Dataset Information

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

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.

SUBMITTER: Malomane DK

PROVIDER: S-EPMC6505202 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Malomane Dorcus Kholofelo DK Simianer Henner H Weigend Annett A Reimer Christian C Schmitt Armin Otto AO Weigend Steffen S

BMC genomics 20190507 1

<h4>Background</h4>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 betw ...[more]

PMID: 31064348

Similar Datasets

Project description:Wheat blast is an emerging threat to wheat production, due to its recent migration to South Asia and Sub-Saharan Africa. Because genomic selection (GS) has emerged as a promising breeding strategy, the key objective of this study was to evaluate it for wheat blast phenotyped at precision phenotyping platforms in Quirusillas (Bolivia), Okinawa (Bolivia) and Jashore (Bangladesh) using three panels: (i) a diversity panel comprising 172 diverse spring wheat genotypes, (ii) a breeding panel comprising 248 elite breeding lines, and (iii) a full-sibs panel comprising 298 full-sibs. We evaluated two genomic prediction models (the genomic best linear unbiased prediction or GBLUP model and the Bayes B model) and compared the genomic prediction accuracies with accuracies from a fixed effects model (with selected blast-associated markers as fixed effects), a GBLUP + fixed effects model and a pedigree relationships-based model (ABLUP). On average, across all the panels and environments analyzed, the GBLUP + fixed effects model (0.63 ± 0.13) and the fixed effects model (0.62 ± 0.13) gave the highest prediction accuracies, followed by the Bayes B (0.59 ± 0.11), GBLUP (0.55 ± 0.1), and ABLUP (0.48 ± 0.06) models. The high prediction accuracies from the fixed effects model resulted from the markers tagging the 2NS translocation that had a large effect on blast in all the panels. This implies that in environments where the 2NS translocation-based blast resistance is effective, genotyping one to few markers tagging the translocation is sufficient to predict the blast response and genome-wide markers may not be needed. We also observed that marker-assisted selection (MAS) based on a few blast-associated markers outperformed GS as it selected the highest mean percentage (88.5%) of lines also selected by phenotypic selection and discarded the highest mean percentage of lines (91.8%) also discarded by phenotypic selection, across all panels. In conclusion, while this study demonstrates that MAS might be a powerful strategy to select for the 2NS translocation-based blast resistance, we emphasize that further efforts to use genomic tools to identify non-2NS translocation-based blast resistance are critical.

Project description:Purpose: Chromosomal microarray analysis (CMA) to assess copy number variation (CNV) content is now used as a first tier genetic diagnostic test for individuals with unexplained neurodevelopmental disorders (NDD) or multiple congenital anomalies (MCA). Over 100 cytogenetic labs worldwide are using the Affymetrix CytoScan HD 2.7M array to genotype >15,000 clinical samples per month. The aim of this study is to develop a CNV resource from a population control cohort that can be used as a community resource for interpretation of clinical and research samples. Methods: We have genotyped a large population control set (1,000 individuals from our Ontario Population Genomics Platform (OPGP)) using the Affymetrix CytoScan HD microarray comprising 2.7 million probes. Four independent algorithms were applied to detect and assess high confidence CNVs. Reproducibility and validations were quantified using sample replicates and Quantitative-PCR (QPCR), respectively. Results: DNA from 873 individuals from the OPGP cohort passed quality control and we have identified 71,178 CNVs (81 CNVs/individual) distributed across 796 different cytogenetic regions in the genome; 9.8% of the CNVs were previously unreported. After applying three layers of filtering criteria, from our high confidence CNVs dataset, we obtained a >95% reproducibility and >90% validation rate. Due to the array's high probe density within genic regions, our high confidence CNV data set show 73% of the detected CNVs overlapped at least one gene. Conclusion: The genotype data and annotated CNVs presented in this study will represent a valuable public resource enabling clinical genetics research and diagnostics. For array quality control, CEL files were processed using modules from the Affymetrix power tools and genotypes were extracted from the CHP file. Samples passing the median of the absolute pairwise differences (MAPD) < 0.20 and waviness-sd < 0.11 were retained for further analysis. After multiple checks, we excluded 52 samples that do not meet quality control (QC) cutoffs. To confirm the sample's self-reported gender, we have matched the sex chromosome information from the array and identified six samples with gender mismatch, which were excluded from the analysis. We also excluded 47 samples due to excessive CNV calls. A final set of 895 samples were used for further analysis. This number included 22 sample replicates (indicated by _1 following the Sample title), which were used to determine reproducibility of the array calls. The CNV data for this study is available from dbVar (NCBI), DGVa (EBI) accession number estd212, and DGV.

Dataset Information

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

Background

Results

Conclusions

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets