Extended mining of the oil biosynthesis pathway in biofuel plant Jatropha curcas by combined analysis of transcriptome and gene interactome data
文献类型：期刊论文
| 作者 | Zhang, Xuan2 ; Li, Jing; Pan, Bang-Zhen; Chen, Wen; Chen, Maosheng; Tang, Mingyong; Xu, Zeng-Fu; Liu, Changning3,4
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| 刊名 | BMC BIOINFORMATICS
 |
| 出版日期 | 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 |
| 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.Univ Chinese Acad Sci, Coll Life Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Innovat Acad Seed Design, Kunming 650223, Yunnan, Peoples R China 3.Chinese Acad Sci, Core Bot Gardens, Ctr Econ Bot, Menglun 666303, Yunnan, Peoples R China 4.Chinese Acad Sci, Xishuangbanna Trop Bot Garden, CAS Key Lab Trop Plant Resources & Sustainable Us, Kunming 650223, 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):-. |
入库方式： OAI收割
来源：西双版纳热带植物园
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