Discerning the traits evolving under neutral conditions from those traits evolving rapidly because of various selection pressures is a great challenge. We propose a new method, composite selection signals (CSS), which unifies the multiple pieces of selection evidence from the rank distribution of its diverse constituent tests. The extreme CSS scores capture highly differentiated loci and underlying common variants hauling excess haplotype homozygosity in the samples of a target population.

Since domestication, significant genetic improvement has been achieved for many traits of commercial importance in cattle, including adaptation, appearance and production. In response to such intense selection pressures, the bovine genome has undergone changes at the underlying regions of functional genetic variants, which are termed “selection signatures”. This article reviews 64 recent (2009–2015) investigations testing genomic diversity for departure from neutrality in worldwide cattle populations. In particular, we constructed a meta-assembly of 16,158 selection signatures for individual breeds and their archetype groups (European, African, Zebu and composite) from 56 genome-wide scans representing 70,743 animals of 90 pure and crossbred cattle breeds. Meta-selection-scores (MSS) were computed by combining published results at every given locus, within a sliding window span. MSS were adjusted for common samples across studies and were weighted for significance thresholds across and within studies. Published selection signatures show extensive coverage across the bovine genome, however, the meta-assembly provides a consensus profile of 263 genomic regions of which 141 were unique (113 were breed-specific) and 122 were shared across cattle archetypes. The most prominent peaks of MSS represent regions under selection across multiple populations and harboured genes of known major effects (coat color, polledness and muscle hypertrophy) and genes known to influence polygenic traits (stature, adaptation, feed efficiency, immunity, behaviour, reproduction, beef and dairy production). As the first meta-assembly of selection signatures, it offers novel insights about the hotspots of selective sweeps in the bovine genome, and this method could equally be applied to other species.

Understanding the evolution and molecular architecture of complex traits is important in domestic animals. Due to phenotypic selection, genomic regions develop unique patterns of genetic diversity called signatures of selection, which are challenging to detect especially for complex polygenic traits. In this study, we applied the composite selection signals (CSS) method to investigate evidence of positive selection in a complex polygenic trait by examining stature, in phenotypically diverse cattle comprising of 47 European and 8 African Bos taurus breeds, utilizing a panel of 38,033 SNPs genotyped on 1,106 animals. CSS were computed for phenotypic contrasts between multi-breed cohorts of cattle by classifying the breeds according to their documented wither height to detect the candidate regions under selection. Using the CSS method, clusters of signatures of selection were detected at 26 regions (nine in European and 17 in African cohorts) on 13 bovine autosomes. Using comparative mapping information on human height, 30 candidate genes mapped at 12 selection regions (on eight autosomes) could be linked to bovine stature diversity. Of these 12 candidate gene regions, three contained known genes (i.e., NCAPG-LCORL, FBP2-PTCH1 and PLAG1-CHCHD7) related to bovine stature, and nine were not previously described in cattle (five in European and four in African cohorts). Overall, this study demonstrates the utility of CSS, coupled with strategies of combining multi-breed datasets in the identification and discovery of genomic regions underlying complex traits. Characterization of multiple signatures of selection and their underlying candidate genes will elucidate the polygenic nature of stature across cattle breeds.

Dehorning is the process of physically removing horns to protect animals and humans from injury, but the process is costly, unpleasant, and faces increasing public scrutiny. Genetic selection for polled (hornless), which is genetically dominant to horned, is a long-term solution to eliminate the need for dehorning. However, due to the limited number of polled Australian Brahman bulls, the northern Australian beef cattle population remains predominantly horned. The potential to use gene editing to produce high-genetic-merit polled cattle was recently demonstrated. To further explore the concept, this study simulated introgression of the POLLED allele into a tropically adapted Australian beef cattle population via conventional breeding or gene editing (top 1% or 10% of seedstock bulls/year) for 3 polled mating schemes and compared results to baseline selection on genetic merit (Japan Ox selection index, $JapOx) alone, over the course of 20 years. The baseline scenario did not significantly decrease the 20-year HORNED allele frequency (80%), but resulted in one of the fastest rates of genetic gain ($8.00/year). Compared to the baseline, the conventional breeding scenarios where polled bulls were preferentially used for breeding, regardless of their genetic merit, significantly decreased the 20-year HORNED allele frequency (30%), but resulted in a significantly slower rate of genetic gain ($6.70/year, P ≤ 0.05). The mating scheme that required the exclusive use of homozygous polled bulls, resulted in the lowest 20-year HORNED allele frequency (8%), but this conventional breeding scenario resulted in the slowest rate of genetic gain ($5.50/year). The addition of gene editing the top 1% or 10% of seedstock bull calves/year to each conventional breeding scenario resulted in significantly faster rates of genetic gain (up to $8.10/year, P ≤ 0.05). Overall, our study demonstrates that, due to the limited number of polled Australian Brahman bulls, strong selection pressure on polled will be necessary to meaningfully increase the number of polled animals in this population. Moreover, these scenarios illustrate how gene editing could be a tool for accelerating the development of high-genetic-merit homozygous polled sires to mitigate the current trade-off of slower genetic gain associated with decreasing HORNED allele frequency in the Australian Brahman population.

Thoroughbred horse racing is a global sport with major hubs in Europe, North America, Australasia and Japan. Regional preferences for certain traits have resulted in phenotypic variation that may result from adaptation to the local racing ecosystem. Here, we test the hypothesis that genes selected for regional phenotypic variation may be identified by analysis of selection signatures in pan-genomic SNP genotype data. Comparing Australian to non-Australian Thoroughbred horses (n = 99), the most highly differentiated loci in a composite selection signals (CSS) analysis were on ECA6 (34.75–34.85 Mb), ECA14 (33.2–33.52 Mb and 35.52–36.94 Mb) and ECA16 (24.28–26.52 Mb) in regions containing candidate genes for exercise adaptations including cardiac function (ARHGAP26, HBEGF, SRA1), synapse development and locomotion (APBB3, ATXN7, CLSTN3), stress response (NR3C1) and the skeletal muscle response to exercise (ARHGAP26, NDUFA2). In a genome-wide association study for field-measured speed in two-year-olds (n = 179) SNPs contained within the single association peak (33.2–35.6 Mb) overlapped with the ECA14 CSS signals and spanned a protocadherin gene cluster. Association tests using higher density SNP genotypes across the ECA14 locus identified a SNP within the PCDHGC5 gene associated with elite racing performance (n = 922). These results indicate that there may be differential selection for racing performance under racing and management conditions that are specific to certain geographic racing regions. In Australia breeders have principally selected horses for favourable genetic variants at loci containing genes that modulate behaviour, locomotion and skeletal muscle physiology that together appear to be contributing to early two-year-old speed.