Pigs are not only important agricultural animals but also key model organisms for studying evolution, complex traits, and human diseases. As genome sequencing and genetic research advance, numerous genetic variants associated with pig domestication, economic traits, and disease have been identified. However, many key variants reside in non-coding regions, and traditional linear genome annotation cannot determine which genes these regulatory variants act upon.

In a study published in Molecular Biology and Evolution on July 30, 2026, a team led by Prof. Zhang Yaping from the Kunming Institute of Zoology (KIZ), along with collaborators from the University of Science and Technology of China and Yunnan University, constructed Pig Matrix, a multi-omics 3D regulatory genomics database for pigs.

The researchers found that Pig Matrix integrates matched multi-omics data from 94 biological samples of 8 pigs with defined genetic and phenotypic information, covering 4 developmental stages, 11 tissues, and 3 commonly used pig cell lines. The database contains 1,170 experimental datasets across 16 library types, including Hi-C, ATAC-seq, WGBS, RNA-seq, snRNA-seq, WGS, and ChIP-seq for CTCF, Pol II, and 7 histone modifications. Because the primary data originate from a unified sample system with consistent experimental protocols, Pig Matrix minimizes batch effects across omics layers.

Unlike traditional linear-genome databases, Pig Matrix integrates chromatin accessibility, histone modifications, and 3D interaction data. Users can query candidate cis-regulatory elements and link them to proximal and distal target genes. The database features a HiGlass-based 3D epigenome browser and integrates domestication signals, artificial selection regions, gene flow between populations, lineage-specific accelerated regions, and GWAS/QTL annotations. A pig-human comparative module and a xenotransplantation resource section are also included.

This study establishes a systematic connection from genetic variants through regulatory elements and 3D chromatin interactions to target genes, providing data and analytical tools for studying pig domestication, adaptive evolution, economic trait genetics, pig-human comparative genomics, and xenotransplantation.