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Background  More than 90 percent of cattle in Tanzania belong to the indigenous Tanzania Short Horn Zebu (TSZ) population which has been classified into 12 strains based on historical evidence, morphological characteristics, and geographic distribution. However, specific genetic information of each TSZ population has been lacking and has caused difficulties in designing programs such as selection, crossbreeding, breed improvement or conservation. This study was designed to evaluate the genetic structure, assess genetic relationships, and to identify signatures of selection among cattle of Tanzania with the main goal of understanding genetic relationship, variation and uniqueness among them.    Methodology/Principal findings  The Illumina  Bos indicus  SNP 80K BeadChip was used to genotype genome wide SNPs in 168 DNA samples obtained from three strains of TSZ cattle namely Maasai, Tarime and Sukuma as well as two comparative breeds; Boran and Friesian. Population structure and signatures of selection were examined using principal component analysis (PCA), admixture analysis, pairwise distances (F ST ), integrated haplotype score (iHS), identical by state (IBS) and runs of homozygosity (ROH). There was a low level of inbreeding (F~0.01) in the TSZ population compared to the Boran and Friesian breeds. The analyses of F ST , IBS and admixture identified no considerable differentiation between TSZ trains. Importantly, common ancestry in Boran and TSZ were revealed based on admixture and IBD, implying gene flow between two populations. In addition, Friesian ancestry was found in Boran. A few common significant iHS were detected, which may reflect influence of recent selection in each breed or strain.    Conclusions  Population admixture and selection signatures could be applied to develop conservation plan of TSZ cattle as well as future breeding programs in East African cattle.

plos one

Determination of Genetic Structure and Signatures of Selection in Three Strains of Tanzania Shorthorn Zebu, Boran and Friesian Cattle by Genome-Wide SNP Analyses