Background: Quantitative trait loci (QTL) are genomic regions that influence essential traits in livestock. Understanding QTL distribution and density across species’ genomes is crucial for animal genetics research. Objectives: This study explored the QTLome of cattle, pigs, sheep, and chickens by analyzing QTL distribution and evaluating the correlation between QTL, gene density, and chromosome size with the aim to identify QTL-enriched genomic regions. Methods: Data from 211,715 QTL (1994–2021) were retrieved from the AnimalQTLdb and analyzed using R software v4.2.1. Unique QTL annotations were identified, and redundant or inconsistent data were removed. Statistical analyses included Pearson correlations and binomial, hypergeometric, and bootstrap-based enrichment tests. Results: QTL densities per Mbp were 10 for bovine, 4 for pig, 1 for sheep, and 3 for chicken genomes. Analysis of QTL distribution across chromosomes revealed uneven patterns, with certain regions enriched for QTL. Correlation analysis revealed a strong positive relationship between QTL and gene density/chromosome size across all species (p < 0.05). Enrichment analysis identified pleiotropic regions, where QTL affect multiple traits, often aligning with known candidate and major genes. Significant QTL-enriched windows (p < 0.05) were detected, with 699 (187), 355 (68), 50 (15), and 38 (17) genomic windows for cattle, pigs, sheep, and chickens, respectively, associated with overall traits (and specific phenotypic categories). Conclusions: This study provides critical insights into QTL distribution and its correlation with gene density, offering valuable data for advancing genetic research in livestock species. The identification of QTL-enriched regions also highlights key areas for future exploration in trait improvement programs.

Context: Genomic prediction is now routinely used in many livestock species to rank individuals based on genomic breeding values (GEBV). Aims: This study reports the first assessment aimed to evaluate the accuracy of direct GEBV for birth (BW) and weaning (WW) weights of registered Charolais cattle in Mexico. Methods: The population assessed included 823 animals genotyped with an array of 77 000 single nucleotide polymorphisms. Genomic prediction used genomic best linear unbiased prediction (GBLUP), Bayes C (BC), and single-step Bayesian regression (SSBR) methods in comparison with a pedigree-based BLUP method. Key results: Our results show that the genomic prediction methods provided low and similar accuracies to BLUP. The prediction accuracy of GBLUP and BC were identical at 0.31 for BW and 0.29 for WW, similar to BLUP. Prediction accuracies of SSBR for BW and WW were up to 4% higher than those by BLUP. Conclusions: Genomic prediction is feasible under current conditions, and provides a slight improvement using SSBR. Implications: Some limitations on reference population size and structure were identified and need to be addressed to obtain more accurate predictions in liveweight traits under the prevalent cattle breeding conditions of Mexico.

El objetivo fue comparar los efectos de una metodología para la clasificación de épocas climáticas, que tradicionalmente son utilizadas para establecer épocas de nacimiento (EN) en estudios y experimentos estadísticos. Esta metodología se basa en un índice de aridez (IA) para clasificar las EN utilizando información meteorológica histórica. Se trabajó una base de datos con un pedigrí de 7,460 animales, se ajustaron dos modelos para peso al nacimiento y peso al destete en bovinos Charolais manejados en pastoreo extensivo. Los modelos incluyeron el efecto fijo de grupo contemporáneo (GC= subclase de hato, sexo, año y EN) y edad de la madre. Los mismos modelos se compararon utilizando una clasificación tradicional de estaciones del año para clasificar las EN. Al estimar los componentes de varianza y valores genéticos (DEP) con sus exactitudes, los modelos fueron diferentes de acuerdo a la prueba de razón de verosimilitudes (P<0.01). El número de GC se redujo en 25 % para la EN basada en el IA, con GC con mayor número de individuos. El principal efecto observado en los modelos analizados fue el cambio en la jerarquización de las DEP para ambas características. Este método de clasificación de épocas de nacimiento, puede ayudar a mejorar el ajuste de modelos estadísticos en los sistemas ganaderos manejados en pastoreo extensivo.

The insulin-like growth factor-1 (IGF-1), a key hormone in muscle development was investigated for single-nucleotide polymorphisms (SNPs) upstream of the IGF-1 gene and their effects upon its cognate mRNA and hormone levels in sheep. A 70 d feeding trial was conducted with 22 F1 (Dorper × Pelibuey) lambs, individually allocated and fed a diet with a forage-to-concentrate ratio of 36:64 and 17% crude protein. Sequence analyses of 265 bp upstream the IGF-1 gene revealed the variant NC_040254.1:g.[184028491G > C;184028493G > A]. These SNPs generate alleles A and B, with frequencies of 0.66 and 0.34 in F1 lambs and of 0.73 and 0.27 in 81 pure Dorper lambs, respectively. Females were grouped by genotype AA, AB and BB (n = 3). IGF-1 hormone concentrations at 14, 42 and 70 d were higher (p < 0.05) in AA lambs compared to AB + BB lambs. The IGF-1 mRNA level was 2.6-fold higher in AA animals (n = 5, p < 0.05) than in AB + BB lambs (n = 7). A DNA binding site for the Inhibitor of Growth family member 4 (ING4) was found in allele B but not in allele A, which could explain the lower mRNA and hormone expression levels for AB + BB animals. The variant reported here appears to function as an eQTL with a negative effect on the level of IGF-1.