The genetics of reproduction is poorly understood because the heritabilities of traits currently recorded are low. To elucidate the genetics underlying reproduction in beef cattle, we performed a genome-wide association study using the bovine SNP50 chip in 2 tropically adapted beef cattle breeds, Brahman and Tropical Composite. Here we present the results for 3 female reproduction traits: 1) age at puberty, defined as age in days at first observed corpus luteum (CL) after frequent ovarian ultrasound scans (AGECL); 2) the postpartum anestrous interval, measured as the number of days from calving to first ovulation postpartum (first rebreeding interval, PPAI); and 3) the occurrence of the first postpartum ovulation before weaning in the first rebreeding period (PW), defined from PPAI. In addition, correlated traits such as BW, height, serum IGF1 concentration, condition score, and fatness were also examined. In the Brahman and Tropical Composite cattle, 169 [false positive rate (FPR) = 0.262] and 84 (FPR = 0.581) SNP, respectively, were significant (P < 0.001) for AGECL. In Brahman, 41% of these significant markers mapped to a single chromosomal region on BTA14. In Tropical Composites, 16% of these significant markers were located on BTA5. For PPAI, 66 (FPR = 0.67) and 113 (FPR = 0.432) SNP were significant (P < 0.001) in Brahman and Tropical Composite, respectively, whereas for PW, 68 (FPR = 0.64) and 113 (FPR = 0.432) SNP were significant (P < 0.01). In Tropical Composites, the largest concentration of PPAI markers were located on BTA5 [19% (PPAI) and 23% (PW)], and BTA16 [17% (PPAI) and 18% (PW)]. In Brahman cattle, the largest concentration of markers for postpartum anestrus was located on BTA3 (14% for PPAI and PW) and BTA14 (17% PPAI). Very few of the significant markers for female reproduction traits for the Brahman and Tropical Composite breeds were located in the same chromosomal regions. However, fatness and BW traits as well as serum IGF1 concentration were found to be associated with similar genome regions within and between breeds. Clusters of SNP associated with multiple traits were located on BTA14 in Brahman and BTA5 in Tropical Composites.

Large scale whole genome scans generate massive amounts of genotype data. It is essential to check genotype integrity and identify genotype errors prior to association analysis. Departure from Hardy-Weinberg Equilibrium has been adopted as one of the main methods to identify genotype errors. However population stratification also causes departure from Hardy-Weinberg Equilibrium, which is a disadvantage of this approach. This study used 2 sets of SNP genotypes to show that after basic editing using Call Rate and minor allele frequency, up to 13% of SNPs departed from Hardy-Weinberg Equilibrium (HWD) and about one third of these HWD SNPs could be falsely identified as genotype errors, were attributable to population subdivision (eg herd of origin, cohort) for one dataset and corresponding numbers for the second dataset are 21% and 16%, respectively. This approach can avoid improper culling of a considerable proportion of SNPs.

The Suppressor of Cytokine Signalling-2 (SOCS2) is the main negative regulator of somatic growth through the mediation of growth hormone signalling (GH/IGF-1). Knock-out and naturally mutant mice have high growth phenotypes. We have mapped the porcine SOCS2 gene to chromosome 5q, located closely to a reported QTL for food conversion ratio (Lee et al., 2003). Here we report five single nucleotide polymorphisms identified by sequencing of the promoter region and exon 1. One PCR-RFLP assay was designed for genotyping the polymorphism at position 1667(A/G). Association analyses were performed in an Australian mapping resource pedigree (PRDC-US43) for a number of traits (feed conversion ratio, backfat, IGF-1 level and growth traits) and showed significant effects on average daily gain on test (ADG2) (p<0.01) and marginal association with feed conversion ratio (FCR) (p<0.08).

Whole genome association studies have been increasingly used for QTL discovery. Analyses can performed using single marker (for example, single-nucleotide polymorphism, SNP) regression, but have also evolved to multiple marker (SNPs) regression to facilitate genomic selection. A major area of importance to the Northern Australian beef industry is female reproductive rate; specifically the number of calves produced over the lifetime of breeding females. An important component of female reproductive rate is age at puberty of heifers. Reduction of age at puberty of heifers can increase calving rates (Taylor and Rudder 1986). This study compared the two types of methods for estimating SNP effects for age at puberty.

We use publicly available methods to impute missing genotypes, infer haplotypes and partition haplotypes into blocks for large numbers of single nucleotide polymorphic data on two sections of chromosomes. Haplotype trend regression was used to associate these haplotype blocks with a continuously distributed trait. A number of significant regions of chromosomes, that were not found when tested with single-marker tests, were identified. This study demonstrated a feasible framework to fine-mapping QTL using haplotypes of SNP markers.

Background: The apparent effect of a single nucleotide polymorphism (SNP) on phenotype depends on the linkage disequilibrium (LD) between the SNP and a quantitative trait locus (QTL). However, the phase of LD between a SNP and a QTL may differ between 'Bos indicus' and 'Bos taurus' because they diverged at least one hundred thousand years ago. Here, we test the hypothesis that the apparent effect of a SNP on a quantitative trait depends on whether the SNP allele is inherited from a 'Bos taurus' or 'Bos indicus' ancestor. Methods: Phenotype data on one or more traits and SNP genotype data for 10 181 cattle from 'Bos taurus', 'Bos indicus' and composite breeds were used. All animals had genotypes for 729 068 SNPs (real or imputed). Chromosome segments were classified as originating from B. 'indicus' or B. 'taurus' on the basis of the haplotype of SNP alleles they contained. Consequently, SNP alleles were classified according to their sub-species origin. Three models were used for the association study: (1) conventional GWAS (genome-wide association study), fitting a single SNP effect regardless of subspecies origin, (2) interaction GWAS, fitting an interaction between SNP and subspecies-origin, and (3) best variable GWAS, fitting the most significant combination of SNP and sub-species origin. Results: Fitting an interaction between SNP and subspecies origin resulted in more significant SNPs (i.e. more power) than a conventional GWAS. Thus, the effect of a SNP depends on the subspecies that the allele originates from. Also, most QTL segregated in only one subspecies, suggesting that many mutations that affect the traits studied occurred after divergence of the subspecies or the mutation became fixed or was lost in one of the subspecies. Conclusions: The results imply that GWAS and genomic selection could gain power by distinguishing SNP alleles based on their subspecies origin, and that only few QTL segregate in both B. 'indicus' and B. 'taurus' cattle. Thus, the QTL that segregate in current populations likely resulted from mutations that occurred in one of the subspecies and can have both positive and negative effects on the traits. There was no evidence that selection has increased the frequency of alleles that increase body weight.

This report summarizes analyses at AGBU and covers two areas. The first area is the supplementary analyses for APL1756 and US43 animals on chromosome 10, as a result of additional genotyping for two APL1756 sire families and re-scoring of some genotypes. The second area reports the analysis of chromosome 4 for US43 animals and of chromosome 9 for APL1756 animals.

Feed efficiency and growth are the most important traits in pig production, and very few genetic markers have been reported to be associated with feed efficiency. The suppressor of cytokine signalling-2 (encoded by SOCS2) is the main negative regulator of somatic growth, and the knockout of SOCS2 and naturally mutant mice have high-growth phenotypes. Porcine SOCS2 was selected as a primary positional candidate for feed efficiency, because it is located on chromosome 5q, in the vicinity of a Quantitative Trait Locus (QTL) region for food conversion ratio in pigs. Here, we report five single nucleotide polymorphisms identified by sequencing of the promoter region and exon 1. One PCR-RFLP assay was designed for genotyping the polymorphism c.1667A > G (GenBank Accession No AY312266). Association analyses were performed in an Australian mapping resource pedigree population (PRDC-US43) for food conversion ratio, backfat, IGF1 level and growth traits and showed significant effects on average daily gain on test (ADG2) (P < 0.01) and marginal association with food conversion ratio (FCR) (P < 0.08).

One of the objectives of this project is to identify genetic markers for major gene that accounts for a significant proportion of the variation in parasite resistance in sheep. This report summarizes data analyses undertaken by AGBU, describing phenotypic and genotypic data, linkage map construction, overview of QTL mapping methods, QTL results and general discussions.

The usefulness of genomic selection was assessed for female reproduction in tropically adapted breeds in northern Australia. Records from experimental populations of Brahman (996) and Tropical Composite (1097) cattle that had had six calving opportunities were used to derive genomic predictions for several measures of female fertility. These measures included age at first corpus luteum (AGECL), at first calving and subsequent postpartum anoestrous interval and measures of early and lifetime numbers of calves born or weaned. In a second population, data on pregnancy and following status (anoestrous or pregnancy) were collected from 27 commercial herds from northern Australia to validate genomic predictions. Cows were genotyped with a variety of single nucleotide polymorphism (SNP) panels and, where necessary, genotypes imputed to the highest density (729 068 SNPs). Genetic parameters of subsets of the complete data were estimated. These subsets were used to validate genomic predictions using genomic best linear unbiased prediction using both univariate cross-validation and bivariate analyses. Estimated heritability ranged from 0.56 for AGECL to 0.03 for lifetime average calving rate in the experimental cows, and from 0.09 to 0.25 for early life reproduction traits in the commercial cows. Accuracies of predictions were generally low, reflecting the limited number of data in the experimental populations. For AGECL and postpartum anoestrous interval, the highest accuracy was 0.35 for experimental Brahman cows using five-fold univariate cross-validation. Greater genetic complexity in the Tropical Composite cows resulted in the corresponding accuracy of 0.23 for AGECL. Similar level of accuracies (from univariate and bivariate analyses) were found for some of the early measures of female reproduction in commercial cows, indicating that there is potential for genomic selection but it is limited by the number of animals with phenotypes.