Genetic diversity evolution in the Mexican Charolais cattle population.

OBJECTIVE: The aim was to characterize the genetic diversity evolution of the registered Mexican Charolais cattle population by pedigree analysis. METHODS: Data consisted of 331,390 pedigree records of animals born from 1934 to 2018. Average complete generation equivalent, generation interval, effective population size (Ne), and effective numbers of founders (fe), ancestors (fa), and founder genomes (Ng) were calculated for seven five-year periods. The inbreeding coefficient was calculated per year of birth, from 1984 to 2018, whereas the gene contribution of the most influential ancestors was calculated for the latter period. RESULTS: Average complete generation equivalent consistently increased across periods, from 4.76, for the first period (1984 through 1988), to 7.86, for the last period (2014 through 2018). The inbreeding coefficient showed a relative steadiness across the last seventeen years, oscillating from 0.0110 to 0.0145. During the last period, the average generation interval for the father-offspring pathways was nearly 1 yr. longer than that of the mother-offspring pathways. The effective population size increased steadily since 1984 (105.0) and until 2013 (237.1), but showed a minor decline from 2013 to 2018 (233.2). The population displayed an increase in the fa since 1984 and until 2008; however, showed a small decrease during the last decade. The effective number of founder genomes increased from 1984 to 2003, but revealed loss of genetic variability during the last fifteen years (from 136.4 to 127.7). The fa:fe ratio suggests that the genetic diversity loss was partially caused by formation of genetic bottlenecks in the pedigree; in addition, the Ng:fa ratio indicates loss of founder alleles due to genetic drift. The most influential ancestor explained 1.8% of the total genetic variability in the progeny born from 2014 to 2018. CONCLUSION: Inbreeding, Ne, fa, and Ng are rather beyond critical levels; therefore, the current genetic status of the population is not at risk.

Genome-Wide Association Study Reveals Candidate Genes for Litter Size Traits in Pelibuey Sheep.

The Pelibuey sheep has adaptability to climatic variations, resistance to parasites, and good maternal ability, whereas some ewes present multiple births, which increases the litter size in farm sheep. The litter size in some wool sheep breeds is associated with the presence of mutations, mainly in the family of the transforming growth factor ß (TGF-ß) genes. To explore genetic mechanisms underlying the variation in litter size, we conducted a genome-wide association study in two groups of Pelibuey sheep (multiparous sheep with two lambs per birth vs. uniparous sheep with a single lamb at birth) using the OvineSNP50 BeadChip. We identified a total of 57 putative SNPs markers (p < 3.0 × 10-3, Bonferroni correction). The candidate genes that may be associated with litter size in Pelibuey sheep are CLSTN2, MTMR2, DLG1, CGA, ABCG5, TRPM6, and HTR1E. Genomic regions were also identified that contain three quantitative trait loci (QTLs) for aseasonal reproduction (ASREP), milk yield (MY), and body weight (BW). These results allowed us to identify SNPs associated with genes that could be involved in the reproductive process related to prolificacy.

Morphostructural Characterization of the Black Creole Goat Raised in Central Mexico, a Currently Threatened Zoogenetic Resource.

In order to evaluate the morphostructural variability of the Black Creole goat (BCG), the present study was carried out in a population of 226 animals from eight localities and 14 morphometric variables were taken. Descriptive statistics for the variables were obtained and 10 of these presented variation coefficients of less than 10%. The degree of harmony in the morphology of the population was determined by the number of positive correlations with significant differences (p < 0.05), including a correlation test using Spearman's method. In order to reduce the matrix of variables, a principal components analysis was performed, and it was evaluated based on Kaiser's criteria (eigenvalue > 1). Finally, a hierarchical analysis of conglomerates using Ward's method was performed using the Euclidean distance to evaluate the distances among localities. Morphometric variables were also included to visualize the relationship among the localities and their average per variable. The results showed that the animals evaluated presented a certain degree of homogeneity and maintained a highly harmonic model. The BCG population showed a high aptitude for milk production, which confirmed the zootechnical purpose of the breed. The BCG populations evaluated maintain similar morphostructural profiles specific to them that can distinguish this population from other animal breeds.

Estimates of missing heritability for complex traits in Brown Swiss cattle.

BACKGROUND: Genomic selection estimates genetic merit based on dense SNP (single nucleotide polymorphism) genotypes and phenotypes. This requires that SNPs explain a large fraction of the genetic variance. The objectives of this work were: (1) to estimate the fraction of genetic variance explained by dense genome-wide markers using 54 K SNP chip genotyping, and (2) to evaluate the effect of alternative marker-based relationship matrices and corrections for the base population on the fraction of the genetic variance explained by markers. METHODS: Two alternative marker-based relationship matrices were estimated using 35 706 SNPs on 1086 dairy bulls. Both pedigree- and marker-based relationship matrices were fitted simultaneously or separately in an animal model to estimate the fraction of variance not explained by the markers, i.e. the fraction explained by the pedigree. The phenotypes considered in the analysis were the deregressed estimated breeding values (dEBV) for milk, fat and protein yield and for somatic cell score (SCS). RESULTS: When dEBV were not sufficiently accurate (50 or 70%), the estimated fraction of the genetic variance explained by the markers was around 65% for yield traits and 45% for SCS. Scaling marker genotypes with locus-specific frequencies of heterozygotes slightly increased the variance explained by markers, compared with scaling with the average frequency of heterozygotes across loci. The estimated fraction of the genetic variance explained by the markers using separately both relationships matrices followed the same trends but the results were underestimated. With less accurate dEBV estimates, the fraction of the genetic variance explained by markers was underestimated, which is probably an artifact due to the dEBV being estimated by a pedigree-based animal model. CONCLUSIONS: When using only highly accurate dEBV, the proportion of the genetic variance explained by the Illumina 54 K SNP chip was approximately 80% for Brown Swiss cattle. These results depend on the SNP chip used and the family structure of the population, i.e. more dense SNPs and closer family relationships are expected to result in a higher fraction of the variance explained by the SNPs.