A genomewide association study for average daily gain in Italian Large White pigs

Average daily gain is an important target trait in pig breeding programs. In this study we performed a genomewide association study for ADG in Italian Large White pigs using a selective genotyping approach. Two extreme and divergent groups of Italian Large White pigs (number 190 + 190) were selected among a population of about 10,000 performance tested gilts (EBV for ADG in the 2 groups were -30 +/- 14 g and 81 +/- 12 g, respectively) and genotyped with the Illumina PorcineSNP60 Bead-Chip. Association analysis was performed treating the pigs of the 2 extreme groups as cases and controls after correction for family-based stratification. A total of 127 SNP resulted significantly associated with ADG (P nominal value [P-raw] < 2.0 x 10(-7), P < 0.01 Bonferroni corrected [P-Bonferroni] < 0.01, false discovery rate < 7.76 x 10(-5)). Another 102 SNP were suggestively associated with the target trait (P-raw between 2.0 x 10(-7) and 2.02 x 10(-6), P-Bonferroni < 0.10, false discovery rate < 4.19 x 10(-4)). These SNP were located on all autosomes and on porcine chromosome (SSC) X. The largest number of SNP within this list was on SSC5 (n = 42), SSC7 (34), SSC6 (30), SSC4 (23), and SSC16 (16). These chromosomes were richer in significant or suggestively significant markers than expected (P < 0.001). A quite high number of these SNP (n = 23) were associated with backfat thickness in a previous genomewide association study performed in the same pig population, confirming the negative correlation between the 2 traits. Two or more SNP targeted the same gene: IGSF3 and HS2ST1 (SSC4), OTOGL (SSC5), FTO region (SSC6), and MYLK4 and MCUR1 (SSC7). Other regions that were associated with ADG in previous candidate gene studies (e.g., MC4R on SSC1, IGF2 and LDHA on SSC2, MUC4 on SSC13) 1) included markers with P-raw < 0.01 that, however, did not pass the stringent threshold of significance adopted in this study or 2) could not be tested because not assigned to the Sscrofa 10.2 genome version. Functional annotation of the significant regions using Gene Ontology suggested that many and complex processes at different levels are involved in affecting ADG, indicating the complexity of the genetic factors controlling this ultimate phenotype. The obtained results may contribute to understand the genetic mechanisms determining ADG that could open new perspectives to improve selection efficiency in this breed.