Dailu Guan

SheepEpimap combines 516 histone CUT&Tag, ATAC-seq and RNA-seq datasets from 43 sheep tissues to annotate 2.93 million cis-regulatory elements and 145,407 allele-specific variants for trait interpretation.

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.

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 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 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 creates an enriched gene atlas for the GRCg7b chicken assembly, increasing the number of annotated lncRNAs and PCGs and providing functional annotations across 47 tissues.

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 uses Oxford Nanopore long-read sequencing to annotate transcript isoforms in 19 chicken tissues, identifying novel transcripts and highlighting tissue-specific expression patterns.

The paper identifies miRNA SNPs in pigs and associates them with lipid traits and gene expression, finding a significant SNP in the apical loop of ssc-miR-326 linked to PPP1CC mRNA levels.