Is neutral genetic diversity related to quantitative variation in semen traits in bulls?

Conservation decisions based on neutral genetic diversity have been observed to promote retention of useful quantitative variation in biological populations. An experiment was undertaken to determine the association between microsatellite marker polymorphisms and phenotypic variation in semen production and cryosurvival traits in bulls. Thirty-five ejaculates were collected from ten bulls of two breeds and evaluated before and after cryopreservation for several semen traits. The bulls were also genotyped using a set of sixteen bovine-specific microsatellite marker loci. Fixation indices (FST ), heterozygosity and Nei's genetic distance measures were computed from allele frequency data for each of the bulls. Molecular and phenotypic data were used to compute tri-distance matrices for the ten bulls and correlated using Mantel's test in GenAIEx 6.5. The study revealed extensive heterogeneity in semen traits, heterozygosity and FST values among the bulls. Large pairwise phenotypic and genetic distances were also observed. Correlation between pairwise genetic distances and phenotypic distances was significant and highly positive for sperm viability (r = .61, p < .001) and moderately positive for sperm motility (r = .40-42, p < .05) variables. For sperm morphology, ejaculate volume and sperm concentration, correlation with genetic distances was positive, low and not significantly different from zero (p > .05). A tendency for a triangular-shaped relationship between genetic and phenotypic distances for post-thaw motility and viability traits was also observed. Accordingly, association with neutral genetic diversity was absent for semen production traits and moderate to highly positive for sperm cryosurvival traits. Given these findings, conservation decisions based on neutral genetic diversity may capture variation in some adaptive traits, but not others.

Evaluation of the International Society for Animal Genetics bovine single nucleotide polymorphism parentage panel in South African Bonsmara and Drakensberger cattle.

A panel of 200 single nucleotide polymorphisms (SNPs) have been recommended by the International Society for Animal Genetics (ISAG) for use in parentage verification of cattle. While the SNPs included on the ISAG panel are segregating in European Bos taurus and Bos indicus breeds, their applicability in South African (SA) Sanga cattle has never been evaluated. This study, therefore, assessed the usefulness of the ISAG panel in SA Bonsmara (BON) and Drakensberger (DRB) cattle. Genotypes of 185 ISAG SNPs from 64 BON and 97 DRB sire-offspring pairs were available, all of which were validated with 119,375 SNPs. Of the 185 ISAG SNPs, 14 and 18 in the BON and DRB, respectively (9 in common to both breeds), were either monomorphic, exhibited at least one discordance between validated sire-offspring pairs, or had poor call rate or clustering issue. The mean minor allele frequency of the 185 ISAG SNPs was 0.331 in the BON and 0.359 in the DRB. The combined probability of parentage exclusion (PE) was the same (99.46%) for both breeds, while the probability of identity varied from 1.61 × 10-48 (BON) to 1.11 × 10-54 (DRB). Fifteen (23.4%) and 32 (33%) of the already validated sire-offspring pairs for the BON and DRB, respectively, were determined by the ISAG panel to be false-negatives based on a threshold of having at least two discordant SNPs. In comparison to sire discovery using the 119,375 SNPs, sire discovery using only the ISAG panel identified correctly 44 (out of 64 identified using the 119,375 SNPs) unique sire-offspring BON pairs and 62 (out of 97 identified using the 119,375 SNPs) unique sire-offspring DRB when all sires were masked. Five BON and three DRB offspring had > 1 sire nominated. This study demonstrated that the use of the ISAG panel may result in incorrect exclusions and multiple candidate sires for a given animal. Selection of more informative SNPs is, therefore, necessary in the pursuit of a low-cost and effective SNP panel for indigenous cattle breeds in SA.

Whole genome scan reveals the genetic signature of African Ankole cattle breed and potential for higher quality beef.

BACKGROUND: Africa is home to numerous cattle breeds whose diversity has been shaped by subtle combinations of human and natural selection. African Sanga cattle are an intermediate type of cattle resulting from interbreeding between Bos taurus and Bos indicus subspecies. Recently, research has asserted the potential of Sanga breeds for commercial beef production with better meat quality as compared to Bos indicus breeds. Here, we identified meat quality related gene regions that are positively selected in Ankole (Sanga) cattle breeds as compared to indicus (Boran, Ogaden, and Kenana) breeds using cross-population (XP-EHH and XP-CLR) statistical methods. RESULTS: We identified 238 (XP-EHH) and 213 (XP-CLR) positively selected genes, of which 97 were detected from both statistics. Among the genes obtained, we primarily reported those involved in different biological process and pathways associated with meat quality traits. Genes (CAPZB, COL9A2, PDGFRA, MAP3K5, ZNF410, and PKM2) involved in muscle structure and metabolism affect meat tenderness. Genes (PLA2G2A, PARK2, ZNF410, MAP2K3, PLCD3, PLCD1, and ROCK1) related to intramuscular fat (IMF) are involved in adipose metabolism and adipogenesis. MB and SLC48A1 affect meat color. In addition, we identified genes (TIMP2, PKM2, PRKG1, MAP3K5, and ATP8A1) related to feeding efficiency. Among the enriched Gene Ontology Biological Process (GO BP) terms, actin cytoskeleton organization, actin filament-based process, and protein ubiquitination are associated with meat tenderness whereas cellular component organization, negative regulation of actin filament depolymerization and negative regulation of protein complex disassembly are involved in adipocyte regulation. The MAPK pathway is responsible for cell proliferation and plays an important role in hyperplastic growth, which has a positive effect on meat tenderness. CONCLUSION: Results revealed several candidate genes positively selected in Ankole cattle in relation to meat quality characteristics. The genes identified are involved in muscle structure and metabolism, and adipose metabolism and adipogenesis. These genes help in the understanding of the biological mechanisms controlling beef quality characteristics in African Ankole cattle. These results provide a basis for further research on the genomic characteristics of Ankole and other Sanga cattle breeds for quality beef.

Assessing single-nucleotide polymorphism selection methods for the development of a low-density panel optimized for imputation in South African Drakensberger beef cattle.

A major obstacle in applying genomic selection (GS) to uniquely adapted local breeds in less-developed countries has been the cost of genotyping at high densities of single-nucleotide polymorphisms (SNP). Cost reduction can be achieved by imputing genotypes from lower to higher densities. Locally adapted breeds tend to be admixed and exhibit a high degree of genomic heterogeneity thus necessitating the optimization of SNP selection for downstream imputation. The aim of this study was to quantify the achievable imputation accuracy for a sample of 1,135 South African (SA) Drakensberger cattle using several custom-derived lower-density panels varying in both SNP density and how the SNP were selected. From a pool of 120,608 genotyped SNP, subsets of SNP were chosen (1) at random, (2) with even genomic dispersion, (3) by maximizing the mean minor allele frequency (MAF), (4) using a combined score of MAF and linkage disequilibrium (LD), (5) using a partitioning-around-medoids (PAM) algorithm, and finally (6) using a hierarchical LD-based clustering algorithm. Imputation accuracy to higher density improved as SNP density increased; animal-wise imputation accuracy defined as the within-animal correlation between the imputed and actual alleles ranged from 0.625 to 0.990 when 2,500 randomly selected SNP were chosen vs. a range of 0.918 to 0.999 when 50,000 randomly selected SNP were used. At a panel density of 10,000 SNP, the mean (standard deviation) animal-wise allele concordance rate was 0.976 (0.018) vs. 0.982 (0.014) when the worst (i.e., random) as opposed to the best (i.e., combination of MAF and LD) SNP selection strategy was employed. A difference of 0.071 units was observed between the mean correlation-based accuracy of imputed SNP categorized as low (0.01 < MAF ≤ 0.1) vs. high MAF (0.4 < MAF ≤ 0.5). Greater mean imputation accuracy was achieved for SNP located on autosomal extremes when these regions were populated with more SNP. The presented results suggested that genotype imputation can be a practical cost-saving strategy for indigenous breeds such as the SA Drakensberger. Based on the results, a genotyping panel consisting of ~10,000 SNP selected based on a combination of MAF and LD would suffice in achieving a <3% imputation error rate for a breed characterized by genomic admixture on the condition that these SNP are selected based on breed-specific selection criteria.