SNP discovery and genotyping using Genotyping-by-Sequencing in Pekin ducks

Zhu, Feng; Cui, Qian-Qian; Hou, Zhuocheng

doi:10.1038/srep36223

Cited by 25 publications

(28 citation statements)

References 20 publications

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“…Our results emphasize that detecting selective sweeps does not require phased haplotype data, as distortions in the frequency spectrum of MLGs capture the reduction in diversity under a sweep similarly well to phased haplotypes. Accordingly, the advent of rapid and cost-effective genotyping-bysequencing technologies (Elshire et al 2011) across diverse taxa including bovine, marine-dwelling, and avian populations means that the adaptive histories of myriad organisms may now be inferred from genome-wide data (Daetwyler et al 2014;Drury et al 2016;Zhu et al 2016). Furthermore, we have shown that the inferences emerging from MLGbased scans align with those of phased haplotype-based scans, with empirical analyses of human populations yielding concordant top outlying candidates for selection, both documented and novel.…”

Section: Discussionmentioning

confidence: 63%

Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity

2018

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Positive natural selection can lead to a decrease in genomic diversity at the selected site and at linked sites, producing a characteristic signature of elevated expected haplotype homozygosity. These selective sweeps can be hard or soft. In the case of a hard selective sweep, a single adaptive haplotype rises to high population frequency, whereas multiple adaptive haplotypes sweep through the population simultaneously in a soft sweep, producing distinct patterns of genetic variation in the vicinity of the selected site. Measures of expected haplotype homozygosity have previously been used to detect sweeps in multiple study systems. However, these methods are formulated for phased haplotype data, typically unavailable for nonmodel organisms, and some may have reduced power to detect soft sweeps due to their increased genetic diversity relative to hard sweeps. To address these limitations, we applied the H12 and H2/H1 statistics proposed in 2015 by Garud et al., which have power to detect both hard and soft sweeps, to unphased multilocus genotypes, denoting them as G12 and G2/G1. G12 (and the more direct expected homozygosity analog to H12, denoted G123) has comparable power to H12 for detecting both hard and soft sweeps. G2/G1 can be used to classify hard and soft sweeps analogously to H2/H1, conditional on a genomic region having high G12 or G123 values. The reason for this power is that, under random mating, the most frequent haplotypes will yield the most frequent multilocus genotypes. Simulations based on parameters compatible with our recent understanding of human demographic history suggest that expected homozygosity methods are best suited for detecting recent sweeps, and increase in power under recent population expansions. Finally, we find candidates for selective sweeps within the 1000 Genomes CEU, YRI, GIH, and CHB populations, which corroborate and complement existing studies.

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Section: Discussionmentioning

confidence: 63%

Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity

2018

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“…Our results emphasize that detecting selective sweeps does not require phased haplotype data, as distortions in the frequency spectrum of MLGs capture the reduction in diversity under a sweep similarly well to phased haplotypes. Accordingly, the advent of rapid and cost-effective genotyping-by-sequencing technologies [Elshire et al, 2011] across diverse taxa including bovine, marine-dwelling, and avian populations means that the adaptive histories of myriad organisms may now be inferred from genome-wide data [Daetwyler et al, 2014, Drury et al, 2011, Zhu et al, 2016]. Furthermore, we have shown that the inferences emerging from MLG-based scans align with those of phased haplotype-based scans, with empirical analyses of human populations yielding concordant top outlying candidates for selection, both documented and novel.…”

Section: Discussionmentioning

confidence: 99%

Detection and classification of hard and soft sweeps from unphased genotypes by multilocus genotype identity

Harris

Garud

DeGiorgio

2018

Preprint

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Positive natural selection can lead to a decrease in genomic diversity at the selected site and at linked sites, producing a characteristic signature of elevated expected haplotype homozygosity. These selective sweeps can be hard or soft. In the case of a hard selective sweep, a single adaptive haplotype rises to high population frequency, whereas multiple adaptive haplotypes sweep through the population simultaneously in a soft sweep, producing distinct patterns of genetic variation in the vicinity of the selected site. Measures of expected haplotype homozygosity have previously been used to detect sweeps in multiple study systems. However, these methods are formulated for phased haplotype data, typically unavailable for nonmodel organisms, and may have reduced power to detect soft sweeps due to their increased genetic diversity relative to hard sweeps. To address these limitations, we applied the H12 and H2/H1 statistics of Garud et al. [2015] to unphased multilocus genotypes, denoting them as G12 and G2/G1. G12 (and the more direct expected homozygosity analogue to H12, denoted G123) has comparable power to H12 for detecting both hard and soft sweeps. G2/G1 can be used to classify hard and soft sweeps analogously to H2/H1, conditional on a genomic region having high G12 or G123 values. The reason for this power is that under random mating, the most frequent haplotypes will yield the most frequent multilocus genotypes. Simulations based on parameters compatible with our recent understanding of human demographic history suggest that expected homozygosity methods are best suited for detecting recent sweeps, and increase in power under recent population expansions. Finally, we find candidates for selective sweeps within the 1000 Genomes CEU, YRI, GIH, and CHB populations, which corroborate and complement existing studies.

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“…Fresh blood was collected from the ducks before slaughtering and genomic DNA was extracted from the blood using a phenol–chloroform-based method. Genotyping was performed using GBS, as described previously [15]. A total of 544 million clean reads (63.25 GB) were generated, of which 96.12% (523 million reads) were mapped to the duck genome, with an average mapping rate of 96.25%.…”

Section: Methodsmentioning

confidence: 99%

“…The data were deposited in the NCBI sequence read archive (SRP068685). GBS procedures are available on Zhu Feng’s article [15]. Restriction enzyme ( MSe1 ) for the PCR-RFLP assay was selected using information from REBASE [33].…”

Section: Methodsmentioning

confidence: 99%

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Genome-wide association study reveals novel loci associated with body size and carcass yields in Pekin ducks

et al. 2019

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BackgroundPekin duck products have become popular in Asia over recent decades and account for an increasing market share. However, the genetic mechanisms affecting carcass growth in Pekin ducks remain unknown. This study aimed to identify quantitative trait loci affecting body size and carcass yields in Pekin ducks.ResultsWe measured 18 carcass traits in 639 Pekin ducks and performed genotyping using genotyping-by-sequencing (GBS). Loci-based association analysis detected 37 significant loci for the 17 traits. Thirty-seven identified candidate genes were involved in many biological processes. One single nucleotide polymorphism (SNP) (Chr1_140105435 A > T) located in the intron of the ATPase phospholipid transporting 11A gene (ATP11A) attained genome-wide significance associated with five weight traits. Eight SNPs were significantly associated with three body size traits, including the candidate gene plexin domain containing 2 (PLXDC2) associated with breast width and tensin 3 (TNS3) associated with fossil bone length. Only two SNPs were significantly associated with foot weight and four SNPs were significantly associated with heart weight. In the gene-based analysis, three genes (LOC101791418, TUBGCP3 (encoding tubulin gamma complex-associated protein 3), and ATP11A) were associated with four traits (42-day body weight, eviscerated weight, half-eviscerated weight, and leg muscle weight percentage). However, no loci were significantly associated with leg muscle weight in this study.ConclusionsThe novel results of this study improve our understanding of the genetic mechanisms regulating body growth in ducks and thus provide a genetic basis for breeding programs aimed at maximizing the economic potential of Pekin ducks.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-5379-1) contains supplementary material, which is available to authorized users.

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SNP discovery and genotyping using Genotyping-by-Sequencing in Pekin ducks

Cited by 25 publications

References 20 publications

Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity

Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity

Detection and classification of hard and soft sweeps from unphased genotypes by multilocus genotype identity

Genome-wide association study reveals novel loci associated with body size and carcass yields in Pekin ducks

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