Use of different statistical approaches to study genetic variability of OAR6 in sheep breeds farmed in Italy.

Abstract

Dense marker maps allow for the investigation of genomic regions that differentiate between breeds. In this work, 496 sheep belonging to 20 Italian sheep breeds were genotyped with the Illumina OvineSNP50 BeadChip. After data editing, 2,180 SNP located on chromosome 6 were analyzed with 4 different approaches. I) Fst Outlier Detection (FOD), implemented in the LOSITAN software, based on the comparison between Fst calculated on actual data and expected heterozygosity (He) and Fst under an island model. II) Composite Log-likelihood (CLL), based on calculation of CLL of the observed allelic frequencies across overlapping windows of 9 markers. III) Correspondence analysis (CA). VI) Canonical Discriminant Analysis (CDA). The different approaches were able to identify regions at OAR6 that expressed variation between breeds. Highest values for all statistics were found for a region spanning between 35 and 41 Mb known to harbour BMPR1b and ABCG2 loci. SNPs with a relevant discriminating power between breeds were also found at 76, 96 and 107 Mb, near to KIT, IL8 and SCD5 genes respectively. FOD detected 227 not neutral markers (17 under positive and 210 under balanced selection) using a confidence interval of 0.95. A total of 62 windows out of 242 were significant for CLL (P < 0.01). Several 85 and 135 SNPs exceeded empirical threshold for CA and CDA, respectively. The discriminating power was high for all methods and in general, they revealed a geographical pattern of variation between breeds. Moreover, each method provided specific information. FOD supplied a relatively low number of markers in divergent selection but it was able to identify loci under balanced selection. CA and CDA allowed a decomposition of total variability in different and uncorrelated variables that could be useful for the identification of genes influencing complex traits. The use of different statistical methods to study genetic variability between ethnic groups could provide indications about the adaptation to local conditions as well as the effect of selection