bioRxivEvolutionary Biology
Association mapping reveals the role of mutation-selection balance in the maintenance of genomic variation for gene expression.
Emily B. Josephs, Young Wha Lee, John R. Stinchcombe, Stephen I. Wright
Abstract
The evolutionary forces that maintain genetic variation for quantitative traits within populations remain poorly understood. One hypothesis suggests that variation is maintained by a balance between new mutations and their removal by selection and drift. Theory predicts that this mutation-selection balance will result in an excess of low-frequency variants and a negative correlation between minor allele frequency and selection coefficients. Here, we test these predictions using the genetic loci associated with total expression variation (eQTLs) and allele-specific expression variation (aseQTLs) mapped within a single population of the plant Capsella grandiflora. In addition to finding eQTLs and aseQTLs for a large fraction of genes, we show that alleles at these loci are rarer than expected and exhibit a negative correlation between phenotypic effect size and frequency. Overall, our results show that the distribution of frequencies and effect sizes of the loci responsible for local expression variation within a single, outcrossing population are consistent with mutation-selection balance.\n\nSignificanceBiologists have long sought to explain why we see genetic variation for traits in populations despite the expectation that selection will remove most variation. We address this question by using gene expression as a model trait and identifying the genetic loci that affect gene expression in a single, large population of the plant Capsella grandiflora. Alleles at loci that affect expression were rarer than expected by chance and there was a negative correlation between phenotypic effect size and frequency of these alleles. These observations are consistent with mutation-selection balance, the hypothesis that variation is maintained by a balance between new mutations and their removal by selection and drift.
- organism: plant (other)
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: eQTL / molecular QTL mapping
- research focus: gene regulatory network inference
- approach: statistical model
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