Root Transcriptomic Analysis Revealing the Importance of Energy Metabolism to the Development of Deep Roots in Rice (Oryza sativa L.).
Root Transcriptomic Analysis Revealing the Importance of Energy Metabolism to the Development of Deep Roots in Rice (Oryza sativa L.).
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根转录组分析揭示能量代谢对水稻深根发育的重要性 (Oryza sativa L.)
DOI:
10.3389/fpls.2017.01314
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发表时间:
2017
影响因子:
5.6
通讯作者:
Zhong Y
中科院分区:
文献类型:
--
作者:
Lou Q;Chen L;Mei H;Xu K;Wei H;Feng F;Li T;Pang X;Shi C;Luo L;Zhong Y
Drought is the most serious abiotic stress limiting rice production, and deep root is the key contributor to drought avoidance. However, the genetic mechanism regulating the development of deep roots is largely unknown. In this study, the transcriptomes of 74 root samples from 37 rice varieties, representing the extreme genotypes of shallow or deep rooting, were surveyed by RNA-seq. The 13,242 differentially expressed genes (DEGs) between deep rooting and shallow rooting varieties (H vs. L) were enriched in the pathway of genetic information processing and metabolism, while the 1,052 DEGs between the deep roots and shallow roots from each of the plants (D vs. S) were significantly enriched in metabolic pathways especially energy metabolism. Ten quantitative trait transcripts (QTTs) were identified and some were involved in energy metabolism. Forty-nine candidate DEGs were confirmed by qRT-PCR and microarray. Through weighted gene co-expression network analysis (WGCNA), we found 18 hub genes. Surprisingly, all these hub genes expressed higher in deep roots than in shallow roots, furthermore half of them functioned in energy metabolism. We also estimated that the ATP production in the deep roots was faster than shallow roots. Our results provided a lot of reliable candidate genes to improve deep rooting, and firstly highlight the importance of energy metabolism to the development of deep roots.
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影响因子:
5.3
作者:
Moumeni A;Satoh K;Kondoh H;Asano T;Hosaka A;Venuprasad R;Serraj R;Kumar A;Leung H;Kikuchi S
通讯作者:
Kikuchi S
影响因子:
6.9
作者:
Edwards JM;Roberts TH;Atwell BJ
通讯作者:
Atwell BJ
影响因子:
64.8
作者:
Gan X;Stegle O;Behr J;Steffen JG;Drewe P;Hildebrand KL;Lyngsoe R;Schultheiss SJ;Osborne EJ;Sreedharan VT;Kahles A;Bohnert R;Jean G;Derwent P;Kersey P;Belfield EJ;Harberd NP;Kemen E;Toomajian C;Kover PX;Clark RM;Rätsch G;Mott R
通讯作者:
Mott R
影响因子:
5.6
作者:
Jung JK;McCouch S
通讯作者:
McCouch S
影响因子:
5.4
作者:
Ding, Xipeng;Li, Xiaokai;Xiong, Lizhong
通讯作者:
Xiong, Lizhong