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10. Novel Common Genetic Susceptibility Loci for Colorectal Cancer

Author

Schmit, Stephanie L, Edlund, Christopher K, Schumacher, Fredrick R, Gong, Jian, Harrison, Tabitha A, Huyghe, Jeroen R, Qu, Chenxu, Melas, Marilena, Van Den Berg, David J, Wang, Hansong, Tring, Stephanie, Plummer, Sarah J, Albanes, Demetrius, Alonso, M Henar, Amos, Christopher I, Anton, Kristen, Aragaki, Aaron K, Arndt, Volker, Barry, Elizabeth L, Berndt, Sonja I, Bezieau, Stéphane, Bien, Stephanie, Bloomer, Amanda, Boehm, Juergen, Boutron-Ruault, Marie-Christine, Brenner, Hermann, Brezina, Stefanie, Buchanan, Daniel D, Butterbach, Katja, Caan, Bette J, Campbell, Peter T, Carlson, Christopher S, Castelao, Jose E, Chan, Andrew T, Chang-Claude, Jenny, Chanock, Stephen J, Cheng, Iona, Cheng, Ya-Wen, Chin, Lee Soo, Church, James M, Church, Timothy, Coetzee, Gerhard A, Cotterchio, Michelle, Correa, Marcia Cruz, Curtis, Keith R, Duggan, David, Easton, Douglas F, English, Dallas, Feskens, Edith JM, Fischer, Rocky, FitzGerald, Liesel M, Fortini, Barbara K, Fritsche, Lars G, Fuchs, Charles S, Gago-Dominguez, Manuela, Gala, Manish, Gallinger, Steven J, Gauderman, W James, Giles, Graham G, Giovannucci, Edward L, Gogarten, Stephanie M, Gonzalez-Villalpando, Clicerio, Gonzalez-Villalpando, Elena M, Grady, William M, Greenson, Joel K, Gsur, Andrea, Gunter, Marc, Haiman, Christopher A, Hampe, Jochen, Harlid, Sophia, Harju, John F, Hayes, Richard B, Hofer, Philipp, Hoffmeister, Michael, Hopper, John L, Huang, Shu-Chen, Huerta, Jose Maria, Hudson, Thomas J, Hunter, David J, Idos, Gregory E, Iwasaki, Motoki, Jackson, Rebecca D, Jacobs, Eric J, Jee, Sun Ha, Jenkins, Mark A, Jia, Wei-Hua, Jiao, Shuo, Joshi, Amit D, Kolonel, Laurence N, Kono, Suminori, Kooperberg, Charles, Krogh, Vittorio, Kuehn, Tilman, Küry, Sébastien, LaCroix, Andrea, Laurie, Cecelia A, Lejbkowicz, Flavio, Lemire, Mathieu, Lenz, Heinz-Josef, and Levine, David

Subjects
Prevention, Cancer, Digestive Diseases, Human Genome, Genetics, Clinical Research, Colo-Rectal Cancer, Aetiology, 2.1 Biological and endogenous factors, Case-Control Studies, Colorectal Neoplasms, Ethnicity, Follow-Up Studies, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Prognosis, United States, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

BackgroundPrevious genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk.MethodsWe conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided.ResultsThe discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0.ConclusionsThis study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.

Published
2019

11. Environmental change legacies attenuate disturbance response of desert soil microbiome and multifunctionality.

Author

Peng, Ziheng, Gao, Hang, Pan, Haibo, Qi, Jiejun, Chen, Shi, Liu, Yu, Wang, Yang, Jin, Chujie, Wei, Gehong, and Jiao, Shuo

Subjects
DESERT soils, ECOLOGICAL disturbances, TUNDRAS, FOSSIL microorganisms, BIOMES, CLIMATE change, WATER supply, MICROBIAL communities
Abstract

Copyright of Functional Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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16. Corrigendum: genome-wide association study of colorectal cancer identifies six new susceptibility loci.

Author

Schumacher, Fredrick R, Schmit, Stephanie L, Jiao, Shuo, Edlund, Christopher K, Wang, Hansong, Zhang, Ben, Hsu, Li, Huang, Shu-Chen, Fischer, Christopher P, Harju, John F, Idos, Gregory E, Lejbkowicz, Flavio, Manion, Frank J, McDonnell, Kevin, McNeil, Caroline E, Melas, Marilena, Rennert, Hedy S, Shi, Wei, Thomas, Duncan C, Van Den Berg, David J, Hutter, Carolyn M, Aragaki, Aaron K, Butterbach, Katja, Caan, Bette J, Carlson, Christopher S, Chanock, Stephen J, Curtis, Keith R, Fuchs, Charles S, Gala, Manish, Giovannucci, Edward L, Gogarten, Stephanie M, Hayes, Richard B, Henderson, Brian, Hunter, David J, Jackson, Rebecca D, Kolonel, Laurence N, Kooperberg, Charles, Küry, Sébastien, LaCroix, Andrea, Laurie, Cathy C, Laurie, Cecelia A, Lemire, Mathieu, Levine, David, Ma, Jing, Makar, Karen W, Qu, Conghui, Taverna, Darin, Ulrich, Cornelia M, Wu, Kana, Kono, Suminori, West, Dee W, Berndt, Sonja I, Bezieau, Stephane, Brenner, Hermann, Campbell, Peter T, Chan, Andrew T, Chang-Claude, Jenny, Coetzee, Gerhard A, Conti, David V, Duggan, David, Figueiredo, Jane C, Fortini, Barbara K, Gallinger, Steven J, Gauderman, W James, Giles, Graham, Green, Roger, Haile, Robert, Harrison, Tabitha A, Hoffmeister, Michael, Hopper, John L, Hudson, Thomas J, Jacobs, Eric, Iwasaki, Motoki, Jee, Sun Ha, Jenkins, Mark, Jia, Wei-Hua, Joshi, Amit, Li, Li, Lindor, Noralene M, Matsuo, Keitaro, Moreno, Victor, Mukherjee, Bhramar, Newcomb, Polly A, Potter, John D, Raskin, Leon, Rennert, Gad, Rosse, Stephanie, Severi, Gianluca, Schoen, Robert E, Seminara, Daniela, Shu, Xiao-Ou, Slattery, Martha L, Tsugane, Shoichiro, White, Emily, Xiang, Yong-Bing, Zanke, Brent W, Zheng, Wei, Le Marchand, Loic, Casey, Graham, and Gruber, Stephen B

Subjects
MD Multidisciplinary
Published
2015

17. Erratum: Corrigendum: Genome-wide association study of colorectal cancer identifies six new susceptibility loci

Author

Schumacher, Fredrick R, Schmit, Stephanie L, Jiao, Shuo, Edlund, Christopher K, Wang, Hansong, Zhang, Ben, Hsu, Li, Huang, Shu-Chen, Fischer, Christopher P, Harju, John F, Idos, Gregory E, Lejbkowicz, Flavio, Manion, Frank J, McDonnell, Kevin, McNeil, Caroline E, Melas, Marilena, Rennert, Hedy S, Shi, Wei, Thomas, Duncan C, Van Den Berg, David J, Hutter, Carolyn M, Aragaki, Aaron K, Butterbach, Katja, Caan, Bette J, Carlson, Christopher S, Chanock, Stephen J, Curtis, Keith R, Fuchs, Charles S, Gala, Manish, Giovannucci, Edward L, Gogarten, Stephanie M, Hayes, Richard B, Henderson, Brian, Hunter, David J, Jackson, Rebecca D, Kolonel, Laurence N, Kooperberg, Charles, Küry, Sébastien, LaCroix, Andrea, Laurie, Cathy C, Laurie, Cecelia A, Lemire, Mathieu, Levine, David, Ma, Jing, Makar, Karen W, Qu, Conghui, Taverna, Darin, Ulrich, Cornelia M, Wu, Kana, Kono, Suminori, West, Dee W, Berndt, Sonja I, Bezieau, Stephane, Brenner, Hermann, Campbell, Peter T, Chan, Andrew T, Chang-Claude, Jenny, Coetzee, Gerhard A, Conti, David V, Duggan, David, Figueiredo, Jane C, Fortini, Barbara K, Gallinger, Steven J, Gauderman, W James, Giles, Graham, Green, Roger, Haile, Robert, Harrison, Tabitha A, Hoffmeister, Michael, Hopper, John L, Hudson, Thomas J, Jacobs, Eric, Iwasaki, Motoki, Jee, Sun Ha, Jenkins, Mark, Jia, Wei-Hua, Joshi, Amit, Li, Li, Lindor, Noralene M, Matsuo, Keitaro, Moreno, Victor, Mukherjee, Bhramar, Newcomb, Polly A, Potter, John D, Raskin, Leon, Rennert, Gad, Rosse, Stephanie, Severi, Gianluca, Schoen, Robert E, Seminara, Daniela, Shu, Xiao-Ou, Slattery, Martha L, Tsugane, Shoichiro, White, Emily, Xiang, Yong-Bing, Zanke, Brent W, Zheng, Wei, Le Marchand, Loic, Casey, Graham, and Gruber, Stephen B

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Digestive Diseases, Cancer, Colo-Rectal Cancer
Published
2015

18. Identification of a common variant with potential pleiotropic effect on risk of inflammatory bowel disease and colorectal cancer

Author

Khalili, Hamed, Gong, Jian, Brenner, Hermann, Austin, Thomas R, Hutter, Carolyn M, Baba, Yoshifumi, Baron, John A, Berndt, Sonja I, Bézieau, Stéphane, Caan, Bette, Campbell, Peter T, Chang-Claude, Jenny, Chanock, Stephen J, Chen, Constance, Hsu, Li, Jiao, Shuo, Conti, David V, Duggan, David, Fuchs, Charles S, Gala, Manish, Gallinger, Steven, Haile, Robert W, Harrison, Tabitha A, Hayes, Richard, Hazra, Aditi, Henderson, Brian, Haiman, Chris, Hoffmeister, Michael, Hopper, John L, Jenkins, Mark A, Kolonel, Laurence N, Küry, Sébastien, LaCroix, Andrea, Le Marchand, Loic, Lemire, Mathieu, Lindor, Noralane M, Ma, Jing, Manson, JoAnn E, Morikawa, Teppei, Nan, Hongmei, Ng, Kimmie, Newcomb, Polly A, Nishihara, Reiko, Potter, John D, Qu, Conghui, Schoen, Robert E, Schumacher, Fredrick R, Seminara, Daniela, Taverna, Darin, Thibodeau, Stephen, Wactawski-Wende, Jean, White, Emily, Wu, Kana, Zanke, Brent W, Casey, Graham, Hudson, Thomas J, Kraft, Peter, Peters, Ulrike, Slattery, Martha L, Ogino, Shuji, and Chan, Andrew T

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Inflammatory Bowel Disease, Digestive Diseases, Clinical Research, Cancer, Genetics, Human Genome, Prevention, Colo-Rectal Cancer, Autoimmune Disease, Crohn's Disease, Aetiology, 2.1 Biological and endogenous factors, Colitis, Ulcerative, Colorectal Neoplasms, Crohn Disease, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Microsatellite Instability, Microsatellite Repeats, Polymorphism, Single Nucleotide, Risk, White People, GECCO and CCFR, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

Although genome-wide association studies (GWAS) have separately identified many genetic susceptibility loci for ulcerative colitis (UC), Crohn's disease (CD) and colorectal cancer (CRC), there has been no large-scale examination for pleiotropy, or shared genetic susceptibility, for these conditions. We used logistic regression modeling to examine the associations of 181 UC and CD susceptibility variants previously identified by GWAS with risk of CRC using data from the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. We also examined associations of significant variants with clinical and molecular characteristics in a subset of the studies. Among 11794 CRC cases and 14190 controls, rs11676348, the susceptibility single nucleotide polymorphism (SNP) for UC, was significantly associated with reduced risk of CRC (P = 7E-05). The multivariate-adjusted odds ratio of CRC with each copy of the T allele was 0.93 (95% CI 0.89-0.96). The association of the SNP with risk of CRC differed according to mucinous histological features (P heterogeneity = 0.008). In addition, the (T) allele was associated with lower risk of tumors with Crohn's-like reaction but not tumors without such immune infiltrate (P heterogeneity = 0.02) and microsatellite instability-high (MSI-high) but not microsatellite stable or MSI-low tumors (P heterogeneity = 0.03). The minor allele (T) in SNP rs11676348, located downstream from CXCR2 that has been implicated in CRC progression, is associated with a lower risk of CRC, particularly tumors with a mucinous component, Crohn's-like reaction and MSI-high. Our findings offer the promise of risk stratification of inflammatory bowel disease patients for complications such as CRC.

Published
2015

20. Genome-wide association study of colorectal cancer identifies six new susceptibility loci.

Author

Schumacher, Fredrick R, Schmit, Stephanie L, Jiao, Shuo, Edlund, Christopher K, Wang, Hansong, Zhang, Ben, Hsu, Li, Huang, Shu-Chen, Fischer, Christopher P, Harju, John F, Idos, Gregory E, Lejbkowicz, Flavio, Manion, Frank J, McDonnell, Kevin, McNeil, Caroline E, Melas, Marilena, Rennert, Hedy S, Shi, Wei, Thomas, Duncan C, Van Den Berg, David J, Hutter, Carolyn M, Aragaki, Aaron K, Butterbach, Katja, Caan, Bette J, Carlson, Christopher S, Chanock, Stephen J, Curtis, Keith R, Fuchs, Charles S, Gala, Manish, Giovannucci, Edward L, Gogarten, Stephanie M, Hayes, Richard B, Henderson, Brian, Hunter, David J, Jackson, Rebecca D, Kolonel, Laurence N, Kooperberg, Charles, Küry, Sébastien, LaCroix, Andrea, Laurie, Cathy C, Laurie, Cecelia A, Lemire, Mathieu, Levine, David, Ma, Jing, Makar, Karen W, Qu, Conghui, Taverna, Darin, Ulrich, Cornelia M, Wu, Kana, Kono, Suminori, West, Dee W, Berndt, Sonja I, Bezieau, Stéphane, Brenner, Hermann, Campbell, Peter T, Chan, Andrew T, Chang-Claude, Jenny, Coetzee, Gerhard A, Conti, David V, Duggan, David, Figueiredo, Jane C, Fortini, Barbara K, Gallinger, Steven J, Gauderman, W James, Giles, Graham, Green, Roger, Haile, Robert, Harrison, Tabitha A, Hoffmeister, Michael, Hopper, John L, Hudson, Thomas J, Jacobs, Eric, Iwasaki, Motoki, Jee, Sun Ha, Jenkins, Mark, Jia, Wei-Hua, Joshi, Amit, Li, Li, Lindor, Noralene M, Matsuo, Keitaro, Moreno, Victor, Mukherjee, Bhramar, Newcomb, Polly A, Potter, John D, Raskin, Leon, Rennert, Gad, Rosse, Stephanie, Severi, Gianluca, Schoen, Robert E, Seminara, Daniela, Shu, Xiao-Ou, Slattery, Martha L, Tsugane, Shoichiro, White, Emily, Xiang, Yong-Bing, Zanke, Brent W, and Zheng, Wei

Subjects
Humans, Colorectal Neoplasms, Genetic Predisposition to Disease, Odds Ratio, Case-Control Studies, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Genetics, Digestive Diseases, Prevention, Cancer, Human Genome, Colo-Rectal Cancer, 2.1 Biological and endogenous factors, MD Multidisciplinary
Abstract

Genetic susceptibility to colorectal cancer is caused by rare pathogenic mutations and common genetic variants that contribute to familial risk. Here we report the results of a two-stage association study with 18,299 cases of colorectal cancer and 19,656 controls, with follow-up of the most statistically significant genetic loci in 4,725 cases and 9,969 controls from two Asian consortia. We describe six new susceptibility loci reaching a genome-wide threshold of P

Published
2015

21. Whole-Exome Sequencing Identifies Rare and Low-Frequency Coding Variants Associated with LDL Cholesterol

Author

Lange, Leslie A, Hu, Youna, Zhang, He, Xue, Chenyi, Schmidt, Ellen M, Tang, Zheng-Zheng, Bizon, Chris, Lange, Ethan M, Smith, Joshua D, Turner, Emily H, Jun, Goo, Kang, Hyun Min, Peloso, Gina, Auer, Paul, Li, Kuo-ping, Flannick, Jason, Zhang, Ji, Fuchsberger, Christian, Gaulton, Kyle, Lindgren, Cecilia, Locke, Adam, Manning, Alisa, Sim, Xueling, Rivas, Manuel A, Holmen, Oddgeir L, Gottesman, Omri, Lu, Yingchang, Ruderfer, Douglas, Stahl, Eli A, Duan, Qing, Li, Yun, Durda, Peter, Jiao, Shuo, Isaacs, Aaron, Hofman, Albert, Bis, Joshua C, Correa, Adolfo, Griswold, Michael E, Jakobsdottir, Johanna, Smith, Albert V, Schreiner, Pamela J, Feitosa, Mary F, Zhang, Qunyuan, Huffman, Jennifer E, Crosby, Jacy, Wassel, Christina L, Do, Ron, Franceschini, Nora, Martin, Lisa W, Robinson, Jennifer G, Assimes, Themistocles L, Crosslin, David R, Rosenthal, Elisabeth A, Tsai, Michael, Rieder, Mark J, Farlow, Deborah N, Folsom, Aaron R, Lumley, Thomas, Fox, Ervin R, Carlson, Christopher S, Peters, Ulrike, Jackson, Rebecca D, van Duijn, Cornelia M, Uitterlinden, André G, Levy, Daniel, Rotter, Jerome I, Taylor, Herman A, Gudnason, Vilmundur, Siscovick, David S, Fornage, Myriam, Borecki, Ingrid B, Hayward, Caroline, Rudan, Igor, Chen, Y Eugene, Bottinger, Erwin P, Loos, Ruth JF, Sætrom, Pål, Hveem, Kristian, Boehnke, Michael, Groop, Leif, McCarthy, Mark, Meitinger, Thomas, Ballantyne, Christie M, Gabriel, Stacey B, O’Donnell, Christopher J, Post, Wendy S, North, Kari E, Reiner, Alexander P, Boerwinkle, Eric, Psaty, Bruce M, Altshuler, David, Kathiresan, Sekar, Lin, Dan-Yu, Jarvik, Gail P, Cupples, L Adrienne, Kooperberg, Charles, Wilson, James G, Nickerson, Deborah A, Abecasis, Goncalo R, and Rich, Stephen S

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Prevention, Clinical Research, Heart Disease, Cardiovascular, Atherosclerosis, Aetiology, 2.1 Biological and endogenous factors, Adult, Aged, Apolipoproteins E, Cholesterol, LDL, Cohort Studies, Dyslipidemias, Exome, Female, Follow-Up Studies, Gene Frequency, Genetic Code, Genome-Wide Association Study, Genotype, Humans, Lipase, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Proprotein Convertase 9, Proprotein Convertases, Receptors, LDL, Sequence Analysis, DNA, Serine Endopeptidases, NHLBI Grand Opportunity Exome Sequencing Project, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or

Published
2014

22. Soil labile organic carbon fractions mediate microbial community assembly processes during long‐term vegetation succession in a semiarid region.

Author

Shi, Jingwei, Yang, Lin, Liao, Yang, Li, Jiwei, Jiao, Shuo, Shangguan, Zhouping, and Deng, Lei

Subjects
MICROBIAL communities, ARID regions, ECOLOGICAL disturbances, SOIL microbiology, ECOSYSTEM dynamics
Abstract

This article discusses a study conducted in the Ziwuling region, which has experienced 160 years of secondary succession. The research focuses on the role of labile organic carbon (OC) fractions in shaping microbial community assembly during this succession. The study finds that deterministic processes, particularly homogeneous selection, are crucial in microbial community assembly. The research also identifies key microbial taxa that drive community assembly and shows that their abundance decreases over time. The findings emphasize the significance of labile OC fractions and microbial community dynamics in ecosystem function. Additionally, the study reveals that labile SOC is the primary driver of microbial community assembly, with labile organic carbon fractions having a greater impact than stable organic carbon. The researchers also observe that soil bacteria influence fungal community assembly and that bacterial alpha diversity plays a role in driving fungal assembly. Overall, the study underscores the importance of labile organic carbon in determining microbial community assembly during long-term vegetation succession. [Extracted from the article]

Published
2023
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23. Identification of Genetic Susceptibility Loci for Colorectal Tumors in a Genome-Wide Meta-analysis

Author

Peters, Ulrike, Jiao, Shuo, Schumacher, Fredrick R, Hutter, Carolyn M, Aragaki, Aaron K, Baron, John A, Berndt, Sonja I, Bézieau, Stéphane, Brenner, Hermann, Butterbach, Katja, Caan, Bette J, Campbell, Peter T, Carlson, Christopher S, Casey, Graham, Chan, Andrew T, Chang–Claude, Jenny, Chanock, Stephen J, Chen, Lin S, Coetzee, Gerhard A, Coetzee, Simon G, Conti, David V, Curtis, Keith R, Duggan, David, Edwards, Todd, Fuchs, Charles S, Gallinger, Steven, Giovannucci, Edward L, Gogarten, Stephanie M, Gruber, Stephen B, Haile, Robert W, Harrison, Tabitha A, Hayes, Richard B, Henderson, Brian E, Hoffmeister, Michael, Hopper, John L, Hudson, Thomas J, Hunter, David J, Jackson, Rebecca D, Jee, Sun Ha, Jenkins, Mark A, Jia, Wei–Hua, Kolonel, Laurence N, Kooperberg, Charles, Küry, Sébastien, LaCroix, Andrea Z, Laurie, Cathy C, Laurie, Cecelia A, Le Marchand, Loic, Lemire, Mathieu, Levine, David, Lindor, Noralane M, Liu, Yan, Ma, Jing, Makar, Karen W, Matsuo, Keitaro, Newcomb, Polly A, Potter, John D, Prentice, Ross L, Qu, Conghui, Rohan, Thomas, Rosse, Stephanie A, Schoen, Robert E, Seminara, Daniela, Shrubsole, Martha, Shu, Xiao–Ou, Slattery, Martha L, Taverna, Darin, Thibodeau, Stephen N, Ulrich, Cornelia M, White, Emily, Xiang, Yongbing, Zanke, Brent W, Zeng, Yi–Xin, Zhang, Ben, Zheng, Wei, Hsu, Li, and Registry, Genetics and Epidemiology of Colorectal Cancer Consortium Colon Cancer Family

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Nutrition and Dietetics, Digestive Diseases, Prevention, Genetics, Cancer, Colo-Rectal Cancer, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Age Distribution, Aged, Aged, 80 and over, Colorectal Neoplasms, Cyclin D2, DNA-Binding Proteins, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Incidence, Laminin, Male, Middle Aged, Polymorphism, Single Nucleotide, Prognosis, Risk Assessment, Sex Distribution, T-Box Domain Proteins, Colon Cancer Family Registry and the Genetics and Epidemiology of Colorectal Cancer Consortium, Neurosciences, Paediatrics and Reproductive Medicine, Gastroenterology & Hepatology, Clinical sciences, Nutrition and dietetics
Abstract

Background & aimsHeritable factors contribute to the development of colorectal cancer. Identifying the genetic loci associated with colorectal tumor formation could elucidate the mechanisms of pathogenesis.MethodsWe conducted a genome-wide association study that included 14 studies, 12,696 cases of colorectal tumors (11,870 cancer, 826 adenoma), and 15,113 controls of European descent. The 10 most statistically significant, previously unreported findings were followed up in 6 studies; these included 3056 colorectal tumor cases (2098 cancer, 958 adenoma) and 6658 controls of European and Asian descent.ResultsBased on the combined analysis, we identified a locus that reached the conventional genome-wide significance level at less than 5.0 × 10(-8): an intergenic region on chromosome 2q32.3, close to nucleic acid binding protein 1 (most significant single nucleotide polymorphism: rs11903757; odds ratio [OR], 1.15 per risk allele; P = 3.7 × 10(-8)). We also found evidence for 3 additional loci with P values less than 5.0 × 10(-7): a locus within the laminin gamma 1 gene on chromosome 1q25.3 (rs10911251; OR, 1.10 per risk allele; P = 9.5 × 10(-8)), a locus within the cyclin D2 gene on chromosome 12p13.32 (rs3217810 per risk allele; OR, 0.84; P = 5.9 × 10(-8)), and a locus in the T-box 3 gene on chromosome 12q24.21 (rs59336; OR, 0.91 per risk allele; P = 3.7 × 10(-7)).ConclusionsIn a large genome-wide association study, we associated polymorphisms close to nucleic acid binding protein 1 (which encodes a DNA-binding protein involved in DNA repair) with colorectal tumor risk. We also provided evidence for an association between colorectal tumor risk and polymorphisms in laminin gamma 1 (this is the second gene in the laminin family to be associated with colorectal cancers), cyclin D2 (which encodes for cyclin D2), and T-box 3 (which encodes a T-box transcription factor and is a target of Wnt signaling to β-catenin). The roles of these genes and their products in cancer pathogenesis warrant further investigation.

Published
2013

24. A systematic mapping approach of 16q12.2/FTO and BMI in more than 20,000 African Americans narrows in on the underlying functional variation: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.

Author

Peters, Ulrike, North, Kari E, Sethupathy, Praveen, Buyske, Steve, Haessler, Jeff, Jiao, Shuo, Fesinmeyer, Megan D, Jackson, Rebecca D, Kuller, Lew H, Rajkovic, Aleksandar, Lim, Unhee, Cheng, Iona, Schumacher, Fred, Wilkens, Lynne, Li, Rongling, Monda, Keri, Ehret, Georg, Nguyen, Khanh-Dung H, Cooper, Richard, Lewis, Cora E, Leppert, Mark, Irvin, Marguerite R, Gu, C Charles, Houston, Denise, Buzkova, Petra, Ritchie, Marylyn, Matise, Tara C, Le Marchand, Loic, Hindorff, Lucia A, Crawford, Dana C, Haiman, Christopher A, and Kooperberg, Charles

Subjects
Humans, Obesity, Genetic Predisposition to Disease, Adaptor Proteins, Signal Transducing, Proteins, Body Mass Index, Chromosome Mapping, Linkage Disequilibrium, Alleles, Adult, Aged, Aged, 80 and over, Middle Aged, Continental Population Groups, African Americans, European Continental Ancestry Group, Female, Male, Genome-Wide Association Study, Metagenomics, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Adaptor Proteins, Signal Transducing, and over, Genetics, Developmental Biology
Abstract

Genetic variants in intron 1 of the fat mass- and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI-associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646-kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3 × 10(-6)) had not been highlighted in previous studies. While rs56137030was correlated at r(2)>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.

Published
2013

25. Characterization of Gene–Environment Interactions for Colorectal Cancer Susceptibility Loci

Author

Hutter, Carolyn M, Chang-Claude, Jenny, Slattery, Martha L, Pflugeisen, Bethann M, Lin, Yi, Duggan, David, Nan, Hongmei, Lemire, Mathieu, Rangrej, Jagadish, Figueiredo, Jane C, Jiao, Shuo, Harrison, Tabitha A, Liu, Yan, Chen, Lin S, Stelling, Deanna L, Warnick, Greg S, Hoffmeister, Michael, Küry, Sébastien, Fuchs, Charles S, Giovannucci, Edward, Hazra, Aditi, Kraft, Peter, Hunter, David J, Gallinger, Steven, Zanke, Brent W, Brenner, Hermann, Frank, Bernd, Ma, Jing, Ulrich, Cornelia M, White, Emily, Newcomb, Polly A, Kooperberg, Charles, LaCroix, Andrea Z, Prentice, Ross L, Jackson, Rebecca D, Schoen, Robert E, Chanock, Stephen J, Berndt, Sonja I, Hayes, Richard B, Caan, Bette J, Potter, John D, Hsu, Li, Bézieau, Stéphane, Chan, Andrew T, Hudson, Thomas J, and Peters, Ulrike

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Digestive Diseases, Nutrition, Prevention, Cancer, Colo-Rectal Cancer, Human Genome, Colorectal Neoplasms, Diet, Gene-Environment Interaction, Genetic Predisposition to Disease, Genotype, Humans, Polymorphism, Single Nucleotide, Oncology and Carcinogenesis, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

Genome-wide association studies (GWAS) have identified more than a dozen loci associated with colorectal cancer (CRC) risk. Here, we examined potential effect-modification between single-nucleotide polymorphisms (SNP) at 10 of these loci and probable or established environmental risk factors for CRC in 7,016 CRC cases and 9,723 controls from nine cohort and case-control studies. We used meta-analysis of an efficient empirical-Bayes estimator to detect potential multiplicative interactions between each of the SNPs [rs16892766 at 8q23.3 (EIF3H/UTP23), rs6983267 at 8q24 (MYC), rs10795668 at 10p14 (FLJ3802842), rs3802842 at 11q23 (LOC120376), rs4444235 at 14q22.2 (BMP4), rs4779584 at 15q13 (GREM1), rs9929218 at 16q22.1 (CDH1), rs4939827 at 18q21 (SMAD7), rs10411210 at 19q13.1 (RHPN2), and rs961253 at 20p12.3 (BMP2)] and select major CRC risk factors (sex, body mass index, height, smoking status, aspirin/nonsteroidal anti-inflammatory drug use, alcohol use, and dietary intake of calcium, folate, red meat, processed meat, vegetables, fruit, and fiber). The strongest statistical evidence for a gene-environment interaction across studies was for vegetable consumption and rs16892766, located on chromosome 8q23.3, near the EIF3H and UTP23 genes (nominal P(interaction) = 1.3 × 10(-4); adjusted P = 0.02). The magnitude of the main effect of the SNP increased with increasing levels of vegetable consumption. No other interactions were statistically significant after adjusting for multiple comparisons. Overall, the association of most CRC susceptibility loci identified in initial GWAS seems to be invariant to the other risk factors considered; however, our results suggest potential modification of the rs16892766 effect by vegetable consumption.

Published
2012

26. Meta-analysis of new genome-wide association studies of colorectal cancer risk

Author

Peters, Ulrike, Hutter, Carolyn M, Hsu, Li, Schumacher, Fredrick R, Conti, David V, Carlson, Christopher S, Edlund, Christopher K, Haile, Robert W, Gallinger, Steven, Zanke, Brent W, Lemire, Mathieu, Rangrej, Jagadish, Vijayaraghavan, Raakhee, Chan, Andrew T, Hazra, Aditi, Hunter, David J, Ma, Jing, Fuchs, Charles S, Giovannucci, Edward L, Kraft, Peter, Liu, Yan, Chen, Lin, Jiao, Shuo, Makar, Karen W, Taverna, Darin, Gruber, Stephen B, Rennert, Gad, Moreno, Victor, Ulrich, Cornelia M, Woods, Michael O, Green, Roger C, Parfrey, Patrick S, Prentice, Ross L, Kooperberg, Charles, Jackson, Rebecca D, LaCroix, Andrea Z, Caan, Bette J, Hayes, Richard B, Berndt, Sonja I, Chanock, Stephen J, Schoen, Robert E, Chang-Claude, Jenny, Hoffmeister, Michael, Brenner, Hermann, Frank, Bernd, Bézieau, Stéphane, Küry, Sébastien, Slattery, Martha L, Hopper, John L, Jenkins, Mark A, Le Marchand, Loic, Lindor, Noralane M, Newcomb, Polly A, Seminara, Daniela, Hudson, Thomas J, Duggan, David J, Potter, John D, and Casey, Graham

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Genetics, Colo-Rectal Cancer, Aging, Human Genome, Cancer, Prevention, Digestive Diseases, 2.1 Biological and endogenous factors, Aetiology, Colorectal Neoplasms, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Odds Ratio, Polymorphism, Single Nucleotide, Risk Factors, Complementary and Alternative Medicine, Paediatrics and Reproductive Medicine, Genetics & Heredity, Reproductive medicine
Abstract

Colorectal cancer is the second leading cause of cancer death in developed countries. Genome-wide association studies (GWAS) have successfully identified novel susceptibility loci for colorectal cancer. To follow up on these findings, and try to identify novel colorectal cancer susceptibility loci, we present results for GWAS of colorectal cancer (2,906 cases, 3,416 controls) that have not previously published main associations. Specifically, we calculated odds ratios and 95% confidence intervals using log-additive models for each study. In order to improve our power to detect novel colorectal cancer susceptibility loci, we performed a meta-analysis combining the results across studies. We selected the most statistically significant single nucleotide polymorphisms (SNPs) for replication using ten independent studies (8,161 cases and 9,101 controls). We again used a meta-analysis to summarize results for the replication studies alone, and for a combined analysis of GWAS and replication studies. We measured ten SNPs previously identified in colorectal cancer susceptibility loci and found eight to be associated with colorectal cancer (p value range 0.02 to 1.8 × 10(-8)). When we excluded studies that have previously published on these SNPs, five SNPs remained significant at p

Published
2012

28. Investigating the genetic relationship between Alzheimer’s disease and cancer using GWAS summary statistics

Author

Feng, Yen-Chen Anne, Cho, Kelly, Lindstrom, Sara, Kraft, Peter, Cormack, Jean, Liang, Liming, Driver, Jane A., Blalock, Kendra, Campbell, Peter T., Casey, Graham, Conti, David V., Edlund, Christopher K., Figueiredo, Jane, James Gauderman, W., Gong, Jian, Green, Roger C., Gruber, Stephen B., Harju, John F., Harrison, Tabitha A., Jacobs, Eric J., Jenkins, Mark A., Jiao, Shuo, Li, Li, Lin, Yi, Manion, Frank J., Moreno, Victor, Mukherjee, Bhramar, Peters, Ulrike, Raskin, Leon, Schumacher, Fredrick R., Seminara, Daniela, Severi, Gianluca, Stenzel, Stephanie L., Thomas, Duncan C., Hopper, John L., Southey, Melissa C., Makalic, Enes, Schmidt, Daniel F., Fletcher, Olivia, Peto, Julian, Gibson, Lorna, dos Santos Silva, Isabel, Hunter, David J., Lindström, Sara, Kraft, Peter, Ahsan, Habib, Whittemore, Alice, Waisfisz, Quinten, Meijers-Heijboer, Hanne, Adank, Muriel, van der Luijt, Rob B., Uitterlinden, Andre G., Hofman, Albert, Meindl, Alfons, Schmutzler, Rita K., Müller-Myhsok, Bertram, Lichtner, Peter, Nevanlinna, Heli, Muranen, Taru A., Aittomäki, Kristiina, Blomqvist, Carl, Chang-Claude, Jenny, Hein, Rebecca, Dahmen, Norbert, Beckman, Lars, Crisponi, Laura, Hall, Per, Czene, Kamila, Irwanto, Astrid, Liu, Jianjun, Easton, Douglas F., Turnbull, Clare, Rahman, Nazneen, Kote-Jarai, Zsofia, Muir, Kenneth, Giles, Graham, Severi, Gianluca, Neal, David, Donovan, Jenny L., Hamdy, Freddie C., Wiklund, Fredrik, Gronberg, Henrik, Haiman, Christopher, Schumacher, Fred, Travis, Ruth, Riboli, Elio, Kraft, Peter, Hunter, David, Gapstur, Susan, Berndt, Sonja, Chanock, Stephen, Han, Younghun, Su, Li, Wei, Yongyue, Hung, Rayjean J., Brhane, Yonathan, McLaughlin, John, Brennan, Paul, McKay, James D., Bickeböller, Heike, Rosenberger, Albert, Houlston, Richard S., Caporaso, Neil, Landi, Maria Teresa, Heinrich, Joachim, Risch, Angela, Wu, Xifeng, Ye, Yuanqing, Christiani, David C., Amos, Christopher I., IGAP Consortium, Colorectal Transdisciplinary Study (CORECT), Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), and Transdisciplinary Research in Cancer of the Lung (TRICL)

Published
2017
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29. Additional file 1 of Plant domestication shapes rhizosphere microbiome assembly and metabolic functions

Author

Yue, Hong, Yue, Wenjie, Jiao, Shuo, Kim, Hyun, Lee, Yong-Hwan, Wei, Gehong, Song, Weining, and Shu, Duntao

Abstract

Additional file 1: Fig. S1. Alpha diversity included Shannon index, Simpson index, ACE index, and Chao index for bacteria and fungi communities in different accession of domesticated and wild wheats. Errors bars represent standard errors (n= 5). Different lowcase letters above the bars indicate significant differences (P< 0.05), based on Kruskal-Wallis test. Fig. S2. The Bray-Curtis dissimilarity of bacteria and fungi communities in domesticated and wild wheats. DB1~DB3 and WB1-WB3 indicates that samples are affiliated with bulk soil in the domesticated and wild wheats, respectively. DT1~DT3 and WT1-WT3 indicates that samples are affiliated with rhizosphere soil in the domesticated and wild wheats, respectively. The dots represent the values of Bray-Curtis dissimilarity between replicates in the any of groups. The details on the D1-D3 and W1-W3 groups are available in Table S2. Fig. S3. Constrained Analysis of Principal Coordinates analysis (CAP) ordination constraned to domestication status (left panel), habitat type (middle panel), and genome group (right panel) based on Bray-Curtis metric of bacteria and fungi communities. Variance of community dissimilarity among five treatment were draw from ANOVA-like permutation analysis. Fig. S4. Principal coordinate analysis ordinations (PCoA) for bacteria and fungi communities in domesticated and wild wheats. Fig. S5. Distribution of dominant phyla and genus in the bacteria and fungi communities in domesticated and wild wheats. Fig. S6. Amplicon sequences variants (ASVs) form bulk soils responsible for the community differences in the wild wheats and domesticated wheats that are calculated by a differential abundance test and random forest classification. (A) and (B) The volcano plot illustrating the enrichment and depletion patterns of rhizosphere bacterial and fungal microbiomes in the three wild wheats compared with three domesticated wheat accessions. DI, depleted index; DSI, dissimilarity index. (C) and (D) Joyplots showing the relative abundance profiles of top 20 ASVs in bacterial and fungal communities that are revealed by a Random forest (RF) classifier. The top ASVs on the genus level are listed along the y-axis represent their importance in contributing to the accuracy of domesticated and wild wheats prediction by calculating their mean decrease accuracy in the RF model. Fig. S7. Microbial interkingdom association networks and node-level topological features for bulk soils. (A) and (B) Interkingdom co-occurrence networks in the domesticated and wild wheats. Only compositionality-robust (p > 0.7) and statistically significant (q < 0.01) correlations were shown. The size of each node indicates the relative abundance of each ASV. The color of each node represents the bacteria or fungi taxa. Blue solid lines represent co-presence associations and red line represent mutual exclusive correlations. The thickness of each link line is proportional to the correlation coefficients of the connections. The keystone taxa and dominant modules for each networks were also shown. (C) and (D) Box graphs illustrating the node-level topological features of each networks, including betweenness and degree. Comparison of these two features demonstrating the high degree and low betweenness for the keystone taxa. Bar diagrams showing the proportion of inter-and intra-kingdom edges of positive or negative correlations in the rhizosphere network. The significance of differences between domesticated and wild wheats were determined by Kruskal-Wallis test. Fig. S8. Network modularity profiles of rhizosphere soil and bulk soil microbial communities in the domesticated and wild wheats. The eight bar plots in the left and middle columns represents microbial taxa on the class level in the module I and module II. The four bar plots in the right columns indicates the proportion of ASVs that affiliated with bacteria and fungi communities in the module I and module II. Fig. S9. The volcano plot illustrating the enrichment and depletion patterns of KO functional categories and KO pathway in the wild wheats compared with domesticated wheat accessions. The KOs were colored by their categorization as “wild-enriched”, “domesticated-enriched”, and “non-differential” according to their values of Log2(count per million) and Log2(fold change). Fig. S10. (A) Nonmetric multidimensional scaling (NMDS) ordination of KEGG Orthology, CAZyome, and COG based on Bray-Curtis distances. The significance of differences between domesticated and wild wheats were determined by Kruskal-Wallis test. (B) Heat map illustrating the relative abundance (Z-score) of functional genes (based on KO) affiliated with carbon cycling in different accession of wheats. Fig. S11. Heat map illustrating the relative abundance (Z-score) of functional genes (based on KO) affiliated with nitrogen (A) and phosphorus (B) cycling in different accession of wheats. Fig. S12. (A-H) Random forest (RF) mean predictor importance of KO functional categories as drivers for the plant phenotypes, including (A) plant height (PH), (B) chlorophyll content (CC), (C) ear length (EL), (D) subsegment length (SSL), (E) Tiller, (F) thousand grain weight (TGW), (G) seed length (SL), and (H) seed width (SW), respectively. The accuracy importance measure was calculated for each tree and averaged over the forest (2000 trees). Percentage increase in the mean squared error (MSE) of variables were applied to evaluate the importance of these predictors, and higher MSE% values represent more important predictors. Significance levels of each predictor are as follows: *P< 0.05, **P< 0.01, and ***P< 0.001. Fig. S13. Partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for root exudates that extracted from roots of wild and domesticated wheats. Fig. S14. (A) The average relative abundance of enriched root exudates in the wild and domesticated wheats. (B) The fold changes of enriched metabolites in domesticated and wild wheats. The error bars represent standard errors of sample replicates and asterisks (*) indicate metabolic categories that are significantly more predominant in wild or domesticated wheats (P value

Published
2023
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30. Additional file 3 of Plant domestication shapes rhizosphere microbiome assembly and metabolic functions

Author

Yue, Hong, Yue, Wenjie, Jiao, Shuo, Kim, Hyun, Lee, Yong-Hwan, Wei, Gehong, Song, Weining, and Shu, Duntao

Abstract

Additional file 3: Method S1. Experiment design and field site management. Method S2. Samples collection, DNA extraction, PCR amplification and amplicon sequencing. Method S3. Shotgun metagenomics sequencing. Method S4. Root exudate collection and LC-MS analysis. Method S5. Microbiota inoculation experiment. Method S6. Statistical analyses.

Published
2023
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38. Temporal Dynamics of Rhizosphere Communities Across the Life Cycle of Panax notoginseng

Author

Wei, Guangfei, primary, Li, Mengzhi, additional, Zhang, Guozhuang, additional, Chen, Zhongjian, additional, Wei, Fugang, additional, Jiao, Shuo, additional, Qian, Jun, additional, Wang, Yong, additional, Wei, Jianhe, additional, Wang, Yitao, additional, Meng, Xiangxiao, additional, Fitzgerald, Martin, additional, Yu, Yuqi, additional, Dong, Linlin, additional, and Chen, Shilin, additional

Published
2022
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41. Common and rare von Willebrand factor (VWF) coding variants, VWF levels, and factor VIII levels in African Americans: the NHLBI Exome Sequencing Project

Author

Johnsen, Jill M., Auer, Paul L., Morrison, Alanna C., Jiao, Shuo, Wei, Peng, Haessler, Jeffrey, Fox, Keolu, McGee, Sean R., Smith, Joshua D., Carlson, Christopher S., Smith, Nicholas, Boerwinkle, Eric, Kooperberg, Charles, Nickerson, Deborah A., Rich, Stephen S., Green, David, Peters, Ulrike, Cushman, Mary, and Reiner, Alex P.

Published
2013
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49. Additional file 2 of Coexistence patterns of soil methanogens are closely tied to methane generation and community assembly in rice paddies

Author

Li, Dong, Haowei Ni, Jiao, Shuo, Yahai Lu, Jizhong Zhou, Sun, Bo, and Liang, Yuting

Abstract

Additional file 1: Figure S1. Sampling and sequencing of methanogens. Abscissa: the number of sequences randomly selected from the sample; ordinate: the species diversity and the number of OTU that can be represented by the random sampling sequence. Each curve in the figure represents a sample, marked with a different color. Figure S2. Linear regression of methanogenic archaea α-diversity and MAT (A) and CH4 emissions (B). Solid lines denote significant relationship with 95% confidence interval (shadow area). Dotted line denotes P > 0.05. Figure S3. The co-occurrence network structure of methanogenic community of 39 plots. Percentage in the top right corner indicates the proportion of 33 key OTUs (Table S4) in total node numbers of each network. Figure S4. Contributions of climatic variables and soil properties to the network topological attributes based on correlation and random forest regression model. Circle size represents the variable importance (that is, proportion of explained variability calculated via forest regression analysis analysis). Colors represent Spearman’s correlation coefficients (node: node number; edge: edge number; modularity: modularity; positive: positive correlations; negative: negative correlations; Avg.C.C: average clustering coefficient; N.D: network diameter; C.P.L: characteristic path length). Figure S5. Spearman’s correlation analysis of network topological attributes and richness. Blue shaded area is a 95% confidence interval. Figure S6. Spearman’s correlation analysis of network topological attributes and CH4 emissions. Dotted lines denote P > 0.05. Solid lines indicate a significant correlation (P < 0.05), with the blue shaded area showing the 95% confidence interval. Figure S7. Relative abundance of OTUs of the five groups of methanogenic archaeal communities. Each column followed by different letters differed significantly at P < 0.05 (ANOVA, Duncan test). (A.endemic: always endemic group; C.endemic: conditionally endemic group; C.common: conditionally common group; A.common: always common group). Figure S8. Relative abundance frequency histogram of 33 keystone OTUs in 429 samples. The blue histogram indicates rare OTUs (average relative abundance < 1% in 429 samples). The red histogram indicates abundant OTUs (average relative abundance > 1% in 429 samples), and the inset represents low-frequency OTUs with average relative abundance < 1%. Figure S9. The relative abundance of keystone taxa (at the family level) changes with temperature. (HL: 1.5°C, CC: 4.5°C, SY:8.3°C, YY: 14.4°C, FQ:13.9°C, LA: 16.1°C, QZ:17.9°C, ZX:17°C, JO:18.8°C, CT:19°C, HY:18°C, QX:21.6°C, HK:23.8°C). Figure S10. The relationship between keystone species and microbial functional genes related to methane generation depicted as colored segments in a CIRCOS plot. Ribbons connecting two segments indicate the interaction between the two. The size of the ribbon is proportional to the number of links. Table S1. Geographic information of 13 sampling regions with 3 plots in each region. Table S2. The topological features of the co-occurrence network in each plot. Table S3. Partial mantel test between network topology attributes and variables. Table S4. Changes of network topology attributes with latitude. Table S5. Information of 33 keystone OTUs involved in common co-occurrence relationship.

Published
2021
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