Genetic and phenotypic traits in livestock

This study uses random regression models to analyze spatio-temporal genomic data in ryegrass, finding improved prediction accuracy for nutritive quality traits but not dry matter yield.

This study uses low-coverage sequencing across multiple generations of a chicken intercross to identify novel minor-effect QTL contributing to body weight, increasing power and explaining more phenotypic variance.

This study evaluates genomic prediction models incorporating gene transcripts and finds that transcript-based models improve accuracy when phenotypes are measured close to transcript sampling, but combining transcript and SNP data does not consistently outperform single-omics models.

The paper performs a genome-wide association study on yak body size traits using a compressed mixed linear model to identify significant SNPs and candidate genes.

This study evaluates the benefits of using whole-genome sequence data for genomic prediction in pigs, finding small improvements over marker arrays in some scenarios.

This study identifies human functional variants with conserved effects in livestock species, showing their utility for understanding disease mechanisms.

The paper identifies HOXB13 as a candidate gene for tail length variation in Merinolandschaf sheep through haplotype mapping and candidate variant analysis.

The paper develops optimal experimental designs and a software tool to estimate SNP effects on infectious disease transmission traits like susceptibility, infectivity, and recoverability.

The paper introduces genomicSimulation, a fast R tool for stochastic simulation of breeding programs using real genotypes, showing it accurately reproduces key population features.

The paper genotypes 50 Pakistani buffalo samples to assess the CSN2 7:32016718C>A marker's association with A1/A2 milk type, finding all samples are homozygous wild-type (CC), indicating exclusive A2 milk production.

The paper investigates the association of the CSN2 variant 6:85451298C>A with A1/A2 milk phenotype in Pakistani cows using ARMS-PCR and Chi-square test, finding significant genotype variability.

The paper investigates the association between the LDHA variant g.2582481G>A and racing performance in Pakistani pigeons, finding a significant genetic link.

The paper uses a linear multivariate animal model to analyze survival traits in white-leg shrimp, finding low heritability but high genetic correlations across survival time points.

The paper constructs a cattle Genotype-Tissue Expression atlas and identifies genetic regulatory variants linked to gene expression and traits in cattle.

The paper evaluates genetic conservation of French local chicken breeds through management programs, finding that early integration into programs reduces inbreeding and highlights the utility of molecular markers for monitoring diversity.

The paper applies genomic selection to sugar kelp with a biphasic life cycle, predicting breeding values for gametophytes and achieving moderate prediction accuracy for yield and morphology traits.

The paper identifies a new sheep breed from West Bengal with distinct genetic identity using phylophenomic and phylogenomic analyses.

The paper analyzes whole mitochondrial genomes of sheep breeds to infer phylogenetic relationships and identify genetic lineages.

PHARP provides a high-quality pig haplotype reference panel for genotype imputation, enabling improved GWAS and genomic prediction.

This paper develops a joint learning approach to improve genomic prediction in polyploid grasses, achieving over 50% accuracy improvements over traditional methods.

The paper develops a high-density 665 K SNP array for rainbow trout and demonstrates its utility in detecting linkage disequilibrium at shorter genomic distances.

The paper introduces a neural network framework for genomic evaluations that integrates pedigree, genotypes, and phenotypes, showing improved prediction performance over traditional methods.

This study evaluates genomic selection for improving growth traits in European flat oysters using low-density SNP panels and finds that similar prediction accuracies can be achieved with fewer markers.

This paper uses simulation to address two key questions in plant breeding: the number of entries needed to select the best one with a defined probability and the probability of selecting the top entries when some are chosen.

This paper predicts dog phenotypes (breed, height, weight) from genotypes using linear and non-linear methods, showing that linear methods outperform non-linear for breed classification but not for height and weight regression.

The paper uses polygenic risk scores to predict production performance in yeast crossbreeding, finding significant correlations between PRS and growth traits in F1 hybrids and their parents.

This paper demonstrates that average semivariance can estimate genetic variance components across different modes of inheritance in complex traits.

This paper introduces a new hyper-parameter, the scale factor, to improve the prediction accuracy of the HBLUP method in genetic evaluation using simulated and real cattle data.

This study compares clonal breeding strategies using stochastic simulation to determine their genetic gain per unit cost, finding that reciprocal recurrent selection (RRS) is optimal in diploids with high genomic selection intensity but not in autopolyploids.

This study genotypes over 11,000 domestic cats to analyze genetic variants related to blood type, disease, and traits, revealing breed-specific distributions and diversity.