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Whole genome sequencing of 39 captive born chimpanzees

ABSTRACT: Inter-individual variation in gene regulation has been shown to be heritable and it is quite often associated with differences in disease susceptibility between individuals. While many human studies focused on mapping associations between genetic and gene regulatory variation, much less attention has been paid to the evolutionary processes that shape the observed differences in gene regulation between individuals in humans or any other primate. To begin addressing this gap, we performed a comparative expression quantitative trait loci (eQTL) mapping study in humans and chimpanzees, using gene expression data from primary heart samples. While expression variability in both species is strongly determined by non-genetic sources, such as cell type heterogeneity, we found evidence that he degree of inter-individual variation in gene regulation is generally conserved in humans and chimpanzees. In particular, we found a significant overlap of genes associated with eQTLs in the two species. We conclude that humans and chimpanzees share sources common determinants of gene expression variability, including genetically regulated constraints from stabilizing and diversifying selection pressures. Associated with SRA project accession PRJNA635393 and GEO accession GSE151397.

INSTRUMENT(S): Illumina NovaSeq 6000

ORGANISM(S): Pan Troglodytes

SUBMITTER: University of Chicago

PROVIDER: PRJEB39475 | EVA | 2020-07-21

REPOSITORIES: EVA

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Project description:BACKGROUND: The transcript levels of many genes exhibit significant variation in tissue samples from inbred laboratory mice. A microarray experiment was designed to separate transcript abundance variation across samples from adipose, heart, kidney, and liver tissues of C57BL/6J mice into within-mouse and between-mouse components. Within-mouse variance captures variation due to heterogeneity of gene expression within tissues, RNA-extraction, and array processing. Between-mouse variance reflects differences in transcript levels between these genetically identical mice. Many biological sources can contribute to heterogeneous transcript levels within a tissue sample including inherent stochasticity of biochemical processes such as intrinsic and extrinsic noise within cells and differences in cell-type composition which can result from heterogeneity of stem and progenitor cell populations. Differences in global signaling patterns between individuals and micro-environmental influences such as interactions with pathogens and cage mates can also contribute to variation, but are likely to contribute more to the between-mouse variance component. RESULTS: The nature and extent of transcript abundance variation differs across tissues. Adipose has the largest total variance and the largest within-mouse variance. Liver has the smallest total variance, but it has the most between-mouse variation. Genes with high variability can be classified into groups with correlated patterns of expression that are enriched for specific biological functions. Variation between mice is associated with circadian rhythm, growth hormone signaling, immune response, androgen regulation, lipid metabolism, and the extracellular matrix. Genes showing correlated patterns of within mouse variation were also associated with biological functions, spatial connectivity of stochastic variation and heterogeneity of cell types within tissues. CONCLUSIONS: Genetically identical mice are individuals and they can experience different outcomes for medically important traits. This is reflected in the stochastic variation in gene expression observed between genetically identical mice. Much of the stochasticity has organismal, tissue, or spatial connectivity. Prior knowledge of the genes and functional classes of genes that are likely to vary in the absence of experimental perturbations, whether these are genetic or environmental, can inform experimental design decisions and the interpretation of gene expression data. Variation in gene expression in genetically identical mice sheds light on the impact of stochastic and micro-environmental factors and their phenotypic consequences.

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Whole genome sequencing of 39 captive born chimpanzees

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