Genetic and phenotypic traits in livestock

This study evaluates genomic selection models for lentil breeding using empirical data, finding that single-trait models perform well without large effect QTL, while models accounting for GEI and multiple traits improve accuracy for low heritability traits.

This paper develops a method to infer genotypes from high-throughput phenotypes to enable genomic selection in plant breeding programs, showing increased genetic gain in simulations.

This study evaluates the performance of low and medium density SNP panels for genomic prediction in aquaculture species, showing that accuracies remain high even at 1,000 SNPs.

The paper analyzes genetic and genomic factors contributing to early abortion in Israeli dairy cattle using heritability estimates and genome-wide association studies.

This study analyzes Y-chromosomal haplotypes in domestic, ancient, and wild goats to reconstruct their population history and phylogeographic patterns.

This study evaluates the effects of selection methods on genetic response in soybean recurrent selection over 40 cycles, identifying interactions that influence short-term gains and long-term genetic potential.

The paper presents a high-quality quail genome and uses it to study social behavior, photoperiodism, and immune response to H5N1 influenza.

This study compares genomic and genetic evaluation for egg quality traits in poultry, finding genomic evaluation more accurate and beneficial for male selection.

SeqBreed evaluates genomic prediction in complex scenarios by simulating genetic data and GP methods, demonstrating its use with Drosophila and potato datasets.

The paper applies multi-trait random regression models to predict daily water usage in rice using high-throughput phenotyping data, showing improved genomic prediction accuracy when integrating shoot biomass measurements.

This study analyzes genomes of wild and domestic ducks to reveal their evolutionary history and identify genetic factors underlying phenotypic variation.

This paper introduces a hierarchical model to estimate haplotype effects using phylogenetic relationships, showing improved estimates with sparse modeling and better performance in low-observation scenarios.

This study evaluates genomic selection for improving Pacific oyster resistance to Ostreid herpesvirus, finding it more accurate than pedigree-based methods and showing low SNP density can suffice for effective breeding.

The paper identifies genetic variants associated with enhanced growth and reduced immune function in modern broilers through comparative genomic analysis of historical and commercial chicken lines.

This paper estimates non-additive genetic variance and inbreeding depression in Nile tilapia using genomic data, finding additive by additive epistasis and maternal effects.

The paper discovers and validates 50,000 high-quality SNPs in Nile tilapia through whole-genome resequencing of 326 individuals, useful for genomic selection and trait analysis.

The paper evaluates robust and classical methods for estimating heritability and predictive accuracy in plant breeding using simulations and empirical data, finding robust methods more reliable in contaminated data.

The paper performs GWAS and fine-mapping on seven health traits in Holstein cattle to identify genetic variants and candidate genes associated with health outcomes.

The paper presents an efficient algorithm for calculating the genomic relationship matrix, achieving 25x speedup over a double precision floating-point implementation.

This study uses whole-genome sequencing of 49 Original Braunvieh cattle ancestors to assess genomic diversity, inbreeding, and selection signatures, finding higher diversity and lower inbreeding compared to European breeds.

The paper proposes a hybrid optimal contribution approach to balance short-term genetic gains with long-term sustainability in plant breeding programs.

This study sequenced 128 camels across Asia to trace the origin and migration of domestic Bactrian camels, finding an Iranian origin followed by eastward migration.

This paper presents the first haplotype-phased genome assembly of river buffalo using a trio sequencing approach, achieving high-quality scaffolding and chromosome-level assembly.

The paper identifies two SNPs associated with salmon flesh color and suggests bco1l as the likely gene responsible for color variation through functional studies.

The paper introduces a multiple-trait Bayesian Lasso (MBL) for genome-based analysis and prediction of complex traits, showing improved predictive performance in Pinus trees compared to existing methods.

The paper introduces the qgg R package for large-scale quantitative genetic analyses, including genetic parameter estimation and predictive modeling of complex traits using human height data from the UK Biobank.

This paper develops Bayesian networks for genomic prediction of developmental traits in biomass sorghum, showing improved accuracy for plant height and biomass yield using multi-time and multi-trait models.

This simulation study investigates how neural networks predict genetic values associated with gene interactions, finding that pruning redundant markers and using networks with few hidden layers improves accuracy.

The paper improves imputation accuracy in cattle by using a multi-breed reference panel with rare variants from the GGP-F250 assay.

The paper assesses the feasibility of improving milk yield and mastitis resistance in dairy sheep through genomic analysis, finding no significant genetic correlation between the traits.