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11. Archaeology Augments Tibet's Genetic History [Response]

Author

BRANTINGHAM, P. JEFFREY, RHODE, DAVID, MADSEN, DAVID B., YI, XIN, LIANG, YU, HUERTA-SANCHEZ, EMILIA, JIN, XIN, CUO, ZHA XI PING, POOL, JOHN E., XU, XUN, JIANG, HUI, VINCKENBOSCH, NICOLAS, KORNELIUSSEN, THORFINN SAND, ZHENG, HANCHENG, LIU, TAO, HE, WEIMING, LI, KUI, LUO, RUIBANG, NIE, XIFANG, WU, HONGLONG, ZHAO, MEIRU, CAO, HONGZHI, ZOU, JING, SHAN, YING, LI, SHUZHENG, YANG, QI, ASAN, NI, PEIXIANG, TIAN, GENG, XU, JUNMING, LIU, XIAO, JIANG, TAO, WU, RENHUA, ZHOU, GUANGYU, TANG, MEIFANG, QIN, JUNJIE, WANG, TONG, FENG, SHUIJIAN, LI, GUOHONG, LUOSANG, JIANGBAI, WANG, WEI, CHEN, FANG, WANG, YADING, ZHENG, XIAOGUANG, LI, ZHUO, BIANBA, ZHUOMA, YANG, GE, WANG, XINPING, TANG, SHUHUI, GAO, GUOYI, CHEN, YONG, LUO, ZHEN, GUSANG, LAMU, CAO, ZHENG, ZHANG, QINGHUI, OUYANG, WEIHAN, REN, XIAOLI, LIANG, HUIQING, ZHENG, HUISONG, HUANG, YEBO, LI, JINGXIANG, BOLUND, LARS, KRISTIANSEN, KARSTEN, LI, YINGRUI, ZHANG, YONG, ZHANG, XIUQING, LI, RUIQIANG, LI, SONGGANG, YANG, HUANMING, NIELSEN, RASMUS, WANG, JUN, and WANG, JIAN

Published
2010

12. Sequencing of 50 Human Exomes Reveals Adaptation to High Altitude

Author

Yi, Xin, Liang, Yu, Huerta-Sanchez, Emilia, Jin, Xin, Cuo, Zha Xi Ping, Pool, John E., Xu, Xun, Jiang, Hui, Vinckenbosch, Nicolas, Korneliussen, Thorfinn Sand, Zheng, Hancheng, Liu, Tao, He, Weiming, Li, Kui, Luo, Ruibang, Nie, Xifang, Wu, Honglong, Zhao, Meiru, Cao, Hongzhi, Zou, Jing, Shan, Ying, Li, Shuzheng, Yang, Qi, Asan, Ni, Peixiang, Tian, Geng, Xu, Junming, Liu, Xiao, Jiang, Tao, Wu, Renhua, Zhou, Guangyu, Tang, Meifang, Qin, Junjie, Wang, Tong, Feng, Shuijian, Li, Guohong, Huasang, Luosang, Jiangbai, Wang, Wei, Chen, Fang, Wang, Yading, Zheng, Xiaoguang, Li, Zhuo, Bianba, Zhuoma, Yang, Ge, Wang, Xinping, Tang, Shuhui, Gao, Guoyi, Chen, Yong, Luo, Zhen, Gusang, Lamu, Cao, Zheng, Zhang, Qinghui, Ouyang, Weihan, Ren, Xiaoli, Liang, Huiqing, Zheng, Huisong, Huang, Yebo, Li, Jingxiang, Bolund, Lars, Kristiansen, Karsten, Li, Yingrui, Zhang, Yong, Zhang, Xiuqing, Li, Ruiqiang, Li, Songgang, Yang, Huanming, Nielsen, Rasmus, Wang, Jun, and Wang, Jian

Published
2010

15. Genome‐wide analysis of epigenetic and transcriptional changes associated with heterosis in pigeonpea

Author

Mukesh Lodha, Vikas K. Singh, Iain R. Searle, Annapurna Chitikineni, Scott A. Jackson, Kulbhushan Saxena, Kyung Do Kim, Vanika Garg, Rachit K. Saxena, Rajeev K. Varshney, Tang Meifang, C. V. Sameer Kumar, Xin Liu, Pallavi Sinha, Wayne Powell, Aamir W. Khan, Yuqi Li, Sandip M. Kale, Eviatar Nevo, and Xun Xu

Subjects
0106 biological sciences, 0301 basic medicine, Heterosis, Plant Science, Biology, 01 natural sciences, Epigenesis, Genetic, Transcriptome, 03 medical and health sciences, Gene Expression Regulation, Plant, microRNA, Gene expression, Hybrid Vigor, heterosis, small RNA, Epigenetics, Gene, Research Articles, miRNA, Epigenomics, Genetics, Gene Expression Profiling, pigeonpea, DNA Methylation, 030104 developmental biology, differentially expression gene, epigenomics, DNA methylation, Agronomy and Crop Science, Genome, Plant, Research Article, 010606 plant biology & botany, Biotechnology
Abstract

Summary Hybrids are extensively used in agriculture to deliver an increase in yield, yet the molecular basis of heterosis is not well understood. Global DNA methylation analysis, transcriptome analysis and small RNA profiling were aimed to understand the epigenetic effect of the changes in gene expression level in the two hybrids and their parental lines. Increased DNA methylation was observed in both the hybrids as compared to their parents. This increased DNA methylation in hybrids showed that majority of the 24‐nt siRNA clusters had higher expression in hybrids than the parents. Transcriptome analysis revealed that various phytohormones (auxin and salicylic acid) responsive hybrid‐MPV DEGs were significantly altered in both the hybrids in comparison to MPV. DEGs associated with plant immunity and growth were overexpressed whereas DEGs associated with basal defence level were repressed. This antagonistic patterns of gene expression might contribute to the greater growth of the hybrids. It was also noticed that some common as well as unique changes in the regulatory pathways were associated with heterotic growth in both the hybrids. Approximately 70% and 67% of down‐regulated hybrid‐MPV DEGs were found to be differentially methylated in ICPH 2671 and ICPH 2740 hybrid, respectively. This reflected the association of epigenetic regulation in altered gene expressions. Our findings also revealed that miRNAs might play important roles in hybrid vigour in both the hybrids by regulating their target genes, especially in controlling plant growth and development, defence and stress response pathways. The above finding provides an insight into the molecular mechanism of pigeonpea heterosis.

Published
2020
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16. A global reference for human genetic variation

Author

Altshuler, David M., (Co-Chair), Durbin, Richard M., (Co-Chair, Principal Investigator), Donnelly, Peter, Green, Eric D., Nickerson, Deborah A., Boerwinkle, Eric, Doddapaneni, Harsha, Han, Yi, Korchina, Viktoriya, Kovar, Christie, Lee, Sandra, Muzny, Donna, Reid, Jeffrey G., Zhu, Yiming, Wang, Jun, (Principal Investigator), Chang, Yuqi, Feng, Qiang, Fang, Xiaodong, Guo, Xiaosen, Jian, Min, Jiang, Hui, Jin, Xin, Lan, Tianming, Li, Guoqing, Li, Jingxiang, Li, Yingrui, Liu, Shengmao, Liu, Xiao, Lu, Yao, Ma, Xuedi, Tang, Meifang, Wang, Bo, Wang, Guangbiao, Wu, Honglong, Wu, Renhua, Xu, Xun, Yin, Ye, Zhang, Dandan, Zhang, Wenwei, Zhao, Jiao, Zhao, Meiru, Zheng, Xiaole, Lander, Eric S., (Principal Investigator), Gabriel, Stacey B., (Co-Chair), Gupta, Namrata, Gharani, Neda, Toji, Lorraine H., Gerry, Norman P., Resch, Alissa M., Barker, Jonathan, Gil, Laurent, Hunt, Sarah E., Kelman, Gavin, Kulesha, Eugene, Leinonen, Rasko, McLaren, William M., Radhakrishnan, Rajesh, Roa, Asier, Smirnov, Dmitriy, Smith, Richard E., Streeter, Ian, Thormann, Anja, Toneva, Iliana, Vaughan, Brendan, Zheng-Bradley, Xiangqun, Bentley, David R., (Principal Investigator), Grocock, Russell, Humphray, Sean, James, Terena, Kingsbury, Zoya, Lehrach, Hans, (Principal Investigator), Sudbrak, Ralf, (Project Leader), Albrecht, Marcus W., Amstislavskiy, Vyacheslav S., Borodina, Tatiana A., Lienhard, Matthias, Mertes, Florian, Sultan, Marc, Timmermann, Bernd, Yaspo, Marie-Laure, Mardis, Elaine R., (Co-Principal Investigator) (Co-Chair), Wilson, Richard K., (Co-Principal Investigator), Fulton, Lucinda, Fulton, Robert, Ananiev, Victor, Belaia, Zinaida, Beloslyudtsev, Dimitriy, Bouk, Nathan, Chen, Chao, Church, Deanna, Cohen, Robert, Cook, Charles, Garner, John, Hefferon, Timothy, Kimelman, Mikhail, Liu, Chunlei, Lopez, John, Meric, Peter, O’Sullivan, Chris, Ostapchuk, Yuri, Phan, Lon, Ponomarov, Sergiy, Schneider, Valerie, Shekhtman, Eugene, Sirotkin, Karl, Slotta, Douglas, Zhang, Hua, Balasubramaniam, Senduran, Burton, John, Danecek, Petr, Keane, Thomas M., Kolb-Kokocinski, Anja, McCarthy, Shane, Stalker, James, Quail, Michael, Schmidt, Jeanette P., (Principal Investigator), Davies, Christopher J., Gollub, Jeremy, Webster, Teresa, Wong, Brant, Zhan, Yiping, Auton, Adam, (Principal Investigator), Campbell, Christopher L., Kong, Yu, Marcketta, Anthony, Yu, Fuli, (Project Leader), Antunes, Lilian, Bainbridge, Matthew, Sabo, Aniko, Huang, Zhuoyi, Coin, Lachlan J. M., Fang, Lin, Li, Qibin, Li, Zhenyu, Lin, Haoxiang, Liu, Binghang, Luo, Ruibang, Shao, Haojing, Xie, Yinlong, Ye, Chen, Yu, Chang, Zhang, Fan, Zheng, Hancheng, Zhu, Hongmei, Alkan, Can, Dal, Elif, Kahveci, Fatma, Garrison, Erik P., (Project Lead), Kural, Deniz, Lee, Wan-Ping, Leong, Wen Fung, Stromberg, Michael, Ward, Alistair N., Wu, Jiantao, Zhang, Mengyao, Daly, Mark J., (Principal Investigator), DePristo, Mark A., (Project Leader), Handsaker, Robert E., (Project Leader), Banks, Eric, Bhatia, Gaurav, del Angel, Guillermo, Genovese, Giulio, Li, Heng, Kashin, Seva, Nemesh, James C., Poplin, Ryan E., Yoon, Seungtai C., (Principal Investigator), Lihm, Jayon, Makarov, Vladimir, Clark, Andrew G., (Principal Investigator), Gottipati, Srikanth, Keinan, Alon, Rodriguez-Flores, Juan L., Rausch, Tobias, (Project Leader), Fritz, Markus H., Stütz, Adrian M., Beal, Kathryn, Datta, Avik, Herrero, Javier, Ritchie, Graham R. S., Zerbino, Daniel, Sabeti, Pardis C., (Principal Investigator), Shlyakhter, Ilya, Schaffner, Stephen F., Vitti, Joseph, Cooper, David N., (Principal Investigator), Ball, Edward V., Stenson, Peter D., Barnes, Bret, Bauer, Markus, Cheetham, Keira R., Cox, Anthony, Eberle, Michael, Kahn, Scott, Murray, Lisa, Peden, John, Shaw, Richard, Kenny, Eimear E., (Principal Investigator), Batzer, Mark A., (Principal Investigator), Konkel, Miriam K., Walker, Jerilyn A., MacArthur, Daniel G., (Principal Investigator), Lek, Monkol, Herwig, Ralf, Koboldt, Daniel C., Larson, David, Ye, Kai, Gravel, Simon, Swaroop, Anand, Chew, Emily, Lappalainen, Tuuli, (Principal Investigator), Erlich, Yaniv, (Principal Investigator), Gymrek, Melissa, Willems, Thomas Frederick, Simpson, Jared T., Shriver, Mark D., (Principal Investigator), Rosenfeld, Jeffrey A., (Principal Investigator), Montgomery, Stephen B., (Principal Investigator), De La Vega, Francisco M., (Principal Investigator), Byrnes, Jake K., Carroll, Andrew W., DeGorter, Marianne K., Lacroute, Phil, Maples, Brian K., Martin, Alicia R., Moreno-Estrada, Andres, Shringarpure, Suyash S., Zakharia, Fouad, Halperin, Eran, (Principal Investigator), Baran, Yael, Cerveira, Eliza, Hwang, Jaeho, Malhotra, Ankit, (Co-Project Lead), Plewczynski, Dariusz, Radew, Kamen, Romanovitch, Mallory, Zhang, Chengsheng, (Co-Project Lead), Hyland, Fiona C. L., Craig, David W., (Principal Investigator), Christoforides, Alexis, Homer, Nils, Izatt, Tyler, Kurdoglu, Ahmet A., Sinari, Shripad A., Squire, Kevin, Xiao, Chunlin, Sebat, Jonathan, (Principal Investigator), Antaki, Danny, Gujral, Madhusudan, Noor, Amina, Ye, Kenny, Burchard, Esteban G., (Principal Investigator), Hernandez, Ryan D., (Principal Investigator), Gignoux, Christopher R., Haussler, David, (Principal Investigator), Katzman, Sol J., Kent, James W., Howie, Bryan, Ruiz-Linares, Andres, (Principal Investigator), Dermitzakis, Emmanouil T., (Principal Investigator), Devine, Scott E., (Principal Investigator), Abecasis, Gonçalo R., (Principal Investigator) (Co-Chair), Kang, Hyun Min, (Project Leader), Kidd, Jeffrey M., (Principal Investigator), Blackwell, Tom, Caron, Sean, Chen, Wei, Emery, Sarah, Fritsche, Lars, Fuchsberger, Christian, Jun, Goo, Li, Bingshan, Lyons, Robert, Scheller, Chris, Sidore, Carlo, Song, Shiya, Sliwerska, Elzbieta, Taliun, Daniel, Tan, Adrian, Welch, Ryan, Wing, Mary Kate, Zhan, Xiaowei, Awadalla, Philip, (Principal Investigator), Hodgkinson, Alan, Li, Yun, Shi, Xinghua, (Principal Investigator), Quitadamo, Andrew, Lunter, Gerton, (Principal Investigator), McVean, Gil A., (Principal Investigator) (Co-Chair), Marchini, Jonathan L., (Principal Investigator), Myers, Simon, (Principal Investigator), Churchhouse, Claire, Delaneau, Olivier, Gupta-Hinch, Anjali, Kretzschmar, Warren, Iqbal, Zamin, Mathieson, Iain, Menelaou, Androniki, Rimmer, Andy, Xifara, Dionysia K., Oleksyk, Taras K., (Principal Investigator), Fu, Yunxin, (Principal Investigator), Liu, Xiaoming, Xiong, Momiao, Jorde, Lynn, (Principal Investigator), Witherspoon, David, Xing, Jinchuan, Browning, Brian L., (Principal Investigator), Browning, Sharon R., (Principal Investigator), Hormozdiari, Fereydoun, Sudmant, Peter H., Khurana, Ekta, (Principal Investigator), Hurles, Matthew E., (Principal Investigator), Albers, Cornelis A., Ayub, Qasim, Chen, Yuan, Colonna, Vincenza, Jostins, Luke, Walter, Klaudia, Xue, Yali, Abyzov, Alexej, Balasubramanian, Suganthi, Chen, Jieming, Clarke, Declan, Fu, Yao, Harmanci, Arif O., Jin, Mike, Lee, Donghoon, Liu, Jeremy, Mu, Xinmeng Jasmine, Zhang, Jing, Zhang, Yan, McCarroll, Steven A., (Principal Investigator), Hartl, Chris, Shakir, Khalid, Degenhardt, Jeremiah, Korbel, Jan O., (Principal Investigator) (Co-Chair), Meiers, Sascha, Raeder, Benjamin, Casale, Francesco Paolo, Stegle, Oliver, Lameijer, Eric-Wubbo, Ding, Li, (Principal Investigator), Hall, Ira, Lee, Charles, (Principal Investigator) (Co-Chair), Bafna, Vineet, Michaelson, Jacob, Gardner, Eugene J., (Project Leader), Mills, Ryan E., (Principal Investigator), Dayama, Gargi, Chen, Ken, (Principle Investigator), Fan, Xian, Chong, Zechen, Chen, Tenghui, Eichler, Evan E., (Principal Investigator) (Co-Chair), Chaisson, Mark J., Huddleston, John, Malig, Maika, Nelson, Bradley J., Parrish, Nicholas F., Blackburne, Ben, Lindsay, Sarah J., Ning, Zemin, Zhang, Yujun, Lam, Hugo, Sisu, Cristina, Gibbs, Richard A., (Principal Investigator) (Co-Chair), Challis, Danny, Evani, Uday S., Lu, James, Nagaswamy, Uma, Yu, Jin, Li, Wangshen, Marth, Gabor T., (Principal Investigator) (Co-Chair), Habegger, Lukas, Yu, Haiyuan, (Principal Investigator), Cunningham, Fiona, Dunham, Ian, Lage, Kasper, (Principal Investigator), Jespersen, Jakob Berg, Horn, Heiko, Tyler-Smith, Chris, (Principal Investigator) (Co-Chair), Gerstein, Mark B., (Principal Investigator) (Co-Chair), Kim, Donghoon, Desalle, Rob, Narechania, Apurva, Wilson Sayres, Melissa A., Bustamante, Carlos D., (Principal Investigator) (Co-Chair), Mendez, Fernando L., Poznik, David G., Underhill, Peter A., Coin, Lachlan, (Principal Investigator), Mittelman, David, Banerjee, Ruby, Cerezo, Maria, Fitzgerald, Thomas W., Louzada, Sandra, Massaia, Andrea, Ritchie, Graham R., Yang, Fengtang, Kalra, Divya, Hale, Walker, Dan, Xu, Flicek, Paul, (Principal Investigator) (Co-Chair), Clarke, Laura, (Project Lead), Sherry, Stephen T., (Principal Investigator) (Co-Chair), Chakravarti, Aravinda, (Co-Chair), Knoppers, Bartha M., (Co-Chair), Barnes, Kathleen C., Beiswanger, Christine, Cai, Hongyu, Cao, Hongzhi, Henn, Brenna, Jones, Danielle, Kaye, Jane S., Kent, Alastair, Kerasidou, Angeliki, Mathias, Rasika, Ossorio, Pilar N., Parker, Michael, Rotimi, Charles N., Royal, Charmaine D., Sandoval, Karla, Su, Yeyang, Tian, Zhongming, Tishkoff, Sarah, Via, Marc, Wang, Yuhong, Yang, Ling, Zhu, Jiayong, Bodmer, Walter, Bedoya, Gabriel, Cai, Zhiming, Gao, Yang, Chu, Jiayou, Peltonen, Leena, Garcia-Montero, Andres, Orfao, Alberto, Dutil, Julie, Martinez-Cruzado, Juan C., Mathias, Rasika A., Hennis, Anselm, Watson, Harold, McKenzie, Colin, Qadri, Firdausi, LaRocque, Regina, Deng, Xiaoyan, Asogun, Danny, Folarin, Onikepe, Happi, Christian, Omoniwa, Omonwunmi, Stremlau, Matt, Tariyal, Ridhi, Jallow, Muminatou, Joof, Fatoumatta Sisay, Corrah, Tumani, Rockett, Kirk, Kwiatkowski, Dominic, Kooner, Jaspal, Hiê`n, Trâ`n Tinh, Dunstan, Sarah J., Hang, Nguyen Thuy, Fonnie, Richard, Garry, Robert, Kanneh, Lansana, Moses, Lina, Schieffelin, John, Grant, Donald S., Gallo, Carla, Poletti, Giovanni, Saleheen, Danish, Rasheed, Asif, Brooks, Lisa D., Felsenfeld, Adam L., McEwen, Jean E., Vaydylevich, Yekaterina, Duncanson, Audrey, Dunn, Michael, Schloss, Jeffery A., and Yang, Huanming

Published
2015
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18. Effects of Waterlogging on Soybean Rhizosphere Microbial Community Profiled Using Illumina MiSeq, LoopSeq, and PacBio 16S rRNA Genes Sequences

Author

Tang Meifang, Cheng Lang, Zhong Hongbin, Liu Qi, Wang ShaSha, Lian Tengxiang, Yu TaoBing, Nian Hai, and Zhou Yuan

Subjects
Rhizosphere, Microbial population biology, Botany, Illumina miseq, Biology, 16S ribosomal RNA, Gene, Waterlogging (agriculture)
Abstract

Background: Waterlogging on the global environment has led to a significant decline in crop yields. However, the response of plant-associated microbes to waterlogging stress on different soils is not known. Moreover, there are few reports on whether this response is influenced by different sequencing methods. In this study, the effects of waterlogging on soybean rhizosphere microbial structure on two types of soil were examined, using a short reading 16S rRNA sequencing variable region V4 and two full-length 16S rRNA sequencing variable regions V1-V9.Results: The results revealed some similarities and differences in three sequencing methods for soybean rhizosphere microbial response to waterlogging stress. Based on CPCoA analysis, all the sequencing methods showed that waterlogging on both types of soil significantly affected the bacterial community structure of the soybean rhizosphere, and increased the relative abundance of Geobacter. However, the full-length sequencing methods had higher classification resolution than short-read sequencing (except phylum level of all sequencing methods and class level of LoopSeq sequencing). Further, analysis on OTU level and network showed that waterlogging increased the abundance of some microorganisms related to nitrogen cycle using V4 sequencing, and microorganisms related to phosphorus cycling when using two full-length sequencing methods. This is in line with the core microbial analysis. Environmental factors affecting the structure of microbial communities differed among sequencing methods.Conclusions: In summary, this piece of work detected the effects of waterlogging on soybean rhizosphere microbes using three sequencing methods. Some functional microbes were enriched in the rhizosphere, which may benefit soybean in resisting waterlogging stress. On the other hand, there were several differences in results among the three sequencing methods which might affect the response of rhizosphere microbial structure to stress. Our analysis of sequencing methods on various levels provides some useful information on environmental samples sequencing.

Published
2021
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19. Application research of chronic disease health management in an urban community based on the PRECEDE-PROCEED model in the long-term management of diabetes mellitus

Author

Kan, Wei, Yang, Rong, and Tang, Meifang

Subjects
Original Article
Abstract

Objective: To evaluate the application of chronic disease health management in an urban community in the long-term management of diabetes mellitus (DM) based on the PRECEDE-PROCEED model. Methods: The PRECEDE-PROCEED model combines PRECEDE (predisposing, enabling and reinforcing constructs in educational diagnosis and evaluation) with PROCEED (policy, management and organization constructs in educational and environmental intervention). A total of 96 diabetic patients treated in our hospital were selected and divided into two groups by random number table, with 48 cases in each group. The routine group was given routine health management, while the PP group was given the urban community chronic disease health management based on the PRECEDE-PROCEED model in addition to the routine health management. After six months of management, the patients’ effect was evaluated by comparing the blood glucose, diabetes knowledge, self-efficacy, self-management level and quality of life between the two groups. Results: The FPG, 2hPG and HbAlc levels of the PP group were lower than those of the routine group after six months of management (all P

Published
2021

20. Additional file 1 of Potential of fecal microbiota for detection and postoperative surveillance of colorectal cancer

Author

Yao, Qiulin, Tang, Meifang, Zeng, Liuhong, Chu, Zhonghua, Sheng, Hui, Zhang, Yuyu, Zhou, Yuan, Zhang, Hongyun, Jiang, Huayan, and Ye, Mingzhi

Abstract

Additional file 1 Table S1. OTUs stat of all groups. Table S2. Bacterial microbiota composition of each group at the genus level. Table S3. Feature list of LefSe analysis. Table S4. Survival state and basic information of 32 patients (paired samples). Figure S1. Venn of OTUs in all groups. Figure S2. Alpha diversity. Observed species, Chao and Ace reflected community richness; Shannon and Simpson reflected community diversity; Good’s coverage reflected the sequencing coverage. Figure S3. Microbiota composition of each group at the phyla level. The relative abundance less that 0.5% in all samples were combined as others. Figure S4. Microbiota composition of each group at the species level. The relative abundance less that 0.5% in all samples were combined as others.

Published
2021
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21. An integrated map of genetic variation from 1,092 human genomes

Author

McVean, Gil A., Altshuler, David M., Durbin, Richard M., Abecasis, Gonçalo R., Bentley, David R., Chakravarti, Aravinda, Clark, Andrew G., Donnelly, Peter, Eichler, Evan E., Flicek, Paul, Gabriel, Stacey B., Gibbs, Richard A., Green, Eric D., Hurles, Matthew E., Knoppers, Bartha M., Korbel, Jan O., Lander, Eric S., Lee, Charles, Lehrach, Hans, Mardis, Elaine R., Marth, Gabor T., Nickerson, Deborah A., Schmidt, Jeanette P., Sherry, Stephen T., Wang, Jun, Wilson, Richard K., Dinh, Huyen, Kovar, Christie, Lee, Sandra, Lewis, Lora, Muzny, Donna, Reid, Jeff, Wang, Min, Wang, Jun, Fang, Xiaodong, Guo, Xiaosen, Jian, Min, Jiang, Hui, Jin, Xin, Li, Guoqing, Li, Jingxiang, Li, Yingrui, Li, Zhuo, Liu, Xiao, Lu, Yao, Ma, Xuedi, Su, Zhe, Tai, Shuaishuai, Tang, Meifang, Wang, Bo, Wang, Guangbiao, Wu, Honglong, Wu, Renhua, Yin, Ye, Zhang, Wenwei, Zhao, Jiao, Zhao, Meiru, Zheng, Xiaole, Zhou, Yan, Lander, Eric S., Gabriel, Stacey B., Gupta, Namrata, Flicek, Paul, Clarke, Laura, Leinonen, Rasko, Smith, Richard E., Zheng-Bradley, Xiangqun, Bentley, David R., Grocock, Russell, Humphray, Sean, James, Terena, Kingsbury, Zoya, Lehrach, Hans, Sudbrak, Ralf, Albrecht, Marcus W., Amstislavskiy, Vyacheslav S., Borodina, Tatiana A., Lienhard, Matthias, Mertes, Florian, Sultan, Marc, Timmermann, Bernd, Yaspo, Marie-Laure, Sherry, Stephen T., McVean, Gil A., Mardis, Elaine R., Wilson, Richard K., Fulton, Lucinda, Fulton, Robert, Weinstock, George M., Durbin, Richard M., Balasubramaniam, Senduran, Burton, John, Danecek, Petr, Keane, Thomas M., Kolb-Kokocinski, Anja, McCarthy, Shane, Stalker, James, Quail, Michael, Schmidt, Jeanette P., Davies, Christopher J., Gollub, Jeremy, Webster, Teresa, Wong, Brant, Zhan, Yiping, Auton, Adam, Yu, Fuli, Bainbridge, Matthew, Challis, Danny, Evani, Uday S., Lu, James, Nagaswamy, Uma, Sabo, Aniko, Wang, Yi, Yu, Jin, Coin, Lachlan J. M., Fang, Lin, Li, Qibin, Li, Zhenyu, Lin, Haoxiang, Liu, Binghang, Luo, Ruibang, Qin, Nan, Shao, Haojing, Wang, Bingqiang, Xie, Yinlong, Ye, Chen, Yu, Chang, Zhang, Fan, Zheng, Hancheng, Zhu, Hongmei, Garrison, Erik P., Kural, Deniz, Lee, Wan-Ping, Fung Leong, Wen, Ward, Alistair N., Wu, Jiantao, Zhang, Mengyao, Lee, Charles, Griffin, Lauren, Hsieh, Chih-Heng, Mills, Ryan E., Shi, Xinghua, von Grotthuss, Marcin, Zhang, Chengsheng, Daly, Mark J., DePristo, Mark A., Banks, Eric, Bhatia, Gaurav, Carneiro, Mauricio O., del Angel, Guillermo, Genovese, Giulio, Handsaker, Robert E., Hartl, Chris, McCarroll, Steven A., Nemesh, James C., Poplin, Ryan E., Schaffner, Stephen F., Shakir, Khalid, Yoon, Seungtai C., Lihm, Jayon, Makarov, Vladimir, Jin, Hanjun, Kim, Wook, Cheol Kim, Ki, Korbel, Jan O., Rausch, Tobias, Beal, Kathryn, Cunningham, Fiona, Herrero, Javier, McLaren, William M., Ritchie, Graham R. S., Clark, Andrew G., Gottipati, Srikanth, Keinan, Alon, Rodriguez-Flores, Juan L., Sabeti, Pardis C., Grossman, Sharon R., Tabrizi, Shervin, Tariyal, Ridhi, Cooper, David N., Ball, Edward V., Stenson, Peter D., Barnes, Bret, Bauer, Markus, Keira Cheetham, R., Cox, Tony, Eberle, Michael, Kahn, Scott, Murray, Lisa, Peden, John, Shaw, Richard, Ye, Kai, Batzer, Mark A., Konkel, Miriam K., Walker, Jerilyn A., MacArthur, Daniel G., Lek, Monkol, Sudbrak, Herwig, Ralf, Shriver, Mark D., Bustamante, Carlos D., Byrnes, Jake K., De La Vega, Francisco M., Gravel, Simon, Kenny, Eimear E., Kidd, Jeffrey M., Lacroute, Phil, Maples, Brian K., Moreno-Estrada, Andres, Zakharia, Fouad, Halperin, Eran, Baran, Yael, Craig, David W., Christoforides, Alexis, Homer, Nils, Izatt, Tyler, Kurdoglu, Ahmet A., Sinari, Shripad A., Squire, Kevin, Xiao, Chunlin, Sebat, Jonathan, Bafna, Vineet, Ye, Kenny, Burchard, Esteban G., Hernandez, Ryan D., Gignoux, Christopher R., Haussler, David, Katzman, Sol J., James Kent, W., Howie, Bryan, Ruiz-Linares, Andres, Dermitzakis, Emmanouil T., Lappalainen, Tuuli, Devine, Scott E., Liu, Xinyue, Maroo, Ankit, Tallon, Luke J., Rosenfeld, Jeffrey A., Min Kang, Hyun, Anderson, Paul, Angius, Andrea, Bigham, Abigail, Blackwell, Tom, Busonero, Fabio, Cucca, Francesco, Fuchsberger, Christian, Jones, Chris, Jun, Goo, Li, Yun, Lyons, Robert, Maschio, Andrea, Porcu, Eleonora, Reinier, Fred, Sanna, Serena, Schlessinger, David, Sidore, Carlo, Tan, Adrian, Kate Trost, Mary, Awadalla, Philip, Hodgkinson, Alan, Lunter, Gerton, McVean, Gil A., Marchini, Jonathan L., Myers, Simon, Churchhouse, Claire, Delaneau, Olivier, Gupta-Hinch, Anjali, Iqbal, Zamin, Mathieson, Iain, Rimmer, Andy, Xifara, Dionysia K., Oleksyk, Taras K., Fu, Yunxin, Liu, Xiaoming, Xiong, Momiao, Jorde, Lynn, Witherspoon, David, Xing, Jinchuan, Eichler, Evan E., Browning, Brian L., Alkan, Can, Hajirasouliha, Iman, Hormozdiari, Fereydoun, Ko, Arthur, Sudmant, Peter H., Mardis, Elaine R., Chen, Ken, Chinwalla, Asif, Ding, Li, Dooling, David, Koboldt, Daniel C., McLellan, Michael D., Wallis, John W., Wendl, Michael C., Zhang, Qunyuan, Hurles, Matthew E., Tyler-Smith, Chris, Albers, Cornelis A., Ayub, Qasim, Chen, Yuan, Coffey, Alison J., Colonna, Vincenza, Huang, Ni, Jostins, Luke, Li, Heng, Scally, Aylwyn, Walter, Klaudia, Xue, Yali, Zhang, Yujun, Gerstein, Mark B., Abyzov, Alexej, Balasubramanian, Suganthi, Chen, Jieming, Clarke, Declan, Fu, Yao, Habegger, Lukas, Harmanci, Arif O., Jin, Mike, Khurana, Ekta, Jasmine Mu, Xinmeng, Sisu, Cristina, Lee, Charles, McCarroll, Steven A., Degenhardt, Jeremiah, Korbel, Jan O., Stütz, Adrian M., Church, Deanna, Michaelson, Jacob J., Eichler, Evan E., Hurles, Matthew E., Blackburne, Ben, Lindsay, Sarah J., Ning, Zemin, DePristo, Mark A., Min Kang, Hyun, Mardis, Elaine R., Yu, Fuli, Michelson, Leslie P., Tyler-Smith, Chris, Frankish, Adam, Harrow, Jennifer, Fowler, Gerald, Hale, Walker, Kalra, Divya, Flicek, Paul, Clarke, Laura, Barker, Jonathan, Kelman, Gavin, Kulesha, Eugene, Radhakrishnan, Rajesh, Roa, Asier, Smirnov, Dmitriy, Streeter, Ian, Toneva, Iliana, Vaughan, Brendan, Sherry, Stephen T., Ananiev, Victor, Belaia, Zinaida, Beloslyudtsev, Dimitriy, Bouk, Nathan, Chen, Chao, Cohen, Robert, Cook, Charles, Garner, John, Hefferon, Timothy, Kimelman, Mikhail, Liu, Chunlei, Lopez, John, Meric, Peter, OʼSullivan, Chris, Ostapchuk, Yuri, Phan, Lon, Ponomarov, Sergiy, Schneider, Valerie, Shekhtman, Eugene, Sirotkin, Karl, Slotta, Douglas, Zhang, Hua, Chakravarti, Aravinda, Knoppers, Bartha M., Barnes, Kathleen C., Beiswanger, Christine, Burchard, Esteban G., Bustamante, Carlos D., Cai, Hongyu, Cao, Hongzhi, Durbin, Richard M., Gharani, Neda, Henn, Brenna, Jones, Danielle, Jorde, Lynn, Kaye, Jane S., Kent, Alastair, Kerasidou, Angeliki, Mathias, Rasika, Ossorio, Pilar N., Parker, Michael, Reich, David, Rotimi, Charles N., Royal, Charmaine D., Sandoval, Karla, Su, Yeyang, Sudbrak, Ralf, Tian, Zhongming, Tishkoff, Sarah, Toji, Lorraine H., Tyler-Smith, Chris, Via, Marc, Wang, Yuhong, Yang, Huanming, Yang, Ling, Zhu, Jiayong, Bodmer, Walter, Bedoya, Gabriel, Ruiz-Linares, Andres, Zhi Ming, Cai, Yang, Gao, Jia You, Chu, Peltonen, Leena, Garcia-Montero, Andres, Orfao, Alberto, Dutil, Julie, Martinez-Cruzado, Juan C., Oleksyk, Taras K., Brooks, Lisa D., Felsenfeld, Adam L., McEwen, Jean E., Clemm, Nicholas C., Duncanson, Audrey, Dunn, Michael, Guyer, Mark S., Peterson, Jane L., Abecasis, Goncalo R., and Auton, Adam

Published
2012
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23. Melatonin inhibiting the survival of human gastric cancer cells under ER stress involving autophagy and Ras‐Raf‐MAPK signalling

Author

Huang, Yongye, primary, Yuan, Kexun, additional, Tang, Meifang, additional, Yue, Jiaming, additional, Bao, Lijun, additional, Wu, Shuang, additional, Zhang, Yanxin, additional, Li, Yin, additional, Wang, Yihang, additional, Ou, Xu, additional, Gou, Jiaxin, additional, Zhao, Qi, additional, and Yuan, Lin, additional

Published
2020
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24. Comparative Analysis of Sample Extraction and Library Construction for Shotgun Metagenomics

Author

Peng, Zonghui, Zhu, Xiaolong, Wang, Zhijiao, Yan, Xianting, Wang, Guangbiao, Tang, Meifang, Jiang, Awei, Kristiansen, Karsten, Peng, Zonghui, Zhu, Xiaolong, Wang, Zhijiao, Yan, Xianting, Wang, Guangbiao, Tang, Meifang, Jiang, Awei, and Kristiansen, Karsten

Abstract

Human fecal specimens, serve as important materials, are widely used in the field of microbiome research, in which inconsistent results have been a pressing issue. The possible attribute factors have been proposed including the specimen status after preservation, extracted DNA quality, library preparation protocol, and sample DNA input. In this study, quality comparisons for shotgun metagenomics sequencing were performed between 2 DNA extraction methods for fresh and freeze-thaw samples, 2 library preparation protocols, and various sample inputs. The results indicate that Mag-Bind® Universal Metagenomics Kit (OM) outperformed DNeasy PowerSoil Kit (QP) with a higher DNA quantity. Controlling on library preparation protocol, OM detected on-average more genes than QP. For library construction comparison by controlling on the same DNA sample, KAPA Hyper Prep Kit (KH) outperformed the TruePrep DNA Library Prep Kit V2 (TP) with the higher number of detected genes number and Shannon index. No significant differences were found in taxonomy between 2 library preparation protocols using the fresh, freeze-thaw and mock community samples. No significant difference was observed between 250 and 50 ng DNA inputs for library preparation on both fresh and freeze-thaw samples. Through the preliminary study, a combined protocol is recommended for performing metagenomics studies, by using OM method plus KH protocol as well as suitable DNA quantity on either fresh or freeze-thaw samples. Our findings provide clues for potential variations from various DNA extraction methods, library protocols, and sample DNA inputs, which are critical for consistent and comprehensive profiling of the human gut microbiome.

Published
2020

25. transcriptome atlas and interactive analysis platform for autoimmune disease.

Author

Shen, Zhuoqiao, Fang, Minghao, Sun, Wujianan, Tang, Meifang, Liu, Nianping, Zhu, Lin, Liu, Qian, Li, Bin, Sun, Ruoming, Shi, Yu, Guo, Chuang, Lin, Jun, and Qu, Kun

Subjects
AUTOIMMUNE diseases, TRANSCRIPTOMES, CELL communication, WEB databases, NUCLEOTIDE sequencing
Abstract

With the rapid development of next-generation sequencing technology, many laboratories have produced a large amount of single-cell transcriptome data of blood and tissue samples from patients with autoimmune diseases, which enables in-depth studies of the relationship between gene transcription and autoimmune diseases. However, there is still a lack of a database that integrates the large amount of autoimmune disease transcriptome sequencing data and conducts effective analysis. In this study, we developed a user-friendly web database tool, Interactive Analysis and Atlas for Autoimmune disease (IAAA), which integrates bulk RNA-seq data of 929 samples of 10 autoimmune diseases and single-cell RNA-seq data of 783 203 cells in 96 samples of 6 autoimmune diseases. IAAA also provides customizable analysis modules, including gene expression, difference, correlation, similar gene detection and cell–cell interaction, and can display results in three formats (plot, table and pdf) through custom parameters. IAAA provides valuable data resources for researchers studying autoimmune diseases and helps users deeply explore the potential value of the current transcriptome data. IAAA is available. Database URL : http://galaxy.ustc.edu.cn/IAAA [ABSTRACT FROM AUTHOR]

Published
2022
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27. Melatonin inhibiting the survival of human gastric cancer cells under ER stress involving autophagy and Ras‐Raf‐MAPK signalling.

Author

Huang, Yongye, Yuan, Kexun, Tang, Meifang, Yue, Jiaming, Bao, Lijun, Wu, Shuang, Zhang, Yanxin, Li, Yin, Wang, Yihang, Ou, Xu, Gou, Jiaxin, Zhao, Qi, and Yuan, Lin

Subjects
STOMACH cancer, CANCER cells, MELATONIN, AUTOPHAGY, CELL cycle
Abstract

Melatonin exhibits antitumour activities in the treatment of many human cancers. In the present study, we aimed to improve the therapeutic potential of melatonin in gastric cancer. Our results confirmed that melatonin dose‐dependently suppressed the proliferation and necrosis, and increased G0/G1 phase arrest, apoptosis, autophagy and endoplasmic reticulum (ER) stress. The Ras‐Raf‐MAPK signalling pathway was activated in cells after melatonin treatment. RNA‐seq was performed and GSEA analysis further confirmed that many down‐regulated genes in melatonin‐treated cells were associated with proliferation. However, GSEA analysis also indicated that many pathways related to metastasis were increased after melatonin treatment. Subsequently, combinatorial treatment was conducted to further investigate the therapeutic outcomes of melatonin. A combination of melatonin and thapsigargin increased the apoptotic rate and G0/G1 cell cycle arrest when compared to treatment with melatonin alone. Melatonin in combination with thapsigargin triggered the increased expression of Bip, LC3‐II, phospho‐Erk1/2 and phospho‐p38 MAPK. In addition, STF‐083010, an IRE1a inhibitor, further exacerbated the decrease in survival rate induced by combinatorial treatment with melatonin and thapsigargin. Collectively, melatonin was effective in gastric cancer treatment by modifying ER stress. [ABSTRACT FROM AUTHOR]

Published
2021
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28. Resequencing of 200 human exomes identifies an excess of low-frequency non-synonymous coding variants

Author

Li, Yingrui, Vinckenbosch, Nicolas, Tian, Geng, Huerta-Sanchez, Emilia, Jiang, Tao, Jiang, Hui, Albrechtsen, Anders, Andersen, Gitte, Cao, Hongzhi, Korneliussen, Thorfinn Sand, Grarup, Niels, Guo, Yiran, Hellman, Ines, Jin, Xin, Li, Qibin, Liu, Jiangtao, Liu, Xiao, Sparsø, Thomas, Tang, Meifang, Wu, Honglong, Wu, Renhua, Yu, Chang, Zheng, Hancheng, Astrup, Arne, Bolund, Lars, Holmkvist, Johan, Jørgensen, Torben, Kristiansen, Karsten, Schmitz, Ole, Schwartz, Thue W, Zhang, Xiuqing, Li, Ruiqiang, Yang, Huanming, Wang, Jian, Hansen, Torben, Pedersen, Oluf, Nielsen, Rasmus, Wang, Jun, Li, Yingrui, Vinckenbosch, Nicolas, Tian, Geng, Huerta-Sanchez, Emilia, Jiang, Tao, Jiang, Hui, Albrechtsen, Anders, Andersen, Gitte, Cao, Hongzhi, Korneliussen, Thorfinn Sand, Grarup, Niels, Guo, Yiran, Hellman, Ines, Jin, Xin, Li, Qibin, Liu, Jiangtao, Liu, Xiao, Sparsø, Thomas, Tang, Meifang, Wu, Honglong, Wu, Renhua, Yu, Chang, Zheng, Hancheng, Astrup, Arne, Bolund, Lars, Holmkvist, Johan, Jørgensen, Torben, Kristiansen, Karsten, Schmitz, Ole, Schwartz, Thue W, Zhang, Xiuqing, Li, Ruiqiang, Yang, Huanming, Wang, Jian, Hansen, Torben, Pedersen, Oluf, Nielsen, Rasmus, and Wang, Jun

Abstract

Targeted capture combined with massively parallel exome sequencing is a promising approach to identify genetic variants implicated in human traits. We report exome sequencing of 200 individuals from Denmark with targeted capture of 18,654 coding genes and sequence coverage of each individual exome at an average depth of 12-fold. On average, about 95% of the target regions were covered by at least one read. We identified 121,870 SNPs in the sample population, including 53,081 coding SNPs (cSNPs). Using a statistical method for SNP calling and an estimation of allelic frequencies based on our population data, we derived the allele frequency spectrum of cSNPs with a minor allele frequency greater than 0.02. We identified a 1.8-fold excess of deleterious, non-syonomyous cSNPs over synonymous cSNPs in the low-frequency range (minor allele frequencies between 2% and 5%). This excess was more pronounced for X-linked SNPs, suggesting that deleterious substitutions are primarily recessive.

Published
2010

29. Archaeology Augments Tibet's Genetic History—Response

Author

Yi, Xin, primary, Liang, Yu, additional, Huerta-Sanchez, Emilia, additional, Jin, Xin, additional, Cuo, Zha Xi Ping, additional, Pool, John E., additional, Xu, Xun, additional, Jiang, Hui, additional, Vinckenbosch, Nicolas, additional, Korneliussen, Thorfinn Sand, additional, Zheng, Hancheng, additional, Liu, Tao, additional, He, Weiming, additional, Li, Kui, additional, Luo, Ruibang, additional, Nie, Xifang, additional, Wu, Honglong, additional, Zhao, Meiru, additional, Cao, Hongzhi, additional, Zou, Jing, additional, Shan, Ying, additional, Li, Shuzheng, additional, Yang, Qi, additional, Asan,  , additional, Ni, Peixiang, additional, Tian, Geng, additional, Xu, Junming, additional, Liu, Xiao, additional, Jiang, Tao, additional, Wu, Renhua, additional, Zhou, Guangyu, additional, Tang, Meifang, additional, Qin, Junjie, additional, Wang, Tong, additional, Feng, Shuijian, additional, Li, Guohong, additional, Huasang,  , additional, Luosang, Jiangbai, additional, Wang, Wei, additional, Chen, Fang, additional, Wang, Yading, additional, Zheng, Xiaoguang, additional, Li, Zhuo, additional, Bianba, Zhuoma, additional, Yang, Ge, additional, Wang, Xinping, additional, Tang, Shuhui, additional, Gao, Guoyi, additional, Chen, Yong, additional, Luo, Zhen, additional, Gusang, Lamu, additional, Cao, Zheng, additional, Zhang, Qinghui, additional, Ouyang, Weihan, additional, Ren, Xiaoli, additional, Liang, Huiqing, additional, Zheng, Huisong, additional, Huang, Yebo, additional, Li, Jingxiang, additional, Bolund, Lars, additional, Kristiansen, Karsten, additional, Li, Yingrui, additional, Zhang, Yong, additional, Zhang, Xiuqing, additional, Li, Ruiqiang, additional, Li, Songgang, additional, Yang, Huanming, additional, Nielsen, Rasmus, additional, Wang, Jun, additional, and Wang, Jian, additional

Published
2010
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30. Mutation characteristics of cancer susceptibility genes in Chinese ovarian cancer patients.

Author

Wang J, Fu K, Zhang M, Liang L, Ni M, Sun HX, Yin R, and Tang M

Abstract

Introduction: The association between mutations in susceptibility genes and the occurrence of ovarian cancer has been extensively studied. Previous research has primarily concentrated on genes involved in the homologous recombination repair pathway, particularly BRCA1 and BRCA2 . However, a wider range of genes related to the DNA damage response pathways has not been fully explored., Methods: To investigate the mutation characteristics of cancer susceptibility genes in the Chinese ovarian cancer population and the associations between gene mutations and clinical data, this study initially gathered a total of 1171 Chinese ovarian cancer samples and compiled a dataset of germline mutations in 171 genes., Results: In this study, it was determined that MC1R and PRKDC were high-frequency ovarian cancer susceptibility genes in the Chinese population, exhibiting notable distinctions from those in European and American populations; moreover high-frequency mutation genes, such as MC1R : c.359T>C and PRKDC : c.10681T>A, typically had high-frequency mutation sites. Furthermore, we identified c.8187G>T as a characteristic mutation of BRCA2 in the Chinese population, and the CHEK2 mutation was significantly associated with the early onset of ovarian cancer, while the CDH1 and FAM175A mutations were more prevalent in Northeast China. Additionally, Fanconi anemia pathway-related genes were significantly associated with ovarian carcinogenesis., Conclusion: In summary, this research provided fundamental data support for the optimization of ovarian cancer gene screening policies and the determination of treatment, and contributed to the precise intervention and management of patients., Competing Interests: Authors JW, LL, MN and MT are employees of BGI Genomics that produces the panel test used in this study. HS was employed by BGI Research. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest., (Copyright © 2024 Wang, Fu, Zhang, Liang, Ni, Sun, Yin and Tang.)

Published
2024
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31. Visible-Light-Induced Monofluoroalkenylation and gem -Difluoroallylation of Inactivated C(sp 3 )-H Bonds via 1,5-Hydrogen Atom Transfer (HAT).

Author

Bao Y, Tang M, Wang Q, Cao ZY, Wang Y, and Yuan Z

Abstract

The direct monofluoroalkenylation of C(sp 3 )-H bonds is of great importance and quite challenging. Current methods have been restricted to the monofluoroalkenylation of activated C(sp 3 )-H bonds. Here, we reported the photocatalyzed C(sp 3 )-H monofluoroalkenylation of inactivated C(sp 3 )-H bonds with gem -difluoroalkenes via 1,5-hydrogen atom transfer. This process shows good functional group tolerance, such as halides (F, Cl), nitrile, sulfone, ester, and pyridine, and good γ-selectivity. Moreover, this method succeeds in the photocatalyzed gem -difluoroallylation of inactivated C(sp 3 )-H with α-trifluoromethyl alkenes.

Published
2023
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32. Application research of chronic disease health management in an urban community based on the PRECEDE-PROCEED model in the long-term management of diabetes mellitus.

Author

Kan W, Yang R, and Tang M

Abstract

Objective: To evaluate the application of chronic disease health management in an urban community in the long-term management of diabetes mellitus (DM) based on the PRECEDE-PROCEED model., Methods: The PRECEDE-PROCEED model combines PRECEDE (predisposing, enabling and reinforcing constructs in educational diagnosis and evaluation) with PROCEED (policy, management and organization constructs in educational and environmental intervention). A total of 96 diabetic patients treated in our hospital were selected and divided into two groups by random number table, with 48 cases in each group. The routine group was given routine health management, while the PP group was given the urban community chronic disease health management based on the PRECEDE-PROCEED model in addition to the routine health management. After six months of management, the patients' effect was evaluated by comparing the blood glucose, diabetes knowledge, self-efficacy, self-management level and quality of life between the two groups., Results: The FPG, 2hPG and HbAlc levels of the PP group were lower than those of the routine group after six months of management (all P<0.05). The 6-month awareness rate, self-efficacy, self-management level and quality of life scores of the PP group were higher than those of the routine group (all P<0.05)., Conclusion: The chronic disease health management in urban communities based on the PRECEDE-PROCEED model in long-term diabetes management can effectively improve patients' diabetes knowledge, lower blood glucose levels, improve self-efficacy and self-management, and improve the quality of life., Competing Interests: None., (AJTR Copyright © 2021.)

Published
2021

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