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Genetic progress depends on accurate knowledge of the genetic composition of a population or herd including level of inbreeding and parentage. However, in many circumstances, such as at an individual property level, the relationships between animals may be unknown, or at best, only partly known. In this study, we used DNA from 938 animals and genotypes from ~54 000 single nucleotide polymorphisms (SNP) to determine the genetic structure of a stud from Central Queensland. Animals on the study were bred using multi-sire mating in mobs of composite tropically adapted cattle of the Senepol, Belmont and Bonsmara breeds. Following genotyping using an array of 54 000 SNP, we were able to separate animals into breed groups using principal components and show that ~400 SNP were sufficient to separate animals into stable groups if the sample was genetically diverse. However, precise principal component values were only achieved when a few thousand SNP were used. We characterised the pedigree relationships between individuals using a genome relationship matrix. At least 3000 SNP were required to calculate accurate relationship coefficients between individuals. Around 19% of paired comparisons between animals showed similarity equivalent to sharing a great-grandparent or 1/64 shared ancestry. Approximately 8% of the individuals showed more than 10% inbreeding. To demonstrate the utility of calculating the relationship coefficients, we counted the tick burden on each animal at more than one time and then calculated the heritability of tick burden of h2 = 0.46 (±0.08). There was no significant genetic difference in tick burden between Belmont and Bonsmara cattle compared with Senepol on this property once a genetic relationship matrix was included to account for co-ancestry of individuals.

The genetics of heifer performance in tropical ‘wet’ and ‘dry’ seasons, and relationships with steer performance, were studied in Brahman (BRAH) and Tropical Composite (TCOMP) (50% Bos indicus, African Sanga or other tropically adapted Bos taurus; 50% non-tropically adapted Bos taurus) cattle of northern Australia. Data were from 2159 heifers (1027 BRAH, 1132 TCOMP), representing 54 BRAH and 51 TCOMP sires. Heifers were assessed after post-weaning ‘wet’ (ENDWET) and ‘dry’ (ENDDRY) seasons. Steers were assessed post-weaning, at feedlot entry, over a 70-day feed test, and after ∼120-day finishing. Measures studied in both heifers and steers were liveweight (LWT), scanned rump fat, rib fat and M. longissimus area (SEMA), body condition score (CS), hip height (HH), serum insulin-like growth factor-I concentration (IGF-I), and average daily gains (ADG). Additional steer measures were scanned intra-muscular fat %, flight time, and daily (DFI) and residual feed intake (RFI). Uni- and bivariate analyses were conducted for combined genotypes and for individual genotypes. Genotype means were predicted for a subset of data involving 34 BRAH and 26 TCOMP sires. A meta-analysis of genetic correlation estimates examined how these were related to the difference between measurement environments for specific traits. There were genotype differences at the level of means, variances and genetic correlations. BRAH heifers were significantly (P < 0.05) faster-growing in the ‘wet’ season, slower-growing in the ‘dry’ season, lighter at ENDDRY, and taller and fatter with greater CS and IGF-I at both ENDWET and ENDDRY. Heritabilities were generally in the 20 to 60% range for both genotypes. Phenotypic and genetic variances, and genetic correlations, were commonly lower for BRAH. Differences were often explained by the long period of tropical adaptation of B. indicus. Genetic correlations were high between corresponding measures at ENDWET and ENDDRY, positive between fat and muscle measures in TCOMP but negative in BRAH (mean of 13 estimates 0.50 and –0.19, respectively), and approximately zero between steer feedlot ADG and heifer ADG in BRAH. Numerous genetic correlations between heifers and steers differed substantially from unity, especially in BRAH, suggesting there may be scope to select differently in the sexes where that would aid the differing roles of heifers and steers in production. Genetic correlations declined as measurement environments became more different, the rates of decline (environment sensitivity) sometimes differing with genotype. Similar measures (LWT, HH and ADG; IGF-I at ENDWET in TCOMP) were genetically correlated with steer DFI in heifers as in steers. Heifer SEMA was genetically correlated with steer feedlot RFI in BRAH (0.75 ± 0.27 at ENDWET, 0.66 ± 0.24 at ENDDRY). Selection to reduce steer RFI would reduce SEMA in BRAH heifers but otherwise have only small effects on heifers before their first joining.

The imprints of domestication and breed development on the genomes of livestock likely differ from those of companion animals. A deep draft sequence assembly of shotgun reads from a single Hereford female and comparative sequences sampled from six additional breeds were used to develop probes to interrogate 37,470 single-nucleotide polymorphisms (SNPs) in 497 cattle from 19 geographically and biologically diverse breeds. These data show that cattle have undergone a rapid recent decrease in effective population size from a very large ancestral population, possibly due to bottlenecks associated with domestication, selection, and breed formation. Domestication and artificial selection appear to have left detectable signatures of selection within the cattle genome, yet the current levels of diversity within breeds are at least as great as exists within humans.