EXPRESSION QTL MAPPING ACROSS SOIL MOISTURE ENVIRONMENTS REVEALS CONTRASTING ASSOCIATIONS WITH GENOMIC FEATURES IN ARABIDOPSIS THALIANA
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ABSTRACT:
ORGANISM(S): Arabidopsis thaliana
PROVIDER: GSE42408 | GEO | 2013/03/02
SECONDARY ACCESSION(S): PRJNA181341
REPOSITORIES: GEO
Similar Datasets
Project description:Understanding the patterns and processes driving natural genetic variation in gene expression is of fundamental importance to biology. In this study, we examined genetic variation in gene transcription through expression QTL (eQTL) analysis in the Tsu-1 x Kas-1 recombinant inbred line (RIL) mapping population of Arabidopsis thaliana. To understand how natural variation in transcription responds to abiotic stress, we conducted eQTL in both well watered and soil drying conditions. Further, we evaluated whether elements of genome structure were associated with eQTL occurance and genes responding to treatment conditions. Overall, we identified thousands of genes that responded to soil moisture availability and hundreds of eQTLs. However, we identified very few interactions between eQTLs and environmental conditions, and both treatment conditions were enriched for similar gene ontology (GO) categories. We did find strong evidence for associations between genome structure and natural variation in transcription. In general, genes with eQTLs were positively associated with local recombination rates and levels of polymorphism while genes responding to the treatment were negatively correlated with these factors. Our study provides further insight into the origin and maintenance of natural variation in transcription and how that variation responds to environmental conditions. Expression analysis by hybridization to atSNPTILE array (Affymetrix). Seed of the 104 RILs from reciprocal crosses between A. thaliana (L.) Heynh. accessions Kas-1 (CS903) and Tsu-1 (CS1640) were sown on fritted clay (Profile Products LLC, Buffalo Grove, IL) in 2.5-inch pots. Plants were arranged in a randomized complete block design consisting of 4 blocks, and then the pots were refrigerated at 4°C in darkness for 6 d to cold-stratify the seeds prior to commencement of a 12 h photoperiod in Conviron ATC60 growth chambers (Controlled Environments, Winnipeg, MB), at 23°C and 40% humidity during the day and 20°C and 50% humidity during the dark period. Light intensity was approximately 330 µmol m-2 s-1. After four weeks of growth, half of the plants were given a drought treatment, while the others remained fully watered. The drought treatment was randomly assigned to 2 of the 4 blocks and consisted of a slow decrease in soil moisture content over the course of one week. Each day, all pots assigned to the drought treatment were weighed, and water was added to individual pots to bring them to the target gravimetric water content. The target water content decreased each day, in the following series: 100%, 90%, 80%, 70%, 60%, 45%, and 40% of field capacity. At the end of the treatment, leaf tissue was collected from both treatments for RNA extraction.
2013-03-02 | E-GEOD-42408 | biostudies-arrayexpress
Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. Totally 1,632 single feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1,459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hotspots among rice genome, each of which controls transcript variations of many e-traits. Gene Ontology analysis revealed enrichment of certain functional categories of genes in some of the eQTL hotspots. In particular, eQTLs for e-traits involving DNA metabolic process was significantly enriched in several eQTL hotspots on chromosomes 3, 5 and 10. Several transcription factors colocalizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between the QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided the clues for identification and characterization of regulatory network in the whole genome at the transcriptional level. To dissect the genetic variation between the two rice indica varieties Minghui 63 and Zhenshan 97, a total of 110 RILs from Minghui 63 and Zhenshan 97 and parents were sampled. And the Affymetrix Genechip rice Genome Array was used to investigate their dynamic transcript levels. Two independent biological replicates were sampled from each RIL, and three replicates for each parent.resulting in a dataset of 226 microarrays.
2011-06-24 | E-GEOD-22564 | biostudies-arrayexpress
Project description:BACKGROUND: The genetics of transcript-level variation is an exciting field that has recently given rise to many studies. Genetical genomics studies have mainly focused on cell lines, blood cells or adipose tissues, from human clinical samples or mice inbred lines. Few eQTL studies have focused on animal tissues sampled from outbred populations to reflect natural genetic variation of gene expression levels in animals. In this work, we analyzed gene expression in a whole tissue, pig skeletal muscle sampled from individuals from a half sib F2 family shortly after slaughtering. RESULTS: QTL detection on transcriptome measurements was performed on a family structured population. The analysis identified 335 eQTLs affecting the expression of 272 transcripts. The ontologic annotation of these eQTLs revealed an over-representation of genes encoding proteins involved in processes that are expected to be induced during muscle development and metabolism, cell morphology, assembly and organization and also in stress response and apoptosis. A gene functional network approach was used to evidence existing biological relationships between all the genes whose expression levels are influenced by eQTLs. eQTLs localization revealed a significant clustered organization of about half the genes located on segments of chromosome 1, 2, 10, 13, 16, and 18. Finally, the combined expression and genetic approaches pointed to putative cis-drivers of gene expression programs in skeletal muscle as COQ4 (SSC1), LOC100513192 (SSC18) where both the gene transcription unit and the eQTL affecting its expression level were shown to be localized in the same genomic region. This suggests cis-causing genetic polymorphims affecting gene expression levels, with (e.g. COQ4) or without (e.g. LOC100513192) potential pleiotropic effects that affect the expression of other genes (cluster of trans-eQTLs). CONCLUSION: Genetic analysis of transcription levels revealed dependence among molecular phenotypes as being affected by variation at the same loci. We observed the genetic variation of molecular phenotypes in a specific situation of cellular stress thus contributing to a better description of muscle physiologic response. In turn, this suggests that large amounts of genetic variation, mediated through transcriptional networks, can drive transient cell response phenotypes and contribute to organismal adaptative potential.
2011-11-10 | GSE26924 | GEO
Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. Totally 1,632 single feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1,459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hotspots among rice genome, each of which controls transcript variations of many e-traits. Gene Ontology analysis revealed enrichment of certain functional categories of genes in some of the eQTL hotspots. In particular, eQTLs for e-traits involving DNA metabolic process was significantly enriched in several eQTL hotspots on chromosomes 3, 5 and 10. Several transcription factors colocalizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between the QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided the clues for identification and characterization of regulatory network in the whole genome at the transcriptional level.
2011-06-24 | GSE22564 | GEO
Project description:Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. While all eQTL studies to date have assayed mRNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblastoid cell lines (LCLs) derived from unrelated Nigerian individuals that have been extensively genotyped by the International HapMap Project. Pooling data from all individuals, we generated a map of the transcriptional landscape of these cells, identifying extensive use of unannotated polyadenylation sites and over 100 novel putative protein-coding exons. Using the genotypes from the HapMap project, we identified over a thousand genes at which genetic variation influences overall expression levels or splicing. We demonstrate that eQTLs near genes generally act via a mechanism involving allele-specific expression, and that variation that influences the inclusion of an exon is enriched within or near the consensus splice sites. Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing, and allele-specific expression across individuals. RNA-Seq in 69 lymphoblastoid cell lines from multiple Yoruban HapMap individuals in at least two replicate lanes per individual
2010-02-28 | E-GEOD-19480 | biostudies-arrayexpress
Project description:Gene transcription is an essential step of gene function and transcriptome variation is of agronomical, ecological and evolutionary importance. To explore global expression patterns and dissect the underlying genetic mechanisms are important scientific inquires which are still largely unknown, especially between a segregating population and the parents. In our study, we used RNA-Seq to profile the shoot apex transcriptome variation (including protein coding genes and non-coding genes) in maize IBM RIL population, to map eQTLs underlying the transcriptome variations and to utilize eQTLs to clone genes involved in maize shoot apices development. We revealed that: Much of the variation (the population mean, the coefficient of variation) of gene expression levels in RILs is reflective of differences present among the parents; These transcriptome variations could be explained by 30,774 eQTLs with 96 trans-eQTL hotspots; In many cases, the genes commonly regulated by a trans-eQTL hotspot are enriched for a specific function or act in the same genetic pathway; Structural variation within and near genes contributs to cis-regulatory variation. All of these results indicate Mendelian factors play as major contributors to the transcriptome variation. Meanwhile, non-Mendelian regulations were also observed as paramutation-like expression pattern for 145 genes, of which 88% genes were predicted to be potential targets of miRNAs or ta-siRNAs, and as unexpected presence/absence expression patterns for 210 genes. These genes with unexpected presence/absence expression patterns in the RILs likely include examples of functional genes as well as transposed gene fragments that may contribute to regulatory variation of their ancestral syntenic genes.
2013-01-30 | E-MTAB-4227 | biostudies-arrayexpress
Project description:Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. While all eQTL studies to date have assayed mRNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblastoid cell lines (LCLs) derived from unrelated Nigerian individuals that have been extensively genotyped by the International HapMap Project. Pooling data from all individuals, we generated a map of the transcriptional landscape of these cells, identifying extensive use of unannotated polyadenylation sites and over 100 novel putative protein-coding exons. Using the genotypes from the HapMap project, we identified over a thousand genes at which genetic variation influences overall expression levels or splicing. We demonstrate that eQTLs near genes generally act via a mechanism involving allele-specific expression, and that variation that influences the inclusion of an exon is enriched within or near the consensus splice sites. Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing, and allele-specific expression across individuals.
2010-02-28 | GSE19480 | GEO
Project description:To assess natural variation in gene expression in Arabidopsis thaliana, genome wide gene expression variation was analyzed in a Ler/Cvi recombinant inbred line (RIL) population.The variation in expression could be explained for many genes by expression quantitative trait loci (eQTLs). These eQTLs are combined with regulator candidate gene selection to generate genetic regulatory networks.
2008-01-24 | E-TABM-214 | biostudies-arrayexpress
Project description:Profiles of sequence variants that influence gene transcription are very important for understanding mechanisms that affect phenotypic variation and disease susceptibility. Using genotypes at 1.4 million SNPs and a comprehensive transcriptional profile of 15,454 coding genes and 6,113 lincRNA genes obtained from peripheral blood cells of 298 Japanese individuals, we mapped expression quantitative trait loci (eQTLs). We identified 3,804 cis-eQTLs (within 500 kb from target genes) and 165 trans-eQTLs (>500 kb away or on different chromosomes). Cis-eQTLs were often located in transcribed or adjacent regions of genes; among these regions, 5’ untranslated regions and 5’ flanking regions had the largest effects. Epigenetic evidence for regulatory potential accumulated in public databases explained the magnitude of the effects of our eQTLs. Cis-eQTLs were often located near the respective target genes, if not within genes. Large effect sizes were observed with eQTLs near target genes, and effect sizes were obviously attenuated as the eQTL distance from the gene increased. Using a very stringent significance threshold, we identified 165 large-effect trans-eQTLs. We used our eQTL map to assess 8,069 disease-associated SNPs identified in 1,436 genome-wide association studies (GWAS). We identified genes that might be truly causative, but GWAS might have failed to identify for 148 out of the GWAS-identified SNPs; for example, TUFM (P=3.3E-48) was identified for inflammatory bowel disease (early onset); ZFP90 (P=4.4E-34) for ulcerative colitis; and IDUA (P=2.2E-11) for Parkinson's disease. We identified four genes (P<2.0E-14) that might be related to three diseases and two hematological traits; each expression is regulated by trans-eQTLs on a different chromosome than the gene. The study subjects were 301 apparently healthy individuals residing in Nagahama City, Japan. Whole blood was collected from each participant when in a non-stimulated state.
2014-06-23 | E-GEOD-53351 | biostudies-arrayexpress
Project description:BACKGROUND: The genetics of transcript-level variation is an exciting field that has recently given rise to many studies. Genetical genomics studies have mainly focused on cell lines, blood cells or adipose tissues, from human clinical samples or mice inbred lines. Few eQTL studies have focused on animal tissues sampled from outbred populations to reflect natural genetic variation of gene expression levels in animals. In this work, we analyzed gene expression in a whole tissue, pig skeletal muscle sampled from individuals from a half sib F2 family shortly after slaughtering. RESULTS: QTL detection on transcriptome measurements was performed on a family structured population. The analysis identified 335 eQTLs affecting the expression of 272 transcripts. The ontologic annotation of these eQTLs revealed an over-representation of genes encoding proteins involved in processes that are expected to be induced during muscle development and metabolism, cell morphology, assembly and organization and also in stress response and apoptosis. A gene functional network approach was used to evidence existing biological relationships between all the genes whose expression levels are influenced by eQTLs. eQTLs localization revealed a significant clustered organization of about half the genes located on segments of chromosome 1, 2, 10, 13, 16, and 18. Finally, the combined expression and genetic approaches pointed to putative cis-drivers of gene expression programs in skeletal muscle as COQ4 (SSC1), LOC100513192 (SSC18) where both the gene transcription unit and the eQTL affecting its expression level were shown to be localized in the same genomic region. This suggests cis-causing genetic polymorphims affecting gene expression levels, with (e.g. COQ4) or without (e.g. LOC100513192) potential pleiotropic effects that affect the expression of other genes (cluster of trans-eQTLs). CONCLUSION: Genetic analysis of transcription levels revealed dependence among molecular phenotypes as being affected by variation at the same loci. We observed the genetic variation of molecular phenotypes in a specific situation of cellular stress thus contributing to a better description of muscle physiologic response. In turn, this suggests that large amounts of genetic variation, mediated through transcriptional networks, can drive transient cell response phenotypes and contribute to organismal adaptative potential. A wide genomic project was designed to combine genetic and transcriptome analysis. This project involved about 1,000 F2 pigs from 15 half-sib families to identify QTL for meat quality traits (Cherel et al., unpublished data). In this study, we focused on one family of 57 half sib F2 pigs. Total RNA was isolated from each of the 57 muscle samples using a commercial kit, and controlled for quality and concentration using an AGILENT 2100 bioanalyzer. cDNA was synthesized and labelled from 5 µg total RNA by simultaneous reverse transcription of mRNA using SuperScriptTM II RNase H- Reverse Transcriptase and 33P-deoxy-CTP. Each muscle sample mRNA was hybridized at 68°C during 24 h to one array. The arrays were then exposed to radioisotopic-sensitive imaging plates that were scanned thereafter with a phosphor imaging system at a 25 µm resolution. Hybridization images were quantified using a semi-automated software through a grid process with a fixed spot diameter. The output was then subjected to the data analysis process.
2011-11-10 | E-GEOD-26924 | biostudies-arrayexpress