Qiang

2014-07-01

MicroRNAs (miRNAs) - as negative regulators of target genes - are associated with various human diseases, but their precise role(s) in diabetic retinopathy (DR) remains to be elucidated. The aim of this study was to elucidate the involvement of miRNAs in early DR using in silico analysis to explore their gene expression patterns. We used the streptozotocin (STZ)-induced diabetic rat to investigate the roles of miRNAs in early DR. Retinal miRNA expression profiles from diabetic versus healthy control rats were examined by miRNA array analysis. Based on several bioinformatic systems, specifically, gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, we identified signatures of the potential pathological processes, gene functions, and signaling pathways that are influenced by dysregulated miRNAs. We used quantitative real-time polymerase chain reaction (qRT-PCR) to validate six (i.e. those with significant changes in expression levels) of the 17 miRNAs that were detected in the miRNA array. We also describe the significant role of the miRNA-gene network, which is based on the interactions between miRNAs and target genes. GO analysis of the 17 miRNAs detected in the miRNA array analysis revealed the most prevalent miRNAs to be those related to biological processes, olfactory bulb development and axonogenesis. These miRNAs also exert significant influence on additional pathways, including the mitogen-activated protein and calcium signaling pathways. Six of the seventeen miRNAs were chosen for qRT-PCR validation. With the exception of a slight difference in miRNA-350, our results are in close agreement with the differential expressions detected by array analysis. This study, which describes miRNA expression during the early developmental phases of DR, revealed extensive miRNA interactions. Based on both their target genes and signaling pathways, we suggest that miRNAs perform critical regulatory functions during the early stages of DR evolution.

Genome sequence analysis of a flocculant-producing bacterium, Paenibacillus shenyangensis.

PubMed

Fu, Lili; Jiang, Binhui; Liu, Jinliang; Zhao, Xin; Liu, Qian; Hu, Xiaomin

2016-03-01

To explore the metabolic process of Paenibacillus shenyangensis that is an efficient bioflocculant-producing bacterium. The biosynthesis mechanism of bioflocculation was used to enrich the genome of Paenibacillus shenyangensis and provide a basis for molecular genetics and functional genomics analyses. According to the analysis of de novo assembly, a total of 5,501,467 bp clean reads were generated, and were assembled into 92 contigs. 4800 unigenes were predicted of which 4393 were annotated showing a specific gene function in the NCBI-Nr database. 3423 genes were found in the database of cluster of orthologous groups. Among the 168 Kyoto Encyclopedia of Genes and Genomes database, cell growth and metabolism were the main biological processes, and a potential metabolic pathway was predicted from glucose to exopolysaccharide within the starch and sucrose metabolism pathway. By using the high-throughput sequencing technology, we provide a genome analysis of Paenibacillus shenyangensis that predicts the main metabolic processes and a potential pathway of exopolysaccharide biosynthesis.

ITGBL1 promotes migration, invasion and predicts a poor prognosis in colorectal cancer.

PubMed

Qiu, Xiao; Feng, Jue-Rong; Qiu, Jun; Liu, Lan; Xie, Yang; Zhang, Yu-Peng; Liu, Jing; Zhao, Qiu

2018-05-14

Colorectal cancer (CRC) is one of the most common malignancies worldwide; its progression and prognosis are associated with oncogenes. The present study aimed to identify differentially expressed genes (DEGs) and explore the role and potential mechanism of integrin subunit β like 1 (ITGBL1) in CRC. The microarray dataset GSE41258 was used to screen DEGs involved in CRC. Survival analysis was performed to predict the prognosis of CRC patients. To validate ITGBL1 expression, immunohistochemistry, quantitative real-time PCR and western blotting were performed in CRC tissues and cells. Subsequently, the effects of ITGBL1 were evaluated through colony formation, cell proliferation, migration and invasion assays. Finally, we took advantage of Gene Ontology (GO) analysis and Gene Set Enrichment Analysis (GSEA) to explore potential function and mechanism of ITGBL1 in CRC. In our study, 182 primary CRC tissues and 54 normal colon tissues were contained in GSE41258 dataset. A total of 318 DEGs were screened, among which ITGBL1 was found to be significantly up-regulated in CRC, and its high expression was associated with shortened survival of CRC patients. Moreover, knockdown of ITGBL1 promoted CRC cell proliferation, migration and invasion. Finally, GO analysis revealed that ITGBL1 was associated with cell adhesion. GSEA indicated that ITGBL1 was enriched in ECM receptor interaction and focal adhesion. In conclusion, a novel oncogene ITGBL1 was identified and demonstrated to be associated with the progression and prognosis of CRC, which might be a potential therapeutic target and prognostic biomarker for CRC patients. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

[Association of estrogen receptor gene polymorphism with cerebral infarction, a case-control study].

PubMed

Zhang, Yan; Xie, Ruping; Wang, Yinhua; Chen, Dafang; Wang, Guoying; Xu, Xiping

2002-11-10

To explore the association between estrogen receptor (ER) gene PvuII and XbaI polymorphisms and cerebral infarction among Chinese Han people. Samples of peripheral blood white cell were extracted among 234 patients with cerebral infarction, aged 63.9 +/- 10.3, and 259 controls without cerebrovascular disease, aged 59.2 +/- 9.2, all of Chinese Han nationality. PCR-RFLP and genotyping of ER PvuII and XbaI polymorphisms were performed. Multiple Logistic regression analysis was made to explore the risk factors for cerebral infarction. After adjustment for major confounders including age, gender, smoking, alcohol drinking, education, history of hypertension, diabetes mellitus, coronary artery disease and hyperlipoidemia, multiple Logistic regression analysis showed that: (1) The Pp genotype of ER PvuII polymorphism increased the risk of cerebral infarction significantly (OR = 1.97, 95% CI: 1.21 - 3.21); (2) The ER XbaI polymorphism was not in association with cerebral infarction significantly; (3) The PPXx/Ppxx genotypes increased the risk of cerebral infarction significantly (OR = 1.67, 2.52 and 2.18 respectively, P < 0.05) before or after all subjects were stratified by the history of hypertension or hyperlipoidemia; and (4) The positive interaction between the ER PvuII polymorphism and the presence of hypertension or diabetes or hyperlipoidemia could increase the risk of cerebral infarction significantly. ER gene may be one of the genetic candidate genes for cerebral infarction among Chinese Han population.

EUCANEXT: an integrated database for the exploration of genomic and transcriptomic data from Eucalyptus species

PubMed Central

Nascimento, Leandro Costa; Salazar, Marcela Mendes; Lepikson-Neto, Jorge; Camargo, Eduardo Leal Oliveira; Parreiras, Lucas Salera; Carazzolle, Marcelo Falsarella

2017-01-01

Abstract Tree species of the genus Eucalyptus are the most valuable and widely planted hardwoods in the world. Given the economic importance of Eucalyptus trees, much effort has been made towards the generation of specimens with superior forestry properties that can deliver high-quality feedstocks, customized to the industrýs needs for both cellulosic (paper) and lignocellulosic biomass production. In line with these efforts, large sets of molecular data have been generated by several scientific groups, providing invaluable information that can be applied in the development of improved specimens. In order to fully explore the potential of available datasets, the development of a public database that provides integrated access to genomic and transcriptomic data from Eucalyptus is needed. EUCANEXT is a database that analyses and integrates publicly available Eucalyptus molecular data, such as the E. grandis genome assembly and predicted genes, ESTs from several species and digital gene expression from 26 RNA-Seq libraries. The database has been implemented in a Fedora Linux machine running MySQL and Apache, while Perl CGI was used for the web interfaces. EUCANEXT provides a user-friendly web interface for easy access and analysis of publicly available molecular data from Eucalyptus species. This integrated database allows for complex searches by gene name, keyword or sequence similarity and is publicly accessible at http://www.lge.ibi.unicamp.br/eucalyptusdb. Through EUCANEXT, users can perform complex analysis to identify genes related traits of interest using RNA-Seq libraries and tools for differential expression analysis. Moreover, all the bioinformatics pipeline here described, including the database schema and PERL scripts, are readily available and can be applied to any genomic and transcriptomic project, regardless of the organism. Database URL: http://www.lge.ibi.unicamp.br/eucalyptusdb PMID:29220468

Transcriptome inference and systems approaches to polypharmacology and drug discovery in herbal medicine.

PubMed

Li, Peng; Chen, Jianxin; Zhang, Wuxia; Fu, Bangze; Wang, Wei

2017-01-04

Herbal medicine is a concoction of numerous chemical ingredients, and it exhibits polypharmacological effects to act on multiple pharmacological targets, regulating different biological mechanisms and treating a variety of diseases. Thus, this complexity is impossible to deconvolute by the reductionist method of extracting one active ingredient acting on one biological target. To dissect the polypharmacological effects of herbal medicines and their underling pharmacological targets as well as their corresponding active ingredients. We propose a system-biology strategy that combines omics and bioinformatical methodologies for exploring the polypharmacology of herbal mixtures. The myocardial ischemia model was induced by Ameroid constriction of the left anterior descending coronary in Ba-Ma miniature pigs. RNA-seq analysis was utilized to find the differential genes induced by myocardial ischemia in pigs treated with formula QSKL. A transcriptome-based inference method was used to find the landmark drugs with similar mechanisms to QSKL. Gene-level analysis of RNA-seq data in QSKL-treated cases versus control animals yields 279 differential genes. Transcriptome-based inference methods identified 80 landmark drugs that covered nearly all drug classes. Then, based on the landmark drugs, 155 potential pharmacological targets and 57 indications were identified for QSKL. Our results demonstrate the power of a combined approach for exploring the pharmacological target and chemical space of herbal medicines. We hope that our method could enhance our understanding of the molecular mechanisms of herbal systems and further accelerate the exploration of the value of traditional herbal medicine systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Co-expression analysis and identification of fecundity-related long non-coding RNAs in sheep ovaries

PubMed Central

Miao, Xiangyang; Luo, Qingmiao; Zhao, Huijing; Qin, Xiaoyu

2016-01-01

Small Tail Han sheep, including the FecBBFecBB (Han BB) and FecB+ FecB+ (Han++) genotypes, and Dorset sheep exhibit different fecundities. To identify novel long non-coding RNAs (lncRNAs) associated with sheep fecundity to better understand their molecular mechanisms, a genome-wide analysis of mRNAs and lncRNAs from Han BB, Han++ and Dorset sheep was performed. After the identification of differentially expressed mRNAs and lncRNAs, 16 significant modules were explored by using weighted gene coexpression network analysis (WGCNA) followed by functional enrichment analysis of the genes and lncRNAs in significant modules. Among these selected modules, the yellow and brown modules were significantly related to sheep fecundity. lncRNAs (e.g., NR0B1, XLOC_041882, and MYH15) in the yellow module were mainly involved in the TGF-β signalling pathway, and NYAP1 and BCORL1 were significantly associated with the oxytocin signalling pathway, which regulates several genes in the coexpression network of the brown module. Overall, we identified several gene modules associated with sheep fecundity, as well as networks consisting of hub genes and lncRNAs that may contribute to sheep prolificacy by regulating the target mRNAs related to the TGF-β and oxytocin signalling pathways. This study provides an alternative strategy for the identification of potential candidate regulatory lncRNAs. PMID:27982099

Co-expression analysis and identification of fecundity-related long non-coding RNAs in sheep ovaries.

PubMed

Miao, Xiangyang; Luo, Qingmiao; Zhao, Huijing; Qin, Xiaoyu

2016-12-16

Small Tail Han sheep, including the FecB B FecB B (Han BB) and FecB + FecB + (Han++) genotypes, and Dorset sheep exhibit different fecundities. To identify novel long non-coding RNAs (lncRNAs) associated with sheep fecundity to better understand their molecular mechanisms, a genome-wide analysis of mRNAs and lncRNAs from Han BB, Han++ and Dorset sheep was performed. After the identification of differentially expressed mRNAs and lncRNAs, 16 significant modules were explored by using weighted gene coexpression network analysis (WGCNA) followed by functional enrichment analysis of the genes and lncRNAs in significant modules. Among these selected modules, the yellow and brown modules were significantly related to sheep fecundity. lncRNAs (e.g., NR0B1, XLOC_041882, and MYH15) in the yellow module were mainly involved in the TGF-β signalling pathway, and NYAP1 and BCORL1 were significantly associated with the oxytocin signalling pathway, which regulates several genes in the coexpression network of the brown module. Overall, we identified several gene modules associated with sheep fecundity, as well as networks consisting of hub genes and lncRNAs that may contribute to sheep prolificacy by regulating the target mRNAs related to the TGF-β and oxytocin signalling pathways. This study provides an alternative strategy for the identification of potential candidate regulatory lncRNAs.

Whole genome sequencing options for bacterial strain typing and epidemiologic analysis based on single nucleotide polymorphism versus gene-by-gene-based approaches.

PubMed

Schürch, A C; Arredondo-Alonso, S; Willems, R J L; Goering, R V

2018-04-01

Whole genome sequence (WGS)-based strain typing finds increasing use in the epidemiologic analysis of bacterial pathogens in both public health as well as more localized infection control settings. This minireview describes methodologic approaches that have been explored for WGS-based epidemiologic analysis and considers the challenges and pitfalls of data interpretation. Personal collection of relevant publications. When applying WGS to study the molecular epidemiology of bacterial pathogens, genomic variability between strains is translated into measures of distance by determining single nucleotide polymorphisms in core genome alignments or by indexing allelic variation in hundreds to thousands of core genes, assigning types to unique allelic profiles. Interpreting isolate relatedness from these distances is highly organism specific, and attempts to establish species-specific cutoffs are unlikely to be generally applicable. In cases where single nucleotide polymorphism or core gene typing do not provide the resolution necessary for accurate assessment of the epidemiology of bacterial pathogens, inclusion of accessory gene or plasmid sequences may provide the additional required discrimination. As with all epidemiologic analysis, realizing the full potential of the revolutionary advances in WGS-based approaches requires understanding and dealing with issues related to the fundamental steps of data generation and interpretation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Overview of research on Bombyx mori microRNA

PubMed Central

Wang, Xin; Tang, Shun-ming; Shen, Xing-jia

2014-01-01

Abstract MicroRNAs (miRNAs) constitute some of the most significant regulatory factors involved at the post-transcriptional level after gene expression, contributing to the modulation of a large number of physiological processes such as development, metabolism, and disease occurrence. This review comprehensively and retrospectively explores the literature investigating silkworm, Bombyx mori L. (Lepidoptera: Bombicidae), miRNAs published to date, including discovery, identification, expression profiling analysis, target gene prediction, and the functional analysis of both miRNAs and their targets. It may provide experimental considerations and approaches for future study of miRNAs and benefit elucidation of the mechanisms of miRNAs involved in silkworm developmental processes and intracellular activities of other unknown non-coding RNAs. PMID:25368077

Whole Genome Gene Expression Meta-Analysis of Inflammatory Bowel Disease Colon Mucosa Demonstrates Lack of Major Differences between Crohn's Disease and Ulcerative Colitis

PubMed Central

Østvik, Ann E.; Drozdov, Ignat; Gustafsson, Bjørn I.; Kidd, Mark; Beisvag, Vidar; Torp, Sverre H.; Waldum, Helge L.; Martinsen, Tom Christian; Damås, Jan Kristian; Espevik, Terje; Sandvik, Arne K.

2013-01-01

Background In inflammatory bowel disease (IBD), genetic susceptibility together with environmental factors disturbs gut homeostasis producing chronic inflammation. The two main IBD subtypes are Ulcerative colitis (UC) and Crohn’s disease (CD). We present the to-date largest microarray gene expression study on IBD encompassing both inflamed and un-inflamed colonic tissue. A meta-analysis including all available, comparable data was used to explore important aspects of IBD inflammation, thereby validating consistent gene expression patterns. Methods Colon pinch biopsies from IBD patients were analysed using Illumina whole genome gene expression technology. Differential expression (DE) was identified using LIMMA linear model in the R statistical computing environment. Results were enriched for gene ontology (GO) categories. Sets of genes encoding antimicrobial proteins (AMP) and proteins involved in T helper (Th) cell differentiation were used in the interpretation of the results. All available data sets were analysed using the same methods, and results were compared on a global and focused level as t-scores. Results Gene expression in inflamed mucosa from UC and CD are remarkably similar. The meta-analysis confirmed this. The patterns of AMP and Th cell-related gene expression were also very similar, except for IL23A which was consistently higher expressed in UC than in CD. Un-inflamed tissue from patients demonstrated minimal differences from healthy controls. Conclusions There is no difference in the Th subgroup involvement between UC and CD. Th1/Th17 related expression, with little Th2 differentiation, dominated both diseases. The different IL23A expression between UC and CD suggests an IBD subtype specific role. AMPs, previously little studied, are strongly overexpressed in IBD. The presented meta-analysis provides a sound background for further research on IBD pathobiology. PMID:23468882

Whole genome gene expression meta-analysis of inflammatory bowel disease colon mucosa demonstrates lack of major differences between Crohn's disease and ulcerative colitis.

PubMed

Granlund, Atle van Beelen; Flatberg, Arnar; Østvik, Ann E; Drozdov, Ignat; Gustafsson, Bjørn I; Kidd, Mark; Beisvag, Vidar; Torp, Sverre H; Waldum, Helge L; Martinsen, Tom Christian; Damås, Jan Kristian; Espevik, Terje; Sandvik, Arne K

2013-01-01

In inflammatory bowel disease (IBD), genetic susceptibility together with environmental factors disturbs gut homeostasis producing chronic inflammation. The two main IBD subtypes are Ulcerative colitis (UC) and Crohn's disease (CD). We present the to-date largest microarray gene expression study on IBD encompassing both inflamed and un-inflamed colonic tissue. A meta-analysis including all available, comparable data was used to explore important aspects of IBD inflammation, thereby validating consistent gene expression patterns. Colon pinch biopsies from IBD patients were analysed using Illumina whole genome gene expression technology. Differential expression (DE) was identified using LIMMA linear model in the R statistical computing environment. Results were enriched for gene ontology (GO) categories. Sets of genes encoding antimicrobial proteins (AMP) and proteins involved in T helper (Th) cell differentiation were used in the interpretation of the results. All available data sets were analysed using the same methods, and results were compared on a global and focused level as t-scores. Gene expression in inflamed mucosa from UC and CD are remarkably similar. The meta-analysis confirmed this. The patterns of AMP and Th cell-related gene expression were also very similar, except for IL23A which was consistently higher expressed in UC than in CD. Un-inflamed tissue from patients demonstrated minimal differences from healthy controls. There is no difference in the Th subgroup involvement between UC and CD. Th1/Th17 related expression, with little Th2 differentiation, dominated both diseases. The different IL23A expression between UC and CD suggests an IBD subtype specific role. AMPs, previously little studied, are strongly overexpressed in IBD. The presented meta-analysis provides a sound background for further research on IBD pathobiology.

An exploration of the sequence of a 2.9-Mb region of the genome of Drosophila melanogaster: the Adh region.

PubMed Central

Ashburner, M; Misra, S; Roote, J; Lewis, S E; Blazej, R; Davis, T; Doyle, C; Galle, R; George, R; Harris, N; Hartzell, G; Harvey, D; Hong, L; Houston, K; Hoskins, R; Johnson, G; Martin, C; Moshrefi, A; Palazzolo, M; Reese, M G; Spradling, A; Tsang, G; Wan, K; Whitelaw, K; Celniker, S

1999-01-01

A contiguous sequence of nearly 3 Mb from the genome of Drosophila melanogaster has been sequenced from a series of overlapping P1 and BAC clones. This region covers 69 chromosome polytene bands on chromosome arm 2L, including the genetically well-characterized "Adh region." A computational analysis of the sequence predicts 218 protein-coding genes, 11 tRNAs, and 17 transposable element sequences. At least 38 of the protein-coding genes are arranged in clusters of from 2 to 6 closely related genes, suggesting extensive tandem duplication. The gene density is one protein-coding gene every 13 kb; the transposable element density is one element every 171 kb. Of 73 genes in this region identified by genetic analysis, 49 have been located on the sequence; P-element insertions have been mapped to 43 genes. Ninety-five (44%) of the known and predicted genes match a Drosophila EST, and 144 (66%) have clear similarities to proteins in other organisms. Genes known to have mutant phenotypes are more likely to be represented in cDNA libraries, and far more likely to have products similar to proteins of other organisms, than are genes with no known mutant phenotype. Over 650 chromosome aberration breakpoints map to this chromosome region, and their nonrandom distribution on the genetic map reflects variation in gene spacing on the DNA. This is the first large-scale analysis of the genome of D. melanogaster at the sequence level. In addition to the direct results obtained, this analysis has allowed us to develop and test methods that will be needed to interpret the complete sequence of the genome of this species.Before beginning a Hunt, it is wise to ask someone what you are looking for before you begin looking for it. Milne 1926 PMID:10471707

Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing

PubMed Central

de Anda-Jáuregui, Guillermo; Guo, Kai; McGregor, Brett A.; Hur, Junguk

2018-01-01

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space. PMID:29545755

Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing.

PubMed

de Anda-Jáuregui, Guillermo; Guo, Kai; McGregor, Brett A; Hur, Junguk

2018-01-01

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space.

TP53 mutations, expression and interaction networks in human cancers

PubMed Central

Wang, Xiaosheng; Sun, Qingrong

2017-01-01

Although the associations of p53 dysfunction, p53 interaction networks and oncogenesis have been widely explored, a systematic analysis of TP53 mutations and its related interaction networks in various types of human cancers is lacking. Our study explored the associations of TP53 mutations, gene expression, clinical outcomes, and TP53 interaction networks across 33 cancer types using data from The Cancer Genome Atlas (TCGA). We show that TP53 is the most frequently mutated gene in a number of cancers, and its mutations appear to be early events in cancer initiation. We identified genes potentially repressed by p53, and genes whose expression correlates significantly with TP53 expression. These gene products may be especially important nodes in p53 interaction networks in human cancers. This study shows that while TP53-truncating mutations often result in decreased TP53 expression, other non-truncating TP53 mutations result in increased TP53 expression in some cancers. Survival analyses in a number of cancers show that patients with TP53 mutations are more likely to have worse prognoses than TP53-wildtype patients, and that elevated TP53 expression often leads to poor clinical outcomes. We identified a set of candidate synthetic lethal (SL) genes for TP53, and validated some of these SL interactions using data from the Cancer Cell Line Project. These predicted SL genes are promising candidates for experimental validation and the development of personalized therapeutics for patients with TP53-mutated cancers. PMID:27880943

TP53 mutations, expression and interaction networks in human cancers.

PubMed

Wang, Xiaosheng; Sun, Qingrong

2017-01-03

Although the associations of p53 dysfunction, p53 interaction networks and oncogenesis have been widely explored, a systematic analysis of TP53 mutations and its related interaction networks in various types of human cancers is lacking. Our study explored the associations of TP53 mutations, gene expression, clinical outcomes, and TP53 interaction networks across 33 cancer types using data from The Cancer Genome Atlas (TCGA). We show that TP53 is the most frequently mutated gene in a number of cancers, and its mutations appear to be early events in cancer initiation. We identified genes potentially repressed by p53, and genes whose expression correlates significantly with TP53 expression. These gene products may be especially important nodes in p53 interaction networks in human cancers. This study shows that while TP53-truncating mutations often result in decreased TP53 expression, other non-truncating TP53 mutations result in increased TP53 expression in some cancers. Survival analyses in a number of cancers show that patients with TP53 mutations are more likely to have worse prognoses than TP53-wildtype patients, and that elevated TP53 expression often leads to poor clinical outcomes. We identified a set of candidate synthetic lethal (SL) genes for TP53, and validated some of these SL interactions using data from the Cancer Cell Line Project. These predicted SL genes are promising candidates for experimental validation and the development of personalized therapeutics for patients with TP53-mutated cancers.

Systemic analysis of genome-wide expression profiles identified potential therapeutic targets of demethylation drugs for glioblastoma.

PubMed

Ning, Tongbo; Cui, Hao; Sun, Feng; Zou, Jidian

2017-09-05

Glioblastoma represents one of the most aggressive malignant brain tumors with high morbidity and motility. Demethylation drugs have been developed for its treatment with little efficacy has been observed. The purpose of this study was to screen therapeutic targets of demethylation drugs or bioactive molecules for glioblastoma through systemic bioinformatics analysis. We firstly downloaded genome-wide expression profiles from the Gene Expression Omnibus (GEO) and conducted the primary analysis through R software, mainly including preprocessing of raw microarray data, transformation between probe ID and gene symbol and identification of differential expression genes (DEGs). Secondly, functional enrichment analysis was conducted via the Database for Annotation, Visualization and Integrated Discovery (DAVID) to explore biological processes involved in the development of glioblastoma. Thirdly, we constructed protein-protein interaction (PPI) network of interested genes and conducted cross analysis for multi datasets to obtain potential therapeutic targets for glioblastoma. Finally, we further confirmed the therapeutic targets through real-time RT-PCR. As a result, biological processes that related to cancer development, amino metabolism, immune response and etc. were found to be significantly enriched in genes that differential expression in glioblastoma and regulated by 5'aza-dC. Besides, network and cross analysis identified ACAT2, UFC1 and CYB5R1 as novel therapeutic targets of demethylation drugs which also confirmed by real time RT-PCR. In conclusions, our study identified several biological processes and genes that involved in the development of glioblastoma and regulated by 5'aza-dC, which would be helpful for the treatment of glioblastoma. Copyright © 2017 Elsevier B.V. All rights reserved.

Gene copy number evolution during tetraploid cotton radiation.

PubMed

Rong, J; Feltus, F A; Liu, L; Lin, L; Paterson, A H

2010-11-01

After polyploid formation, retention or loss of duplicated genes is not random. Genes with some functional domains are convergently restored to 'singleton' state after many independent genome duplications, and have been referred to as 'duplication-resistant' (DR) genes. To further explore the timeframe for their restoration to the singleton state, 27 cotton homologs of genes found to be 'DR' in Arabidopsis were selected based on diagnostic Pfam domains. Their copy numbers were studied using southern hybridization and sequence analysis in five tetraploid species and their ancestral A and D genome diploids. DR genes had significantly lower copy number than gene families hybridizing to randomly selected cotton ESTs. Three DR genes showed complete loss of D genome-derived homoeologs in some or all tetraploid species. Prior analysis has shown gene loss in polyploid cotton to be rare, and herein only one randomly selected gene showed loss of a homoeolog in only one of the five tetraploid species (Gossypium mustelinum). BAC sequencing confirmed two cases of gene loss in tetraploid cotton. Divergence among 5' sequences of DR genes amplified from G. arboreum, G. raimondii, and Gossypioides kirkii was correlated with gene copy number. These results show that genes containing Pfam domains associated with duplication resistance in Arabidopsis have also been preferentially restored to low copy number after a more recent polyploidization event in cotton. In tetraploid cotton, genes from the progenitor D genome seem to experience more gene copy number divergence than genes from the A genome. Together with D subgenome-biased alterations in gene expression, perhaps gene loss may contribute to the relatively larger portion of quantitative trait variation attributable to D than A subgenome chromosomes of tetraploid cotton.

MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers

PubMed Central

Allot, Alexis; Chennen, Kirsley; Nevers, Yannis; Poidevin, Laetitia; Kress, Arnaud; Ripp, Raymond; Thompson, Julie Dawn; Poch, Olivier

2017-01-01

Background The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. Objective MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. Methods MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. Results MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user’s specific interests and provides an efficient way to share information with collaborators. Furthermore, the user’s behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. Conclusions We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. PMID:28623182

Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2014-01-01

Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. This study illustrates that we can improve detection power and discovery consistency through a concordant integrative analysis of multiple large-scale two-sample gene expression data sets.

A method for gene-based pathway analysis using genomewide association study summary statistics reveals nine new type 1 diabetes associations.

PubMed

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

2014-12-01

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 (P=9.85×10-11) with 12 of the 22 SNPs showing P<0.05. Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, P=7.86×10-9), NRP1 (rs722988, 4.88×10-8), BAD (rs694739, 2.37×10-7), CTSB (rs1296023, 2.79×10-7), FYN (rs11964650, P=5.60×10-7), UBE2G1 (rs9906760, 5.08×10-7), MAP3K14 (rs17759555, 9.67×10-7), ITGB1 (rs1557150, 1.93×10-6), and IL7R (rs1445898, 2.76×10-6). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available. © 2014 The Authors. ** Genetic Epidemiology published by Wiley Periodicals, Inc.

Exploring the molecular mechanisms of Traditional Chinese Medicine components using gene expression signatures and connectivity map.

PubMed

Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kim, Jihye; Kang, Jaewoo; Tan, Aik Choon

2018-04-04

Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the "multi-component, multi-target" nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map. We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource. We performed systematic data mining and analysis on the mechanism of action (MoA) of these TCM components based on the CMap results. We clustered the 102 TCM components into four groups based on their MoAs using next generation CMap resource. We performed gene set enrichment analysis on these components to provide additional supports for explaining these molecular mechanisms. We also provided literature evidence to validate the MoAs identified through this bioinformatics analysis. Finally, we developed the Traditional Chinese Medicine Drug Repurposing Hub (TCM Hub) - a connectivity map resource to facilitate the elucidation of TCM MoA for drug repurposing research. TCMHub is freely available in http://tanlab.ucdenver.edu/TCMHub. Molecular mechanisms of TCM could be uncovered by using gene expression signatures and connectivity map. Through this analysis, we identified many of the TCM components possess diverse MoAs, this may explain the applications of TCM in treating various symptoms and diseases. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Extending bicluster analysis to annotate unclassified ORFs and predict novel functional modules using expression data

PubMed Central

Bryan, Kenneth; Cunningham, Pádraig

2008-01-01

Background Microarrays have the capacity to measure the expressions of thousands of genes in parallel over many experimental samples. The unsupervised classification technique of bicluster analysis has been employed previously to uncover gene expression correlations over subsets of samples with the aim of providing a more accurate model of the natural gene functional classes. This approach also has the potential to aid functional annotation of unclassified open reading frames (ORFs). Until now this aspect of biclustering has been under-explored. In this work we illustrate how bicluster analysis may be extended into a 'semi-supervised' ORF annotation approach referred to as BALBOA. Results The efficacy of the BALBOA ORF classification technique is first assessed via cross validation and compared to a multi-class k-Nearest Neighbour (kNN) benchmark across three independent gene expression datasets. BALBOA is then used to assign putative functional annotations to unclassified yeast ORFs. These predictions are evaluated using existing experimental and protein sequence information. Lastly, we employ a related semi-supervised method to predict the presence of novel functional modules within yeast. Conclusion In this paper we demonstrate how unsupervised classification methods, such as bicluster analysis, may be extended using of available annotations to form semi-supervised approaches within the gene expression analysis domain. We show that such methods have the potential to improve upon supervised approaches and shed new light on the functions of unclassified ORFs and their co-regulation. PMID:18831786

Gene and Metabolite Regulatory Network Analysis of Early Developing Fruit Tissues Highlights New Candidate Genes for the Control of Tomato Fruit Composition and Development1[C][W][OA

PubMed Central

Mounet, Fabien; Moing, Annick; Garcia, Virginie; Petit, Johann; Maucourt, Michael; Deborde, Catherine; Bernillon, Stéphane; Le Gall, Gwénaëlle; Colquhoun, Ian; Defernez, Marianne; Giraudel, Jean-Luc; Rolin, Dominique; Rothan, Christophe; Lemaire-Chamley, Martine

2009-01-01

Variations in early fruit development and composition may have major impacts on the taste and the overall quality of ripe tomato (Solanum lycopersicum) fruit. To get insights into the networks involved in these coordinated processes and to identify key regulatory genes, we explored the transcriptional and metabolic changes in expanding tomato fruit tissues using multivariate analysis and gene-metabolite correlation networks. To this end, we demonstrated and took advantage of the existence of clear structural and compositional differences between expanding mesocarp and locular tissue during fruit development (12–35 d postanthesis). Transcriptome and metabolome analyses were carried out with tomato microarrays and analytical methods including proton nuclear magnetic resonance and liquid chromatography-mass spectrometry, respectively. Pairwise comparisons of metabolite contents and gene expression profiles detected up to 37 direct gene-metabolite correlations involving regulatory genes (e.g. the correlations between glutamine, bZIP, and MYB transcription factors). Correlation network analyses revealed the existence of major hub genes correlated with 10 or more regulatory transcripts and embedded in a large regulatory network. This approach proved to be a valuable strategy for identifying specific subsets of genes implicated in key processes of fruit development and metabolism, which are therefore potential targets for genetic improvement of tomato fruit quality. PMID:19144766

Genome-wide evolutionary characterization and expression analyses of WRKY family genes in Brachypodium distachyon.

PubMed

Wen, Feng; Zhu, Hong; Li, Peng; Jiang, Min; Mao, Wenqing; Ong, Chermaine; Chu, Zhaoqing

2014-06-01

Members of plant WRKY gene family are ancient transcription factors that function in plant growth and development and respond to biotic and abiotic stresses. In our present study, we have investigated WRKY family genes in Brachypodium distachyon, a new model plant of family Poaceae. We identified a total of 86 WRKY genes from B. distachyon and explored their chromosomal distribution and evolution, domain alignment, promoter cis-elements, and expression profiles. Combining the analysis of phylogenetic tree of BdWRKY genes and the result of expression profiling, results showed that most of clustered gene pairs had higher similarities in the WRKY domain, suggesting that they might be functionally redundant. Neighbour-joining analysis of 301 WRKY domains from Oryza sativa, Arabidopsis thaliana, and B. distachyon suggested that BdWRKY domains are evolutionarily more closely related to O. sativa WRKY domains than those of A. thaliana. Moreover, tissue-specific expression profile of BdWRKY genes and their responses to phytohormones and several biotic or abiotic stresses were analysed by quantitative real-time PCR. The results showed that the expression of BdWRKY genes was rapidly regulated by stresses and phytohormones, and there was a strong correlation between promoter cis-elements and the phytohormones-induced BdWRKY gene expression. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Discovering genetic variants in Crohn's disease by exploring genomic regions enriched of weak association signals.

PubMed

D'Addabbo, Annarita; Palmieri, Orazio; Maglietta, Rosalia; Latiano, Anna; Mukherjee, Sayan; Annese, Vito; Ancona, Nicola

2011-08-01

A meta-analysis has re-analysed previous genome-wide association scanning definitively confirming eleven genes and further identifying 21 new loci. However, the identified genes/loci still explain only the minority of genetic predisposition of Crohn's disease. To identify genes weakly involved in disease predisposition by analysing chromosomal regions enriched of single nucleotide polymorphisms with modest statistical association. We utilized the WTCCC data set evaluating 1748 CD and 2938 controls. The identification of candidate genes/loci was performed by a two-step procedure: first of all chromosomal regions enriched of weak association signals were localized; subsequently, weak signals clustered in gene regions were identified. The statistical significance was assessed by non parametric permutation tests. The cytoband enrichment analysis highlighted 44 regions (P≤0.05) enriched with single nucleotide polymorphisms significantly associated with the trait including 23 out of 31 previously confirmed and replicated genes. Importantly, we highlight further 20 novel chromosomal regions carrying approximately one hundred genes/loci with modest association. Amongst these we find compelling functional candidate genes such as MAPT, GRB2 and CREM, LCT, and IL12RB2. Our study suggests a different statistical perspective to discover genes weakly associated with a given trait, although further confirmatory functional studies are needed. Copyright © 2011 Editrice Gastroenterologica Italiana S.r.l. All rights reserved.

Computational analysis of TRAPPC9: candidate gene for autosomal recessive non-syndromic mental retardation.

PubMed

Khattak, Naureen Aslam; Mir, Asif

2014-01-01

Mental retardation (MR)/ intellectual disability (ID) is a neuro-developmental disorder characterized by a low intellectual quotient (IQ) and deficits in adaptive behavior related to everyday life tasks such as delayed language acquisition, social skills or self-help skills with onset before age 18. To date, a few genes (PRSS12, CRBN, CC2D1A, GRIK2, TUSC3, TRAPPC9, TECR, ST3GAL3, MED23, MAN1B1, NSUN1) for autosomal-recessive forms of non syndromic MR (NS-ARMR) have been identified and established in various families with ID. The recently reported candidate gene TRAPPC9 was selected for computational analysis to explore its potentially important role in pathology as it is the only gene for ID reported in more than five different familial cases worldwide. YASARA (12.4.1) was utilized to generate three dimensional structures of the candidate gene TRAPPC9. Hybrid structure prediction was employed. Crystal Structure of a Conserved Metalloprotein From Bacillus Cereus (3D19-C) was selected as best suitable template using position-specific iteration-BLAST. Template (3D19-C) parameters were based on E-value, Z-score and resolution and quality score of 0.32, -1.152, 2.30°A and 0.684 respectively. Model reliability showed 93.1% residues placed in the most favored region with 96.684 quality factor, and overall 0.20 G-factor (dihedrals 0.06 and covalent 0.39 respectively). Protein-Protein docking analysis demonstrated that TRAPPC9 showed strong interactions of the amino acid residues S(253), S(251), Y(256), G(243), D(131) with R(105), Q(425), W(226), N(255), S(233), its functional partner 1KBKB. Protein-protein interacting residues could facilitate the exploration of structural and functional outcomes of wild type and mutated TRAPCC9 protein. Actively involved residues can be used to elucidate the binding properties of the protein, and to develop drug therapy for NS-ARMR patients.

Identifying key genes, pathways and screening therapeutic agents for manganese-induced Alzheimer disease using bioinformatics analysis.

PubMed

Ling, JunJun; Yang, Shengyou; Huang, Yi; Wei, Dongfeng; Cheng, Weidong

2018-06-01

Alzheimer disease (AD) is a progressive neurodegenerative disease, the etiology of which remains largely unknown. Accumulating evidence indicates that elevated manganese (Mn) in brain exerts toxic effects on neurons and contributes to AD development. Thus, we aimed to explore the gene and pathway variations through analysis of high through-put data in this process.To screen the differentially expressed genes (DEGs) that may play critical roles in Mn-induced AD, public microarray data regarding Mn-treated neurocytes versus controls (GSE70845), and AD versus controls (GSE48350), were downloaded and the DEGs were screened out, respectively. The intersection of the DEGs of each datasets was obtained by using Venn analysis. Then, gene ontology (GO) function analysis and KEGG pathway analysis were carried out. For screening hub genes, protein-protein interaction network was constructed. At last, DEGs were analyzed in Connectivity Map (CMAP) for identification of small molecules that overcome Mn-induced neurotoxicity or AD development.The intersection of the DEGs obtained 140 upregulated and 267 downregulated genes. The top 5 items of biological processes of GO analysis were taxis, chemotaxis, cell-cell signaling, regulation of cellular physiological process, and response to wounding. The top 5 items of KEGG pathway analysis were cytokine-cytokine receptor interaction, apoptosis, oxidative phosphorylation, Toll-like receptor signaling pathway, and insulin signaling pathway. Afterwards, several hub genes such as INSR, VEGFA, PRKACB, DLG4, and BCL2 that might play key roles in Mn-induced AD were further screened out. Interestingly, tyrphostin AG-825, an inhibitor of tyrosine phosphorylation, was predicted to be a potential agent for overcoming Mn-induced neurotoxicity or AD development.The present study provided a novel insight into the molecular mechanisms of Mn-induced neurotoxicity or AD development and screened out several small molecular candidates that might be critical for Mn neurotoxicity prevention and Mn-induced AD treatment.

Transcriptomics Analysis on Excellent Meat Quality Traits of Skeletal Muscles of the Chinese Indigenous Min Pig Compared with the Large White Breed

PubMed Central

Liu, Yingzi; Yang, Xiuqin; Jing, Xiaoyan; He, Xinmiao; Wang, Liang; Liu, Yang; Liu, Di

2017-01-01

The Min pig (Sus scrofa) is a well-known indigenous breed in China. One of its main advantages over European breeds is its high meat quality. Additionally, different cuts of pig also show some different traits of meat quality. To explore the underlying mechanism responsible for the differences of meat quality between different breeds or cuts, the longissimus dorsi muscle (LM) and the biceps femoris muscle (BF) from Min and Large White pigs were investigated using transcriptome analysis. The gene expression profiling identified 1371 differentially expressed genes (DEGs) between LM muscles from Min and Large White pigs, and 114 DEGs between LM and BF muscles from the same Min pigs. Gene Ontology (GO) enrichment of biological functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the gene products were mainly involved in the IRS1/Akt/FoxO1 signaling pathway, adenosine 5′-monophosphate-activated protein kinase (AMPK) cascade effects, lipid metabolism and amino acid metabolism pathway. Such pathways contributed to fatty acid metabolism, intramuscular fat deposition, and skeletal muscle growth in Min pig. These results give an insight into the mechanisms underlying the formation of skeletal muscle and provide candidate genes for improving meat quality. It will contribute to improving meat quality of pigs through molecular breeding. PMID:29271915

Heterogenic expression of genes encoding secreted proteins at the periphery of Aspergillus niger colonies.

PubMed

Vinck, Arman; de Bekker, Charissa; Ossin, Adam; Ohm, Robin A; de Vries, Ronald P; Wösten, Han A B

2011-01-01

Colonization of a substrate by fungi starts with the invasion of exploring hyphae. These hyphae secrete enzymes that degrade the organic material into small molecules that can be taken up by the fungus to serve as nutrients. We previously showed that only part of the exploring hyphae of Aspergillus niger highly express the glucoamylase gene glaA. This was an unexpected finding since all exploring hyphae are exposed to the same environmental conditions. Using GFP as a reporter, we here demonstrate that the acid amylase gene aamA, the α-glucuronidase gene aguA, and the feruloyl esterase gene faeA of A. niger are also subject to heterogenic expression within the exploring mycelium. Coexpression studies using GFP and dTomato as reporters showed that hyphae that highly express one of these genes also highly express the other genes encoding secreted proteins. Moreover, these hyphae also highly express the amylolytic regulatory gene amyR, and the glyceraldehyde-3-phosphate dehydrogenase gene gpdA. In situ hybridization demonstrated that the high expressers are characterized by a high 18S rRNA content. Taken together, it is concluded that two subpopulations of hyphae can be distinguished within the exploring mycelium of A. niger. The experimental data indicate that these subpopulations differ in their transcriptional and translational activity. © 2010 Society for Applied Microbiology and Blackwell Publishing Ltd.

Transcriptome Sequencing of Dianthus spiculifolius and Analysis of the Genes Involved in Responses to Combined Cold and Drought Stress.

PubMed

Zhou, Aimin; Ma, Hongping; Liu, Enhui; Jiang, Tongtong; Feng, Shuang; Gong, Shufang; Wang, Jingang

2017-04-17

Dianthus spiculifolius , a perennial herbaceous flower and a member of the Caryophyllaceae family, has strong resistance to cold and drought stresses. To explore the transcriptional responses of D. spiculifolius to individual and combined stresses, we performed transcriptome sequencing of seedlings under normal conditions or subjected to cold treatment (CT), simulated drought treatment (DT), or their combination (CTDT). After de novo assembly of the obtained reads, 112,015 unigenes were generated. Analysis of differentially expressed genes (DEGs) showed that 2026, 940, and 2346 genes were up-regulated and 1468, 707, and 1759 were down-regulated in CT, DT, and CTDT samples, respectively. Among all the DEGs, 182 up-regulated and 116 down-regulated genes were identified in all the treatment groups. Analysis of metabolic pathways and regulatory networks associated with the DEGs revealed overlaps and cross-talk between cold and drought stress response pathways. The expression profiles of the selected DEGs in CT, DT, and CTDT samples were characterized and confirmed by quantitative RT-PCR. These DEGs and metabolic pathways may play important roles in the response of D. spiculifolius to the combined stress. Functional characterization of these genes and pathways will provide new targets for enhancement of plant stress tolerance through genetic manipulation.

Transcriptome Sequencing of Dianthus spiculifolius and Analysis of the Genes Involved in Responses to Combined Cold and Drought Stress

PubMed Central

Zhou, Aimin; Ma, Hongping; Liu, Enhui; Jiang, Tongtong; Feng, Shuang; Gong, Shufang; Wang, Jingang

2017-01-01

Dianthus spiculifolius, a perennial herbaceous flower and a member of the Caryophyllaceae family, has strong resistance to cold and drought stresses. To explore the transcriptional responses of D. spiculifolius to individual and combined stresses, we performed transcriptome sequencing of seedlings under normal conditions or subjected to cold treatment (CT), simulated drought treatment (DT), or their combination (CTDT). After de novo assembly of the obtained reads, 112,015 unigenes were generated. Analysis of differentially expressed genes (DEGs) showed that 2026, 940, and 2346 genes were up-regulated and 1468, 707, and 1759 were down-regulated in CT, DT, and CTDT samples, respectively. Among all the DEGs, 182 up-regulated and 116 down-regulated genes were identified in all the treatment groups. Analysis of metabolic pathways and regulatory networks associated with the DEGs revealed overlaps and cross-talk between cold and drought stress response pathways. The expression profiles of the selected DEGs in CT, DT, and CTDT samples were characterized and confirmed by quantitative RT-PCR. These DEGs and metabolic pathways may play important roles in the response of D. spiculifolius to the combined stress. Functional characterization of these genes and pathways will provide new targets for enhancement of plant stress tolerance through genetic manipulation. PMID:28420173

Transcriptome analysis of thermogenic Arum concinnatum reveals the molecular components of floral scent production

PubMed Central

Onda, Yoshihiko; Mochida, Keiichi; Yoshida, Takuhiro; Sakurai, Tetsuya; Seymour, Roger S.; Umekawa, Yui; Pirintsos, Stergios Arg; Shinozaki, Kazuo; Ito, Kikukatsu

2015-01-01

Several plant species can generate enough heat to increase their internal floral temperature above ambient temperature. Among thermogenic plants, Arum concinnatum shows the highest respiration activity during thermogenesis. However, an overall understanding of the genes related to plant thermogenesis has not yet been achieved. In this study, we performed de novo transcriptome analysis of flower organs in A. concinnatum. The de novo transcriptome assembly represented, in total, 158,490 non-redundant transcripts, and 53,315 of those showed significant homology with known genes. To explore genes associated with thermogenesis, we filtered 1266 transcripts that showed a significant correlation between expression pattern and the temperature trend of each sample. We confirmed five putative alternative oxidase transcripts were included in filtered transcripts as expected. An enrichment analysis of the Gene Ontology terms for the filtered transcripts suggested over-representation of genes involved in 1-deoxy-d-xylulose-5-phosphate synthase (DXS) activity. The expression profiles of DXS transcripts in the methyl-d-erythritol 4-phosphate (MEP) pathway were significantly correlated with thermogenic levels. Our results suggest that the MEP pathway is the main biosynthesis route for producing scent monoterpenes. To our knowledge, this is the first report describing the candidate pathway and the key enzyme for floral scent production in thermogenic plants. PMID:25736477

Comparative Transcriptomes Analysis of Red- and White-Fleshed Apples in an F1 Population of Malus sieversii f. niedzwetzkyana Crossed with M. domestica ‘Fuji’

PubMed Central

Wang, Nan; Zheng, Yi; Duan, Naibin; Zhang, Zongying; Ji, Xiaohao; Jiang, Shenghui; Sun, Shasha; Yang, Long; Bai, Yang; Fei, Zhangjun; Chen, Xuesen

2015-01-01

Transcriptome profiles of the red- and white-fleshed apples in an F1 segregating population of Malus sieversii f.Niedzwetzkyana and M.domestica ‘Fuji’ were generated using the next-generation high-throughput RNA sequencing (RNA-Seq) technology and compared. A total of 114 differentially expressed genes (DEGs) were obtained, of which 88 were up-regulated and 26 were down-regulated in red-fleshed apples. The 88 up-regulated genes were enriched with those related to flavonoid biosynthetic process and stress responses. Further analysis identified 22 genes associated with flavonoid biosynthetic process and 68 genes that may be related to stress responses. Furthermore, the expression of 20 up-regulated candidate genes (10 related to flavonoid biosynthesis, two encoding MYB transcription factors and eight related to stress responses) and 10 down-regulated genes were validated by quantitative real-time PCR. After exploring the possible regulatory network, we speculated that flavonoid metabolism might be involved in stress responses in red-fleshed apple. Our findings provide a theoretical basis for further enriching gene resources associated with flavonoid synthesis and stress responses of fruit trees and for breeding elite apples with high flavonoid content and/or increased stress tolerances. PMID:26207813

Modulation of yeast genome expression in response to defective RNA polymerase III-dependent transcription.

PubMed

Conesa, Christine; Ruotolo, Roberta; Soularue, Pascal; Simms, Tiffany A; Donze, David; Sentenac, André; Dieci, Giorgio

2005-10-01

We used genome-wide expression analysis in Saccharomyces cerevisiae to explore whether and how the expression of protein-coding, RNA polymerase (Pol) II-transcribed genes is influenced by a decrease in RNA Pol III-dependent transcription. The Pol II transcriptome was characterized in four thermosensitive, slow-growth mutants affected in different components of the RNA Pol III transcription machinery. Unexpectedly, we found only a modest correlation between altered expression of Pol II-transcribed genes and their proximity to class III genes, a result also confirmed by the analysis of single tRNA gene deletants. Instead, the transcriptome of all of the four mutants was characterized by increased expression of genes known to be under the control of the Gcn4p transcriptional activator. Indeed, GCN4 was found to be translationally induced in the mutants, and deleting the GCN4 gene eliminated the response. The Gcn4p-dependent expression changes did not require the Gcn2 protein kinase and could be specifically counteracted by an increased gene dosage of initiator tRNA(Met). Initiator tRNA(Met) depletion thus triggers a GCN4-dependent reprogramming of genome expression in response to decreased Pol III transcription. Such an effect might represent a key element in the coordinated transcriptional response of yeast cells to environmental changes.

Genome-Based Genetic Tool Development for Bacillus methanolicus: Theta- and Rolling Circle-Replicating Plasmids for Inducible Gene Expression and Application to Methanol-Based Cadaverine Production.

PubMed

Irla, Marta; Heggeset, Tonje M B; Nærdal, Ingemar; Paul, Lidia; Haugen, Tone; Le, Simone B; Brautaset, Trygve; Wendisch, Volker F

2016-01-01

Bacillus methanolicus is a thermophilic methylotroph able to overproduce amino acids from methanol, a substrate not used for human or animal nutrition. Based on our previous RNA-seq analysis a mannitol inducible promoter and a putative mannitol activator gene mtlR were identified. The mannitol inducible promoter was applied for controlled gene expression using fluorescent reporter proteins and a flow cytometry analysis, and improved by changing the -35 promoter region and by co-expression of the mtlR regulator gene. For independent complementary gene expression control, the heterologous xylose-inducible system from B. megaterium was employed and a two-plasmid gene expression system was developed. Four different replicons for expression vectors were compared with respect to their copy number and stability. As an application example, methanol-based production of cadaverine was shown to be improved from 11.3 to 17.5 g/L when a heterologous lysine decarboxylase gene cadA was expressed from a theta-replicating rather than a rolling-circle replicating vector. The current work on inducible promoter systems and compatible theta- or rolling circle-replicating vectors is an important extension of the poorly developed B. methanolicus genetic toolbox, valuable for genetic engineering and further exploration of this bacterium.

Genome-Based Genetic Tool Development for Bacillus methanolicus: Theta- and Rolling Circle-Replicating Plasmids for Inducible Gene Expression and Application to Methanol-Based Cadaverine Production

PubMed Central

Irla, Marta; Heggeset, Tonje M. B.; Nærdal, Ingemar; Paul, Lidia; Haugen, Tone; Le, Simone B.; Brautaset, Trygve; Wendisch, Volker F.

2016-01-01

Bacillus methanolicus is a thermophilic methylotroph able to overproduce amino acids from methanol, a substrate not used for human or animal nutrition. Based on our previous RNA-seq analysis a mannitol inducible promoter and a putative mannitol activator gene mtlR were identified. The mannitol inducible promoter was applied for controlled gene expression using fluorescent reporter proteins and a flow cytometry analysis, and improved by changing the -35 promoter region and by co-expression of the mtlR regulator gene. For independent complementary gene expression control, the heterologous xylose-inducible system from B. megaterium was employed and a two-plasmid gene expression system was developed. Four different replicons for expression vectors were compared with respect to their copy number and stability. As an application example, methanol-based production of cadaverine was shown to be improved from 11.3 to 17.5 g/L when a heterologous lysine decarboxylase gene cadA was expressed from a theta-replicating rather than a rolling-circle replicating vector. The current work on inducible promoter systems and compatible theta- or rolling circle-replicating vectors is an important extension of the poorly developed B. methanolicus genetic toolbox, valuable for genetic engineering and further exploration of this bacterium. PMID:27713731

Comparative Transcriptomes Analysis of Red- and White-Fleshed Apples in an F1 Population of Malus sieversii f. niedzwetzkyana Crossed with M. domestica 'Fuji'.

PubMed

Wang, Nan; Zheng, Yi; Duan, Naibin; Zhang, Zongying; Ji, Xiaohao; Jiang, Shenghui; Sun, Shasha; Yang, Long; Bai, Yang; Fei, Zhangjun; Chen, Xuesen

2015-01-01

Transcriptome profiles of the red- and white-fleshed apples in an F1 segregating population of Malus sieversii f.Niedzwetzkyana and M.domestica 'Fuji' were generated using the next-generation high-throughput RNA sequencing (RNA-Seq) technology and compared. A total of 114 differentially expressed genes (DEGs) were obtained, of which 88 were up-regulated and 26 were down-regulated in red-fleshed apples. The 88 up-regulated genes were enriched with those related to flavonoid biosynthetic process and stress responses. Further analysis identified 22 genes associated with flavonoid biosynthetic process and 68 genes that may be related to stress responses. Furthermore, the expression of 20 up-regulated candidate genes (10 related to flavonoid biosynthesis, two encoding MYB transcription factors and eight related to stress responses) and 10 down-regulated genes were validated by quantitative real-time PCR. After exploring the possible regulatory network, we speculated that flavonoid metabolism might be involved in stress responses in red-fleshed apple. Our findings provide a theoretical basis for further enriching gene resources associated with flavonoid synthesis and stress responses of fruit trees and for breeding elite apples with high flavonoid content and/or increased stress tolerances.

RNA-Seq reveals seven promising candidate genes affecting the proportion of thick egg albumen in layer-type chickens.

PubMed

Wan, Yi; Jin, Sihua; Ma, Chendong; Wang, Zhicheng; Fang, Qi; Jiang, Runshen

2017-12-22

Eggs with a much higher proportion of thick albumen are preferred in the layer industry, as they are favoured by consumers. However, the genetic factors affecting the thick egg albumen trait have not been elucidated. Using RNA sequencing, we explored the magnum transcriptome in 9 Rhode Island white layers: four layers with phenotypes of extremely high ratios of thick to thin albumen (high thick albumen, HTA) and five with extremely low ratios (low thick albumen, LTA). A total of 220 genes were differentially expressed, among which 150 genes were up-regulated and 70 were down-regulated in the HTA group compared with the LTA group. Gene Ontology (GO) analysis revealed that the up-regulated genes in HTA were mainly involved in a wide range of regulatory functions. In addition, a large number of these genes were related to glycosphingolipid biosynthesis, focal adhesion, ECM-receptor interactions and cytokine-cytokine receptor interactions. Based on functional analysis, ST3GAL4, FUT4, ITGA2, SDC3, PRLR, CDH4 and GALNT9 were identified as promising candidate genes for thick albumen synthesis and metabolism during egg formation. These results provide new insights into the molecular mechanisms of egg albumen traits and may contribute to future breeding strategies that optimise the proportion of thick egg albumen.

Genome-Wide Identification and Comprehensive Expression Profiling of Ribosomal Protein Small Subunit (RPS) Genes and their Comparative Analysis with the Large Subunit (RPL) Genes in Rice

PubMed Central

Saha, Anusree; Das, Shubhajit; Moin, Mazahar; Dutta, Mouboni; Bakshi, Achala; Madhav, M. S.; Kirti, P. B.

2017-01-01

Ribosomal proteins (RPs) are indispensable in ribosome biogenesis and protein synthesis, and play a crucial role in diverse developmental processes. Our previous studies on Ribosomal Protein Large subunit (RPL) genes provided insights into their stress responsive roles in rice. In the present study, we have explored the developmental and stress regulated expression patterns of Ribosomal Protein Small (RPS) subunit genes for their differential expression in a spatiotemporal and stress dependent manner. We have also performed an in silico analysis of gene structure, cis-elements in upstream regulatory regions, protein properties and phylogeny. Expression studies of the 34 RPS genes in 13 different tissues of rice covering major growth and developmental stages revealed that their expression was substantially elevated, mostly in shoots and leaves indicating their possible involvement in the development of vegetative organs. The majority of the RPS genes have manifested significant expression under all abiotic stress treatments with ABA, PEG, NaCl, and H2O2. Infection with important rice pathogens, Xanthomonas oryzae pv. oryzae (Xoo) and Rhizoctonia solani also induced the up-regulation of several of the RPS genes. RPS4, 13a, 18a, and 4a have shown higher transcript levels under all the abiotic stresses, whereas, RPS4 is up-regulated in both the biotic stress treatments. The information obtained from the present investigation would be useful in appreciating the possible stress-regulatory attributes of the genes coding for rice ribosomal small subunit proteins apart from their functions as house-keeping proteins. A detailed functional analysis of independent genes is required to study their roles in stress tolerance and generating stress- tolerant crops. PMID:28966624

A Transcriptional Signature of Fatigue Derived from Patients with Primary Sjögren's Syndrome.

PubMed

James, Katherine; Al-Ali, Shereen; Tarn, Jessica; Cockell, Simon J; Gillespie, Colin S; Hindmarsh, Victoria; Locke, James; Mitchell, Sheryl; Lendrem, Dennis; Bowman, Simon; Price, Elizabeth; Pease, Colin T; Emery, Paul; Lanyon, Peter; Hunter, John A; Gupta, Monica; Bombardieri, Michele; Sutcliffe, Nurhan; Pitzalis, Costantino; McLaren, John; Cooper, Annie; Regan, Marian; Giles, Ian; Isenberg, David; Saravanan, Vadivelu; Coady, David; Dasgupta, Bhaskar; McHugh, Neil; Young-Min, Steven; Moots, Robert; Gendi, Nagui; Akil, Mohammed; Griffiths, Bridget; Wipat, Anil; Newton, Julia; Jones, David E; Isaacs, John; Hallinan, Jennifer; Ng, Wan-Fai

2015-01-01

Fatigue is a debilitating condition with a significant impact on patients' quality of life. Fatigue is frequently reported by patients suffering from primary Sjögren's Syndrome (pSS), a chronic autoimmune condition characterised by dryness of the eyes and the mouth. However, although fatigue is common in pSS, it does not manifest in all sufferers, providing an excellent model with which to explore the potential underpinning biological mechanisms. Whole blood samples from 133 fully-phenotyped pSS patients stratified for the presence of fatigue, collected by the UK primary Sjögren's Syndrome Registry, were used for whole genome microarray. The resulting data were analysed both on a gene by gene basis and using pre-defined groups of genes. Finally, gene set enrichment analysis (GSEA) was used as a feature selection technique for input into a support vector machine (SVM) classifier. Classification was assessed using area under curve (AUC) of receiver operator characteristic and standard error of Wilcoxon statistic, SE(W). Although no genes were individually found to be associated with fatigue, 19 metabolic pathways were enriched in the high fatigue patient group using GSEA. Analysis revealed that these enrichments arose from the presence of a subset of 55 genes. A radial kernel SVM classifier with this subset of genes as input displayed significantly improved performance over classifiers using all pathway genes as input. The classifiers had AUCs of 0.866 (SE(W) 0.002) and 0.525 (SE(W) 0.006), respectively. Systematic analysis of gene expression data from pSS patients discordant for fatigue identified 55 genes which are predictive of fatigue level using SVM classification. This list represents the first step in understanding the underlying pathophysiological mechanisms of fatigue in patients with pSS.

Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma

PubMed Central

Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

2014-01-01

Background Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. Principal Findings In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Conclusions Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers. PMID:24988079

Integrated analysis of mutation data from various sources identifies key genes and signaling pathways in hepatocellular carcinoma.

PubMed

Zhang, Yuannv; Qiu, Zhaoping; Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

2014-01-01

Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers.

RNA-Seq and Gene Network Analysis Uncover Activation of an ABA-Dependent Signalosome During the Cork Oak Root Response to Drought

PubMed Central

Magalhães, Alexandre P.; Verde, Nuno; Reis, Francisca; Martins, Inês; Costa, Daniela; Lino-Neto, Teresa; Castro, Pedro H.; Tavares, Rui M.; Azevedo, Herlânder

2016-01-01

Quercus suber (cork oak) is a West Mediterranean species of key economic interest, being extensively explored for its ability to generate cork. Like other Mediterranean plants, Q. suber is significantly threatened by climatic changes, imposing the need to quickly understand its physiological and molecular adaptability to drought stress imposition. In the present report, we uncovered the differential transcriptome of Q. suber roots exposed to long-term drought, using an RNA-Seq approach. 454-sequencing reads were used to de novo assemble a reference transcriptome, and mapping of reads allowed the identification of 546 differentially expressed unigenes. These were enriched in both effector genes (e.g., LEA, chaperones, transporters) as well as regulatory genes, including transcription factors (TFs) belonging to various different classes, and genes associated with protein turnover. To further extend functional characterization, we identified the orthologs of differentially expressed unigenes in the model species Arabidopsis thaliana, which then allowed us to perform in silico functional inference, including gene network analysis for protein function, protein subcellular localization and gene co-expression, and in silico enrichment analysis for TFs and cis-elements. Results indicated the existence of extensive transcriptional regulatory events, including activation of ABA-responsive genes and ABF-dependent signaling. We were then able to establish that a core ABA-signaling pathway involving PP2C-SnRK2-ABF components was induced in stressed Q. suber roots, identifying a key mechanism in this species’ response to drought. PMID:26793200

The Human EST Ontology Explorer: a tissue-oriented visualization system for ontologies distribution in human EST collections.

PubMed

Merelli, Ivan; Caprera, Andrea; Stella, Alessandra; Del Corvo, Marcello; Milanesi, Luciano; Lazzari, Barbara

2009-10-15

The NCBI dbEST currently contains more than eight million human Expressed Sequenced Tags (ESTs). This wide collection represents an important source of information for gene expression studies, provided it can be inspected according to biologically relevant criteria. EST data can be browsed using different dedicated web resources, which allow to investigate library specific gene expression levels and to make comparisons among libraries, highlighting significant differences in gene expression. Nonetheless, no tool is available to examine distributions of quantitative EST collections in Gene Ontology (GO) categories, nor to retrieve information concerning library-dependent EST involvement in metabolic pathways. In this work we present the Human EST Ontology Explorer (HEOE) http://www.itb.cnr.it/ptp/human_est_explorer, a web facility for comparison of expression levels among libraries from several healthy and diseased tissues. The HEOE provides library-dependent statistics on the distribution of sequences in the GO Direct Acyclic Graph (DAG) that can be browsed at each GO hierarchical level. The tool is based on large-scale BLAST annotation of EST sequences. Due to the huge number of input sequences, this BLAST analysis was performed with the aid of grid computing technology, which is particularly suitable to address data parallel task. Relying on the achieved annotation, library-specific distributions of ESTs in the GO Graph were inferred. A pathway-based search interface was also implemented, for a quick evaluation of the representation of libraries in metabolic pathways. EST processing steps were integrated in a semi-automatic procedure that relies on Perl scripts and stores results in a MySQL database. A PHP-based web interface offers the possibility to simultaneously visualize, retrieve and compare data from the different libraries. Statistically significant differences in GO categories among user selected libraries can also be computed. The HEOE provides an alternative and complementary way to inspect EST expression levels with respect to approaches currently offered by other resources. Furthermore, BLAST computation on the whole human EST dataset was a suitable test of grid scalability in the context of large-scale bioinformatics analysis. The HEOE currently comprises sequence analysis from 70 non-normalized libraries, representing a comprehensive overview on healthy and unhealthy tissues. As the analysis procedure can be easily applied to other libraries, the number of represented tissues is intended to increase.

Analysis of gene expression profile induced by EMP-1 in esophageal cancer cells using cDNA Microarray

PubMed Central

Wang, Hai-Tao; Kong, Jian-Ping; Ding, Fang; Wang, Xiu-Qin; Wang, Ming-Rong; Liu, Lian-Xin; Wu, Min; Liu, Zhi-Hua

2003-01-01

AIM: To obtain human esophageal cancer cell EC9706 stably expressed epithelial membrane protein-1 (EMP-1) with integrated eukaryotic plasmid harboring the open reading frame (ORF) of human EMP-1, and then to study the mechanism by which EMP-1 exerts its diverse cellular action on cell proliferation and altered gene profile by exploring the effect of EMP-1. METHODS: The authors first constructed pcDNA3.1/myc-his expression vector harboring the ORF of EMP-1 and then transfected it into human esophageal carcinoma cell line EC9706. The positive clones were analyzed by Western blot and RT-PCR. Moreover, the cell growth curve was observed and the cell cycle was checked by FACS technique. Using cDNA microarray technology, the authors compared the gene expression pattern in positive clones with control. To confirm the gene expression profile, semi-quantitative RT-PCR was carried out for 4 of the randomly picked differentially expressed genes. For those differentially expressed genes, classification was performed according to their function and cellular component. RESULTS: Human EMP-1 gene can be stably expressed in EC9706 cell line transfected with human EMP-1. The authors found the cell growth decreased, among which S phase was arrested and G1 phase was prolonged in the transfected positive clones. By cDNA microarray analysis, 35 genes showed an over 2.0 fold change in expression level after transfection, with 28 genes being consistently up-regulated and 7 genes being down-regulated. Among the classified genes, almost half of the induced genes (13 out of 28 genes) were related to cell signaling, cell communication and particularly to adhesion. CONCLUSION: Overexpression of human EMP-1 gene can inhibit the proliferation of EC9706 cell with S phase arrested and G1 phase prolonged. The cDNA microarray analysis suggested that EMP-1 may be one of regulators involved in cell signaling, cell communication and adhesion regulators. PMID:12632483

Analysis of gene expression profile induced by EMP-1 in esophageal cancer cells using cDNA Microarray.

PubMed

Wang, Hai-Tao; Kong, Jian-Ping; Ding, Fang; Wang, Xiu-Qin; Wang, Ming-Rong; Liu, Lian-Xin; Wu, Min; Liu, Zhi-Hua

2003-03-01

To obtain human esophageal cancer cell EC9706 stably expressed epithelial membrane protein-1 (EMP-1) with integrated eukaryotic plasmid harboring the open reading frame (ORF) of human EMP-1, and then to study the mechanism by which EMP-1 exerts its diverse cellular action on cell proliferation and altered gene profile by exploring the effect of EMP-1. The authors first constructed pcDNA3.1/myc-his expression vector harboring the ORF of EMP-1 and then transfected it into human esophageal carcinoma cell line EC9706. The positive clones were analyzed by Western blot and RT-PCR. Moreover, the cell growth curve was observed and the cell cycle was checked by FACS technique. Using cDNA microarray technology, the authors compared the gene expression pattern in positive clones with control. To confirm the gene expression profile, semi-quantitative RT-PCR was carried out for 4 of the randomly picked differentially expressed genes. For those differentially expressed genes, classification was performed according to their function and cellular component. Human EMP-1 gene can be stably expressed in EC9706 cell line transfected with human EMP-1. The authors found the cell growth decreased, among which S phase was arrested and G1 phase was prolonged in the transfected positive clones. By cDNA microarray analysis, 35 genes showed an over 2.0 fold change in expression level after transfection, with 28 genes being consistently up-regulated and 7 genes being down-regulated. Among the classified genes, almost half of the induced genes (13 out of 28 genes) were related to cell signaling, cell communication and particularly to adhesion. Overexpression of human EMP-1 gene can inhibit the proliferation of EC9706 cell with S phase arrested and G1 phase prolonged. The cDNA microarray analysis suggested that EMP-1 may be one of regulators involved in cell signaling, cell communication and adhesion regulators.

Clustering change patterns using Fourier transformation with time-course gene expression data.

PubMed

Kim, Jaehee

2011-01-01

To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a period of time because biologically related gene groups can share the same change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. This work is aimed at discovering gene groups with similar change patterns which share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. We applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns.

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.

Use of RNA-seq to identify cardiac genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy.

PubMed

Friedenberg, Steven G; Chdid, Lhoucine; Keene, Bruce; Sherry, Barbara; Motsinger-Reif, Alison; Meurs, Kathryn M

2016-07-01

OBJECTIVE To identify cardiac tissue genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy (DCM). ANIMALS 8 dogs with and 5 dogs without DCM. PROCEDURES Following euthanasia, samples of left ventricular myocardium were collected from each dog. Total RNA was extracted from tissue samples, and RNA sequencing was performed on each sample. Samples from dogs with and without DCM were grouped to identify genes that were differentially regulated between the 2 populations. Overrepresentation analysis was performed on upregulated and downregulated gene sets to identify altered molecular pathways in dogs with DCM. RESULTS Genes involved in cellular energy metabolism, especially metabolism of carbohydrates and fats, were significantly downregulated in dogs with DCM. Expression of cardiac structural proteins was also altered in affected dogs. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that RNA sequencing may provide important insights into the pathogenesis of DCM in dogs and highlight pathways that should be explored to identify causative mutations and develop novel therapeutic interventions.

Naked gene therapy of hepatocyte growth factor for dextran sulfate sodium-induced colitis in mice

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

Kanbe, Takamasa; Murai, Rie; Mukoyama, Tomoyuki

Ulcerative colitis (UC) is progressive and relapsing disease. To explore the therapeutic effects of naked gene therapy of hepatocyte growth factor (HGF) on UC, the SR{alpha} promoter driving HGF gene was intrarectally administered to the mice in which colitis was induced by dextran sulfate sodium (DSS). Expression of the transgene was seen in surface epithelium, lamina propria, and muscularis mucosae. The HGF-treated mice showed reduced colonic mucosal damage and increased body weights, compared with control mice (P < 0.01 and P < 0.05, respectively). The HGF-treated mice displayed increased number of PCNA-positive cells and decreased number of apoptotic cells thanmore » in control mice (P < 0.01, each). Phosphorylated AKT was dramatically increased after HGF gene administration, however, phosphorylated ERK1/2 was not altered. Microarray analysis revealed that HGF induced expression of proliferation- and apoptosis-associated genes. These data suggest that naked HGF gene delivery causes therapeutic effects through regulation of many downstream genes.« less

Saltatory Evolution of the Ectodermal Neural Cortex Gene Family at the Vertebrate Origin

PubMed Central

Feiner, Nathalie; Murakami, Yasunori; Breithut, Lisa; Mazan, Sylvie; Meyer, Axel; Kuraku, Shigehiro

2013-01-01

The ectodermal neural cortex (ENC) gene family, whose members are implicated in neurogenesis, is part of the kelch repeat superfamily. To date, ENC genes have been identified only in osteichthyans, although other kelch repeat-containing genes are prevalent throughout bilaterians. The lack of elaborate molecular phylogenetic analysis with exhaustive taxon sampling has obscured the possible link of the establishment of this gene family with vertebrate novelties. In this study, we identified ENC homologs in diverse vertebrates by means of database mining and polymerase chain reaction screens. Our analysis revealed that the ENC3 ortholog was lost in the basal eutherian lineage through single-gene deletion and that the triplication between ENC1, -2, and -3 occurred early in vertebrate evolution. Including our original data on the catshark and the zebrafish, our comparison revealed high conservation of the pleiotropic expression pattern of ENC1 and shuffling of expression domains between ENC1, -2, and -3. Compared with many other gene families including developmental key regulators, the ENC gene family is unique in that conventional molecular phylogenetic inference could identify no obvious invertebrate ortholog. This suggests a composite nature of the vertebrate-specific gene repertoire, consisting not only of de novo genes introduced at the vertebrate origin but also of long-standing genes with no apparent invertebrate orthologs. Some of the latter, including the ENC gene family, may be too rapidly evolving to provide sufficient phylogenetic signals marking orthology to their invertebrate counterparts. Such gene families that experienced saltatory evolution likely remain to be explored and might also have contributed to phenotypic evolution of vertebrates. PMID:23843192

The genetic potential for key biogeochemical processes in Arctic frost flowers and young sea ice revealed by metagenomic analysis.

PubMed

Bowman, Jeff S; Berthiaume, Chris T; Armbrust, E Virginia; Deming, Jody W

2014-08-01

Newly formed sea ice is a vast and biogeochemically active environment. Recently, we reported an unusual microbial community dominated by members of the Rhizobiales in frost flowers at the surface of Arctic young sea ice based on the presence of 16S gene sequences related to these strains. Here, we use metagenomic analysis of two samples, from a field of frost flowers and the underlying young sea ice, to explore the metabolic potential of this surface ice community. The analysis links genes for key biogeochemical processes to the Rhizobiales, including dimethylsulfide uptake, betaine glycine turnover, and halocarbon production. Nodulation and nitrogen fixation genes characteristic of terrestrial root-nodulating Rhizobiales were generally lacking from these metagenomes. Non-Rhizobiales clades at the ice surface had genes that would enable additional biogeochemical processes, including mercury reduction and dimethylsulfoniopropionate catabolism. Although the ultimate source of the observed microbial community is not known, considerations of the possible role of eolian deposition or transport with particles entrained during ice formation favor a suspended particle source for this microbial community. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction.

PubMed

Reyes-Gibby, Cielito C; Yuan, Christine; Wang, Jian; Yeung, Sai-Ching J; Shete, Sanjay

2015-06-05

Addictions to alcohol and tobacco, known risk factors for cancer, are complex heritable disorders. Addictive behaviors have a bidirectional relationship with pain. We hypothesize that the associations between alcohol, smoking, and opioid addiction observed in cancer patients have a genetic basis. Therefore, using bioinformatics tools, we explored the underlying genetic basis and identified new candidate genes and common biological pathways for smoking, alcohol, and opioid addiction. Literature search showed 56 genes associated with alcohol, smoking and opioid addiction. Using Core Analysis function in Ingenuity Pathway Analysis software, we found that ERK1/2 was strongly interconnected across all three addiction networks. Genes involved in immune signaling pathways were shown across all three networks. Connect function from IPA My Pathway toolbox showed that DRD2 is the gene common to both the list of genetic variations associated with all three addiction phenotypes and the components of the brain neuronal signaling network involved in substance addiction. The top canonical pathways associated with the 56 genes were: 1) calcium signaling, 2) GPCR signaling, 3) cAMP-mediated signaling, 4) GABA receptor signaling, and 5) G-alpha i signaling. Cancer patients are often prescribed opioids for cancer pain thus increasing their risk for opioid abuse and addiction. Our findings provide candidate genes and biological pathways underlying addiction phenotypes, which may be future targets for treatment of addiction. Further study of the variations of the candidate genes could allow physicians to make more informed decisions when treating cancer pain with opioid analgesics.

In Silico Estimation of Translation Efficiency in Human Cell Lines: Potential Evidence for Widespread Translational Control

PubMed Central

Stevens, Stewart G.; Brown, Chris M

2013-01-01

Recently large scale transcriptome and proteome datasets for human cells have become available. A striking finding from these studies is that the level of an mRNA typically predicts no more than 40% of the abundance of protein. This correlation represents the overall figure for all genes. We present here a bioinformatic analysis of translation efficiency – the rate at which mRNA is translated into protein. We have analysed those human datasets that include genome wide mRNA and protein levels determined in the same study. The analysis comprises five distinct human cell lines that together provide comparable data for 8,170 genes. For each gene we have used levels of mRNA and protein combined with protein stability data from the HeLa cell line to estimate translation efficiency. This was possible for 3,990 genes in one or more cell lines and 1,807 genes in all five cell lines. Interestingly, our analysis and modelling shows that for many genes this estimated translation efficiency has considerable consistency between cell lines. Some deviations from this consistency likely result from the regulation of protein degradation. Others are likely due to known translational control mechanisms. These findings suggest it will be possible to build improved models for the interpretation of mRNA expression data. The results we present here provide a view of translation efficiency for many genes. We provide an online resource allowing the exploration of translation efficiency in genes of interest within different cell lines (http://bioanalysis.otago.ac.nz/TranslationEfficiency). PMID:23460887

Differential Gene Expression Reveals Candidate Genes for Drought Stress Response in Abies alba (Pinaceae)

PubMed Central

Ziegenhagen, Birgit; Liepelt, Sascha

2015-01-01

Increasing drought periods as a result of global climate change pose a threat to many tree species by possibly outpacing their adaptive capabilities. Revealing the genetic basis of drought stress response is therefore implemental for future conservation strategies and risk assessment. Access to informative genomic regions is however challenging, especially for conifers, partially due to their large genomes, which puts constraints on the feasibility of whole genome scans. Candidate genes offer a valuable tool to reduce the complexity of the analysis and the amount of sequencing work and costs. For this study we combined an improved drought stress phenotyping of needles via a novel terahertz water monitoring technique with Massive Analysis of cDNA Ends to identify candidate genes for drought stress response in European silver fir (Abies alba Mill.). A pooled cDNA library was constructed from the cotyledons of six drought stressed and six well-watered silver fir seedlings, respectively. Differential expression analyses of these libraries revealed 296 candidate genes for drought stress response in silver fir (247 up- and 49 down-regulated) of which a subset was validated by RT-qPCR of the twelve individual cotyledons. A majority of these genes code for currently uncharacterized proteins and hint on new genomic resources to be explored in conifers. Furthermore, we could show that some traditional reference genes from model plant species (GAPDH and eIF4A2) are not suitable for differential analysis and we propose a new reference gene, TPC1, for drought stress expression profiling in needles of conifer seedlings. PMID:25924061

Exploration of new perspectives and limitations in Agrobacterium mediated gene transfer technology. Progress report, [June 1, 1992-- May 31, 1994

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

Marton, L.

1994-12-31

This report describes progress aimed at constructing gene-transfer technology for Nicotiana plumbaginifolia. Most actual effort as described herein has so far been directed at exploring new perspectives and limitations in Agrobacterium mediated gene transfer. Accomplishments are described using a core homologous gene targeting vector.

An evaluation of genotyping by sequencing (GBS) to map the Breviaristatum-e (ari-e) locus in cultivated barley.

PubMed

Liu, Hui; Bayer, Micha; Druka, Arnis; Russell, Joanne R; Hackett, Christine A; Poland, Jesse; Ramsay, Luke; Hedley, Pete E; Waugh, Robbie

2014-02-06

We explored the use of genotyping by sequencing (GBS) on a recombinant inbred line population (GPMx) derived from a cross between the two-rowed barley cultivar 'Golden Promise' (ari-e.GP/Vrs1) and the six-rowed cultivar 'Morex' (Ari-e/vrs1) to map plant height. We identified three Quantitative Trait Loci (QTL), the first in a region encompassing the spike architecture gene Vrs1 on chromosome 2H, the second in an uncharacterised centromeric region on chromosome 3H, and the third in a region of chromosome 5H coinciding with the previously described dwarfing gene Breviaristatum-e (Ari-e). Barley cultivars in North-western Europe largely contain either of two dwarfing genes; Denso on chromosome 3H, a presumed ortholog of the rice green revolution gene OsSd1, or Breviaristatum-e (ari-e) on chromosome 5H. A recessive mutant allele of the latter gene, ari-e.GP, was introduced into cultivation via the cv. 'Golden Promise' that was a favourite of the Scottish malt whisky industry for many years and is still used in agriculture today. Using GBS mapping data and phenotypic measurements we show that ari-e.GP maps to a small genetic interval on chromosome 5H and that alternative alleles at a region encompassing Vrs1 on 2H along with a region on chromosome 3H also influence plant height. The location of Ari-e is supported by analysis of near-isogenic lines containing different ari-e alleles. We explored use of the GBS to populate the region with sequence contigs from the recently released physically and genetically integrated barley genome sequence assembly as a step towards Ari-e gene identification. GBS was an effective and relatively low-cost approach to rapidly construct a genetic map of the GPMx population that was suitable for genetic analysis of row type and height traits, allowing us to precisely position ari-e.GP on chromosome 5H. Mapping resolution was lower than we anticipated. We found the GBS data more complex to analyse than other data types but it did directly provide linked SNP markers for subsequent higher resolution genetic analysis.

Gene-gene interactions and gene polymorphisms of VEGFA and EG-VEGF gene systems in recurrent pregnancy loss.

PubMed

Su, Mei-Tsz; Lin, Sheng-Hsiang; Chen, Yi-Chi; Kuo, Pao-Lin

2014-06-01

Both vascular endothelial growth factor A (VEGFA) and endocrine gland-derived vascular endothelial growth factor (EG-VEGF) systems play major roles in angiogenesis. A body of evidence suggests VEGFs regulate critical processes during pregnancy and have been associated with recurrent pregnancy loss (RPL). However, little information is available regarding the interaction of these two major major angiogenesis-related systems in early human pregnancy. This study was conducted to investigate the association of gene polymorphisms and gene-gene interaction among genes in VEGFA and EG-VEGF systems and idiopathic RPL. A total of 98 women with history of idiopathic RPL and 142 controls were included, and 5 functional SNPs selected from VEGFA, KDR, EG-VEGF (PROK1), PROKR1 and PROKR2 were genotyped. We used multifactor dimensionality reduction (MDR) analysis to choose a best model and evaluate gene-gene interactions. Ingenuity pathways analysis (IPA) was introduced to explore possible complex interactions. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL (P<0.01). The MDR test revealed that the KDR (Q472H) polymorphism was the best loci to be associated with RPL (P=0.02). IPA revealed EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3 signaling pathways. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL. EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3.

Genetic basis of interindividual susceptibility to cancer cachexia: selection of potential candidate gene polymorphisms for association studies.

PubMed

Johns, N; Tan, B H; MacMillan, M; Solheim, T S; Ross, J A; Baracos, V E; Damaraju, S; Fearon, K C H

2014-12-01

Cancer cachexia is a complex and multifactorial disease. Evolving definitions highlight the fact that a diverse range of biological processes contribute to cancer cachexia. Part of the variation in who will and who will not develop cancer cachexia may be genetically determined. As new definitions, classifications and biological targets continue to evolve, there is a need for reappraisal of the literature for future candidate association studies. This review summarizes genes identified or implicated as well as putative candidate genes contributing to cachexia, identified through diverse technology platforms and model systems to further guide association studies. A systematic search covering 1986-2012 was performed for potential candidate genes / genetic polymorphisms relating to cancer cachexia. All candidate genes were reviewed for functional polymorphisms or clinically significant polymorphisms associated with cachexia using the OMIM and GeneRIF databases. Pathway analysis software was used to reveal possible network associations between genes. Functionality of SNPs/genes was explored based on published literature, algorithms for detecting putative deleterious SNPs and interrogating the database for expression of quantitative trait loci (eQTLs). A total of 154 genes associated with cancer cachexia were identified and explored for functional polymorphisms. Of these 154 genes, 119 had a combined total of 281 polymorphisms with functional and/or clinical significance in terms of cachexia associated with them. Of these, 80 polymorphisms (in 51 genes) were replicated in more than one study with 24 polymorphisms found to influence two or more hallmarks of cachexia (i.e., inflammation, loss of fat mass and/or lean mass and reduced survival). Selection of candidate genes and polymorphisms is a key element of multigene study design. The present study provides a contemporary basis to select genes and/or polymorphisms for further association studies in cancer cachexia, and to develop their potential as susceptibility biomarkers of cachexia.

Multi-breed and multi-trait co-association analysis of meat tenderness and other meat quality traits in three French beef cattle breeds.

PubMed

Ramayo-Caldas, Yuliaxis; Renand, Gilles; Ballester, Maria; Saintilan, Romain; Rocha, Dominique

2016-04-23

Studies to identify markers associated with beef tenderness have focused on Warner-Bratzler shear force (WBSF) but the interplay between the genes associated with WBSF has not been explored. We used the association weight matrix (AWM), a systems biology approach, to identify a set of interacting genes that are co-associated with tenderness and other meat quality traits, and shared across the Charolaise, Limousine and Blonde d'Aquitaine beef cattle breeds. Genome-wide association studies were performed using ~500K single nucleotide polymorphisms (SNPs) and 17 phenotypes measured on more than 1000 animals for each breed. First, this multi-trait approach was applied separately for each breed across 17 phenotypes and second, between- and across-breed comparisons at the AWM and functional levels were performed. Genetic heterogeneity was observed, and most of the variants that were associated with WBSF segregated within rather than across breeds. We identified 206 common candidate genes associated with WBSF across the three breeds. SNPs in these common genes explained between 28 and 30 % of the phenotypic variance for WBSF. A reduced number of common SNPs mapping to the 206 common genes were identified, suggesting that different mutations may target the same genes in a breed-specific manner. Therefore, it is likely that, depending on allele frequencies and linkage disequilibrium patterns, a SNP that is identified for one breed may not be informative for another unrelated breed. Well-known candidate genes affecting beef tenderness were identified. In addition, some of the 206 common genes are located within previously reported quantitative trait loci for WBSF in several cattle breeds. Moreover, the multi-breed co-association analysis detected new candidate genes, regulators and metabolic pathways that are likely involved in the determination of meat tenderness and other meat quality traits in beef cattle. Our results suggest that systems biology approaches that explore associations of correlated traits increase statistical power to identify candidate genes beyond the one-dimensional approach. Further studies on the 206 common genes, their pathways, regulators and interactions will expand our knowledge on the molecular basis of meat tenderness and could lead to the discovery of functional mutations useful for genomic selection in a multi-breed beef cattle context.

Patterns and architecture of genomic islands in marine bacteria

PubMed Central

2012-01-01

Background Genomic Islands (GIs) have key roles since they modulate the structure and size of bacterial genomes displaying a diverse set of laterally transferred genes. Despite their importance, GIs in marine bacterial genomes have not been explored systematically to uncover possible trends and to analyze their putative ecological significance. Results We carried out a comprehensive analysis of GIs in 70 selected marine bacterial genomes detected with IslandViewer to explore the distribution, patterns and functional gene content in these genomic regions. We detected 438 GIs containing a total of 8152 genes. GI number per genome was strongly and positively correlated with the total GI size. In 50% of the genomes analyzed the GIs accounted for approximately 3% of the genome length, with a maximum of 12%. Interestingly, we found transposases particularly enriched within Alphaproteobacteria GIs, and site-specific recombinases in Gammaproteobacteria GIs. We described specific Homologous Recombination GIs (HR-GIs) in several genera of marine Bacteroidetes and in Shewanella strains among others. In these HR-GIs, we recurrently found conserved genes such as the β-subunit of DNA-directed RNA polymerase, regulatory sigma factors, the elongation factor Tu and ribosomal protein genes typically associated with the core genome. Conclusions Our results indicate that horizontal gene transfer mediated by phages, plasmids and other mobile genetic elements, and HR by site-specific recombinases play important roles in the mobility of clusters of genes between taxa and within closely related genomes, modulating the flexible pool of the genome. Our findings suggest that GIs may increase bacterial fitness under environmental changing conditions by acquiring novel foreign genes and/or modifying gene transcription and/or transduction. PMID:22839777

Integrated Analysis of Alzheimer's Disease and Schizophrenia Dataset Revealed Different Expression Pattern in Learning and Memory.

PubMed

Li, Wen-Xing; Dai, Shao-Xing; Liu, Jia-Qian; Wang, Qian; Li, Gong-Hua; Huang, Jing-Fei

2016-01-01

Alzheimer's disease (AD) and schizophrenia (SZ) are both accompanied by impaired learning and memory functions. This study aims to explore the expression profiles of learning or memory genes between AD and SZ. We downloaded 10 AD and 10 SZ datasets from GEO-NCBI for integrated analysis. These datasets were processed using RMA algorithm and a global renormalization for all studies. Then Empirical Bayes algorithm was used to find the differentially expressed genes between patients and controls. The results showed that most of the differentially expressed genes were related to AD whereas the gene expression profile was little affected in the SZ. Furthermore, in the aspects of the number of differentially expressed genes, the fold change and the brain region, there was a great difference in the expression of learning or memory related genes between AD and SZ. In AD, the CALB1, GABRA5, and TAC1 were significantly downregulated in whole brain, frontal lobe, temporal lobe, and hippocampus. However, in SZ, only two genes CRHBP and CX3CR1 were downregulated in hippocampus, and other brain regions were not affected. The effect of these genes on learning or memory impairment has been widely studied. It was suggested that these genes may play a crucial role in AD or SZ pathogenesis. The different gene expression patterns between AD and SZ on learning and memory functions in different brain regions revealed in our study may help to understand the different mechanism between two diseases.

Lipid metabolism in Rhodnius prolixus: Lessons from the genome.

PubMed

Majerowicz, David; Calderón-Fernández, Gustavo M; Alves-Bezerra, Michele; De Paula, Iron F; Cardoso, Lívia S; Juárez, M Patricia; Atella, Georgia C; Gondim, Katia C

2017-01-05

The kissing bug Rhodnius prolixus is both an important vector of Chagas' disease and an interesting model for investigation into the field of physiology, including lipid metabolism. The publication of this insect genome will bring a huge amount of new molecular biology data to be used in future experiments. Although this work represents a promising scenario, a preliminary analysis of the sequence data is necessary to identify and annotate the genes involved in lipid metabolism. Here, we used bioinformatics tools and gene expression analysis to explore genes from different genes families and pathways, including genes for fat breakdown, as lipases and phospholipases, and enzymes from β-oxidation, fatty acid metabolism, and acyl-CoA and glycerolipid synthesis. The R. prolixus genome encodes 31 putative lipase genes, including 21 neutral lipases and 5 acid lipases. The expression profiles of some of these genes were analyzed. We were able to identify nine phospholipase A2 genes. A variety of gene families that participate in fatty acid synthesis and modification were studied, including fatty acid synthase, elongase, desaturase and reductase. Concerning the synthesis of glycerolipids, we found a second isoform of glycerol-3-phosphate acyltransferase that was ubiquitously expressed throughout the organs. Finally, all genes involved in fatty acid β-oxidation were identified, but not a long-chain acyl-CoA dehydrogenase. These results provide fundamental data to be used in future research on insect lipid metabolism and its possible relevance to Chagas' disease transmission. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of pan-genome to identify the core genes and essential genes of Brucella spp.

PubMed

Yang, Xiaowen; Li, Yajie; Zang, Juan; Li, Yexia; Bie, Pengfei; Lu, Yanli; Wu, Qingmin

2016-04-01

Brucella spp. are facultative intracellular pathogens, that cause a contagious zoonotic disease, that can result in such outcomes as abortion or sterility in susceptible animal hosts and grave, debilitating illness in humans. For deciphering the survival mechanism of Brucella spp. in vivo, 42 Brucella complete genomes from NCBI were analyzed for the pan-genome and core genome by identification of their composition and function of Brucella genomes. The results showed that the total 132,143 protein-coding genes in these genomes were divided into 5369 clusters. Among these, 1710 clusters were associated with the core genome, 1182 clusters with strain-specific genes and 2477 clusters with dispensable genomes. COG analysis indicated that 44 % of the core genes were devoted to metabolism, which were mainly responsible for energy production and conversion (COG category C), and amino acid transport and metabolism (COG category E). Meanwhile, approximately 35 % of the core genes were in positive selection. In addition, 1252 potential essential genes were predicted in the core genome by comparison with a prokaryote database of essential genes. The results suggested that the core genes in Brucella genomes are relatively conservation, and the energy and amino acid metabolism play a more important role in the process of growth and reproduction in Brucella spp. This study might help us to better understand the mechanisms of Brucella persistent infection and provide some clues for further exploring the gene modules of the intracellular survival in Brucella spp.

Scale dependent inference in landscape genetics

Treesearch

Samuel A. Cushman; Erin L. Landguth

2010-01-01

Ecological relationships between patterns and processes are highly scale dependent. This paper reports the first formal exploration of how changing scale of research away from the scale of the processes governing gene flow affects the results of landscape genetic analysis. We used an individual-based, spatially explicit simulation model to generate patterns of genetic...

PHYLOGENETIC RELATIONSHIP OF ALEXANDRIUM MONILATUM (DINOPHYCEAE) TO OTHER ALEXANDRIUM SPECIES BASED ON 18S RIBOSOMAL RNA GENE SEQUENCES

EPA Science Inventory

The phylogenetic relationship of Alexandrium monilatum to other Alexandrium spp. was explored using 18S rDNA sequences. Maximum likelilhood phylogenetic analysis of the combined rDNA sequences established that A. monilatum paired with Alexandrium taylori and that the pair was the...

Mutagen Structure and Transcriptional Response: Induction of Distinct Transcriptional Profiles in Salmonella TA100 by the Drinking-Water Mutagen MX and Its Homologues

EPA Science Inventory

The relationship between chemical structure and biological activity has been examined for various compounds and endpoints for decades. To explore this question relative to global gene expression, we performed microarray analysis of Salmonella TA100 after treatment under condition...

PHYLOGENETIC RELATIONSHIP OF ALEXANDRIUM MONILATUM (DINOPHYCAE)TO OTHER ALEXANDRIUM SPECIES BASED ON 18S RIBOSOMAL RNA GENE SEQUENCES

EPA Science Inventory

The phylogenetic relationship of Alexandrium monilatum to other Alexandrium spp. was explored using 18S rDNA sequences. Maximum likelihood phylogenetic analysis of the combined rDNA sequences established that A. monilatum paired with Alexandrium taylori and that the pair was the ...

MutationAligner: a resource of recurrent mutation hotspots in protein domains in cancer

PubMed Central

Gauthier, Nicholas Paul; Reznik, Ed; Gao, Jianjiong; Sumer, Selcuk Onur; Schultz, Nikolaus; Sander, Chris; Miller, Martin L.

2016-01-01

The MutationAligner web resource, available at http://www.mutationaligner.org, enables discovery and exploration of somatic mutation hotspots identified in protein domains in currently (mid-2015) more than 5000 cancer patient samples across 22 different tumor types. Using multiple sequence alignments of protein domains in the human genome, we extend the principle of recurrence analysis by aggregating mutations in homologous positions across sets of paralogous genes. Protein domain analysis enhances the statistical power to detect cancer-relevant mutations and links mutations to the specific biological functions encoded in domains. We illustrate how the MutationAligner database and interactive web tool can be used to explore, visualize and analyze mutation hotspots in protein domains across genes and tumor types. We believe that MutationAligner will be an important resource for the cancer research community by providing detailed clues for the functional importance of particular mutations, as well as for the design of functional genomics experiments and for decision support in precision medicine. MutationAligner is slated to be periodically updated to incorporate additional analyses and new data from cancer genomics projects. PMID:26590264

Novel microbial diversity retrieved by autonomous robotic exploration of the world's deepest vertical phreatic sinkhole.

PubMed

Sahl, Jason W; Fairfield, Nathaniel; Harris, J Kirk; Wettergreen, David; Stone, William C; Spear, John R

2010-03-01

The deep phreatic thermal explorer (DEPTHX) is an autonomous underwater vehicle designed to navigate an unexplored environment, generate high-resolution three-dimensional (3-D) maps, collect biological samples based on an autonomous sampling decision, and return to its origin. In the spring of 2007, DEPTHX was deployed in Zacatón, a deep (approximately 318 m), limestone, phreatic sinkhole (cenote) in northeastern Mexico. As DEPTHX descended, it generated a 3-D map based on the processing of range data from 54 onboard sonars. The vehicle collected water column samples and wall biomat samples throughout the depth profile of the cenote. Post-expedition sample analysis via comparative analysis of 16S rRNA gene sequences revealed a wealth of microbial diversity. Traditional Sanger gene sequencing combined with a barcoded-amplicon pyrosequencing approach revealed novel, phylum-level lineages from the domains Bacteria and Archaea; in addition, several novel subphylum lineages were also identified. Overall, DEPTHX successfully navigated and mapped Zacatón, and collected biological samples based on an autonomous decision, which revealed novel microbial diversity in a previously unexplored environment.

Genome-wide analysis of a Wnt1-regulated transcriptional network implicates neurodegenerative pathways.

PubMed

Wexler, Eric M; Rosen, Ezra; Lu, Daning; Osborn, Gregory E; Martin, Elizabeth; Raybould, Helen; Geschwind, Daniel H

2011-10-04

Wnt proteins are critical to mammalian brain development and function. The canonical Wnt signaling pathway involves the stabilization and nuclear translocation of β-catenin; however, Wnt also signals through alternative, noncanonical pathways. To gain a systems-level, genome-wide view of Wnt signaling, we analyzed Wnt1-stimulated changes in gene expression by transcriptional microarray analysis in cultured human neural progenitor (hNP) cells at multiple time points over a 72-hour time course. We observed a widespread oscillatory-like pattern of changes in gene expression, involving components of both the canonical and the noncanonical Wnt signaling pathways. A higher-order, systems-level analysis that combined independent component analysis, waveform analysis, and mutual information-based network construction revealed effects on pathways related to cell death and neurodegenerative disease. Wnt effectors were tightly clustered with presenilin1 (PSEN1) and granulin (GRN), which cause dominantly inherited forms of Alzheimer's disease and frontotemporal dementia (FTD), respectively. We further explored a potential link between Wnt1 and GRN and found that Wnt1 decreased GRN expression by hNPs. Conversely, GRN knockdown increased WNT1 expression, demonstrating that Wnt and GRN reciprocally regulate each other. Finally, we provided in vivo validation of the in vitro findings by analyzing gene expression data from individuals with FTD. These unbiased and genome-wide analyses provide evidence for a connection between Wnt signaling and the transcriptional regulation of neurodegenerative disease genes.

Improved detection of overrepresentation of Gene-Ontology annotations with parent child analysis.

PubMed

Grossmann, Steffen; Bauer, Sebastian; Robinson, Peter N; Vingron, Martin

2007-11-15

High-throughput experiments such as microarray hybridizations often yield long lists of genes found to share a certain characteristic such as differential expression. Exploring Gene Ontology (GO) annotations for such lists of genes has become a widespread practice to get first insights into the potential biological meaning of the experiment. The standard statistical approach to measuring overrepresentation of GO terms cannot cope with the dependencies resulting from the structure of GO because they analyze each term in isolation. Especially the fact that annotations are inherited from more specific descendant terms can result in certain types of false-positive results with potentially misleading biological interpretation, a phenomenon which we term the inheritance problem. We present here a novel approach to analysis of GO term overrepresentation that determines overrepresentation of terms in the context of annotations to the term's parents. This approach reduces the dependencies between the individual term's measurements, and thereby avoids producing false-positive results owing to the inheritance problem. ROC analysis using study sets with overrepresented GO terms showed a clear advantage for our approach over the standard algorithm with respect to the inheritance problem. Although there can be no gold standard for exploratory methods such as analysis of GO term overrepresentation, analysis of biological datasets suggests that our algorithm tends to identify the core GO terms that are most characteristic of the dataset being analyzed.

Gene regulation is governed by a core network in hepatocellular carcinoma.

PubMed

Gu, Zuguang; Zhang, Chenyu; Wang, Jin

2012-05-01

Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide, and the mechanisms that lead to the disease are still relatively unclear. However, with the development of high-throughput technologies it is possible to gain a systematic view of biological systems to enhance the understanding of the roles of genes associated with HCC. Thus, analysis of the mechanism of molecule interactions in the context of gene regulatory networks can reveal specific sub-networks that lead to the development of HCC. In this study, we aimed to identify the most important gene regulations that are dysfunctional in HCC generation. Our method for constructing gene regulatory network is based on predicted target interactions, experimentally-supported interactions, and co-expression model. Regulators in the network included both transcription factors and microRNAs to provide a complete view of gene regulation. Analysis of gene regulatory network revealed that gene regulation in HCC is highly modular, in which different sets of regulators take charge of specific biological processes. We found that microRNAs mainly control biological functions related to mitochondria and oxidative reduction, while transcription factors control immune responses, extracellular activity and the cell cycle. On the higher level of gene regulation, there exists a core network that organizes regulations between different modules and maintains the robustness of the whole network. There is direct experimental evidence for most of the regulators in the core gene regulatory network relating to HCC. We infer it is the central controller of gene regulation. Finally, we explored the influence of the core gene regulatory network on biological pathways. Our analysis provides insights into the mechanism of transcriptional and post-transcriptional control in HCC. In particular, we highlight the importance of the core gene regulatory network; we propose that it is highly related to HCC and we believe further experimental validation is worthwhile.

Alteration of gene expression by alcohol exposure at early neurulation.

PubMed

Zhou, Feng C; Zhao, Qianqian; Liu, Yunlong; Goodlett, Charles R; Liang, Tiebing; McClintick, Jeanette N; Edenberg, Howard J; Li, Lang

2011-02-21

We have previously demonstrated that alcohol exposure at early neurulation induces growth retardation, neural tube abnormalities, and alteration of DNA methylation. To explore the global gene expression changes which may underline these developmental defects, microarray analyses were performed in a whole embryo mouse culture model that allows control over alcohol and embryonic variables. Alcohol caused teratogenesis in brain, heart, forelimb, and optic vesicle; a subset of the embryos also showed cranial neural tube defects. In microarray analysis (accession number GSM9545), adopting hypothesis-driven Gene Set Enrichment Analysis (GSEA) informatics and intersection analysis of two independent experiments, we found that there was a collective reduction in expression of neural specification genes (neurogenin, Sox5, Bhlhe22), neural growth factor genes [Igf1, Efemp1, Klf10 (Tieg), and Edil3], and alteration of genes involved in cell growth, apoptosis, histone variants, eye and heart development. There was also a reduction of retinol binding protein 1 (Rbp1), and de novo expression of aldehyde dehydrogenase 1B1 (Aldh1B1). Remarkably, four key hematopoiesis genes (glycophorin A, adducin 2, beta-2 microglobulin, and ceruloplasmin) were absent after alcohol treatment, and histone variant genes were reduced. The down-regulation of the neurospecification and the neurotrophic genes were further confirmed by quantitative RT-PCR. Furthermore, the gene expression profile demonstrated distinct subgroups which corresponded with two distinct alcohol-related neural tube phenotypes: an open (ALC-NTO) and a closed neural tube (ALC-NTC). Further, the epidermal growth factor signaling pathway and histone variants were specifically altered in ALC-NTO, and a greater number of neurotrophic/growth factor genes were down-regulated in the ALC-NTO than in the ALC-NTC embryos. This study revealed a set of genes vulnerable to alcohol exposure and genes that were associated with neural tube defects during early neurulation.

New genetic signatures associated with cancer cachexia as defined by low skeletal muscle index and weight loss

PubMed Central

Johns, Neil; Stretch, Cynthia; Tan, Benjamin H.L.; Solheim, Tora S.; Sørhaug, Sveinung; Stephens, Nathan A.; Gioulbasanis, Ioannis; Skipworth, Richard J.E.; Deans, D.A. Christopher; Vigano, Antonio; Ross, James A.; Bathe, Oliver F.; Tremblay, Michel L.; Kaasa, Stein; Strasser, Florian; Gagnon, Bruno; Baracos, Vickie E.; Damaraju, Sambasivarao

2016-01-01

Background Cachexia affects the majority with advanced cancer. Based on current demographic and clinical factors, it is not possible to predict who will develop cachexia or not. Such variation may, in part, be due to genotype. It has recently been proposed to extend the diagnostic criteria for cachexia to include a direct measure of low skeletal muscle index (LSMI) in addition to weight loss (WL). We aimed to explore our panel of candidate single nucleotide polymorphism (SNPs) for association with WL +/− computerized tomography‐defined LSMI. We also explored whether the transcription in muscle of identified genes was altered according to such cachexia phenotype Methods A retrospective cohort study design was used. Analysis explored associations of candidate SNPs with WL (n = 1276) and WL + LSMI (n = 943). Human muscle transcriptome (n = 134) was analysed using an Agilent platform. Results Single nucleotide polymorphisms in the following genes showed association with WL alone: GCKR, LEPR, SELP, ACVR2B, TLR4, FOXO3, IGF1, CPN1, APOE, FOXO1, and GHRL. SNPs in LEPR, ACVR2B, TNF, and ACE were associated with concurrent WL + LSMI. There was concordance between muscle‐specific expression for ACVR2B, FOXO1 and 3, LEPR, GCKR, and TLR4 genes and LSMI and/or WL (P < 0.05). Conclusions The rs1799964 in the TNF gene and rs4291 in the ACE gene are new associations when the definition of cachexia is based on a combination of WL and LSMI. These findings focus attention on pro‐inflammatory cytokines and the renin–angiotensin system as biomarkers/mediators of muscle wasting in cachexia. PMID:27897403

Expression analysis in a rat psychosis model identifies novel candidate genes validated in a large case–control sample of schizophrenia

PubMed Central

Ingason, A; Giegling, I; Hartmann, A M; Genius, J; Konte, B; Friedl, M; Ripke, S; Sullivan, P F; St. Clair, D; Collier, D A; O'Donovan, M C; Mirnics, K; Rujescu, D

2015-01-01

Antagonists of the N-methyl-D-aspartate (NMDA)-type glutamate receptor induce psychosis in healthy individuals and exacerbate schizophrenia symptoms in patients. In this study we have produced an animal model of NMDA receptor hypofunction by chronically treating rats with low doses of the NMDA receptor antagonist MK-801. Subsequently, we performed an expression study and identified 20 genes showing altered expression in the brain of these rats compared with untreated animals. We then explored whether the human orthologs of these genes are associated with schizophrenia in the largest schizophrenia genome-wide association study published to date, and found evidence for association for 4 out of the 20 genes: SF3B1, FOXP1, DLG2 and VGLL4. Interestingly, three of these genes, FOXP1, SF3B1 and DLG2, have previously been implicated in neurodevelopmental disorders. PMID:26460480

Expression analysis in a rat psychosis model identifies novel candidate genes validated in a large case-control sample of schizophrenia.

PubMed

Ingason, A; Giegling, I; Hartmann, A M; Genius, J; Konte, B; Friedl, M; Ripke, S; Sullivan, P F; St Clair, D; Collier, D A; O'Donovan, M C; Mirnics, K; Rujescu, D

2015-10-13

Antagonists of the N-methyl-D-aspartate (NMDA)-type glutamate receptor induce psychosis in healthy individuals and exacerbate schizophrenia symptoms in patients. In this study we have produced an animal model of NMDA receptor hypofunction by chronically treating rats with low doses of the NMDA receptor antagonist MK-801. Subsequently, we performed an expression study and identified 20 genes showing altered expression in the brain of these rats compared with untreated animals. We then explored whether the human orthologs of these genes are associated with schizophrenia in the largest schizophrenia genome-wide association study published to date, and found evidence for association for 4 out of the 20 genes: SF3B1, FOXP1, DLG2 and VGLL4. Interestingly, three of these genes, FOXP1, SF3B1 and DLG2, have previously been implicated in neurodevelopmental disorders.

Pathway modeling of microarray data: A case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP)

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

Ovacik, Meric A.; Sen, Banalata; Euling, Susan Y.

Pathway activity level analysis, the approach pursued in this study, focuses on all genes that are known to be members of metabolic and signaling pathways as defined by the KEGG database. The pathway activity level analysis entails singular value decomposition (SVD) of the expression data of the genes constituting a given pathway. We explore an extension of the pathway activity methodology for application to time-course microarray data. We show that pathway analysis enhances our ability to detect biologically relevant changes in pathway activity using synthetic data. As a case study, we apply the pathway activity level formulation coupled with significancemore » analysis to microarray data from two different rat testes exposed in utero to Dibutyl Phthalate (DBP). In utero DBP exposure in the rat results in developmental toxicity of a number of male reproductive organs, including the testes. One well-characterized mode of action for DBP and the male reproductive developmental effects is the repression of expression of genes involved in cholesterol transport, steroid biosynthesis and testosterone synthesis that lead to a decreased fetal testicular testosterone. Previous analyses of DBP testes microarray data focused on either individual gene expression changes or changes in the expression of specific genes that are hypothesized, or known, to be important in testicular development and testosterone synthesis. However, a pathway analysis may inform whether there are additional affected pathways that could inform additional modes of action linked to DBP developmental toxicity. We show that Pathway activity analysis may be considered for a more comprehensive analysis of microarray data.« less

Analysis of Copy Number Variation in the Abp Gene Regions of Two House Mouse Subspecies Suggests Divergence during the Gene Family Expansions

PubMed Central

Pezer, Željka; Chung, Amanda G.; Karn, Robert C.

2017-01-01

Abstract The Androgen-binding protein (Abp) gene region of the mouse genome contains 64 genes, some encoding pheromones that influence assortative mating between mice from different subspecies. Using CNVnator and quantitative PCR, we explored copy number variation in this gene family in natural populations of Mus musculus domesticus (Mmd) and Mus musculus musculus (Mmm), two subspecies of house mice that form a narrow hybrid zone in Central Europe. We found that copy number variation in the center of the Abp gene region is very common in wild Mmd, primarily representing the presence/absence of the final duplications described for the mouse genome. Clustering of Mmd individuals based on this variation did not reflect their geographical origin, suggesting no population divergence in the Abp gene cluster. However, copy number variation patterns differ substantially between Mmd and other mouse taxa. Large blocks of Abp genes are absent in Mmm, Mus musculus castaneus and an outgroup, Mus spretus, although with differences in variation and breakpoint locations. Our analysis calls into question the reliance on a reference genome for interpreting the detailed organization of genes in taxa more distant from the Mmd reference genome. The polymorphic nature of the gene family expansion in all four taxa suggests that the number of Abp genes, especially in the central gene region, is not critical to the survival and reproduction of the mouse. However, Abp haplotypes of variable length may serve as a source of raw genetic material for new signals influencing reproductive communication and thus speciation of mice. PMID:28575204

A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

PubMed

Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

2015-09-01

Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

Identification and Functional Analysis of Healing Regulators in Drosophila

PubMed Central

Álvarez-Fernández, Carmen; Tamirisa, Srividya; Prada, Federico; Chernomoretz, Ariel; Podhajcer, Osvaldo; Blanco, Enrique; Martín-Blanco, Enrique

2015-01-01

Wound healing is an essential homeostatic mechanism that maintains the epithelial barrier integrity after tissue damage. Although we know the overall steps in wound healing, many of the underlying molecular mechanisms remain unclear. Genetically amenable systems, such as wound healing in Drosophila imaginal discs, do not model all aspects of the repair process. However, they do allow the less understood aspects of the healing response to be explored, e.g., which signal(s) are responsible for initiating tissue remodeling? How is sealing of the epithelia achieved? Or, what inhibitory cues cancel the healing machinery upon completion? Answering these and other questions first requires the identification and functional analysis of wound specific genes. A variety of different microarray analyses of murine and humans have identified characteristic profiles of gene expression at the wound site, however, very few functional studies in healing regulation have been carried out. We developed an experimentally controlled method that is healing-permissive and that allows live imaging and biochemical analysis of cultured imaginal discs. We performed comparative genome-wide profiling between Drosophila imaginal cells actively involved in healing versus their non-engaged siblings. Sets of potential wound-specific genes were subsequently identified. Importantly, besides identifying and categorizing new genes, we functionally tested many of their gene products by genetic interference and overexpression in healing assays. This non-saturated analysis defines a relevant set of genes whose changes in expression level are functionally significant for proper tissue repair. Amongst these we identified the TCP1 chaperonin complex as a key regulator of the actin cytoskeleton essential for the wound healing response. There is promise that our newly identified wound-healing genes will guide future work in the more complex mammalian wound healing response. PMID:25647511

From root to fruit: RNA-Seq analysis shows that arbuscular mycorrhizal symbiosis may affect tomato fruit metabolism.

PubMed

Zouari, Inès; Salvioli, Alessandra; Chialva, Matteo; Novero, Mara; Miozzi, Laura; Tenore, Gian Carlo; Bagnaresi, Paolo; Bonfante, Paola

2014-03-21

Tomato (Solanum lycopersicum) establishes a beneficial symbiosis with arbuscular mycorrhizal (AM) fungi. The formation of the mycorrhizal association in the roots leads to plant-wide modulation of gene expression. To understand the systemic effect of the fungal symbiosis on the tomato fruit, we used RNA-Seq to perform global transcriptome profiling on Moneymaker tomato fruits at the turning ripening stage. Fruits were collected at 55 days after flowering, from plants colonized with Funneliformis mosseae and from control plants, which were fertilized to avoid responses related to nutrient deficiency. Transcriptome analysis identified 712 genes that are differentially expressed in fruits from mycorrhizal and control plants. Gene Ontology (GO) enrichment analysis of these genes showed 81 overrepresented functional GO classes. Up-regulated GO classes include photosynthesis, stress response, transport, amino acid synthesis and carbohydrate metabolism functions, suggesting a general impact of fungal symbiosis on primary metabolisms and, particularly, on mineral nutrition. Down-regulated GO classes include cell wall, metabolism and ethylene response pathways. Quantitative RT-PCR validated the RNA-Seq results for 12 genes out of 14 when tested at three fruit ripening stages, mature green, breaker and turning. Quantification of fruit nutraceutical and mineral contents produced values consistent with the expression changes observed by RNA-Seq analysis. This RNA-Seq profiling produced a novel data set that explores the intersection of mycorrhization and fruit development. We found that the fruits of mycorrhizal plants show two transcriptomic "signatures": genes characteristic of a climacteric fleshy fruit, and genes characteristic of mycorrhizal status, like phosphate and sulphate transporters. Moreover, mycorrhizal plants under low nutrient conditions produce fruits with a nutrient content similar to those from non-mycorrhizal plants under high nutrient conditions, indicating that AM fungi can help replace exogenous fertilizer for fruit crops.

Genome-Wide Identification, Expression, and Functional Analysis of the Sugar Transporter Gene Family in Cassava (Manihot esculenta).

PubMed

Liu, Qin; Dang, Huijie; Chen, Zhijian; Wu, Junzheng; Chen, Yinhua; Chen, Songbi; Luo, Lijuan

2018-03-26

The sugar transporter ( STP ) gene family encodes monosaccharide transporters that contain 12 transmembrane domains and belong to the major facilitator superfamily. STP genes play critical roles in monosaccharide distribution and participate in diverse plant metabolic processes. To investigate the potential roles of STPs in cassava ( Manihot esculenta ) tuber root growth, genome-wide identification and expression and functional analyses of the STP gene family were performed in this study. A total of 20 MeSTP genes ( MeSTP1 - 20 ) containing the Sugar_tr conserved motifs were identified from the cassava genome, which could be further classified into four distinct groups in the phylogenetic tree. The expression profiles of the MeSTP genes explored using RNA-seq data showed that most of the MeSTP genes exhibited tissue-specific expression, and 15 out of 20 MeSTP genes were mainly expressed in the early storage root of cassava. qRT-PCR analysis further confirmed that most of the MeSTPs displayed higher expression in roots after 30 and 40 days of growth, suggesting that these genes may be involved in the early growth of tuber roots. Although all the MeSTP proteins exhibited plasma membrane localization, variations in monosaccharide transport activity were found through a complementation analysis in a yeast ( Saccharomyces cerevisiae ) mutant, defective in monosaccharide uptake. Among them, MeSTP2, MeSTP15, and MeSTP19 were able to efficiently complement the uptake of five monosaccharides in the yeast mutant, while MeSTP3 and MeSTP16 only grew on medium containing galactose, suggesting that these two MeSTP proteins are transporters specific for galactose. This study provides significant insights into the potential functions of MeSTPs in early tuber root growth, which possibly involves the regulation of monosaccharide distribution.

Molecular variation and horizontal gene transfer of the homocysteine methyltransferase gene mmuM and its distribution in clinical pathogens.

PubMed

Ying, Jianchao; Wang, Huifeng; Bao, Bokan; Zhang, Ying; Zhang, Jinfang; Zhang, Cheng; Li, Aifang; Lu, Junwan; Li, Peizhen; Ying, Jun; Liu, Qi; Xu, Teng; Yi, Huiguang; Li, Jinsong; Zhou, Li; Zhou, Tieli; Xu, Zuyuan; Ni, Liyan; Bao, Qiyu

2015-01-01

The homocysteine methyltransferase encoded by mmuM is widely distributed among microbial organisms. It is the key enzyme that catalyzes the last step in methionine biosynthesis and plays an important role in the metabolism process. It also enables the microbial organisms to tolerate high concentrations of selenium in the environment. In this research, 533 mmuM gene sequences covering 70 genera of the bacteria were selected from GenBank database. The distribution frequency of mmuM is different in the investigated genera of bacteria. The mapping results of 160 mmuM reference sequences showed that the mmuM genes were found in 7 species of pathogen genomes sequenced in this work. The polymerase chain reaction products of one mmuM genotype (NC_013951 as the reference) were sequenced and the sequencing results confirmed the mapping results. Furthermore, 144 representative sequences were chosen for phylogenetic analysis and some mmuM genes from totally different genera (such as the genes between Escherichia and Klebsiella and between Enterobacter and Kosakonia) shared closer phylogenetic relationship than those from the same genus. Comparative genomic analysis of the mmuM encoding regions on plasmids and bacterial chromosomes showed that pKF3-140 and pIP1206 plasmids shared a 21 kb homology region and a 4.9 kb fragment in this region was in fact originated from the Escherichia coli chromosome. These results further suggested that mmuM gene did go through the gene horizontal transfer among different species or genera of bacteria. High-throughput sequencing combined with comparative genomics analysis would explore distribution and dissemination of the mmuM gene among bacteria and its evolution at a molecular level.

Gene regulatory networks in lactation: identification of global principles using bioinformatics.

PubMed

Lemay, Danielle G; Neville, Margaret C; Rudolph, Michael C; Pollard, Katherine S; German, J Bruce

2007-11-27

The molecular events underlying mammary development during pregnancy, lactation, and involution are incompletely understood. Mammary gland microarray data, cellular localization data, protein-protein interactions, and literature-mined genes were integrated and analyzed using statistics, principal component analysis, gene ontology analysis, pathway analysis, and network analysis to identify global biological principles that govern molecular events during pregnancy, lactation, and involution. Several key principles were derived: (1) nearly a third of the transcriptome fluctuates to build, run, and disassemble the lactation apparatus; (2) genes encoding the secretory machinery are transcribed prior to lactation; (3) the diversity of the endogenous portion of the milk proteome is derived from fewer than 100 transcripts; (4) while some genes are differentially transcribed near the onset of lactation, the lactation switch is primarily post-transcriptionally mediated; (5) the secretion of materials during lactation occurs not by up-regulation of novel genomic functions, but by widespread transcriptional suppression of functions such as protein degradation and cell-environment communication; (6) the involution switch is primarily transcriptionally mediated; and (7) during early involution, the transcriptional state is partially reverted to the pre-lactation state. A new hypothesis for secretory diminution is suggested - milk production gradually declines because the secretory machinery is not transcriptionally replenished. A comprehensive network of protein interactions during lactation is assembled and new regulatory gene targets are identified. Less than one fifth of the transcriptionally regulated nodes in this lactation network have been previously explored in the context of lactation. Implications for future research in mammary and cancer biology are discussed.

Gastrointestinal Fibroblasts Have Specialized, Diverse Transcriptional Phenotypes: A Comprehensive Gene Expression Analysis of Human Fibroblasts

PubMed Central

Ishii, Genichiro; Aoyagi, Kazuhiko; Sasaki, Hiroki; Ochiai, Atsushi

2015-01-01

Background Fibroblasts are the principal stromal cells that exist in whole organs and play vital roles in many biological processes. Although the functional diversity of fibroblasts has been estimated, a comprehensive analysis of fibroblasts from the whole body has not been performed and their transcriptional diversity has not been sufficiently explored. The aim of this study was to elucidate the transcriptional diversity of human fibroblasts within the whole body. Methods Global gene expression analysis was performed on 63 human primary fibroblasts from 13 organs. Of these, 32 fibroblasts from gastrointestinal organs (gastrointestinal fibroblasts: GIFs) were obtained from a pair of 2 anatomical sites: the submucosal layer (submucosal fibroblasts: SMFs) and the subperitoneal layer (subperitoneal fibroblasts: SPFs). Using hierarchical clustering analysis, we elucidated identifiable subgroups of fibroblasts and analyzed the transcriptional character of each subgroup. Results In unsupervised clustering, 2 major clusters that separate GIFs and non-GIFs were observed. Organ- and anatomical site-dependent clusters within GIFs were also observed. The signature genes that discriminated GIFs from non-GIFs, SMFs from SPFs, and the fibroblasts of one organ from another organ consisted of genes associated with transcriptional regulation, signaling ligands, and extracellular matrix remodeling. Conclusions GIFs are characteristic fibroblasts with specific gene expressions from transcriptional regulation, signaling ligands, and extracellular matrix remodeling related genes. In addition, the anatomical site- and organ-dependent diversity of GIFs was also discovered. These features of GIFs contribute to their specific physiological function and homeostatic maintenance, and create a functional diversity of the gastrointestinal tract. PMID:26046848

A systems biology approach to detect key pathways and interaction networks in gastric cancer on the basis of microarray analysis.

PubMed

Guo, Leilei; Song, Chunhua; Wang, Peng; Dai, Liping; Zhang, Jianying; Wang, Kaijuan

2015-11-01

The aim of the present study was to explore key molecular pathways contributing to gastric cancer (GC) and to construct an interaction network between significant pathways and potential biomarkers. Publicly available gene expression profiles of GSE29272 for GC, and data for the corresponding normal tissue, were downloaded from Gene Expression Omnibus. Pre‑processing and differential analysis were performed with R statistical software packages, and a number of differentially expressed genes (DEGs) were obtained. A functional enrichment analysis was performed for all the DEGs with a BiNGO plug‑in in Cytoscape. Their correlation was analyzed in order to construct a network. The modularity analysis and pathway identification operations were used to identify graph clusters and associated pathways. The underlying molecular mechanisms involving these DEGs were also assessed by data mining. A total of 249 DEGs, which were markedly upregulated and downregulated, were identified. The extracellular region contained the most significantly over‑represented functional terms, with respect to upregulated and downregulated genes, and the closest topological matches were identified for taste transduction and regulation of autophagy. In addition, extracellular matrix‑receptor interactions were identified as the most relevant pathway associated with the progression of GC. The genes for fibronectin 1, secreted phosphoprotein 1, collagen type 4 variant α‑1/2 and thrombospondin 1, which are involved in the pathways, may be considered as potential therapeutic targets for GC. A series of associations between candidate genes and key pathways were also identified for GC, and their correlation may provide novel insights into the pathogenesis of GC.

gsSKAT: Rapid gene set analysis and multiple testing correction for rare-variant association studies using weighted linear kernels.

PubMed

Larson, Nicholas B; McDonnell, Shannon; Cannon Albright, Lisa; Teerlink, Craig; Stanford, Janet; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng; Cooney, Kathleen A; Lange, Ethan; Schleutker, Johanna; Carpten, John D; Powell, Isaac; Bailey-Wilson, Joan E; Cussenot, Olivier; Cancel-Tassin, Geraldine; Giles, Graham G; MacInnis, Robert J; Maier, Christiane; Whittemore, Alice S; Hsieh, Chih-Lin; Wiklund, Fredrik; Catalona, William J; Foulkes, William; Mandal, Diptasri; Eeles, Rosalind; Kote-Jarai, Zsofia; Ackerman, Michael J; Olson, Timothy M; Klein, Christopher J; Thibodeau, Stephen N; Schaid, Daniel J

2017-05-01

Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results. © 2017 WILEY PERIODICALS, INC.

Aspergillus collagen-like genes (acl): identification, sequence polymorphism, and assessment for PCR-based pathogen detection.

PubMed

Tuntevski, Kiril; Durney, Brandon C; Snyder, Anna K; Lasala, P Rocco; Nayak, Ajay P; Green, Brett J; Beezhold, Donald H; Rio, Rita V M; Holland, Lisa A; Lukomski, Slawomir

2013-12-01

The genus Aspergillus is a burden to public health due to its ubiquitous presence in the environment, its production of allergens, and wide demographic susceptibility among cystic fibrosis, asthmatic, and immunosuppressed patients. Current methods of detection of Aspergillus colonization and infection rely on lengthy morphological characterization or nonstandardized serological assays that are restricted to identifying a fungal etiology. Collagen-like genes have been shown to exhibit species-specific conservation across the noncollagenous regions as well as strain-specific polymorphism in the collagen-like regions. Here we assess the conserved region of the Aspergillus collagen-like (acl) genes and explore the application of PCR amplicon size-based discrimination among the five most common etiologic species of the Aspergillus genus, including Aspergillus fumigatus, A. flavus, A. nidulans, A. niger, and A. terreus. Genetic polymorphism and phylogenetic analysis of the aclF1 gene were additionally examined among the available strains. Furthermore, the applicability of the PCR-based assay to identification of these five species in cultures derived from sputum and bronchoalveolar fluid from 19 clinical samples was explored. Application of capillary electrophoresis on nanogels was additionally demonstrated to improve the discrimination between Aspergillus species. Overall, this study demonstrated that Aspergillus acl genes could be used as PCR targets to discriminate between clinically relevant Aspergillus species. Future studies aim to utilize the detection of Aspergillus acl genes in PCR and microfluidic applications to determine the sensitivity and specificity for the identification of Aspergillus colonization and invasive aspergillosis in immunocompromised subjects.

Global identification of genes regulated by estrogen signaling and demethylation in MCF-7 breast cancer cells

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

Putnik, Milica, E-mail: milica.putnik@ki.se; Zhao, Chunyan, E-mail: chunyan.zhao@ki.se; Gustafsson, Jan-Ake, E-mail: jan-ake.gustafsson@ki.se

Highlights: Black-Right-Pointing-Pointer Estrogen signaling and demethylation can both control gene expression in breast cancers. Black-Right-Pointing-Pointer Cross-talk between these mechanisms is investigated in human MCF-7 breast cancer cells. Black-Right-Pointing-Pointer 137 genes are influenced by both 17{beta}-estradiol and demethylating agent 5-aza-2 Prime -deoxycytidine. Black-Right-Pointing-Pointer A set of genes is identified as targets of both estrogen signaling and demethylation. Black-Right-Pointing-Pointer There is no direct molecular interplay of mediators of estrogen and epigenetic signaling. -- Abstract: Estrogen signaling and epigenetic modifications, in particular DNA methylation, are involved in regulation of gene expression in breast cancers. Here we investigated a potential regulatory cross-talk between thesemore » two pathways by identifying their common target genes and exploring underlying molecular mechanisms in human MCF-7 breast cancer cells. Gene expression profiling revealed that the expression of approximately 140 genes was influenced by both 17{beta}-estradiol (E2) and a demethylating agent 5-aza-2 Prime -deoxycytidine (DAC). Gene ontology (GO) analysis suggests that these genes are involved in intracellular signaling cascades, regulation of cell proliferation and apoptosis. Based on previously reported association with breast cancer, estrogen signaling and/or DNA methylation, CpG island prediction and GO analysis, we selected six genes (BTG3, FHL2, PMAIP1, BTG2, CDKN1A and TGFB2) for further analysis. Tamoxifen reverses the effect of E2 on the expression of all selected genes, suggesting that they are direct targets of estrogen receptor. Furthermore, DAC treatment reactivates the expression of all selected genes in a dose-dependent manner. Promoter CpG island methylation status analysis revealed that only the promoters of BTG3 and FHL2 genes are methylated, with DAC inducing demethylation, suggesting DNA methylation directs repression of these genes in MCF-7 cells. In a further analysis of the potential interplay between estrogen signaling and DNA methylation, E2 treatment showed no effect on the methylation status of these promoters. Additionally, we show that the ER{alpha} recruitment occurs at the FHL2 promoter in an E2- and DAC-independent fashion. In conclusion, we identified a set of genes regulated by both estrogen signaling and DNA methylation. However, our data does not support a direct molecular interplay of mediators of estrogen and epigenetic signaling at promoters of regulated genes.« less

dictyExpress: a web-based platform for sequence data management and analytics in Dictyostelium and beyond.

PubMed

Stajdohar, Miha; Rosengarten, Rafael D; Kokosar, Janez; Jeran, Luka; Blenkus, Domen; Shaulsky, Gad; Zupan, Blaz

2017-06-02

Dictyostelium discoideum, a soil-dwelling social amoeba, is a model for the study of numerous biological processes. Research in the field has benefited mightily from the adoption of next-generation sequencing for genomics and transcriptomics. Dictyostelium biologists now face the widespread challenges of analyzing and exploring high dimensional data sets to generate hypotheses and discovering novel insights. We present dictyExpress (2.0), a web application designed for exploratory analysis of gene expression data, as well as data from related experiments such as Chromatin Immunoprecipitation sequencing (ChIP-Seq). The application features visualization modules that include time course expression profiles, clustering, gene ontology enrichment analysis, differential expression analysis and comparison of experiments. All visualizations are interactive and interconnected, such that the selection of genes in one module propagates instantly to visualizations in other modules. dictyExpress currently stores the data from over 800 Dictyostelium experiments and is embedded within a general-purpose software framework for management of next-generation sequencing data. dictyExpress allows users to explore their data in a broader context by reciprocal linking with dictyBase-a repository of Dictyostelium genomic data. In addition, we introduce a companion application called GenBoard, an intuitive graphic user interface for data management and bioinformatics analysis. dictyExpress and GenBoard enable broad adoption of next generation sequencing based inquiries by the Dictyostelium research community. Labs without the means to undertake deep sequencing projects can mine the data available to the public. The entire information flow, from raw sequence data to hypothesis testing, can be accomplished in an efficient workspace. The software framework is generalizable and represents a useful approach for any research community. To encourage more wide usage, the backend is open-source, available for extension and further development by bioinformaticians and data scientists.

Integrative Genome-Wide Gene Expression Profiling of Clear Cell Renal Cell Carcinoma in Czech Republic and in the United States

PubMed Central

Wozniak, Magdalena B.; Le Calvez-Kelm, Florence; Abedi-Ardekani, Behnoush; Byrnes, Graham; Durand, Geoffroy; Carreira, Christine; Michelon, Jocelyne; Janout, Vladimir; Holcatova, Ivana; Foretova, Lenka; Brisuda, Antonin; Lesueur, Fabienne; McKay, James; Brennan, Paul; Scelo, Ghislaine

2013-01-01

Gene expression microarray and next generation sequencing efforts on conventional, clear cell renal cell carcinoma (ccRCC) have been mostly performed in North American and Western European populations, while the highest incidence rates are found in Central/Eastern Europe. We conducted whole-genome expression profiling on 101 pairs of ccRCC tumours and adjacent non-tumour renal tissue from Czech patients recruited within the “K2 Study”, using the Illumina HumanHT-12 v4 Expression BeadChips to explore the molecular variations underlying the biological and clinical heterogeneity of this cancer. Differential expression analysis identified 1650 significant probes (fold change ≥2 and false discovery rate <0.05) mapping to 630 up- and 720 down-regulated unique genes. We performed similar statistical analysis on the RNA sequencing data of 65 ccRCC cases from the Cancer Genome Atlas (TCGA) project and identified 60% (402) of the downregulated and 74% (469) of the upregulated genes found in the K2 series. The biological characterization of the significantly deregulated genes demonstrated involvement of downregulated genes in metabolic and catabolic processes, excretion, oxidation reduction, ion transport and response to chemical stimulus, while simultaneously upregulated genes were associated with immune and inflammatory responses, response to hypoxia, stress, wounding, vasculature development and cell activation. Furthermore, genome-wide DNA methylation analysis of 317 TCGA ccRCC/adjacent non-tumour renal tissue pairs indicated that deregulation of approximately 7% of genes could be explained by epigenetic changes. Finally, survival analysis conducted on 89 K2 and 464 TCGA cases identified 8 genes associated with differential prognostic outcomes. In conclusion, a large proportion of ccRCC molecular characteristics were common to the two populations and several may have clinical implications when validated further through large clinical cohorts. PMID:23526956

Comparative pharmacokinetics of rhein in normal and loperamide-induced constipated rats and microarray analysis of drug-metabolizing genes.

PubMed

Hou, Mei-Ling; Chang, Li-Wen; Lin, Chi-Hung; Lin, Lie-Chwen; Tsai, Tung-Hu

2014-09-11

Rhein is a pharmacological active component found in Rheum palmatum L. that is the major herb of the San-Huang-Xie-Xin-Tang (SHXXT), a medicinal herbal product used as a remedy for constipation. Here we have investigated the comparative pharmacokinetics of rhein in normal and constipated rats. Microarray analysis was used to explore whether drug-metabolizing genes will be altered after SHXXT treatment. The comparative pharmacokinetics of rhein in normal and loperamide-induced constipated rats was studied by liquid chromatography with electrospray ionization tandem mass spectrometry (LC-MS/MS). Gene expression profiling in drug-metabolizing genes after SHXXT treatment was investigated by microarray analysis and real-time polymerase chain reaction (RT-PCR). A validated LC-MS/MS method was applied to investigate the comparative pharmacokinetics of rhein in normal and loperamide-induced constipated rats. The pharmacokinetic results demonstrate that the loperamide-induced constipation reduced the absorption of rhein. Cmax significantly reduced by 2.5-fold, the AUC decreased by 27.8%; however, the elimination half-life (t1/2) was prolonged by 1.6-fold. Tmax and mean residence time (MRT) were significantly prolonged by 2.8-fold, and 1.7-fold, respectively. The volume of distribution (Vss) increased by 2.2-fold. The data of microarray analysis on gene expression indicate that five drug-metabolizing genes, including Cyp7a1, Cyp2c6, Ces2e, Atp1b1, and Slc7a2 were significantly altered by the SHXXT (0.5 g/kg) treatment. The loperamide-induced constipation reduced the absorption of rhein. Since among the 25,338 genes analyzed, there were five genes significantly altered by SHXXT treatment. Thus, information on minor drug-metabolizing genes altered by SHXXT treatment indicates that SHXXT is relatively safe for clinical application. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Updated regulation curation model at the Saccharomyces Genome Database

PubMed Central

Engel, Stacia R; Skrzypek, Marek S; Hellerstedt, Sage T; Wong, Edith D; Nash, Robert S; Weng, Shuai; Binkley, Gail; Sheppard, Travis K; Karra, Kalpana; Cherry, J Michael

2018-01-01

Abstract The Saccharomyces Genome Database (SGD) provides comprehensive, integrated biological information for the budding yeast Saccharomyces cerevisiae, along with search and analysis tools to explore these data, enabling the discovery of functional relationships between sequence and gene products in fungi and higher organisms. We have recently expanded our data model for regulation curation to address regulation at the protein level in addition to transcription, and are presenting the expanded data on the ‘Regulation’ pages at SGD. These pages include a summary describing the context under which the regulator acts, manually curated and high-throughput annotations showing the regulatory relationships for that gene and a graphical visualization of its regulatory network and connected networks. For genes whose products regulate other genes or proteins, the Regulation page includes Gene Ontology enrichment analysis of the biological processes in which those targets participate. For DNA-binding transcription factors, we also provide other information relevant to their regulatory function, such as DNA binding site motifs and protein domains. As with other data types at SGD, all regulatory relationships and accompanying data are available through YeastMine, SGD’s data warehouse based on InterMine. Database URL: http://www.yeastgenome.org PMID:29688362

Members of a new subgroup of Streptococcus anginosus harbor virulence related genes previously observed in Streptococcus pyogenes.

PubMed

Babbar, Anshu; Kumar, Venkatesan Naveen; Bergmann, René; Barrantes, Israel; Pieper, Dietmar H; Itzek, Andreas; Nitsche-Schmitz, D Patric

2017-04-01

Conventionally categorized as commensals, the Streptococci of the species S. anginosus are facultative human pathogens that are difficult to diagnose and often overlooked. Furthermore, detailed investigation and diagnosis of S. anginosus infections is hampered by unexplored taxonomy and widely elusive molecular pathogenesis. To explore their pathogenic potential, S. anginosus isolates collected from patients of two geographical locations (Vellore, India and Leipzig, Germany) were subjected to multi-locus sequence analysis (MLSA). This analysis revealed the potential presence of a new distinct clade of the species S. anginosus, tentatively termed here as genomosubspecies vellorensis. A complementary PCR-based screening for S. pyogenes virulence factor as well as antibiotic resistance genes revealed not only the presence of superantigen- and extracellular DNase coding genes identical to corresponding genes of S. pyogenes, but also of erythromycin and tetracycline resistance genes in the genomes of the analyzed S. anginosus isolates, thus posing a matter of significant health concern. Identification of new pathogenic S. anginosus strains capable of causing difficult to treat infections may pose additional challenges to the diagnosis and treatment of Streptococcus based infections. Copyright © 2017 Elsevier GmbH. All rights reserved.

CellLineNavigator: a workbench for cancer cell line analysis

PubMed Central

Krupp, Markus; Itzel, Timo; Maass, Thorsten; Hildebrandt, Andreas; Galle, Peter R.; Teufel, Andreas

2013-01-01

The CellLineNavigator database, freely available at http://www.medicalgenomics.org/celllinenavigator, is a web-based workbench for large scale comparisons of a large collection of diverse cell lines. It aims to support experimental design in the fields of genomics, systems biology and translational biomedical research. Currently, this compendium holds genome wide expression profiles of 317 different cancer cell lines, categorized into 57 different pathological states and 28 individual tissues. To enlarge the scope of CellLineNavigator, the database was furthermore closely linked to commonly used bioinformatics databases and knowledge repositories. To ensure easy data access and search ability, a simple data and an intuitive querying interface were implemented. It allows the user to explore and filter gene expression, focusing on pathological or physiological conditions. For a more complex search, the advanced query interface may be used to query for (i) differentially expressed genes; (ii) pathological or physiological conditions; or (iii) gene names or functional attributes, such as Kyoto Encyclopaedia of Genes and Genomes pathway maps. These queries may also be combined. Finally, CellLineNavigator allows additional advanced analysis of differentially regulated genes by a direct link to the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources. PMID:23118487

Expression of HOXB genes is significantly different in acute myeloid leukemia with a partial tandem duplication of MLL vs. a MLL translocation: a cross-laboratory study.

PubMed

Liu, Hsi-Che; Shih, Lee-Yung; May Chen, Mei-Ju; Wang, Chien-Chih; Yeh, Ting-Chi; Lin, Tung-Huei; Chen, Chien-Yu; Lin, Chih-Jen; Liang, Der-Cherng

2011-05-01

In acute myeloid leukemia (AML), the mixed lineage leukemia (MLL) gene may be rearranged to generate a partial tandem duplication (PTD), or fused to partner genes through a chromosomal translocation (tMLL). In this study, we first explored the differentially expressed genes between MLL-PTD and tMLL using gene expression profiling of our cohort (15 MLL-PTD and 10 tMLL) and one published data set. The top 250 probes were chosen from each set, resulting in 29 common probes (21 unique genes) to both sets. The selected genes include four HOXB genes, HOXB2, B3, B5, and B6. The expression values of these HOXB genes significantly differ between MLL-PTD and tMLL cases. Clustering and classification analyses were thoroughly conducted to support our gene selection results. Second, as MLL-PTD, FLT3-ITD, and NPM1 mutations are identified in AML with normal karyotypes, we briefly studied their impact on the HOXB genes. Another contribution of this study is to demonstrate that using public data from other studies enriches samples for analysis and yields more conclusive results. 2011 Elsevier Inc. All rights reserved.

Reduction in expression of the benign AR transcriptome is a hallmark of localised prostate cancer progression.

PubMed

Stuchbery, Ryan; Macintyre, Geoff; Cmero, Marek; Harewood, Laurence M; Peters, Justin S; Costello, Anthony J; Hovens, Christopher M; Corcoran, Niall M

2016-05-24

Despite the importance of androgen receptor (AR) signalling to prostate cancer development, little is known about how this signalling pathway changes with increasing grade and stage of the disease. To explore changes in the normal AR transcriptome in localised prostate cancer, and its relation to adverse pathological features and disease recurrence. Publically accessible human prostate cancer expression arrays as well as RNA sequencing data from the prostate TCGA. Tumour associated PSA and PSAD were calculated for a large cohort of men (n=1108) undergoing prostatectomy. We performed a meta-analysis of the expression of an androgen-regulated gene set across datasets using Oncomine. Differential expression of selected genes in the prostate TCGA database was probed using the edgeR Bioconductor package. Changes in tumour PSA density with stage and grade were assessed by Student's t-test, and its association with biochemical recurrence explored by Kaplan-Meier curves and Cox regression. Meta-analysis revealed a systematic decline in the expression of a previously identified benign prostate androgen-regulated gene set with increasing tumour grade, reaching significance in nine of 25 genes tested despite increasing AR expression. These results were confirmed in a large independent dataset from the TCGA. At the protein level, when serum PSA was corrected for tumour volume, significantly lower levels were observed with increasing tumour grade and stage, and predicted disease recurrence. Lower PSA secretion-per-tumour-volume is associated with increasing grade and stage of prostate cancer, has prognostic relevance, and reflects a systematic perturbation of androgen signalling.

Birt-Hogg-Dubé syndrome in two Chinese families with mutations in the FLCN gene.

PubMed

Hou, Xiaocan; Zhou, Yuan; Peng, Yun; Qiu, Rong; Xia, Kun; Tang, Beisha; Zhuang, Wei; Jiang, Hong

2018-01-22

Birt-Hogg-Dubé syndrome is an autosomal dominant hereditary condition caused by mutations in the folliculin-encoding gene FLCN (NM_144997). It is associated with skin lesions such as fibrofolliculoma, acrochordon and trichodiscoma; pulmonary lesions including spontaneous pneumothorax and pulmonary cysts and renal cancer. Genomic DNA was extracted from peripheral venous blood samples of the propositi and their family members. Genetic analysis was performed by whole exome sequencing and Sanger sequencing aiming at corresponding exons in FLCN gene to explore the genetic mutations of these two families. In this study, we performed genetic analysis by whole exome sequencing and Sanger sequencing aiming at corresponding exons in FLCN gene to explore the genetic mutations in two Chinese families. Patients from family 1 mostly suffered from pneumothorax and pulmonary cysts, several of whom also mentioned skin lesions or kidney lesions. While in family 2, only thoracic lesions were found in the patients, without any other clinical manifestations. Two FLCN mutations have been identified: One is an insertion mutation (c.1579_1580insA/p.R527Xfs on exon 14) previously reported in three Asian families (one mainland family and two Taiwanese families); while the other is a firstly reviewed mutation in Asian population (c.649C > T / p.Gln217X on exon 7) that ever been detected in a French family. Overall, The detection of these two mutations expands the spectrum of FLCN mutations and will provide insight into genetic diagnosis and counseling of Birt-Hogg-Dubé syndrome.

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

Sardi, Maria; Rovinskiy, Nikolay; Zhang, Yaoping

We report a major obstacle to sustainable lignocellulosic biofuel production is microbe inhibition by the combinatorial stresses in pretreated plant hydrolysate. Chemical biomass pretreatment releases a suite of toxins that interact with other stressors, including high osmolarity and temperature, which together can have poorly understood synergistic effects on cells. Improving tolerance in industrial strains has been hindered, in part because the mechanisms of tolerance reported in the literature often fail to recapitulate in other strain backgrounds. Here, we explored and then exploited variations in stress tolerance, toxin-induced transcriptomic responses, and fitness effects of gene overexpression in different Saccharomyces cerevisiae (yeast)more » strains to identify genes and processes linked to tolerance of hydrolysate stressors. Using six different S. cerevisiae strains that together maximized phenotypic and genetic diversity, first we explored transcriptomic differences between resistant and sensitive strains to identify common and strain-specific responses. This comparative analysis implicated primary cellular targets of hydrolysate toxins, secondary effects of defective defense strategies, and mechanisms of tolerance. Dissecting the responses to individual hydrolysate components across strains pointed to synergistic interactions between osmolarity, pH, hydrolysate toxins, and nutrient composition. By characterizing the effects of high-copy gene overexpression in three different strains, we revealed the breadth of the background-specific effects of gene fitness contributions in synthetic hydrolysate. Lastly, our approach identified new genes for engineering improved stress tolerance in diverse strains while illuminating the effects of genetic background on molecular mechanisms.« less

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

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit.

PubMed

Pendergrass, Sarah A; Verma, Shefali S; Holzinger, Emily R; Moore, Carrie B; Wallace, John; Dudek, Scott M; Huggins, Wayne; Kitchner, Terrie; Waudby, Carol; Berg, Richard; McCarty, Catherine A; Ritchie, Marylyn D

2013-01-01

Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, 2580 cataract cases and 1367 controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) Biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 529,431 single nucleotide polymorphisms (SNPs) with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using the Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 5 statistically significant models with an interaction term with p-value < 0.05, as well as an overall model with p-value < 0.05 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use; these environmental factors have been previously associated with the formation of cataracts. We found a total of 288 models that exhibit an interaction term with a p-value ≤ 1×10(-4) associated with cataract status. Our results show these approaches enable advanced searches for epistasis and gene-environment interactions beyond GWAS, and that the EHR based approach provides an additional source of data for seeking these advanced explanatory models of the etiology of complex disease/outcome such as cataracts.

Identification of gene regulation models from single-cell data

NASA Astrophysics Data System (ADS)

Weber, Lisa; Raymond, William; Munsky, Brian

2018-09-01

In quantitative analyses of biological processes, one may use many different scales of models (e.g. spatial or non-spatial, deterministic or stochastic, time-varying or at steady-state) or many different approaches to match models to experimental data (e.g. model fitting or parameter uncertainty/sloppiness quantification with different experiment designs). These different analyses can lead to surprisingly different results, even when applied to the same data and the same model. We use a simplified gene regulation model to illustrate many of these concerns, especially for ODE analyses of deterministic processes, chemical master equation and finite state projection analyses of heterogeneous processes, and stochastic simulations. For each analysis, we employ MATLAB and PYTHON software to consider a time-dependent input signal (e.g. a kinase nuclear translocation) and several model hypotheses, along with simulated single-cell data. We illustrate different approaches (e.g. deterministic and stochastic) to identify the mechanisms and parameters of the same model from the same simulated data. For each approach, we explore how uncertainty in parameter space varies with respect to the chosen analysis approach or specific experiment design. We conclude with a discussion of how our simulated results relate to the integration of experimental and computational investigations to explore signal-activated gene expression models in yeast (Neuert et al 2013 Science 339 584–7) and human cells (Senecal et al 2014 Cell Rep. 8 75–83)5.

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.

[Construction of transgenic tobacco expressing tomato GGPS2 gene and analysis of its low light tolerance].

PubMed

Li, Cuiping; Dong, Weihua; Zhang, Xingguo

2015-05-01

To explore the influence of low light on the synthesis of carotenoids, chlorophyll and the adaptability of transgenic plants with tomato Solanum lycopersicon L. GGPS2 gene, we constructed a vector containing a GGPS2 gene with green fluorescent protein (GFP) as report gene under the control of a cauliflower mosaic virus 35S promoter and introduced it into tobacco Nicotiana tabacum L. cv. Wisconsin 38 by Agrobacterium tumefaciens-mediated transformation. PCR analysis of the DNA from kanamycin resistant tobacco indicated that the transgenic tobacco containing the nptII gene, SlaGGPS2 gene and without contamination of Agrobacterium. We also detected the root tip of kanamycin resistant tobacco showing characteristic fluorescence. The contents of carotenoid, chlorophyll and photosynthesis of transgenic tobacco increased in comparison with wild tobacco after low light treatment. In addition, leaf mass per unit area, total dry weight, ratio of root to shoot in transgenic tobacco were all higher than that of the wild tobacco, which proved that the transgenic tobacco could increase the accumulation of biomass and promote it transport to root. The transgenic tobacco with SlaGGPS2 gene can increase the contents of carotenoid, chlorophyll, enhance the photosynthetic rate, promote the biomass accumulation and its distribution to root. Hence, the transgenic tobacco with SlaGGPS2 gene had increased low light tolerance and the SlaGGPS2 gene maybe can be used in other crops.

RNA sequencing-based analysis of gallbladder cancer reveals the importance of the liver X receptor and lipid metabolism in gallbladder cancer

PubMed Central

Zuo, Mingxin; Rashid, Asif; Wang, Ying; Jain, Apurva; Li, Donghui; Behari, Anu; Kapoor, Vinay Kumar; Koay, Eugene J.; Chang, Ping; Vauthey, Jean Nicholas; Li, Yanan; Espinoza, Jaime A.; Roa, Juan Carlos; Javle, Milind

2016-01-01

Gallbladder cancer (GBC) is an aggressive malignancy. Although surgical resection may be curable, most patients are diagnosed at an advanced unresectable disease stage. Cholelithiasis is the major risk factor; however the pathogenesis of the disease, from gallstone cholecystitis to cancer, is still not understood. To understand the molecular genetic underpinnings of this cancer and explore novel therapeutic targets for GBC, we examined the key genes and pathways involved in GBC using RNA sequencing. We performed gene expression analysis of 32 cases of surgically-resected GBC along with normal gallbladder tissue controls. We observed that 519 genes were differentially expressed between GBC and normal GB mucosal controls. The liver X receptor (LXR)/retinoid X receptor (RXR) and farnesoid X receptor (FXR) /RXR pathways were the top canonical pathways involved in GBC. Key genes in these pathways, including SERPINB3 and KLK1, were overexpressed in GBC, especially in female GBC patients. Additionally, ApoA1 gene expression suppressed in GBC as compared with normal control tissues. LXR and FXR genes, known to be important in lipid metabolism also function as tumor suppressors and their down regulation appears to be critical for GBC pathogenesis. LXR agonists may have therapeutic value and as potential therapeutic targets. PMID:27167107

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

Mechanisms of HO-1 mediated attenuation of renal immune injury: a gene profiling study.

PubMed

Duann, Pu; Lianos, Elias A

2011-10-01

Using a mouse model of immune injury directed against the renal glomerular vasculature and resembling human forms of glomerulonephritis (GN), we assessed the effect of targeted expression of the cytoprotective enzyme heme oxygenase (HO)-1. A human (h) HO-1 complementary DNAN (cDNA) sequence was targeted to glomerular epithelial cells (GECs) using a GEC-specific murine nephrin promoter. Injury by administration of antibody against the glomerular basement membrane (anti-GBM) to transgenic (TG) mice with GEC-targeted hHO-1 was attenuated compared with wild-type (WT) controls. To explore changes in the expression of genes that could mediate this salutary effect, we performed gene expression profiling using a microarray analysis of RNA isolated from the renal cortex of WT or TG mice with or without anti-GBM antibody-induced injury. Significant increases in expression were detected in 9 major histocompatibility complex (MHC)-class II genes, 2 interferon-γ (IFN-γ)-inducible guanosine triphosphate (GTP)ases, and 3 genes of the ubiquitin-proteasome system. The increase in MHC-class II and proteasome gene expression in TG mice with injury was validated by real-time polymerase chain reaction (PCR) or Western blot analysis. The observations point to novel mechanisms underlying the cytoprotective effect of HO-1 in renal immune injury. Copyright © 2011. Published by Mosby, Inc.

Strigolactone-Induced Putative Secreted Protein 1 Is Required for the Establishment of Symbiosis by the Arbuscular Mycorrhizal Fungus Rhizophagus irregularis.

PubMed

Tsuzuki, Syusaku; Handa, Yoshihiro; Takeda, Naoya; Kawaguchi, Masayoshi

2016-04-01

Arbuscular mycorrhizal (AM) symbiosis is the most widespread association between plants and fungi. To provide novel insights into the molecular mechanisms of AM symbiosis, we screened and investigated genes of the AM fungus Rhizophagus irregularis that contribute to the infection of host plants. R. irregularis genes involved in the infection were explored by RNA-sequencing (RNA-seq) analysis. One of the identified genes was then characterized by a reverse genetic approach using host-induced gene silencing (HIGS), which causes RNA interference in the fungus via the host plant. The RNA-seq analysis revealed that 19 genes are up-regulated by both treatment with strigolactone (SL) (a plant symbiotic signal) and symbiosis. Eleven of the 19 genes were predicted to encode secreted proteins and, of these, SL-induced putative secreted protein 1 (SIS1) showed the largest induction under both conditions. In hairy roots of Medicago truncatula, SIS1 expression is knocked down by HIGS, resulting in significant suppression of colonization and formation of stunted arbuscules. These results suggest that SIS1 is a putative secreted protein that is induced in a wide spatiotemporal range including both the presymbiotic and symbiotic stages and that SIS1 positively regulates colonization of host plants by R. irregularis.

Knockdown of the schizophrenia susceptibility gene TCF4 alters gene expression and proliferation of progenitor cells from the developing human neocortex.

PubMed

Hill, Matthew J; Killick, Richard; Navarrete, Katherinne; Maruszak, Aleksandra; McLaughlin, Gemma M; Williams, Brenda P; Bray, Nicholas J

2017-05-01

Common variants in the TCF4 gene are among the most robustly supported genetic risk factors for schizophrenia. Rare TCF4 deletions and loss-of-function point mutations cause Pitt-Hopkins syndrome, a developmental disorder associated with severe intellectual disability. To explore molecular and cellular mechanisms by which TCF4 perturbation could interfere with human cortical development, we experimentally reduced the endogenous expression of TCF4 in a neural progenitor cell line derived from the developing human cerebral cortex using RNA interference. Effects on genome-wide gene expression were assessed by microarray, followed by Gene Ontology and pathway analysis of differentially expressed genes. We tested for genetic association between the set of differentially expressed genes and schizophrenia using genome-wide association study data from the Psychiatric Genomics Consortium and competitive gene set analysis (MAGMA). Effects on cell proliferation were assessed using high content imaging. Genes that were differentially expressed following TCF4 knockdown were highly enriched for involvement in the cell cycle. There was a nonsignificant trend for genetic association between the differentially expressed gene set and schizophrenia. Consistent with the gene expression data, TCF4 knockdown was associated with reduced proliferation of cortical progenitor cells in vitro. A detailed mechanistic explanation of how TCF4 knockdown alters human neural progenitor cell proliferation is not provided by this study. Our data indicate effects of TCF4 perturbation on human cortical progenitor cell proliferation, a process that could contribute to cognitive deficits in individuals with Pitt-Hopkins syndrome and risk for schizophrenia.

[Analysis of tissue-specific differentially methylated genes with differential gene expression in non-small cell lung cancer].

PubMed

Yin, L G; Zou, Z Q; Zhao, H Y; Zhang, C L; Shen, J G; Qi, L; Qi, M; Xue, Z Q

2014-01-01

Adenocarcinoma (ADC) and squamous cell carcinomas (SCC) are two subtypes of non-small cell lung carcinomas which are regarded as the leading cause of cancer-related malignancy worldwide. The aim of this study is to detect the differentially methylated loci (DMLs) and differentially methylated genes (DMGs) of these two tumor sets, and then to illustrate the different expression level of specific methylated genes. Using TCGA database and Illumina HumanMethylation 27 arrays, we first screened the DMGs and DMLs in tumor samples. Then, we explored the BiologicalProcess terms of hypermethylated and hypomethylated genes using Functional Gene Ontology (GO) catalogues. Hypermethylation intensively occurred in CpG-island, whereas hypomethylation was located in non-CpG-island. Most SCC and ADC hypermethylated genes involved GO function of DNA dependenit regulation of transcription, and hypomethylated genes mainly 'enriched in the term of immune responses. Additionally, the expression level of specific differentially methylated genesis distinctbetween ADC and SCC. It is concluded that ADC and SCC have different methylated status that might play an important role in carcinogenesis.

Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

PubMed Central

Liu, Li; Sabo, Aniko; Neale, Benjamin M.; Nagaswamy, Uma; Stevens, Christine; Lim, Elaine; Bodea, Corneliu A.; Muzny, Donna; Reid, Jeffrey G.; Banks, Eric; Coon, Hillary; DePristo, Mark; Dinh, Huyen; Fennel, Tim; Flannick, Jason; Gabriel, Stacey; Garimella, Kiran; Gross, Shannon; Hawes, Alicia; Lewis, Lora; Makarov, Vladimir; Maguire, Jared; Newsham, Irene; Poplin, Ryan; Ripke, Stephan; Shakir, Khalid; Samocha, Kaitlin E.; Wu, Yuanqing; Boerwinkle, Eric; Buxbaum, Joseph D.; Cook, Edwin H.; Devlin, Bernie; Schellenberg, Gerard D.; Sutcliffe, James S.; Daly, Mark J.; Gibbs, Richard A.; Roeder, Kathryn

2013-01-01

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD. PMID:23593035

Towards understanding the breast cancer epigenome: a comparison of genome-wide DNA methylation and gene expression data

PubMed Central

Michiels, Stefan; Metzger-Filho, Otto; Saini, Kamal S.

2016-01-01

Until recently, an elevated disease risk has been ascribed to a genetic predisposition, however, exciting progress over the past years has discovered alternate elements of inheritance that involve epigenetic regulation. Epigenetic changes are heritably stable alterations that include DNA methylation, histone modifications and RNA-mediated silencing. Aberrant DNA methylation is a common molecular basis for a number of important human diseases, including breast cancer. Changes in DNA methylation profoundly affect global gene expression patterns. What is emerging is a more dynamic and complex association between DNA methylation and gene expression than previously believed. Although many tools have already been developed for analyzing genome-wide gene expression data, tools for analyzing genome-wide DNA methylation have not yet reached the same level of refinement. Here we provide an in-depth analysis of DNA methylation in parallel with gene expression data characteristics and describe the particularities of low-level and high-level analyses of DNA methylation data. Low-level analysis refers to pre-processing of methylation data (i.e. normalization, transformation and filtering), whereas high-level analysis is focused on illustrating the application of the widely used class comparison, class prediction and class discovery methods to DNA methylation data. Furthermore, we investigate the influence of DNA methylation on gene expression by measuring the correlation between the degree of CpG methylation and the level of expression and to explore the pattern of methylation as a function of the promoter region. PMID:26657508

Towards understanding the breast cancer epigenome: a comparison of genome-wide DNA methylation and gene expression data.

PubMed

Singhal, Sandeep K; Usmani, Nawaid; Michiels, Stefan; Metzger-Filho, Otto; Saini, Kamal S; Kovalchuk, Olga; Parliament, Matthew

2016-01-19

Until recently, an elevated disease risk has been ascribed to a genetic predisposition, however, exciting progress over the past years has discovered alternate elements of inheritance that involve epigenetic regulation. Epigenetic changes are heritably stable alterations that include DNA methylation, histone modifications and RNA-mediated silencing. Aberrant DNA methylation is a common molecular basis for a number of important human diseases, including breast cancer. Changes in DNA methylation profoundly affect global gene expression patterns. What is emerging is a more dynamic and complex association between DNA methylation and gene expression than previously believed. Although many tools have already been developed for analyzing genome-wide gene expression data, tools for analyzing genome-wide DNA methylation have not yet reached the same level of refinement. Here we provide an in-depth analysis of DNA methylation in parallel with gene expression data characteristics and describe the particularities of low-level and high-level analyses of DNA methylation data. Low-level analysis refers to pre-processing of methylation data (i.e. normalization, transformation and filtering), whereas high-level analysis is focused on illustrating the application of the widely used class comparison, class prediction and class discovery methods to DNA methylation data. Furthermore, we investigate the influence of DNA methylation on gene expression by measuring the correlation between the degree of CpG methylation and the level of expression and to explore the pattern of methylation as a function of the promoter region.

Whole transcriptome analysis of the fasting and fed Burmese python heart: insights into extreme physiological cardiac adaptation.

PubMed

Wall, Christopher E; Cozza, Steven; Riquelme, Cecilia A; McCombie, W Richard; Heimiller, Joseph K; Marr, Thomas G; Leinwand, Leslie A

2011-01-01

The infrequently feeding Burmese python (Python molurus) experiences significant and rapid postprandial cardiac hypertrophy followed by regression as digestion is completed. To begin to explore the molecular mechanisms of this response, we have sequenced and assembled the fasted and postfed Burmese python heart transcriptomes with Illumina technology using the chicken (Gallus gallus) genome as a reference. In addition, we have used RNA-seq analysis to identify differences in the expression of biological processes and signaling pathways between fasted, 1 day postfed (DPF), and 3 DPF hearts. Out of a combined transcriptome of ∼2,800 mRNAs, 464 genes were differentially expressed. Genes showing differential expression at 1 DPF compared with fasted were enriched for biological processes involved in metabolism and energetics, while genes showing differential expression at 3 DPF compared with fasted were enriched for processes involved in biogenesis, structural remodeling, and organization. Moreover, we present evidence for the activation of physiological and not pathological signaling pathways in this rapid, novel model of cardiac growth in pythons. Together, our data provide the first comprehensive gene expression profile for a reptile heart.

FUNDAMENTALS OF VITAMIN D HORMONE-REGULATED GENE EXPRESSION

PubMed Central

Pike, J. Wesley; Meyer, Mark B.

2014-01-01

Initial research focused upon several known genetic targets provided early insight into the mechanism of action of the vitamin D hormone (1,25-dihydroxyvitamin D3 (1,25(OH)2D3)). Recently, however, a series of technical advances involving the coupling of chromatin immunoprecipitation (ChIP) to unbiased methodologies that initially involved tiled DNA microarrays (ChIP-chip analysis) and now Next Generation DNA Sequencing techniques (ChIP-Seq analysis) has opened new avenues of research into the mechanisms through which 1,25(OH)2D3 regulates gene expression. In this review, we summarize briefly the results of this early work and then focus on more recent studies in which ChIP-chip and ChIP-seq analyses have been used to explore the mechanisms of 1,25(OH)2D3 action on a genome-wide scale providing specific target genes as examples. The results of this work have advanced our understanding of the mechanisms involved at both genetic and epigenetic levels and have revealed a series of new principles through which the vitamin D hormone functions to control the expression of genes. PMID:24239506

Hierarchy within the mammary STAT5-driven Wap super-enhancer.

PubMed

Shin, Ha Youn; Willi, Michaela; HyunYoo, Kyung; Zeng, Xianke; Wang, Chaochen; Metser, Gil; Hennighausen, Lothar

2016-08-01

Super-enhancers comprise dense transcription factor platforms highly enriched for active chromatin marks. A paucity of functional data led us to investigate the role of super-enhancers in the mammary gland, an organ characterized by exceptional gene regulatory dynamics during pregnancy. ChIP-seq analysis for the master regulator STAT5A, the glucocorticoid receptor, H3K27ac and MED1 identified 440 mammary-specific super-enhancers, half of which were associated with genes activated during pregnancy. We interrogated the Wap super-enhancer, generating mice carrying mutations in STAT5-binding sites within its constituent enhancers. Individually, the most distal site displayed the greatest enhancer activity. However, combinatorial mutation analysis showed that the 1,000-fold induction in gene expression during pregnancy relied on all enhancers. Disabling the binding sites of STAT5, NFIB and ELF5 in the proximal enhancer incapacitated the entire super-enhancer. Altogether, these data suggest a temporal and functional enhancer hierarchy. The identification of mammary-specific super-enhancers and the mechanistic exploration of the Wap locus provide insights into the regulation of cell-type-specific expression of hormone-sensing genes.

The evolutionary landscape of intergenic trans-splicing events in insects

PubMed Central

Kong, Yimeng; Zhou, Hongxia; Yu, Yao; Chen, Longxian; Hao, Pei; Li, Xuan

2015-01-01

To explore the landscape of intergenic trans-splicing events and characterize their functions and evolutionary dynamics, we conduct a mega-data study of a phylogeny containing eight species across five orders of class Insecta, a model system spanning 400 million years of evolution. A total of 1,627 trans-splicing events involving 2,199 genes are identified, accounting for 1.58% of the total genes. Homology analysis reveals that mod(mdg4)-like trans-splicing is the only conserved event that is consistently observed in multiple species across two orders, which represents a unique case of functional diversification involving trans-splicing. Thus, evolutionarily its potential for generating proteins with novel function is not broadly utilized by insects. Furthermore, 146 non-mod trans-spliced transcripts are found to resemble canonical genes from different species. Trans-splicing preserving the function of ‘breakup' genes may serve as a general mechanism for relaxing the constraints on gene structure, with profound implications for the evolution of genes and genomes. PMID:26521696

Integration of lncRNA and mRNA Transcriptome Analyses Reveals Genes and Pathways Potentially Involved in Calf Intestinal Growth and Development during the Early Weeks of Life

PubMed Central

Do, Duy N.; Dudemaine, Pier-Luc; Fomenky, Bridget E.

2018-01-01

A better understanding of the factors that regulate growth and immune response of the gastrointestinal tract (GIT) of calves will promote informed management practices in calf rearing. This study aimed to explore genomics (messenger RNA (mRNA)) and epigenomics (long non-coding RNA (lncRNA)) mechanisms regulating the development of the rumen and ileum in calves. Thirty-two calves (≈5-days-old) were reared for 96 days following standard procedures. Sixteen calves were humanely euthanized on experiment day 33 (D33) (pre-weaning) and another 16 on D96 (post-weaning) for collection of ileum and rumen tissues. RNA from tissues was subjected to next generation sequencing and 3310 and 4217 mRNAs were differentially expressed (DE) between D33 and D96 in ileum and rumen tissues, respectively. Gene ontology and pathways enrichment of DE genes confirmed their roles in developmental processes, immunity and lipid metabolism. A total of 1568 (63 known and 1505 novel) and 4243 (88 known and 4155 novel) lncRNAs were detected in ileum and rumen tissues, respectively. Cis target gene analysis identified BMPR1A, an important gene for a GIT disease (juvenile polyposis syndrome) in humans, as a candidate cis target gene for lncRNAs in both tissues. LncRNA cis target gene enrichment suggested that lncRNAs might regulate growth and development in both tissues as well as posttranscriptional gene silencing by RNA or microRNA processing in rumen, or disease resistance mechanisms in ileum. This study provides a catalog of bovine lncRNAs and set a baseline for exploring their functions in calf GIT development. PMID:29510583

Integration of lncRNA and mRNA Transcriptome Analyses Reveals Genes and Pathways Potentially Involved in Calf Intestinal Growth and Development during the Early Weeks of Life.

PubMed

Ibeagha-Awemu, Eveline M; Do, Duy N; Dudemaine, Pier-Luc; Fomenky, Bridget E; Bissonnette, Nathalie

2018-03-05

A better understanding of the factors that regulate growth and immune response of the gastrointestinal tract (GIT) of calves will promote informed management practices in calf rearing. This study aimed to explore genomics (messenger RNA (mRNA)) and epigenomics (long non-coding RNA (lncRNA)) mechanisms regulating the development of the rumen and ileum in calves. Thirty-two calves (≈5-days-old) were reared for 96 days following standard procedures. Sixteen calves were humanely euthanized on experiment day 33 (D33) (pre-weaning) and another 16 on D96 (post-weaning) for collection of ileum and rumen tissues. RNA from tissues was subjected to next generation sequencing and 3310 and 4217 mRNAs were differentially expressed (DE) between D33 and D96 in ileum and rumen tissues, respectively. Gene ontology and pathways enrichment of DE genes confirmed their roles in developmental processes, immunity and lipid metabolism. A total of 1568 (63 known and 1505 novel) and 4243 (88 known and 4155 novel) lncRNAs were detected in ileum and rumen tissues, respectively. Cis target gene analysis identified BMPR1A , an important gene for a GIT disease (juvenile polyposis syndrome) in humans, as a candidate cis target gene for lncRNAs in both tissues. LncRNA cis target gene enrichment suggested that lncRNAs might regulate growth and development in both tissues as well as posttranscriptional gene silencing by RNA or microRNA processing in rumen, or disease resistance mechanisms in ileum. This study provides a catalog of bovine lncRNAs and set a baseline for exploring their functions in calf GIT development.

Interactive Effects of in Utero Nutrition and Genetic Inheritance on Cognition: New Evidence Using Sibling Comparisons1

PubMed Central

Cook, C. Justin; Fletcher, Jason M.

2013-01-01

A large literature links early environments and later outcomes, such as cognition; however, little is known about the mechanisms. One potential mechanism is sensitivity to early environments that is moderated or amplified by the genotype. With this mechanism in mind, a complementary literature outside economics examines the interaction between genes and environments, but often problems of endogeneity and bias in estimation are uncorrected. A key issue in the literature is exploring environmental variation that is not exogenous, which is potentially problematic if there are gene-environment correlation or gene-gene interactions. Using sibling pairs with genetic data in the Wisconsin Longitudinal Study we extend a previous, and widely cited, gene-environment study that explores an interaction between the FADS2 gene, which is associated with the processing of essential fatty acids related to cognitive development, and early life nutrition in explaining later-life IQ. Our base OLS findings suggest that individuals with specific FADS2 variants gain roughly 0.15 standard deviations in IQ for each standard deviation increase in birth weight, our measure of the early nutrition environment; while, individuals with other variants of FADS2 do not have a statistically significant association with early nutrition, implying the genotype is influencing the effects of environmental exposure. When including family-level fixed effects, however, the magnitude of the gene-environment interaction is reduced by half and statistical significance dissipates, implying the interaction between FADS2 and early nutrition in explaining later life IQ may in part be due to unobserved, family-level factors. The example has wider implications for the practice of investigating gene-environment interactions when the environmental exposure is not exogenous and robustness to unobserved variation in the genome is not controlled for in the analysis. PMID:24172871

Clinical value of miR-182-5p in lung squamous cell carcinoma: a study combining data from TCGA, GEO, and RT-qPCR validation.

PubMed

Luo, Jie; Shi, Ke; Yin, Shu-Ya; Tang, Rui-Xue; Chen, Wen-Jie; Huang, Lin-Zhen; Gan, Ting-Qing; Cai, Zheng-Wen; Chen, Gang

2018-04-10

MiR-182-5p, as a member of miRNA family, can be detected in lung cancer and plays an important role in lung cancer. To explore the clinical value of miR-182-5p in lung squamous cell carcinoma (LUSC) and to unveil the molecular mechanism of LUSC. The clinical value of miR-182-5p in LUSC was investigated by collecting and calculating data from The Cancer Genome Atlas (TCGA) database, the Gene Expression Omnibus (GEO) database, and real-time quantitative polymerase chain reaction (RT-qPCR). Twelve prediction platforms were used to predict the target genes of miR-182-5p. Protein-protein interaction (PPI) networks and gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to explore the molecular mechanism of LUSC. The expression of miR-182-5p was significantly over-expressed in LUSC than in non-cancerous tissues, as evidenced by various approaches, including the TCGA database, GEO microarrays, RT-qPCR, and a comprehensive meta-analysis of 501 LUSC cases and 148 non-cancerous cases. Furthermore, a total of 81 potential target genes were chosen from the union of predicted genes and the TCGA database. GO and KEGG analyses demonstrated that the target genes are involved in pathways related to biological processes. PPIs revealed the relationships between these genes, with EPAS1, PRKCE, NR3C1, and RHOB being located in the center of the PPI network. MiR-182-5p upregulation greatly contributes to LUSC and may serve as a biomarker in LUSC.

Integrative View of α2,3-Sialyltransferases (ST3Gal) Molecular and Functional Evolution in Deuterostomes: Significance of Lineage-Specific Losses

PubMed Central

Petit, Daniel; Teppa, Elin; Mir, Anne-Marie; Vicogne, Dorothée; Thisse, Christine; Thisse, Bernard; Filloux, Cyril; Harduin-Lepers, Anne

2015-01-01

Sialyltransferases are responsible for the synthesis of a diverse range of sialoglycoconjugates predicted to be pivotal to deuterostomes’ evolution. In this work, we reconstructed the evolutionary history of the metazoan α2,3-sialyltransferases family (ST3Gal), a subset of sialyltransferases encompassing six subfamilies (ST3Gal I–ST3Gal VI) functionally characterized in mammals. Exploration of genomic and expressed sequence tag databases and search of conserved sialylmotifs led to the identification of a large data set of st3gal-related gene sequences. Molecular phylogeny and large scale sequence similarity network analysis identified four new vertebrate subfamilies called ST3Gal III-r, ST3Gal VII, ST3Gal VIII, and ST3Gal IX. To address the issue of the origin and evolutionary relationships of the st3gal-related genes, we performed comparative syntenic mapping of st3gal gene loci combined to ancestral genome reconstruction. The ten vertebrate ST3Gal subfamilies originated from genome duplication events at the base of vertebrates and are organized in three distinct and ancient groups of genes predating the early deuterostomes. Inferring st3gal gene family history identified also several lineage-specific gene losses, the significance of which was explored in a functional context. Toward this aim, spatiotemporal distribution of st3gal genes was analyzed in zebrafish and bovine tissues. In addition, molecular evolutionary analyses using specificity determining position and coevolved amino acid predictions led to the identification of amino acid residues with potential implication in functional divergence of vertebrate ST3Gal. We propose a detailed scenario of the evolutionary relationships of st3gal genes coupled to a conceptual framework of the evolution of ST3Gal functions. PMID:25534026

Analysis tools for the interplay between genome layout and regulation.

PubMed

Bouyioukos, Costas; Elati, Mohamed; Képès, François

2016-06-06

Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes. Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation. SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information. We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation.

Differentially Coexpressed Disease Gene Identification Based on Gene Coexpression Network.

PubMed

Jiang, Xue; Zhang, Han; Quan, Xiongwen

2016-01-01

Screening disease-related genes by analyzing gene expression data has become a popular theme. Traditional disease-related gene selection methods always focus on identifying differentially expressed gene between case samples and a control group. These traditional methods may not fully consider the changes of interactions between genes at different cell states and the dynamic processes of gene expression levels during the disease progression. However, in order to understand the mechanism of disease, it is important to explore the dynamic changes of interactions between genes in biological networks at different cell states. In this study, we designed a novel framework to identify disease-related genes and developed a differentially coexpressed disease-related gene identification method based on gene coexpression network (DCGN) to screen differentially coexpressed genes. We firstly constructed phase-specific gene coexpression network using time-series gene expression data and defined the conception of differential coexpression of genes in coexpression network. Then, we designed two metrics to measure the value of gene differential coexpression according to the change of local topological structures between different phase-specific networks. Finally, we conducted meta-analysis of gene differential coexpression based on the rank-product method. Experimental results demonstrated the feasibility and effectiveness of DCGN and the superior performance of DCGN over other popular disease-related gene selection methods through real-world gene expression data sets.

CellMiner Companion: an interactive web application to explore CellMiner NCI-60 data.

PubMed

Wang, Sufang; Gribskov, Michael; Hazbun, Tony R; Pascuzzi, Pete E

2016-08-01

The NCI-60 human tumor cell line panel is an invaluable resource for cancer researchers, providing drug sensitivity, molecular and phenotypic data for a range of cancer types. CellMiner is a web resource that provides tools for the acquisition and analysis of quality-controlled NCI-60 data. CellMiner supports queries of up to 150 drugs or genes, but the output is an Excel file for each drug or gene. This output format makes it difficult for researchers to explore the data from large queries. CellMiner Companion is a web application that facilitates the exploration and visualization of output from CellMiner, further increasing the accessibility of NCI-60 data. The web application is freely accessible at https://pul-bioinformatics.shinyapps.io/CellMinerCompanion The R source code can be downloaded at https://github.com/pepascuzzi/CellMinerCompanion.git ppascuzz@purdue.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

[Gene deletion and functional analysis of the heptyl glycosyltransferase (waaF) gene in Vibrio parahemolyticus O-antigen cluster].

PubMed

Zhao, Feng; Meng, Songsong; Zhou, Deqing

2016-02-04

To construct heptyl glycosyltransferase gene II (waaF) gene deletion mutant of Vibrio parahaemolyticus, and explore the function of the waaF gene in Vibrio parahaemolyticus. The waaF gene deletion mutant was constructed by chitin-based transformation technology using clinical isolates, and then the growth rate, morphology and serotypes were identified. The different sources (O3, O5 and O10) waaF gene complementations were constructed through E. coli S17λpir strains conjugative transferring with Vibrio parahaemolyticus, and the function of the waaF gene was further verified by serotypes. The waaF gene deletion mutant strain was successfully constructed and it grew normally. The growth rate and morphology of mutant were similar with the wild type strains (WT), but the mutant could not occurred agglutination reaction with O antisera. The O3 and O5 sources waaF gene complementations occurred agglutination reaction with O antisera, but the O10 sources waaF gene complementations was not. The waaF gene was related with O-antigen synthesis and it was the key gene of O-antigen synthesis pathway in Vibrio parahaemolyticus. The function of different sources waaF gene were not the same.

An evidence-based knowledgebase of metastasis suppressors to identify key pathways relevant to cancer metastasis

PubMed Central

Zhao, Min; Li, Zhe; Qu, Hong

2015-01-01

Metastasis suppressor genes (MS genes) are genes that play important roles in inhibiting the process of cancer metastasis without preventing growth of the primary tumor. Identification of these genes and understanding their functions are critical for investigation of cancer metastasis. Recent studies on cancer metastasis have identified many new susceptibility MS genes. However, the comprehensive illustration of diverse cellular processes regulated by metastasis suppressors during the metastasis cascade is lacking. Thus, the relationship between MS genes and cancer risk is still unclear. To unveil the cellular complexity of MS genes, we have constructed MSGene (http://MSGene.bioinfo-minzhao.org/), the first literature-based gene resource for exploring human MS genes. In total, we manually curated 194 experimentally verified MS genes and mapped to 1448 homologous genes from 17 model species. Follow-up functional analyses associated 194 human MS genes with epithelium/tissue morphogenesis and epithelia cell proliferation. In addition, pathway analysis highlights the prominent role of MS genes in activation of platelets and coagulation system in tumor metastatic cascade. Moreover, global mutation pattern of MS genes across multiple cancers may reveal common cancer metastasis mechanisms. All these results illustrate the importance of MSGene to our understanding on cell development and cancer metastasis. PMID:26486520

Analysis of functional polymorphisms in three synaptic plasticity-related genes (BDNF, COMT AND UCHL1) in Alzheimer's disease in Colombia.

PubMed

Forero, Diego A; Benítez, Bruno; Arboleda, Gonzalo; Yunis, Juan J; Pardo, Rodrigo; Arboleda, Humberto

2006-07-01

In recent years, it has been proposed that synaptic dysfunction may be an important etiological factor for Alzheimer's disease (AD). This hypothesis has important implications for the analysis of AD genetic risk in case-control studies. In the present work, we analyzed common functional polymorphisms in three synaptic plasticity-related genes (brain-derived neurotrophic factor, BDNF Val66Met; catechol-O-methyl transferase, COMT Val158; ubiquitin carboxyl-terminal hydroxylase, UCHL1 S18Y) in a sample of 102 AD cases and 168 age and sex matched controls living in Bogotá, Colombia. There was not association between UCHL1 polymorphism and AD in our sample. We have found an initial association with BDNF polymorphism in familial cases and with COMT polymorphism in male and sporadic patients. These initial associations were lost after Bonferroni correction for multiple testing. Unadjusted results may be compatible with the expected functional effect of variations in these genes on pathological memory and cognitive dysfunction, as has been implicated in animal and cell models and also from neuropsychological analysis of normal subjects carriers of the AD associated genotypes. An exploration of functional variants in these and in other synaptic plasticity-related genes (a synaptogenomics approach) in independent larger samples will be important to discover new genes associated with AD.

Pathway-based variant enrichment analysis on the example of dilated cardiomyopathy.

PubMed

Backes, Christina; Meder, Benjamin; Lai, Alan; Stoll, Monika; Rühle, Frank; Katus, Hugo A; Keller, Andreas

2016-01-01

Genome-wide association (GWA) studies have significantly contributed to the understanding of human genetic variation and its impact on clinical traits. Frequently only a limited number of highly significant associations were considered as biologically relevant. Increasingly, network analysis of affected genes is used to explore the potential role of the genetic background on disease mechanisms. Instead of first determining affected genes or calculating scores for genes and performing pathway analysis on the gene level, we integrated both steps and directly calculated enrichment on the genetic variant level. The respective approach has been tested on dilated cardiomyopathy (DCM) GWA data as showcase. To compute significance values, 5000 permutation tests were carried out and p values were adjusted for multiple testing. For 282 KEGG pathways, we computed variant enrichment scores and significance values. Of these, 65 were significant. Surprisingly, we discovered the "nucleotide excision repair" and "tuberculosis" pathways to be most significantly associated with DCM (p = 10(-9)). The latter pathway is driven by genes of the HLA-D antigen group, a finding that closely resembles previous discoveries made by expression quantitative trait locus analysis in the context of DCM-GWA. Next, we implemented a sub-network-based analysis, which searches for affected parts of KEGG, however, independent on the pre-defined pathways. Here, proteins of the contractile apparatus of cardiac cells as well as the FAS sub-network were found to be affected by common polymorphisms in DCM. In this work, we performed enrichment analysis directly on variants, leveraging the potential to discover biological information in thousands of published GWA studies. The applied approach is cutoff free and considers a ranked list of genetic variants as input.

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Tabatabaei, Seyyed Mohammad; Namaki, Saeed

2016-01-01

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets. PMID:28028462

Identification and Validation of Reference Genes for RT-qPCR Analysis in Non-Heading Chinese Cabbage Flowers

PubMed Central

Wang, Cheng; Cui, Hong-Mi; Huang, Tian-Hong; Liu, Tong-Kun; Hou, Xi-Lin; Li, Ying

2016-01-01

Non-heading Chinese cabbage (Brassica rapa ssp. chinensis Makino) is an important vegetable member of Brassica rapa crops. It exhibits a typical sporophytic self-incompatibility (SI) system and is an ideal model plant to explore the mechanism of SI. Gene expression research are frequently used to unravel the complex genetic mechanism and in such studies appropriate reference selection is vital. Validation of reference genes have neither been conducted in Brassica rapa flowers nor in SI trait. In this study, 13 candidate reference genes were selected and examined systematically in 96 non-heading Chinese cabbage flower samples that represent four strategic groups in compatible and self-incompatible lines of non-heading Chinese cabbage. Two RT-qPCR analysis software, geNorm and NormFinder, were used to evaluate the expression stability of these genes systematically. Results revealed that best-ranked references genes should be selected according to specific sample subsets. DNAJ, UKN1, and PP2A were identified as the most stable reference genes among all samples. Moreover, our research further revealed that the widely used reference genes, CYP and ACP, were the least suitable reference genes in most non-heading Chinese cabbage flower sample sets. To further validate the suitability of the reference genes identified in this study, the expression level of SRK and Exo70A1 genes which play important roles in regulating interaction between pollen and stigma were studied. Our study presented the first systematic study of reference gene(s) selection for SI study and provided guidelines to obtain more accurate RT-qPCR results in non-heading Chinese cabbage. PMID:27375663

Solexa-Sequencing Based Transcriptome Study of Plaice Skin Phenotype in Rex Rabbits (Oryctolagus cuniculus)

PubMed Central

Pan, Lei; Liu, Yan; Wei, Qiang; Xiao, Chenwen; Ji, Quanan; Bao, Guolian; Wu, Xinsheng

2015-01-01

Background Fur is an important genetically-determined characteristic of domestic rabbits; rabbit furs are of great economic value. We used the Solexa sequencing technology to assess gene expression in skin tissues from full-sib Rex rabbits of different phenotypes in order to explore the molecular mechanisms associated with fur determination. Methodology/Principal Findings Transcriptome analysis included de novo assembly, gene function identification, and gene function classification and enrichment. We obtained 74,032,912 and 71,126,891 short reads of 100 nt, which were assembled into 377,618 unique sequences by Trinity strategy (N50=680 nt). Based on BLAST results with known proteins, 50,228 sequences were identified at a cut-off E-value ≥ 10-5. Using Blast to Gene Ontology (GO), Clusters of Orthologous Groups (KOG) and Kyoto Encyclopedia of Genes and Genomes (KEGG), we obtained several genes with important protein functions. A total of 308 differentially expressed genes were obtained by transcriptome analysis of plaice and un-plaice phenotype animals; 209 additional differentially expressed genes were not found in any database. These genes included 49 that were only expressed in plaice skin rabbits. The novel genes may play important roles during skin growth and development. In addition, 99 known differentially expressed genes were assigned to PI3K-Akt signaling, focal adhesion, and ECM-receptor interactin, among others. Growth factors play a role in skin growth and development by regulating these signaling pathways. We confirmed the altered expression levels of seven target genes by qRT-PCR. And chosen a key gene for SNP to found the differentially between plaice and un-plaice phenotypes rabbit. Conclusions/Significance The rabbit transcriptome profiling data provide new insights in understanding the molecular mechanisms underlying rabbit skin growth and development. PMID:25955442

Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs.

PubMed

Jouffe, Vincent; Rowe, Suzanne; Liaubet, Laurence; Buitenhuis, Bart; Hornshøj, Henrik; SanCristobal, Magali; Mormède, Pierre; de Koning, D J

2009-07-16

Microarray studies can supplement QTL studies by suggesting potential candidate genes in the QTL regions, which by themselves are too large to provide a limited selection of candidate genes. Here we provide a case study where we explore ways to integrate QTL data and microarray data for the pig, which has only a partial genome sequence. We outline various procedures to localize differentially expressed genes on the pig genome and link this with information on published QTL. The starting point is a set of 237 differentially expressed cDNA clones in adrenal tissue from two pig breeds, before and after treatment with adrenocorticotropic hormone (ACTH). Different approaches to localize the differentially expressed (DE) genes to the pig genome showed different levels of success and a clear lack of concordance for some genes between the various approaches. For a focused analysis on 12 genes, overlapping QTL from the public domain were presented. Also, differentially expressed genes underlying QTL for ACTH response were described. Using the latest version of the draft sequence, the differentially expressed genes were mapped to the pig genome. This enabled co-location of DE genes and previously studied QTL regions, but the draft genome sequence is still incomplete and will contain many errors. A further step to explore links between DE genes and QTL at the pathway level was largely unsuccessful due to the lack of annotation of the pig genome. This could be improved by further comparative mapping analyses but this would be time consuming. This paper provides a case study for the integration of QTL data and microarray data for a species with limited genome sequence information and annotation. The results illustrate the challenges that must be addressed but also provide a roadmap for future work that is applicable to other non-model species.

Is the Val66Met polymorphism of the brain-derived neurotrophic factor gene associated with panic disorder? A meta-analysis.

PubMed

Chen, Kaiyuan; Wang, Na; Zhang, Jie; Hong, Xiaohong; Xu, Haiyun; Zhao, Xiaofeng; Huang, Qingjun

2017-06-01

Although emerging evidence has suggested an association between the Val66Met (rs6265) polymorphisms in brain-derived neurotrophic factor (BDNF) gene and the panic disorder, the conclusion is inclusive given the mixed results. This meta-analysis reviewed and analyzed the recent studies addressing the potential association between the Val66Met polymorphisms and panic disorder susceptibility. Related case-control studies were retrieved by database searching and selected according to established inclusion criteria. Six articles were identified, which explored the association between the BDNF Val66Met polymorphism and panic disorder. Statistical analyses revealed no association for the allele contrast and the dominant model. However, the recessive model showed a significant association between the BDNF Val66Met polymorphism and panic disorder (odds ratio = 1.26, 95% confidence interval = 1.04-1.52, z = 2.39, P = 0.02). Despite of some limitations, this meta-analysis suggests that the Val66Met polymorphism of BDNF gene is a susceptibility factor for panic disorder. © 2015 Wiley Publishing Asia Pty Ltd.

Genome-wide analysis of tandem repeats in plants and green algae

Treesearch

Zhixin Zhao; Cheng Guo; Sreeskandarajan Sutharzan; Pei Li; Craig Echt; Jie Zhang; Chun Liang

2014-01-01

Tandem repeats (TRs) extensively exist in the genomes of prokaryotes and eukaryotes. Based on the sequenced genomes and gene annotations of 31 plant and algal species in Phytozome version 8.0 (http://www.phytozome.net/), we examined TRs in a genome-wide scale, characterized their distributions and motif features, and explored their putative biological functions. Among...

Interaction of Dopamine Transporter (DAT1) Genotype and Maltreatment for ADHD: A Latent Class Analysis

ERIC Educational Resources Information Center

Li, James J.; Lee, Steve S.

2012-01-01

Background: Although the association of the dopamine transporter (DAT1) gene and attention-deficit/hyperactivity disorder (ADHD) has been widely studied, far less is known about its potential interaction with environmental risk factors. Given that maltreatment is a replicated risk factor for ADHD, we explored the interaction between DAT1 and…

A Twin and Adoption Study of Reading Achievement: Exploration of Shared-Environmental and Gene-Environment-Interaction Effects

ERIC Educational Resources Information Center

Kirkpatrick, Robert M.; Legrand, Lisa N.; Iacono, William G.; McGue, Matt

2011-01-01

Existing behavior-genetic research implicates substantial influence of heredity and modest influence of shared environment on reading achievement and reading disability. Applying DeFries-Fulker analysis to a combined sample of twins and adoptees (N = 4886, including 266 reading-disabled probands), the present study replicates prior findings of…

Global transcriptome analysis of the maize (Zea mays L.) inbred line 08LF during leaf senescence initiated by pollination-prevention.

PubMed

Wu, Liancheng; Li, Mingna; Tian, Lei; Wang, Shunxi; Wu, Liuji; Ku, Lixia; Zhang, Jun; Song, Xiaoheng; Liu, Haiping; Chen, Yanhui

2017-01-01

In maize (Zea mays), leaf senescence acts as a nutrient recycling process involved in proteins, lipids, and nucleic acids degradation and transport to the developing sink. However, the molecular mechanisms of pre-maturation associated with pollination-prevention remain unclear in maize. To explore global gene expression changes during the onset and progression of senescence in maize, the inbred line 08LF, with severe early senescence caused by pollination prevention, was selected. Phenotypic observation showed that the onset of leaf senescence of 08LF plants occurred approximately 14 days after silking (DAS) by pollination prevention. Transcriptional profiling analysis of the leaf at six developmental stages during induced senescence revealed that a total of 5,432 differentially expressed genes (DEGs) were identified, including 2314 up-regulated genes and 1925 down-regulated genes. Functional annotation showed that the up-regulated genes were mainly enriched in multi-organism process and nitrogen compound transport, whereas down-regulated genes were involved in photosynthesis. Expression patterns and pathway enrichment analyses of early-senescence related genes indicated that these DEGs are involved in complex regulatory networks, especially in the jasmonic acid pathway. In addition, transcription factors from several families were detected, particularly the CO-like, NAC, ERF, GRAS, WRKY and ZF-HD families, suggesting that these transcription factors might play important roles in driving leaf senescence in maize as a result of pollination-prevention.

Genome-wide identification, characterization, and expression profile of aquaporin gene family in flax (Linum usitatissimum)

PubMed Central

Shivaraj, S. M.; Deshmukh, Rupesh K.; Rai, Rhitu; Bélanger, Richard; Agrawal, Pawan K.; Dash, Prasanta K.

2017-01-01

Membrane intrinsic proteins (MIPs) form transmembrane channels and facilitate transport of myriad substrates across the cell membrane in many organisms. Majority of plant MIPs have water transporting ability and are commonly referred as aquaporins (AQPs). In the present study, we identified aquaporin coding genes in flax by genome-wide analysis, their structure, function and expression pattern by pan-genome exploration. Cross-genera phylogenetic analysis with known aquaporins from rice, arabidopsis, and poplar showed five subgroups of flax aquaporins representing 16 plasma membrane intrinsic proteins (PIPs), 17 tonoplast intrinsic proteins (TIPs), 13 NOD26-like intrinsic proteins (NIPs), 2 small basic intrinsic proteins (SIPs), and 3 uncharacterized intrinsic proteins (XIPs). Amongst aquaporins, PIPs contained hydrophilic aromatic arginine (ar/R) selective filter but TIP, NIP, SIP and XIP subfamilies mostly contained hydrophobic ar/R selective filter. Analysis of RNA-seq and microarray data revealed high expression of PIPs in multiple tissues, low expression of NIPs, and seed specific expression of TIP3 in flax. Exploration of aquaporin homologs in three closely related Linum species bienne, grandiflorum and leonii revealed presence of 49, 39 and 19 AQPs, respectively. The genome-wide identification of aquaporins, first in flax, provides insight to elucidate their physiological and developmental roles in flax. PMID:28447607

Genome-wide identification, characterization, and expression profile of aquaporin gene family in flax (Linum usitatissimum).

PubMed

Shivaraj, S M; Deshmukh, Rupesh K; Rai, Rhitu; Bélanger, Richard; Agrawal, Pawan K; Dash, Prasanta K

2017-04-27

Membrane intrinsic proteins (MIPs) form transmembrane channels and facilitate transport of myriad substrates across the cell membrane in many organisms. Majority of plant MIPs have water transporting ability and are commonly referred as aquaporins (AQPs). In the present study, we identified aquaporin coding genes in flax by genome-wide analysis, their structure, function and expression pattern by pan-genome exploration. Cross-genera phylogenetic analysis with known aquaporins from rice, arabidopsis, and poplar showed five subgroups of flax aquaporins representing 16 plasma membrane intrinsic proteins (PIPs), 17 tonoplast intrinsic proteins (TIPs), 13 NOD26-like intrinsic proteins (NIPs), 2 small basic intrinsic proteins (SIPs), and 3 uncharacterized intrinsic proteins (XIPs). Amongst aquaporins, PIPs contained hydrophilic aromatic arginine (ar/R) selective filter but TIP, NIP, SIP and XIP subfamilies mostly contained hydrophobic ar/R selective filter. Analysis of RNA-seq and microarray data revealed high expression of PIPs in multiple tissues, low expression of NIPs, and seed specific expression of TIP3 in flax. Exploration of aquaporin homologs in three closely related Linum species bienne, grandiflorum and leonii revealed presence of 49, 39 and 19 AQPs, respectively. The genome-wide identification of aquaporins, first in flax, provides insight to elucidate their physiological and developmental roles in flax.

Common Variants within Oxidative Phosphorylation Genes Influence Risk of Ischemic Stroke and Intracerebral Hemorrhage

PubMed Central

Anderson, Christopher D.; Biffi, Alessandro; Nalls, Michael A.; Devan, William J.; Schwab, Kristin; Ayres, Alison M.; Valant, Valerie; Ross, Owen A.; Rost, Natalia S.; Saxena, Richa; Viswanathan, Anand; Worrall, Bradford B.; Brott, Thomas G.; Goldstein, Joshua N.; Brown, Devin; Broderick, Joseph P.; Norrving, Bo; Greenberg, Steven M.; Silliman, Scott L.; Hansen, Björn M.; Tirschwell, David L.; Lindgren, Arne; Slowik, Agnieszka; Schmidt, Reinhold; Selim, Magdy; Roquer, Jaume; Montaner, Joan; Singleton, Andrew B.; Kidwell, Chelsea S.; Woo, Daniel; Furie, Karen L.; Meschia, James F.; Rosand, Jonathan

2013-01-01

Background and Purpose Prior studies demonstrated association between mitochondrial DNA variants and ischemic stroke (IS). We investigated whether variants within a larger set of oxidative phosphorylation (OXPHOS) genes encoded by both autosomal and mitochondrial DNA were associated with risk of IS and, based on our results, extended our investigation to intracerebral hemorrhage (ICH). Methods This association study employed a discovery cohort of 1643 individuals, a validation cohort of 2432 individuals for IS, and an extension cohort of 1476 individuals for ICH. Gene-set enrichment analysis (GSEA) was performed on all structural OXPHOS genes, as well as genes contributing to individual respiratory complexes. Gene-sets passing GSEA were tested by constructing genetic scores using common variants residing within each gene. Associations between each variant and IS that emerged in the discovery cohort were examined in validation and extension cohorts. Results IS was associated with genetic risk scores in OXPHOS as a whole (odds ratio (OR)=1.17, p=0.008) and Complex I (OR=1.06, p=0.050). Among IS subtypes, small vessel (SV) stroke showed association with OXPHOS (OR=1.16, p=0.007), Complex I (OR=1.13, p=0.027) and Complex IV (OR 1.14, p=0.018). To further explore this SV association, we extended our analysis to ICH, revealing association between deep hemispheric ICH and Complex IV (OR=1.08, p=0.008). Conclusions This pathway analysis demonstrates association between common genetic variants within OXPHOS genes and stroke. The associations for SV stroke and deep ICH suggest that genetic variation in OXPHOS influences small vessel pathobiology. Further studies are needed to identify culprit genetic variants and assess their functional consequences. PMID:23362085

Transcriptome analysis and identification of P450 genes relevant to imidacloprid detoxification in Bradysia odoriphaga.

PubMed

Chen, Chengyu; Wang, Cuicui; Liu, Ying; Shi, Xueyan; Gao, Xiwu

2018-02-07

Pesticide tolerance poses many challenges for pest control, particularly for destructive pests such as Bradysia odoriphaga. Imidacloprid has been used to control B. odoriphaga since 2013, however, imidacloprid resistance in B. odoriphaga has developed in recent years. Identifying actual and potential genes involved in detoxification metabolism of imidacloprid could offer solutions for controlling this insect. In this study, RNA-seq was used to explore differentially expressed genes in B. odoriphaga that respond to imidacloprid treatment. Differential expression data between imidacloprid treatment and the control revealed 281 transcripts (176 with annotations) showing upregulation and 394 transcripts (235 with annotations) showing downregulation. Among them, differential expression levels of seven P450 unigenes were associated with imidacloprid detoxification mechanism, with 4 unigenes that were upregulated and 3 unigenes that were downregulated. The qRT-PCR results of the seven differential expression P450 unigenes after imidacloprid treatment were consistent with RNA-Seq data. Furthermore, oral delivery mediated RNA interference of these four upregulated P450 unigenes followed by an insecticide bioassay significantly increased the mortality of imidacloprid-treated B. odoriphaga. This result indicated that the four upregulated P450s are involved in detoxification of imidacloprid. This study provides a genetic basis for further exploring P450 genes for imidacloprid detoxification in B. odoriphaga.

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis

DOE PAGES

Pavlopoulos, Georgios A.; Paez-Espino, David; Kyrpides, Nikos C.; ...

2017-07-18

Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today’s indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. Lastly, we comment on their strengths and their weaknesses andmore » empirically discuss their scalability, user friendliness, and postvisualization capabilities.« less

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis

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

Pavlopoulos, Georgios A.; Paez-Espino, David; Kyrpides, Nikos C.

Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today’s indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. Lastly, we comment on their strengths and their weaknesses andmore » empirically discuss their scalability, user friendliness, and postvisualization capabilities.« less

Gene and genetic diagnostic method patent claims: a comparison under current European and US patent law

PubMed Central

Huys, Isabelle; Van Overwalle, Geertrui; Matthijs, Gert

2011-01-01

The paper focuses on the fundamental debate that is going on in Europe and the United States about whether genes and genetic diagnostic methods are to be regarded as inventions or subject matter eligible for patent protection, or whether they are discoveries or principles of nature and thus excluded from patentability. The study further explores some possible scenarios of American influences on European patent applications with respect to genetic diagnostic methods. Our analysis points out that patent eligibility for genes and genetic diagnostic methods, as discussed in the United States in the Association of Molecular Pathology versus US Patent and Trademark Office decision, is based on a different reasoning compared with the European Patent Convention. PMID:21654725

Gene and genetic diagnostic method patent claims: a comparison under current European and US patent law.

PubMed

Huys, Isabelle; Van Overwalle, Geertrui; Matthijs, Gert

2011-10-01

The paper focuses on the fundamental debate that is going on in Europe and the United States about whether genes and genetic diagnostic methods are to be regarded as inventions or subject matter eligible for patent protection, or whether they are discoveries or principles of nature and thus excluded from patentability. The study further explores some possible scenarios of American influences on European patent applications with respect to genetic diagnostic methods. Our analysis points out that patent eligibility for genes and genetic diagnostic methods, as discussed in the United States in the Association of Molecular Pathology versus US Patent and Trademark Office decision, is based on a different reasoning compared with the European Patent Convention.

Risk Factors of Extended-Spectrum β-Lactamase Producing Enterobacteriaceae Occurrence in Farms in Reunion, Madagascar and Mayotte Islands, 2016–2017

PubMed Central

Gay, Noellie; Leclaire, Alexandre; Laval, Morgane; Miltgen, Guillaume; Jégo, Maël; Stéphane, Ramin; Jaubert, Julien; Belmonte, Olivier; Cardinale, Eric

2018-01-01

In South Western Indian ocean (IO), Extended-Spectrum β-Lactamase producing Enterobacteriaceae (ESBL-E) are a main public health issue. In livestock, ESBL-E burden was unknown. The aim of this study was estimating the prevalence of ESBL-E on commercial farms in Reunion, Mayotte and Madagascar and genes involved. Secondly, risk factors of ESBL-E occurrence in broiler, beef cattle and pig farms were explored. In 2016–2017, commercial farms were sampled using boot swabs and samples stored at 4 °C before microbiological analysis for phenotypical ESBL-E and gene characterization. A dichotomous questionnaire was performed. Prevalences observed in all production types and territories were high, except for beef cattle in Reunion, which differed significantly. The most common ESBL gene was blaCTX-M-1. Generalized linear models explaining ESBL-E occurrence varied between livestock production sectors and allowed identifying main protective (e.g., water quality control and detergent use for cleaning) and risk factors (e.g., recent antibiotic use, other farmers visiting the exploitation, pet presence). This study is the first to explore tools for antibiotic resistance management in IO farms. It provides interesting hypothesis to explore about antibiotic use in IO territories and ESBL-E transmission between pig, beef cattle and humans in Madagascar. PMID:29473906

Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer. | Office of Cancer Genomics

Cancer.gov

Body mass index (BMI) has been implicated as a primary factor influencing cancer development. However, understanding the relationship between these two complex traits has been confounded by both environmental and genetic heterogeneity. Analysis of QTL linked to tumorigenesis and BMI identified several loci associated with both phenotypes. Exploring these loci in greater detail revealed a novel relationship between the Pannexin 3 gene (Panx3) and both BMI and tumorigenesis. Panx3 is positively associated with BMI and is strongly tied to a lipid metabolism gene expression network.

Implantation of Vascular Grafts Lined with Genetically Modified Endothelial Cells

NASA Astrophysics Data System (ADS)

Wilson, James M.; Birinyi, Louis K.; Salomon, Robert N.; Libby, Peter; Callow, Allan D.; Mulligan, Richard C.

1989-06-01

The possibility of using the vascular endothelial cell as a target for gene replacement therapy was explored. Recombinant retroviruses were used to transduce the lacZ gene into endothelial cells harvested from mongrel dogs. Prosthetic vascular grafts seeded with the genetically modified cells were implanted as carotid interposition grafts into the dogs from which the original cells were harvested. Analysis of the graft 5 weeks after implantation revealed genetically modified endothelial cells lining the luminal surface of the graft. This technology could be used in the treatment of atherosclerosis disease and the design of new drug delivery systems.

First Report of Arg587Cys Mutation of Notch3 Gene in Two Chinese Families with CADASIL.

PubMed

You, Jinsong; Liao, Shaojun; Zhang, Foming; Ma, Zhaohui; Li, Guifu

2017-01-01

To explore Notch3 mutation sites of Chinese patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). Direct sequencing of all exons in Notch3 gene was performed on 12 unrelated suspected CADASIL cases from mainland China. A missense p.Arg587Cys (1759C>T) mutation in exon 11 was identified in 2 patients through genetic analysis. Chinese patients with CADASIL of R587C mutation in exon 11 was firstly reported. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

The pathogenesis shared between abdominal aortic aneurysms and intracranial aneurysms: a microarray analysis.

PubMed

Wang, Wen; Li, Hao; Zhao, Zheng; Wang, Haoyuan; Zhang, Dong; Zhang, Yan; Lan, Qing; Wang, Jiangfei; Cao, Yong; Zhao, Jizong

2018-04-01

Abdominal aortic aneurysms (AAAs) and intracranial saccular aneurysms (IAs) are the most common types of aneurysms. This study was to investigate the common pathogenesis shared between these two kinds of aneurysms. We collected 12 IAs samples and 12 control arteries from the Beijing Tiantan Hospital and performed microarray analysis. In addition, we utilized the microarray datasets of IAs and AAAs from the Gene Expression Omnibus (GEO), in combination with our microarray results, to generate messenger RNA expression profiles for both AAAs and IAs in our study. Functional exploration and protein-protein interaction (PPI) analysis were performed. A total of 727 common genes were differentially expressed (404 was upregulated; 323 was downregulated) for both AAAs and IAs. The GO and pathway analyses showed that the common dysregulated genes were mainly enriched in vascular smooth muscle contraction, muscle contraction, immune response, defense response, cell activation, IL-6 signaling and chemokine signaling pathways, etc. The further protein-protein analysis identified 35 hub nodes, including TNF, IL6, MAPK13, and CCL5. These hub node genes were enriched in inflammatory response, positive regulation of IL-6 production, chemokine signaling pathway, and T/B cell receptor signaling pathway. Our study will gain new insight into the molecular mechanisms for the pathogenesis of both types of aneurysms and provide new therapeutic targets for the patients harboring AAAs and IAs.

Analysis of Copy Number Variation in the Abp Gene Regions of Two House Mouse Subspecies Suggests Divergence during the Gene Family Expansions.

PubMed

Pezer, Željka; Chung, Amanda G; Karn, Robert C; Laukaitis, Christina M

2017-06-01

The Androgen-binding protein ( Abp ) gene region of the mouse genome contains 64 genes, some encoding pheromones that influence assortative mating between mice from different subspecies. Using CNVnator and quantitative PCR, we explored copy number variation in this gene family in natural populations of Mus musculus domesticus ( Mmd ) and Mus musculus musculus ( Mmm ), two subspecies of house mice that form a narrow hybrid zone in Central Europe. We found that copy number variation in the center of the Abp gene region is very common in wild Mmd , primarily representing the presence/absence of the final duplications described for the mouse genome. Clustering of Mmd individuals based on this variation did not reflect their geographical origin, suggesting no population divergence in the Abp gene cluster. However, copy number variation patterns differ substantially between Mmd and other mouse taxa. Large blocks of Abp genes are absent in Mmm , Mus musculus castaneus and an outgroup, Mus spretus , although with differences in variation and breakpoint locations. Our analysis calls into question the reliance on a reference genome for interpreting the detailed organization of genes in taxa more distant from the Mmd reference genome. The polymorphic nature of the gene family expansion in all four taxa suggests that the number of Abp genes, especially in the central gene region, is not critical to the survival and reproduction of the mouse. However, Abp haplotypes of variable length may serve as a source of raw genetic material for new signals influencing reproductive communication and thus speciation of mice. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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

PubMed

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

2015-01-01

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

The Ocean Gene Atlas: exploring the biogeography of plankton genes online.

PubMed

Villar, Emilie; Vannier, Thomas; Vernette, Caroline; Lescot, Magali; Cuenca, Miguelangel; Alexandre, Aurélien; Bachelerie, Paul; Rosnet, Thomas; Pelletier, Eric; Sunagawa, Shinichi; Hingamp, Pascal

2018-05-21

The Ocean Gene Atlas is a web service to explore the biogeography of genes from marine planktonic organisms. It allows users to query protein or nucleotide sequences against global ocean reference gene catalogs. With just one click, the abundance and location of target sequences are visualized on world maps as well as their taxonomic distribution. Interactive results panels allow for adjusting cutoffs for alignment quality and displaying the abundances of genes in the context of environmental features (temperature, nutrients, etc.) measured at the time of sampling. The ease of use enables non-bioinformaticians to explore quantitative and contextualized information on genes of interest in the global ocean ecosystem. Currently the Ocean Gene Atlas is deployed with (i) the Ocean Microbial Reference Gene Catalog (OM-RGC) comprising 40 million non-redundant mostly prokaryotic gene sequences associated with both Tara Oceans and Global Ocean Sampling (GOS) gene abundances and (ii) the Marine Atlas of Tara Ocean Unigenes (MATOU) composed of >116 million eukaryote unigenes. Additional datasets will be added upon availability of further marine environmental datasets that provide the required complement of sequence assemblies, raw reads and contextual environmental parameters. Ocean Gene Atlas is a freely-available web service at: http://tara-oceans.mio.osupytheas.fr/ocean-gene-atlas/.

Genome-wide gene by lead exposure interaction analysis identifies UNC5D as a candidate gene for neurodevelopment.

PubMed

Wang, Zhaoxi; Claus Henn, Birgit; Wang, Chaolong; Wei, Yongyue; Su, Li; Sun, Ryan; Chen, Han; Wagner, Peter J; Lu, Quan; Lin, Xihong; Wright, Robert; Bellinger, David; Kile, Molly; Mazumdar, Maitreyi; Tellez-Rojo, Martha Maria; Schnaas, Lourdes; Christiani, David C

2017-07-28

Neurodevelopment is a complex process involving both genetic and environmental factors. Prenatal exposure to lead (Pb) has been associated with lower performance on neurodevelopmental tests. Adverse neurodevelopmental outcomes are more frequent and/or more severe when toxic exposures interact with genetic susceptibility. To explore possible loci associated with increased susceptibility to prenatal Pb exposure, we performed a genome-wide gene-environment interaction study (GWIS) in young children from Mexico (n = 390) and Bangladesh (n = 497). Prenatal Pb exposure was estimated by cord blood Pb concentration. Neurodevelopment was assessed using the Bayley Scales of Infant Development. We identified a locus on chromosome 8, containing UNC5D, and demonstrated evidence of its genome-wide significance with mental composite scores (rs9642758, p meta  = 4.35 × 10 -6 ). Within this locus, the joint effects of two independent single nucleotide polymorphisms (SNPs, rs9642758 and rs10503970) had a p-value of 4.38 × 10 -9 for mental composite scores. Correlating GWIS results with in vitro transcriptomic profiles identified one common gene, SLC1A5, which is involved in synaptic function, neuronal development, and excitotoxicity. Further analysis revealed interconnected interactions that formed a large network of 52 genes enriched with oxidative stress genes and neurodevelopmental genes. Our findings suggest that certain genetic polymorphisms within/near genes relevant to neurodevelopment might modify the toxic effects of Pb exposure via oxidative stress.

In vivo functional analysis of L-rhamnose metabolic pathway in Aspergillus niger: a tool to identify the potential inducer of RhaR.

PubMed

Khosravi, Claire; Kun, Roland Sándor; Visser, Jaap; Aguilar-Pontes, María Victoria; de Vries, Ronald P; Battaglia, Evy

2017-11-06

The genes of the non-phosphorylative L-rhamnose catabolic pathway have been identified for several yeast species. In Schefferomyces stipitis, all L-rhamnose pathway genes are organized in a cluster, which is conserved in Aspergillus niger, except for the lra-4 ortholog (lraD). The A. niger cluster also contains the gene encoding the L-rhamnose responsive transcription factor (RhaR) that has been shown to control the expression of genes involved in L-rhamnose release and catabolism. In this paper, we confirmed the function of the first three putative L-rhamnose utilisation genes from A. niger through gene deletion. We explored the identity of the inducer of the pathway regulator (RhaR) through expression analysis of the deletion mutants grown in transfer experiments to L-rhamnose and L-rhamnonate. Reduced expression of L-rhamnose-induced genes on L-rhamnose in lraA and lraB deletion strains, but not on L-rhamnonate (the product of LraB), demonstrate that the inducer of the pathway is of L-rhamnonate or a compound downstream of it. Reduced expression of these genes in the lraC deletion strain on L-rhamnonate show that it is in fact a downstream product of L-rhamnonate. This work showed that the inducer of RhaR is beyond L-rhamnonate dehydratase (LraC) and is likely to be the 2-keto-3-L-deoxyrhamnonate.

A Functional and Regulatory Network Associated with PIP Expression in Human Breast Cancer

PubMed Central

Debily, Marie-Anne; Marhomy, Sandrine El; Boulanger, Virginie; Eveno, Eric; Mariage-Samson, Régine; Camarca, Alessandra; Auffray, Charles; Piatier-Tonneau, Dominique; Imbeaud, Sandrine

2009-01-01

Background The PIP (prolactin-inducible protein) gene has been shown to be expressed in breast cancers, with contradictory results concerning its implication. As both the physiological role and the molecular pathways in which PIP is involved are poorly understood, we conducted combined gene expression profiling and network analysis studies on selected breast cancer cell lines presenting distinct PIP expression levels and hormonal receptor status, to explore the functional and regulatory network of PIP co-modulated genes. Principal Findings Microarray analysis allowed identification of genes co-modulated with PIP independently of modulations resulting from hormonal treatment or cell line heterogeneity. Relevant clusters of genes that can discriminate between [PIP+] and [PIP−] cells were identified. Functional and regulatory network analyses based on a knowledge database revealed a master network of PIP co-modulated genes, including many interconnecting oncogenes and tumor suppressor genes, half of which were detected as differentially expressed through high-precision measurements. The network identified appears associated with an inhibition of proliferation coupled with an increase of apoptosis and an enhancement of cell adhesion in breast cancer cell lines, and contains many genes with a STAT5 regulatory motif in their promoters. Conclusions Our global exploratory approach identified biological pathways modulated along with PIP expression, providing further support for its good prognostic value of disease-free survival in breast cancer. Moreover, our data pointed to the importance of a regulatory subnetwork associated with PIP expression in which STAT5 appears as a potential transcriptional regulator. PMID:19262752

Transcriptome and gene expression analysis of DHA producer Aurantiochytrium under low temperature conditions

PubMed Central

Ma, Zengxin; Tan, Yanzhen; Cui, Guzhen; Feng, Yingang; Cui, Qiu; Song, Xiaojin

2015-01-01

Aurantiochytrium is a promising docosahexaenoic acid (DHA) production candidate due to its fast growth rate and high proportions of lipid and DHA content. In this study, high-throughput RNA sequencing technology was employed to explore the acclimatization of this DHA producer under cold stress at the transcriptional level. The overall de novo assembly of the cDNA sequence data generated 29,783 unigenes, with an average length of 1,200 bp. In total, 13,245 unigenes were annotated in at least one database. A comparative genomic analysis between normal conditions and cold stress revealed that 2,013 genes were differentially expressed during the growth stage, while 2,071 genes were differentially expressed during the lipid accumulation stage. Further functional categorization and analyses showed some differentially expressed genes were involved in processes crucial to cold acclimation, such as signal transduction, cellular component biogenesis, and carbohydrate and lipid metabolism. A brief survey of the transcripts obtained in response to cold stress underlines the survival strategy of Aurantiochytrium; of these transcripts, many directly or indirectly influence the lipid composition. This is the first study to perform a transcriptomic analysis of the Aurantiochytrium under low temperature conditions. Our results will help to enhance DHA production by Aurantiochytrium in the future. PMID:26403200

Transcriptome and gene expression analysis of DHA producer Aurantiochytrium under low temperature conditions.

PubMed

Ma, Zengxin; Tan, Yanzhen; Cui, Guzhen; Feng, Yingang; Cui, Qiu; Song, Xiaojin

2015-09-25

Aurantiochytrium is a promising docosahexaenoic acid (DHA) production candidate due to its fast growth rate and high proportions of lipid and DHA content. In this study, high-throughput RNA sequencing technology was employed to explore the acclimatization of this DHA producer under cold stress at the transcriptional level. The overall de novo assembly of the cDNA sequence data generated 29,783 unigenes, with an average length of 1,200 bp. In total, 13,245 unigenes were annotated in at least one database. A comparative genomic analysis between normal conditions and cold stress revealed that 2,013 genes were differentially expressed during the growth stage, while 2,071 genes were differentially expressed during the lipid accumulation stage. Further functional categorization and analyses showed some differentially expressed genes were involved in processes crucial to cold acclimation, such as signal transduction, cellular component biogenesis, and carbohydrate and lipid metabolism. A brief survey of the transcripts obtained in response to cold stress underlines the survival strategy of Aurantiochytrium; of these transcripts, many directly or indirectly influence the lipid composition. This is the first study to perform a transcriptomic analysis of the Aurantiochytrium under low temperature conditions. Our results will help to enhance DHA production by Aurantiochytrium in the future.

Noninvasive prenatal diagnosis for single gene disorders.

PubMed

Allen, Stephanie; Young, Elizabeth; Bowns, Benjamin

2017-04-01

Noninvasive prenatal diagnosis for single gene disorders is coming to fruition in its clinical utility. The presence of cell-free DNA in maternal plasma has been recognized for many years, and a number of applications have developed from this. Noninvasive prenatal diagnosis for single gene disorders has lagged behind due to complexities of technology development, lack of investment and the need for validation samples for rare disorders. Publications are emerging demonstrating a variety of technical approaches and feasibility of clinical application. Techniques for analysis of cell-free DNA including digital PCR, next-generation sequencing and relative haplotype dosage have been used most often for assay development. Analysis of circulating fetal cells in the maternal blood is still being investigated as a viable alternative and more recently transcervical trophoblast cells. Studies exploring ethical and social issues are generally positive but raise concerns around the routinization of prenatal testing. Further work is necessary to make testing available to all patients with a pregnancy at risk of a single gene disorder, and it remains to be seen if the development of more powerful technologies such as isolation and analysis of single cells will shift the emphasis of noninvasive prenatal diagnosis. As testing becomes possible for a wider range of conditions, more ethical questions will become relevant.

The genetic regulatory network centered on Pto-Wuschela and its targets involved in wood formation revealed by association studies.

PubMed

Yang, Xiaohui; Wei, Zunzheng; Du, Qingzhang; Chen, Jinhui; Wang, Qingshi; Quan, Mingyang; Song, Yuepeng; Xie, Jianbo; Zhang, Deqiang

2015-11-09

Transcription factors (TFs) regulate gene expression and can strongly affect phenotypes. However, few studies have examined TF variants and TF interactions with their targets in plants. Here, we used genetic association in 435 unrelated individuals of Populus tomentosa to explore the variants in Pto-Wuschela and its targets to decipher the genetic regulatory network of Pto-Wuschela. Our bioinformatics and co-expression analysis identified 53 genes with the motif TCACGTGA as putative targets of Pto-Wuschela. Single-marker association analysis showed that Pto-Wuschela was associated with wood properties, which is in agreement with the observation that it has higher expression in stem vascular tissues in Populus. Also, SNPs in the 53 targets were associated with growth or wood properties under additive or dominance effects, suggesting these genes and Pto-Wuschela may act in the same genetic pathways that affect variation in these quantitative traits. Epistasis analysis indicated that 75.5% of these genes directly or indirectly interacted Pto-Wuschela, revealing the coordinated genetic regulatory network formed by Pto-Wuschela and its targets. Thus, our study provides an alternative method for dissection of the interactions between a TF and its targets, which will strength our understanding of the regulatory roles of TFs in complex traits in plants.

Identification and characterization of a novel human hepatocellular carcinoma-associated gene

PubMed Central

Wang, Z-X; Wang, H-Y; Wu, M-C

2001-01-01

To investigate liver cancer-associated genes and to explore the molecular basis of liver cancer genesis, we have cloned a novel hepatocellular carcinoma (HCC)-related gene with a transcript of 2520 base pairs in length named HCCA2 by mRNA differential display polymerase chain reaction (DDPCR) and screening a placenta cDNA library. No significant homologous protein with known genes was found. Western blot analysis showed that HCCA2 could be expressed in transfected 293 cells. Northern hybridization analysis showed that HCCA2 mRNA was expressed in 79% (34/43) patients with HCC, most of whom had significantly high expression in HCC tissues, while not expressed in corresponding noncancerous liver tissues. The clinical pathological data showed that the HCCA2 was significantly associated with the invasion of tumour capsule (P= 0.0007) and the expression of ki-67 protein (P= 0.0022). Immunohistochemical staining confirmed that the HCCA2 protein was localized in cytoplasm of liver cancer tissues. According to amino acid analysis of the protein and its localization, it may play a role in a cascade of intracellular signal transduction because the protein was characterized with two Src homology 3 (SH3) binding-domains and several functional motifs of phophorylation. © 2001 Cancer Research Campaign  http://www.bjcancer.com PMID:11710830

The association between MTHFR gene C677T polymorphism and ALL risk based on a meta-analysis involving 17,469 subjects.

PubMed

Zhang, Beibei; Zhang, Weiming; Yan, Liang; Wang, Daogang

2017-03-01

The methylenetetrahydrofolate reductase (MTHFR) gene C677T polymorphism is closely related to the acute lymphoblastic leukaemia (ALL) indicated by many previous epidemiologic studies. However, their conclusions were still conflicting. Our aim is to evaluate their associations using a more comprehensive updated meta-analysis. Electronic searches were conducted to select published studies prior to February, 2016. Totally, 39 case-control studies including 6551 ALL cases and 10,918 controls were selected in current meta-analysis. The association was detected significantly between MTHFR C677T polymorphism and ALL reducing susceptibility. Our results indicate that the MTHFR C677T polymorphism may be a promising ALL biomarker and studies to explore the protein levels of the variants and their functional role are required for the definitive conclusions. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrative analysis of RNA, translation, and protein levels reveals distinct regulatory variation across humans

PubMed Central

Cenik, Can; Cenik, Elif Sarinay; Byeon, Gun W.; Grubert, Fabian; Candille, Sophie I.; Spacek, Damek; Alsallakh, Bilal; Tilgner, Hagen; Araya, Carlos L.; Tang, Hua; Ricci, Emiliano; Snyder, Michael P.

2015-01-01

Elucidating the consequences of genetic differences between humans is essential for understanding phenotypic diversity and personalized medicine. Although variation in RNA levels, transcription factor binding, and chromatin have been explored, little is known about global variation in translation and its genetic determinants. We used ribosome profiling, RNA sequencing, and mass spectrometry to perform an integrated analysis in lymphoblastoid cell lines from a diverse group of individuals. We find significant differences in RNA, translation, and protein levels suggesting diverse mechanisms of personalized gene expression control. Combined analysis of RNA expression and ribosome occupancy improves the identification of individual protein level differences. Finally, we identify genetic differences that specifically modulate ribosome occupancy—many of these differences lie close to start codons and upstream ORFs. Our results reveal a new level of gene expression variation among humans and indicate that genetic variants can cause changes in protein levels through effects on translation. PMID:26297486

Use of RNA-seq to identify cardiac genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy

PubMed Central

Friedenberg, Steven G.; Chdid, Lhoucine; Keene, Bruce; Sherry, Barbara; Motsinger-Reif, Alison; Meurs, Kathryn M.

2017-01-01

OBJECTIVE To identify cardiac tissue genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy (DCM). ANIMALS 8 dogs with and 5 dogs without DCM. PROCEDURES Following euthanasia, samples of left ventricular myocardium were collected from each dog. Total RNA was extracted from tissue samples, and RNA sequencing was performed on each sample. Samples from dogs with and without DCM were grouped to identify genes that were differentially regulated between the 2 populations. Overrepresentation analysis was performed on upregulated and downregulated gene sets to identify altered molecular pathways in dogs with DCM. RESULTS Genes involved in cellular energy metabolism, especially metabolism of carbohydrates and fats, were significantly downregulated in dogs with DCM. Expression of cardiac structural proteins was also altered in affected dogs. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that RNA sequencing may provide important insights into the pathogenesis of DCM in dogs and highlight pathways that should be explored to identify causative mutations and develop novel therapeutic interventions. PMID:27347821

Microarray‑based bioinformatics analysis of the prospective target gene network of key miRNAs influenced by long non‑coding RNA PVT1 in HCC.

PubMed

Zhang, Yu; Mo, Wei-Jia; Wang, Xiao; Zhang, Tong-Tong; Qin, Yuan; Wang, Han-Lin; Chen, Gang; Wei, Dan-Ming; Dang, Yi-Wu

2018-05-02

The long non‑coding RNA (lncRNA) PVT1 plays vital roles in the tumorigenesis and development of various types of cancer. However, the potential expression profiling, functions and pathways of PVT1 in HCC remain unknown. PVT1 was knocked down in SMMC‑7721 cells, and a miRNA microarray analysis was performed to detect the differentially expressed miRNAs. Twelve target prediction algorithms were used to predict the underlying targets of these differentially expressed miRNAs. Bioinformatics analysis was performed to explore the underlying functions, pathways and networks of the targeted genes. Furthermore, the relationship between PVT1 and the clinical parameters in HCC was confirmed based on the original data in the TCGA database. Among the differentially expressed miRNAs, the top two upregulated and downregulated miRNAs were selected for further analysis based on the false discovery rate (FDR), fold‑change (FC) and P‑values. Based on the TCGA database, PVT1 was obviously highly expressed in HCC, and a statistically higher PVT1 expression was found for sex (male), ethnicity (Asian) and pathological grade (G3+G4) compared to the control groups (P<0.05). Furthermore, Gene Ontology (GO) analysis revealed that the target genes were involved in complex cellular pathways, such as the macromolecule biosynthetic process, compound metabolic process, and transcription. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the MAPK and Wnt signaling pathways may be correlated with the regulation of the four candidate miRNAs. The results therefore provide significant information on the differentially expressed miRNAs associated with PVT1 in HCC, and we hypothesized that PVT1 may play vital roles in HCC by regulating different miRNAs or target gene expression (particularly MAPK8) via the MAPK or Wnt signaling pathways. Thus, further investigation of the molecular mechanism of PVT1 in HCC is needed.

Quantitative DNA methylation analysis of paired box gene 1 and LIM homeobox transcription factor 1 α genes in cervical cancer

PubMed Central

Xu, Ling; Xu, Jun; Hu, Zheng; Yang, Baohua; Wang, Lifeng; Lin, Xiao; Xia, Ziyin; Zhang, Zhiling; Zhu, Yunheng

2018-01-01

DNA methylation is associated with tumorigenesis and may act as a potential biomarker for detecting cervical cancer. The aim of the present study was to explore the methylation status of the paired box gene 1 (PAX1) and the LIM homeobox transcription factor 1 α (LMX1A) gene in a spectrum of cervical lesions in an Eastern Chinese population. This single-center study involved 121 patients who were divided into normal cervix (NC; n=28), low-grade squamous intraepithelial lesion (LSIL; n=32), high-grade squamous intraepithelial lesion (HSIL; n=34) and cervical squamous cell carcinoma (CSCC; n=27) groups, according to biopsy results. Following extraction and modification of the DNA, quantitative assessment of the PAX1 and LMX1A genes in exfoliated cells was performed using pyrosequencing analysis. Receiver operating characteristic (ROC) curves were generated to calculate the sensitivity and specificity of each parameter and cut-off values of the percentage of methylation reference (PMR) for differentiation diagnosis. Analysis of variance was used to identify differences among groups. The PMR of the two genes was significantly higher in the HSIL and CSCC groups compared with that in the NC and LSIL groups (P<0.001). ROC curve analysis demonstrated that the sensitivity, specificity and accuracy for detection of CSCC were 0.790, 0.837 and 0.809, respectively, using PAX1; and 0.633, 0.357 and 0.893, respectively, using LMX1A. These results indicated that quantitative PAX1 methylation demonstrates potential for cervical cancer screening, while further investigation is required to determine the potential of LMX1A methylation. PMID:29541217

Analysis of phylogeny and codon usage bias and relationship of GC content, amino acid composition with expression of the structural nif genes.

PubMed

Mondal, Sunil Kanti; Kundu, Sudip; Das, Rabindranath; Roy, Sujit

2016-08-01

Bacteria and archaea have evolved with the ability to fix atmospheric dinitrogen in the form of ammonia, catalyzed by the nitrogenase enzyme complex which comprises three structural genes nifK, nifD and nifH. The nifK and nifD encodes for the beta and alpha subunits, respectively, of component 1, while nifH encodes for component 2 of nitrogenase. Phylogeny based on nifDHK have indicated that Cyanobacteria is closer to Proteobacteria alpha and gamma but not supported by the tree based on 16SrRNA. The evolutionary ancestor for the different trees was also different. The GC1 and GC2% analysis showed more consistency than GC3% which appeared to below for Firmicutes, Cyanobacteria and Euarchaeota while highest in Proteobacteria beta and clearly showed the proportional effect on the codon usage with a few exceptions. Few genes from Firmicutes, Euryarchaeota, Proteobacteria alpha and delta were found under mutational pressure. These nif genes with low and high GC3% from different classes of organisms showed similar expected number of codons. Distribution of the genes and codons, based on codon usage demonstrated opposite pattern for different orientation of mirror plane when compared with each other. Overall our results provide a comprehensive analysis on the evolutionary relationship of the three structural nif genes, nifK, nifD and nifH, respectively, in the context of codon usage bias, GC content relationship and amino acid composition of the encoded proteins and exploration of crucial statistical method for the analysis of positive data with non-constant variance to identify the shape factors of codon adaptation index.

VAMPS: a website for visualization and analysis of microbial population structures.

PubMed

Huse, Susan M; Mark Welch, David B; Voorhis, Andy; Shipunova, Anna; Morrison, Hilary G; Eren, A Murat; Sogin, Mitchell L

2014-02-05

The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 10⁵-10⁸ reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing. We developed the free web service VAMPS (Visualization and Analysis of Microbial Population Structures, http://vamps.mbl.edu) to address these challenges and to facilitate research by individuals or collaborating groups working on projects with large-scale sequencing data. Users can upload marker gene sequences and associated metadata; reads are quality filtered and assigned to both taxonomic structures and to taxonomy-independent clusters. A simple point-and-click interface allows users to select for analysis any combination of their own or their collaborators' private data and data from public projects, filter these by their choice of taxonomic and/or abundance criteria, and then explore these data using a wide range of analytic methods and visualizations. Each result is extensively hyperlinked to other analysis and visualization options, promoting data exploration and leading to a greater understanding of data relationships. VAMPS allows researchers using marker gene sequence data to analyze the diversity of microbial communities and the relationships between communities, to explore these analyses in an intuitive visual context, and to download data, results, and images for publication. VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret massive amounts of next-generation sequence data. Any web-capable device can be used to upload, process, explore, and extract data and results from VAMPS. VAMPS encourages researchers to share sequence and metadata, and fosters collaboration between researchers of disparate biomes who recognize common patterns in shared data.

Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database

PubMed Central

Davis, Allan Peter; Wiegers, Thomas C.; King, Benjamin L.; Wiegers, Jolene; Grondin, Cynthia J.; Sciaky, Daniela; Johnson, Robin J.; Mattingly, Carolyn J.

2016-01-01

Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) manually curates chemical-gene, chemical-disease, and gene-disease interactions from the scientific literature. The use of official gene symbols in CTD interactions enables this information to be combined with the Gene Ontology (GO) file from NCBI Gene. By integrating these GO-gene annotations with CTD’s gene-disease dataset, we produce 753,000 inferences between 15,700 GO terms and 4,200 diseases, providing opportunities to explore presumptive molecular underpinnings of diseases and identify biological similarities. Through a variety of applications, we demonstrate the utility of this novel resource. As a proof-of-concept, we first analyze known repositioned drugs (e.g., raloxifene and sildenafil) and see that their target diseases have a greater degree of similarity when comparing GO terms vs. genes. Next, a computational analysis predicts seemingly non-intuitive diseases (e.g., stomach ulcers and atherosclerosis) as being similar to bipolar disorder, and these are validated in the literature as reported co-diseases. Additionally, we leverage other CTD content to develop testable hypotheses about thalidomide-gene networks to treat seemingly disparate diseases. Finally, we illustrate how CTD tools can rank a series of drugs as potential candidates for repositioning against B-cell chronic lymphocytic leukemia and predict cisplatin and the small molecule inhibitor JQ1 as lead compounds. The CTD dataset is freely available for users to navigate pathologies within the context of extensive biological processes, molecular functions, and cellular components conferred by GO. This inference set should aid researchers, bioinformaticists, and pharmaceutical drug makers in finding commonalities in disease mechanisms, which in turn could help identify new therapeutics, new indications for existing pharmaceuticals, potential disease comorbidities, and alerts for side effects. PMID:27171405

Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.

PubMed

Davis, Allan Peter; Wiegers, Thomas C; King, Benjamin L; Wiegers, Jolene; Grondin, Cynthia J; Sciaky, Daniela; Johnson, Robin J; Mattingly, Carolyn J

2016-01-01

Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) manually curates chemical-gene, chemical-disease, and gene-disease interactions from the scientific literature. The use of official gene symbols in CTD interactions enables this information to be combined with the Gene Ontology (GO) file from NCBI Gene. By integrating these GO-gene annotations with CTD's gene-disease dataset, we produce 753,000 inferences between 15,700 GO terms and 4,200 diseases, providing opportunities to explore presumptive molecular underpinnings of diseases and identify biological similarities. Through a variety of applications, we demonstrate the utility of this novel resource. As a proof-of-concept, we first analyze known repositioned drugs (e.g., raloxifene and sildenafil) and see that their target diseases have a greater degree of similarity when comparing GO terms vs. genes. Next, a computational analysis predicts seemingly non-intuitive diseases (e.g., stomach ulcers and atherosclerosis) as being similar to bipolar disorder, and these are validated in the literature as reported co-diseases. Additionally, we leverage other CTD content to develop testable hypotheses about thalidomide-gene networks to treat seemingly disparate diseases. Finally, we illustrate how CTD tools can rank a series of drugs as potential candidates for repositioning against B-cell chronic lymphocytic leukemia and predict cisplatin and the small molecule inhibitor JQ1 as lead compounds. The CTD dataset is freely available for users to navigate pathologies within the context of extensive biological processes, molecular functions, and cellular components conferred by GO. This inference set should aid researchers, bioinformaticists, and pharmaceutical drug makers in finding commonalities in disease mechanisms, which in turn could help identify new therapeutics, new indications for existing pharmaceuticals, potential disease comorbidities, and alerts for side effects.

MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers.

PubMed

Allot, Alexis; Chennen, Kirsley; Nevers, Yannis; Poidevin, Laetitia; Kress, Arnaud; Ripp, Raymond; Thompson, Julie Dawn; Poch, Olivier; Lecompte, Odile

2017-06-16

The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user's specific interests and provides an efficient way to share information with collaborators. Furthermore, the user's behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. ©Alexis Allot, Kirsley Chennen, Yannis Nevers, Laetitia Poidevin, Arnaud Kress, Raymond Ripp, Julie Dawn Thompson, Olivier Poch, Odile Lecompte. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.06.2017.

Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model

PubMed Central

Omony, Jimmy; de Jong, Anne; Krawczyk, Antonina O.; Eijlander, Robyn T.; Kuipers, Oscar P.

2018-01-01

Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes. PMID:29424683

Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model.

PubMed

Omony, Jimmy; de Jong, Anne; Krawczyk, Antonina O; Eijlander, Robyn T; Kuipers, Oscar P

2018-02-09

Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes.

Differential Connectivity in Colorectal Cancer Gene Expression Network

PubMed

Izadi, Fereshteh

2018-05-30

Colorectal cancer (CRC) is one of the challenging types of cancers; thus, exploring effective biomarkers related to colorectal could lead to significant progresses toward the treatment of this disease. In the present study, CRC gene expression datasets have been reanalyzed. Mutual differentially expressed genes across 294 normal mucosa and adjacent tumoral samples were then utilized in order to build two independent transcriptional regulatory networks. By analyzing the networks topologically, genes with differential global connectivity related to cancer state were determined for which the potential transcriptional regulators including transcription factors were identified. The majority of differentially connected genes (DCGs) were up-regulated in colorectal transcriptome experiments. Moreover, a number of these genes have been experimentally validated as cancer or CRC-associated genes. The DCGs, including GART, TGFB1, ITGA2, SLC16A5, SOX9, and MMP7, were investigated across 12 cancer types. Functional enrichment analysis followed by detailed data mining exhibited that these candidate genes could be related to CRC by mediating in metastatic cascade in addition to shared pathways with 12 cancer types by triggering the inflammatory events Our study uncovered correlated alterations in gene expression related to CRC susceptibility and progression that the potent candidate biomarkers could provide a link to disease.

High-throughput multiplex HLA-typing by ligase detection reaction (LDR) and universal array (UA) approach.

PubMed

Consolandi, Clarissa

2009-01-01

One major goal of genetic research is to understand the role of genetic variation in living systems. In humans, by far the most common type of such variation involves differences in single DNA nucleotides, and is thus termed single nucleotide polymorphism (SNP). The need for improvement in throughput and reliability of traditional techniques makes it necessary to develop new technologies. Thus the past few years have witnessed an extraordinary surge of interest in DNA microarray technology. This new technology offers the first great hope for providing a systematic way to explore the genome. It permits a very rapid analysis of thousands genes for the purpose of gene discovery, sequencing, mapping, expression, and polymorphism detection. We generated a series of analytical tools to address the manufacturing, detection and data analysis components of a microarray experiment. In particular, we set up a universal array approach in combination with a PCR-LDR (polymerase chain reaction-ligation detection reaction) strategy for allele identification in the HLA gene.

IMG-ABC: An Atlas of Biosynthetic Gene Clusters to Fuel the Discovery of Novel Secondary Metabolites

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

Chen, I-Min; Chu, Ken; Ratner, Anna

2014-10-28

In the discovery of secondary metabolites (SMs), large-scale analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of relevant computational resources. We present IMG-ABC (https://img.jgi.doe.gov/abc/) -- An Atlas of Biosynthetic gene Clusters within the Integrated Microbial Genomes (IMG) system1. IMG-ABC is a rich repository of both validated and predicted biosynthetic clusters (BCs) in cultured isolates, single-cells and metagenomes linked with the SM chemicals they produce and enhanced with focused analysis tools within IMG. The underlying scalable framework enables traversal of phylogenetic dark matter and chemical structure space -- serving as a doorwaymore » to a new era in the discovery of novel molecules.« less

Investigation of candidate genes for osteoarthritis based on gene expression profiles.

PubMed

Dong, Shuanghai; Xia, Tian; Wang, Lei; Zhao, Qinghua; Tian, Jiwei

2016-12-01

To explore the mechanism of osteoarthritis (OA) and provide valid biological information for further investigation. Gene expression profile of GSE46750 was downloaded from Gene Expression Omnibus database. The Linear Models for Microarray Data (limma) package (Bioconductor project, http://www.bioconductor.org/packages/release/bioc/html/limma.html) was used to identify differentially expressed genes (DEGs) in inflamed OA samples. Gene Ontology function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were performed based on Database for Annotation, Visualization and Integrated Discovery data, and protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins database. Regulatory network was screened based on Encyclopedia of DNA Elements. Molecular Complex Detection was used for sub-network screening. Two sub-networks with highest node degree were integrated with transcriptional regulatory network and KEGG functional enrichment analysis was processed for 2 modules. In total, 401 up- and 196 down-regulated DEGs were obtained. Up-regulated DEGs were involved in inflammatory response, while down-regulated DEGs were involved in cell cycle. PPI network with 2392 protein interactions was constructed. Moreover, 10 genes including Interleukin 6 (IL6) and Aurora B kinase (AURKB) were found to be outstanding in PPI network. There are 214 up- and 8 down-regulated transcription factor (TF)-target pairs in the TF regulatory network. Module 1 had TFs including SPI1, PRDM1, and FOS, while module 2 contained FOSL1. The nodes in module 1 were enriched in chemokine signaling pathway, while the nodes in module 2 were mainly enriched in cell cycle. The screened DEGs including IL6, AGT, and AURKB might be potential biomarkers for gene therapy for OA by being regulated by TFs such as FOS and SPI1, and participating in the cell cycle and cytokine-cytokine receptor interaction pathway. Copyright © 2016 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.

Gene expression profiling in equine polysaccharide storage myopathy revealed inflammation, glycogenesis inhibition, hypoxia and mitochondrial dysfunctions.

PubMed

Barrey, Eric; Mucher, Elodie; Jeansoule, Nicolas; Larcher, Thibaut; Guigand, Lydie; Herszberg, Bérénice; Chaffaux, Stéphane; Guérin, Gérard; Mata, Xavier; Benech, Philippe; Canale, Marielle; Alibert, Olivier; Maltere, Péguy; Gidrol, Xavier

2009-08-07

Several cases of myopathies have been observed in the horse Norman Cob breed. Muscle histology examinations revealed that some families suffer from a polysaccharide storage myopathy (PSSM). It is assumed that a gene expression signature related to PSSM should be observed at the transcriptional level because the glycogen storage disease could also be linked to other dysfunctions in gene regulation. Thus, the functional genomic approach could be conducted in order to provide new knowledge about the metabolic disorders related to PSSM. We propose exploring the PSSM muscle fiber metabolic disorders by measuring gene expression in relationship with the histological phenotype. Genotypying analysis of GYS1 mutation revealed 2 homozygous (AA) and 5 heterozygous (GA) PSSM horses. In the PSSM muscles, histological data revealed PAS positive amylase resistant abnormal polysaccharides, inflammation, necrosis, and lipomatosis and active regeneration of fibers. Ultrastructural evaluation revealed a decrease of mitochondrial number and structural disorders. Extensive accumulation of an abnormal polysaccharide displaced and partially replaced mitochondria and myofibrils. The severity of the disease was higher in the two homozygous PSSM horses.Gene expression analysis revealed 129 genes significantly modulated (p < 0.05). The following genes were up-regulated over 2 fold: IL18, CTSS, LUM, CD44, FN1, GST01. The most down-regulated genes were the following: mitochondrial tRNA, SLC2A2, PRKCalpha, VEGFalpha. Data mining analysis showed that protein synthesis, apoptosis, cellular movement, growth and proliferation were the main cellular functions significantly associated with the modulated genes (p < 0.05). Several up-regulated genes, especially IL18, revealed a severe muscular inflammation in PSSM muscles. The up-regulation of glycogen synthase kinase-3 (GSK3beta) under its active form could be responsible for glycogen synthase (GYS1) inhibition and hypoxia-inducible factor (HIF1alpha) destabilization. The main disorders observed in PSSM muscles could be related to mitochondrial dysfunctions, glycogenesis inhibition and the chronic hypoxia of the PSSM muscles.

A Transcriptional Signature of Fatigue Derived from Patients with Primary Sjögren’s Syndrome

PubMed Central

James, Katherine; Al-Ali, Shereen; Tarn, Jessica; Cockell, Simon J.; Gillespie, Colin S.; Hindmarsh, Victoria; Locke, James; Mitchell, Sheryl; Lendrem, Dennis; Bowman, Simon; Price, Elizabeth; Pease, Colin T.; Emery, Paul; Lanyon, Peter; Hunter, John A.; Gupta, Monica; Bombardieri, Michele; Sutcliffe, Nurhan; Pitzalis, Costantino; McLaren, John; Cooper, Annie; Regan, Marian; Giles, Ian; Isenberg, David; Saravanan, Vadivelu; Coady, David; Dasgupta, Bhaskar; McHugh, Neil; Young-Min, Steven; Moots, Robert; Gendi, Nagui; Akil, Mohammed; Griffiths, Bridget; Wipat, Anil; Newton, Julia; Jones, David E.; Isaacs, John; Hallinan, Jennifer; Ng, Wan-Fai

2015-01-01

Background Fatigue is a debilitating condition with a significant impact on patients’ quality of life. Fatigue is frequently reported by patients suffering from primary Sjögren’s Syndrome (pSS), a chronic autoimmune condition characterised by dryness of the eyes and the mouth. However, although fatigue is common in pSS, it does not manifest in all sufferers, providing an excellent model with which to explore the potential underpinning biological mechanisms. Methods Whole blood samples from 133 fully-phenotyped pSS patients stratified for the presence of fatigue, collected by the UK primary Sjögren’s Syndrome Registry, were used for whole genome microarray. The resulting data were analysed both on a gene by gene basis and using pre-defined groups of genes. Finally, gene set enrichment analysis (GSEA) was used as a feature selection technique for input into a support vector machine (SVM) classifier. Classification was assessed using area under curve (AUC) of receiver operator characteristic and standard error of Wilcoxon statistic, SE(W). Results Although no genes were individually found to be associated with fatigue, 19 metabolic pathways were enriched in the high fatigue patient group using GSEA. Analysis revealed that these enrichments arose from the presence of a subset of 55 genes. A radial kernel SVM classifier with this subset of genes as input displayed significantly improved performance over classifiers using all pathway genes as input. The classifiers had AUCs of 0.866 (SE(W) 0.002) and 0.525 (SE(W) 0.006), respectively. Conclusions Systematic analysis of gene expression data from pSS patients discordant for fatigue identified 55 genes which are predictive of fatigue level using SVM classification. This list represents the first step in understanding the underlying pathophysiological mechanisms of fatigue in patients with pSS. PMID:26694930

Frontotemporal dementia: insights into the biological underpinnings of disease through gene co-expression network analysis.

PubMed

Ferrari, Raffaele; Forabosco, Paola; Vandrovcova, Jana; Botía, Juan A; Guelfi, Sebastian; Warren, Jason D; Momeni, Parastoo; Weale, Michael E; Ryten, Mina; Hardy, John

2016-02-24

In frontotemporal dementia (FTD) there is a critical lack in the understanding of biological and molecular mechanisms involved in disease pathogenesis. The heterogeneous genetic features associated with FTD suggest that multiple disease-mechanisms are likely to contribute to the development of this neurodegenerative condition. We here present a systems biology approach with the scope of i) shedding light on the biological processes potentially implicated in the pathogenesis of FTD and ii) identifying novel potential risk factors for FTD. We performed a gene co-expression network analysis of microarray expression data from 101 individuals without neurodegenerative diseases to explore regional-specific co-expression patterns in the frontal and temporal cortices for 12 genes (MAPT, GRN, CHMP2B, CTSC, HLA-DRA, TMEM106B, C9orf72, VCP, UBQLN2, OPTN, TARDBP and FUS) associated with FTD and we then carried out gene set enrichment and pathway analyses, and investigated known protein-protein interactors (PPIs) of FTD-genes products. Gene co-expression networks revealed that several FTD-genes (such as MAPT and GRN, CTSC and HLA-DRA, TMEM106B, and C9orf72, VCP, UBQLN2 and OPTN) were clustering in modules of relevance in the frontal and temporal cortices. Functional annotation and pathway analyses of such modules indicated enrichment for: i) DNA metabolism, i.e. transcription regulation, DNA protection and chromatin remodelling (MAPT and GRN modules); ii) immune and lysosomal processes (CTSC and HLA-DRA modules), and; iii) protein meta/catabolism (C9orf72, VCP, UBQLN2 and OPTN, and TMEM106B modules). PPI analysis supported the results of the functional annotation and pathway analyses. This work further characterizes known FTD-genes and elaborates on their biological relevance to disease: not only do we indicate likely impacted regional-specific biological processes driven by FTD-genes containing modules, but also do we suggest novel potential risk factors among the FTD-genes interactors as targets for further mechanistic characterization in hypothesis driven cell biology work.

Whole-genome sequencing reveals novel insights into sulfur oxidation in the extremophile Acidithiobacillus thiooxidans.

PubMed

Yin, Huaqun; Zhang, Xian; Li, Xiaoqi; He, Zhili; Liang, Yili; Guo, Xue; Hu, Qi; Xiao, Yunhua; Cong, Jing; Ma, Liyuan; Niu, Jiaojiao; Liu, Xueduan

2014-07-04

Acidithiobacillus thiooxidans (A. thiooxidans), a chemolithoautotrophic extremophile, is widely used in the industrial recovery of copper (bioleaching or biomining). The organism grows and survives by autotrophically utilizing energy derived from the oxidation of elemental sulfur and reduced inorganic sulfur compounds (RISCs). However, the lack of genetic manipulation systems has restricted our exploration of its physiology. With the development of high-throughput sequencing technology, the whole genome sequence analysis of A. thiooxidans has allowed preliminary models to be built for genes/enzymes involved in key energy pathways like sulfur oxidation. The genome of A. thiooxidans A01 was sequenced and annotated. It contains key sulfur oxidation enzymes involved in the oxidation of elemental sulfur and RISCs, such as sulfur dioxygenase (SDO), sulfide quinone reductase (SQR), thiosulfate:quinone oxidoreductase (TQO), tetrathionate hydrolase (TetH), sulfur oxidizing protein (Sox) system and their associated electron transport components. Also, the sulfur oxygenase reductase (SOR) gene was detected in the draft genome sequence of A. thiooxidans A01, and multiple sequence alignment was performed to explore the function of groups of related protein sequences. In addition, another putative pathway was found in the cytoplasm of A. thiooxidans, which catalyzes sulfite to sulfate as the final product by phosphoadenosine phosphosulfate (PAPS) reductase and adenylylsulfate (APS) kinase. This differs from its closest relative Acidithiobacillus caldus, which is performed by sulfate adenylyltransferase (SAT). Furthermore, real-time quantitative PCR analysis showed that most of sulfur oxidation genes were more strongly expressed in the S0 medium than that in the Na2S2O3 medium at the mid-log phase. Sulfur oxidation model of A. thiooxidans A01 has been constructed based on previous studies from other sulfur oxidizing strains and its genome sequence analyses, providing insights into our understanding of its physiology and further analysis of potential functions of key sulfur oxidation genes.

Whole-genome sequencing reveals novel insights into sulfur oxidation in the extremophile Acidithiobacillus thiooxidans

PubMed Central

2014-01-01

Background Acidithiobacillus thiooxidans (A. thiooxidans), a chemolithoautotrophic extremophile, is widely used in the industrial recovery of copper (bioleaching or biomining). The organism grows and survives by autotrophically utilizing energy derived from the oxidation of elemental sulfur and reduced inorganic sulfur compounds (RISCs). However, the lack of genetic manipulation systems has restricted our exploration of its physiology. With the development of high-throughput sequencing technology, the whole genome sequence analysis of A. thiooxidans has allowed preliminary models to be built for genes/enzymes involved in key energy pathways like sulfur oxidation. Results The genome of A. thiooxidans A01 was sequenced and annotated. It contains key sulfur oxidation enzymes involved in the oxidation of elemental sulfur and RISCs, such as sulfur dioxygenase (SDO), sulfide quinone reductase (SQR), thiosulfate:quinone oxidoreductase (TQO), tetrathionate hydrolase (TetH), sulfur oxidizing protein (Sox) system and their associated electron transport components. Also, the sulfur oxygenase reductase (SOR) gene was detected in the draft genome sequence of A. thiooxidans A01, and multiple sequence alignment was performed to explore the function of groups of related protein sequences. In addition, another putative pathway was found in the cytoplasm of A. thiooxidans, which catalyzes sulfite to sulfate as the final product by phosphoadenosine phosphosulfate (PAPS) reductase and adenylylsulfate (APS) kinase. This differs from its closest relative Acidithiobacillus caldus, which is performed by sulfate adenylyltransferase (SAT). Furthermore, real-time quantitative PCR analysis showed that most of sulfur oxidation genes were more strongly expressed in the S0 medium than that in the Na2S2O3 medium at the mid-log phase. Conclusion Sulfur oxidation model of A. thiooxidans A01 has been constructed based on previous studies from other sulfur oxidizing strains and its genome sequence analyses, providing insights into our understanding of its physiology and further analysis of potential functions of key sulfur oxidation genes. PMID:24993543

Aspergillus Collagen-Like Genes (acl): Identification, Sequence Polymorphism, and Assessment for PCR-Based Pathogen Detection

PubMed Central

Tuntevski, Kiril; Durney, Brandon C.; Snyder, Anna K.; LaSala, P. Rocco; Nayak, Ajay P.; Green, Brett J.; Beezhold, Donald H.; Rio, Rita V. M.; Holland, Lisa A.

2013-01-01

The genus Aspergillus is a burden to public health due to its ubiquitous presence in the environment, its production of allergens, and wide demographic susceptibility among cystic fibrosis, asthmatic, and immunosuppressed patients. Current methods of detection of Aspergillus colonization and infection rely on lengthy morphological characterization or nonstandardized serological assays that are restricted to identifying a fungal etiology. Collagen-like genes have been shown to exhibit species-specific conservation across the noncollagenous regions as well as strain-specific polymorphism in the collagen-like regions. Here we assess the conserved region of the Aspergillus collagen-like (acl) genes and explore the application of PCR amplicon size-based discrimination among the five most common etiologic species of the Aspergillus genus, including Aspergillus fumigatus, A. flavus, A. nidulans, A. niger, and A. terreus. Genetic polymorphism and phylogenetic analysis of the aclF1 gene were additionally examined among the available strains. Furthermore, the applicability of the PCR-based assay to identification of these five species in cultures derived from sputum and bronchoalveolar fluid from 19 clinical samples was explored. Application of capillary electrophoresis on nanogels was additionally demonstrated to improve the discrimination between Aspergillus species. Overall, this study demonstrated that Aspergillus acl genes could be used as PCR targets to discriminate between clinically relevant Aspergillus species. Future studies aim to utilize the detection of Aspergillus acl genes in PCR and microfluidic applications to determine the sensitivity and specificity for the identification of Aspergillus colonization and invasive aspergillosis in immunocompromised subjects. PMID:24123732

Genome-wide genetic variation and comparison of fruit-associated traits between kumquat (Citrus japonica) and Clementine mandarin (Citrus clementina).

PubMed

Liu, Tian-Jia; Li, Yong-Ping; Zhou, Jing-Jing; Hu, Chun-Gen; Zhang, Jin-Zhi

2018-03-01

The comprehensive genetic variation of two citrus species were analyzed at genome and transcriptome level. A total of 1090 differentially expressed genes were found during fruit development by RNA-sequencing. Fruit size (fruit equatorial diameter) and weight (fresh weight) are the two most important components determining yield and consumer acceptability for many horticultural crops. However, little is known about the genetic control of these traits. Here, we performed whole-genome resequencing to reveal the comprehensive genetic variation of the fruit development between kumquat (Citrus japonica) and Clementine mandarin (Citrus clementina). In total, 5,865,235 single-nucleotide polymorphisms (SNPs) and 414,447 insertions/deletions (InDels) were identified in the two citrus species. Based on integrative analysis of genome and transcriptome of fruit, 640,801 SNPs and 20,733 InDels were identified. The features, genomic distribution, functional effect, and other characteristics of these genetic variations were explored. RNA-sequencing identified 1090 differentially expressed genes (DEGs) during fruit development of kumquat and Clementine mandarin. Gene Ontology revealed that these genes were involved in various molecular functional and biological processes. In addition, the genetic variation of 939 DEGs and 74 multiple fruit development pathway genes from previous reports were also identified. A global survey identified 24,237 specific alternative splicing events in the two citrus species and showed that intron retention is the most prevalent pattern of alternative splicing. These genome variation data provide a foundation for further exploration of citrus diversity and gene-phenotype relationships and for future research on molecular breeding to improve kumquat, Clementine mandarin and related species.

Transcriptome analysis identifies genes involved in ethanol response of Saccharomyces cerevisiae in Agave tequilana juice.

PubMed

Ramirez-Córdova, Jesús; Drnevich, Jenny; Madrigal-Pulido, Jaime Alberto; Arrizon, Javier; Allen, Kirk; Martínez-Velázquez, Moisés; Alvarez-Maya, Ikuri

2012-08-01

During ethanol fermentation, yeast cells are exposed to stress due to the accumulation of ethanol, cell growth is altered and the output of the target product is reduced. For Agave beverages, like tequila, no reports have been published on the global gene expression under ethanol stress. In this work, we used microarray analysis to identify Saccharomyces cerevisiae genes involved in the ethanol response. Gene expression of a tequila yeast strain of S. cerevisiae (AR5) was explored by comparing global gene expression with that of laboratory strain S288C, both after ethanol exposure. Additionally, we used two different culture conditions, cells grown in Agave tequilana juice as a natural fermentation media or grown in yeast-extract peptone dextrose as artificial media. Of the 6368 S. cerevisiae genes in the microarray, 657 genes were identified that had different expression responses to ethanol stress due to strain and/or media. A cluster of 28 genes was found over-expressed specifically in the AR5 tequila strain that could be involved in the adaptation to tequila yeast fermentation, 14 of which are unknown such as yor343c, ylr162w, ygr182c, ymr265c, yer053c-a or ydr415c. These could be the most suitable genes for transforming tequila yeast to increase ethanol tolerance in the tequila fermentation process. Other genes involved in response to stress (RFC4, TSA1, MLH1, PAU3, RAD53) or transport (CYB2, TIP20, QCR9) were expressed in the same cluster. Unknown genes could be good candidates for the development of recombinant yeasts with ethanol tolerance for use in industrial tequila fermentation.

Identification of Differentially Expressed Genes in Blood Cells of Narcolepsy Patients

PubMed Central

Tanaka, Susumu; Honda, Yutaka; Honda, Makoto

2007-01-01

Study Objective: A close association between the human leukocyte antigen (HLA)-DRB1*1501/DQB1*0602 and abnormalities in some inflammatory cytokines have been demonstrated in narcolepsy. Specific alterations in the immune system have been suggested to occur in this disorder. We attempted to identify alterations in gene expression underlying the abnormalities in the blood cells of narcoleptic patients. Designs: Total RNA from 12 narcolepsy-cataplexy patients and from 12 age- and sex-matched healthy controls were pooled. The pooled samples were initially screened for candidate genes for narcolepsy by differential display analysis using annealing control primers (ACP). The second screening of the samples was carried out by semiquantitative PCR using gene-specific primers. Finally, the expression levels of the candidate genes were further confirmed by quantitative real-time PCR using a new set of samples (20 narcolepsy-cataplexy patients and 20 healthy controls). Results: The second screening revealed differential expression of 4 candidate genes. Among them, MX2 was confirmed as a significantly down-regulated gene in the white blood cells of narcoleptic patients by quantitative real-time PCR. Conclusion: We found the MX2 gene to be significantly less expressed in comparison with normal subjects in the white blood cells of narcoleptic patients. This gene is relevant to the immune system. Although differential display analysis using ACP technology has a limitation in that it does not help in determining the functional mechanism underlying sleep/wakefulness dysregulation, it is useful for identifying novel genetic factors related to narcolepsy, such as HLA molecules. Further studies are required to explore the functional relationship between the MX2 gene and narcolepsy pathophysiology. Citation: Tanaka S; Honda Y; Honda M. Identification of differentially expressed genes in blood cells of narcolepsy patients. SLEEP 2007;30(8):974-979. PMID:17702266

Identification of potential therapeutic target genes, key miRNAs and mechanisms in oral lichen planus by bioinformatics analysis.

PubMed

Gong, Cuihua; Sun, Shangtong; Liu, Bing; Wang, Jing; Chen, Xiaodong

2017-06-01

The study aimed to identify the potential target genes and key miRNAs as well as to explore the underlying mechanisms in the pathogenesis of oral lichen planus (OLP) by bioinformatics analysis. The microarray data of GSE38617 were downloaded from Gene Expression Omnibus (GEO) database. A total of 7 OLP and 7 normal samples were used to identify the differentially expressed genes (DEGs) and miRNAs. The DEGs were then performed functional enrichment analyses. Furthermore, DEG-miRNA network and miRNA-function network were constructed by Cytoscape software. Total 1758 DEGs (598 up- and 1160 down-regulated genes) and 40 miRNAs (17 up- and 23 down-regulated miRNAs) were selected. The up-regulated genes were related to nuclear factor-Kappa B (NF-κB) signaling pathway, while down-regulated genes were mainly enriched in the function of ribosome. Tumor necrosis factor (TNF), caspase recruitment domain family, member 11 (CARD11) and mitochondrial ribosomal protein (MRP) genes were identified in these functions. In addition, miR-302 was a hub node in DEG-miRNA network and regulated cyclin D1 (CCND1). MiR-548a-2 was the key miRNA in miRNA-function network by regulating multiple functions including ribosomal function. The NF-κB signaling pathway and ribosome function may be the pathogenic mechanisms of OLP. The genes such as TNF, CARD11, MRP genes and CCND1 may be potential therapeutic target genes in OLP. MiR-548a-2 and miR-302 may play important roles in OLP development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genome wide re-sequencing of newly developed Rice Lines from common wild rice (Oryza rufipogon Griff.) for the identification of NBS-LRR genes.

PubMed

Liu, Wen; Ghouri, Fozia; Yu, Hang; Li, Xiang; Yu, Shuhong; Shahid, Muhammad Qasim; Liu, Xiangdong

2017-01-01

Common wild rice (Oryza rufipogon Griff.) is an important germplasm for rice breeding, which contains many resistance genes. Re-sequencing provides an unprecedented opportunity to explore the abundant useful genes at whole genome level. Here, we identified the nucleotide-binding site leucine-rich repeat (NBS-LRR) encoding genes by re-sequencing of two wild rice lines (i.e. Huaye 1 and Huaye 2) that were developed from common wild rice. We obtained 128 to 147 million reads with approximately 32.5-fold coverage depth, and uniquely covered more than 89.6% (> = 1 fold) of reference genomes. Two wild rice lines showed high SNP (single-nucleotide polymorphisms) variation rate in 12 chromosomes against the reference genomes of Nipponbare (japonica cultivar) and 93-11 (indica cultivar). InDels (insertion/deletion polymorphisms) count-length distribution exhibited normal distribution in the two lines, and most of the InDels were ranged from -5 to 5 bp. With reference to the Nipponbare genome sequence, we detected a total of 1,209,308 SNPs, 161,117 InDels and 4,192 SVs (structural variations) in Huaye 1, and 1,387,959 SNPs, 180,226 InDels and 5,305 SVs in Huaye 2. A total of 44.9% and 46.9% genes exhibited sequence variations in two wild rice lines compared to the Nipponbare and 93-11 reference genomes, respectively. Analysis of NBS-LRR mutant candidate genes showed that they were mainly distributed on chromosome 11, and NBS domain was more conserved than LRR domain in both wild rice lines. NBS genes depicted higher levels of genetic diversity in Huaye 1 than that found in Huaye 2. Furthermore, protein-protein interaction analysis showed that NBS genes mostly interacted with the cytochrome C protein (Os05g0420600, Os01g0885000 and BGIOSGA038922), while some NBS genes interacted with heat shock protein, DNA-binding activity, Phosphoinositide 3-kinase and a coiled coil region. We explored abundant NBS-LRR encoding genes in two common wild rice lines through genome wide re-sequencing, which proved to be a useful tool to exploit elite NBS-LRR genes in wild rice. The data here provide a foundation for future work aimed at dissecting the genetic basis of disease resistance in rice, and the two wild rice lines will be useful germplasm for the molecular improvement of cultivated rice.

Genome wide re-sequencing of newly developed Rice Lines from common wild rice (Oryza rufipogon Griff.) for the identification of NBS-LRR genes

PubMed Central

Yu, Hang; Li, Xiang; Yu, Shuhong; Shahid, Muhammad Qasim

2017-01-01

Common wild rice (Oryza rufipogon Griff.) is an important germplasm for rice breeding, which contains many resistance genes. Re-sequencing provides an unprecedented opportunity to explore the abundant useful genes at whole genome level. Here, we identified the nucleotide-binding site leucine-rich repeat (NBS-LRR) encoding genes by re-sequencing of two wild rice lines (i.e. Huaye 1 and Huaye 2) that were developed from common wild rice. We obtained 128 to 147 million reads with approximately 32.5-fold coverage depth, and uniquely covered more than 89.6% (> = 1 fold) of reference genomes. Two wild rice lines showed high SNP (single-nucleotide polymorphisms) variation rate in 12 chromosomes against the reference genomes of Nipponbare (japonica cultivar) and 93–11 (indica cultivar). InDels (insertion/deletion polymorphisms) count-length distribution exhibited normal distribution in the two lines, and most of the InDels were ranged from -5 to 5 bp. With reference to the Nipponbare genome sequence, we detected a total of 1,209,308 SNPs, 161,117 InDels and 4,192 SVs (structural variations) in Huaye 1, and 1,387,959 SNPs, 180,226 InDels and 5,305 SVs in Huaye 2. A total of 44.9% and 46.9% genes exhibited sequence variations in two wild rice lines compared to the Nipponbare and 93–11 reference genomes, respectively. Analysis of NBS-LRR mutant candidate genes showed that they were mainly distributed on chromosome 11, and NBS domain was more conserved than LRR domain in both wild rice lines. NBS genes depicted higher levels of genetic diversity in Huaye 1 than that found in Huaye 2. Furthermore, protein-protein interaction analysis showed that NBS genes mostly interacted with the cytochrome C protein (Os05g0420600, Os01g0885000 and BGIOSGA038922), while some NBS genes interacted with heat shock protein, DNA-binding activity, Phosphoinositide 3-kinase and a coiled coil region. We explored abundant NBS-LRR encoding genes in two common wild rice lines through genome wide re-sequencing, which proved to be a useful tool to exploit elite NBS-LRR genes in wild rice. The data here provide a foundation for future work aimed at dissecting the genetic basis of disease resistance in rice, and the two wild rice lines will be useful germplasm for the molecular improvement of cultivated rice. PMID:28700714

Genetic variations and patient-reported quality of life among patients with lung cancer.

PubMed

Sloan, Jeff A; de Andrade, Mariza; Decker, Paul; Wampfler, Jason; Oswold, Curtis; Clark, Matthew; Yang, Ping

2012-05-10

Recent evidence has suggested a relationship between the baseline quality of life (QOL) self-reported by patients with cancer and genetic disposition. We report an analysis exploring relationships among baseline QOL assessments and candidate genetic variations in a large cohort of patients with lung cancer. QOL data were provided by 1,299 patients with non-small-cell lung cancer observed at the Mayo Clinic between 1997 and 2007. Overall QOL and subdomains were assessed by either Lung Cancer Symptom Scale or Linear Analog Self Assessment measures; scores were transformed to a scale of 0 to 10, with higher scores representing better status. Baseline QOL scores assessed within 1 year of diagnosis were dichotomized as clinically deficient (CD) or not. A total of 470 single nucleotide polymorphisms (SNPs) in 56 genes of three biologic pathways were assessed for association with QOL measures. Logistic regression with training/validation samples was used to test the association of SNPs with CD QOL. Six SNPs on four genes were replicated using our split schemes. Three SNPs in the MGMT gene (adjusted analysis, rs3858300; unadjusted analysis, rs10741191 and rs3852507) from DNA repair pathway were associated with overall QOL. Two SNPs (rs2287396 [GSTZ1] and rs9524885 [ABCC4]) from glutathione metabolic pathway were associated with fatigue in unadjusted analysis. In adjusted analysis, two SNPs (rs2756109 [ABCC2] and rs9524885 [ABCC4]) from glutathione metabolic pathway were associated with pain. We identified three SNPs in three glutathione metabolic pathway genes and three SNPs in two DNA repair pathway genes associated with QOL measures in patients with non-small-cell lung cancer.

Correlation of gene expression with bladder capacity in interstitial cystitis/bladder pain syndrome.

PubMed

Colaco, Marc; Koslov, David S; Keys, Tristan; Evans, Robert J; Badlani, Gopal H; Andersson, Karl-Erik; Walker, Stephen J

2014-10-01

Interstitial cystitis and bladder pain syndrome are terms used to describe a heterogeneous chronic pelvic and bladder pain disorder. Despite its significant prevalence, our understanding of disease etiology is poor. We molecularly characterized interstitial cystitis/bladder pain syndrome and determined whether there are clinical factors that correlate with gene expression. Bladder biopsies from female subjects with interstitial cystitis/bladder pain syndrome and female controls without signs of the disease were collected and divided into those with normal and low anesthetized bladder capacity, respectively. Samples then underwent RNA extraction and microarray assay. Data generated by these assays were analyzed using Omics Explorer (Qlucore, Lund, Sweden), GeneSifter® Analysis Edition 4.0 and Ingenuity® Pathway Analysis to determine similarity among samples within and between groups, and measure differentially expressed transcripts unique to each phenotype. A total of 16 subjects were included in study. Principal component analysis and unsupervised hierarchical clustering showed clear separation between gene expression in tissues from subjects with low compared to normal bladder capacity. Gene expression in tissue from patients with interstitial cystitis/bladder pain syndrome who had normal bladder capacity did not significantly differ from that in controls without interstitial cystitis/bladder pain syndrome. Pairwise analysis revealed that pathways related to inflammatory and immune response were most involved. Microarray analysis provides insight into the potential pathological condition underlying interstitial cystitis/bladder pain syndrome. This pilot study shows that patients with this disorder who have low compared to normal bladder capacity have significantly different molecular characteristics, which may reflect a difference in disease pathophysiology. Copyright © 2014 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

CHARACTERIZATION OF INFLAMMATORY GENE EXPRESSION AND GALECTIN-3 FUNCTION AFTER SPINAL CORD INJURY IN MICE

PubMed Central

Pajoohesh-Ganji, Ahdeah; Knoblach, Susan M.; Faden, Alan I.; Byrnes, Kimberly R.

2012-01-01

Inflammation has long been implicated in secondary tissue damage after spinal cord injury (SCI). Our previous studies of inflammatory gene expression in rats after SCI revealed two temporally correlated clusters: the first was expressed early after injury and the second was up-regulated later, with peak expression at 1–2 weeks and persistent up-regulation through 6 months. To further address the role of inflammation after SCI, we examined inflammatory genes in a second species, mice, through 28 days after SCI. Using anchor gene clustering analysis, we found similar expression patterns for both the acute and chronic gene clusters previously identified after rat SCI. The acute group returned to normal expression levels by 7 days post-injury. The chronic group, which included C1qB, p22phox and galectin-3, showed peak expression at 7 days and remained up-regulated through 28 days. Immunohistochemistry and western blot analysis showed that the protein expression of these genes was consistent with the mRNA expression. Further exploration of the role of one of these genes, galectin-3, suggests that galectin-3 may contribute to secondary injury. In summary, our findings extend our prior gene profiling data by demonstrating the chronic expression of a cluster of microglial associated inflammatory genes after SCI in mice. Moreover, by demonstrating that inhibition of one such factor improves recovery, the findings suggest that such chronic up-regulation of inflammatory processes may contribute to secondary tissue damage after SCI, and that there may be a broader therapeutic window for neuroprotection than generally accepted. PMID:22884909

Exploring Genetic Attributions Underlying Radiotherapy-Induced Fatigue in Prostate Cancer Patients.

PubMed

Hashemi, Sepehr; Fernandez Martinez, Juan Luis; Saligan, Leorey; Sonis, Stephen

2017-09-01

Despite numerous proposed mechanisms, no definitive pathophysiology underlying radiotherapy-induced fatigue (RIF) has been established. However, the dysregulation of a set of 35 genes was recently validated to predict development of fatigue in prostate cancer patients receiving radiotherapy. To hypothesize novel pathways, and provide genetic targets for currently proposed pathways implicated in RIF development through analysis of the previously validated gene set. The gene set was analyzed for all phenotypic attributions implicated in the phenotype of fatigue. Initially, a "directed" approach was used by querying specific fatigue-related sub-phenotypes against all known phenotypic attributions of the gene set. Then, an "undirected" approach, reviewing the entirety of the literature referencing the 35 genes, was used to increase analysis sensitivity. The dysregulated genes attribute to neural, immunological, mitochondrial, muscular, and metabolic pathways. In addition, certain genes suggest phenotypes not previously emphasized in the context of RIF, such as ionizing radiation sensitivity, DNA damage, and altered DNA repair frequency. Several genes also associated with prostate cancer depression, possibly emphasizing variable radiosensitivity by RIF-prone patients, which may have palliative care implications. Despite the relevant findings, many of the 35 RIF-predictive genes are poorly characterized, warranting their investigation. The implications of herein presented RIF pathways are purely theoretical until specific end-point driven experiments are conducted in more congruent contexts. Nevertheless, the presented attributions are informative, directing future investigation to definitively elucidate RIF's pathoetiology. This study demonstrates an arguably comprehensive method of approaching known differential expression underlying a complex phenotype, to correlate feasible pathophysiology. Copyright © 2017 American Academy of Hospice and Palliative Medicine. All rights reserved.

Molecular Evolution and Mosaicism of Leptospiral Outer Membrane Proteins Involves Horizontal DNA Transfer

PubMed Central

Haake, David A.; Suchard, Marc A.; Kelley, Melissa M.; Dundoo, Manjula; Alt, David P.; Zuerner, Richard L.

2004-01-01

Leptospires belong to a genus of parasitic bacterial spirochetes that have adapted to a broad range of mammalian hosts. Mechanisms of leptospiral molecular evolution were explored by sequence analysis of four genes shared by 38 strains belonging to the core group of pathogenic Leptospira species: L. interrogans, L. kirschneri, L. noguchii, L. borgpetersenii, L. santarosai, and L. weilii. The 16S rRNA and lipL32 genes were highly conserved, and the lipL41 and ompL1 genes were significantly more variable. Synonymous substitutions are distributed throughout the ompL1 gene, whereas nonsynonymous substitutions are clustered in four variable regions encoding surface loops. While phylogenetic trees for the 16S, lipL32, and lipL41 genes were relatively stable, 8 of 38 (20%) ompL1 sequences had mosaic compositions consistent with horizontal transfer of DNA between related bacterial species. A novel Bayesian multiple change point model was used to identify the most likely sites of recombination and to determine the phylogenetic relatedness of the segments of the mosaic ompL1 genes. Segments of the mosaic ompL1 genes encoding two of the surface-exposed loops were likely acquired by horizontal transfer from a peregrine allele of unknown ancestry. Identification of the most likely sites of recombination with the Bayesian multiple change point model, an approach which has not previously been applied to prokaryotic gene sequence analysis, serves as a model for future studies of recombination in molecular evolution of genes. PMID:15090524

Transcriptional analysis of product-concentration driven changes in cellular programs of recombinant Clostridium acetobutylicumstrains.

PubMed

Tummala, Seshu B; Junne, Stefan G; Paredes, Carlos J; Papoutsakis, Eleftherios T

2003-12-30

Antisense RNA (asRNA) downregulation alters protein expression without changing the regulation of gene expression. Downregulation of primary metabolic enzymes possibly combined with overexpression of other metabolic enzymes may result in profound changes in product formation, and this may alter the large-scale transcriptional program of the cells. DNA-array based large-scale transcriptional analysis has the potential to elucidate factors that control cellular fluxes even in the absence of proteome data. These themes are explored in the study of large-scale transcriptional analysis programs and the in vivo primary-metabolism fluxes of several related recombinant C. acetobutylicum strains: C. acetobutylicum ATCC 824(pSOS95del) (plasmid control; produces high levels of butanol snd acetone), 824(pCTFB1AS) (expresses antisense RNA against CoA transferase (ctfb1-asRNA); produces very low levels of butanol and acetone), and 824(pAADB1) (expresses ctfb1-asRNA and the alcohol-aldehyde dahydrogenase gene (aad); produce high alcohol and low acetone levels). DNA-array based transcriptional analysis revealed that the large changes in product concentrations (snd notably butanol concentration) due to ctfb1-asRNA expression alone and in combination with aad overexpression resulted in dramatic changes of the cellular transcriptome. Cluster analysis and gene expression patterns of established and putative operons involved in stress response, motility, sporulation, and fatty-acid biosynthesis indicate that these simple genetic changes dramatically alter the cellular programs of C. acetobutylicum. Comparison of gene expression and flux analysis data may point to possible flux-controling steps and suggest unknown regulatory mechanisms. Copyright 2003; Wiley Periodicals, Inc.

USE OF SERIAL ANALYSIS OF GENE EXPRESSION (SAGE) TO STUDY GENETIC RESPONSES TO THE PRESENCE OF THE TNT OR RDX BY ARABIDOPSIS THALIANA

EPA Science Inventory

Phytoremediation is currently being explored for its potential to clean-up of the large number of military sites that have been contaminated by explosives such as 2,4,6-trinitrotoluene (TNT) and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). Although some of the enzymes responsi...

MutationAligner: a resource of recurrent mutation hotspots in protein domains in cancer.

PubMed

Gauthier, Nicholas Paul; Reznik, Ed; Gao, Jianjiong; Sumer, Selcuk Onur; Schultz, Nikolaus; Sander, Chris; Miller, Martin L

2016-01-04

The MutationAligner web resource, available at http://www.mutationaligner.org, enables discovery and exploration of somatic mutation hotspots identified in protein domains in currently (mid-2015) more than 5000 cancer patient samples across 22 different tumor types. Using multiple sequence alignments of protein domains in the human genome, we extend the principle of recurrence analysis by aggregating mutations in homologous positions across sets of paralogous genes. Protein domain analysis enhances the statistical power to detect cancer-relevant mutations and links mutations to the specific biological functions encoded in domains. We illustrate how the MutationAligner database and interactive web tool can be used to explore, visualize and analyze mutation hotspots in protein domains across genes and tumor types. We believe that MutationAligner will be an important resource for the cancer research community by providing detailed clues for the functional importance of particular mutations, as well as for the design of functional genomics experiments and for decision support in precision medicine. MutationAligner is slated to be periodically updated to incorporate additional analyses and new data from cancer genomics projects. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Gene essentiality, conservation index and co-evolution of genes in cyanobacteria.

PubMed

Tiruveedula, Gopi Siva Sai; Wangikar, Pramod P

2017-01-01

Cyanobacteria, a group of photosynthetic prokaryotes, dominate the earth with ~ 1015 g wet biomass. Despite diversity in habitats and an ancient origin, cyanobacterial phylum has retained a significant core genome. Cyanobacteria are being explored for direct conversion of solar energy and carbon dioxide into biofuels. For this, efficient cyanobacterial strains will need to be designed via metabolic engineering. This will require identification of target knockouts to channelize the flow of carbon toward the product of interest while minimizing deletions of essential genes. We propose "Gene Conservation Index" (GCI) as a quick measure to predict gene essentiality in cyanobacteria. GCI is based on phylogenetic profile of a gene constructed with a reduced dataset of cyanobacterial genomes. GCI is the percentage of organism clusters in which the query gene is present in the reduced dataset. Of the 750 genes deemed to be essential in the experimental study on S. elongatus PCC 7942, we found 494 to be conserved across the phylum which largely comprise of the essential metabolic pathways. On the contrary, the conserved but non-essential genes broadly comprise of genes required under stress conditions. Exceptions to this rule include genes such as the glycogen synthesis and degradation enzymes, deoxyribose-phosphate aldolase (DERA), glucose-6-phosphate 1-dehydrogenase (zwf) and fructose-1,6-bisphosphatase class1, which are conserved but non-essential. While the essential genes are to be avoided during gene knockout studies as potentially lethal deletions, the non-essential but conserved set of genes could be interesting targets for metabolic engineering. Further, we identify clusters of co-evolving genes (CCG), which provide insights that may be useful in annotation. Principal component analysis (PCA) plots of the CCGs are demonstrated as data visualization tools that are complementary to the conventional heatmaps. Our dataset consists of phylogenetic profiles for 23,643 non-redundant cyanobacterial genes. We believe that the data and the analysis presented here will be a great resource to the scientific community interested in cyanobacteria.

A method to identify differential expression profiles of time-course gene data with Fourier transformation.

PubMed

Kim, Jaehee; Ogden, Robert Todd; Kim, Haseong

2013-10-18

Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization.The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics.

Leveraging Genetic-Background Effects in Saccharomyces cerevisiae To Improve Lignocellulosic Hydrolysate Tolerance

DOE PAGES

Sardi, Maria; Rovinskiy, Nikolay; Zhang, Yaoping; ...

2016-07-22

We report a major obstacle to sustainable lignocellulosic biofuel production is microbe inhibition by the combinatorial stresses in pretreated plant hydrolysate. Chemical biomass pretreatment releases a suite of toxins that interact with other stressors, including high osmolarity and temperature, which together can have poorly understood synergistic effects on cells. Improving tolerance in industrial strains has been hindered, in part because the mechanisms of tolerance reported in the literature often fail to recapitulate in other strain backgrounds. Here, we explored and then exploited variations in stress tolerance, toxin-induced transcriptomic responses, and fitness effects of gene overexpression in different Saccharomyces cerevisiae (yeast)more » strains to identify genes and processes linked to tolerance of hydrolysate stressors. Using six different S. cerevisiae strains that together maximized phenotypic and genetic diversity, first we explored transcriptomic differences between resistant and sensitive strains to identify common and strain-specific responses. This comparative analysis implicated primary cellular targets of hydrolysate toxins, secondary effects of defective defense strategies, and mechanisms of tolerance. Dissecting the responses to individual hydrolysate components across strains pointed to synergistic interactions between osmolarity, pH, hydrolysate toxins, and nutrient composition. By characterizing the effects of high-copy gene overexpression in three different strains, we revealed the breadth of the background-specific effects of gene fitness contributions in synthetic hydrolysate. Lastly, our approach identified new genes for engineering improved stress tolerance in diverse strains while illuminating the effects of genetic background on molecular mechanisms.« less

Temperature controls on the basal emission rate of isoprene in a tropical tree Ficus septica: exploring molecular regulatory mechanisms.

PubMed

Mutanda, Ishmael; Inafuku, Masashi; Saitoh, Seikoh; Iwasaki, Hironori; Fukuta, Masakazu; Watanabe, Keiichi; Oku, Hirosuke

2016-10-01

Isoprene emission from plants is very sensitive to environmental temperature both at short-term and long-term scales. Our previous study demonstrated suppression of isoprene emission by cold temperatures in a high emitting tropical tree Ficus septica and revealed a strong correlation of emission to isoprene synthase (IspS) protein levels. When challenged with decreasing daily temperatures from 30 to 12 °C, F. septica completely stopped isoprene emission at 12 °C, only to recover on the second day after re-exposure to 30 °C. Here, we explored this regulation of isoprene emission in response to environmental temperature by a comprehensive analysis of transcriptome data, gene expressions and metabolite pools of the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway. MEP pathway genes and metabolites dynamics did not support substrate-level limitations as major control over observed basal emission, but transcriptome data, network inferences and putative regulatory elements on IspS promoter suggested transcriptional regulation of IspS gene through circadian rhythm and phytohormone signalling processes. Expression levels of 29 genes involved in these pathways were examined by quantitative real-time PCR. We propose that temperature controls over basal isoprene emission at a time-scale of hours to few days are regulated by phytohormone-mediated transcriptional modulation of IspS gene under synchronization by the circadian clock. © 2016 John Wiley & Sons Ltd.

Parallel Selection Revealed by Population Sequencing in Chicken.

PubMed

Qanbari, Saber; Seidel, Michael; Strom, Tim-Mathias; Mayer, Klaus F X; Preisinger, Ruedi; Simianer, Henner

2015-11-13

Human-driven selection during domestication and subsequent breed formation has likely left detectable signatures within the genome of modern chicken. The elucidation of these signatures of selection is of interest from the perspective of evolutionary biology, and for identifying genes relevant to domestication and improvement that ultimately may help to further genetically improve this economically important animal. We used whole genome sequence data from 50 hens of commercial white (WL) and brown (BL) egg-laying chicken along with pool sequences of three meat-type chicken to perform a systematic screening of past selection in modern chicken. Evidence of positive selection was investigated in two steps. First, we explored evidence of parallel fixation in regions with overlapping elevated allele frequencies in replicated populations of layers and broilers, suggestive of selection during domestication or preimprovement ages. We confirmed parallel fixation in BCDO2 and TSHR genes and found four candidates including AGTR2, a gene heavily involved in "Ascites" in commercial birds. Next, we explored differentiated loci between layers and broilers suggestive of selection during improvement in chicken. This analysis revealed evidence of parallel differentiation in genes relevant to appearance and production traits exemplified with the candidate gene OPG, implicated in Osteoporosis, a disorder related to overconsumption of calcium in egg-laying hens. Our results illustrate the potential for population genetic techniques to identify genomic regions relevant to the phenotypes of importance to breeders. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

UPLC/Q-TOF MS-Based Metabolomics and qRT-PCR in Enzyme Gene Screening with Key Role in Triterpenoid Saponin Biosynthesis of Polygala tenuifolia

PubMed Central

Li, Zhenyu; Xu, Xiaoshuang; Peng, Bing; Qin, Xuemei; Du, Guanhua

2014-01-01

Background The dried root of Polygala tenuifolia, named Radix Polygalae, is a well-known traditional Chinese medicine. Triterpenoid saponins are some of the most important components of Radix Polygalae extracts and are widely studied because of their valuable pharmacological properties. However, the relationship between gene expression and triterpenoid saponin biosynthesis in P. tenuifolia is unclear. Methodology/Findings In this study, ultra-performance liquid chromatography (UPLC) coupled with quadrupole time-of-flight mass spectrometry (Q-TOF MS)-based metabolomic analysis was performed to identify and quantify the different chemical constituents of the roots, stems, leaves, and seeds of P. tenuifolia. A total of 22 marker compounds (VIP>1) were explored, and significant differences in all 7 triterpenoid saponins among the different tissues were found. We also observed an efficient reference gene GAPDH for different tissues in this plant and determined the expression level of some genes in the triterpenoid saponin biosynthetic pathway. Results showed that MVA pathway has more important functions in the triterpenoid saponin biosynthesis of P. tenuifolia. The expression levels of squalene synthase (SQS), squalene monooxygenase (SQE), and beta-amyrin synthase (β-AS) were highly correlated with the peak area intensity of triterpenoid saponins compared with data from UPLC/Q-TOF MS-based metabolomic analysis. Conclusions/Significance This finding suggested that a combination of UPLC/Q-TOF MS-based metabolomics and gene expression analysis can effectively elucidate the mechanism of triterpenoid saponin biosynthesis and can provide useful information on gene discovery. These findings can serve as a reference for using the overexpression of genes encoding for SQS, SQE, and/or β-AS to increase the triterpenoid saponin production of P. tenuifolia. PMID:25148032

UPLC/Q-TOF MS-based metabolomics and qRT-PCR in enzyme gene screening with key role in triterpenoid saponin biosynthesis of Polygala tenuifolia.

PubMed

Zhang, Fusheng; Li, Xiaowei; Li, Zhenyu; Xu, Xiaoshuang; Peng, Bing; Qin, Xuemei; Du, Guanhua

2014-01-01

The dried root of Polygala tenuifolia, named Radix Polygalae, is a well-known traditional Chinese medicine. Triterpenoid saponins are some of the most important components of Radix Polygalae extracts and are widely studied because of their valuable pharmacological properties. However, the relationship between gene expression and triterpenoid saponin biosynthesis in P. tenuifolia is unclear. In this study, ultra-performance liquid chromatography (UPLC) coupled with quadrupole time-of-flight mass spectrometry (Q-TOF MS)-based metabolomic analysis was performed to identify and quantify the different chemical constituents of the roots, stems, leaves, and seeds of P. tenuifolia. A total of 22 marker compounds (VIP>1) were explored, and significant differences in all 7 triterpenoid saponins among the different tissues were found. We also observed an efficient reference gene GAPDH for different tissues in this plant and determined the expression level of some genes in the triterpenoid saponin biosynthetic pathway. Results showed that MVA pathway has more important functions in the triterpenoid saponin biosynthesis of P. tenuifolia. The expression levels of squalene synthase (SQS), squalene monooxygenase (SQE), and beta-amyrin synthase (β-AS) were highly correlated with the peak area intensity of triterpenoid saponins compared with data from UPLC/Q-TOF MS-based metabolomic analysis. This finding suggested that a combination of UPLC/Q-TOF MS-based metabolomics and gene expression analysis can effectively elucidate the mechanism of triterpenoid saponin biosynthesis and can provide useful information on gene discovery. These findings can serve as a reference for using the overexpression of genes encoding for SQS, SQE, and/or β-AS to increase the triterpenoid saponin production of P. tenuifolia.

Genome-wide identification and characterization of polygalacturonase genes in Cucumis sativus and Citrullus lanatus.

PubMed

Yu, Youjian; Liang, Ying; Lv, Meiling; Wu, Jian; Lu, Gang; Cao, Jiashu

2014-01-01

Polygalacturonase (PG, EC3.2.1.15), one of the hydrolytic enzymes associated with the modification of pectin network in plant cell wall, has an important role in various cell-separation processes that are essential for plant development. PGs are encoded by a large gene family in plants. However, information on this gene family in plant development remains limited. In the present study, 53 and 62 putative members of the PG gene family in cucumber and watermelon genomes, respectively, were identified by genome-wide search to explore the composition, structure, and evolution of the PG family in Cucurbitaceae crops. The results showed that tandem duplication could be an important factor that contributes to the expansion of the PG genes in the two crops. The phylogenetic and evolutionary analyses suggested that PGs could be classified into seven clades, and that the exon/intron structures and intron phases were conserved within but divergent between clades. At least 24 ancestral PGs were detected in the common ancestor of Arabidopsis and Cucumis sativus. Expression profile analysis by quantitative real-time polymerase chain reaction demonstrated that most CsPGs exhibit specific or high expression pattern in one of the organs/tissues. The 16 CsPGs associated with fruit development could be divided into three subsets based on their specific expression patterns and the cis-elements of fruit-specific, endosperm/seed-specific, and ethylene-responsive exhibited in their promoter regions. Our comparative analysis provided some basic information on the PG gene family, which would be valuable for further functional analysis of the PG genes during plant development. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Integrated annotation and analysis of in situ hybridization images using the ImAnno system: application to the ear and sensory organs of the fetal mouse.

PubMed

Romand, Raymond; Ripp, Raymond; Poidevin, Laetitia; Boeglin, Marcel; Geffers, Lars; Dollé, Pascal; Poch, Olivier

2015-01-01

An in situ hybridization (ISH) study was performed on 2000 murine genes representing around 10% of the protein-coding genes present in the mouse genome using data generated by the EURExpress consortium. This study was carried out in 25 tissues of late gestation embryos (E14.5), with a special emphasis on the developing ear and on five distinct developing sensory organs, including the cochlea, the vestibular receptors, the sensory retina, the olfactory organ, and the vibrissae follicles. The results obtained from an analysis of more than 11,000 micrographs have been integrated in a newly developed knowledgebase, called ImAnno. In addition to managing the multilevel micrograph annotations performed by human experts, ImAnno provides public access to various integrated databases and tools. Thus, it facilitates the analysis of complex ISH gene expression patterns, as well as functional annotation and interaction of gene sets. It also provides direct links to human pathways and diseases. Hierarchical clustering of expression patterns in the 25 tissues revealed three main branches corresponding to tissues with common functions and/or embryonic origins. To illustrate the integrative power of ImAnno, we explored the expression, function and disease traits of the sensory epithelia of the five presumptive sensory organs. The study identified 623 genes (out of 2000) concomitantly expressed in the five embryonic epithelia, among which many (∼12%) were involved in human disorders. Finally, various multilevel interaction networks were characterized, highlighting differential functional enrichments of directly or indirectly interacting genes. These analyses exemplify an under-represention of "sensory" functions in the sensory gene set suggests that E14.5 is a pivotal stage between the developmental stage and the functional phase that will be fully reached only after birth.

Inhibition of DNA methyltransferases regulates cocaine self-administration by rats: a genome-wide DNA methylation study.

PubMed

Fonteneau, M; Filliol, D; Anglard, P; Befort, K; Romieu, P; Zwiller, J

2017-03-01

DNA methylation is a major epigenetic process which regulates the accessibility of genes to the transcriptional machinery. In the present study, we investigated whether modifying the global DNA methylation pattern in the brain would alter cocaine intake by rats, using the cocaine self-administration test. The data indicate that treatment of rats with the DNA methyltransferase inhibitors 5-aza-2'-deoxycytidine (dAZA) and zebularine enhanced the reinforcing properties of cocaine. To obtain some insights about the underlying neurobiological mechanisms, a genome-wide methylation analysis was undertaken in the prefrontal cortex of rats self-administering cocaine and treated with or without dAZA. The study identified nearly 189 000 differentially methylated regions (DMRs), about half of them were located inside gene bodies, while only 9% of DMRs were found in the promoter regions of genes. About 99% of methylation changes occurred outside CpG islands. Gene expression studies confirmed the inverse correlation usually observed between increased methylation and transcriptional activation when methylation occurs in the gene promoter. This inverse correlation was not observed when methylation took place inside gene bodies. Using the literature-based Ingenuity Pathway Analysis, we explored how the differentially methylated genes were related. The analysis showed that increase in cocaine intake by rats in response to DNA methyltransferase inhibitors underlies plasticity mechanisms which mainly concern axonal growth and synaptogenesis as well as spine remodeling. Together with the Akt/PI3K pathway, the Rho-GTPase family was found to be involved in the plasticity underlying the effect of dAZA on the observed behavioral changes. © 2016 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

JOINT AND INDIVIDUAL VARIATION EXPLAINED (JIVE) FOR INTEGRATED ANALYSIS OF MULTIPLE DATA TYPES.

PubMed

Lock, Eric F; Hoadley, Katherine A; Marron, J S; Nobel, Andrew B

2013-03-01

Research in several fields now requires the analysis of datasets in which multiple high-dimensional types of data are available for a common set of objects. In particular, The Cancer Genome Atlas (TCGA) includes data from several diverse genomic technologies on the same cancerous tumor samples. In this paper we introduce Joint and Individual Variation Explained (JIVE), a general decomposition of variation for the integrated analysis of such datasets. The decomposition consists of three terms: a low-rank approximation capturing joint variation across data types, low-rank approximations for structured variation individual to each data type, and residual noise. JIVE quantifies the amount of joint variation between data types, reduces the dimensionality of the data, and provides new directions for the visual exploration of joint and individual structure. The proposed method represents an extension of Principal Component Analysis and has clear advantages over popular two-block methods such as Canonical Correlation Analysis and Partial Least Squares. A JIVE analysis of gene expression and miRNA data on Glioblastoma Multiforme tumor samples reveals gene-miRNA associations and provides better characterization of tumor types.

Effect of curcumin on aged Drosophila melanogaster: a pathway prediction analysis.

PubMed

Zhang, Zhi-guo; Niu, Xu-yan; Lu, Ai-ping; Xiao, Gary Guishan

2015-02-01

To re-analyze the data published in order to explore plausible biological pathways that can be used to explain the anti-aging effect of curcumin. Microarray data generated from other study aiming to investigate effect of curcumin on extending lifespan of Drosophila melanogaster were further used for pathway prediction analysis. The differentially expressed genes were identified by using GeneSpring GX with a criterion of 3.0-fold change. Two Cytoscape plugins including BisoGenet and molecular complex detection (MCODE) were used to establish the protein-protein interaction (PPI) network based upon differential genes in order to detect highly connected regions. The function annotation clustering tool of Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for pathway analysis. A total of 87 genes expressed differentially in D. melanogaster melanogaster treated with curcumin were identified, among which 50 were up-regulated significantly and 37 were remarkably down-regulated in D. melanogaster melanogaster treated with curcumin. Based upon these differential genes, PPI network was constructed with 1,082 nodes and 2,412 edges. Five highly connected regions in PPI networks were detected by MCODE algorithm, suggesting anti-aging effect of curcumin may be underlined through five different pathways including Notch signaling pathway, basal transcription factors, cell cycle regulation, ribosome, Wnt signaling pathway, and p53 pathway. Genes and their associated pathways in D. melanogaster melanogaster treated with anti-aging agent curcumin were identified using PPI network and MCODE algorithm, suggesting that curcumin may be developed as an alternative therapeutic medicine for treating aging-associated diseases.

Archaeal Clusters of Orthologous Genes (arCOGs): An Update and Application for Analysis of Shared Features between Thermococcales, Methanococcales, and Methanobacteriales

PubMed Central

Makarova, Kira S.; Wolf, Yuri I.; Koonin, Eugene V.

2015-01-01

With the continuously accelerating genome sequencing from diverse groups of archaea and bacteria, accurate identification of gene orthology and availability of readily expandable clusters of orthologous genes are essential for the functional annotation of new genomes. We report an update of the collection of archaeal Clusters of Orthologous Genes (arCOGs) to cover, on average, 91% of the protein-coding genes in 168 archaeal genomes. The new arCOGs were constructed using refined algorithms for orthology identification combined with extensive manual curation, including incorporation of the results of several completed and ongoing research projects in archaeal genomics. A new level of classification is introduced, superclusters that unit two or more arCOGs and more completely reflect gene family evolution than individual, disconnected arCOGs. Assessment of the current archaeal genome annotation in public databases indicates that consistent use of arCOGs can significantly improve the annotation quality. In addition to their utility for genome annotation, arCOGs also are a platform for phylogenomic analysis. We explore this aspect of arCOGs by performing a phylogenomic study of the Thermococci that are traditionally viewed as the basal branch of the Euryarchaeota. The results of phylogenomic analysis that involved both comparison of multiple phylogenetic trees and a search for putative derived shared characters by using phyletic patterns extracted from the arCOGs reveal a likely evolutionary relationship between the Thermococci, Methanococci, and Methanobacteria. The arCOGs are expected to be instrumental for a comprehensive phylogenomic study of the archaea. PMID:25764277

Passenger mutations and aberrant gene expression in congenic tissue plasminogen activator-deficient mouse strains.

PubMed

Szabo, R; Samson, A L; Lawrence, D A; Medcalf, R L; Bugge, T H

2016-08-01

Essentials C57BL/6J-tissue plasminogen activator (tPA)-deficient mice are widely used to study tPA function. Congenic C57BL/6J-tPA-deficient mice harbor large 129-derived chromosomal segments. The 129-derived chromosomal segments contain gene mutations that may confound data interpretation. Passenger mutation-free isogenic tPA-deficient mice were generated for study of tPA function. Background The ability to generate defined null mutations in mice revolutionized the analysis of gene function in mammals. However, gene-deficient mice generated by using 129-derived embryonic stem cells may carry large segments of 129 DNA, even when extensively backcrossed to reference strains, such as C57BL/6J, and this may confound interpretation of experiments performed in these mice. Tissue plasminogen activator (tPA), encoded by the PLAT gene, is a fibrinolytic serine protease that is widely expressed in the brain. A number of neurological abnormalities have been reported in tPA-deficient mice. Objectives To study genetic contamination of tPA-deficient mice. Materials and methods Whole genome expression array analysis, RNAseq expression profiling, low- and high-density single nucleotide polymorphism (SNP) analysis, bioinformatics and genome editing were used to analyze gene expression in tPA-deficient mouse brains. Results and conclusions Genes differentially expressed in the brain of Plat(-/-) mice from two independent colonies highly backcrossed onto the C57BL/6J strain clustered near Plat on chromosome 8. SNP analysis attributed this anomaly to about 20 Mbp of DNA flanking Plat being of 129 origin in both strains. Bioinformatic analysis of these 129-derived chromosomal segments identified a significant number of mutations in genes co-segregating with the targeted Plat allele, including several potential null mutations. Using zinc finger nuclease technology, we generated novel 'passenger mutation'-free isogenic C57BL/6J-Plat(-/-) and FVB/NJ-Plat(-/-) mouse strains by introducing an 11 bp deletion into the exon encoding the signal peptide. These novel mouse strains will be a useful community resource for further exploration of tPA function in physiological and pathological processes. © 2016 International Society on Thrombosis and Haemostasis.

Inherited variation in immune response genes in follicular lymphoma and diffuse large B-cell lymphoma.

PubMed

Nielsen, Kaspar Rene; Steffensen, Rudi; Haunstrup, Thure Mors; Bødker, Julie Støve; Dybkær, Karen; Baech, John; Bøgsted, Martin; Johnsen, Hans Erik

2015-01-01

Diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) both depend on immune-mediated survival and proliferation signals from the tumor microenvironment. Inherited genetic variation influences this complex interaction. A total of 89 studies investigating immune-response genes in DLBCL and FL were critically reviewed. Relatively consistent association exists for variation in the tumor necrosis factor alpha (TNFA) and interleukin-10 loci and DLBCL risk; for DLBCL outcome association with the TNFA locus exists. Variations at chromosome 6p31-32 were associated with FL risk. Importantly, individual risk alleles have been shown to interact with each other. We suggest that the pathogenetic impact of polymorphic genes should include gene-gene interaction analysis and should be validated in preclinical model systems of normal B lymphopoiesis and B-cell malignancies. In the future, large cohort studies of interactions and genome-wide association studies are needed to extend the present findings and explore new risk alleles to be studied in preclinical models.

Gene Expression Omnibus (GEO): Microarray data storage, submission, retrieval, and analysis

PubMed Central

Barrett, Tanya

2006-01-01

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely distributes high-throughput molecular abundance data, predominantly gene expression data generated by DNA microarray technology. The database has a flexible design that can handle diverse styles of both unprocessed and processed data in a MIAME- (Minimum Information About a Microarray Experiment) supportive infrastructure that promotes fully annotated submissions. GEO currently stores about a billion individual gene expression measurements, derived from over 100 organisms, submitted by over 1,500 laboratories, addressing a wide range of biological phenomena. To maximize the utility of these data, several user-friendly Web-based interfaces and applications have been implemented that enable effective exploration, query, and visualization of these data, at the level of individual genes or entire studies. This chapter describes how the data are stored, submission procedures, and mechanisms for data retrieval and query. GEO is publicly accessible at http://www.ncbi.nlm.nih.gov/projects/geo/. PMID:16939800

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

Williams, Kelly Porter

Key goals towards national biosecurity include methods for analyzing pathogens, predicting their emergence, and developing countermeasures. These goals are served by studying bacterial genes that promote pathogenicity and the pathogenicity islands that mobilize them. Cyberinfrastructure promoting an island database advances this field and enables deeper bioinformatic analysis that may identify novel pathogenicity genes. New automated methods and rich visualizations were developed for identifying pathogenicity islands, based on the principle that islands occur sporadically among closely related strains. The chromosomally-ordered pan-genome organizes all genes from a clade of strains; gaps in this visualization indicate islands, and decorations of the gene matrixmore » facilitate exploration of island gene functions. A %E2%80%9Clearned phyloblocks%E2%80%9D method was developed for automated island identification, that trains on the phylogenetic patterns of islands identified by other methods. Learned phyloblocks better defined termini of previously identified islands in multidrug-resistant Klebsiella pneumoniae ATCC BAA-2146, and found its only antibiotic resistance island.« less

RNA-seq comparative analysis of Peking ducks spleen gene expression 24 h post-infected with duck plague virulent or attenuated virus.

PubMed

Liu, Tian; Cheng, Anchun; Wang, Mingshu; Jia, Renyong; Yang, Qiao; Wu, Ying; Sun, Kunfeng; Zhu, Dekang; Chen, Shun; Liu, Mafeng; Zhao, XinXin; Chen, Xiaoyue

2017-09-13

Duck plague virus (DPV), a member of alphaherpesvirus sub-family, can cause significant economic losses on duck farms in China. DPV Chinese virulent strain (CHv) is highly pathogenic and could induce massive ducks death. Attenuated DPV vaccines (CHa) have been put into service against duck plague with billions of doses in China each year. Researches on DPV have been development for many years, however, a comprehensive understanding of molecular mechanisms underlying pathogenicity of CHv strain and protection of CHa strain to ducks is still blank. In present study, we performed RNA-seq technology to analyze transcriptome profiling of duck spleens for the first time to identify differentially expressed genes (DEGs) associated with the infection of CHv and CHa at 24 h. Comparison of gene expression with mock ducks revealed 748 DEGs and 484 DEGs after CHv and CHa infection, respectively. Gene pathway analysis of DEGs highlighted valuable biological processes involved in host immune response, cell apoptosis and viral invasion. Genes expressed in those pathways were different in CHv infected duck spleens and CHa vaccinated duck spleens. The results may provide valuable information for us to explore the reasons of pathogenicity caused by CHv strain and protection activated by CHa strain.

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

PubMed Central

2010-01-01

Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

PubMed

Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

2010-01-18

The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

Systematic characterization of the peroxidase gene family provides new insights into fungal pathogenicity in Magnaporthe oryzae

PubMed Central

Mir, Albely Afifa; Park, Sook-Young; Sadat, Md. Abu; Kim, Seongbeom; Choi, Jaeyoung; Jeon, Junhyun; Lee, Yong-Hwan

2015-01-01

Fungal pathogens have evolved antioxidant defense against reactive oxygen species produced as a part of host innate immunity. Recent studies proposed peroxidases as components of antioxidant defense system. However, the role of fungal peroxidases during interaction with host plants has not been explored at the genomic level. Here, we systematically identified peroxidase genes and analyzed their impact on fungal pathogenesis in a model plant pathogenic fungus, Magnaporthe oryzae. Phylogeny reconstruction placed 27 putative peroxidase genes into 15 clades. Expression profiles showed that majority of them are responsive to in planta condition and in vitro H2O2. Our analysis of individual deletion mutants for seven selected genes including MoPRX1 revealed that these genes contribute to fungal development and/or pathogenesis. We identified significant and positive correlations among sensitivity to H2O2, peroxidase activity and fungal pathogenicity. In-depth analysis of MoPRX1 demonstrated that it is a functional ortholog of thioredoxin peroxidase in Saccharomyces cerevisiae and is required for detoxification of the oxidative burst within host cells. Transcriptional profiling of other peroxidases in ΔMoprx1 suggested interwoven nature of the peroxidase-mediated antioxidant defense system. The results from this study provide insight into the infection strategy built on evolutionarily conserved peroxidases in the rice blast fungus. PMID:26134974

Comparison of Gene Expression in Human Embryonic Stem Cells, hESC-Derived Mesenchymal Stem Cells and Human Mesenchymal Stem Cells.

PubMed

Barbet, Romain; Peiffer, Isabelle; Hatzfeld, Antoinette; Charbord, Pierre; Hatzfeld, Jacques A

2011-01-01

We present a strategy to identify developmental/differentiation and plasma membrane marker genes of the most primitive human Mesenchymal Stem Cells (hMSCs). Using sensitive and quantitative TaqMan Low Density Arrays (TLDA) methodology, we compared the expression of 381 genes in human Embryonic Stem Cells (hESCs), hESC-derived MSCs (hES-MSCs), and hMSCs. Analysis of differentiation genes indicated that hES-MSCs express the sarcomeric muscle lineage in addition to the classical mesenchymal lineages, suggesting they are more primitive than hMSCs. Transcript analysis of membrane antigens suggests that IL1R1(low), BMPR1B(low), FLT4(low), LRRC32(low), and CD34 may be good candidates for the detection and isolation of the most primitive hMSCs. The expression in hMSCs of cytokine genes, such as IL6, IL8, or FLT3LG, without expression of the corresponding receptor, suggests a role for these cytokines in the paracrine control of stem cell niches. Our database may be shared with other laboratories in order to explore the considerable clinical potential of hES-MSCs, which appear to represent an intermediate developmental stage between hESCs and hMSCs.

The Glaciozyma antarctica genome reveals an array of systems that provide sustained responses towards temperature variations in a persistently cold habitat

PubMed Central

Hashim, Noor Haza Fazlin; Bharudin, Izwan; Abu Bakar, Mohd Faizal; Huang, Kie Kyon; Alias, Halimah; Lee, Bernard K. B.; Mat Isa, Mohd Noor; Mat-Sharani, Shuhaila; Sulaiman, Suhaila; Tay, Lih Jinq; Zolkefli, Radziah; Muhammad Noor, Yusuf; Law, Douglas Sie Nguong; Abdul Rahman, Siti Hamidah; Md-Illias, Rosli; Abu Bakar, Farah Diba; Najimudin, Nazalan; Abdul Murad, Abdul Munir; Mahadi, Nor Muhammad

2018-01-01

Extremely low temperatures present various challenges to life that include ice formation and effects on metabolic capacity. Psyhcrophilic microorganisms typically have an array of mechanisms to enable survival in cold temperatures. In this study, we sequenced and analysed the genome of a psychrophilic yeast isolated in the Antarctic region, Glaciozyma antarctica. The genome annotation identified 7857 protein coding sequences. From the genome sequence analysis we were able to identify genes that encoded for proteins known to be associated with cold survival, in addition to annotating genes that are unique to G. antarctica. For genes that are known to be involved in cold adaptation such as anti-freeze proteins (AFPs), our gene expression analysis revealed that they were differentially transcribed over time and in response to different temperatures. This indicated the presence of an array of adaptation systems that can respond to a changing but persistent cold environment. We were also able to validate the activity of all the AFPs annotated where the recombinant AFPs demonstrated anti-freeze capacity. This work is an important foundation for further collective exploration into psychrophilic microbiology where among other potential, the genes unique to this species may represent a pool of novel mechanisms for cold survival. PMID:29385175

The LAM-PCR Method to Sequence LV Integration Sites.

PubMed

Wang, Wei; Bartholomae, Cynthia C; Gabriel, Richard; Deichmann, Annette; Schmidt, Manfred

2016-01-01

Integrating viral gene transfer vectors are commonly used gene delivery tools in clinical gene therapy trials providing stable integration and continuous gene expression of the transgene in the treated host cell. However, integration of the reverse-transcribed vector DNA into the host genome is a potentially mutagenic event that may directly contribute to unwanted side effects. A comprehensive and accurate analysis of the integration site (IS) repertoire is indispensable to study clonality in transduced cells obtained from patients undergoing gene therapy and to identify potential in vivo selection of affected cell clones. To date, next-generation sequencing (NGS) of vector-genome junctions allows sophisticated studies on the integration repertoire in vitro and in vivo. We have explored the use of the Illumina MiSeq Personal Sequencer platform to sequence vector ISs amplified by non-restrictive linear amplification-mediated PCR (nrLAM-PCR) and LAM-PCR. MiSeq-based high-quality IS sequence retrieval is accomplished by the introduction of a double-barcode strategy that substantially minimizes the frequency of IS sequence collisions compared to the conventionally used single-barcode protocol. Here, we present an updated protocol of (nr)LAM-PCR for the analysis of lentiviral IS using a double-barcode system and followed by deep sequencing using the MiSeq device.

Spatial and temporal expression of the Grainyhead-like transcription factor family during murine development.

PubMed

Auden, Alana; Caddy, Jacinta; Wilanowski, Tomasz; Ting, Stephen B; Cunningham, John M; Jane, Stephen M

2006-10-01

The Drosophila transcription factor Grainyhead (grh) is expressed in ectoderm-derived tissues where it regulates several key developmental events including cuticle formation, tracheal elongation and dorsal closure. Our laboratory has recently identified three novel mammalian homologues of the grh gene, Grainyhead-like 1, -2 and -3 (Grhl1-3) that rewrite the phylogeny of this family. Using gene targeting in mice, we have shown that Grhl3 is essential for neural tube closure, skin barrier formation and wound healing. Despite their extensive sequence homology, Grhl1 and Grhl2 are unable to compensate for loss of Grhl3 in these developmental processes. To explore this lack of redundancy, and to gain further insights into the functions of this gene family in mammalian development we have performed an extensive in situ hybridisation analysis. We demonstrate that, although all three Grhl genes are highly expressed in the developing epidermis, they display subtle differences in the timing and level of expression. Surprisingly, we also demonstrate differential expression patterns in non-ectoderm-derived tissues, including the heart, the lung, and the metanephric kidney. These findings expand our understanding of the unique role of Grhl3 in neurulation and epidermal morphogenesis, and provide a focus for further functional analysis of the Grhl genes during mouse embryogenesis.

Genome-wide analysis of Glycine soja ubiquitin (UBQ) genes and functional analysis of GsUBQ10 in response to alkaline stress.

PubMed

Chen, Chao; Chen, Ranran; Wu, Shengyang; Zhu, Dan; Sun, Xiaoli; Liu, Beidong; Li, Qiang; Zhu, Yanming

2018-03-26

Ubiquitin is a highly conserved protein with multiple essential regulation functions through the ubiquitin-proteasome system. Even though its functions in the ubiquitin-mediated protein degradation pathway were very well characterized. The functions of ubiquitin genes in regulating alkaline stress response are not fully established. In this study, we identified 12 potential UBQ genes in Glycine soja genome, and analyzed their evolutionary relationship, conserved domains and promoter cis-elements. We also explored the expression profiles of G. soja UBQ genes under alkaline stress, based on the transcriptome sequencing. We found that the expression of GsUBQ10 was significantly induced by alkaline stress, and function of GsUBQ10 was characterized using overexpression transgenic alfalfa (Medicago sativa). Our results suggested that GsUBQ10 transgenic lines significantly improved the alkaline tolerance in alfalfa. The GsUBQ10 transgenic lines showed lower relative membrane permeability, lower malon dialdehyde content and higher catalase activity than in the wild-type plants. This indicates that GsUBQ10 is involved in regulating the reactive oxygen species accumulation under alkaline stress. Taken together, we identified an ubiquitin gene GsUBQ10 from G. soja, which plays a positive role in responses to alkaline stress in alfalfa. This article is protected by copyright. All rights reserved.

Haplotypes in the APOA1-C3-A4-A5 gene cluster affect plasma lipids in both humans and baboons

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

Wang, Qian-fei; Liu, Xin; O'Connell, Jeff

2003-09-15

Genetic studies in non-human primates serve as a potential strategy for identifying genomic intervals where polymorphisms impact upon human disease-related phenotypes. It remains unclear, however, whether independently arising polymorphisms in orthologous regions of non-human primates leads to similar variation in a quantitative trait found in both species. To explore this paradigm, we studied a baboon apolipoprotein gene cluster (APOA1/C3/A4/A5) for which the human gene orthologs have well established roles in influencing plasma HDL-cholesterol and triglyceride concentrations. Our extensive polymorphism analysis of this 68 kb gene cluster in 96 pedigreed baboons identified several haplotype blocks each with limited diversity, consistent withmore » haplotype findings in humans. To determine whether baboons, like humans, also have particular haplotypes associated with lipid phenotypes, we genotyped 634 well characterized baboons using 16 haplotype tagging SNPs. Genetic analysis of single SNPs, as well as haplotypes, revealed an association of APOA5 and APOC3 variants with HDL cholesterol and triglyceride concentrations, respectively. Thus, independent variation in orthologous genomic intervals does associate with similar quantitative lipid traits in both species, supporting the possibility of uncovering human QTL genes in a highly controlled non-human primate model.« less

Analysis for the presence of determinants involved in the transport of mercury across bacterial membrane from polluted water bodies of India

PubMed Central

Jan, Arif Tasleem; Azam, Mudsser; Choi, Inho; Ali, Arif; Haq, Qazi Mohd. Rizwanul

2016-01-01

Mercury, which is ubiquitous and recalcitrant to biodegradation processes, threatens human health by escaping to the environment via various natural and anthropogenic activities. Non-biodegradability of mercury pollutants has necessitated the development and implementation of economic alternatives with promising potential to remove metals from the environment. Enhancement of microbial based remediation strategies through genetic engineering approaches provides one such alternative with a promising future. In this study, bacterial isolates inhabiting polluted sites were screened for tolerance to varying concentrations of mercuric chloride. Following identification, several Pseudomonas and Klebsiella species were found to exhibit the highest tolerance to both organic and inorganic mercury. Screened bacterial isolates were examined for their genetic make-up in terms of the presence of genes (merP and merT) involved in the transport of mercury across the membrane either alone or in combination to deal with the toxic mercury. Gene sequence analysis revealed that the merP gene showed 86–99% homology, while the merT gene showed >98% homology with previously reported sequences. By exploring the genes involved in imparting metal resistance to bacteria, this study will serve to highlight the credentials that are particularly advantageous for their practical application to remediation of mercury from the environment. PMID:26887227

De Novo Assembled Wheat Transcriptomes Delineate Differentially Expressed Host Genes in Response to Leaf Rust Infection.

PubMed

Chandra, Saket; Singh, Dharmendra; Pathak, Jyoti; Kumari, Supriya; Kumar, Manish; Poddar, Raju; Balyan, Harindra Singh; Gupta, Puspendra Kumar; Prabhu, Kumble Vinod; Mukhopadhyay, Kunal

2016-01-01

Pathogens like Puccinia triticina, the causal organism for leaf rust, extensively damages wheat production. The interaction at molecular level between wheat and the pathogen is complex and less explored. The pathogen induced response was characterized using mock- or pathogen inoculated near-isogenic wheat lines (with or without seedling leaf rust resistance gene Lr28). Four Serial Analysis of Gene Expression libraries were prepared from mock- and pathogen inoculated plants and were subjected to Sequencing by Oligonucleotide Ligation and Detection, which generated a total of 165,767,777 reads, each 35 bases long. The reads were processed and multiple k-mers were attempted for de novo transcript assembly; 22 k-mers showed the best results. Altogether 21,345 contigs were generated and functionally characterized by gene ontology annotation, mining for transcription factors and resistance genes. Expression analysis among the four libraries showed extensive alterations in the transcriptome in response to pathogen infection, reflecting reorganizations in major biological processes and metabolic pathways. Role of auxin in determining pathogenesis in susceptible and resistant lines were imperative. The qPCR expression study of four LRR-RLK (Leucine-rich repeat receptor-like protein kinases) genes showed higher expression at 24 hrs after inoculation with pathogen. In summary, the conceptual model of induced resistance in wheat contributes insights on defense responses and imparts knowledge of Puccinia triticina-induced defense transcripts in wheat plants.

Genome-wide analysis of the Glycerol-3-Phosphate Acyltransferase (GPAT) gene family reveals the evolution and diversification of plant GPATs

PubMed Central

Waschburger, Edgar; Kulcheski, Franceli Rodrigues; Veto, Nicole Moreira; Margis, Rogerio; Margis-Pinheiro, Marcia; Turchetto-Zolet, Andreia Carina

2018-01-01

Abstract sn-Glycerol-3-phosphate 1-O-acyltransferase (GPAT) is an important enzyme that catalyzes the transfer of an acyl group from acyl-CoA or acyl-ACP to the sn-1 or sn-2 position of sn-glycerol-3-phosphate (G3P) to generate lysophosphatidic acids (LPAs). The functional studies of GPAT in plants demonstrated its importance in controlling storage and membrane lipid. Identifying genes encoding GPAT in a variety of plant species is crucial to understand their involvement in different metabolic pathways and physiological functions. Here, we performed genome-wide and evolutionary analyses of GPATs in plants. GPAT genes were identified in all algae and plants studied. The phylogenetic analysis showed that these genes group into three main clades. While clades I (GPAT9) and II (soluble GPAT) include GPATs from algae and plants, clade III (GPAT1-8) includes GPATs specific from plants that are involved in the biosynthesis of cutin or suberin. Gene organization and the expression pattern of GPATs in plants corroborate with clade formation in the phylogeny, suggesting that the evolutionary patterns is reflected in their functionality. Overall, our results provide important insights into the evolution of the plant GPATs and allowed us to explore the evolutionary mechanism underlying the functional diversification among these genes. PMID:29583156

De Novo Assembled Wheat Transcriptomes Delineate Differentially Expressed Host Genes in Response to Leaf Rust Infection

PubMed Central

Pathak, Jyoti; Kumari, Supriya; Kumar, Manish; Poddar, Raju; Balyan, Harindra Singh; Gupta, Puspendra Kumar; Prabhu, Kumble Vinod; Mukhopadhyay, Kunal

2016-01-01

Pathogens like Puccinia triticina, the causal organism for leaf rust, extensively damages wheat production. The interaction at molecular level between wheat and the pathogen is complex and less explored. The pathogen induced response was characterized using mock- or pathogen inoculated near-isogenic wheat lines (with or without seedling leaf rust resistance gene Lr28). Four Serial Analysis of Gene Expression libraries were prepared from mock- and pathogen inoculated plants and were subjected to Sequencing by Oligonucleotide Ligation and Detection, which generated a total of 165,767,777 reads, each 35 bases long. The reads were processed and multiple k-mers were attempted for de novo transcript assembly; 22 k-mers showed the best results. Altogether 21,345 contigs were generated and functionally characterized by gene ontology annotation, mining for transcription factors and resistance genes. Expression analysis among the four libraries showed extensive alterations in the transcriptome in response to pathogen infection, reflecting reorganizations in major biological processes and metabolic pathways. Role of auxin in determining pathogenesis in susceptible and resistant lines were imperative. The qPCR expression study of four LRR-RLK (Leucine-rich repeat receptor-like protein kinases) genes showed higher expression at 24 hrs after inoculation with pathogen. In summary, the conceptual model of induced resistance in wheat contributes insights on defense responses and imparts knowledge of Puccinia triticina-induced defense transcripts in wheat plants. PMID:26840746