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Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits.

ABSTRACT: Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTL under selection affects the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50-100%) can be explained by detected QTL in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates.

SUBMITTER: Kessner D

PROVIDER: S-EPMC4391575 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits.

Kessner Darren D Novembre John J

Genetics 20150210 4

Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis use ...[more]

PMID: 25672748

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Project description:Xiang pig (XP) is one of the best-known indigenous pig breeds in China, which is characterized by its small body size, strong disease resistance, high adaptability, favorite meat quality, small litter sizes, and early sexual maturity. However, the genomic evidence that links these unique traits of XP is still poorly understood. To identify the genomic signatures of selection in XP, we performed whole-genome resequencing on 25 unrelated individual XPs. We obtained 876.70 Gb of raw data from the genomic libraries. The LD analysis showed that the lowest level of linkage disequilibrium was observed in Xiang pig. Comparative genomic analysis between XPs and other breeds including Tibetan, Meishan, Duroc and Landrace revealed 3062, 1228, 907 and 1519 selected regions, respectively. The genes identified in selected regions of XPs were associated with growth and development processes (IGF1R, PROP1, TBX19, STAC3, RLF, SELENOM, MSTN), immunity and disease resistance (ZCCHC2, SERPINB2, ADGRE5, CYP7B1, STAT6, IL2, CD80, RHBDD3, PIK3IP1), environmental adaptation (NR2E1, SERPINB8, SERPINB10, SLC26A7, MYO1A, SDR9C7, UVSSA, EXPH5, VEGFC, PDE1A), reproduction (CCNB2, TRPM6, EYA3, CYP7B1, LIMK2, RSPO1, ADAM32, SPAG16), meat quality traits (DECR1, EWSR1), and early sexual maturity (TAC3). Through the absolute allele frequency difference (ΔAF) analysis, we explored two population-specific missense mutations occurred in NR6A1 and LTBP2 genes, which well explained that the vertebrae numbers of Xiang pigs were less than that of the European pig breeds. Our results indicated that Xiang pigs were less affected by artificial selection than the European and Meishan pig breeds. The selected candidate genes were mainly involved in growth and development, disease resistance, reproduction, meat quality, and early sexual maturity. This study provided a list of functional candidate genes, as well as a number of genetic variants, which would provide insight into the molecular basis for the unique traits of Xiang pig.

Dataset Information

Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits.

Publications

Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits.

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