Human Variation Panel: Gene Expression and Genotype
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA129983 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:This SuperSeries is composed of the following subset Series: GSE23120: Basal gene expression data from Human Variation Panel GSE24245: Genome-wide SNP array data from Human Variation Panel by Illumina 510S GSE24260: Genome-wide SNP array data from Human Variation Panel by Illumina 550K GSE24274: Genome-wide SNP array data from Human Variation Panel by Illumina 650K Refer to individual Series
2010-09-24 | E-GEOD-24277 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2010-09-25 | GSE24277 | GEO
Project description:We used microarrays to identify the variation of basal gene expression level among 287 lymphoblastoid cell lines. Radiation therapy is used to treat half of all cancer patients. Response to radiation therapy varies widely among patients. Therefore, we performed a genome-wide association study (GWAS) to identify biomarkers to help predict radiation response using 277 ethnically defined human lymphoblastoid cell lines (LCLs). Basal gene expression levels and 1.3 million genome-wide SNP markers from both Affymetrix and Illumina platforms were assayed for all 277 human LCLs. MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) assays for radiation cytotoxicity were also performed to obtain area under the curve (AUC) as a radiation response phenotype for use in the association studies. Functional validation of candidate genes, selected from an integrated analysis that used SNP, expression and AUC data, was performed with multiple cancer cell lines using specific siRNA knockdown, followed by MTS and colony-forming assays. 27 loci, each containing at least 2 SNPs within 50kb with p-values <10-4, were associated with radiation AUC. 270 expression probe sets were associated with radiation AUC with p<10-3. The integrated analysis identified 50 SNPs in 14 of the 27 loci that were associated with both AUC and the expression of 39 genes that were also associated with radiation AUC (p<10-3). Functional validation using siRNA knockdown in multiple tumor cell lines showed that C13orf34, MAD2L1, PLK4, TPD52 and DEPDC1B each significantly altered radiation sensitivity in at least 2 cancer cell lines. Studies performed with LCLs can help to identify novel biomarkers that might contribute to variation in response to radiation therapy and enhance our understanding of mechanisms underlying that variation.
2010-07-24 | GSE23120 | GEO
Project description:Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups. Here we report the analysis and public release of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with geographic distance from Africa, as expected under a serial founder effect for an out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected—including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas—the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations. Keywords: High Density SNP array
2008-02-05 | GSE10331 | GEO
Project description:Coevolutionary change requires reciprocal selection between interacting species, i.e., that the partner genotypes that are favored in one species depend on the genetic composition of the interacting species. Coevolutionary genetic variation is manifested as genotype ´ genotype (G ´ G) interactions for fitness from interspecific interactions. Although quantitative genetic approaches have revealed abundant evidence for G ´ G interactions in symbioses, the molecular basis of this variation remains unclear. Here we study the molecular basis of G ´ G interactions in a model legume-rhizobium mutualism using gene expression microarrays. We find that, like quantitative traits such as fitness, variation in the symbiotic transcriptome may be partitioned into additive and interactive genetic components. Our results suggest that plant genetic variation is the largest influence on nodule gene expression, and that plant genotype and the plant genotype ´ rhizobium genotype interaction determine global shifts in rhizobium gene expression that in turn feedback to influence plant fitness benefits. Moreover, the transcriptomic variation we uncover implicates regulatory changes in both species as drivers of symbiotic gene expression variation. Our study is the first to partition genetic variation in a symbiotic transcriptome, and illuminates potential molecular routes of coevolutionary change. We assayed gene expression using three biological replicates for each plant genotype × rhizobium genotype combination (4 combinations) for a total of 12 chips.
2012-05-01 | GSE29027 | GEO
Project description:Expression profiling analyses for eight maize inbreds reveals extensive transcriptional variation. Many genes exhibit presence-absence variation among the inbred lines. Keywords: Genotype comparison series
2008-01-26 | GSE10237 | GEO
Project description:We study the effect of four QTN in RME1, IME1 & RSF1 that are causative for variation in sporulation efficiency. We investigate the relationship between genotype, gene expression and phenotype and whether the amount of gene expression variation explained by the sporulation QTN is predictive of the amount of phenotypic variation explained by them. RNA-Seq analysis of 4 replicates each of 16 allele replacement panel strains containing all combinations of the four sporulation QTN after 2 hours in sporulation medium.
2014-05-30 | E-GEOD-55409 | biostudies-arrayexpress
Project description:Human buffy coat gene expression, custom 250-plex Nanostring panel
| PRJNA512473 | ENA
Project description:It is well established that epigenetic features, such as histone modifications and DNA methylation, are associated with gene expression across cell types. However, it is not well known how variation in genotype affects epigenetic state, or to what extent such variation contributes to variation in gene expression across genetically distinct individuals. Here we investigated the relationship between heritable epigenetic variation and gene expression in hepatocytes across nine inbred mouse strains. Eight of the inbred strains were founders of the diversity outbred (DO) mice, and the ninth was DBA/2J, which, along with C57BL/6J, is one of the founders of the BxD recombinant inbred panel of mice. We surveyed four histone modifications, H3K4me1, H3K4me3, H3K27me3 and H3K27ac, as well as DNA methylation. We used ChromHMM to identify 14 chromatin states representing distinct combinations of the four measured histone modifications. We found that variation in chromatin state mirrored genetic variation across the inbred strains. Furthermore, epigenetic variation was correlated with gene expression across strains. The correspondence between epigenetic state and gene expression was replicated in an independent population of DO mice in which we imputed local epigenetic state. In contrast, we found that DNA methylation did not vary across inbred strains and was not correlated with variation in expression in DO mice. This work suggests that chromatin state is highly influenced by local genotype and may be a primary mode through which expression quantitative trait loci (eQTLs) are mediated. We further demonstrate that strain variation in chromatin state, paired with gene expression is useful for annotation of functional regions of the mouse genome. Finally, we provide a data resource that documents variation in chromatin state across genetically distinct individuals.
2022-09-25 | GSE213967 | GEO
Project description:It is well established that epigenetic features, such as histone modifications and DNA methylation, are associated with gene expression across cell types. However, it is not well known how variation in genotype affects epigenetic state, or to what extent such variation contributes to variation in gene expression across genetically distinct individuals. Here we investigated the relationship between heritable epigenetic variation and gene expression in hepatocytes across nine inbred mouse strains. Eight of the inbred strains were founders of the diversity outbred (DO) mice, and the ninth was DBA/2J, which, along with C57BL/6J, is one of the founders of the BxD recombinant inbred panel of mice. We surveyed four histone modifications, H3K4me1, H3K4me3, H3K27me3 and H3K27ac, as well as DNA methylation. We used ChromHMM to identify 14 chromatin states representing distinct combinations of the four measured histone modifications. We found that variation in chromatin state mirrored genetic variation across the inbred strains. Furthermore, epigenetic variation was correlated with gene expression across strains. The correspondence between epigenetic state and gene expression was replicated in an independent population of DO mice in which we imputed local epigenetic state. In contrast, we found that DNA methylation did not vary across inbred strains and was not correlated with variation in expression in DO mice. This work suggests that chromatin state is highly influenced by local genotype and may be a primary mode through which expression quantitative trait loci (eQTLs) are mediated. We further demonstrate that strain variation in chromatin state, paired with gene expression is useful for annotation of functional regions of the mouse genome. Finally, we provide a data resource that documents variation in chromatin state across genetically distinct individuals.
2022-09-25 | GSE213965 | GEO