Genetic Distinctness and Diversity of American Aberdeen Cattle Compared to Common Beef Breeds in the United States

American Aberdeen (AD) cattle in the USA descend from an Aberdeen Angus herd originally brought to the Trangie Agricultural Research Centre, New South Wales, AUS. Although put under specific selection pressure for yearling growth rate, AD remain genomically uncharacterized. The objective was to characterize the genetic diversity and structure of purebred and crossbred AD cattle relative to seven common USA beef breeds using available whole-genome SNP data. A total of 1140 animals consisting of 404 purebred (n = 8 types) and 736 admixed individuals (n = 10 types) was used. Genetic diversity metrics, an analysis of molecular variance, and a discriminant analysis of principal components were employed. When linkage disequilibrium was not accounted for, markers influenced basic diversity parameter estimates, especially for AD cattle. Even so, intrapopulation and interpopulation estimates separate AD cattle from other purebred types (e.g., Latter’s pairwise FST ranged from 0.1129 to 0.2209), where AD cattle were less heterozygous and had lower allelic richness than other purebred types. The admixed AD-influenced cattle were intermediate to other admixed types for similar parameters. The diversity metrics separation and differences support strong artificial selection pressures during and after AD breed development, shaping the evolution of the breed and making them genomically distinct from similar breeds.

[1]  M. Calus,et al.  The use of a genomic relationship matrix for breed assignment of cattle breeds: comparison and combination with a machine learning method , 2023, Journal of animal science.

[2]  Joshua A. Thia Guidelines for standardising the application of discriminant analysis of principal components to genotype data , 2022, bioRxiv.

[3]  H. Soyeurt,et al.  Development of a genomic tool for breed assignment by comparison of different classification models: Application to three local cattle breeds. , 2021, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

[4]  K. Marshall,et al.  SNP panels for the estimation of dairy breed proportion and parentage assignment in African crossbred dairy cattle , 2021, Genetics, selection, evolution : GSE.

[5]  Michael N Romanov,et al.  Assessing the effects of rare alleles and linkage disequilibrium on estimates of genetic diversity in the chicken populations. , 2021, Animal : an international journal of animal bioscience.

[6]  Hong Chen,et al.  Assessing genomic diversity and signatures of selection in Jiaxian Red cattle using whole-genome sequencing data , 2021, BMC Genomics.

[7]  S. McWilliam,et al.  A low-density SNP genotyping panel for the accurate prediction of cattle breeds. , 2020, Journal of animal science.

[8]  Se Pill Park,et al.  Genetic characteristics of Korean Jeju Black cattle with high density single nucleotide polymorphisms , 2020, Asian-Australasian journal of animal sciences.

[9]  C. Cullingham,et al.  The influence of a priori grouping on inference of genetic clusters: simulation study and literature review of the DAPC method , 2020, Heredity.

[10]  Earl T. Barr,et al.  POSIT: Simultaneously Tagging Natural and Programming Languages , 2020, 2020 IEEE/ACM 42nd International Conference on Software Engineering (ICSE).

[11]  Steven G. Schroeder,et al.  De novo assembly of the cattle reference genome with single-molecule sequencing , 2020, GigaScience.

[12]  A. Löytynoja,et al.  Effects of marker type and filtering criteria on QST-FST comparisons , 2019, Royal Society Open Science.

[13]  B. Bhushan,et al.  Comparative analysis of five different methods to design a breed-specific SNP panel for cattle , 2019, Animal biotechnology.

[14]  H. Pausch,et al.  Assessing genomic diversity and signatures of selection in Original Braunvieh cattle using whole-genome sequencing data , 2019, BMC Genomics.

[15]  I. Hulsegge,et al.  Development of a genetic tool for determining breed purity of cattle , 2019, Livestock Science.

[16]  Jiabao Zhang,et al.  Genome-wide assessment of genetic diversity and population structure insights into admixture and introgression in Chinese indigenous cattle , 2018, BMC Genetics.

[17]  J. Thioulouse Multivariate Analysis of Ecological Data with ade4 , 2018 .

[18]  S. Dray,et al.  Supervised Multiblock Analysis in R with the ade4 Package , 2018 .

[19]  Daniel Falush,et al.  A tutorial on how not to over-interpret STRUCTURE and ADMIXTURE bar plots , 2018, Nature Communications.

[20]  Emmanuel Paradis,et al.  ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R , 2018, Bioinform..

[21]  G. Brem,et al.  Whole-genome SNP analysis elucidates the genetic structure of Russian cattle and its relationship with Eurasian taurine breeds , 2018, Genetics Selection Evolution.

[22]  Heebal Kim,et al.  Deciphering signature of selection affecting beef quality traits in Angus cattle , 2017, Genes & Genomics.

[23]  L. Verardo,et al.  Genetic diversity, population structure, and correlations between locally adapted zebu and taurine breeds in Brazil using SNP markers , 2017, Tropical Animal Health and Production.

[24]  R. Sleator,et al.  Ultra-low-density genotype panels for breed assignment of Angus and Hereford cattle. , 2017, Animal : an international journal of animal bioscience.

[25]  T. Iso-Touru,et al.  Genetic diversity and genomic signatures of selection among cattle breeds from Siberia, eastern and northern Europe. , 2016, Animal genetics.

[26]  C. Gondro,et al.  Local and global patterns of admixture and population structure in Iranian native cattle , 2016, BMC Genetics.

[27]  Steven G. Schroeder,et al.  Diversity and population-genetic properties of copy number variations and multicopy genes in cattle , 2016, DNA research : an international journal for rapid publication of reports on genes and genomes.

[28]  T. Jombart,et al.  Estimation and Tests of Hierarchical F-Statistics , 2015 .

[29]  Mathieu Gautier,et al.  WIDDE: a Web-Interfaced next generation database for genetic diversity exploration, with a first application in cattle , 2015, BMC Genomics.

[30]  J. Piedrafita,et al.  Genetic diversity and divergence among Spanish beef cattle breeds assessed by a bovine high-density SNP chip. , 2015, Journal of animal science.

[31]  G. Galimberti,et al.  Combined use of principal component analysis and random forests identify population-informative single nucleotide polymorphisms: application in cattle breeds. , 2015, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

[32]  Zhian N. Kamvar,et al.  Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality , 2015, Front. Genet..

[33]  K. S. Kim,et al.  Genome-wide genetic diversity, population structure and admixture analysis in African and Asian cattle breeds. , 2015, Animal : an international journal of animal bioscience.

[34]  E. van Marle-Köster,et al.  Genetic diversity and population structure among six cattle breeds in South Africa using a whole genome SNP panel , 2014, Front. Genet..

[35]  M. V. D. da Silva,et al.  Identification of selection signatures in livestock species , 2014, Genetics and molecular biology.

[36]  Zhian N. Kamvar,et al.  Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction , 2014, PeerJ.

[37]  A. Rogers How Population Growth Affects Linkage Disequilibrium , 2013, Genetics.

[38]  C. Dimauro,et al.  Use of the canonical discriminant analysis to select SNP markers for bovine breed assignment and traceability purposes. , 2013, Animal genetics.

[39]  P. Sullivan,et al.  Population structure, migration, and diversifying selection in the Netherlands , 2013, European Journal of Human Genetics.

[40]  Heebal Kim,et al.  Genetic diversity, population structure and relationships in indigenous cattle populations of Ethiopia and Korean Hanwoo breeds using SNP markers , 2013, Front. Genet..

[41]  Thibaut Jombart,et al.  adegenet 1.3-1: new tools for the analysis of genome-wide SNP data , 2011, Bioinform..

[42]  O. Hanotte,et al.  Time to Tap Africa's Livestock Genomes , 2010, Science.

[43]  H. Mannen,et al.  Genetic diversity and structure in Bos taurus and Bos indicus populations analyzed by SNP markers. , 2010, Animal science journal = Nihon chikusan Gakkaiho.

[44]  David R. Kelley,et al.  A whole-genome assembly of the domestic cow, Bos taurus , 2009, Genome Biology.

[45]  Timothy P. L. Smith,et al.  Development and Characterization of a High Density SNP Genotyping Assay for Cattle , 2009, PloS one.

[46]  Robert D Schnabel,et al.  Genome-Wide Survey of SNP Variation Uncovers the Genetic Structure of Cattle Breeds , 2009, Science.

[47]  K. Shianna,et al.  Long-range LD can confound genome scans in admixed populations. , 2008, American journal of human genetics.

[48]  T. Jombart adegenet: a R package for the multivariate analysis of genetic markers , 2008, Bioinform..

[49]  J. Aerts,et al.  An assessment of population structure in eight breeds of cattle using a whole genome SNP panel , 2008, BMC Genetics.

[50]  Anne-Béatrice Dufour,et al.  The ade4 Package: Implementing the Duality Diagram for Ecologists , 2007 .

[51]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[52]  G. Abecasis,et al.  A note on exact tests of Hardy-Weinberg equilibrium. , 2005, American journal of human genetics.

[53]  O. Hanotte,et al.  Weitzman's Approach and Conservation of Breed Diversity: an Application to African Cattle Breeds , 2003 .

[54]  J. Archer,et al.  Correlated responses in rate of maturation and mature size of cows and steers to divergent selection for yearling growth rate in Angus cattle , 1998 .

[55]  P. Parnell,et al.  Direct response to divergent selection for yearling growth rate in Angus cattle , 1997 .

[56]  E. Richardson,et al.  Correlated responses in calf body weight and size to divergent selection for yearling growth rate in Angus cattle , 1997 .

[57]  N Takezaki,et al.  Genetic distances and reconstruction of phylogenetic trees from microsatellite DNA. , 1996, Genetics.

[58]  M. Nei Molecular Evolutionary Genetics , 1987 .

[59]  B. Weir,et al.  ESTIMATING F‐STATISTICS FOR THE ANALYSIS OF POPULATION STRUCTURE , 1984, Evolution; international journal of organic evolution.

[60]  S. Speidel,et al.  Genetic diversity and population structure of American Red Angus cattle. , 2010, Journal of animal science.

[61]  M. Northridge,et al.  Who are we? , 2008, American journal of public health.

[62]  D. Perry,et al.  Correlated responses in body composition and fat partitioning to divergent selection for yearling growth rate in Angus cattle. , 2000 .

[63]  D. Notter,et al.  The importance of genetic diversity in livestock populations of the future. , 1999, Journal of animal science.