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Simple Summary: Maintaining the flexibility of the genetic resources of native animals to face local environment constraints is still a major challenge. In Tunisia, the Noire de Thibar breed is a local sheep, typically with black coloration, known for its ability to tolerate "hypericum perforatum", which causes skin photosensitization in white colored sheep. The goal of this study was to perform a genome scan, by considering genotyping-by-sequencing (GBS) markers that were genotyped in divergent coat colored sheep (black vs. white) to identify strong, and recent, artificial selection that is involved in skin-photosensitization. Interestingly, the genomic differentiation analysis identified F ST markers within genomic regions containing key pigmentation and photosensitivity related-genes. These findings help in understanding the background of coat color genetics and its potential role in adaptation to local environment constraints.Abstract: The Tunisian Noire de Thibar sheep breed is a composite breed, recently selected to create animals that are uniformly black in order to avoid skin photosensitization after the ingestion of toxic "hypericum perforatum" weeds, which causes a major economic loss to sheep farmers. We assessed genetic differentiation and estimated marker F ST using genotyping-by-sequencing (GBS) data in black (Noire de Thibar) and related white-coated (Queue fine de l'ouest) sheep breeds to identify signals of artificial selection. The results revealed the selection signatures within candidate genes related to coat color, which are assumed to be indirectly involved in the mechanism of photosensitization in sheep. The identified genes could provide important information for molecular breeding.

In developing countries, the use of simple and cost‐efficient molecular technology is crucial for genetic characterization of local animal resources and better development of conservation strategies. The genotyping by sequencing (GBS) technique, also called restriction enzyme‐ reduced representational sequencing, is an efficient, cost‐effective method for simultaneous discovery and genotyping of many markers. In the present study, we applied a two‐enzyme GBS protocol (PstI/MspI) to discover and genotype SNP markers among 197 Tunisian sheep samples. A total of 100 333 bi‐allelic SNPs were discovered and genotyped with an SNP call rate of 0.69 and mean sample depth 3.33. The genomic relatedness between 183 samples grouped the samples perfectly to their populations and pointed out a high genetic relatedness of inbred subpopulation reflecting the current adopted reproductive strategies. The genome‐wide association study contrasting fat vs. thin‐tailed breeds detected 41 significant variants including a peak positioned on OAR20. We identified FOXC1, GMDS, VEGFA, OXCT1, VRTN and BMP2 as the most promising for sheep tail‐type trait. The GBS data have been useful to assess the population structure and improve our understanding of the genomic architecture of distinctive characteristics shaped by selection pressure in local sheep breeds. This study successfully investigates a cost‐efficient method to discover genotypes, assign populations and understand insights into sheep adaptation to arid area. GBS could be of potential utility in livestock species in developing/emerging countries.

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