Dataset Information

Genetic diversity, breed composition and admixture of Kenyan domestic pigs.

ABSTRACT: The genetic diversity of African pigs, whether domestic or wild has not been widely studied and there is very limited published information available. Available data suggests that African domestic pigs originate from different domestication centers as opposed to international commercial breeds. We evaluated two domestic pig populations in Western Kenya, in order to characterize the genetic diversity, breed composition and admixture of the pigs in an area known to be endemic for African swine fever (ASF). One of the reasons for characterizing these specific populations is the fact that a proportion of indigenous pigs have tested ASF virus (ASFv) positive but do not present with clinical symptoms of disease indicating some form of tolerance to infection. Pigs were genotyped using either the porcine SNP60 or SNP80 chip. Village pigs were sourced from Busia and Homabay counties in Kenya. Because bush pigs (Potamochoerus larvatus) and warthogs (Phacochoerus spp.) are known to be tolerant to ASFv infection (exhibiting no clinical symptoms despite infection), they were included in the study to assess whether domestic pigs have similar genomic signatures. Additionally, samples representing European wild boar and international commercial breeds were included as references, given their potential contribution to the genetic make-up of the target domestic populations. The data indicate that village pigs in Busia are a non-homogenous admixed population with significant introgression of genes from international commercial breeds. Pigs from Homabay by contrast, represent a homogenous population with a "local indigenous' composition that is distinct from the international breeds, and clusters more closely with the European wild boar than African wild pigs. Interestingly, village pigs from Busia that tested negative by PCR for ASFv genotype IX, had significantly higher local ancestry (>54%) compared to those testing positive, which contained more commercial breed gene introgression. This may have implication for breed selection and utilization in ASF endemic areas. A genome wide scan detected several regions under preferential selection with signatures for pigs from Busia and Homabay being very distinct. Additionally, there was no similarity in specific genes under selection between the wild pigs and domestic pigs despite having some broad areas under similar selection signatures. These results provide a basis to explore possible genetic determinants underlying tolerance to infection by ASFv genotypes and suggests multiple pathways for genetically mediated ASFv tolerance given the diversity of selection signatures observed among the populations studied.

SUBMITTER: Mujibi FD

PROVIDER: S-EPMC5777648 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Genetic diversity, breed composition and admixture of Kenyan domestic pigs.

Mujibi Fidalis Denis FD Okoth Edward E Cheruiyot Evans K EK Onzere Cynthia C Bishop Richard P RP Fèvre Eric M EM Thomas Lian L Masembe Charles C Plastow Graham G Rothschild Max M

PloS one 20180122 1

The genetic diversity of African pigs, whether domestic or wild has not been widely studied and there is very limited published information available. Available data suggests that African domestic pigs originate from different domestication centers as opposed to international commercial breeds. We evaluated two domestic pig populations in Western Kenya, in order to characterize the genetic diversity, breed composition and admixture of the pigs in an area known to be endemic for African swine fev ...[more]

PMID: 29357367

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Project description:Background: The use of breed-informative genetic markers, specifically coding Single Nucleotide Polymorphisms (SNPs), is crucial for breed traceability, authentication of meat and dairy products, and the preservation and improvement of pig breeds. By identifying breed informative markers, we aimed to gain insights into the genetic mechanisms that influence production traits, enabling informed decisions in animal management and promoting sustainable pig production to meet the growing demand for animal products. Methods: Our dataset consists of 300 coding SNPs genotyped from three Italian commercial pig populations: Landrace, Yorkshire, and Duroc. Firstly, we analyzed the genetic diversity among the populations. Then, we applied a discriminant analysis of principal components to identify the most informative SNPs for discriminating between these populations. Lastly, we conducted a functional enrichment analysis to identify the most enriched pathways related to the genetic variation observed in the pig populations. Results: The alpha diversity indexes revealed a high genetic diversity within the three breeds. The higher proportion of observed heterozygosity than expected revealed an excess of heterozygotes in the populations that was supported by negative values of the fixation index (FIS) and deviations from the Hardy-Weinberg equilibrium. The Euclidean distance, the pairwise FST, and the pairwise Nei's GST genetic distances revealed that Yorkshire and Landrace breeds are genetically the closest, with distance values of 2.242, 0.029, and 0.033, respectively. Conversely, Landrace and Duroc breeds showed the highest genetic divergence, with distance values of 2.815, 0.048, and 0.052, respectively. We identified 28 significant SNPs that are related to phenotypic traits and these SNPs were able to differentiate between the pig breeds with high accuracy. The Functional Enrichment Analysis of the informative SNPs highlighted biological functions related to DNA packaging, chromatin integrity, and the preparation of DNA into higher-order structures. Conclusion: Our study sheds light on the genetic underpinnings of phenotypic variation among three Italian pig breeds, offering potential insights into the mechanisms driving breed differentiation. By prioritizing breed-specific coding SNPs, our approach enables a more focused analysis of specific genomic regions relevant to the research question compared to analyzing the entire genome.

Project description:A variety of statistical methods, such as admixture models, have been used to estimate genomic breed composition (GBC). These methods, however, tend to produce non-zero components to reference breeds that shared some genomic similarity with a test animal. These non-essential GBC components, in turn, offset the estimated GBC for the breed to which it belongs. As a result, not all purebred animals have 100% GBC of their respective breeds, which statistically indicates an elevated false-negative rate in the identification of purebred animals with 100% GBC as the cutoff. Otherwise, a lower cutoff of estimated GBC will have to be used, which is arbitrary, and the results are less interpretable. In the present study, three admixture models with regularization were proposed, which produced sparse solutions through suppressing the noise in the estimated GBC due to genomic similarities. The regularization or penalty forms included the L1 norm penalty, minimax concave penalty (MCP), and smooth clipped absolute deviation (SCAD). The performances of these regularized admixture models on the estimation of GBC were examined in purebred and composite animals, respectively, and compared to that of the non-regularized admixture model as the baseline model. The results showed that, given optimal values for ?, the three sparsely regularized admixture models had higher power and thus reduced the false-negative rate for the breed identification of purebred animals than the non-regularized admixture model. Of the three regularized admixture models, the two with a non-convex penalty outperformed the one with L1 norm penalty. In the Brangus, a composite cattle breed, estimated GBC were roughly comparable among the four admixture models, but all the four models underestimated the GBC for these composite animals when non-ancestral breeds were included as the reference. In conclusion, the admixture models with sparse regularization gave more parsimonious, consistent and interpretable results of estimated GBC for purebred animals than the non-regularized admixture model. Nevertheless, the utility of regularized admixture models for estimating GBC in crossbred or composite animals needs to be taken with caution.

Dataset Information

Genetic diversity, breed composition and admixture of Kenyan domestic pigs.

Publications

Genetic diversity, breed composition and admixture of Kenyan domestic pigs.

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