Mapping genomic regions and genes associated with the fat-tail, an adaptation trait in indigenous sheep

Poster prepared for a share fair, Addis Ababa, May 201

Invited review: Genomic selection for small ruminants in developed countries: how applicable for the rest of the world?

Improved management and use of estimated breeding values in breeding programmes, have resulted in rapid genetic progress for small ruminants (SR) in Europe and other developed countries. The development of single nucleotide polymorphisms chips opened opportunities for genomic selection (GS) in SR in these countries. Initially focused on production traits (growth and milk), GS has been extended to functional traits (reproductive performance, disease resistance and meat quality). The GS systems have been characterized by smaller reference populations compared with those of dairy cattle and consisting mostly of cross- or multi-breed populations. Molecular information has resulted in gains in accuracy of between 0.05 and 0.27 and proved useful in parentage verification and the identification of QTLs for economically important traits. Except for a few established breeds with some degree of infrastructure, the basic building blocks to support conventional breeding programmes in small holder systems are lacking in most developing countries. In these systems, molecular data could offer quick wins in undertaking parentage verification and genetic evaluations using G matrix, and determination of breed composition. The development of next-generation molecular tools has prompted investigations on genome-wide signatures of selection for mainly adaptive and reproduction traits in SR in developing countries. Here, the relevance of the developments and application of GS and other molecular tools in developed countries to developing countries context is examined. Worth noting is that in the latter, the application of GS in SR will not be a ‘one-size fits all’ scenario. For breeds with some degree of conventional genetic improvement, classical GS may be feasible. In small holder systems, where production is key, community-based breeding programmes can provide the framework to implement GS. However, in fragile growth systems, for example those found in marginal environments, innovative GS to maximize adaptive diversity will be required. A cost-benefit analysis should accompany any strategy of implementing GS in these systems

Whole-genome resequencing reveals genomic variation and dynamics in Ethiopian indigenous goats

Ethiopia has about 52 million indigenous goats with marked phenotypic variability, which is the outcome of natural and artificial selection. Here, we obtained whole-genome sequence data of three Ethiopian indigenous goat populations (Arab, Fellata, and Oromo) from northwestern Ethiopia and analyzed their genome-wide genetic diversity, population structure, and signatures of selection. We included genotype data from four other Ethiopian goat populations (Abergelle, Keffa, Gumuz, and Woyto-Guji) and goats from Asia; Europe; and eastern, southern, western, and northern Africa to investigate the genetic predisposition of the three Ethiopian populations and performed comparative genomic analysis. Genetic diversity analysis showed that Fellata goats exhibited the lowest heterozygosity values (Ho = 0.288 ± 0.005 and He = 0.334 ± 0.0001). The highest values were observed in Arab goats (Ho = 0.310 ± 0.010 and He = 0.347 ± 4.35e-05). A higher inbreeding coefficient (FROH = 0.137 ± 0.016) was recorded for Fellata goats than the 0.105 ± 0.030 recorded for Arab and the 0.112 ± 0.034 recorded for Oromo goats. This indicates that the Fellata goat population should be prioritized in future conservation activities. The three goat populations showed the majority (∼63%) of runs of homozygosity in the shorter (100-150 Kb) length category, illustrating ancient inbreeding and/or small founder effects. Population relationship and structure analysis separated the Ethiopian indigenous goats into two distinct genetic clusters lacking phylogeographic structure. Arab, Fellata, Oromo, Abergelle, and Keffa represented one genetic cluster. Gumuz and Woyto-Guji formed a separate cluster and shared a common genetic background with the Kenyan Boran goat. Genome-wide selection signature analysis identified nine strongest regions spanning 163 genes influencing adaptation to arid and semi-arid environments (HOXC12, HOXC13, HOXC4, HOXC6, and HOXC9, MAPK8IP2), immune response (IL18, TYK2, ICAM3, ADGRG1, and ADGRG3), and production and reproduction (RARG and DNMT1). Our results provide insights into a thorough understanding of genetic architecture underlying selection signatures in Ethiopian indigenous goats in a semi-arid tropical environment and deliver valuable information for goat genetic improvement, conservation strategy, genome-wide association study, and marker-assisted breeding.</p