Extended mining of the oil biosynthesis pathway in biofuel plant Jatropha curcas by combined analysis of transcriptome and gene interactome data

doi:10.1186/s12859-021-04319-w

CORC > 西双版纳热带植物园 > 中国科学院西双版纳热带植物园 > 2012年后新成立研究组

	Extended mining of the oil biosynthesis pathway in biofuel plant Jatropha curcas by combined analysis of transcriptome and gene interactome data
	Zhang, Xuan 1; Li, Jing ; Pan, Bang-Zhen ; Chen, Wen ; Chen, Maosheng ; Tang, Mingyong ; Xu, Zeng-Fu ; Liu, Changning 3,4
刊名	BMC BIOINFORMATICS
	2021
卷号	22 期号:SUPPL 6 页码:-
关键词	Extended mining Oil biosynthesis Jatropha curcas Transcriptome Gene interactome
ISSN号	1471-2105
DOI	10.1186/s12859-021-04319-w
英文摘要	Background Jatropha curcas L. is an important non-edible oilseed crop with a promising future in biodiesel production. However, little is known about the molecular biology of oil biosynthesis in this plant when compared with other established oilseed crops, resulting in the absence of agronomically improved varieties of Jatropha. To extensively discover the potentially novel genes and pathways associated with the oil biosynthesis in J. curcas, new strategy other than homology alignment is on the demand. Results In this study, we proposed a multi-step computational framework that integrates transcriptome and gene interactome data to predict functional pathways in non-model organisms in an extended process, and applied it to study oil biosynthesis pathway in J. curcas. Using homologous mapping against Arabidopsis and transcriptome profile analysis, we first constructed protein-protein interaction (PPI) and co-expression networks in J. curcas. Then, using the homologs of Arabidopsis oil-biosynthesis-related genes as seeds, we respectively applied two algorithm models, random walk with restart (RWR) in PPI network and negative binomial distribution (NBD) in co-expression network, to further extend oil-biosynthesis-related pathways and genes in J. curcas. At last, using k-nearest neighbors (KNN) algorithm, the predicted genes were further classified into different sub-pathways according to their possible functional roles. Conclusions Our method exhibited a highly efficient way of mining the extended oil biosynthesis pathway of J. curcas. Overall, 27 novel oil-biosynthesis-related gene candidates were predicted and further assigned to 5 sub-pathways. These findings can help better understanding of the oil biosynthesis pathway of J. curcas, as well as paving the way for the following J. curcas breeding application.
学科主题	Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
语种	英语
WOS记录号	WOS:000686671200001
内容类型	期刊论文
源URL	[http://ir.xtbg.org.cn/handle/353005/12309]
专题	西双版纳热带植物园_2012年后新成立研究组
作者单位	1.Chinese Acad Sci, Innovat Acad Seed Design, Kunming 650223, Yunnan, Peoples R China 2.Univ Chinese Acad Sci, Coll Life Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Xishuangbanna Trop Bot Garden, CAS Key Lab Trop Plant Resources & Sustainable Us, Kunming 650223, Yunnan, Peoples R China 4.Chinese Acad Sci, Core Bot Gardens, Ctr Econ Bot, Menglun 666303, Yunnan, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Xuan,Li, Jing,Pan, Bang-Zhen,et al. Extended mining of the oil biosynthesis pathway in biofuel plant Jatropha curcas by combined analysis of transcriptome and gene interactome data[J]. BMC BIOINFORMATICS,2021,22(SUPPL 6):-.
APA	Zhang, Xuan.,Li, Jing.,Pan, Bang-Zhen.,Chen, Wen.,Chen, Maosheng.,...&Liu, Changning.(2021).Extended mining of the oil biosynthesis pathway in biofuel plant Jatropha curcas by combined analysis of transcriptome and gene interactome data.BMC BIOINFORMATICS,22(SUPPL 6),-.
MLA	Zhang, Xuan,et al."Extended mining of the oil biosynthesis pathway in biofuel plant Jatropha curcas by combined analysis of transcriptome and gene interactome data".BMC BIOINFORMATICS 22.SUPPL 6(2021):-.