Genetic and phenotypic traits in livestock

The paper examines how gut microbiome composition at different production stages affects meat quality and carcass traits in pigs, finding microbiome contributions vary over time and impact genomic correlations.

This study uses SNP genotyping to analyze population structure and genetic relationships among five Kazakh sheep breeds and global sheep diversity.

The paper identifies eQTLs in Danish pigs linked to feed efficiency, revealing trans-eQTLs associated with gene regulation and expression pathways.

AlphaImpute2 improves imputation accuracy and speed for large livestock populations, outperforming existing methods in both metrics.

This study uses human height GWAS data to prioritize genes and variants for cattle stature, finding some overlap but no added benefit over within-species data.

The paper applies genomic selection to optimize doubled haploid breeding in maize by improving prediction accuracy for DH production and agronomic traits.

This study evaluates the impact of sequencing depth, marker number, and genetic models on genomic selection accuracy in autopolyploid crops, finding that fewer SNPs and additive models are sufficient for most traits.

This paper uses genomic selection to predict apple fruit texture traits, achieving high accuracy by optimizing the training set size and composition.

This study identifies 38 QTL regions associated with resistance to Mareks Disease Virus (MDV) in chickens, highlighting candidate genes and variants that could inform breeding, vaccine design, or gene-editing strategies.

The paper re-examines the mechanism of the DGAT1 K232A mutation in bovine milk production, showing it modulates gene expression through splicing enhancement.

The paper identifies a 505-bp indel variant in the FGF5 gene associated with cashmere growth in goats through whole-genome sequencing and functional validation.

The paper introduces CORE GREML, a method to estimate covariance between random effects in LMMs for genomic analyses, showing improved performance in variance partitioning.

This study compares genetic gain and accuracy of genomic selection (GS) versus phenotypic selection in perennial ryegrass breeding programs, finding GS achieves significantly higher genetic gain.

This study shows that the BMORS model improves genomic prediction accuracy for sorghum grain composition traits compared to single-trait models.

The paper evaluates using radial basis function neural networks (RBFNN) with marker subset selection for genome-enabled prediction of genetic values, showing improved accuracy and reduced error compared to RR-BLUP.

The paper analyzes DNA variation patterns across autosomes, X, and Y chromosomes in Bos taurus using a new genome assembly, finding differences in variant density, divergence, and Tajima's D.

The paper develops methods that integrate day length data with genomic prediction tools to improve prediction of time-related traits like days to heading in unobserved environments.

This study identifies a candidate recessive lethal variant in the LY49B gene in Thoroughbred horses, associated with high heterozygosity and absence of homozygotes.

This study evaluates genomic prediction for malting quality traits in barley breeding using different cross-validation methods and training population sizes, finding medium to high heritability and accuracy improvements with larger training populations.

The paper identifies genetic variants at RNF212 and RNF212B associated with recombination rate variation in Soay sheep using a larger dataset and animal models.

This study identifies selection signatures in farmed coho salmon using genome-wide SNP data and detects genes associated with growth and disease resistance traits.

The paper analyzes the impact of white spotting alleles, including W20, on the APHA-defined white spotting phenotype in American Paint Horses using genetic data from 1,054 registered animals.

The paper identifies a 63-bp insertion in the KIF21A gene as the causal mutation for arthrogryposis multiplex congenita in pigs.

The paper identifies selection signatures in three farmed Nile tilapia strains using whole-genome sequencing and SNP analysis.

This paper proposes a general definition of animal breeding programs using a modular graph representation and introduces a web tool and R-package for simulating and analyzing breeding programs.

This study analyzes genetic diversity and population structure among four goat genotypes in Kenya using SNP markers and clustering methods, revealing gene intermixing and admixture patterns.

This study uses metabolomics and genomic approaches to improve prediction of healthful compounds in oat seeds by identifying latent factors associated with lipid metabolism.

The paper estimates heritability of body and antler traits in free-ranging white-tailed deer using genomic-relatedness matrices and finds moderate heritability for body traits but low and variable heritability for antler traits.

This study evaluates the impact of including the X chromosome in genomic predictions for reproductive and andrological traits in beef cattle, finding improved predictive accuracy for some traits.

The paper designs experiments for fine-mapping quantitative trait loci in livestock populations, showing that optimal sample size depends on heritability and the number of causative variants.