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      Development of Diagnostic SNP Markers To Monitor Hybridization Between Sika Deer ( Cervus nippon) and Wapiti ( Cervus elaphus)

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          Abstract

          Sika deer ( Cervus Nippon) and wapiti ( Cervus elaphus) are closely related species and their hybridization can result in significant allele-shift of their gene pool. Additive genetic effects and putative heterotic effects of their hybridization on growth performance could confer considerable economic advantage in deer farming. Here, we used double-digest restriction site-associated DNA sequencing technology (ddRAD-seq) and detected ∼320,000 genome-wide SNPs from 30 captive individuals: 7 sika deer, 6 wapiti and 17 F1 hybrids (reciprocal cross). By screening observed heterozygosity of each SNP across four taxonomic groups, we report for the first time a resource of 2,015 putative diagnostic SNP markers (species-specific SNPs for sika deer and wapiti), which can be used to design tools for assessing or monitoring the degree of hybridization between sika deer and wapiti. These ddRAD-seq data and SNP datasets are also valuable resources for genome-wide studies, including trait discovery for breeders of domestic deer.

          Most cited references24

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          A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data

          (2013)
          Motivation: Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. Results: We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. Availability: http://samtools.sourceforge.net. Contact: hengli@broadinstitute.org.
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            The role of hybridization in evolution.

            N H Barton (2001)
            Hybridization may influence evolution in a variety of ways. If hybrids are less fit, the geographical range of ecologically divergent populations may be limited, and prezygotic reproductive isolation may be reinforced. If some hybrid genotypes are fitter than one or both parents, at least in some environments, then hybridization could make a positive contribution. Single alleles that are at an advantage in the alternative environment and genetic background will introgress readily, although such introgression may be hard to detect. 'Hybrid speciation', in which fit combinations of alleles are established, is more problematic; its likelihood depends on how divergent populations meet, and on the structure of epistasis. These issues are illustrated using Fisher's model of stabilizing selection on multiple traits, under which reproductive isolation evolves as a side-effect of adaptation in allopatry. This confirms a priori arguments that while recombinant hybrids are less fit on average, some gene combinations may be fitter than the parents, even in the parental environment. Fisher's model does predict heterosis in diploid F1s, asymmetric incompatibility in reciprocal backcrosses, and (when dominance is included) Haldane's Rule. However, heterosis arises only when traits are additive, whereas the latter two patterns require dominance. Moreover, because adaptation is via substitutions of small effect, Fisher's model does not generate the strong effects of single chromosome regions often observed in species crosses.
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              Deriving genotypes from RAD-seq short-read data using Stacks

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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
                22 May 2018
                July 2018
                : 8
                : 7
                : 2173-2179
                Affiliations
                [1]State Key Laboratory for Molecular Biology of Special Wild Economic Animals, Institute of Special Wild Economic Animals and Plants, Chinese Academy of Agricultural Sciences, No. 4899, Juye Street, Jingyue District, Changchun, Jilin province, 130112, P.R. China
                Author notes
                [1 ]Corresponding author: Chunyi Li, PhD, E-mail: Lichunyi1959@ 123456163.com ; Hengxing Ba, PhD, E-mail: bahengxing@ 123456caas.cn .
                [2]

                Hengxing Ba and Zhipeng Li contributed to this manuscript equally

                Author information
                http://orcid.org/0000-0003-0882-8841
                http://orcid.org/0000-0001-8474-045X
                Article
                GGG_200417
                10.1534/g3.118.200417
                6027871
                29789312
                05bddfa5-86f0-46c3-9ecc-a94063afc2eb
                Copyright © 2018 Ba 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
                : 26 April 2018
                : 20 May 2018
                Page count
                Figures: 4, Tables: 1, Equations: 0, References: 35, Pages: 7
                Categories
                Software and Data Resources

                Genetics
                sika deer,wapiti,hybridization,ddrad-seq,snp discovery,stacks software
                Genetics
                sika deer, wapiti, hybridization, ddrad-seq, snp discovery, stacks software

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