Genetics of growth, feed intake, and milk yield in Holstein cattle

International audienc

1000 Bull Genomes Consortium Project

Genomic selection, where selection decisions are based on estimates of breeding value from genome wide-marker effects, has enormous potential to improve genetic gain in dairy and beef cattle. Although successful in dairy cattle, some major challenges remain 1) only a proportion of the genetic variance is captured, particularly for some traits 2) marker effects are rarely consistent across breeds, 3) accuracy of genomic predictions decays rapidly over time. Using full genome sequences rather than DNA markers in genomic selection could address these challenges. However, sequencing all individuals in the very large resource populations required to estimate the typically small effects of mutations on target traits would be prohibitively expensive. An alternative is to sequence key ancestors contributing most of the genetic material of the current population, and to use this reference for imputation of sequence from SNP chip data. The reference set must still be large, in order to capture for example, rare variants which are likely to explain some of the variation in our target traits. Recognising the need for a comprehensive “reference set” of key ancestors by many groups undertaking cattle research and cattle breeding programs, we have initiated the 1000 bull genomes project. The project will assemble whole genome sequences of cattle from institutions around the world, to provide an extended data base for imputation of genetic variants. This will enable the bovine genomics community to impute full genome sequence from SNP genotypes, and then use this data for genomic selection, and rapid discovery of causal mutations. Some preliminary results from the variant detection pipeline will be reported

1000 Bull Genomes - Toward genomic Selectionf from whole genome sequence Data in Dairy and Beef Cattle

Genomic prediction of breeding values is now used as the basis for selection of dairy cattle, and in some cases beef cattle, in a number of countries. When genomic prediction was introduced most of the information was to thought to be derived from linkage disequilibrium between markers and causative variants. It has become clear that much of the predictive power, based on 50,000 DNA markers, in fact derives from prediction of the effect of large chromosome segments that segregate within fairly closely related animals. This has lead to problems with across breed prediction, rapid decay of predictive power over generations and insufficient accuracy in some situations. Using full genome sequence data in genomic prediction should overcome these problems. If linkage disequilibrium between SNP on standard arrays and causative mutations affecting the quantitative trait is incomplete, accuracy of prediction should be improved as a result of including the actual causative mutations affecting the trait of interest in the data set. Secondly, persistence of accuracy of genomic predictions across generations will be improved with full sequence data, as the genomic predictions no longer depend on associations between SNP and causative mutations which currently erode quite rapidly with recombination. Thirdly, if genomic predictions are made across breeds, using full sequence data is likely to be particularly advantageous, as there is no longer a need to rely on marker- associations which may not persist across breeds. However, the cost of sequencing is such that the very large numbers of animals required for genomic prediction will not be sequenced An alternative strategy is to sequence key ancestors of the population, then impute the genotypes for the sequence variants into much larger reference sets with phenotypes and SNP panel genotypes. The 1000 Bull Genomes Project aims at building such a resource of sequenced key ancestor bulls for the bovine research community. The most recent run of the project included 238 full genome sequences of 130 Holstein, 43 Fleckvieh, 48 Angus and 15 Jersey bulls, sequenced at an average of 10.5 fold coverage. There were 25.2 million filtered sequence variants detected in the sequences, including 23.5 million SNP and 1.7 million insertion-deletions. Agreement of sequence genotypes to genotypes from an 800K SNP array in the sequenced Holstein bulls, where there was most data, was excellent at 98.8%. This increased to 99.7% when the genotypes were imputed based on all sequences. Concordance was slightly lower in other breeds. This project will provide an excellent opportunity to identify the most important causative variants, leading to greater understanding of biology underlying quantitative traits. Examples are given of genomic predictions for fertility, health and production traits using imputed sequence data

1000 Bull Genomes Consortium Project

Genomic selection, where selection decisions are based on estimates of breeding value from genome wide-marker effects, has enormous potential to improve genetic gain in dairy and beef cattle. Although successful in dairy cattle, some major challenges remain 1) only a proportion of the genetic variance is captured, particularly for some traits 2) marker effects are rarely consistent across breeds, 3) accuracy of genomic predictions decays rapidly over time. Using full genome sequences rather than DNA markers in genomic selection could address these challenges. However, sequencing all individuals in the very large resource populations required to estimate the typically small effects of mutations on target traits would be prohibitively expensive. An alternative is to sequence key ancestors contributing most of the genetic material of the current population, and to use this reference for imputation of sequence from SNP chip data. The reference set must still be large, in order to capture for example, rare variants which are likely to explain some of the variation in our target traits. Recognising the need for a comprehensive “reference set” of key ancestors by many groups undertaking cattle research and cattle breeding programs, we have initiated the 1000 bull genomes project. The project will assemble whole genome sequences of cattle from institutions around the world, to provide an extended data base for imputation of genetic variants. This will enable the bovine genomics community to impute full genome sequence from SNP genotypes, and then use this data for genomic selection, and rapid discovery of causal mutations. Some preliminary results from the variant detection pipeline will be reported

Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle

The 1000 bull genomes project supports the goal of accelerating the rates of genetic gain in domestic cattle while at the same time considering animal health and welfare by providing the annotated sequence variants and genotypes of key ancestor bulls. In the first phase of the 1000 bull genomes project, we sequenced the whole genomes of 234 cattle to an average of 8.3-fold coverage. This sequencing includes data for 129 individuals from the global Holstein-Friesian population, 43 individuals from the Fleckvieh breed and 15 individuals from the Jersey breed. We identified a total of 28.3 million variants, with an average of 1.44 heterozygous sites per kilobase for each individual. We demonstrate the use of this database in identifying a recessive mutation underlying embryonic death and a dominant mutation underlying lethal chrondrodysplasia. We also performed genome-wide association studies for milk production and curly coat, using imputed sequence variants, and identified variants associated with these traits in cattle

Agroecological transformation for sustainable food systems : Insight on France-CGIAR research

This 26th dossier d’Agropolis is devoted to research and partnerships in agroecology. The French Commission for International Agricultural Research (CRAI) and Agropolis International, on behalf of CIRAD, INRAE and IRD and in partnership with CGIAR, has produced this new issue in the ‘Les dossiers d’Agropolis international’ series devoted to agroecology. This publication has been produced within the framework of the Action Plan signed by CGIAR and the French government on February 4th 2021 to strengthen French collaboration with CGIAR, where agroecology is highlighted as one of the three key priorities (alongside climate change, nutrition and food systems)