Artificial insemination (AI) has been used as a routine technology globally in the pig production industry since 1930. One of the preferable advantages of AI technology is that the semen of elite boars can be disseminated to the commercial sow population rapidly. Understanding the genetic background of semen traits may help in developing genetic improvement programs of boars by including these traits into the selection index. In this study, we utilized weighted single-step genome-wide association study (wssGWAS) to identify genetic regions and further candidate genes associated with sperm morphology abnormalities (proximal droplet, distal droplet, bent tail, coiled tail, and distal midpiece reflex) in a Duroc boar population. Several genomic regions explained 2.76%–9.22% of the genetic variances for sperm morphology abnormalities were identified. The first three detected QTL regions together explained about 7.65%–25.10% of the total genetic variances of the studied traits. Several genes were detected and considered as candidate genes for each of the traits under study: coiled tail, HOOK1, ARSA, SYCE3, SOD3, GMNN, RBPJ, STIL, and FGF1; bent tail, FGF1, ADIPOR1, ARPC5, FGFR3, PANX1, IZUMO1R, ANKRD49, and GAL; proximal droplet, NSF, WNT3, WNT9B, LYZL6, FGFR1OP, RNASET2, FYN, LRRC6, EPC1, DICER1, FNDC3A, and PFN1; distal droplet, ARSA, SYCE3, MOV10L1, CBR1, KDM6B, TP53, PTBP2, UBR7, KIF18A, ADAM15, FAAH, TEKT3, and SRD5A1; and distal midpiece reflex, OMA1, PFN1, PELP1, BMP2, GPR18, TM9SF2, and SPIN1. GO and KEGG enrichment analysis revealed the potential function of the identified candidate genes in spermatogenesis, testis functioning, and boar spermatozoa plasma membrane activating and maintenance. In conclusion, we detected candidate genes associated with the coiled tail, bent tail, proximal droplet, distal droplet, and distal midpiece reflex in a Duroc boar population using wssGWAS. Overall, these novel results reflect the polygenic genetic architecture of the studied sperm morphology abnormality traits, which may provide knowledge for conducting genomic selection on these traits. The detected genetic regions can be used in developing trait-specific marker assisted selection models by assigning higher genetic variances to these regions. © 2019
