Micro-coevolution of host genetics with gut microbiome in three Chinese ethnic groups

Mingyue Cheng; Xueling Ge; Chaofang Zhong; Ruiqing Fu; Kang Ning; Shuhua Xu

doi:10.1016/j.jgg.2021.09.002

Volume 48 Issue 11

Nov. 2021

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Article Navigation > Journal of Genetics and Genomics > 2021 > 48(11): 972-983

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Micro-coevolution of host genetics with gut microbiome in three Chinese ethnic groups

doi: 10.1016/j.jgg.2021.09.002

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.
- Micro-coevolution,
- Gut microbiome,
- Host genetics,
- Uyghur,
- Kazakh,
- Han Chinese

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References

Abbasi, A., Deetman, P.E., Corpeleijn, E., Gansevoort, R.T., Gans, R.O., Hillege, H.L., van der Harst, P., Stolk, R.P., Navis, G., Alizadeh, B.Z., et al., 2015. Bilirubin as a potential causal factor in type 2 diabetes risk:a mendelian randomization study. Diabetes 64, 1459-1469.

Alexander, D.H., Novembre, J., Lange, K., 2009. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655-1664.

Arumugam, M., Raes, J., Pelletier, E., Le Paslier, D., Yamada, T., Mende, D.R., Fernandes, G.R., Tap, J., Bruls, T., Batto, J.M., et al., 2011. Enterotypes of the human gut microbiome. Nature 473, 174-180.

Auton, A., Brooks, L.D., Durbin, R.M., Garrison, E.P., Kang, H.M., Korbel, J.O., Marchini, J.L., McCarthy, S., McVean, G.A., Abecasis, G.R., 2015. A global reference for human genetic variation. Nature 526, 68-74.

Barrett, J.C., Fry, B., Maller, J., Daly, M.J., 2005. Haploview:analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263-265.

Blekhman, R., Goodrich, J.K., Huang, K., Sun, Q., Bukowski, R., Bell, J.T., Spector, T.D., Keinan, A., Ley, R.E., Gevers, D., et al., 2015. Host genetic variation impacts microbiome composition across human body sites. Genome Biol. 16, 191.

Bonder, M.J., Kurilshikov, A., Tigchelaar, E.F., Mujagic, Z., Imhann, F., Vila, A.V., Deelen, P., Vatanen, T., Schirmer, M., Smeekens, S.P., et al., 2016. The effect of host genetics on the gut microbiome. Nat. Genet. 48, 1407-1412.

Bray, F., Ferlay, J., Soerjomataram, I., Siegel, R.L., Torre, L.A., Jemal, A., 2018. Global cancer statistics 2018:globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 68, 394-424.

Caliński, T., Harabasz, J., 1974. A dendrite method for cluster analysis. Commun. Stat. Theor. Methods 3, 1-27.

Cano, P.G., Santacruz, A., Trejo, F.M., Sanz, Y., 2013. Bifidobacterium CECT 7765 improves metabolic and immunological alterations associated with obesity in high-fat diet-fed mice. Obesity 21, 2310-2321.

Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., Fierer, N., Pena, A.G., Goodrich, J.K., Gordon, J.I., et al., 2010. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335-2336.

Caspi, R., Foerster, H., Fulcher, C.A., Kaipa, P., Krummenacker, M., Latendresse, M., Paley, S., Rhee, S.Y., Shearer, A.G., Tissier, C., et al., 2008. The metacyc database of metabolic pathways and enzymes and the biocyc collection of pathway/genome databases. Nucleic Acids Res. 36, D623-D631.

Chen, Y., Liu, Z., Wang, H., Tang, Z., Liu, Y., Liang, Z., Deng, X., Zhao, M., Fu, Q., Li, L., et al., 2020. VPS33B negatively modulated by nicotine functions as a tumor suppressor in colorectal cancer. Int. J. Cancer. 146, 496-509.

Costea, P.I., Hildebrand, F., Manimozhiyan, A., Bäckhed, F., Blaser, M.J., Bushman, F.D., de Vos, W.M., Ehrlich, S.D., Fraser, C.M., Hattori, M., 2018. Enterotypes in the landscape of gut microbial community composition. Nat. Microbiol. 3, 8-16.

Delaneau, O., Zagury, J.F., Marchini, J., 2013. Improved whole-chromosome phasing for disease and population genetic studies. Nat. Methods 10, 5-6.

Dias-Alves, T., Mairal, J., Blum, M.G.B., 2018. Loter:a software package to infer local ancestry for a wide range of species. Mol. Biol. Evol. 35, 2318-2326.

Edgar, R.C., 2010. Search and clustering orders of magnitude faster than blast. Bioinformatics 26, 2460-2461.

Fang, D., Shi, D., Lv, L., Gu, S., Wu, W., Chen, Y., Guo, J., Li, A., Hu, X., Guo, F., et al., 2017. Bifidobacterium pseudocatenulatum LI09 and Bifidobacterium catenulatum LI10 attenuate D-galactosamine-induced liver injury by modifying the gut microbiota. Sci. Rep. 7, 8770.

Feng, Q.D., Lu, Y., Ni, X.M., Yuan, K., Yang, Y.J., Yang, X., Liu, C., Lou, H.Y., Ning, Z.L., Wang, Y.C., et al., 2017. Genetic history of Xinjiang's Uyghurs suggests bronze age multiple-way contacts in Eurasia. Mol. Biol. Evol. 34, 2572-2582.

Franzosa, E.A., McIver, L.J., Rahnavard, G., Thompson, L.R., Schirmer, M., Weingart, G., Lipson, K.S., Knight, R., Caporaso, J.G., Segata, N., et al., 2018. Species-level functional profiling of metagenomes and metatranscriptomes. Nat. Methods 15, 962-968.

Gomez-Hurtado, I., Zapater, P., Portune, K., Juanola, O., Fernandez-Iglesias, A., Gonzalez-Navajas, J.M., Gracia-Sancho, J., Sanz, Y., Frances, R., 2019. Improved hemodynamic and liver function in portal hypertensive cirrhotic rats after administration of B. Pseudocatenulatum CECT 7765. Eur. J. Nutr. 58, 1647-1658.

Goodrich, J.K., Davenport, E.R., Beaumont, M., Jackson, M.A., Knight, R., Ober, C., Spector, T.D., Bell, J.T., Clark, A.G., Ley, R.E., 2016. Genetic determinants of the gut microbiome in UK twins. Cell Host Microbe 19, 731-743.

Goodrich, J.K., Waters, J.L., Poole, A.C., Sutter, J.L., Koren, O., Blekhman, R., Beaumont, M., Van Treuren, W., Knight, R., Bell, J.T., et al., 2014. Human genetics shape the gut microbiome. Cell 159, 789-799.

GTEx Consortium, 2013. The genotype-tissue expression (GTEx) project. Nat. Genet. 45, 580-585.

He, Y., Zhai, F., Yang, X., Ge, K., 2009. The Chinese diet balance index revised. Acta Nutr. Sin. 31, 532-536.

Hughes, D.A., Bacigalupe, R., Wang, J., Rühlemann, M.C., Tito, R.Y., Falony, G., Joossens, M., Vieira-Silva, S., Henckaerts, L., Rymenans, L., et al., 2020. Genome-wide associations of human gut microbiome variation and implications for causal inference analyses. Nat. Microbiol. 5, 1079-1087.

Hyatt, D., Chen, G.L., Locascio, P.F., Land, M.L., Larimer, F.W., Hauser, L.J., 2010. Prodigal:prokaryotic gene recognition and translation initiation site identification. BMC Bioinf. 11, 119.

Kobayashi, M., Sugumaran, G., Liu, J., Shworak, N.W., Silbert, J.E., Rosenberg, R.D., 1999. Molecular cloning and characterization of a human uronyl 2-sulfotransferase that sulfates iduronyl and glucuronyl residues in dermatan/chondroitin sulfate. J. Biol. Chem. 274, 10474-10480.

Koboldt, D.C., Zhang, Q., Larson, D.E., Shen, D., McLellan, M.D., Lin, L., Miller, C.A., Mardis, E.R., Ding, L., Wilson, R.K., 2012. Varscan 2:somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res. 22, 568-576.

Kolde, R., Franzosa, E.A., Rahnavard, G., Hall, A.B., Vlamakis, H., Stevens, C., Daly, M.J., Xavier, R.J., Huttenhower, C., 2018. Host genetic variation and its microbiome interactions within the human microbiome project. Genome Med. 10, 6.

Lachance, J., Vernot, B., Elbers, C.C., Ferwerda, B., Froment, A., Bodo, J.M., Lema, G., Fu, W., Nyambo, T.B., Rebbeck, T.R., et al., 2012. Evolutionary history and adaptation from high-coverage whole-genome sequences of diverse African hunter-gatherers. Cell 150, 457-469.

Langmead, B., Salzberg, S.L., 2012. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357-359.

Li, D., Luo, R., Liu, C.M., Leung, C.M., Ting, H.F., Sadakane, K., Yamashita, H., Lam, T.W., 2016. Megahit v1.0:a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods 102, 3-11.

Lazaridis, I., Patterson, N., Mittnik, A., Renaud, G., Mallick, S., Kirsanow, K., Sudmant, P.H., Schraiber, J.G., Castellano, S., Lipson, M., et al., 2014. Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature 513, 409-413.

Lee, N., Kwon, J.H., Kim, Y.B., Kim, S.H., Park, S.J., Xu, W., Jung, H.Y., Kim, K.T., Wang, H.J., Choi, K.Y., 2015. Vaccinia-related kinase 1 promotes hepatocellular carcinoma by controlling the levels of cell cycle regulators associated with G1/S transition. Oncotarget 6, 30130-30148.

Li, H., Durbin, R., 2010. Fast and accurate long-read alignment with burrows-wheeler transform. Bioinformatics 26, 589-595.

Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., Genome Project Data Processing, S., 2009. The sequence alignment/map format and samtools. Bioinformatics 25, 2078-2079.

Li, J., Fu, R.Q., Yang, Y.J., Horz, H.P., Guan, Y.Q., Lu, Y., Lou, H.Y., Tian, L., Zheng, S.J., Liu, H.J., et al., 2018. A metagenomic approach to dissect the genetic composition of enterotypes in han Chinese and two muslim groups. Syst. Appl. Microbiol. 41, 1-12.

Li, W., Godzik, A., 2006. Cd-hit:a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658-1659.

Li, Y., Tinoco, R., Elmen, L., Segota, I., Xian, Y., Fujita, Y., Sahu, A., Zarecki, R., Marie, K., Feng, Y., et al., 2019. Gut microbiota dependent anti-tumor immunity restricts melanoma growth in Rnf5^-/- mice. Nat. Commun. 10, 1492.

Lombard, V., Golaconda Ramulu, H., Drula, E., Coutinho, P.M., Henrissat, B., 2014. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 42, D490-D495.

Lou, H.Y., Li, S.L., Jin, W.F., Fu, R.Q., Lu, D.S., Pan, X.W., Zhou, H.G., Ping, Y., Jin, L., Xu, S.H., 2015. Copy number variations and genetic admixtures in three Xinjiang ethnic minority groups. Eur. J. Hum. Genet. 23, 536-542.

Manichaikul, A., Mychaleckyj, J.C., Rich, S.S., Daly, K., Sale, M., Chen, W.M., 2010. Robust relationship inference in genome-wide association studies. Bioinformatics 26, 2867-2873.

Mantel, N., 1967. The detection of disease clustering and a generalized regression approach. Cancer Res 27, 209-220.

O'Leary, N.A., Wright, M.W., Brister, J.R., Ciufo, S., Haddad, D., McVeigh, R., Rajput, B., Robbertse, B., Smith-White, B., Ako-Adjei, D., et al., 2016. Reference sequence (RefSeq) database at NCBI:current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. 44, D733-D745.

Patterson, N., Price, A.L., Reich, D., 2006. Population structure and eigenanalysis. PLoS Genet. 2, 2074-2093.

Pianta, A., Arvikar, S., Strle, K., Drouin, E.E., Wang, Q., Costello, C.E., Steere, A.C., 2017. Evidence of the immune relevance of Prevotella copri, a gut microbe, in patients with rheumatoid arthritis. Arthritis Rheum. 69, 964-975.

Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M.A.R., Bender, D., Maller, J., Sklar, P., de Bakker, P.I.W., Daly, M.J., et al., 2007. Plink:a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559-575.

Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., Liang, S., Zhang, W., Guan, Y., Shen, D., et al., 2012. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490, 55-60.

Rook, G., Backhed, F., Levin, B.R., McFall-Ngai, M.J., McLean, A.R., 2017. Evolution, human-microbe interactions, and life history plasticity. Lancet 390, 521-530.

Rothschild, D., Weissbrod, O., Barkan, E., Kurilshikov, A., Korem, T., Zeevi, D., Costea, P.I., Godneva, A., Kalka, I.N., Bar, N., et al., 2018. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210-215.

Rousseeuw, P.J., 1987. Silhouettes:a graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53-65.

Sanchis-Chorda, J., Del Pulgar, E.M.G., Carrasco-Luna, J., Benitez-Paez, A., Sanz, Y., Codoner-Franch, P., 2019. Bifidobacterium pseudocatenulatum CECT 7765 supplementation improves inflammatory status in insulin-resistant obese children. Eur. J. Nutr. 58, 2789-2800.

Storey, J.D., Tibshirani, R., 2003. Statistical significance for genomewide studies. Proc. Natl. Acad. Sci. U. S. A. 100, 9440-9445.

Tett, A., Huang, K.D., Asnicar, F., Fehlner-Peach, H., Pasolli, E., Karcher, N., Armanini, F., Manghi, P., Bonham, K., Zolfo, M., et al., 2019. The prevotella copri complex comprises four distinct clades underrepresented in westernized populations. Cell Host Microbe 26, 666-679.

Truong, D.T., Franzosa, E.A., Tickle, T.L., Scholz, M., Weingart, G., Pasolli, E., Tett, A., Huttenhower, C., Segata, N., 2015. Metaphlan2 for enhanced metagenomic taxonomic profiling. Nat. Methods 12, 902-903.

Turpin, W., Espin-Garcia, O., Xu, W., Silverberg, M.S., Kevans, D., Smith, M.I., Guttman, D.S., Griffiths, A., Panaccione, R., Otley, A., et al., 2016. Association of host genome with intestinal microbial composition in a large healthy cohort. Nat. Genet. 48, 1413-1417.

Wang, Q., Garrity, G.M., Tiedje, J.M., Cole, J.R., 2007. Naive bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261-5267.

Weir, B.S., Cockerham, C.C., 1984. Estimating F-statistics for the analysis of population-structure. Evolution 38, 1358-1370.

Xie, H., Guo, R., Zhong, H., Feng, Q., Lan, Z., Qin, B., Ward, K.J., Jackson, M.A., Xia, Y., Chen, X., et al., 2016. Shotgun metagenomics of 250 adult twins reveals genetic and environmental impacts on the gut microbiome. Cell Syst. 3, 572-584.

Yang, C., Mogno, I., Contijoch, E.J., Borgerding, J.N., Aggarwala, V., Li, Z., Siu, S., Grasset, E.K., Helmus, D.S., Dubinsky, M.C., et al., 2020. Fecal IgA levels are determined by strain-level differences in bacteroides ovatus and are modifiable by gut microbiota manipulation. Cell Host Microbe 27, 467-475.

Yin, Y., Mao, X., Yang, J., Chen, X., Mao, F., Xu, Y., 2012. dbCAN:a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 40, W445-W451.

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