Genetic diversity and population structure of three native cattle populations in Mozambique.

In the present work, the population diversity and structure of three populations of native Mozambican cattle were studied, to develop knowledge that is required for sound conservation and genetic improvement programs of these genetic resources. A total of 228 animals (Landim, Angone, and Tete) were genotyped using the International Dairy and Beef version three (IDBV3) SNP BeadChip array. Population parameters varied within a limited scope, with the average minor allele frequency (MAF) ranging from 0.228 ± 0.154 in the Angone to 0.245 ± 0.145 in the Tete population, while estimates of expected heterozygosities varied from 0.304 ± 0.166 in the Angone to 0.329 ± 0.148 in the Tete population. Low positive (0.065 ± 0.109) inbreeding rates were detected in the three cattle groups. Population structure and admixture analyses indicated low genetic differentiation and various degrees of admixture among the populations. The effective population size has decreased over time and at 12 generations ago ranged between 349 (Tete) and 929 (Landim). The average linkage disequilibrium (LD) of the studied populations ranged from 0.400 ± 0.213 (Tete) to 0.434 ± 0.232 (Landim). The findings of this study will be valuable for formulating management and conservation strategies for indigenous Mozambican cattle populations.

Draft De Novo Genome Sequence of Agapornis roseicollis for Application in Avian Breeding.

In aviculture, lovebirds are considered one of the most popular birds to keep. This African parakeet is known for its range of plumage colors and ease to tame. Plumage variation is the most important price-determining trait of these birds, and also the main selection criterion for breeders. Currently, no genetic screening tests for traits of economic importance or to confirm pedigree data are available for any of the nine lovebird species. As a starting point to develop these tests, the de novo genome of Agapornis roseicollis (rosy-faced lovebird) was sequenced, assembled, and annotated. Sequencing was done on the Illumina HiSeq 2000 platform and the assembly was performed using SOAPdenovo v2.04. The genome was found to be 1.1 Gb in size and 16,044 genes were identified and annotated. This compared well with other previously sequenced avian genomes, such as the chicken, zebra finch, and budgerigar. To assess genome completeness, the number of benchmarking universal single-copy orthologs were identified in the genome. This was compared to other previously assembled avian genomes and the results indicated that the genome will be useful in the development of genetic screening tests to aid lovebird breeders in selecting breeding pairs.

Genetic diversity in South African Nguni cattle ecotypes based on microsatellite markers.

The Nguni cattle breed is a landrace breed adapted to different ecological regions of South Africa. A number of ecotypes are recognised based on phenotype within the breed, but it is not known if they are genetically distinct. In this study, molecular characterisation was performed on Makhathini (MAK), Pedi (PED), Shangaan (SHA) and Venda (VEN) Nguni cattle ecotypes. Two Nguni cattle populations, not kept as separate ecotypes, from the University of Fort Hare (UFH) and Agricultural Research Council Loskop South farm (LOS) were also included. Genotypic data was generated for 189 unrelated Nguni cattle selected based on pedigree records using 22 microsatellite markers. The expected heterozygosity values varied from 69 % (UFH) to 72 % (PED) with a mean number of alleles ranging from 6.0 to 6.9. The F ST estimate demonstrated that 4.8 % of the total genetic variation was due to the genetic differentiation between the populations and 92.2 % accounted for differences within the populations. The genetic distances and structure analysis revealed the closest relationship between MAK, PEDI and SHA ecotypes, followed by SHA and VEN. The UFH population clustered with the MAK ecotype, indicating that they are more genetically similar, while the LOS cattle grouped as a distinct cluster. Results suggest that the genetic differentiation between the PED and SHA ecotypes is low and can be regarded as one ecotype based on limited genetic differences. The results of this study can be applied as a point of reference for further genetic studies towards conservation of Nguni cattle ecotypes.

Genetic diversity and population structure of the endangered Namaqua Afrikaner sheep.

The Namaqua Afrikaner is an endangered sheep breed indigenous to South Africa, primarily used in smallholder farming systems. Genetic characterization is essential for the breed's conservation and utilization. In this study, a genetic characterization was performed on 144 Namaqua Afrikaner sheep kept at the Karakul Experimental Station (KES), Carnarvon Experimental Station (CES), and a private farm Welgeluk (WGK) using 22 microsatellite markers. The mean number of alleles observed was low (3.7 for KES, 3.9 for CES, and 4.2 for WGK). Expected heterozygosity values across loci ranged between 46 % for WGK, 48 % for KES, and 55 % for CES, indicating low to moderate genetic variation. The analysis of molecular variance revealed that 89.5 % of the genetic variation was due to differences within populations. The population structure confirmed the differentiation of three clusters with high relationships between the CES and WGK populations. In the population structure comparison with Pedi and South African Mutton Merino sheep, limited hybridization between the Namaqua Afrikaner sheep and both of these breeds was observed. The results of this study will serve as a reference for genetic management and conservation of Namaqua Afrikaner sheep.

Pedigree and genome-based patterns of homozygosity in the South African Ayrshire, Holstein, and Jersey breeds.

The erosion of genetic diversity limits long-term genetic gain and impedes the sustainability of livestock production. In the South African (SA) dairy industry, the major commercial dairy breeds have been applying estimated breeding values (EBVs) and/or have been participating in Multiple Across Country Evaluations (MACE). The transition to genomic estimated breeding values (GEBVs) in selection strategies requires monitoring of the genetic diversity and inbreeding of current genotyped animals, especially considering the comparatively small population sizes of global dairy breeds in SA. This study aimed to perform a homozygosity-based evaluation of the SA Ayrshire (AYR), Holstein (HST), and Jersey (JER) dairy cattle breeds. Three sources of information, namely 1) single nucleotide polymorphism (SNP) genotypes (3,199 animals genotyped for 35,572 SNPs) 2) pedigree records (7,885 AYR; 28,391 HST; 18,755 JER), and 3) identified runs of homozygosity (ROH) segments were used to quantify inbreeding related parameters. The lowest pedigree completeness was for the HST population reducing from a value of 0.990 to 0.186 for generation depths of one to six. Across all breeds, 46.7% of the detected ROH were between 4 megabase pairs (Mb) and 8 Mb in length. Two conserved homozygous haplotypes were identified in more than 70% of the JER population on Bos taurus autosome (BTA) 7. The JER breed displayed the highest level of inbreeding across all inbreeding coefficients. The mean (± standard deviation) pedigree-based inbreeding coefficient (FPED) ranged from 0.051 (±0.020) for AYR to 0.062 (±0.027) for JER, whereas SNP-based inbreeding coefficients (FSNP) ranged from 0.020 (HST) to 0.190 (JER) and ROH-based inbreeding coefficients, considering all ROH segment coverage (FROH), ranged from 0.053 (AYR) to 0.085 (JER). Within-breed Spearman correlations between pedigree-based and genome-based estimates ranged from weak (AYR: 0.132 between FPED and FROH calculated for ROH <4Mb in size) to moderate (HST: 0.584 between FPED and FSNP). Correlations strengthened between FPED and FROH as the ROH length category was considered lengthened, suggesting a dependency on breed-specific pedigree depth. The genomic homozygosity-based parameters studied proved useful in investigating the current inbreeding status of reference populations genotyped to implement genomic selection in the three most prominent South African dairy cattle breeds.

Application of DNA markers in parentage verification of Boran cattle in Kenya.

Boran cattle provide livelihood to thousands of households in the arid and semiarid lands of Kenya. Due to their superior adaptive and productive traits in comparison to other breeds of cattle, they have also become a popular choice for breeders in Eastern and Southern Africa. Continued genetic improvement of the breed is important, and therefore accurate performance and pedigree records are required. One hundred seventy-eight pedigree records and blood samples of four Boran stud herds were evaluated for accuracy of parentage allocation using 11 microsatellite markers recommended by ISAG for parentage verification. The panel of the 11 microsatellite markers was found to be highly polymorphic (PIC of 0.6901) with a combined probability of exclusion of 0.9997. The dam misidentification was low ranging between 0% and 5% for the herds tested. The estimated rate of mispaternity however ranged between 4.3% and 80% among the four stud herds, and more than 50% of the offspring of some herds were misidentified. The high rate of mispaternity will have a negative impact on the response to selection. The use of DNA markers for parentage assignment will improve the accuracy of the pedigree records of Boran stud cattle in Kenya and contribute to more accurate selection of superior animals.

Unintended consequences of selection for increased production on the health and welfare of livestock.

Modern farming technologies, including quantitative selection and breeding methods in farm animal species, resulted in increased production and efficiency. Selection for increased output in both intensive and extensive production systems has trade-offs and negative outcomes, often more pronounced in intensive systems. Animal welfare and health are often adversely affected and this influences sustainable production. The relative importance of animal welfare differs among developed and developing countries due to the level of economic development, food security and education, as well as religious and cultural practices which presents challenges for sound scientific research. Due to breeding goals in the past set on growth performance, traits such as fertility, welfare and health have been neglected. Fertility is the single most important trait in all livestock species. Reduced fertility and lameness, claw health and mastitis results in unnecessary culling and reduced longevity. Selection pressure for growth accompanied with inbreeding has resulted in a number of genetic defects in beef, sheep and pigs. This review demonstrated the importance of inclusion of animal welfare concepts into breeding objectives and selection strategies. Accurate phenotyping of welfare traits is a limiting factor in the implementation of mitigating strategies, which include diagnostic testing, control of inbreeding and genomic selection.

Whole-Genome SNP Characterisation Provides Insight for Sustainable Use of Local South African Livestock Populations.

Local cattle and sheep populations are important for animal production and food security in South Africa. These genetic resources are well adapted to the diverse climatic conditions and hold potential to be utilized in production systems subjected to climate change. The local beef breeds are well integrated into commercial livestock production systems with access to performance recording and genetic evaluations, while local sheep breeds are mainly utilised in smallholder and communal systems. The GeneSeek® Genomic Profiler™ Bovine 150 K SNP genotyping array was used to evaluate the diversity and inbreeding status of four indigenous (Boran, Drakensberger, Nguni, Tuli), two composite (Bonsmara and Beefmaster) and two exotic (SA Hereford and Charolais) beef breeds. The Illumina® Ovine 50 K SNP BeadChip was used to investigate five indigenous (Black Head Persian, Damara, Fat tail, Namaqua Afrikaner, Pedi) and three commercial (Dorper, Dohne Merino and SA Merino) populations. Although ascertainment bias was indicated by the low MAF (the autosome-wide proportion of SNPs with MAF< 0.05 ranged from 6.18 to 9.97% for cattle, and 7.59-13.81% for sheep), moderate genomic diversity was observed (mean Ho ranged from 0.296 to 0.403 for cattle, and 0.327 to 0.367 for sheep). Slightly higher levels of ROH-based inbreeding were calculated for cattle (FROH range: 0.018-0.104), than for sheep populations (FROH range: 0.002-0.031). The abundance of short ROH fragments (mean proportion of <4 Mb fragments: 0.405 for cattle, and 0.794 for sheep) indicated ancient inbreeding in both species. The eight cattle populations were categorized into indicine, taurine or Sanga subspecies based on principal component, model-based clustering and phylogenetic analyses, with high levels of admixture observed within the Drakensberger, Nguni and Tuli breeds. Within the sheep populations, a clear distinction could be seen between the dual-purpose breeds, the meat breed and the indigenous breeds. Despite directional selection practiced in the cattle breeds, genomic diversity was moderate with low inbreeding. The non-commercialized, indigenous sheep populations are more vulnerable with small effective populations. These results emphasise the value of genomic information for effective management to exploit the potential contribution of local genetic cattle and sheep resources in a changing environment.

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.

Genetic Improvement in South African Livestock: Can Genomics Bridge the Gap Between the Developed and Developing Sectors?

South Africa (SA) holds a unique position on the African continent with a rich diversity in terms of available livestock resources, vegetation, climatic regions and cultures. The livestock sector has been characterized by a dual system of a highly developed commercial sector using modern technology vs. a developing sector including emerging and smallholder farmers. Emerging farmers typically aim to join the commercial sector, but lag behind with regard to the use of modern genetic technologies, while smallholder farmers use traditional practices aimed at subsistence. Several factors influence potential application of genomics by the livestock industries, which include available research funding, socio-economic constraints and extension services. State funded Beef and Dairy genomic programs have been established with the aim of building reference populations for genomic selection with most of the potential beneficiaries in the well-developed commercial sector. The structure of the beef, dairy and small stock industries is fragmented and the outcomes of selection strategies are not perceived as an advantage by the processing industry or the consumer. The indigenous and local composites represent approximately 40% of the total beef and sheep populations and present valuable genetic resources. Genomic research has mostly provided insight on genetic biodiversity of these resources, with limited attention to novel phenotypes associated with adaptation or disease tolerance. Genetic improvement of livestock through genomic technology needs to address the role of adapted breeds in challenging environments, increasing reproductive and growth efficiency. National animal recording schemes contributed significantly to progress in the developed sector with regard to genetic evaluations and estimated breeding values (EBV) as a selection tool over the past three decades. The challenge remains on moving the focus to novel traits for increasing efficiency and addressing welfare and environmental issues. Genetic research programs are required that will be directed to bridge the gap between the elite breeders and the developing livestock sector. The aim of this review was to provide a perspective on the dichotomy in the South African livestock sector arguing that a realistic approach to the use of genomics in beef, dairy and small stock is required to ensure sustainable long term genetic progress.

Genetic Diversity and Population Structure in South African, French and Argentinian Angora Goats from Genome-Wide SNP Data.

The Angora goat populations in Argentina (AR), France (FR) and South Africa (SA) have been kept geographically and genetically distinct. Due to country-specific selection and breeding strategies, there is a need to characterize the populations on a genetic level. In this study we analysed genetic variability of Angora goats from three distinct geographical regions using the standardized 50k Goat SNP Chip. A total of 104 goats (AR: 30; FR: 26; SA: 48) were genotyped. Heterozygosity values as well as inbreeding coefficients across all autosomes per population were calculated. Diversity, as measured by expected heterozygosity (HE) ranged from 0.371 in the SA population to 0.397 in the AR population. The SA goats were the only population with a positive average inbreeding coefficient value of 0.009. After merging the three datasets, standard QC and LD-pruning, 15 105 SNPs remained for further analyses. Principal component and clustering analyses were used to visualize individual relationships within and between populations. All SA Angora goats were separated from the others and formed a well-defined, unique cluster, while outliers were identified in the FR and AR breeds. Apparent admixture between the AR and FR populations was observed, while both these populations showed signs of having some common ancestry with the SA goats. LD averaged over adjacent loci within the three populations per chromosome were calculated. The highest LD values estimated across populations were observed in the shorter intervals across populations. The Ne for the Angora breed was estimated to be 149 animals ten generations ago indicating a declining trend. Results confirmed that geographic isolation and different selection strategies caused genetic distinctiveness between the populations.