7
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Genetic diversity in reproductive traits of Braunvieh cattle determined with SNP markers

      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

          Braunvieh is an important dual‐purpose breed in the Mexican tropics. The study of its genetic diversity is key to implementing genetic improvement programs. This study was conducted to determine genetic diversity of reproductive traits in a Mexican Braunvieh beef cattle population using single nucleotide polymorphisms in candidate genes. Information from 24 genes with 52 intra‐genic loci reported in literature to be associated with productive life, pregnancy rate and cow and heifer conception rate of 150 Braunvieh males and females was considered. Observed heterozygosity (Ho) revealed high genetic diversity for the studied traits, Ho = 0.42 ± 0.087, relative to that of other populations of the same breed. Cluster analyses were carried out using the Ward and K‐means algorithms. These analyses revealed high genetic diversity that was observed in the biplot of non‐metric multi‐dimensional scaling. It was found that clustering strategy allowed visualisation of distant groups by genotype but not by favourable alleles in all the loci. We found that the genes CSNK1E, DNAH11, DSC2, IBSP and OCLN affected most of the traits in our study and they were highly informative. Therefore, they represent a potential resource for selection and crossbreeding programs of the traits studied in Braunvieh. The analyses showed that the Mexican Braunvieh population has a high level of genetic diversity, arguably due to decades‐long adaptation to the Mexican tropics.

          Abstract

          We studied the genetic diversity of reproductive traits in a Mexican Braunvieh beef cattle using SNP markers. Analyses revealed that the genes CSNK1E, DNAH11, DSC2, IBSP and OCLN affected most of the traits in our study and they were highly informative.

          Related collections

          Most cited references32

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

          Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment.

          Genotypes are frequently used to identify parentage. Such analysis is notoriously vulnerable to genotyping error, and there is ongoing debate regarding how to solve this problem. Many scientists have used the computer program CERVUS to estimate parentage, and have taken advantage of its option to allow for genotyping error. In this study, we show that the likelihood equations used by versions 1.0 and 2.0 of CERVUS to accommodate genotyping error miscalculate the probability of observing an erroneous genotype. Computer simulation and reanalysis of paternity in Rum red deer show that correcting this error increases success in paternity assignment, and that there is a clear benefit to accommodating genotyping errors when errors are present. A new version of CERVUS (3.0) implementing the corrected likelihood equations is available at http://www.fieldgenetics.com.
            Bookmark
            • Record: found
            • Abstract: not found
            • Book: not found

            R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              A missense mutation in growth differentiation factor 9 (GDF9) is strongly associated with litter size in sheep

              Background A genome wide association study for litter size in Norwegian White Sheep (NWS) was conducted using the recently developed ovine 50K SNP chip from Illumina. After genotyping 378 progeny tested artificial insemination (AI) rams, a GWAS analysis was performed on estimated breeding values (EBVs) for litter size. Results A QTL-region was identified on sheep chromosome 5, close to the growth differentiation factor 9 (GDF9), which is known to be a strong candidate gene for increased ovulation rate/litter size. Sequencing of the GDF9 coding region in the most extreme sires (high and low BLUP values) revealed a single nucleotide polymorphism (c.1111G>A), responsible for a Val→Met substitution at position 371 (V371M). This polymorphism has previously been identified in Belclare and Cambridge sheep, but was not found to be associated with fertility. In our NWS-population the c.1111G>A SNP showed stronger association with litter size than any other single SNP on the Illumina 50K ovine SNP chip. Based on the estimated breeding values, daughters of AI rams homozygous for c.1111A will produce minimum 0.46 - 0.57 additional lambs compared to daughters of wild-type rams. Conclusion We have identified a missense mutation in the bioactive part of the GDF9 protein that shows strong association with litter size in NWS. Based on the NWS breeding history and the marked increase in the c.1111A allele frequency in the AI ram population since 1983, we hypothesize that c.1111A allele originate from Finnish landrace imported to Norway around 1970. Because of the widespread use of Finnish landrace and the fact that the ewes homozygous for the c.1111A allele are reported to be fertile, we expect the commercial impact of this mutation to be high.
                Bookmark

                Author and article information

                Contributors
                arf@correo.chapingo.mx
                perpdgo@colpos.mx
                Journal
                Vet Med Sci
                Vet Med Sci
                10.1002/(ISSN)2053-1095
                VMS3
                Veterinary Medicine and Science
                John Wiley and Sons Inc. (Hoboken )
                2053-1095
                12 May 2022
                July 2022
                : 8
                : 4 ( doiID: 10.1002/vms3.v8.4 )
                : 1709-1720
                Affiliations
                [ 1 ] Posgrado en Producción Animal Universidad Autónoma Chapingo Texcoco Estado de México Mexico
                [ 2 ] Socio Economía Estadística e Informática Colegio de Postgraduados Texcoco Estado de México Mexico
                Author notes
                [*] [* ] Correspondence

                Paulino Pérez‐Rodríguez, Socio Economía Estadística e Informática, Colegio de Postgraduados, Texcoco, Estado de México, Mexico.

                Email: perpdgo@ 123456colpos.mx

                Agustín Ruíz‐Flores, Posgrado en Producción Animal, Universidad Autónoma Chapingo, Texcoco, Estado de México, Mexico.

                Email: arf@ 123456correo.chapingo.mx

                Author information
                https://orcid.org/0000-0002-3242-1040
                https://orcid.org/0000-0001-8267-2107
                https://orcid.org/0000-0001-6077-783X
                https://orcid.org/0000-0002-3202-1784
                Article
                VMS3836
                10.1002/vms3.836
                9297803
                35545927
                15c427b8-6747-41d4-a9e7-a76951d86fdb
                © 2022 The Authors. Veterinary Medicine and Science published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                Page count
                Figures: 4, Tables: 5, Pages: 12, Words: 7369
                Funding
                Funded by: Universidad Autónoma Chapingo , doi 10.13039/100009534;
                Award ID: DGIP‐166701012
                Categories
                Original Article
                RUMINANTS
                Original Articles
                Custom metadata
                2.0
                July 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.7 mode:remove_FC converted:20.07.2022

                brown swiss,candidate gene,cluster analysis,genetic variability

                Comments

                Comment on this article