Limits...
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.

Show MeSH
Relationship between power to detect eQTL and simulated effectsize, when the true eQTL is masked.Purple line shows the baboon data; pink line shows the baboon datawith SNP density subsampled to match the YRI; orange line shows theYRI data. Masking the simulated eQTL SNP demonstrates that the baboondata set has greater power to detect eQTL due to both increasedcis-regulatory SNP density and more extended LD.Subsampling the SNP density in baboon to the level of the YRI data setreduces the difference in power but does not remove it completely.DOI:http://dx.doi.org/10.7554/eLife.04729.019
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4383332&req=5

fig2s1: Relationship between power to detect eQTL and simulated effectsize, when the true eQTL is masked.Purple line shows the baboon data; pink line shows the baboon datawith SNP density subsampled to match the YRI; orange line shows theYRI data. Masking the simulated eQTL SNP demonstrates that the baboondata set has greater power to detect eQTL due to both increasedcis-regulatory SNP density and more extended LD.Subsampling the SNP density in baboon to the level of the YRI data setreduces the difference in power but does not remove it completely.DOI:http://dx.doi.org/10.7554/eLife.04729.019

Mentions: Because our RNA-seq-based approach does not identify variants outside oftranscribed regions, causal SNPs were probably often not typed. To quantify thepower to detect eQTL under this scenario, we again simulated eQTL among genes inthe baboon and YRI data sets, but masked the causal sites. Doing so revealed muchgreater power to identify eQTL in baboons than in humans, across all values ofsimulated PVE or effect size (Figure 2B;Figure 2—figure supplement 1).One possible explanation for this observation stems from increased geneticdiversity in the baboons compared to the YRI. Indeed, in baboons we tested anaverage of 45.4 (±57.0 s.d.) genetic variants for each gene, whereasapplying the same pipeline in YRI yielded an average of 20.3 (±21.4 s.d.)testable variants per gene. An alternative explanation relates to patterns of LD,which we estimate to decay somewhat more slowly in the baboons (Figure 2B, inset). Higher SNP density inbaboons increases the likelihood that, when a causal SNP is not typed, a nearbySNP will be available that tags it. Longer range LD suggests that a given SNPcould also tag distant causal variants more effectively.


The genetic architecture of gene expression levels in wild baboons.

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

Relationship between power to detect eQTL and simulated effectsize, when the true eQTL is masked.Purple line shows the baboon data; pink line shows the baboon datawith SNP density subsampled to match the YRI; orange line shows theYRI data. Masking the simulated eQTL SNP demonstrates that the baboondata set has greater power to detect eQTL due to both increasedcis-regulatory SNP density and more extended LD.Subsampling the SNP density in baboon to the level of the YRI data setreduces the difference in power but does not remove it completely.DOI:http://dx.doi.org/10.7554/eLife.04729.019
© Copyright Policy
Related In: Results  -  Collection

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

fig2s1: Relationship between power to detect eQTL and simulated effectsize, when the true eQTL is masked.Purple line shows the baboon data; pink line shows the baboon datawith SNP density subsampled to match the YRI; orange line shows theYRI data. Masking the simulated eQTL SNP demonstrates that the baboondata set has greater power to detect eQTL due to both increasedcis-regulatory SNP density and more extended LD.Subsampling the SNP density in baboon to the level of the YRI data setreduces the difference in power but does not remove it completely.DOI:http://dx.doi.org/10.7554/eLife.04729.019
Mentions: Because our RNA-seq-based approach does not identify variants outside oftranscribed regions, causal SNPs were probably often not typed. To quantify thepower to detect eQTL under this scenario, we again simulated eQTL among genes inthe baboon and YRI data sets, but masked the causal sites. Doing so revealed muchgreater power to identify eQTL in baboons than in humans, across all values ofsimulated PVE or effect size (Figure 2B;Figure 2—figure supplement 1).One possible explanation for this observation stems from increased geneticdiversity in the baboons compared to the YRI. Indeed, in baboons we tested anaverage of 45.4 (±57.0 s.d.) genetic variants for each gene, whereasapplying the same pipeline in YRI yielded an average of 20.3 (±21.4 s.d.)testable variants per gene. An alternative explanation relates to patterns of LD,which we estimate to decay somewhat more slowly in the baboons (Figure 2B, inset). Higher SNP density inbaboons increases the likelihood that, when a causal SNP is not typed, a nearbySNP will be available that tags it. Longer range LD suggests that a given SNPcould also tag distant causal variants more effectively.

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