Adaptive selection is a major factor influencing the evolution and differentiation of human phenotypes, as well as differences in disease susceptibility among different racial populations. Non-coding elements in the genome play an important role in shaping phenotypes. In recent years, non-coding regulatory elements in the human genome, such as enhancers and promoters, have been systematically identified and annotated. However, the role of these non-coding regulatory elements in population adaptive selection has not been systematically investigated.

A research team led by Profs. XU Tao and HE Shunmin from the Institute of Biophysics of the Chinese Academy of Sciences has elucidated the impact of non-coding regulatory elements on phenotypic evolution under adaptive selection in Han Chinese genome.

This study was published in Molecular Biology and Evolution.

The researchers found that about 12% of the autosomal genome regions in the Han Chinese population are under adaptive selection, with around 15% of non-coding regulatory elements (promoters and enhancers) under adaptive selection, a proportion slightly lower than that of protein-coding genes.

Through functional enrichment analysis of target genes regulated by elements undergoing adaptive selection, they discovered that positively selected regulatory elements are mainly enriched in biological pathways such as cell adhesion, while balanced selection regulatory elements are mainly enriched in immune-related pathways.

By further pinpointing the ancient human gene infiltration regions under positive selection, the researchers found that such events are concentrated in the 3p13.11 region, with the regulatory elements within this region primarily associated with adaptation to ultraviolet radiation. A key target gene identified was the HYAL gene, which encodes hyaluronidase for the degradation of hyaluronic acid.

The influence of positive selection in the genome on disease risk genes is also an important evolutionary question. By analyzing the influence of positively selected sites on linked disease risk genes, the research team found that nearly half of the disease risk genes are accelerated for elimination under positive selection, while the elimination efficiency of the other half is slowed down under positive selection.

This work systematically identifies adaptive selection across the genome and reveals the impact of adaptive selection of non-coding regulatory elements on population phenotypes. It has important implications for the analysis and evaluation of non-coding mutations involved in adaptation.

Reported by Center for Big Data Research in Health (Image by HE Shunmin's group)