Genetic and phenotypic traits in livestock

This study investigates how linkage disequilibrium and epistasis affect genetic variances and covariances in inbred and non-inbred populations using simulated data.

This study compares multi-task deep learning with traditional methods for genomic predictions in breeding lines across environments, finding moderate improvements in accuracy.

This study analyzes genomic features of the endangered Garfagnina goat breed using SNP data to assess inbreeding, admixture, and traceability.

This paper identifies a bias in the scGRM method for kinship estimation and proposes an unbiased method, UKin, which reduces bias and improves association mapping power.

A GWAS identifies a BMP15 nonsense mutation in pigs causing infertility and increased litter size, with trade-offs in lean meat growth.

The paper analyzes population structure, kinship coefficients, and inbreeding trends in Tatra Shepherd dogs based on sex, breeding status, and country of origin, finding higher inbreeding rates in non-champion and Polish dogs.

The paper sequences the mitochondrial genome of Bos frontalis from Bangladesh to study genetic traits and evolutionary relationships.

The paper explores using crop models as gene-to-phenotype link functions to optimize selection in plant breeding programs by integrating quantitative genetic theory and trait modeling.

This study identifies selection signatures in the Vrindavani cattle genome, finding stronger selective pressure on adaptation-related regions than milk yield.

This study identifies polygenic loci associated with antler and body size in white-tailed deer using whole genome re-sequencing of phenotypically extreme pools.

AlphaSimR is an R package for simulating plant and animal breeding programs, offering flexibility in modeling complex breeding strategies.

The paper analyzes mitochondrial D-loop sequences from 96 Cleveland Bay horses to assess genetic diversity and maternal ancestry, revealing four main haplotype clusters and a close relationship with Northern European, Iberian, and North African horse breeds.

This study introduces the iterative screen regression model (ISR) for polygenic prediction of complex traits and shows it outperforms existing methods in simulations and across multiple species.

This paper compares bivariate genomic prediction models for plant traits across two growing seasons, finding that models incorporating epistasis improve prediction accuracy.

This study identifies PDGFD as a major gene underlying fat-tail selection in sheep using a global dataset and selection signature analysis.

This study investigates genetic variation in bTB resistance in Bos indicus cattle in Cameroon using genomic analysis and heritability studies.

This study shows spatial modelling improves genetic evaluation in smallholder dairy cattle systems by better separating genetic and environmental effects.

This study examines how identity-by-descent and inbreeding affect disease and fitness in Canid populations, finding that ROH burden correlates with disease and that breed popularity influences OMIA variant counts.

This paper proposes local convolutional neural networks for genomic prediction, showing improved performance over traditional methods in most cases, especially with medium complexity traits and large datasets.

The paper evaluates imputation accuracy in Nellore cattle using two bovine genome assemblies, showing improved accuracy with larger reference and target panels.

The paper analyzes genetic diversity in the endangered Cleveland Bay horse using pedigree and microsatellite data, revealing significant loss of genetic variation and reliance on a small number of founders.

This study predicts Drosophila complex traits using genotypes, gene expression, and gene ontology, finding that expression and GO terms improve accuracy, especially when sample sizes are small.

The paper evaluates the accuracy of Zoetis GeneMax Advantage genomic predictions in Angus cattle by comparing genomic scores with calf phenotypes for several traits.

The paper develops a genetic evaluation for hair shedding in American Angus cattle to improve thermotolerance by identifying genomic loci associated with the trait.

This study evaluates the economic benefits of genomic selection in a winter wheat breeding program by analyzing prediction accuracy, genotyping costs, and heritability levels.

This paper examines the validity of using a kinship matrix in linear mixed models for BLUP and finds that routine practice leads to misleading breeding value estimates.

This study compares genomic prediction methods for ordinal traits like IDC tolerance, finding that Random Forest provides the best decision metrics for breeding decisions.

This paper introduces SEM-BayesC{Pi}, a multi-trait Bayesian regression method for GWAS that incorporates causal structures, showing improved genotype-phenotype mapping compared to multi-trait BayesC{Pi}.

The paper optimizes population design for genomic prediction by selecting preexisting individuals to phenotype and extending this to connected population designs for maize hybrids.