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11 results on '"Duan, Guangya"'

1. BioKA: a curated and integrated biomarker knowledgebase for animals

Author

Wang, Yibo, primary, Lin, Yihao, additional, Wu, Sicheng, additional, Sun, Jiani, additional, Meng, Yuyan, additional, Jin, Enhui, additional, Kong, Demian, additional, Duan, Guangya, additional, Bei, Shaoqi, additional, Fan, Zhuojing, additional, Wu, Gangao, additional, Hao, Lili, additional, Song, Shuhui, additional, Tang, Bixia, additional, and Zhao, Wenming, additional

Published
2023
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2. TCOD: an integrated resource for tropical crops

Author

Kang, Hailong, primary, Huang, Tianhao, additional, Duan, Guangya, additional, Meng, Yuyan, additional, Chen, Xiaoning, additional, He, Shuang, additional, Xia, Zhiqiang, additional, Zhou, Xincheng, additional, Chao, Jinquan, additional, Tang, Bixia, additional, Wang, Zhonghuang, additional, Zhu, Junwei, additional, Du, Zhenglin, additional, Sun, Yanlin, additional, Zhang, Sisi, additional, Xiao, Jingfa, additional, Tian, Weimin, additional, Wang, Wenquan, additional, and Zhao, Wenming, additional

Published
2023
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4. TCOD: an integrated resource for tropical crops.

Author

Kang, Hailong, Huang, Tianhao, Duan, Guangya, Meng, Yuyan, Chen, Xiaoning, He, Shuang, Xia, Zhiqiang, Zhou, Xincheng, Chao, Jinquan, Tang, Bixia, Wang, Zhonghuang, Zhu, Junwei, Du, Zhenglin, Sun, Yanlin, Zhang, Sisi, Xiao, Jingfa, Tian, Weimin, Wang, Wenquan, and Zhao, Wenming

Published
2024
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5. HGD: an integrated homologous gene database across multiple species

Author

Duan, Guangya, primary, Wu, Gangao, additional, Chen, Xiaoning, additional, Tian, Dongmei, additional, Li, Zhaohua, additional, Sun, Yanling, additional, Du, Zhenglin, additional, Hao, Lili, additional, Song, Shuhui, additional, Gao, Yuan, additional, Xiao, Jingfa, additional, Zhang, Zhang, additional, Bao, Yiming, additional, Tang, Bixia, additional, and Zhao, Wenming, additional

Published
2022
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6. Global cold-chain related SARS-CoV-2 transmission identified by pandemic-scale phylogenomics

Author

Yu, Dalang, Zhu, Junwei, Yang, Jianing, Pan, Yi-Hsuan, Mu, Hailong, Cao, Ruifang, Tang, Bixia, Duan, Guangya, Hao, Zi-Qian, Dai, Long, Zhao, Guo-Ping, Zhang, Ya-Ping, Zhao, Wenming, Zhang, Guo-Qing, and Li, Haipeng

Subjects
SARS-CoV-2, Cold-chain related transmission, fungi, COVID-19, Delta VOC, Wuhan outbreak, D614G
Abstract

The manuscript has been published on a peer-reviewed journal. It can be accessed freely via http://dx.doi.org/10.24272/j.issn.2095-8137.2022.238 The COVID-19 pandemic caused by SARS-CoV-2 poses a tremendous threat to human society. SARS-CoV-2 is airborne and mainly transmitted through social contact; however, it is highly debated whether cold-chain related transmission has occurred. Here, we present a new method and distinguish two transmission routes by detecting a lineage-specific reduction of SARS-CoV-2 evolutionary rate. After analyzing 1,610,125 SARS-CoV-2 genomic sequences, we found that two outbreaks in Xinfadi-Beijing and Auckland may be cold-chain related and respectively caused by two mutation-dormant variants. A Dalian outbreak in July 2020 and a Yingkou outbreak ten months later were epidemiologically connected and derived from a cold-chain related variant. Mutation-dormant variants were detected during the spread of spike D614G variant and the Delta Variant of Concern. Moreover, the earliest SARS-CoV-2 variant (i.e., the most recent common ancestor of SARS-CoV-2) was found to be a mutation-dormant variant. Its repeated spillover events were observed during the last two years, indicating that the COVID-19 outbreak in Wuhan could be associated with spillover events from cold-chains. In all the observed cases, the virus re-started mutating after the spillover events from cold-chains. A systematic identification of spillover events revealed that the frequency of cold-chain related transmission is in the order of magnitude of 0.1-10%. Our results indicate that that cold-chain related transmission should be rare but may have happened globally., DATA AND SOFTWARE AVAILABILITY The data was downloaded from https://ngdc.cncb.ac.cn/ncov/apis/, and the Coronavirus GenBrowser (CGB) is freely available from http://www.egps-software.net/egpscloud/eGPS_Desktop.html, as a plug-in of the eGPS Desktop. The algorithm developed in this study was integrated into the CGB, to search for mutation-dormant variants. It is available in the version 1.13, or the latest version of the eGPS Desktop.

Published
2022
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8. Global Cold-Chain Related SARS-CoV-2 Transmission

Author

Yu, Dalang, primary, Zhu, Junwei, additional, Yang, Jianing, additional, Pan, Yi-Hsuan, additional, Mu, Hailong, additional, Cao, Ruifang, additional, Tang, Bixia, additional, Duan, Guangya, additional, Hao, Zi-Qian, additional, Dai, Long, additional, Zhao, Guo-Ping, additional, Zhang, Ya-Ping, additional, Zhao, Wenming, additional, Zhang, Guoqing, additional, and Li, Haipeng, additional

Published
2021
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9. The Global Landscape of SARS-CoV-2 Genomes, Variants, and Haplotypes in 2019nCoVR

Author

Song, Shuhui, primary, Ma, Lina, additional, Zou, Dong, additional, Tian, Dongmei, additional, Li, Cuiping, additional, Zhu, Junwei, additional, Chen, Meili, additional, Wang, Anke, additional, Ma, Yingke, additional, Li, Mengwei, additional, Teng, Xufei, additional, Cui, Ying, additional, Duan, Guangya, additional, Zhang, Mochen, additional, Jin, Tong, additional, Shi, Chengmin, additional, Du, Zhenglin, additional, Zhang, Yadong, additional, Liu, Chuandong, additional, Li, Rujiao, additional, Zeng, Jingyao, additional, Hao, Lili, additional, Jiang, Shuai, additional, Chen, Hua, additional, Han, Dali, additional, Xiao, Jingfa, additional, Zhang, Zhang, additional, Zhao, Wenming, additional, Xue, Yongbiao, additional, and Bao, Yiming, additional

Published
2020
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10. Coronavirus GenBrowser for monitoring the transmission and evolution of SARS-CoV-2.

Author

Yu, Dalang, Yang, Xiao, Tang, Bixia, Pan, Yi-Hsuan, Yang, Jianing, Duan, Guangya, Zhu, Junwei, Hao, Zi-Qian, Mu, Hailong, Dai, Long, Hu, Wangjie, Zhang, Mochen, Cui, Ying, Jin, Tong, Li, Cui-Ping, Ma, Lina, team, Language translation, Su, Xiao, Zhang, Guoqing, and Zhao, Wenming

Subjects
SARS-CoV-2, COVID-19
Abstract

Genomic epidemiology is important to study the COVID-19 pandemic, and more than two million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequences were deposited into public databases. However, the exponential increase of sequences invokes unprecedented bioinformatic challenges. Here, we present the Coronavirus GenBrowser (CGB) based on a highly efficient analysis framework and a node-picking rendering strategy. In total, 1,002,739 high-quality genomic sequences with the transmission-related metadata were analyzed and visualized. The size of the core data file is only 12.20 MB, highly efficient for clean data sharing. Quick visualization modules and rich interactive operations are provided to explore the annotated SARS-CoV-2 evolutionary tree. CGB binary nomenclature is proposed to name each internal lineage. The pre-analyzed data can be filtered out according to the user-defined criteria to explore the transmission of SARS-CoV-2. Different evolutionary analyses can also be easily performed, such as the detection of accelerated evolution and ongoing positive selection. Moreover, the 75 genomic spots conserved in SARS-CoV-2 but non-conserved in other coronaviruses were identified, which may indicate the functional elements specifically important for SARS-CoV-2. The CGB was written in Java and JavaScript. It not only enables users who have no programming skills to analyze millions of genomic sequences, but also offers a panoramic vision of the transmission and evolution of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Published
2022
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