Abstract

Both natural and artificial selection are among the main driving forces shaping genetic variation across the genome of livestock species. Selection typically leaves signatures in the genome, which are often characterized by high genetic differentiation across breeds and/or a strong reduction in genetic diversity in regions associated with traits under intense selection pressure. In this study, we evaluated selection signatures and genomic inbreeding coefficients, FROH, based on runs of homozygosity (ROH), in six Ugandan goat breeds: Boer (n = 13), and the indigenous breeds Karamojong (n = 15), Kigezi (n = 29), Mubende (n = 29), Small East African (n = 29), and Sebei (n = 29). After genotyping quality control, 45,294 autosomal single nucleotide polymorphisms (SNPs) remained for further analyses. A total of 394 and 6 breed-specific putative selection signatures were identified across all breeds, based on marker-specific fixation index (FST-values) and haplotype differentiation (hapFLK), respectively. These regions were enriched with genes involved in signaling pathways associated directly or indirectly with environmental adaptation, such as immune response (e.g., IL10RB and IL23A), growth and fatty acid composition (e.g., FGF9 and IGF1), and thermo-tolerance (e.g., MTOR and MAPK3). The study revealed little overlap between breeds in genomic regions under selection and generally did not display the typical classic selection signatures as expected due to the complex nature of the traits. In the Boer breed, candidate genes associated with production traits, such as body size and growth (e.g., GJB2 and GJA3) were also identified. Furthermore, analysis of ROH in indigenous goat breeds showed very low levels of genomic inbreeding (with the mean FROH per breed ranging from 0.8% to 2.4%), as compared to higher inbreeding in Boer (mean FROH = 13.8%). Short ROH were more frequent than long ROH, except in Karamojong, providing insight in the developmental history of these goat breeds. This study provides insights into the effects of long-term selection in Boer and indigenous Ugandan goat breeds, which are relevant for implementation of breeding programs and conservation of genetic resources, as well as their sustainable use and management.

Highlights

  • Goats are among the most important livestock species in developing countries, such as Uganda, playing a significant socio-economic, nutritional and cultural role in smallholder production systems (MAAIF, 2011)

  • While exotic breeds are subjected to more intense artificial selection, it is expected that the effect of natural selection is more apparent in the indigenous breeds and has played an important role in their development

  • We focused on length classes from 2 to 16 Mb to investigate more ancient inbreeding (2 and 16 Mb are the expected lengths of runs of homozygosity (ROH) derived from common ancestors 25 and 3 generations ago, respectively) and >16 Mb to assess more recent inbreeding

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Summary

Introduction

Goats are among the most important livestock species in developing countries, such as Uganda, playing a significant socio-economic, nutritional and cultural role in smallholder production systems (MAAIF, 2011). The total goat population in Uganda is estimated to consist of over million animals, predominantly from indigenous breeds (98%) and a small proportion (2%) from exotic breeds (MAAIF and UBOS, 2009; UBOS, 2015). While exotic breeds are subjected to more intense artificial selection, it is expected that the effect of natural selection (i.e., adaptation to the specific environment) is more apparent in the indigenous breeds and has played an important role in their development. Based on this hypothesis, it is expected that indigenous breeds will tend to exhibit resistance to gastro-intestinal parasites and local diseases, tolerance to heat, water scarcity and ability to use low quality fodder. Adaptation is a complex trait that involves many biological processes and quantitative trait loci with each having a small but cumulative effect on the overall expression of the phenotype (Kim et al, 2016; Yang et al, 2016; Mwacharo et al, 2017)

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