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      Genome-wide characterization of genetic variants and putative regions under selection in meat and egg-type chicken lines

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          Abstract

          Background

          Meat and egg-type chickens have been selected for several generations for different traits. Artificial and natural selection for different phenotypes can change frequency of genetic variants, leaving particular genomic footprints throghtout the genome. Thus, the aims of this study were to sequence 28 chickens from two Brazilian lines (meat and white egg-type) and use this information to characterize genome-wide genetic variations, identify putative regions under selection using Fst method, and find putative pathways under selection.

          Results

          A total of 13.93 million SNPs and 1.36 million INDELs were identified, with more variants detected from the broiler (meat-type) line. Although most were located in non-coding regions, we identified 7255 intolerant non-synonymous SNPs, 512 stopgain/loss SNPs, 1381 frameshift and 1094 non-frameshift INDELs that may alter protein functions. Genes harboring intolerant non-synonymous SNPs affected metabolic pathways related mainly to reproduction and endocrine systems in the white-egg layer line, and lipid metabolism and metabolic diseases in the broiler line. Fst analysis in sliding windows, using SNPs and INDELs separately, identified over 300 putative regions of selection overlapping with more than 250 genes. For the first time in chicken, INDEL variants were considered for selection signature analysis, showing high level of correlation in results between SNP and INDEL data. The putative regions of selection signatures revealed interesting candidate genes and pathways related to important phenotypic traits in chicken, such as lipid metabolism, growth, reproduction, and cardiac development.

          Conclusions

          In this study, Fst method was applied to identify high confidence putative regions under selection, providing novel insights into selection footprints that can help elucidate the functional mechanisms underlying different phenotypic traits relevant to meat and egg-type chicken lines. In addition, we generated a large catalog of line-specific and common genetic variants from a Brazilian broiler and a white egg layer line that can be used for genomic studies involving association analysis with phenotypes of economic interest to the poultry industry.

          Electronic supplementary material

          The online version of this article (10.1186/s12864-018-4444-0) contains supplementary material, which is available to authorized users.

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          Most cited references50

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          Human non-synonymous SNPs: server and survey.

          Human single nucleotide polymorphisms (SNPs) represent the most frequent type of human population DNA variation. One of the main goals of SNP research is to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. Non-synonymous coding SNPs (nsSNPs) comprise a group of SNPs that, together with SNPs in regulatory regions, are believed to have the highest impact on phenotype. Here we present a World Wide Web server to predict the effect of an nsSNP on protein structure and function. The prediction method enabled analysis of the publicly available SNP database HGVbase, which gave rise to a dataset of nsSNPs with predicted functionality. The dataset was further used to compare the effect of various structural and functional characteristics of amino acid substitutions responsible for phenotypic display of nsSNPs. We also studied the dependence of selective pressure on the structural and functional properties of proteins. We found that in our dataset the selection pressure against deleterious SNPs depends on the molecular function of the protein, although it is insensitive to several other protein features considered. The strongest selective pressure was detected for proteins involved in transcription regulation.
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            Development of a high density 600K SNP genotyping array for chicken

            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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              DNA methylation in lung cells is associated with asthma endotypes and genetic risk.

              The epigenome provides a substrate through which environmental exposures can exert their effects on gene expression and disease risk, but the relative importance of epigenetic variation on human disease onset and progression is poorly characterized. Asthma is a heterogeneous disease of the airways, for which both onset and clinical course result from interactions between host genotype and environmental exposures, yet little is known about the molecular mechanisms for these interactions. We assessed genome-wide DNA methylation using the Infinium Human Methylation 450K Bead Chip and characterized the transcriptome by RNA sequencing in primary airway epithelial cells from 74 asthmatic and 41 nonasthmatic adults. Asthma status was based on doctor's diagnosis and current medication use. Genotyping was performed using various Illumina platforms. Our study revealed a regulatory locus on chromosome 17q12-21 associated with asthma risk and epigenetic signatures of specific asthma endotypes and molecular networks. Overall, these data support a central role for DNA methylation in lung cells, which promotes distinct molecular pathways of asthma pathogenesis and modulates the effects of genetic variation on disease risk and clinical heterogeneity.
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                Author and article information

                Contributors
                clarissaboschi@yahoo.com
                gcmmoreira@usp.br
                almas.gheyas@ed.ac.uk
                thaisfernanda.godoy@gmail.com
                gustavo_gasparin@yahoo.com.br
                pilarmariani@hotmail.com
                marcelapaduan@hotmail.com
                alinecesar@usp.br
                monica.ledur@embrapa.br
                llcoutinho@usp.br
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                25 January 2018
                25 January 2018
                2018
                : 19
                : 83
                Affiliations
                [1 ]ISNI 0000 0004 1937 0722, GRID grid.11899.38, Animal Biotechnology Laboratory, Animal Science Department, , Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo (USP), ; Piracicaba, SP 13418-900 Brazil
                [2 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Department of Genetics and Genomics, , The Roslin Institute and Royal School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, ; Midlothian, EH25 9RG UK
                [3 ]Embrapa Suínos e Aves, Concórdia, SC 89715-899 Brazil
                [4 ]Noble Reserch Institute, 2510 Sam Noble Parkway, Ardmore, Oklahoma 73401 USA
                Author information
                http://orcid.org/0000-0002-6575-5266
                Article
                4444
                10.1186/s12864-018-4444-0
                5785814
                29370772
                f59e2a45-842a-482e-97e8-bc641450ca4e
                © The Author(s). 2018

                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
                : 2 April 2017
                : 10 January 2018
                Funding
                Funded by: Fundação de Amparo à Pesquisa do Estado de São Paulo (BR)
                Award ID: 2014/08704-0
                Funded by: FundRef http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Award ID: 370620/2013-5
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001807, Fundação de Amparo à Pesquisa do Estado de São Paulo;
                Award ID: 14/21380-9
                Award ID: 15/00616-7
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Genetics
                fat deposition,fst,genetic variants,next generation sequencing,indel,selection signatures,snp,poultry
                Genetics
                fat deposition, fst, genetic variants, next generation sequencing, indel, selection signatures, snp, poultry

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