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The genetic architecture of gene expression levels in wild baboons.

Tung J, Zhou X, Alberts SC, Stephens M, Gilad Y - Elife (2015)

Bottom Line: Primate evolution has been argued to result, in part, from changes in how genes are regulated.We performed complementary expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses, discovering substantial evidence for, and surprising power to detect, genetic effects on gene expression levels in the baboons. eQTL were most likely to be identified for lineage-specific, rapidly evolving genes; interestingly, genes with eQTL significantly overlapped between baboons and a comparable human eQTL data set.Our results suggest that genes vary in their tolerance of genetic perturbation, and that this property may be conserved across species.

View Article: PubMed Central - PubMed

Affiliation: Department of Human Genetics, University of Chicago, Chicago, United States.

ABSTRACT
Primate evolution has been argued to result, in part, from changes in how genes are regulated. However, we still know little about gene regulation in natural primate populations. We conducted an RNA sequencing (RNA-seq)-based study of baboons from an intensively studied wild population. We performed complementary expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses, discovering substantial evidence for, and surprising power to detect, genetic effects on gene expression levels in the baboons. eQTL were most likely to be identified for lineage-specific, rapidly evolving genes; interestingly, genes with eQTL significantly overlapped between baboons and a comparable human eQTL data set. Our results suggest that genes vary in their tolerance of genetic perturbation, and that this property may be conserved across species. Further, they establish the feasibility of eQTL mapping using RNA-seq data alone, and represent an important step towards understanding the genetic architecture of gene expression in primates.

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Power to detect ASE vs eQTL.(A) Detection of ASE is favored for genes with higherexpression levels (p = 3.99 × 10−209),(B) whereas detection of eQTL is favored for genes withgreater cis-regulatory SNP density (p = 1.05× 10−73).DOI:http://dx.doi.org/10.7554/eLife.04729.011
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fig1s8: Power to detect ASE vs eQTL.(A) Detection of ASE is favored for genes with higherexpression levels (p = 3.99 × 10−209),(B) whereas detection of eQTL is favored for genes withgreater cis-regulatory SNP density (p = 1.05× 10−73).DOI:http://dx.doi.org/10.7554/eLife.04729.011

Mentions: Both analyses converged to reveal extensive segregating genetic variation affectinggene expression levels in the Amboseli population. At a 10% false discovery rate, weidentified eQTL for 1787 (17.2%) of the genes we analyzed, and evidence for ASE for510 (23.4%) of tested genes. Consistent with reports in humans (e.g., Veyrieras et al., 2008; Pickrell et al., 2010a), eQTL were strongly enriched near genetranscription start sites and in gene bodies (Figure1; controlling for the background distribution of sites tested, which werealso enriched in and around genes). Within gene bodies, eQTL were particularly likelyto be detected near transcription end sites; this potentially reflects enrichment in3′ untranslated regions, which are poorly annotated in baboon. Also asexpected, genes with eQTL were more likely to exhibit significant ASE and vice-versa(hypergeometric test: p < 10−25; Figure 1—figure supplement 7). The magnitude anddirection of ASE and eQTL were significantly correlated when an eQTL SNP could alsobe assessed for ASE (n = 123 genes; r = 0.719, p< 10−20, Figure1—figure supplement 7), and when ASE SNPs were assessed as eQTL (n= 510 genes; r = 0.575, p <10−45, Figure 1—figuresupplement 7). Detection of ASE was most strongly favored for highlyexpressed genes (i.e., higher RPKM: Wilcoxon test: p <10−208; Figure 1—figuresupplement 8), whereas detection of eQTL was most strongly favored forgenes with high local SNP density (p < 10−72; Figure 1—figure supplement 8).


The genetic architecture of gene expression levels in wild baboons.

Tung J, Zhou X, Alberts SC, Stephens M, Gilad Y - Elife (2015)

Power to detect ASE vs eQTL.(A) Detection of ASE is favored for genes with higherexpression levels (p = 3.99 × 10−209),(B) whereas detection of eQTL is favored for genes withgreater cis-regulatory SNP density (p = 1.05× 10−73).DOI:http://dx.doi.org/10.7554/eLife.04729.011
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4383332&req=5

fig1s8: Power to detect ASE vs eQTL.(A) Detection of ASE is favored for genes with higherexpression levels (p = 3.99 × 10−209),(B) whereas detection of eQTL is favored for genes withgreater cis-regulatory SNP density (p = 1.05× 10−73).DOI:http://dx.doi.org/10.7554/eLife.04729.011
Mentions: Both analyses converged to reveal extensive segregating genetic variation affectinggene expression levels in the Amboseli population. At a 10% false discovery rate, weidentified eQTL for 1787 (17.2%) of the genes we analyzed, and evidence for ASE for510 (23.4%) of tested genes. Consistent with reports in humans (e.g., Veyrieras et al., 2008; Pickrell et al., 2010a), eQTL were strongly enriched near genetranscription start sites and in gene bodies (Figure1; controlling for the background distribution of sites tested, which werealso enriched in and around genes). Within gene bodies, eQTL were particularly likelyto be detected near transcription end sites; this potentially reflects enrichment in3′ untranslated regions, which are poorly annotated in baboon. Also asexpected, genes with eQTL were more likely to exhibit significant ASE and vice-versa(hypergeometric test: p < 10−25; Figure 1—figure supplement 7). The magnitude anddirection of ASE and eQTL were significantly correlated when an eQTL SNP could alsobe assessed for ASE (n = 123 genes; r = 0.719, p< 10−20, Figure1—figure supplement 7), and when ASE SNPs were assessed as eQTL (n= 510 genes; r = 0.575, p <10−45, Figure 1—figuresupplement 7). Detection of ASE was most strongly favored for highlyexpressed genes (i.e., higher RPKM: Wilcoxon test: p <10−208; Figure 1—figuresupplement 8), whereas detection of eQTL was most strongly favored forgenes with high local SNP density (p < 10−72; Figure 1—figure supplement 8).

Bottom Line: Primate evolution has been argued to result, in part, from changes in how genes are regulated.We performed complementary expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses, discovering substantial evidence for, and surprising power to detect, genetic effects on gene expression levels in the baboons. eQTL were most likely to be identified for lineage-specific, rapidly evolving genes; interestingly, genes with eQTL significantly overlapped between baboons and a comparable human eQTL data set.Our results suggest that genes vary in their tolerance of genetic perturbation, and that this property may be conserved across species.

View Article: PubMed Central - PubMed

Affiliation: Department of Human Genetics, University of Chicago, Chicago, United States.

ABSTRACT
Primate evolution has been argued to result, in part, from changes in how genes are regulated. However, we still know little about gene regulation in natural primate populations. We conducted an RNA sequencing (RNA-seq)-based study of baboons from an intensively studied wild population. We performed complementary expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses, discovering substantial evidence for, and surprising power to detect, genetic effects on gene expression levels in the baboons. eQTL were most likely to be identified for lineage-specific, rapidly evolving genes; interestingly, genes with eQTL significantly overlapped between baboons and a comparable human eQTL data set. Our results suggest that genes vary in their tolerance of genetic perturbation, and that this property may be conserved across species. Further, they establish the feasibility of eQTL mapping using RNA-seq data alone, and represent an important step towards understanding the genetic architecture of gene expression in primates.

Show MeSH