A predicted protein functional network aids in novel gene mining for characteristic secondary metabolites in tea plant (Camellia sinensis)

Simple item page
dc.contributor.authorZhang, Shihuaen_US
dc.contributor.authorMa, Yongen_US
dc.contributor.authorZhang, Ruien_US
dc.contributor.authorHe, Xiaolongen_US
dc.contributor.authorChen, Yingen_US
dc.contributor.authorDu, Jingkeen_US
dc.contributor.authorHo, Chi-Tangen_US
dc.contributor.authorZhang, Youhuaen_US
dc.contributor.authorHan, Guominen_US
dc.contributor.authorHu, Xiaoyien_US
dc.date.accessioned2020-11-18T10:14:15Z
dc.date.available2020-11-18T10:14:15Z
dc.date.issued2020-10
dc.description.abstractModeling a protein functional network in concerned species is an efficient approach for identifying novel genesin certain biological pathways. Tea plant (Camellia sinensis) is an important commercial crop abundant innumerous characteristic secondary metabolites (e.g., polyphenols, alkaloids, alkaloids) that confer tea qualityand health benefits. Decoding novel genes responsible for tea characteristic components is an important basisfor applied genetic improvement and metabolic engineering. Herein, a high-quality protein functional networkfor tea plant (TeaPoN) was predicted using cross-species protein functional associations transferring andintegration combined with a stringent biological network criterion control. TeaPoN contained 31,273 nonredundant functional interactions among 6,634 tea proteins (or genes), with general network topologicalproperties such as scale-free and small-world. We revealed the modular organization of genes related to themajor three tea characteristic components (theanine, caffeine, catechin) in TeaPoN, which served as strongevidence for the utility of TeaPoN in novel gene mining. Importantly, several case studies regarding geneidentification for tea characteristic components were presented. To aid in the use of TeaPoN, a concise webinterface for data deposit and novel gene screening was developed (https://teapon.wchoda.com). We believe thatTeaPoN will serve as a useful platform for functional genomics studies associated with characteristic secondarymetabolites in tea plant.en_US
dc.identifier.affiliationsCollege of Life Science and Health, Wuhan University of Science and Technology, Wuhan, Chinaen_US
dc.identifier.affiliationsCollege of Information and Computer Science, Anhui Agricultural University, Hefei, Chinaen_US
dc.identifier.affiliationsCollege of Information and Computer Science, Anhui Agricultural University, Hefei, Chinaen_US
dc.identifier.affiliationsState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, Chinaen_US
dc.identifier.affiliationsState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei Chinaen_US
dc.identifier.affiliationsState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei Chinaen_US
dc.identifier.affiliationsDepartment of Food Science, Rutgers University, New Brunswick, NJ 08901, USAen_US
dc.identifier.affiliationsCollege of Information and Computer Science, Anhui Agricultural University, Hefei, Chinaen_US
dc.identifier.affiliationsCollege of Life Science, Anhui Agricultural University, Hefei, Chinaen_US
dc.identifier.affiliationsSchool of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei, China, guominhan@ahau.edu.cnen_US
dc.identifier.citationZhang Shihua, Ma Yong, Zhang Rui, He Xiaolong, Chen Ying, Du Jingke, Ho Chi-Tang, Zhang Youhua, Han Guomin, Hu Xiaoyi. A predicted protein functional network aids in novel gene mining for characteristic secondary metabolites in tea plant (Camellia sinensis). Journal of Biosciences. 2020 Oct; : 1-10en_US
dc.identifier.issn0250-5991
dc.identifier.issn0973-7138
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/214225
dc.languageenen_US
dc.publisherIndian Academy of Sciencesen_US
dc.relation.volume45en_US
dc.source.urihttps://dx.doi.org//10.1007/s12038-020-00101-xen_US
dc.subjectCharacteristic secondary metabolitesen_US
dc.subjectnovel gene miningen_US
dc.subjectprotein functional networken_US
dc.subjecttea planten_US
dc.titleA predicted protein functional network aids in novel gene mining for characteristic secondary metabolites in tea plant (Camellia sinensis)en_US
dc.typeJournal Articleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
jbsc2020v45pf1.pdf
Size:
806.77 KB
Format:
Adobe Portable Document Format
Download
Collections
Journal of Biosciences