A comprehensive analysis of the genetic diversity and environmental adaptability in worldwide Merino and Merino-derived sheep breeds

BACKGROUND: To enhance and extend the knowledge about the global historical and phylogenetic relationships between Merino and Merino-derived breeds, 19 populations were genotyped with the OvineSNP50 BeadChip specifically for this study, while an additional 23 populations from the publicly available genotypes were retrieved. Three complementary statistical tests, Rsb (extended haplotype homozygosity between-populations), XP-EHH (cross-population extended haplotype homozygosity), and runs of homozygosity (ROH) islands were applied to identify genomic variants with potential impact on the adaptability of Merino genetic type in two contrasting climate zones. RESULTS: The results indicate that a large part of the Merino's genetic relatedness and admixture patterns are explained by their genetic background and/or geographic origin, followed by local admixture. Multi-dimensional scaling, Neighbor-Net, Admixture, and TREEMIX analyses consistently provided evidence of the role of Australian, Rambouillet and German strains in the extensive gene introgression into the other Merino and Merino-derived breeds. The close relationship between Iberian Merinos and other South-western European breeds is consistent with the Iberian origin of the Merino genetic type, with traces from previous contributions of other Mediterranean stocks. Using Rsb and XP-EHH approaches, signatures of selection were detected spanning four genomic regions located on Ovis aries chromosomes (OAR) 1, 6 and 16, whereas two genomic regions on OAR6, that partially overlapped with the previous ones, were highlighted by ROH islands. Overall, the three approaches identified 106 candidate genes putatively under selection. Among them, genes related to immune response were identified via the gene interaction network. In addition, several candidate genes were found, such as LEKR1, LCORL, GHR, RBPJ, BMPR1B, PPARGC1A, and PRKAA1, related to morphological, growth and reproductive traits, adaptive thermogenesis, and hypoxia responses. CONCLUSIONS: To the best of our knowledge, this is the first comprehensive dataset that includes most of the Merino and Merino-derived sheep breeds raised in different regions of the world. The results provide an in-depth picture of the genetic makeup of the current Merino and Merino-derived breeds, highlighting the possible selection pressures associated with the combined effect of anthropic and environmental factors. The study underlines the importance of Merino genetic types as invaluable resources of possible adaptive diversity in the context of the occurring climate changes

THE EXTENT AND DISTRIBUTION OF LINKAGE DISEQUILIBRIUM IN EXTENSIVELY RAISED CHICKEN POPULATIONS OF SOUTHERN AFRICA

SUMMARY The amount of linkage disequilibrium (LD) is an important source of information about historical events of recombination and allows inferences about genetic diversity and genomic regions that have undergone selection. Linkage disequilibrium is equally important in studying effective population size and rate of inbreeding particularly in extensively raised and wild animal populations where pedigree records are scarce. The objective of this study was to investigate LD in village chicken populations of Southern Africa. These chickens are raised under scavenging systems of production characterized by uncontrolled breeding and frequent population bottlenecks due to disease outbreaks and fluctuations in feed supplies. DNA samples from 312 extensively raised chickens from South Africa, Malawi and Zimbabwe were genotyped using the Illumina iSelect chicken SNP60K BeadChip. A panel of 43,157 out of the total 57,636 (74.8%) SNPs was used in the final analysis after screening for those that had a minor allele frequency of less than 5%, were out of Hardy-Weinberg equilibrium (P<0.01) and had a call rate of less that 95%. Results indicated that LD averaged between 0.45 and 0.58 for SNPs that had a pairwise distance of less than 20 kb. LD dropped to 0.34 for SNPs between 20 and 100 kb after which it remained constant. LD was further analyzed for its decay over marker distance and differences between populations from different geographic locations. Results are discussed in terms of historical changes in effective population size and resultant recombination rates. The utility of the iSelect chicken SNP60K beadchip in investigating free-range chicken population genetics is demonstrated

Current address: Discipline of Genetics

________________________________________________________________________________ Abstract Genetic evaluation of dairy cattle using test-day models is now common internationally. In South Africa a fixed regression test-day model is used to generate breeding values for dairy animals on a routine basis. The model is, however, often criticized for erroneously assuming a standard lactation curve for cows in similar contemporary groups and homogeneity of additive genetic variances across lactation and for its inability to account for persistency of lactation. The random regression test-day model has been suggested as a more appropriate method and is currently implemented by several Interbull member-countries. This review traces the development of random regression methods and their adoption in test-day models. Comparisons are drawn with the fixed regression test-day model. The paper discusses reasons for suggesting the adoption of the random regression approach for dairy cattle evaluation in South Africa and identifies the key areas where research efforts should focus. _______________________________________________________________________________

Table1_Selection signature analysis and genome-wide divergence of South African Merino breeds from their founders.XLSX

Merino sheep are a breed of choice across the world, popularly kept for their wool and mutton value. They are often reared as a pure breed or used in crossbreeding and are a common component in synthetic breed development. This study evaluated genetic diversity, population structure, and breed divergence in 279 animals of Merino and Merino-based sheep breeds in South Africa using the Illumina Ovine SNP 50K BeadChip. The sheep breeds analysed included the three Merino-derived breeds of Dohne Merino (n = 50); Meatmaster (n = 47); and Afrino (n = 52) and five presumed ancestral populations of Merinos (Merino (n = 46); South African Merino (n = 10); and South African Mutton Merino (n = 8)); and the non-Merino founding breeds of Damara (n = 20); Ronderib Afrikaner (n = 17); and Nguni (n = 29). Highest genetic diversity values were observed in the Dohne Merino (DM), with Ho = 0.39 ± 0.01, followed by the Meatmaster and South African Merino (SAM), with Ho = 0.37 ± 0.03. The level of inbreeding ranged from 0.0 ± 0.02 (DM) to 0.27 ± 0.05 (Nguni). Analysis of molecular variance (AMOVA) showed high within-population variance (>80%) across all population categories. The first principal component (PC1) separated the Merino, South African Mutton Merino (SAMM), DM, and Afrino (AFR) from the Meatmaster, Damara, Nguni, and Ronderib Afrikaner (RDA). PC2 aligned each Merino-derived breed with its presumed ancestors and separated the SAMM from the Merino and SAM. The iHS analysis yielded selection sweeps across the AFR (12 sweeps), Meatmaster (four sweeps), and DM (29 sweeps). Hair/wool trait genes such as FGF12; metabolic genes of ICA1, NXPH1, and GPR171; and immune response genes of IL22, IL26, IFNAR1, and IL10RB were reported. Other genes include HMGA, which was observed as selection signatures in other populations; WNT5A, important in the development of the skeleton and mammary glands; ANTXR2, associated with adaptation to variation in climatic conditions; and BMP2, which has been reported as strongly selected in both fat-tailed and thin-tailed sheep. The DM vs. SAMM shared all six sweep regions on chromosomes 1, 10, and 11 with AFR vs. SAMM. Genes such as FGF12 on OAR 1:191.3–194.7 Mb and MAP2K4 on OAR 11:28.6–31.3 Mb were observed. The selection sweep on chromosome 10 region 28.6–30.3 Mb harbouring the RXFP2 for polledness was shared between the DM vs. Merino, the Meatmaster vs. Merino, and the Meatmaster vs. Nguni. The DM vs. Merino and the Meatmaster vs. Merino also shared an Rsb-based selection sweep on chromosome 1 region 268.5–269.9 Mb associated with the Calpain gene, CAPN7. The study demonstrated some genetic similarities between the Merino and Merino-derived breeds emanating from common founding populations and some divergence driven by breed-specific selection goals. Overall, information regarding the evolution of these composite breeds from their founding population will guide future breed improvement programs and management and conservation efforts.</p

Random regression test-day model for the analysis of dairy cattle production data in South Africa : Creating the framework

CITATION: Dzomba, E. F., et al. 2010. Random regression test-day model for the analysis of dairy cattle production data in South Africa : creating the framework. South African Journal of Animal Science, 40(4):273-284.The original publication is available at https://journals.co.za/content/sajas/40/4/EJC94760Genetic evaluation of dairy cattle using test-day models is now common internationally. In South Africa a fixed regression test-day model is used to generate breeding values for dairy animals on a routine basis. The model is, however, often criticized for erroneously assuming a standard lactation curve for cows in similar contemporary groups and homogeneity of additive genetic variances across lactation and for its inability to account for persistency of lactation. The random regression test-day model has been suggested as a more appropriate method and is currently implemented by several Interbull member-countries. This review traces the development of random regression methods and their adoption in test-day models. Comparisons are drawn with the fixed regression test-day model. The paper discusses reasons for suggesting the adoption of the random regression approach for dairy cattle evaluation in South Africa and identifies the key areas where research efforts should focus. .Publisher's versio

Data from: Landscape genomics and pathway analysis to understand genetic adaptation of South African indigenous goat populations

Extensively raised livestock populations in most smallholder farming communities are exposed to harsh and heterogeneous climates and disease pathogen that they adapt to in order to survive. Majority of these livestock species including goats are of non-descript breeds and their response to natural selection presented by heterogeneous environments is still unresolved. This study investigated genetic diversity and its association with environmental and geographic conditions in 194 South African indigenous goats from different geographic using Illumina goat SNP50K genotypes. The Tankwa goats formed a homogeneous genetic cluster restricted to the Northern Cape province. Overall, the Boer, Kalahari Red, and Savanna showed a wide geographic spread of shared genetic components whereas the village ecotypes revealed a longitudinal distribution. The relative importance of environmental factors on genetic variation of goat populations was assessed using Redundancy Analysis (RDA). Variance partitioning using Model I with both climatic and geographic variables explained 22% of the total variation while model II with climatic variables accounted for 17%. Model III, which accounted for geographic variables, explained 1% of the total variation. The first axis (Model I) of the RDA analysis, revealed 329 outlier SNPs. Landscape genomic approaches of Spatial Analysis Method identified a total of 843 (1.75%) SNPs, while Latent Factor Mixed Models identified 714 (1.48%) SNPs significantly associated with environmental variables. Significant markers were within genes involved in biological functions potentially important for environmental adaptation. Overall, the study suggested environmental factors to have some effect in shaping the genetic variation of South African indigenous goat populations