Chao Ning

This paper introduces GenSep, a framework to quantify genetic separability of disease subtypes, showing current PRSs fall short of theoretical limits.

The paper presents a cattle metabolome atlas linking genetic variants to metabolites and traits, revealing colocalization with eQTL and causal gene-metabolite-trait networks.

The paper identifies host genetic and microbial factors associated with loin muscle weight in meat rabbits, finding links between cecal microbiota and host genes.

StratGWAS improves GWAS power by incorporating phenotype heterogeneity while maintaining specificity, identifying more significant loci in depression and other traits.

This study uses whole-genome resequencing to trace the origin and domestication of Chinese domestic rabbits, identifying genetic adaptations and multiple potential origins.

This study uses low-coverage sequencing and imputation to identify QTLs for wool traits in rabbits, finding six QTLs with phenotypic contributions up to 7.50%.

This paper introduces an improved linear mixed model for multivariate genome-wide association studies that handles incomplete data and reduces computational complexity.

The paper identifies and characterizes unknown porcine protein isoforms using tissue-based proteome maps and improves genome annotation.

The paper introduces a rapid mixed model for genome-wide epistatic association analysis that handles multiple polygenic effects and demonstrates its efficiency on yeast and human datasets.

The paper develops efficient multivariate association algorithms for longitudinal GWAS, improving statistical power and computational speed for analyzing large-scale longitudinal data.