the objectives of this study were to identify genomic regions by bayesian methods (bayesa, BayesB, or BayesN) that fit fixed-length haplotypes or SNPs using GenSel. Covariates for haplo-type alleles of five lengths (125, 250, 500 kb, 1 or 2 Mb) were generated, and rare haplotypes were removed at three thresholds (1, 5, or 10%). Subsequently, we performed gene network analyses to investigate the biological processes shared by genes that were identified for the same across traits. Genotypes at 41,034 SNPs that were common on OvineSNP50 panel were phased for 751 Scottish Blackface (SBF) lambs. This is the first study to quantify the proportion of genetic variance us-ing haplotypes across the whole genome in an SBF population. The genetic variance explained of haplotype-based GWAS was higher than that of SNP-based GWAS in across traits studied. In this population, fitting 500kb haplotypes with a 1% frequency threshold resulted in the highest propor-tion of genetic variance explained for nematode resistance and fitting 2Mb haplotypes with a 10% frequency threshold improved genetic variance explained for body weight comparable to fitting SNPs by BayesB. Candidate genes, includingCXCR4, STAT4, CCL1, CCL2, CCL3, CCL5, CCL8, CCL16, CCL18, CARMIL2, and HSPA14were identified for nematode resistance and ADH5, PP-P3CA,and FABP4 for body weight traits. Network analysis provided annotation results linking to all identified candidate genes. This study supported previous results from GWAS of nematode resistance and body weight and revealed additional regions in the ovine genome associated with these economically important traits. These results suggest that network analysis can provide new information regarding biological mechanisms and genes leading to complex phenotypes, like nem-atode resistance and body weight of lamb.
