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      Identifying Genetic Differences Between Dongxiang Blue-Shelled and White Leghorn Chickens Using Sequencing Data

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          Abstract

          The Dongxiang Blue-shelled chicken is one of the most valuable Chinese indigenous poultry breeds. However, compared to the Italian native White Leghorn, although this Chinese breed possesses numerous favorable characteristics, it also exhibits lower growth performance and fertility. Here, we utilized genotyping sequencing data obtained via genome reduction on a sequencing platform to detect 100,114 single nucleotide polymorphisms and perform further biological analysis and functional annotation. We employed cross-population extended haplotype homozygosity, eigenvector decomposition combined with genome-wide association studies (EigenGWAS), and efficient mixed-model association expedited methods to detect areas of the genome that are potential selected regions (PSR) in both chicken breeds, and performed gene ontology (GO) enrichment and quantitative trait loci (QTL) analyses annotating using the Kyoto Encyclopedia of Genes and Genomes. The results of this study revealed a total of 2424 outlier loci ( p-value <0.01), of which 2144 occur in the White Leghorn breed and 280 occur in the Dongxiang Blue-shelled chicken. These correspond to 327 and 94 PSRs containing 297 and 54 genes, respectively. The most significantly selected genes in Blue-shelled chicken are TMEM141 and CLIC3, while the SLCO1B3 gene, related to eggshell color, was identified via EigenGWAS. We show that the White Leghorn genes JARID2, RBMS3, GPC3, TRIB2, ROBO1, SAMSN1, OSBP2, and IGFALS are involved in immunity, reproduction, and growth, and thus might represent footprints of the selection process. In contrast, we identified six significantly enriched pathways in the Dongxiang Blue-shelled chicken that are related to amino acid and lipid metabolism as well as signal transduction. Our results also reveal the presence of a GO term associated with cell metabolism that occurs mainly in the White Leghorn breed, while the most significant QTL regions mapped to the Chicken QTL Database (GG_4.0) for the Dongxiang Blue-shelled breed are predominantly related to lesions, bone mineral content, and other related traits compared to tibia length and body weight ( i.e., at 14, 28, 42, and 70 d) in the White Leghorn. The results of this study highlight differences in growth, immunity, and egg quality traits between the two breeds, and provide a foundation for the exploration of their genetic mechanisms.

          Most cited references21

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          A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase.

          We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because of recombination, this clustering tends to be local in nature, our model allows cluster memberships to change continuously along the chromosome according to a hidden Markov model. This approach is flexible, allowing for both "block-like" patterns of linkage disequilibrium (LD) and gradual decline in LD with distance. The resulting model is also fast and, as a result, is practicable for large data sets (e.g., thousands of individuals typed at hundreds of thousands of markers). We illustrate the utility of the model by applying it to dense single-nucleotide-polymorphism genotype data for the tasks of imputing missing genotypes and estimating haplotypic phase. For imputing missing genotypes, methods based on this model are as accurate or more accurate than existing methods. For haplotype estimation, the point estimates are slightly less accurate than those from the best existing methods (e.g., for unrelated Centre d'Etude du Polymorphisme Humain individuals from the HapMap project, switch error was 0.055 for our method vs. 0.051 for PHASE) but require a small fraction of the computational cost. In addition, we demonstrate that the model accurately reflects uncertainty in its estimates, in that probabilities computed using the model are approximately well calibrated. The methods described in this article are implemented in a software package, fastPHASE, which is available from the Stephens Lab Web site.
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            A test of neutral molecular evolution based on nucleotide data.

            The neutral theory of molecular evolution predicts that regions of the genome that evolve at high rates, as revealed by interspecific DNA sequence comparisons, will also exhibit high levels of polymorphism within species. We present here a conservative statistical test of this prediction based on a constant-rate neutral model. The test requires data from an interspecific comparison of at least two regions of the genome and data on levels of intraspecific polymorphism in the same regions from at least one species. The model is rejected for data from the region encompassing the Adh locus and the 5' flanking sequence of Drosophila melanogaster and Drosophila sechellia. The data depart from the model in a direction that is consistent with the presence of balanced polymorphism in the coding region.
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              The Population Reference Sample, POPRES: a resource for population, disease, and pharmacological genetics research.

              Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetics research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This growing resource was initially genotyped with a commercially available genome-wide 500,000 single-nucleotide polymorphism panel. This project includes nearly 6,000 subjects of African-American, East Asian, South Asian, Mexican, and European origin. Seven informative axes of variation identified via principal-component analysis (PCA) of these data confirm the overall integrity of the data and highlight important features of the genetic structure of diverse populations. The potential value of such extensively genotyped collections is illustrated by selection of genetically matched population controls in a genome-wide analysis of abacavir-associated hypersensitivity reaction. We find that matching based on country of origin, identity-by-state distance, and multidimensional PCA do similarly well to control the type I error rate. The genotype and demographic data from this reference sample are freely available through the NCBI database of Genotypes and Phenotypes (dbGaP).
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                Author and article information

                Journal
                G3 (Bethesda)
                Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                2160-1836
                29 November 2017
                February 2018
                : 8
                : 2
                : 469-476
                Affiliations
                [* ]Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, 200240, P.R. China
                []Institute of Animal Husbandry and Veterinary Research, Shanghai Academy of Agricultural Sciences, Shanghai 201106, China
                []Shanghai Key Laboratory of Veterinary Biotechnology, Shanghai 200240, P.R. China
                Author notes
                [1 ]Corresponding authors: School of Agriculture and Biology, Shanghai Jiao Tong University, No. 800 Dongchuan Rd., Minhang District, Shanghai 200240, P.R. China. E-mail: xiangzhezhang@ 123456sjtu.edu.cn ; and panyuchun1963@ 123456aliyun.com
                Article
                GGG_300382
                10.1534/g3.117.300382
                5919749
                29187421
                726a23bd-2173-478c-be35-d8935087da48
                Copyright © 2018 Zhao et al.

                This is an open-access article 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 the original work is properly cited.

                History
                : 24 October 2017
                : 19 November 2017
                Page count
                Figures: 3, Tables: 3, Equations: 1, References: 32, Pages: 8
                Categories
                Investigations

                Genetics
                chicken,xp-ehh,eigengwas,emmax,selected regions,functional annotation
                Genetics
                chicken, xp-ehh, eigengwas, emmax, selected regions, functional annotation

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