Genetic and phenotypic traits in livestock

The paper remaps eQTLs in horse PBMCs to a new genome and identifies treatment-induced changes in gene expression regulation.

This study evaluates methods for genomic prediction in heterogeneous populations, finding that modeling heterogeneity improves accuracy in some cases while reducing it does not always help.

The paper uses whole-genome sequencing to analyze three native cattle breeds from northern regions, identifying genetic adaptations and population history.

The paper benchmarks six open-source database systems for genomic selection, finding that HDF5 outperforms others in data extraction speed due to efficient allele matrix handling.

This study simulates strategies for using surrogate sire technology to enhance genetic merit in livestock breeding, finding a three-stage approach most effective for maximizing genetic gain.

This paper evaluates using genotype-by-sequencing data for parentage assignment, showing high-coverage data performs similarly to array data and low-coverage data can be effective with sufficient markers.

The paper analyzes population structure and linkage disequilibrium in Chilean farmed Atlantic salmon using SNP genotypes, finding genetic differentiation and varying LD decay across populations.

The paper analyzes genomic and transcriptomic data from DLY pigs to identify breed-of-origin SNPs and ASE genes, suggesting their role in improved performance and genetic architecture of three-way crossbreeding.

This paper applies sparse Bayesian learning to predict yeast phenotypes and rank influential markers, showing it performs as well as other methods and identifies key markers affecting growth.

This paper introduces hybrid peeling, a method for efficiently calling, phasing, and imputing sequence data in pedigrees, showing improved accuracy and coverage.

The paper investigates how marker allele frequencies and linkage disequilibrium affect estimates of genetic correlation between populations, finding that marker allele frequencies should reflect causal loci frequencies for unbiased estimates.

The paper analyzes sequence variation, constraint, and selection in the CD163 gene in pigs, finding no knock-out variants and evidence of positive selection but no recent selective sweeps.

This study evaluates genomic selection accuracy for growth and wood quality traits in Norway spruce using exome capture, finding that full-sib family structures and 8000 SNPs are sufficient for effective prediction.

The paper identifies genomic selection signatures for gait traits in Yili horses using SNP data, finding two candidate genes related to locomotory behavior.

The paper uses ddRAD-Seq to assess genetic diversity and introgression in Taishu horses, finding reduced diversity and limited introgression signatures.

The paper identifies seven SNPs in the CYP7A1 gene in ducks and finds associations between these variants and lipid traits like IMF, AFP, TG, and TC.

This study examines genetic correlations between growth and disease resistance traits in Pacific salmon, finding favorable genetic links between early growth and survival during infection.

This paper introduces phenomic selection, a low-cost, high-throughput method using near-infrared spectroscopy to predict complex traits in wheat and poplar with accuracy comparable to molecular markers.

The paper introduces CIERA, a data management system for crop breeding programs, enabling efficient collation and integration of phenotypic, genealogy, and genotypic data to support cross planning and genetic gain.

The paper develops a 58K SNP-array and high-density linkage map for Nile tilapia to improve genomic selection and genetic progress in aquaculture.

The paper applies structural equation models to GWAS in chickens to decompose SNP effects into direct, indirect, and total effects, showing greater insight into causal relationships than traditional multi-trait methods.

A consumer genomics study of 6,000 dogs identifies a 98.6-kb duplication linked to blue eyes and heterochromia in Siberian Huskies through a large-scale GWAS.

The paper imputes sequence variants in Holstein bulls and performs fine-mapping of 35 traits using a Bayesian approach, identifying candidate genes and variants.

The paper identifies additional Merle alleles in dogs and highlights mosaicism and health risks associated with Merle breeding.

The paper identifies QTL affecting muscle yield in rainbow trout using a 50K transcribed gene SNP-chip, finding larger genetic variance explained compared to previous studies.

This study compares hidden Markov model-based imputation methods in animal breeding, finding that pre-phasing with Eagle2 or HAPI-UR and haploid imputation with minimac3 or IMPUTE2 is faster and more accurate than diploid imputation.

This study compares liver proteomic profiles of two pig breeds using label-free LC-MS, identifying 25 differentially expressed proteins linked to metabolic differences.

This paper applies random regression models to predict longitudinal shoot growth traits in rice using genomic data, showing improved accuracy over single time point predictions.

DeepGS predicts phenotypes from genotypes using deep learning, achieving higher accuracy than conventional methods and RR-BLUP across multiple traits.