Inter-individual variation among worms in a shared environment
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ABSTRACT:
ORGANISM(S): Caenorhabditis elegans
PROVIDER: GSE98747 | GEO | 2017/12/05
SECONDARY ACCESSION(S): PRJNA386108
REPOSITORIES: GEO
Similar Datasets
Project description:Background: Gene expression variation is a phenotypic trait of particular interest as it represents the initial link between genotype and other phenotypes. Analyzing how such variation apportions among and within groups allows for the evaluation of how genetic and environmental factors influence such traits. It also provides opportunities to identify genes and pathways that may have been influenced by non-neutral processes. Here we use a population genetics framework and next generation sequencing to evaluate how gene expression variation is apportioned among four human groups in a natural biological tissue, the placenta. Results: We estimate that on average, 33.2%, 58.9% and 7.8% of the placental transcriptome is explained by variation within individuals, among individuals and among human groups, respectively. Additionally, when technical and biological traits are included in models of gene expression they account for roughly 2% of total gene expression variation. Notably, the variation that is significantly different among groups is enriched in biological pathways associated with immune response, cell signaling and metabolism. Many biological traits demonstrated correlated changes in expression in numerous pathways of potential interest to clinicians and evolutionary biologists. Finally, we estimate that the majority of the human placental transcriptome (65% of expressed genes) exhibits expression profiles consistent with neutrality; the remainder are consistent with stabilizing selection (26%), directional selection (4.9%), or diversifying selection (4.8%). Conclusion: We apportion placental gene expression variation into individual, population and biological trait factors and identify how each influence the transcriptome. Additionally, we advance methods to associate expression profiles with different forms of selection. Placental mRNA was sequenced on an Illumina GAIIx. Samples were derived from 4 human groups, 10 individuals per group, 2 samples per individual
2015-03-07 | E-GEOD-66622 | biostudies-arrayexpress
Project description:Background: Gene expression variation is a phenotypic trait of particular interest as it represents the initial link between genotype and other phenotypes. Analyzing how such variation apportions among and within groups allows for the evaluation of how genetic and environmental factors influence such traits. It also provides opportunities to identify genes and pathways that may have been influenced by non-neutral processes. Here we use a population genetics framework and next generation sequencing to evaluate how gene expression variation is apportioned among four human groups in a natural biological tissue, the placenta. Results: We estimate that on average, 33.2%, 58.9% and 7.8% of the placental transcriptome is explained by variation within individuals, among individuals and among human groups, respectively. Additionally, when technical and biological traits are included in models of gene expression they account for roughly 2% of total gene expression variation. Notably, the variation that is significantly different among groups is enriched in biological pathways associated with immune response, cell signaling and metabolism. Many biological traits demonstrated correlated changes in expression in numerous pathways of potential interest to clinicians and evolutionary biologists. Finally, we estimate that the majority of the human placental transcriptome (65% of expressed genes) exhibits expression profiles consistent with neutrality; the remainder are consistent with stabilizing selection (26%), directional selection (4.9%), or diversifying selection (4.8%). Conclusion: We apportion placental gene expression variation into individual, population and biological trait factors and identify how each influence the transcriptome. Additionally, we advance methods to associate expression profiles with different forms of selection.
2015-03-07 | GSE66622 | GEO
Project description:Analysis of the extent to which inter-individual variation in mRNA decay contributes to inter-individual variation in gene expression levels in humans. The study examines properties of genome-wide decay rates and the relationship between mRNA decay and gene expression across genes, across individuals, and finally across genotype classes.
2012-10-01 | GSE37451 | GEO
Project description:Genetic variation is known to influence the amount of mRNA produced by a gene. Because molecular machines control mRNA levels of multiple genes, we expect genetic variation in components of these machines would influence multiple genes in a similar fashion. We show that this assumption is correct by using correlation of mRNA levels measured from multiple tissues in mouse strain panels to detect shared genetic influences. These correlating groups of genes (CGGs) have collective properties that on average account for 52–79% of the variability of their constituent genes and can contain genes that encode functionally related proteins. We show that the genetic influences are essentially tissue-specific and, consequently, the same genetic variations in one animal may upregulate a CGG in one tissue but downregulate the CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. Thus, this class of genetic variation can result in complex inter- and intra-individual differences. This will create substantial challenges in humans, where multiple tissues are not readily available.
2009-05-19 | GSE8356 | GEO
Project description:Genetic variation is known to influence the amount of mRNA produced by a gene. Because molecular machines control mRNA levels of multiple genes, we expect genetic variation in components of these machines would influence multiple genes in a similar fashion. We show that this assumption is correct by using correlation of mRNA levels measured from multiple tissues in mouse strain panels to detect shared genetic influences. These correlating groups of genes (CGGs) have collective properties that on average account for 52–79% of the variability of their constituent genes and can contain genes that encode functionally related proteins. We show that the genetic influences are essentially tissue-specific and, consequently, the same genetic variations in one animal may upregulate a CGG in one tissue but downregulate the CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. Thus, this class of genetic variation can result in complex inter- and intra-individual differences. This will create substantial challenges in humans, where multiple tissues are not readily available.
2009-05-19 | GSE8355 | GEO
Project description:The aim of this study was to map inter-individual variation in the human milk peptidome and to investigate relationships between these data and possible explanations for observed variation.
2022-05-04 | PXD028294 | Pride
Project description:The aim of this study was to map inter-individual variation in the human milk proteome and to investigate relationships between these data and possible explanations for observed variation.
2022-05-04 | PXD028280 | Pride
Project description:Genetic variation is known to influence the amount of mRNA produced by a gene. Because molecular machines control mRNA levels of multiple genes, we expect genetic variation in components of these machines would influence multiple genes in a similar fashion. We show that this assumption is correct by using correlation of mRNA levels measured from multiple tissues in mouse strain panels to detect shared genetic influences. These correlating groups of genes (CGGs) have collective properties that on average account for 52â79% of the variability of their constituent genes and can contain genes that encode functionally related proteins. We show that the genetic influences are essentially tissue-specific and, consequently, the same genetic variations in one animal may upregulate a CGG in one tissue but downregulate the CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. Thus, this class of genetic variation can result in complex inter- and intra-individual differences. This will create substantial challenges in humans, where multiple tissues are not readily available. Each sample is a single hybridisation from a given BxD strain to a C57BL/6J reference sample. Two-colour glass arrays were used. No dye swaps were employed. Data from whole brain.
2010-06-25 | E-GEOD-8355 | biostudies-arrayexpress
Project description:Genetic variation is known to influence the amount of mRNA produced by a gene. Because molecular machines control mRNA levels of multiple genes, we expect genetic variation in components of these machines would influence multiple genes in a similar fashion. We show that this assumption is correct by using correlation of mRNA levels measured from multiple tissues in mouse strain panels to detect shared genetic influences. These correlating groups of genes (CGGs) have collective properties that on average account for 52â79% of the variability of their constituent genes and can contain genes that encode functionally related proteins. We show that the genetic influences are essentially tissue-specific and, consequently, the same genetic variations in one animal may upregulate a CGG in one tissue but downregulate the CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. Thus, this class of genetic variation can result in complex inter- and intra-individual differences. This will create substantial challenges in humans, where multiple tissues are not readily available. Common reference design where each hybridisation compares a single BxD strain to a common reference of C57BL/6J in the green channel. Two-colour, spotted glass arrays were used. No dye swaps were employed.
2010-06-25 | E-GEOD-8356 | biostudies-arrayexpress
Project description:Background: DNA methylation has long been known to play an essential role in the epigenetic regulation of gene expression and other cellular functions, and has been in some cases linked to genetic variation. While its presence near the transcription start site of a gene has been associated with reduced expression, the variation in methylation levels across individuals, its environmental or genetic causes, and its association with gene expression remain poorly understood. Results: We report the joint analysis of sequence variants, gene expression and DNA methylation in primary fibroblast samples derived from a set of 62 unrelated individuals. Approximately 2% of the most variable CpG sites are mappable in cis to sequence variation, usually within 5kb. Via eQTL analysis with microarray data combined with mapping of allelic expression regions, we obtained a set of 2770 regions mappable in cis to sequence variation. In 9.5% of these expressed regions, an associated SNP was also a methylation QTL. Methylation and gene expression are often correlated without direct discernible involvement of sequence variation, but not always in the expected direction (negative for promoter CpGs, positive for gene body CpGs). Population-level correlation between methylation and expression is strongest in a subset of developmentally significant genes, including all four HOX clusters. The presence and sign of this correlation are best predicted using specific histone marks or DNase I hypersensitivity rather than position of the CpG site with respect to the gene, showing that other epigenetic markers are necessary to interpret downstream effects of individual methylation variants. Conclusion: Our results indicate a wide variety of relationships between gene expression, DNA methylation and sequence variation in untransformed adult human fibroblasts, with considerable involvement of chromatin features. We note particularly high levels of variation and correlation in DNA methylation and gene expression at key developmental loci, with little discernible involvement of sequence variation.
2013-12-13 | GSE53243 | GEO