Identification of genes and quantitative trait loci (QTL) that control hematopoietic stem cell functioning
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE2031 | GEO | 2004/12/02
SECONDARY ACCESSION(S): PRJNA91863
REPOSITORIES: GEO
Similar Datasets
Project description:We have combined large-scale mRNA expression and gene mapping methods to identify genes and loci that control hematopoietic stem cell (HSC) functioning. mRNA expression levels were measured in purified HSC isolated from a panel of densely genotyped recombinant inbred mouse strains. Quantitative trait loci (QTLs) associated with variation in expression of thousands of transcripts were mapped. Comparison of the physical transcript position with the location of the controlling QTL identified polymorphic cis-acting stem cell genes. In addition, multiple trans-acting control loci were highlighted that modify expression of large numbers of genes. These groups of co-regulated transcripts identify pathways that specify variation in stem cells. We illustrate this concept with the identification of strong candidate genes involved with HSC turnover. We compared expression QTLs in HSC and brain from the same animals, and document both shared and tissue-specific QTLs. Our data are accessible through WebQTL, a web-based interface that allows custom genetic linkage analysis and identification of co-regulated transcripts.
2007-11-16 | E-GEOD-2031 | biostudies-arrayexpress
Project description:Genetic variants that impact gene regulation are important contributors to human phenotypic variation. For this reason, considerable efforts have been made to identify genetic associations with differences in mRNA levels of nearby genes, namely, cis expression quantitative trait loci (eQTLs). The phenotypic consequences of eQTLs are presumably due, in most cases, to their ultimate effects on protein expression levels. Yet, only few studies have quantified the impact of genetic variation on proteins levels directly. It remains unclear how faithfully eQTLs are reflected at the protein level, and whether there is a significant layer of cis regulatory variation acting primarily on translation or steady state protein levels. To address these questions, we measured ribosome occupancy by high-throughput sequencing, and relative protein levels by high-resolution quantitative mass spectrometry, in a panel of lymphoblastoid cell lines (LCLs) in which we had previously measured transcript expression using RNA sequencing. We then mapped genetic variants that are associated with changes in transcript expression (eQTLs), ribosome occupancy (rQTLs), or protein abundance (pQTLs). Most of the QTLs we detected are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, we found that eQTLs tend to have significantly reduced effect sizes on protein levels, suggesting that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we confirmed the presence of a class of cis QTLs that specifically affect protein abundance with little or no effect on mRNA levels; most of these QTLs have little effect on ribosome occupancy, and hence may arise from differences in post-translational regulation.
2014-12-19 | PXD001406 | Pride
Project description:A proportion of the genetic variants underlying complex phenotypes do so through their effects on gene expression, so an important challenge in complex trait analysis is to discover the genetic basis for the variation in transcript abundance. So far, the potential of mapping both quantitative trait loci (QTLs) and expression quantitative trait loci (eQTLs) in rodents has been limited by the low mapping resolution inherent in crosses between inbred strains. We provide a megabase resolution map of thousands of eQTLs in hippocampus, lung, and liver samples from heterogeneous stock (HS) mice in which 843 QTLs have also been mapped at megabase resolution. We exploit dense mouse SNP data to show that artifacts due to allele-specific hybridization occur in _30% of the cis-acting eQTLs and, by comparison with exon expression data, we show that alternative splicing of the 3_ end of the genes accounts for <1% of cis-acting eQTLs. Approximately one third of cis-acting eQTLs and one half of trans-acting eQTLs are tissue specific. We have created an important systems biology resource for the genetic analysis of complex traits in a key model organism.
2009-10-22 | E-MTAB-88 | biostudies-arrayexpress
Project description:In rice (Oryza sativa L.), the number of panicles, spikelets per panicle and grain weight are important components of grain yield. These characteristics are controlled by quantitative trait loci (QTLs) and are derived from variation inherent in crops.The identification of different yield related QTLs facilitates an understanding of the mechanisms involved in cereal crop yield, and may have utility in improving grain yield in cereal crops. an understanding of the mechanisms involved in cereal crop yield, and may have utility in improving grain yield in cereal crops. In the present study, We cloned and characterized a large-panicle QTL, and confirmed that the newly identified gene OsEBS (enhancing biomass and spikelet number) increased plant height, leaf size and spikelet number per panicle, leading to an average of 37.62% increase in total grain yield per plant. trait loci (QTLs) and are derived from variation inherent in crops. OsEBS-transgenic rice B10201 and B10301 and control Guichao2
2013-05-04 | E-GEOD-46616 | biostudies-arrayexpress
Project description:In rice (Oryza sativa L.), the number of panicles, spikelets per panicle and grain weight are important components of grain yield. These characteristics are controlled by quantitative trait loci (QTLs) and are derived from variation inherent in crops.The identification of different yield related QTLs facilitates an understanding of the mechanisms involved in cereal crop yield, and may have utility in improving grain yield in cereal crops. an understanding of the mechanisms involved in cereal crop yield, and may have utility in improving grain yield in cereal crops. In the present study, We cloned and characterized a large-panicle QTL, and confirmed that the newly identified gene OsEBS (enhancing biomass and spikelet number) increased plant height, leaf size and spikelet number per panicle, leading to an average of 37.62% increase in total grain yield per plant. trait loci (QTLs) and are derived from variation inherent in crops.
2013-05-04 | GSE46616 | GEO
Project description:The liver is the primary site for the metabolism of nutrients, drugs, and chemical agents. Although metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variations in gene expression levels, introduces complexity into research on liver disease. This study dissected genetic networks that control liver gene expression through the combination of large-scale quantitative mRNA expression analysis with genetic mapping in a reference population of BXD recombinant inbred mouse strains for which extensive single-nucleotide polymorphism, haplotype, and phenotypic data are publicly available. We profiled gene expression in livers of naive mice of both sexes from C57BL/6J, DBA/2J, B6D2F1, and 41 BXD strains using Agilent oligonucleotide microarrays. These data were used to map quantitative trait loci (QTLs) responsible for variations in the expression of about 19,000 transcripts. We identified polymorphic local and distant QTLs, including several loci that control the expression of large numbers of genes in liver, by comparing the physical transcript position with the location of the controlling QTL. CONCLUSION: The data are available through a public web-based resource (www.genenetwork.org) that allows custom data mining, identification of coregulated transcripts and correlated phenotypes, cross-tissue, and cross-species comparisons, as well as testing of a broad array of hypotheses.
2009-08-06 | GSE17522 | GEO
Project description:Deciphering the impact of genetic variants on gene regulation is fundamental to understanding human disease. Although gene regulation often involves long-range interactions, it is unknown to what extent non-coding genetic variants influence distal molecular phenotypes. Here, we integrate chromatin profiling for three histone marks in lymphoblastoid cell lines (LCLs) from 75 sequenced individuals with LCL-specific Hi-C and ChIA-PET-based chromatin contact maps to uncover one of the largest collections of local and distal histone quantitative trait loci (hQTLs). Distal QTLs are enriched within topologically associated domains and exhibit largely concordant variation of chromatin state coordinated by proximal and distal non-coding genetic variants. Histone QTLs are enriched for common variants associated with autoimmune diseases and enable identification of putative target genes of disease-associated variants from genome-wide association studies. These analyses provide insights into how genetic variation can affect human disease phenotypes by coordinated changes in chromatin at interacting regulatory elements.
2015-08-20 | GSE62742 | GEO
Project description:The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid (SA) and jasmonic acid (JA), have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs, e-QTLs) affecting host resistance responses. We surveyed recombinant inbred lines (RILs) from a population derived from a cross of inbred Arabidopsis accessions Bayreuth-0 (Bay-0) and Shahdara (Sha) in order to map e-QTLs controlling ELPs. We treated vegetatively grown plants with either SA or a control solution (Silwet), and harvested the plants 28 hours after chemical treatment. We present Affymetrix GeneChip microarray expression data for 2 biological replications of the control (Silwet) samples for 148 RILs, plus replicated Bay-0 and Sha control samples grown at the same time as the RILs. These GeneChips were used to develop genetic markers and derive high-density haplotypes for the RILs
2007-01-10 | E-TABM-62 | biostudies-arrayexpress
Project description:Genetic variants that impact gene regulation are important contributors to human phenotypic variation. For this reason, considerable efforts have been made to identify genetic associations with differences in mRNA levels of nearby genes, namely, cis expression quantitative trait loci (eQTLs). The phenotypic consequences of eQTLs are presumably due, in most cases, to their ultimate effects on protein expression levels. Yet, only few studies have quantified the impact of genetic variation on proteins levels directly. It remains unclear how faithfully eQTLs are reflected at the protein level, and whether there is a significant layer of cis regulatory variation acting primarily on translation or steady state protein levels. To address these questions, we measured ribosome occupancy by high-throughput sequencing, and relative protein levels by high-resolution quantitative mass spectrometry, in a panel of lymphoblastoid cell lines (LCLs) in which we had previously measured transcript expression using RNA sequencing. We then mapped genetic variants that are associated with changes in transcript expression (eQTLs), ribosome occupancy (rQTLs), or protein abundance (pQTLs). Most of the QTLs we detected are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, we found that eQTLs tend to have significantly reduced effect sizes on protein levels, suggesting that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we confirmed the presence of a class of cis QTLs that specifically affect protein abundance with little or no effect on mRNA levels; most of these QTLs have little effect on ribosome occupancy, and hence may arise from differences in post-translational regulation. We measured level of translation transcriptome-wide in lymphoblastoid cell lines derived from 72 HapMap Yoruba individuals using ribosome profiling assay, for which we have transcript level, protein level (62 out of 72) and genotype information collected.
2014-12-19 | E-GEOD-61742 | biostudies-arrayexpress
Project description:Although the evidence for a genetic predisposition to human essential hypertension is compelling, the genetic control of blood pressure (BP) is poorly understood. The Dahl salt-sensitive (S) rat is a model for studying the genetic component of BP. Using this model we previously reported the identification of 16 different genomic regions that contain one or more BP quantitative trait loci (QTLs). The proximal region of rat chromosome 1 contains multiple BP QTLs. Of these, we have localized the BP QTL1b region to a 13.5cM (20Mb) region. Interestingly, five additional independent studies in rats and four independent studies in humans have reported genetic linkage for BP control by regions homologous to QTL1b. To view the overall renal transcriptional topography of the positional candidate genes for this QTL, we sought a comparative gene expression profiling between a congenic strain containing QTL1b and control S rats by employing: (1) a saturated QTL1b interval specific oligonucleotide array, and (2) a whole genome cDNA microarray representing 20,465 unique genes that are positioned outside the QTL. Results indicated that 19 out of the 231 positional candidate genes for this QTL are differentially expressed between the two strains tested. Surprisingly, over 1,500 genes outside of QTL1b were differentially expressed between the two rat strains. Integrating the results from the two approaches revealed at least one complex network of transcriptional control initiated by the positional candidate Nr2f2. This network appears to account for the majority of gene expression differences occurring outside of the QTL interval. Further substitution mapping is currently underway to test the validity of each of these differentially expressed positional candidate genes. These results demonstrate the importance of using a saturated oligonucleotide array for identifying and prioritizing differentially expressed positional candidate genes of a BP QTL. Keywords: : rat, hypertension, genetics, polygenic trait, microarray, gene expression
2004-07-31 | GSE1622 | GEO