Genomics Tools for the Characterization of Genetic Adaptation of Low Input Extensively Raised Chickens

Evolutionary change emanating from differential contribution of genotypes to the next generation can determine success in survival and reproduction in chickens. For extensively raised chickens reared under low-input production systems in smallholder farming areas, conditions of resources deprivation and exposure to diverse and threatening natural selection pressures are common in many countries worldwide. Numerous studies have demonstrated that village chickens and other extensively raised chicken populations represent a valuable source of biodiversity adapted to the local production conditions and selection pressures. Manipulation of their acquired adaptive genetic diversity depends on unravelling the selection footprints in the genomes of these chickens that could point towards candidate genes for traits that enable the animals to survive under the harsh production environments. This chapter summarizes the evidence for chickens’ adaptation to extreme environments and describes an inventory of modern tools that could be used in characterizing the production systems of chicken genetic resources. The role of natural selection in shaping the biodiversity of chicken genetic resources is discussed. The continued advancement of biotechnological tools to assess chicken populations has been beneficial to research in genetic adaptation. Genomics tools, as evidenced by assays of whole genome and transcriptome sequences, and single nucleotide polymorphism (SNP) genotypes of chickens, now allow analyses of functional genomic regions that are linked to adaptation. The use of these methods to characterize and investigate signatures of selection in the chicken genomes is highlighted. This chapter looks at how information on the selection hotspots in the chicken genomes can be manipulated to improve genetic adaptation in indigenous chicken populations with the desire to transfer the benefits to other chicken breeds raised under similar production systems

Genetic diversity and differentiation of pelt, mutton and wool sheep breeds of South Africa using genome-wide single nucleotide polymorphisms.

Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Sheep, Ovis aries, are a versatile species that has, over hundreds of years, been adapted to South African environmental conditions resulting in more than 40 breeds that are raised for various objectives and production systems and constituting a population of close to 30 million animals. The South African sheep genetic resource presents unique and distinct phenotypes and genotypes that, put together, contribute to the global biodiversity observed in sheep that ought to be conserved and used for improved human livelihoods and economies. South Africa shares its sheep genetics with the global world, through both exportation and importation of germplasm. The broad objective of the study was to profile the genomic architecture of South African sheep populations to provide information for optimal utilization, conservation and improvement. Four hundred South African sheep belonging to 13 breeds of mutton, wool, dual purpose (mutton and wool), pelt and uncharacterised non-descript indigenous sheep were sampled and genotyped. In addition, 623 genotypes from the International Sheep Genomics Consortium representing European, Asian, African sheep breeds were subsampled. A series of statistical genomic analyses were pursued. In Chapter 3, genetic diversity, population genetic structure and divergence between South African sheep breeds was investigated using the OvineSNP50 Beadchip. A total of 400 sheep belonging to 13 breeds representing mutton, pelt and mutton and wool dual-purpose breeds and Nguni sheep as a representative of indigenous non-descript genotypes were genotyped. To gain a clearer understanding of the genetic diversity of South African breeds relative to other breeds, 623 genotypes from six African, two Asian and eight European breeds were included in the analyses. The study demonstrated low genetic diversity (HO ≤ 0.27) in small and geographically restricted populations of Namaqua Afrikaner; Nguni, and Blackhead Persian relative to moderate to high diversity (HO ≥ 0.38) in Merino and Merino-derived commercial breeds (i.e. Dohne Merino, Australian Merino and Chinese Merino). Overall, the African and Asian populations were the most inbred populations with FIS ranging from 0.17 ± 0.05 in Grey Swakara and Ronderib Afrikaner sheep to 0.34 ± 0.07 in the Namaqua Afrikaner. Principal component analysis separated the fat-tailed sheep (i.e. Swakaras, Nguni, Black Head Persian, Ethiopian Menzi, Meatmaster) from the rump-tailed sheep of Merino and Dorset Horn etc., as well as according to breed history and production systems. Similarly, ADMIXTUREbased clustering revealed various sources of within- and amongst-breed genomic variation associated with production purpose, adaptation and history of the breeds. An analysis of FSTv based breed differentiating SNPs suggested selection and population divergence on genomic regions associated with growth, adaptation and reproduction. Overall, the analysis gave insight into the current status of the sheep genetic resources of South Africa relative to the global sheep population highlighting both genetic similarities as well as divergence associated with production system and geographical distribution and local adaptation. The second set of analyses (Chapter 4) focused on assessing the genetic diversity, population structure and breed divergence in 279 animals including the three Merino-derived breeds and five presumed ancestral populations of Merinos and non-Merino founding breeds of Damara, Ronderib Afrikaner and Nguni. Highest genetic diversity values were observed in Dohne Merino with Ho = 0.39 ± 0.01 followed by Meatmaster and South African Merino with Ho = 0.37 ± 0.03. The level of inbreeding ranged from 0.0 ± 0.02 (Dohne Merino) 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), Dohne Merino and Afrino from the Meatmaster, Damara, Nguni and Ronderib Afrikaner. PC2 aligned each Merino derived breed with its presumed ancestors and separated the SAMM from the Merino and SA Merino. Within population selection based on |iHS| indices yielded selection sweeps across the AFR (12 sweeps), Meatmaster (4 sweeps) and Dohne Merino (29 sweeps). Genes associated with hair/wool traits such as FGF12, metabolic genes of ICA1, NXPH1 and GPR171 and immune response genes of IL22 IL26, IFNAR1 and IL10RB were reported. Other genes included HMGA which was observed as a selection signature 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. Using the Rsb analysis for selection sweeps, the Dohne Merino vs SAMM shared all six sweeps regions on chromosomes 1, 10 and 11 with the comparison for Afrino vs SAMM. Genes such as FGF12 on OAR 1:191,3-194,7Mb and MAP2K4 on OAR11:28,6-31,3Mb were observed. The selection sweep on chromosome 10 region 28,6-30,3 Mb, harbouring the RXFP2 for polledness, was shared between Dohne Merino vs Merino, Meatmaster vs Merino and Meatmaster vs Nguni. The Dohne Merino 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 as well as some divergence driven by breed-specific selection goals. Chapter 5 tested the hypothesis that production systems geared towards specific traits of importance or natural or artificial selection pressures influenced the occurrence and distribution of runs of homozygosity (ROH) in the South African sheep population. The ROH were screened and their distribution within chromosomes and between breeds were analysed to assess breed history and associated selected pressures. ROH were computed at cut-offs of 1-6 Mb, 6-12 Mb, 12-24 Mb, 24-48 Mb and >48 Mb. Analysis of the distribution of ROH according to their size showed that, for all breeds, the majority of the detected ROH were in the short (1- 6 Mb) category (88 %). Most animals had no ROH >48 Mb. Of the South African breeds, the Nguni and the Blackhead Persian displayed high ROH based inbreeding (FROH) of 0.31 ± 0.05 and 0.31 ± 0.04, respectively. Highest incidence of common ROH per SNP across breeds was observed on chromosome 10 with over 250 incidences of common ROHs. Mean proportion of SNPs per breed per ROH islands ranged from 0.02 ± 0.15 (island ROH224 on chromosome 23) to 0.13 ± 0.29 (island ROH175 on chromosome 15). Seventeen of the islands had SNPs observed in single populations (unique ROH islands). The MacArthur Merino population had five unique ROH islands followed by Blackhead Persian and Nguni with three each whilst the South African Mutton Merino, SA Merino, White Vital Swakara, Karakul, Dorset Horn and Chinese Merino each had one unique ROH island. Genes within ROH islands were predominantly associated with metabolic and immune response traits and predomestic selection for traits such as presence or absence of horns. In line with observations in Chapter 3, the frequency and patterns of distribution of ROH observed in this study corresponded to the breed history and implied selection pressures exposed to the sheep populations under study. Chapter 6 investigated (i) LD between adjacent SNPs, (ii) LD decay with increased marker distance, (iii) trends in effective population size over time and (iv) consistency of gametic phase in 13 South African sheep breeds South African Merino (n = 56), Merino (n =10); Mutton Merino (n = 10), Dohne Merino (n = 50), Meatmaster (n = 48), Blackhead Persian (n =14) and Namaqua Afrikaner (n = 12), the four pelt-colour based Swakara subpopulations of Grey (n = 22); Black (n = 16); White-vital (n = 41) and White-subvital (n =17) Dorper (n = 23); Afrino (n = 51) and unimproved Nguni sheep (n = 30). Linkage disequilibrium (r2) averaged 0.16 ± 0.021and ranged from 0.09 ± 0.14 and 0.09 ± 0.13 observed in the SA Merino and Dohne Merino respectively to 0.28 ± 0.29 observed in the Blackhead Persian sheep. Chromosome 10 had the highest LD with r2 values ranging from 0.10 ± 0.15 (SA Merino) and 0.12 ± 0.18 (Dohne Merino) to 0.28 ± 0.30 in Blackhead Persian and 0.29 ± 0.30 (SA Mutton Merino). Across the 14 breeds, LD decayed from 0.27 ± 0.30 at 0-10Kb window to 0.02 ± 0.03 at 1000- 2000 Kb window. A progressive decrease in Ne across generations across all populations was observed with effective population size of <500 for all the populations 66 generations ago decreasing to <250, 23 generations ago and well below 100, 13 generations ago. Highest correlations in gametic phase were observed within the 0-10kb window between pairs of Merino and Merino-derived breeds. The highest correlation observed with Nguni sheep was with Dorper sheep (0.33) within the 0-10kb window, which was similar to that observed with Blackhead Persian sheep and Dorper (0.32) again within the same window. The study reported considerable LD persistent over short distance in the South African sheep breeds. The implications of the observed LD, LD decay and consistency in gamete phase on applications such as GWAS, QTL mapping and GS were discussed. It was concluded that the South African sheep population is highly diverse with that diversity found both within and between populations. Genetic differences between fat tailed sheep population, Merino type breeds and the English Dorset were demonstrated as well as low levels of genetic diversity in small and indigenous breeds such as the Nguni, Namaqua Afrikaner and Blackhead Persian. The frequency and patterns of distribution of ROH observed in this study corresponded to the breed history and implied selection pressures exposed to the sheep populations under study. The utility of the OvineSNP50 Beadchip as a genomic tool for the South African Sheep population was also demonstrated. Keywords: Ovis aries; SNP data; genomic structure; production system; selection signatures; RO

IBD sharing patterns as intra-breed admixture indicators in small ruminants

In this study, we investigated how IBD patterns shared between individuals of the same breed could be informative of its admixture level, with the underlying assumption that the most admixed breeds, i.e. the least genetically isolated, should have a much more fragmented genome. We considered 111 goat breeds (i.e. 2501 individuals) and 156 sheep breeds (i.e. 3304 individuals) from Europe, Africa and Asia, for which beadchip SNP genotypes had been performed. We inferred the breed’s level of admixture from: (i) the proportion of the genome shared by breed’s members (i.e. “genetic integrity level” assessed from ADMIXTURE software analyses), and (ii) the “AV index” (calculated from Reynolds’ genetic distances), used as a proxy for the “genetic distinctiveness”. In both goat and sheep datasets, the statistical analyses (comparison of means, Spearman correlations, LM and GAM models) revealed that the most genetically isolated breeds, also showed IBD profiles made up of more shared IBD segments, which were also longer. These results pave the way for further research that could lead to the development of admixture indicators, based on the characterization of intra-breed shared IBD segments, particularly effective as they would be independent of the knowledge of the whole genetic landscape in which the breeds evolve. Finally, by highlighting the fragmentation experienced by the genomes subjected to crossbreeding carried out over the last few generations, the study reminds us of the need to preserve local breeds and the integrity of their adaptive architectures that have been shaped over the centuries.</p

Population genetic structure, linkage disequilibrium and effective population size of conserved and extensively raised village chicken populations of Southern Africa

Extensively raised village chickens are considered a valuable source of biodiversity, with genetic variability developed over thousands of years that ought to be characterised and utilized. Surveys that can reveal a population’s genetic structure and provide an insight into its demographic history will give valuable information to manage and conserve important indigenous animal genetic resources. This study reports population diversity and structure, linkage disequilibrium and effective population sizes of Southern African village chickens and conservation flocks from South Africa. DNA samples from 312 chickens from South African village and conservation flocks (n =146), Malawi (n =30) and Zimbabwe (n =136) were genotyped using the Illumina iSelect chicken SNP60K BeadChip. Population genetic structure analysis distinguished the four conservation flocks from the village chicken populations. Of the four flocks, the Ovambo clustered closer to the village chickens particularly those sampled from South Africa. Clustering of the village chickens followed a geographic gradient whereby South African chickens were closer to those from Zimbabwe than to chickens from Malawi. Different conservation flocks seemed to have maintained different components of the ancestral genomes with a higher proportion of village chicken diversity found in the Ovambo population. Overall population LD averaged over chromosomes ranged from 0.03 ± 0.07 to 0.58 ± 0.41 and averaged 0.15 ± 0.16. Higher LD, ranging from 0.29-0.36, was observed between SNP markers that were less than 10kb apart in the conservation flocks. LD in the conservation flocks steadily decreased to 0.15 (PK) and 0.24 (VD) at SNP marker interval of 500kb. Genomewide LD decay in the village chickens from Malawi, Zimbabwe and South Africa followed a similar trend as the conservation flocks although the mean LD values for the investigated SNP intervals were lower. The results suggest low effective population sizes particularly in th

Carcass Quality Profiles and Associated Genomic Regions of South African Goat Populations Investigated Using Goat SNP50K Genotypes

Carcass quality includes a battery of essential economic meat traits that play a significant role in influencing farmer breed preferences. A preliminary study was undertaken to investigate the carcass quality and the associated genomic regions in a small nucleus of animals that are representative of South African goat genetic resources. Samples of the South African Boer (n = 14), Northern Cape Speckled (n = 14), Eastern Cape Xhosa Lob ear (n = 12), Nguni/Mbuzi (n = 13), and Village (n = 20) were genotyped using the Illumina goat SNP50K and were phenotyped for carcass quality traits. SA Boer goats had heavier warm and cold carcass weights (17.2 &plusmn; 2.3 kg and 16.3 &plusmn; 2.3 kg). Pella village goats raised under an intensive system had significantly (p &lt; 0.05) heavier warm and cold carcass weights (9.9 &plusmn; 1.1 kg and 9.2 &plusmn; 1.2 kg) compared to the village goats that are raised extensively (9.1 &plusmn; 2.0 kg and 8.4 &plusmn; 1.9). A total of 40 SNPs located on chromosomes 6, 10, 12, 13, 19, and 21 were significantly associated with carcass traits at (&minus;log10 [p &lt; 0.05]). Candidate genes that were associated with carcass characteristics (GADD45G, IGF2R, GAS1, VAV3, CAPN8, CAPN7, CAPN2, GHSR, COLQ, MRAS, and POU1F1) were also observed. Results from this study will inform larger future studies that will ultimately find use in breed improvement programs

SA_Goatpopulation_2017

South African indigenous goat population genotyping data

R-Codes_Mdladlaet al

R codes used for RDA and geographic plot of ADMIXTUR

Linkage Disequilibrium, Haplotype Block Structures, Effective Population Size and Genome-Wide Signatures of Selection of Two Conservation Herds of the South African Nguni Cattle

The Nguni cattle of South Africa are a Sanga breed, characterized by many eco-types and research populations that have been established in an effort to conserve the diversity within the breed. The aim of this study was to investigate the overall genetic diversity as well as similarities and differences within and between two conservation herds of the South African Nguni Cattle. Mean LD (r2) estimates were 0.413 &plusmn; 0.219 for Bartlow Combine and 0.402 &plusmn; 0.209 for Kokstad. Genome-wide average LD (r2) decreased with increasing genetic marker distance for both populations from an average of 0.76 &plusmn; 0.28 and 0.77 &plusmn; 0.27 at 0&ndash;1 kb bin to 0.31 &plusmn; 0.13 and 0.32 &plusmn; 0.13 at 900&ndash;1000 kb bin in Bartlow Combine and Kokstad populations, respectively. Variation in LD levels across autosomes was observed in both populations. The results showed higher levels of LD than previously reported in Nguni field populations and other South African breeds, especially at shorter marker distances of less than 20 kb. A total number of 77,305 and 66,237 haplotype blocks covering a total of 1570.09 Mb (61.99% genome coverage) and 1367.42 Mb (53.96% genome coverage) were detected in Bartlow Combine and Kokstad populations, respectively. A total of 18,449 haploblocks were shared between the two populations while 58,856 and 47,788 haploblocks were unique to Bartlow Combine and Kokstad populations, respectively. Effective population size (Ne) results demonstrated a rapid decrease in Ne across generations for both Bartlow Combine and Kokstad conservation herds. Two complementary methods, integrated haplotype score (iHS) and Extend Haplotype Homozygosity Test (XP-EHH), were implemented in this study to detect the selection signatures in the two herds. A total of 553 and 166 selected regions were identified in Bartlow Combine and Kokstad populations, respectively. DAVID and GO terms analysis of the regions under selection reported genes/QTLs associated with fertility, carcass weight, coat colour, immune response, and eye area pigmentation. Some genes, such as HCAR1, GNAI1, PIK3R3, WNT3, RAB5A, BOLA-N (Class IB MHC Antigen QA-2-Related), BOLA (Class IB MHC Antigen QA-2-Related), and Rab-8B, etc., were found in regions under selection in this study. Overall, the study implied reduced genetic diversity in the two herds calling for corrective measures to maintain the diversity of the South African Nguni cattle. This study presented a comprehensive analysis of the genomic architecture of South African Nguni cattle populations, providing essential genetic information of utility in the management of conservation flocks

Genetic Diversity of South African Indigenous Goat Population from Four Provinces Using Genome-Wide SNP Data

Genome-wide assessments of the genetic landscape of Farm Animal Genetic Resources (FAnGR) are key to developing sustainable breed improvements. Understanding the FAnGR adaptation to different environments and supporting their conservation programs from community initiative to national policymakers is very important. The objective of the study was to investigate the genetic diversity and population structure of communal indigenous goat populations from four provinces of South Africa. Communal indigenous goat populations from the Free State (FS) (n = 24), Gauteng (GP) (n = 28), Limpopo (LP) (n = 30), and North West (NW) (n = 35) provinces were genotyped using the Illumina Goats SNP50 BeadChip. An Illumina Goats SNP50 BeadChip data from commercial meat-type breeds: Boer (n = 33), Kalahari Red (n = 40), and Savanna (n = 31) was used in this study as reference populations. The Ho revealed that the genetic diversity of a population ranged between 0.39 &plusmn; 0.11 Ho in LP to 0.42 &plusmn; 0.09 Ho in NW. Analysis of molecular variance revealed variations of 3.39% (p &lt; 0.0001) and 90.64% among and within populations, respectively. The first two Principal Component Analyses (PCAs) revealed a unique Limpopo population separated from GP, FS, and NW communal indigenous goat populations with high levels of admixture with commercial goat populations. There were unique populations of Kalahari and Savanna that were observed and admixed individuals. Marker FST (Limpopo versus commercial goat populations) revealed 442 outlier single nucleotide polymorphisms (SNPs) across all chromosomes, and the SNP with the highest FST value (FST = 0.72; chromosome 8) was located on the UHRF2 gene. Population differentiation tests (PCAdapt) revealed PC2 as optimal and five outlier SNPs were detected on chromosomes 10, 15, 20, and 21. The study revealed that the SNPs identified by the first two principal components show high FST values in LP communal goat populations and allowed us to identify candidate genes which can be used in the development of breed selection programs to improve this unique LP population and other communal goat population of FS, GP, and NW, and find genetic factors contributing to the adaptation to harsh environments. Effective management and utilization of South African communal indigenous goat populations is important, and effort should be made to maintain unique genetic resources for conservation

Breed ancestry, divergence, admixture, and selection patterns of the Simbra crossbreed

In this study, we evaluated an admixed South African Simbra crossbred population, as well as the Brahman (Indicine) and Simmental (Taurine) ancestor populations to understand their genetic architecture and detect genomic regions showing signatures of selection. Animals were genotyped using the Illumina BovineLD v2 BeadChip (7K). Genomic structure analysis confirmed that the South African Simbra cattle have an admixed genome, composed of 5/8 Taurine and 3/8 Indicine, ensuring that the Simbra genome maintains favorable traits from both breeds. Genomic regions that have been targeted by selection were detected using the linkage disequilibrium-based methods iHS and Rsb. These analyses identified 10 candidate regions that are potentially under strong positive selection, containing genes implicated in cattle health and production (e.g., TRIM63, KCNA10, NCAM1, SMIM5, MIER3, and SLC24A4). These adaptive alleles likely contribute to the biological and cellular functions determining phenotype in the Simbra hybrid cattle breed. Our data suggested that these alleles were introgressed from the breed’s original indicine and taurine ancestors. The Simbra breed thus possesses derived parental alleles that combine the superior traits of the founder Brahman and Simmental breeds. These regions and genes might represent good targets for ad-hoc physiological studies, selection of breeding material and eventually even gene editing, for improved traits in modern cattle breeds. This study represents an important step toward developing and improving strategies for selection and population breeding to ultimately contribute meaningfully to the beef production industry.ARC, Technology Innovation Agency (TIA) and Beef Genomics Project (BGP).http://frontiersin.org/Geneticspm2021BiochemistryGeneticsMicrobiology and Plant Patholog