Jinyan Teng

The paper identifies context-dependent genetic regulation of gene expression in pigs using quantile regression, revealing eQTLs that are conserved with humans and influence disease-relevant genes.

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

The paper identifies sex-specific genetic regulatory effects in chickens using whole-genome sequencing and transcriptomes, revealing sex-dependent gene regulation and structural variants.

OmiGA improves molQTL mapping in complex populations by using an efficient linear mixed model, enhancing power and reducing false positives.

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.

The paper presents a multi-tissue sheep atlas identifying regulatory variants and their effects on molecular phenotypes, revealing allelic heterogeneity and evolutionary patterns.

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 ChickenGTEx project provides a multi-tissue reference of regulatory variants in chicken, analyzing their functional impacts and utility in genetics, genomics, and evolutionary studies.

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

This paper develops DeepGCF, a deep learning method to predict functional conservation between human and pig using epigenome and transcriptome data, showing improved performance and insights into regulatory and heritability patterns.

The paper introduces a web server for multi-species transcriptome-wide association study (TWAS) analysis, enabling gene expression prediction and trait association in humans and farm animals.