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4. A practical approach for minimising inbreeding and maximising genetic gain in dairy cattle

Author

Goddard Mike E, Bowman Phil J, and Haile-Mariam Mekonnen

Subjects
inbreeding, dairy cattle, bull selection methods, genetic merit, Animal culture, SF1-1100, Genetics, QH426-470
Abstract

Abstract A method that predicts the genetic composition and inbreeding (F) of the future dairy cow population using information on the current cow population, semen use and progeny test bulls is described. This is combined with information on genetic merit of bulls to compare bull selection methods that minimise F and maximise breeding value for profit (called APR in Australia). The genetic composition of the future cow population of Australian Holstein-Friesian (HF) and Jersey up to 6 years into the future was predicted. F in Australian HF and Jersey breeds is likely to increase by about 0.002 and 0.003 per year between 2002 and 2008, respectively. A comparison of bull selection methods showed that a method that selects the best bull from all available bulls for each current or future cow, based on its calf's APR minus F depression, is better than bull selection methods based on APR alone, APR adjusted for mean F of prospective progeny after random mating and mean APR adjusted for the relationship between the selected bulls. This method reduced F of prospective progeny by about a third to a half compared to the other methods when bulls are mated to current and future cows that will be available 5 to 6 years from now. The method also reduced the relationship between the bulls selected to nearly the same extent as the method that is aimed at maximising genetic gain adjusted for the relationship between bulls. The method achieves this because cows with different pedigree exist in the population and the method selects relatively unrelated bulls to mate to these different cows. Selecting the best bull for each current or future cow so that the calf's genetic merit minus F depression is maximised can slow the rate of increase in F in the population.

Published
2007
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5. Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals

Author

Bouwman, Aniek C., Daetwyler, Hans D., Chamberlain, Amanda J., Hurtado Ponce, Carla, Sargolzaei, Mehdi, Schenkel, Flavio S., Sahana, Goutam, Govignon-Gion, Armelle, Boitard, Simon, Dolezal, Marlies, Pausch, Hubert, Brøndum, Rasmus F., Bowman, Phil J., Thomsen, Bo, Guldbrandtsen, Bernt, Lund, Morgns S., Servin, Bertrand, Garrick, Dorian J., Reecy, James, Vilkki, Johanna, Bagnato, Alessandro, Wang, Min, Hoff, Jesse L., Schnabel, Robert D., Taylor, Jeremy F., Vinkhuyzen, Anna A. E., Panitz, Frank, Bendixen, Christian, Holm, Lars-Erik, Gredler, Birgit, Hozé, Chris, Boussaha, Mekki, Sanchez, Marie-Pierre, Rocha, Dominique, Capitan, Aurelien, Tribout, Thierry, Barbat, Anne, Croiseau, Pascal, Drögemüller, Cord, Jagannathan, Vidhya, Vander Jagt, Christy, Bieber, Anna, Purfield, Deidre C., Berry, Donagh P., Emmerling, Reiner, Götz, Kay-Uwe, Frischknecht, Mirjam, Russ, Ingolf, Sölkner, Johann, Van Tassel, Curtis P., Fries, Ruedi, Stothard, Paul, Veerkamp, Roel F., Boichard, Didier, Goddard, Mike E., Hayes, Ben J., Bouwman, Aniek C., Daetwyler, Hans D., Chamberlain, Amanda J., Hurtado Ponce, Carla, Sargolzaei, Mehdi, Schenkel, Flavio S., Sahana, Goutam, Govignon-Gion, Armelle, Boitard, Simon, Dolezal, Marlies, Pausch, Hubert, Brøndum, Rasmus F., Bowman, Phil J., Thomsen, Bo, Guldbrandtsen, Bernt, Lund, Morgns S., Servin, Bertrand, Garrick, Dorian J., Reecy, James, Vilkki, Johanna, Bagnato, Alessandro, Wang, Min, Hoff, Jesse L., Schnabel, Robert D., Taylor, Jeremy F., Vinkhuyzen, Anna A. E., Panitz, Frank, Bendixen, Christian, Holm, Lars-Erik, Gredler, Birgit, Hozé, Chris, Boussaha, Mekki, Sanchez, Marie-Pierre, Rocha, Dominique, Capitan, Aurelien, Tribout, Thierry, Barbat, Anne, Croiseau, Pascal, Drögemüller, Cord, Jagannathan, Vidhya, Vander Jagt, Christy, Bieber, Anna, Purfield, Deidre C., Berry, Donagh P., Emmerling, Reiner, Götz, Kay-Uwe, Frischknecht, Mirjam, Russ, Ingolf, Sölkner, Johann, Van Tassel, Curtis P., Fries, Ruedi, Stothard, Paul, Veerkamp, Roel F., Boichard, Didier, Goddard, Mike E., and Hayes, Ben J.

Abstract

Stature is affected by many polymorphisms of small effect in humans1. In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes2,3. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10−8) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP–seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.

Published
2018

8. Genomic prediction from whole genome sequence in livestock: the 1000 Bull Genomes Project

Author

Hayes, Benjamin John, MacLeod, I.M., Daetwyler, Hans D, Bowman, Phil J, Chamberlian, A.J., Vander Jagt, C.J., Capitan, Aurelien, Pausch, Hubert, Stothard, Paul, Liao, X., Schrooten, Chris, Mullaart, Erik, Fries, Ruedi, Guldbrandtsen, Bernt, Lund, Mogens Sando, Boichard, Didier, Veerkamp, Roel F, VanTassell, Curt P, Gredler, Birgit, Druet, Tom, Bagnato, Alessandro, Vilkki, Johanna, deKoning, D.J., Santus, Enrico, Goddard, Mike E, La Trobe University [Melbourne], Department of Environment and Primary Industries, Dairy Futures Cooperative Research Centre, University of Melbourne, Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Union Nationale des Coopératives Agricoles d'Elevage et d'Insémination Animale, Chair of Animal Breeding, Technische Universität München [München] (TUM), University of Alberta, Coöperatie Rundvee Verbetering (CRV), Aarhus University [Aarhus], Wageningen University and Research Centre [Wageningen] (WUR), United States Department of Agriculture, Qualitas AG, Unit of Animal Genomics, GIGA, Université de Liège, Università degli studi di Milano [Milano], Agrifood Research Finland, Swedish University of Agricultural Sciences (SLU), ANARB, ANR Apisgene Cartoseq, Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Union nationale des coopératives d’élevage et d’insémination animale (UNCEIA), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Wageningen University and Research [Wageningen] (WUR), and Università degli Studi di Milano [Milano] (UNIMI)

Subjects
Genomic prediction, séquençage du génome, bovin, sélection génomique, biological information, [SDV]Life Sciences [q-bio], whole genome sequence
Abstract

Advantages of using whole genome sequence data to predict genomic estimated breeding values (GEBV) include better persistence of accuracy of GEBV across generations and more accurate GEBV across breeds. The 1000 Bull Genomes Project provides a database of whole genome sequenced key ancestor bulls, for imputing sequence variant genotypes into reference sets for genomic prediction. Run 3.0 included 429 sequences, with 31.8 million variants detected. BayesRC, a new method for genomic prediction, addresses some challenges associated with using the sequence data, and takes advantage of biological information. In a dairy data set, predictions using BayesRC and imputed sequence data from 1000 Bull Genomes were 2% more accurate than with 800k data. We could demonstrate the method identified causal mutations in some cases. Further improvements will come from more accurate imputation of sequence variant genotypes and improved biological information

Published
2014

11. Bos taurus strain:dairy beef (cattle): 1000 Bull Genomes Run 2, Bovine Whole Genome Sequence

Author

Bouwman, A.C., Daetwyler, H.D., Chamberlain, Amanda J., Ponce, Carla Hurtado, Sargolzaei, Mehdi, Schenkel, Flavio S., Sahana, Goutam, Govignon-Gion, Armelle, Boitard, Simon, Dolezal, Marlies, Pausch, Hubert, Brøndum, Rasmus F., Bowman, Phil J., Thomsen, Bo, Guldbrandtsen, Bernt, Lund, Mogens S., Servin, Bertrand, Garrick, Dorian J., Reecy, James M., Vilkki, Johanna, Bagnato, Alessandro, Wang, Min, Hoff, Jesse L., Schnabel, Robert D., Taylor, Jeremy F., Vinkhuyzen, Anna A.E., Panitz, Frank, Bendixen, Christian, Holm, Lars-Erik, Gredler, Birgit, Hozé, Chris, Boussaha, Mekki, Sanchez, Marie Pierre, Rocha, Dominique, Capitan, Aurelien, Tribout, Thierry, Barbat, Anne, Croiseau, Pascal, Drögemüller, Cord, Jagannathan, Vidhya, Vander Jagt, Christy, Crowley, John J., Bieber, Anna, Purfield, Deirdre C., Berry, Donagh P., Emmerling, Reiner, Götz, Kay Uwe, Frischknecht, Mirjam, Russ, Ingolf, Sölkner, Johann, van Tassell, Curtis P., Fries, Ruedi, Stothard, Paul, Veerkamp, R.F., Boichard, Didier, Goddard, Mike E., Hayes, Ben J., Bouwman, A.C., Daetwyler, H.D., Chamberlain, Amanda J., Ponce, Carla Hurtado, Sargolzaei, Mehdi, Schenkel, Flavio S., Sahana, Goutam, Govignon-Gion, Armelle, Boitard, Simon, Dolezal, Marlies, Pausch, Hubert, Brøndum, Rasmus F., Bowman, Phil J., Thomsen, Bo, Guldbrandtsen, Bernt, Lund, Mogens S., Servin, Bertrand, Garrick, Dorian J., Reecy, James M., Vilkki, Johanna, Bagnato, Alessandro, Wang, Min, Hoff, Jesse L., Schnabel, Robert D., Taylor, Jeremy F., Vinkhuyzen, Anna A.E., Panitz, Frank, Bendixen, Christian, Holm, Lars-Erik, Gredler, Birgit, Hozé, Chris, Boussaha, Mekki, Sanchez, Marie Pierre, Rocha, Dominique, Capitan, Aurelien, Tribout, Thierry, Barbat, Anne, Croiseau, Pascal, Drögemüller, Cord, Jagannathan, Vidhya, Vander Jagt, Christy, Crowley, John J., Bieber, Anna, Purfield, Deirdre C., Berry, Donagh P., Emmerling, Reiner, Götz, Kay Uwe, Frischknecht, Mirjam, Russ, Ingolf, Sölkner, Johann, van Tassell, Curtis P., Fries, Ruedi, Stothard, Paul, Veerkamp, R.F., Boichard, Didier, Goddard, Mike E., and Hayes, Ben J.

Abstract

Whole genome sequence data (BAM format) of 234 bovine individuals aligned to UMD3.1. The aim of the study was to identify genetic variants (SNPs and indels) for downstream analysis such as imputation, GWAS, and detection of lethal recessives. Additional sequences for later 1000 bull genomes runs can be found at partners individual projects including PRJEB9343, PRJNA176557, PRJEB18113, PRNJA343262, PRJNA324822, PRJNA324270, PRJNA277147, PRJEB5462.

Published
2014

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