Genome association analyses have been successful in identifying quantitative trait loci (QTLs) for pig body weights measured at a single age. However, when considering the whole weight trajectories over time in the context of genome association analyses, it is important to look at the markers that affect growth curve parameters. The easiest way to consider them is via the two-step method, in which the growth curve parameters and marker effects are estimated separately, thereby resulting in a reduction of the statistical power and the precision of estimates. One efficient solution is to adopt nonlinear mixed models (NMM), which enables a joint modeling of the individual growth curves and marker effects. Our aim was to propose a genome association analysis for growth curves in pigs based on NMM as well as to compare it with the traditional two-step method. In addition, we also aimed to identify the nearest candidate genes related to significant SNP (single nucleotide polymorphism) markers. The NMM presented a higher number of significant SNPs for adult weight (A) and maturity rate (K), and provided a direct way to test SNP significance simultaneously for both the A and K parameters. Furthermore, all significant SNPs from the two-step method were also reported in the NMM analysis. The ontology of the three candidate genes (SH3BGRL2, MAPK14, and MYL9) derived from significant SNPs (simultaneously affecting A and K) allows us to make inferences with regards to their contribution to the pig growth process in the population studied.

Traditional selection programs for dairy cattle, based on quantitative principles, have worked well and allowed strong selection processes in the world over many decades. The objectives of this work were to estimate linkage disequilibrium (LD) levels at varying SNPs densities, to evaluate the effective population size of Holstein cattle, to characterize runs of homozygosity (ROH) distribution through Holstein cattle from Nariño and, to estimate and compare inbreeding coefficient (F) based on genomic markers information, runs of homozygosity (FROH), genomic relationship matrix (FGRM), and excess of homozygous (FSNP). After quality control, the dataset used was composed of 606 Holstein animals and 22200 SNP markers. PLINK program was used to identify LD, Ne, ROH segment and FROH and FSNP, FGRM was calculated with BLUPF90 family of programs. The average of r2 in all chromosomes was 0.011, the highest r2 was found in BTA3 (0.0323), and the lowest in BTA12 (0.0039). 533 ROH segments were identified in 319 animals; findings obtained in this study suggest that on average 0,28% of Holstein genome is autozygous. Total length of ROH was composed mostly of small segments (ROH1-4Mb and ROH4-8Mb). These segments accounted for approximately 96%, while larger ROH (ROH>8Mb) were 3.37% of all ROH detected. Inbreeding averages FROH, FSNP and FGRM methodologies were 0.28%, 3.11% and 3.36% respectively. The Pearson’s correlation among these different F values was: 0.49 (FROH-FSNP), 0.25 (FROH-FGRM), 0.22 (FSNP-FGRM). The distribution of ROH shared regions identified on 19 autosome chromosomes, cover a relevant number of genes inside these ROH. Our result evidenced lowest LD extension levels compared with other Holstein populations; inbreeding results suggest that FGRM and FSNP may be useful estimators of individual autozygosity in Holstein from Colombia. Genes related with production and reproduction were found, but the most important are the two that may be related to adaptation to Colombian high tropics. This work is a pioneer and be the starting point for programs of genetic improvement and genomic population studies in the country and mainly in high tropic areas where the dairy breeds have an important production.

In Colombia, different dairy breeds were introduced from Europe and the United States, which underwent different crossing and selection processes that generated specific qualities or differences and which likely have their own genomic structure. To characterize genetic diversity, population structure, and admixture, we used genotypes from 23,182 autosomal single nucleotide polymorphisms (SNPs) of 130 animals representing four dairy cattle breed groups from Nariño. In addition, we merged genotypes from 43,043 autosomal SNPs, from 137 animals from the Decker database (Decker et al., 2014) (DRYAD doi:10.5061/dryad.th092). After the quality control process of pruning the merged dataset, we were left with 7,475 autosomal SNPs shared by both databases of Nariño (127 samples) and Decker (135 samples). Genetic diversity levels were moderate in all breeds (average observed heterozygosity = 0.40). Based on the fixation index values, we conclude that Brahman individuals were more differentiated than the taurine breeds (-0.374 to 0.076 for Brown Swiss). Pairs between taurine breeds showed low genetic differentiation (0.011-0.479). Principal component analysis revealed that in both the Nariño and Decker databases, the taurine formed the most compact cluster compared with other breeds known not to share the same ancestry, and Jersey, Brown Swiss, and Normand individuals exhibited high similarity with Holstein individuals. Hierarchical cluster analysis with Admixture revealed that Brahman, Jersey, Normand, and Holstein from the Decker databases most of which were clustered together with the dairy breeds of the Nariño highland tropics are not able to create different groups, thus having greater similarity with each other. This can be explained by the crosses made by farmers to increase milk production volume, always based on the Holstein breed with semen of bulls from America and Canada. Detrimental impacts due to intensive selection might cause some specific traits from the region to be fixed in the offspring, which can influence their adaptive capacity to the highland tropics.