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The 1000 Bull Genomes Project aims to provide, for the bovine research community, a large database for imputation of genetic variants for genomic prediction and genome wide association studies in all cattle breeds. The project aims to develop a resource to allow project partners to impute full genome sequence in bulls and cows that have been genotyped with SNP arrays. This could be used, for example, for improving the accuracy of genomic prediction, as well as in genome wide association studies interested in the identification of causal mutations., The 1000 Bull Genomes Project aims to provide, for the bovine research community, a large database for imputation of genetic variants for genomic prediction and genome wide association studies in all cattle breeds. The project aims to develop a resource to allow project partners to impute full genome sequence in bulls and cows that have been genotyped with SNP arrays. This could be used, for example, for improving the accuracy of genomic prediction, as well as in genome wide association studies interested in the identification of causal mutations.

Background: Genetic variation in both the composition and distribution of fat and muscle in the body is important to human health as well as the healthiness and value of meat from cattle and sheep. Here we use detailed phenotyping and a multi-trait approach to identify genes explaining variation in body composition traits. Results: A multi-trait genome wide association analysis of 56 carcass composition traits measured on 10,613 sheep with imputed and real genotypes on 510,174 SNPs was performed. We clustered 71 significant SNPs into five groups based on their pleiotropic effects across the 56 traits. Among these 71 significant SNPs, one group of 11 SNPs affected the fatty acid profile of the muscle and were close to 8 genes involved in fatty acid or triglyceride synthesis. Another group of 23 SNPs had an effect on mature size, based on their pattern of effects across traits, but the genes near this group of SNPs did not share any obvious function. Many of the likely candidate genes near SNPs with significant pleiotropic effects on the 56 traits are involved in intra-cellular signalling pathways. Among the significant SNPs were some with a convincing candidate gene due to the function of the gene (e.g. glycogen synthase affecting glycogen concentration) or because the same gene was associated with similar traits in other species. Conclusions: Using a multi-trait analysis increased the power to detect associations between SNP and body composition traits compared with the single trait analyses. Detailed phenotypic information helped to identify a convincing candidate in some cases as did information from other species.

Previous association studies revealed several single nucleotide polymorphisms (SNPs) that explained the observed phenotypic variation for meat tenderness and long-chain omega-3 polyunsaturated fatty acid (PUFA) content of Australian lamb. To confirm the validity of these associated SNPs at predicting meat tenderness and omega-3 PUFA content, an independent validation study was designed. The OvineSNP50 genotypes of these animals were used to impute the 192 SNP Meat Quality Research (MQR) panel genotypes on nearly 6200 animals from the Cooperative Research Centre for Sheep Industry Innovation Information Nucleus Flock and Sheep Genomics Falkiner Memorial Field Station flock. Association analysis revealed numerous SNP from the 192 SNP MQR panel that were associated with carcass quality - fat depth at the C-site and eye muscle depth; shear force at day 1 and day 5 after slaughter (SF1 and SF5); and omega-3 PUFA content at P < 0.01. However, 1 SNP was independently validated for SF5 (i.e. CAST_101781475). The magnitude of the effect of each significant SNP and the relative allele frequencies across Merino-, Maternal- and Terminal-sired progeny was determined. The independently validated SNP for SF5 and the associated SNP with omega-3 PUFA content will accelerate efforts to improve these phenotypic traits in Australian lamb.

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.

Whole genome association studies in humans have shown a strong relationship between omega-3 levels in plasma and single nucleotide polymorphisms (SNP) located close to genes whose protein products are involved in the biosynthesis of long-chain omega-3 fatty acids. In sheep and other livestock species, the calpain/calpastatin system is the principal influence on natural variation in meat tenderness between animals. Using targeted next generation sequencing, we sequenced the fatty acid desaturase locus (FADS1/2/3), ELOVL2 and SLC26A10 and the calpain/calpastatin (CAPN1/2/3 and CAST) gene loci of 35 industry sires from the Australian flock. A total of 753 SNP were identified and 182 of these SNP were selected for incorporation onto a research SNP panel that represented the genetic variation across the nine genes. A total of 1252 animals were genotyped from the Australian Sheep CRC Information Nucleus Flock for these SNP and the genomic association was calculated for omega-3 fatty acid content and objective meat tenderness in lamb. Six SNP within CAST and CAPN2 showed association with shear force at Day 5 post-mortem at a significance level of P ≤ 0.01. When these were fitted simultaneously in a mixed-model analysis with fixed effects and covariates, three SNP remained significant. These SNP each had an unfavourable effect on shear force of between 1.1 and 1.8 N, with a combined effect of 4.1 N. The frequency of the favourable alleles in the progeny measured indicates that these SNP hold good potential for improving the management of meat tenderness across Merino, Border Leicester and Terminal sire types. No SNP within the FADS1/2/3, ELOVL2 and SLC26A10 gene regions were associated with lamb muscle omega-3 levels. This indicates that genetic variation in the long-chain omega-3 biosynthesis pathway genes analysed here may not be important for omega-3 content in lamb within the Information Nucleus Flock population.

Dit proefschrift onderzoekt het gebruik van moleculaire merkers voor genetische evaluatie van populaties. Moleculaire merkers kunnen worden gebruikt om de nauwkeurigheid van geschatte fokwaardes te verhogen. In het verleden was men gericht op het opsporen van een beperkt aantal zogenaamde QTL, delen van het genoom, die direct in verband staan met een kenmerk. Het doel was om deze QTL te benutten in fokprogramma’s met behulp van merker-ondersteunde selectie. Met het beschikbaar komen van grote hoeveelheden SNP-merkers kan gebruik worden gemaakt van een methode die gericht is op het gehele genoom, en bekend staat als “genome-wide evaluation” (GWE). Dit proefschrift presenteert resultaten van zowel QTL-detectie als GWE. Deterministische voorspellingen van nauwkeurigheid worden gepresenteerd en getest, en de invloed van de genetische structuur op nauwkeurigheid wordt onderzocht. Een methode wordt gepresenteerd voor het berekenen van missende genotypes, met als doel merkerdichtheid en nauwkeurigheid van GWE te verhogen. Daarnaast worden praktische toepassing van GWE en manieren om ontbrekende genetische variatie te kwantificeren bediscussieerd.

Background - The prediction of the genetic disease risk of an individual is a powerful public health tool. While predicting risk has been successful in diseases which follow simple Mendelian inheritance, it has proven challenging in complex diseases for which a large number of loci contribute to the genetic variance. The large numbers of single nucleotide polymorphisms now available provide new opportunities for predicting genetic risk of complex diseases with high accuracy. Methodology/Principal Findings - We have derived simple deterministic formulae to predict the accuracy of predicted genetic risk from population or case control studies using a genome-wide approach and assuming a dichotomous disease phenotype with an underlying continuous liability. We show that the prediction equations are special cases of the more general problem of predicting the accuracy of estimates of genetic values of a continuous phenotype. Our predictive equations are responsive to all parameters that affect accuracy and they are independent of allele frequency and effect distributions. Deterministic prediction errors when tested by simulation were generally small. The common link among the expressions for accuracy is that they are best summarized as the product of the ratio of number of phenotypic records per number of risk loci and the observed heritability. Conclusions/Significance - This study advances the understanding of the relative power of case control and population studies of disease. The predictions represent an upper bound of accuracy which may be achievable with improved effect estimation methods. The formulae derived will help researchers determine an appropriate sample size to attain a certain accuracy when predicting genetic risk