Search for authorsSearch for similar articles
19
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Single-step genome-wide association study for social genetic effects and direct genetic effects on growth in Landrace pigs

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In livestock social interactions, social genetic effects (SGE) represent associations between phenotype of one individual and genotype of another. Such associations occur when the trait of interest is affected by transmissible phenotypes of social partners. The aim of this study was to estimate SGE and direct genetic effects (DGE, genetic effects of an individual on its own phenotype) on average daily gain (ADG) in Landrace pigs, and to conduct single-step genome-wide association study using SGE and DGE as dependent variables to identify quantitative trait loci (QTLs) and their positional candidate genes. A total of 1,041 Landrace pigs were genotyped using the Porcine SNP 60K BeadChip. Estimates of the two effects were obtained using an extended animal model. The SGE contributed 16% of the total heritable variation of ADG. The total heritability estimated by the extended animal model including both SGE and DGE was 0.52. The single-step genome-wide association study identified a total of 23 QTL windows for the SGE on ADG distributed across three chromosomes (i.e., SSC1, SSC2, and SSC6). Positional candidate genes within these QTL regions included PRDM13, MAP3K7, CNR1, HTR1E, IL4, IL5, IL13, KIF3A, EFHD2, SLC38A7, mTOR, CNOT1, PLCB2, GABRR1, and GABRR2, which have biological roles in neuropsychiatric processes. The results of biological pathway and gene network analyses also support the association of the neuropsychiatric processes with SGE on ADG in pigs. Additionally, a total of 11 QTL windows for DGE on ADG in SSC2, 3, 6, 9, 10, 12, 14, 16, and 17 were detected with positional candidate genes such as ARL15. We found a putative pleotropic QTL for both SGE and DGE on ADG on SSC6. Our results in this study provide important insights that can help facilitate a better understanding of the molecular basis of SGE for socially affected traits.

          Related collections

          Most cited references51

          • Record: found
          • Abstract: found
          • Article: not found

          Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score.

          The first national single-step, full-information (phenotype, pedigree, and marker genotype) genetic evaluation was developed for final score of US Holsteins. Data included final scores recorded from 1955 to 2009 for 6,232,548 Holsteins cows. BovineSNP50 (Illumina, San Diego, CA) genotypes from the Cooperative Dairy DNA Repository (Beltsville, MD) were available for 6,508 bulls. Three analyses used a repeatability animal model as currently used for the national US evaluation. The first 2 analyses used final scores recorded up to 2004. The first analysis used only a pedigree-based relationship matrix. The second analysis used a relationship matrix based on both pedigree and genomic information (single-step approach). The third analysis used the complete data set and only the pedigree-based relationship matrix. The fourth analysis used predictions from the first analysis (final scores up to 2004 and only a pedigree-based relationship matrix) and prediction using a genomic based matrix to obtain genetic evaluation (multiple-step approach). Different allele frequencies were tested in construction of the genomic relationship matrix. Coefficients of determination between predictions of young bulls from parent average, single-step, and multiple-step approaches and their 2009 daughter deviations were 0.24, 0.37 to 0.41, and 0.40, respectively. The highest coefficient of determination for a single-step approach was observed when using a genomic relationship matrix with assumed allele frequencies of 0.5. Coefficients for regression of 2009 daughter deviations on parent-average, single-step, and multiple-step predictions were 0.76, 0.68 to 0.79, and 0.86, respectively, which indicated some inflation of predictions. The single-step regression coefficient could be increased up to 0.92 by scaling differences between the genomic and pedigree-based relationship matrices with little loss in accuracy of prediction. One complete evaluation took about 2h of computing time and 2.7 gigabytes of memory. Computing times for single-step analyses were slightly longer (2%) than for pedigree-based analysis. A national single-step genetic evaluation with the pedigree relationship matrix augmented with genomic information provided genomic predictions with accuracy and bias comparable to multiple-step procedures and could account for any population or data structure. Advantages of single-step evaluations should increase in the future when animals are pre-selected on genotypes. Copyright 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Design of a High Density SNP Genotyping Assay in the Pig Using SNPs Identified and Characterized by Next Generation Sequencing Technology

            Background The dissection of complex traits of economic importance to the pig industry requires the availability of a significant number of genetic markers, such as single nucleotide polymorphisms (SNPs). This study was conducted to discover several hundreds of thousands of porcine SNPs using next generation sequencing technologies and use these SNPs, as well as others from different public sources, to design a high-density SNP genotyping assay. Methodology/Principal Findings A total of 19 reduced representation libraries derived from four swine breeds (Duroc, Landrace, Large White, Pietrain) and a Wild Boar population and three restriction enzymes (AluI, HaeIII and MspI) were sequenced using Illumina's Genome Analyzer (GA). The SNP discovery effort resulted in the de novo identification of over 372K SNPs. More than 549K SNPs were used to design the Illumina Porcine 60K+SNP iSelect Beadchip, now commercially available as the PorcineSNP60. A total of 64,232 SNPs were included on the Beadchip. Results from genotyping the 158 individuals used for sequencing showed a high overall SNP call rate (97.5%). Of the 62,621 loci that could be reliably scored, 58,994 were polymorphic yielding a SNP conversion success rate of 94%. The average minor allele frequency (MAF) for all scorable SNPs was 0.274. Conclusions/Significance Overall, the results of this study indicate the utility of using next generation sequencing technologies to identify large numbers of reliable SNPs. In addition, the validation of the PorcineSNP60 Beadchip demonstrated that the assay is an excellent tool that will likely be used in a variety of future studies in pigs.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Adipogenesis and WNT signalling.

              An inability of adipose tissue to expand consequent to exhausted capacity to recruit new adipocytes might underlie the association between obesity and insulin resistance. Adipocytes arise from mesenchymal precursors whose commitment and differentiation along the adipocytic lineage is tightly regulated. These regulatory factors mediate cross-talk between adipose cells, ensuring that adipocyte growth and differentiation are coupled to energy storage demands. The WNT family of autocrine and paracrine growth factors regulates adult tissue maintenance and remodelling and, consequently, is well suited to mediate adipose cell communication. Indeed, several recent reports, summarized in this review, implicate WNT signalling in regulating adipogenesis. Manipulating the WNT pathway to alter adipose cellular makeup, therefore, constitutes an attractive drug-development target to combat obesity-associated metabolic complications.
                Bookmark

                Author and article information

                Contributors
                heebokpark@kongju.ac.kr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                11 September 2020
                11 September 2020
                2020
                : 10
                : 14958
                Affiliations
                [1 ]GRID grid.420186.9, ISNI 0000 0004 0636 2782, National Institute of Animal Science, Rural Development Administration, ; Cheonan, 31000 Republic of Korea
                [2 ]GRID grid.411545.0, ISNI 0000 0004 0470 4320, Korea Zoonosis Research Institute, , Chonbuk National University, ; 54531 Iksan, Republic of Korea
                [3 ]GRID grid.8581.4, ISNI 0000 0001 1943 6646, Animal Breeding and Genetics Program, Institute for Research and Technology in Food and Agriculture (IRTA), ; Torre Marimon, 08140 Caldes de Montbui, Spain
                [4 ]GRID grid.411968.3, ISNI 0000 0004 0642 2618, Department of Animal Life Resources, , Hankyong National University, ; Anseong, 17579 Republic of Korea
                [5 ]GRID grid.411118.c, ISNI 0000 0004 0647 1065, Department of Animal Resources Science, , Kongju National University, ; Yesan, 32439 Republic of Korea
                Article
                71647
                10.1038/s41598-020-71647-x
                7486944
                32917921
                4a05e7b6-644c-44df-bc03-2ed7619c96ef
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 February 2020
                : 3 August 2020
                Funding
                Funded by: Rural Development Administration
                Award ID: PJ00997101
                Funded by: Kongju National University
                Award ID: 2019-0260-01
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                genetics,agricultural genetics,animal breeding,genetic association study,genetic markers,genomics,heritable quantitative trait,systems biology,biochemical networks

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content468

                Cited by9

                Most referenced authors918