Xueling Ge
Chaofang Zhong
Ruiqing Fu
Kang Ning
Shuhua Xu
a Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;
b Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China;
c State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China;
d School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China;
e Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China;
f Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450052, China;
g Human Phenome Institute, Fudan University, Shanghai 201203, China
Funds: XDB38000000) of the Chinese Academy of Sciences, National Key Research and Development Program of China (2018YFC0910502, 2016YFC0906403)
the UK Royal Society-Newton Advanced Fellowship (NAF\R1\191094), and the Shanghai Municipal Science and Technology Major Project (2017SHZDZX01).
We are extremely grateful to all volunteers who donated their DNA samples and all participants who contributed to this study. We thank Drs. Yajun Yang, Jing Li, Lei Tian, Asif Khan, Kun Tang, and Sijia Wang for their contribution to the collection of samples and data. This work was supported by the National Natural Science Foundation of China (NSFC) (31771388, 32030020, 31525014, 32071465, 31871334, 31671374, 91731303, 31961130380, and 32041008), the Strategic Priority Research Program (XDPB17
Received Date: 2021-08-14
Accepted Date:2021-09-06
Rev Recd Date:2021-09-03
Publish Date:2021-11-20
Abstract
Abstract
Understanding the micro-coevolution of the human gut microbiome with host genetics is challenging but essential in both evolutionary and medical studies. To gain insight into the interactions between host genetic variation and the gut microbiome, we analyzed both the human genome and gut microbiome collected from a cohort of 190 students in the same boarding college and representing 3 ethnic groups, Uyghur, Kazakh, and Han Chinese. We found that differences in gut microbiome were greater between genetically distinct ethnic groups than those genetically closely related ones in taxonomic composition, functional composition, enterotype stratification, and microbiome genetic differentiation. We also observed considerable correlations between host genetic variants and the abundance of a subset of gut microbial species. Notably, interactions between gut microbiome species and host genetic variants might have coordinated effects on specific human phenotypes. Bacteroides ovatus, previously reported to modulate intestinal immunity, is significantly correlated with the host genetic variant rs12899811 (meta-P=5.55 × 10-5), which regulates the VPS33B expression in the colon, acting as a tumor suppressor of colorectal cancer. These results advance our understanding of the micro-coevolution of the human gut microbiome and their interactive effects with host genetic variation on phenotypic diversity.Keywords: Micro-coevolution,
Gut microbiome,
Host genetics,
Uyghur,
Kazakh,
Han Chinese
PDF全文下载地址:
http://www.jgenetgenomics.org/article/exportPdf?id=d17b44e0-07a5-4412-89e8-71f1fc81003e&language=en
