Intra- and inter-individual genetic differences in gene expression (BXD Brain)
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE8355 | GEO | 2009/05/19
SECONDARY ACCESSION(S): PRJNA101371
REPOSITORIES: GEO
Similar Datasets
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 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:Genetic variation is known to influence the amount of mRNA produced by a gene, but the effects in different tissues is unclear. We studied gene expression levels in whole brain, kidney or liver, comparing 8 week old, male C57BL/6J to DBA/2J mice. Genes differentially expressed due to genetic background in one tissue were not differentially expressed in other tissues, suggesting that genetic variation of gene expression is tissue specific in inbred mice. Data used in a comparison to the BXD panel of mice in GSE8355, GSE8356, GSE6621 and to SJL/J in GSE8358.
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Project description:Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosomal footprinting to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes, more than half as many as showed genetic differences in mRNA levels. Similarly, allele specific measurements in the diploid hybrid between the two strains found roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, strong effects on translation were rare, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. Across all expressed genes, there was a tendency for translation to more often reinforce than buffer mRNA differences, resulting in footprint differences with greater magnitudes than the mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains. Overall, genetic variation clearly influences translation, but primarily does so by subtly modulating differences in mRNA levels. Translation does not appear to create strong discrepancies between genetic influences on mRNA and protein levels.
2014-03-31 | GSE55400 | 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
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Project description:Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosomal footprinting to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes, more than half as many as showed genetic differences in mRNA levels. Similarly, allele specific measurements in the diploid hybrid between the two strains found roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, strong effects on translation were rare, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. Across all expressed genes, there was a tendency for translation to more often reinforce than buffer mRNA differences, resulting in footprint differences with greater magnitudes than the mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains. Overall, genetic variation clearly influences translation, but primarily does so by subtly modulating differences in mRNA levels. Translation does not appear to create strong discrepancies between genetic influences on mRNA and protein levels. Ribsosomal footprinting and RNASeq in the two yeast strains BY and RM as well as their diploid hybrid. We generated one library each for the BY and RM parents, and two libraries (biological replicates) for the hybrid data.
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