Genome‑wide scan for selection signatures in six cattle breeds in South Africa

BACKGROUND : The detection of selection signatures in breeds of livestock species can contribute to the identification of regions of the genome that are, or have been, functionally important and, as a consequence, have been targeted by selection. METHODS : This study used two approaches to detect signatures of selection within and between six cattle breeds in South Africa, including Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), Bonsmara (n = 44), Angus (n = 31) and Holstein (n = 29). The first approach was based on the detection of genomic regions in which haplotypes have been driven towards complete fixation within breeds. The second approach identified regions of the genome that had very different allele frequencies between populations (FST). RESULTS AND DISCUSSION : Forty-seven candidate genomic regions were identified as harbouring putative signatures of selection using both methods. Twelve of these candidate selected regions were shared among the breeds and ten were validated by previous studies. Thirty-three of these regions were successfully annotated and candidate genes were identified. Among these genes the keratin genes (KRT222, KRT24, KRT25, KRT26, and KRT27) and one heat shock protein gene (HSPB9) on chromosome 19 between 42,896,570 and 42,897,840 bp were detected for the Nguni breed. These genes were previously associated with adaptation to tropical environments in Zebu cattle. In addition, a number of candidate genes associated with the nervous system (WNT5B, FMOD, PRELP, and ATP2B), immune response (CYM, CDC6, and CDK10), production (MTPN, IGFBP4, TGFB1, and AJAP1) and reproductive performance (ADIPOR2, OVOS2, and RBBP8) were also detected as being under selection. CONCLUSIONS : The results presented here provide a foundation for detecting mutations that underlie genetic variation of traits that have economic importance for cattle breeds in South Africa.Additional file 1: Table S1. Symbols and names for all annotated candidate genes.ARChttp://gsejournal.biomedcentral.com/am2017Animal and Wildlife Science

Integrative QTL mapping and selection signatures in Groningen White Headed cattle inferred from whole-genome sequences

Here, we aimed to identify and characterize genomic regions that differ between Groningen White Headed (GWH) breed and other cattle, and in particular to identify candidate genes associated with coat color and/or eye-protective phenotypes. Firstly, whole genome sequences of 170 animals from eight breeds were used to evaluate the genetic structure of the GWH in relation to other cattle breeds by carrying out principal components and model-based clustering analyses. Secondly, the candidate genomic regions were identified by integrating the findings from: a) a genome-wide association study using GWH, other white headed breeds (Hereford and Simmental), and breeds with a non-white headed phenotype (Dutch Friesian, Deep Red, Meuse-Rhine-Yssel, Dutch Belted, and Holstein Friesian); b) scans for specific signatures of selection in GWH cattle by comparison with four other Dutch traditional breeds (Dutch Friesian, Deep Red, Meuse-Rhine-Yssel and Dutch Belted) and the commercial Holstein Friesian; and c) detection of candidate genes identified via these approaches. The alignment of the filtered reads to the reference genome (ARS-UCD1.2) resulted in a mean depth of coverage of 8.7X. After variant calling, the lowest number of breed-specific variants was detected in Holstein Friesian (148,213), and the largest in Deep Red (558,909). By integrating the results, we identified five genomic regions under selection on BTA4 (70.2–71.3 Mb), BTA5 (10.0–19.7 Mb), BTA20 (10.0–19.9 and 20.0–22.7 Mb), and BTA25 (0.5–9.2 Mb). These regions contain positional and functional candidate genes associated with retinal degeneration (e.g., CWC27 and CLUAP1), ultraviolet protection (e.g., ERCC8), and pigmentation (e.g. PDE4D) which are probably associated with the GWH specific pigmentation and/or eye-protective phenotypes, e.g. Ambilateral Circumocular Pigmentation (ACOP). Our results will assist in characterizing the molecular basis of GWH phenotypes and the biological implications of its adaptation

A balanced perspective on the importance of extensive ruminant production for human nutrition and livelihoods and its contribution to greenhouse gas emissions

There is a general perception that ruminants produce large quantities of greenhouse gases which contribute to global warming. Sometimes percentages are quoted out of context. For example, the percentage quoted for developed countries indicates the greenhouse gas contribution from livestock is less than 6%, while that for developing countries is 40–50%. However, the reason for this relatively low contribution from developed countries is because of very high contributions from other sectors. Ruminant production also is in the spotlight as it is the world’s largest user of land and South Africa is no exception. Only ruminants can utilise areas of non-arable land where the vegetation is rich in fibre and convert this fibre into high-quality nutrients for human consumption. Foods from animal sources (including ruminants) are essential for the human diet, as they support early childhood and cognitive development. Many rural households depend on ruminants and these animals are central to the livelihoods and well-being of these communities. The negative effects of red meat on human health and the negative environmental impact of livestock production are overemphasised, while the higher bioavailability of nutrients from livestock source foods, which stimulates mental and cognitive development compared to vegetarian or grain based foods, is ignored. Here we estimate that livestock are responsible for only 4% of the world’s greenhouse gases through methane production. We also highlight that if the high fibre vegetation is not utilised by livestock, it will still produce greenhouse gases through burning or rotting, without any benefit to humans. Livestock source foods are important if global nutritional, educational and economic needs are to be met; and this message should be conveyed to the public. Significance: We propose that a balanced message should be conveyed to the broader scientific community and the public on the role of livestock in meeting global nutritional needs and contributing to global warming. Livestock source foods are important if the global nutritional, educational and economic needs are to be met and can be used to feed developing countries out of poverty

Investigation of reliability of genomic predictions in the admixed Nordic Red dairy cattle

The success of genomic selection (GS) in small breeds which are likely to have admixed structures has been minimal. This is because accuracy of GS depends on the extent of linkage disequilibrium (LD) between markers and quantitative trait loci (QTL) and LD depends on the genetic structure of the population and marker density. In the current study, we evaluate reliability of genomic predictions in young unproven bulls, when interactions between marker effects and breed of origin are accounted for in the Nordic Red dairy cattle (RDC). The population structure of the RDC is admixed. Data consisted of animal breed proportions calculated from the full pedigree, deregressed proofs (DRP) of published estimated breeding values (EBV) for yield traits and genotypic data for 37,595 SNP markers. Direct genomic breeding values (DGV) were estimated using 2 models, one accounting for breed-specific effects and other assuming uniform population. Validation reliabilities were calculated as the squared correlation between DRP and DGV (r2DRP, DGV), corrected by the mean reliability ofDRP. Using the breed-specific model increased the reliability of DGV by 2% and 3% for milk and protein, respectively, when compared to homogeneous population GBLUP model. The exception was for fat, where there was no gain in reliability. Estimated validation reliabilities were low for milk (0.32) and protein (0.32) and slightly higher (0.42) for fat

Integrative QTL mapping and selection signatures in Groningen White Headed cattle inferred from whole-genome sequences

Here, we aimed to identify and characterize genomic regions that differ between Groningen White Headed (GWH) breed and other cattle, and in particular to identify candidate genes associated with coat color and/or eye-protective phenotypes. Firstly, whole genome sequences of 170 animals from eight breeds were used to evaluate the genetic structure of the GWH in relation to other cattle breeds by carrying out principal components and model-based clustering analyses. Secondly, the candidate genomic regions were identified by integrating the findings from: a) a genome-wide association study using GWH, other white headed breeds (Hereford and Simmental), and breeds with a non-white headed phenotype (Dutch Friesian, Deep Red, Meuse-Rhine-Yssel, Dutch Belted, and Holstein Friesian); b) scans for specific signatures of selection in GWH cattle by comparison with four other Dutch traditional breeds (Dutch Friesian, Deep Red, Meuse-Rhine-Yssel and Dutch Belted) and the commercial Holstein Friesian; and c) detection of candidate genes identified via these approaches. The alignment of the filtered reads to the reference genome (ARS-UCD1.2) resulted in a mean depth of coverage of 8.7X. After variant calling, the lowest number of breed-specific variants was detected in Holstein Friesian (148,213), and the largest in Deep Red (558,909). By integrating the results, we identified five genomic regions under selection on BTA4 (70.2–71.3 Mb), BTA5 (10.0–19.7 Mb), BTA20 (10.0–19.9 and 20.0–22.7 Mb), and BTA25 (0.5–9.2 Mb). These regions contain positional and functional candidate genes associated with retinal degeneration (e.g., CWC27 and CLUAP1), ultraviolet protection (e.g., ERCC8), and pigmentation (e.g. PDE4D) which are probably associated with the GWH specific pigmentation and/or eye-protective phenotypes, e.g. Ambilateral Circumocular Pigmentation (ACOP). Our results will assist in characterizing the molecular basis of GWH phenotypes and the biological implications of its adaptation

Insight into the genetic composition of South African Sanga cattle using SNP data from cattle breeds worldwide

International audienceAbstractBackgroundUnderstanding the history of cattle breeds is important because it provides the basis for developing appropriate selection and breed improvement programs. In this study, patterns of ancestry and admixture in Afrikaner, Nguni, Drakensberger and Bonsmara cattle of South Africa were investigated. We used 50 K single nucleotide polymorphism genotypes that were previously generated for the Afrikaner (n = 36), Nguni (n = 50), Drakensberger (n = 47) and Bonsmara (n = 44) breeds, and for 394 reference animals representing European taurine, African taurine, African zebu and Bos indicus.Results and discussionOur findings support previous conclusions that Sanga cattle breeds are composites between African taurine and Bos indicus. Among these breeds, the Afrikaner breed has significantly diverged from its ancestral forebears, probably due to genetic drift and selection to meet breeding objectives of the breed society that enable registration. The Nguni, Drakensberger and Bonsmara breeds are admixed, perhaps unintentionally in the case of Nguni and Drakensberger, but certainly by design in the case of Bonsmara, which was developed through crossbreeding between the Afrikaner, Hereford and Shorthorn breeds.ConclusionsWe established patterns of admixture and ancestry for South African Sanga cattle breeds, which provide a basis for developing appropriate strategies for their genetic improvement