Genetic and phenotypic traits in livestock

The paper introduces a similarity matrix to preserve haplotype diversity in genomic selection by quantifying parent similarity based on gamete covariance, showing improved genetic variability and gain.

The paper shows that combining multiple genomic prediction models improves accuracy and reduces errors in predicting crop traits, supporting the Diversity Prediction Theorem.

This study combines genomic and phenomic selection in corn breeding using single-kernel NIRS to improve predictive accuracy and reduce genotyping costs.

The paper analyzes the genomic data of 385 horses from 49 breeds to explore the demographic history and genetic factors influencing body size in ponies, identifying cis-regulatory elements and genetic affinities.

The paper analyzes trait persistence in laying hens from 70 to 92 weeks, identifying traits with stable genetic variance and those requiring alternative selection strategies.

The paper selects for large body size in black soldier flies and finds repeatable phenotypic but not genetic responses, highlighting high genetic redundancy in polygenic traits.

This study evaluates how epistasis affects genomic prediction of untested single crosses in multi-environment trials, finding that epistasis significantly impacts prediction accuracy and coincidence index.

This study optimizes the constitution of cryopreserved collections for managing genetic diversity in animal populations by simulating breeding scenarios and evaluating the impact of collection size, age, and sampling strategies.

This paper compares genomic and phenomic prediction for soybean seed yield, protein, and oil content, finding phenomic prediction outperforms genomic for yield while genomic is better for protein and oil.

The paper identifies haplotypes and explores population structure in Indian dog breeds using SNP data, revealing genetic connections between breeds from Punjab and Haryana.

This study evaluates cross-selection methods with genomic selection in potato breeding to improve long-term genetic gain while maintaining diversity.

This study improves genomic selection in hexaploid wheat by incorporating additive and epistatic effects, leading to a 3% increase in prediction accuracy for grain yield.

The paper performs a multi-breed meta-GWAS in pigs to identify genomic regions associated with complex traits and integrates with PigGTEx to prioritize variant-gene-tissue-trait circuits.

The paper compares statistical learning methods for predicting complex traits from gene expression in Drosophila, finding method-specific accuracy differences and improved performance with functional annotations.

WISER improves phenotype estimation in omics studies by correcting population structure, outperforming LS and BLUP across multiple species and datasets.

This paper optimizes a ddRAD GBS pipeline for non-model species using mock reference genomes and demonstrates its effectiveness in bovine and European whitefish data.

This study examines inbreeding depression in a self-pollinated eucalyptus population by analyzing genomic and phenotypic data to estimate inbreeding depression and genetic parameters.

PIGOME is a multi-omics database for pig functional genomics that integrates various sequencing datasets and provides tools for exploring genomic variants, gene expression, and epigenetic signals.

The paper uses PCA to analyze biometric traits and indices of three indigenous sheep populations in Ethiopia, finding correlations with body weights and suggesting their suitability for different production purposes.

This study evaluates genomic and phenomic prediction methods for apple breeding, showing that expanding training sets improves predictive ability but leave-one-family-out validation reduces it, while phenomic data are less effective.

This paper evaluates genotyping strategies for a service dog population using simulation, finding that low-pass sequencing outperforms SNP arrays in imputation accuracy and cost-effectiveness.

The paper proposes an iterative feedback method combining pooled genotyping and imputation to improve SNP genotype accuracy at reduced cost.

This study identifies genomic signatures of selection in guineafowl and chicken populations across Africa, Asia, and Europe, revealing genes and pathways involved in stress response and environmental adaptation.

This study proposes a method to select optimal cross pairs in inter-population crosses by considering genetic effects across populations, showing increased genetic gains in multiple traits.

The paper identifies the Id locus in Black Bone Chickens, locates it to a 1.6 Mb region, and suggests it may function as a polygenic supergene cluster influencing dermal pigmentation.

The paper evaluates genomic prediction models for 36 traits in Arabidopsis thaliana, finding regression models generally most accurate, with random forest better for biochemical traits.

The paper uses stochastic simulations to optimize a maize breeding scheme by balancing genetic gains and diversity through additional phenotyping and external genetic material.

The paper argues that benchmarking phenomic prediction against genomic prediction using cross-validation is inappropriate because accuracy differences do not reliably reflect breeder's equation parameters and other factors influence selection outcomes.

The paper compares selection strategies to improve genetic gain and reduce inbreeding over multiple generations using simulation software.

The paper evaluates methods for predicting inbreeding levels using genomic data in small populations, finding that model-based and rule-based approaches perform well under various conditions.