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Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality.

ABSTRACT: To gain a detailed understanding of how plant microbes evolve and adapt to hosts, pesticides, and other factors, knowledge of the population dynamics and evolutionary history of populations is crucial. Plant pathogen populations are often clonal or partially clonal which requires different analytical tools. With the advent of high throughput sequencing technologies, obtaining genome-wide population genetic data has become easier than ever before. We previously contributed the R package poppr specifically addressing issues with analysis of clonal populations. In this paper we provide several significant extensions to poppr with a focus on large, genome-wide SNP data. Specifically, we provide several new functionalities including the new function mlg.filter to define clone boundaries allowing for inspection and definition of what is a clonal lineage, minimum spanning networks with reticulation, a sliding-window analysis of the index of association, modular bootstrapping of any genetic distance, and analyses across any level of hierarchies.

SUBMITTER: Kamvar ZN

PROVIDER: S-EPMC4462096 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality.

Kamvar Zhian N ZN Brooks Jonah C JC Grünwald Niklaus J NJ

Frontiers in genetics 20150610

To gain a detailed understanding of how plant microbes evolve and adapt to hosts, pesticides, and other factors, knowledge of the population dynamics and evolutionary history of populations is crucial. Plant pathogen populations are often clonal or partially clonal which requires different analytical tools. With the advent of high throughput sequencing technologies, obtaining genome-wide population genetic data has become easier than ever before. We previously contributed the R package poppr spe ...[more]

PMID: 26113860

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Project description:Following chicken domestication, diversified chicken breeds were developed by both natural and artificial selection, which led to the accumulation of abundant genetic and phenotypic variations, making chickens an ideal genetic research model. To better understand the genetic structure of chicken breeds under different selection pressures, we genotyped various chicken populations with specific selection targets, including indigenous, commercial, gamecock, and wild ancestral chickens, using the 600K SNP array. We analyzed the population structure, genetic relationships, run of homozygosity (ROH), effective population number (Ne), and other genetic parameters. The wild ancestral population, red junglefowl (RJF), possessed the highest diversity, in comparison with all other domesticated populations, which was supported by linkage disequilibrium decay (LD), effective population number, and ROH analyses. The gamecock breeds, which were subjected to stronger male-biased selection for fighting-related traits, also presented higher variation than the commercial and indigenous breeds. Admixture analysis also indicated that game breed is a relatively independent branch of Chinese local breeds. Following intense selection for reproductive and productive traits, the commercial lines showed the least diversity. We also observed that the European local chickens had lower genetic variation than the Chinese local breeds, which could be attributed to the shorter history of the European breed. ROH were present in a breed specific manner and 191 ROH island were detected on four groups (commercial, local, game and wild chickens). These ROH islands were involved in egg production, growth and silky feathers and other traits. Moreover, we estimated the effective sex ratio of these breeds to demonstrate the change in the ratio of the two sexes. We found that commercial chickens had a greater sex imbalance between females and males. The commercial lines showed the highest female-to-male ratios. Interestingly, RJF comprised a greater proportion of males than females. Our results show the population genetics of chickens under selection pressures, and can aid in the development of better conservation strategies for different chicken breeds.

Dataset Information

Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality.

Publications

Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality.

Similar Datasets

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