Jicai Jiang

The paper uses Genomic SEM to identify loci underlying locomotor activity in rats, finding 31 loci compared to fewer from other methods.

This study shows that common GWAS methods can produce misleading associations in livestock with polygenic architecture, highlighting the need for methods that control long-range LD spillover.

This paper develops a framework explaining differences in GWAS results between livestock and humans by linking them to effective genomic dimensionality and population genetics parameters.

The paper presents CattleGTEx, a resource characterizing regulatory effects in cattle, resolving GWAS signals and providing insights into adaptive evolution and selection.

This study constructs a multi-tissue cell atlas of pigs, identifies cell-type-specific gene regulation, and links these to complex traits and human phenotypes.

This paper introduces Bayesian fine-mapping methods adapted for related individuals, showing improved accuracy in pig data compared to existing tools.

The paper constructs a bovine epigenomic atlas to annotate regulatory elements and decode the regulatory syntax of the cattle genome, aiding in fine-mapping GWAS loci for complex traits.

The paper constructs a cattle cell-type-specific regulatory variant atlas by integrating bulk and single-cell RNA-seq data, identifying eQTL and linking them to GWAS loci for breeding insights.

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 presents PigGTEx, a resource linking genetic variants to transcriptomic phenotypes in pigs, showing pigs' similarity to humans in gene regulation and complex traits.

This study identifies selection signatures and loci associated with complex traits in pigs by analyzing multi-omics data from Eastern and Western breeds.

The paper estimates heritability for height and BMI using whole-genome sequence data and finds that rare variants contribute significantly to the missing heritability.

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