The SYNBREED chicken diversity panel: a global resource to assess chicken diversity at high genomic resolution

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Abstract

Background

Since domestication, chickens did not only disperse into the different parts of the world but they have also undergone significant genomic changes in this process. Many breeds, strains or lines have been formed and those represent the diversity of the species. However, other than the natural evolutionary forces, management practices (including those that threaten the persistence of genetic diversity) following domestication have shaped the genetic make-up of and diversity between today’s chicken breeds. As part of the SYNBREED project, samples from a wide variety of chicken populations have been collected across the globe and were genotyped with a high density SNP array. The panel consists of the wild type, commercial layers and broilers, indigenous village/local type and fancy chicken breeds. The SYNBREED chicken diversity panel (SCDP) is made available to serve as a public basis to study the genetic structure of chicken diversity. In the current study we analyzed the genetic diversity between and within the populations in the SCDP, which is important for making informed decisions for effective management of farm animal genetic resources.

Results

Many of the fancy breeds cover a wide spectrum and clustered with other breeds of similar supposed origin as shown by the phylogenetic tree and principal component analysis. However, the fancy breeds as well as the highly selected commercial layer lines have reduced genetic diversity within the population, with the average observed heterozygosity estimates lower than 0.205 across their breeds’ categories and the average proportion of polymorphic loci lower than 0.680. We show that there is still a lot of genetic diversity preserved within the wild and less selected African, South American and some local Asian and European breeds with the average observed heterozygosity greater than 0.225 and the average proportion of polymorphic loci larger than 0.720 within their breeds’ categories.

Conclusions

It is important that such highly diverse breeds are maintained for the sustainability and flexibility of future chicken breeding. This diversity panel provides opportunities for exploitation for further chicken molecular genetic studies. With the possibility to further expand, it constitutes a very useful community resource for chicken genetic diversity research.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5727-9) contains supplementary material, which is available to authorized users.

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Most cited references 48

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Fast model-based estimation of ancestry in unrelated individuals.

David H. Alexander, John Novembre, Kenneth Lange (2009)

Population stratification has long been recognized as a confounding factor in genetic association studies. Estimated ancestries, derived from multi-locus genotype data, can be used to perform a statistical correction for population stratification. One popular technique for estimation of ancestry is the model-based approach embodied by the widely applied program structure. Another approach, implemented in the program EIGENSTRAT, relies on Principal Component Analysis rather than model-based estimation and does not directly deliver admixture fractions. EIGENSTRAT has gained in popularity in part owing to its remarkable speed in comparison to structure. We present a new algorithm and a program, ADMIXTURE, for model-based estimation of ancestry in unrelated individuals. ADMIXTURE adopts the likelihood model embedded in structure. However, ADMIXTURE runs considerably faster, solving problems in minutes that take structure hours. In many of our experiments, we have found that ADMIXTURE is almost as fast as EIGENSTRAT. The runtime improvements of ADMIXTURE rely on a fast block relaxation scheme using sequential quadratic programming for block updates, coupled with a novel quasi-Newton acceleration of convergence. Our algorithm also runs faster and with greater accuracy than the implementation of an Expectation-Maximization (EM) algorithm incorporated in the program FRAPPE. Our simulations show that ADMIXTURE's maximum likelihood estimates of the underlying admixture coefficients and ancestral allele frequencies are as accurate as structure's Bayesian estimates. On real-world data sets, ADMIXTURE's estimates are directly comparable to those from structure and EIGENSTRAT. Taken together, our results show that ADMIXTURE's computational speed opens up the possibility of using a much larger set of markers in model-based ancestry estimation and that its estimates are suitable for use in correcting for population stratification in association studies.

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Application of phylogenetic networks in evolutionary studies.

Daniel Huson, David Bryant (2006)

The evolutionary history of a set of taxa is usually represented by a phylogenetic tree, and this model has greatly facilitated the discussion and testing of hypotheses. However, it is well known that more complex evolutionary scenarios are poorly described by such models. Further, even when evolution proceeds in a tree-like manner, analysis of the data may not be best served by using methods that enforce a tree structure but rather by a richer visualization of the data to evaluate its properties, at least as an essential first step. Thus, phylogenetic networks should be employed when reticulate events such as hybridization, horizontal gene transfer, recombination, or gene duplication and loss are believed to be involved, and, even in the absence of such events, phylogenetic networks have a useful role to play. This article reviews the terminology used for phylogenetic networks and covers both split networks and reticulate networks, how they are defined, and how they can be interpreted. Additionally, the article outlines the beginnings of a comprehensive statistical framework for applying split network methods. We show how split networks can represent confidence sets of trees and introduce a conservative statistical test for whether the conflicting signal in a network is treelike. Finally, this article describes a new program, SplitsTree4, an interactive and comprehensive tool for inferring different types of phylogenetic networks from sequences, distances, and trees.

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Development of a high density 600K SNP genotyping array for chicken

Andreas Kranis, Almas A. Gheyas, Clarissa Boschiero … (2013)

Background High density (HD) SNP genotyping arrays are an important tool for genetic analyses of animals and plants. Although the chicken is one of the most important farm animals, no HD array is yet available for high resolution genetic analysis of this species. Results We report here the development of a 600 K Affymetrix® Axiom® HD genotyping array designed using SNPs segregating in a wide variety of chicken populations. In order to generate a large catalogue of segregating SNPs, we re-sequenced 243 chickens from 24 chicken lines derived from diverse sources (experimental, commercial broiler and layer lines) by pooling 10–15 samples within each line. About 139 million (M) putative SNPs were detected by mapping sequence reads to the new reference genome (Gallus_gallus_4.0) of which ~78 M appeared to be segregating in different lines. Using criteria such as high SNP-quality score, acceptable design scores predicting high conversion performance in the final array and uniformity of distribution across the genome, we selected ~1.8 M SNPs for validation through genotyping on an independent set of samples (n = 282). About 64% of the SNPs were polymorphic with high call rates (>98%), good cluster separation and stable Mendelian inheritance. Polymorphic SNPs were further analysed for their population characteristics and genomic effects. SNPs with extreme breach of Hardy-Weinberg equilibrium (P < 0.00001) were excluded from the panel. The final array, designed on the basis of these analyses, consists of 580,954 SNPs and includes 21,534 coding variants. SNPs were selected to achieve an essentially uniform distribution based on genetic map distance for both broiler and layer lines. Due to a lower extent of LD in broilers compared to layers, as reported in previous studies, the ratio of broiler and layer SNPs in the array was kept as 3:2. The final panel was shown to genotype a wide range of samples including broilers and layers with over 100 K to 450 K informative SNPs per line. A principal component analysis was used to demonstrate the ability of the array to detect the expected population structure which is an important pre-investigation step for many genome-wide analyses. Conclusions This Affymetrix® Axiom® array is the first SNP genotyping array for chicken that has been made commercially available to the public as a product. This array is expected to find widespread usage both in research and commercial application such as in genomic selection, genome-wide association studies, selection signature analyses, fine mapping of QTLs and detection of copy number variants.

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Author and article information

Contributors

Dorcus Kholofelo Malomane:

ORCID: http://orcid.org/0000-0003-4577-0781

dmaloma@gwdg.de

Henner Simianer: hsimian@gwdg.de

Annett Weigend: annett.weigend@fli.de

Christian Reimer: creimer@gwdg.de

Armin Otto Schmitt: armin.schmitt@uni-goettingen.de

Steffen Weigend: Steffen.Weigend@fli.de

Journal

Journal ID (nlm-ta): BMC Genomics

Journal ID (iso-abbrev): BMC Genomics

Title: BMC Genomics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2164

Publication date (Electronic): 7 May 2019

Publication date PMC-release: 7 May 2019

Publication date Collection: 2019

Volume: 20

Electronic Location Identifier: 345

Affiliations

[1 ]ISNI 0000 0001 2364 4210, GRID grid.7450.6, Animal Breeding and Genetics Group, Department of Animal Sciences, , University of Goettingen, ; 37075 Goettingen, Germany

[2 ]ISNI 0000 0001 2364 4210, GRID grid.7450.6, Center for Integrated Breeding Research, Department of Animal Sciences, , University of Goettingen, ; 37075 Goettingen, Germany

[3 ]ISNI 0000 0001 2364 4210, GRID grid.7450.6, Breeding Informatics Group, Department of Animal Sciences, , University of Göttingen, ; 37075 Göttingen, Germany

[4 ]GRID grid.417834.d, Institute of Farm Animal Genetics, , Friedrich-Loeffler-Institut, ; 31535 Neustadt, Germany

Author information

Dorcus Kholofelo Malomane http://orcid.org/0000-0003-4577-0781

Article

Publisher ID: 5727

DOI: 10.1186/s12864-019-5727-9

PMC ID: 6505202

PubMed ID: 31064348

SO-VID: 5692b9df-1813-49ec-be71-d529754f8a6d

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 10 December 2018

Date accepted : 23 April 2019

Funding

Funded by: German Federal Ministry of Education and Research

Award ID: FKZ 0315528E

Award Recipient : Steffen Weigend

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: synbreed panel,global chickens,genetic diversity,fancy breeds,snps

Data availability:

ScienceOpen disciplines: Genetics

Keywords: synbreed panel, global chickens, genetic diversity, fancy breeds, snps

The SYNBREED chicken diversity panel: a global resource to assess chicken diversity at high genomic resolution

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Arabidopsis genomics

Most cited references 48

Fast model-based estimation of ancestry in unrelated individuals.

Application of phylogenetic networks in evolutionary studies.

Development of a high density 600K SNP genotyping array for chicken

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