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Patterns of allele frequency differences among domestic cat breeds assessed by a 63K SNP array
Hasan Alhaddad1, Mona Abdi1, Leslie A Lyons2
1Department of Biological Sciences, Kuwait University, Safat, Kuwait.
Abstract:
Cats are ubiquitous companion animals that have been keenly associated with humans for thousands of years and only recently have been intentionally bred for aesthetically appealing coat looks and body forms. The intense selection on single gene phenotypes and the various breeding histories of cat breeds have left different marks on the genomes. Using a previously published 63K Feline SNP array dataset of twenty-six cat breeds, this study utilized a genetic differentiation-based method (di) to empirically identify candidate regions under selection. Defined as three or more overlapping (500Kb) windows of high levels of population differentiation, we identified a total of 205 candidate regions under selection across cat breeds with an average of 6 candidate regions per breed and an average size of 1.5 Mb per candidate region. Using the combined size of candidate regions of each breed, we conservatively estimate that a minimum of ~ 0.1-0.7% of the autosomal genome is potentially under selection in cats. As positive controls and tests of our methodology, we explored the candidate regions of known breed-defining genes (e.g., FGF5 for longhaired breeds) and we were able to detect the genes within candidate regions, each in its corresponding breed. For breed specific exploration of candidate regions under selection, eleven representative candidate regions were found to encompass potential candidate genes for several phenotypes such as brachycephaly of Persian (DLX6, DLX5, DLX2), curled ears of American Curl (MCRIP2, PBX1), and body-form of Siamese and Oriental (ADGRD1), which encourages further molecular investigations. The current assessment of the candidate regions under selection is empiric and detailed analyses are needed to rigorously disentangle effects of demography and population structure from artificial selection.
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