作物学报 ›› 2019, Vol. 45 ›› Issue (9): 1349-1364.doi: 10.3724/SP.J.1006.2019.82061
LI Xu-Kai1,LI Ren-Jian2,ZHANG Bao-Jun2,*()
摘要:
加权共表达网络分析(Weighted Gene Co-expression Network Analysis, WGCNA)是用来描述不同样品之间基因关联模式的系统生物学方法, 可以用来鉴定高度协同变化的基因集。本研究利用正常水稻组织共47份转录组数据, 通过冷胁迫、干旱胁迫、盐胁迫不同的处理方式, 使用WGCNA方法, 根据已克隆基因的报道与以上3种胁迫相关的关键基因, 探究不同逆境下基因之间的调控关系。通过对低表达量基因的过滤, 最终利用筛选的30,339个表达的基因来构建共表达矩阵, 得到15个模块。分析发现已知的水稻3种相关基因在各个模块均有存在, 于是对预测到的靶基因进行GO富集分析。对3种胁迫下处理的转录组数据进行差异表达基因分析, 结合已报道与胁迫相关的基因, 选取各胁迫相关的2个模块进行了基因调控网络的构建。鉴于3种胁迫相关基因在green模块中大量分布, 通过对green模块下各自特有的基因和共有的基因的GO功能富集分析, 并对共有的基因构建调控网络, 挖掘到2599个与3种胁迫都相关的基因, 并预测出25个抗逆相关的关键基因, 为水稻的抗逆及综合抗逆能力等研究提供了新思路。
[1] | Larcher W . Physiological Plant Ecology. England: J R Etherington, 1996. pp 630-631. |
[2] | Krasensky J, Jonak C . Drought, salt, and temperature stress-induced metabolic rearrangements and regulatory networks. J Exp Bot, 2012, 63:1593-1608. |
[3] | Abebe T, Guenzi A C, Martin B, Cushman J C . Tolerance of mannitol-accumulating transgenic wheat to water stress and salinity. Plant Physiol, 2003,131:1748-1755. |
[4] | Richards R A . Defining selection criteria to improve yield under drought. Plant Growth Regul, 1996,20:157-166. |
[5] | Cushman J C, Bohnert H J . Genomic approaches to plant stress tolerance. Curr Opin Plant Biol, 2000,3:117-124. |
[6] | Jin J J, Zhang H, Zhang J F, Liu P P, Cao P J . Integrated transcriptomics and mtabolomics analysis to characterize cold stress responses in Nicotiana tabacum. BMC Genomics, 2017,18:496. |
[7] | Duan M, Zhang R X, Zhu F G, Zhang Z Q, Gou L M, Wang T . A lipid-anchored NAC transcription factor is translocated into the nucleus and activates glyoxalase I expression during drought stress. Plant Cell, 2017,29:1748-1772. |
[8] | Zhang B, Horvath S . A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol, 2005,4:17. |
[9] | Goldberg D H, Victor J D, Gardner E P, Gardner D . Spike train analysis toolkit: enabling wider application of information-theoretic techniques to neurophysiology. Neuroinformatics, 2009,7:165-178. |
[10] | Kroll K W, Mokaram N E, Pelletier A R, Frankhouser D E, Westphal M S, Bundschuh R, Blachly J S, Yan P . Quality control for RNA-Seq (QuaCRS): an integrated quality control pipeline. Cancer Inform, 2014,13(S3):7-14. |
[11] | Bolger A M . Trimmomatic: a flexible trimmer for illumina sequence data. Bioinformatics, 2014, 30:2114-2120. |
[12] | Kim D, Langmead B, Salzberg S L . HISAT: a fast spliced aligner with low memory requirements. Nat Methods, 2015,12:357-360. |
[13] | Liao Y, Smyth G K, Shi W . featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics, 2014,30:923-930. |
[14] | Langfelder P, Horvath S . WGCNA: an R package for weighted correlation network analysis. BMC Bioinform, 2008,9:559. |
[15] | Robinson M D, McCarthy D J, Smyth G K . edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 2010,26:139-140. |
[16] | Chen C J, Xia R, Chen H, He Y H . TBtools, a Toolkit for Biologists integrating various HTS-data handling tools with a user- friendly interface. BioRxiv, 2018 [2018-10-31]. https://doi.org/10.1101/289660. |
[17] | Su G, Morris J H, Demchak B, Bader G D . Biological network exploration with Cytoscape 3. Curr Protoc Bioinformatics, 2014, 47: 8.13.1-8.13.24. |
[18] | Jin J, Zhang H, Kong L, Gao G, Luo J . A portal for the functional and evolutionary study of plant transcription factors. Nucl Acids Res, 2014,42:D1182-1187. |
[19] | Song J, Wei X J, Shao G N, Sheng Z, Chen D, Liu C, Jiao G, Xie L, Tang S P, Hu P S . The rice nuclear gene WLP1 encoding a chloroplast ribosome L13 protein is needed for chloroplast development in rice grown under low temperature conditions. Plant Mol Biol, 2014,84:301-314. |
[20] | Fang J, Chai C L, Qian Q, Li C, Tang J, Sun L, Huang Z, Guo X, Sun C, Liu M, Zhang Y, Lu Q, Wang Y, Lu C, Han B, Chen F, Cheng Z K, Chu C C . Mutations of genes in synthesis of the carotenoid precursors of ABA lead to pre-harvest sprouting and photo-oxidation in rice. Plant J, 2008,54:177-189. |
[21] | Qin Y H, Shen X, Wang N L, Ding X P . Characterization of a novel cyclase-like gene family involved in controlling stress tolerance in rice. J Plant Physiol, 2015,181:30-41. |
[22] | Lu G W, Wu F Q, Wu W, Wang H J, Zheng X M, Zhang Y, Chen X, Zhou K, Jin M, Cheng Z, Li X Y, Jiang L, Wang H Y, Wan J M . Rice LTG1 is involved in adaptive growth and fitness under low ambient temperature. Plant J, 2014,78:468-480. |
[23] | Chen J Q, Meng X P, Zhang Y, Xia M, Wang X P . Over- expression of OsDREB genes lead to enhanced drought tolerance in rice. Biotechnol Lett, 2008,30:2191-2198. |
[24] | Singh A, Sahi C, Grover A . Chymotrypsin protease inhibitor gene family in rice: genomic organization and evidence for the presence of a bidirectional promoter shared between two chymotrypsin protease inhibitor genes. Gene, 2009,428:9-19. |
[25] | Zhang X, Zhang B, Li M J, Cui Y C, Wang M L, Xia X J . OsMSR15 encoding a rice C2H2-type zinc finger protein confers enhanced drought tolerance in transgenic Arabidopsis. J Plant Biol, 2016,59:271-281. |
[26] | Huang J, Wang M M, Bao Y M, Sun S J, Pan L J, Zhang H S . SRWD: a novel WD40 protein subfamily regulated by salt stress in rice(Oryza sativa L.). Gene, 2008,424:71-79. |
[27] | Liu S P, Zheng L Q, Xue Y H, Zhang Q, Wang L, Shou H X . Overexpression of OsVP1 and OsNHX1 increases tolerance to drought and salinity in rice. J Plant Biol, 2010,53:444-452. |
[28] | Zhou L G, Liu Z C, Liu Y H, Kong D Y, Li T F, Chen L, Luo L J . A novel gene OsAHL1 improves both drought avoidance and drought tolerance in rice. Sci Rep, 2016,6:30264. |
[29] | Xiong L Z, Yang Y N . Disease resistance and abiotic stress tolerance in rice areinversely modulated by an abscisicacid- inducible mitogen-activated protein kinase. Plant Cell, 2003,15:745-759. |
[30] | Ohnishi T, Sugahara S, Yamada T, Kikuchi K, Yoshiba Y, Hirano H Y, Tsutsumi N . OsNAC6, a member of the NAC gene family, is induced by various stresses in rice. Genes Genet Syst, 2005,80:135-139. |
[31] | Du H, Wu N, Chang Y, Li X H, Xiao J H, Xiong L Z . Carotenoid deficiency impairs ABA and IAA biosynthesis and differentially affects drought and cold tolerance in rice. Plant Mol Biol, 2013,83:475-488. |
[32] | Liu K M, Wang L, Xu Y Y, Chen N, Ma Q B, Li F, Chong K . Overexpression of OsCOIN, a putative cold inducible zinc finger protein, increased tolerance to chilling, salt and drought, and enhanced proline level in rice. Planta, 2007,226:1007-1016. |
[33] | Zhang X, Zhang B, Li M J, Yin X M, Huang L F, Cui Y C, Wang M L, Xia X J . OsMSR15 encoding a rice C2H2-type zinc finger protein confers enhanced drought tolerance in transgenic Arabidopsis. J Plant Biol, 2016,59:271-281. |
[34] | Huang J, Wang M M, Bao Y M, Sun S J, Pan L J, Zhang H S . A novel WD40 protein subfamily regulated by salt stress in rice(Oryza sativa L.). Gene, 2008,424:71-79. |
[35] | Hackenberg T, Juul T, Auzina A, Gwizdz S, Malolepszy A, Van Der Kelen K, Dam S, Bressendorff S, Lorentzen A, Roepstorff P, Lehmann Nielsen K, Jørgensen J E, Hofius D, Van Breusegem F, Petersen M, Andersen S U . Catalase and NO CATALASE ACTIVITY1 promote autophagy-dependent cell death in Arabidopsis. Plant Cell, 2013,25:4616-4626. |
[36] | 刘晓东, 王若仲, 焦彬彬, 代培红, 李月 . 拟南芥IAA酰胺合成酶GH3-6负调控干旱和盐胁迫的反应. 植物学报, 2016,51:586-593. |
Liu X D, Wang R Z, Jiao B B, Dai P H, Li Y . Indole acetic acid-amido aynthetase GH3-6 negatively regulates response to drought and salt in arabidopsis. Chin Bull Bot, 2016,51:586-593 (in Chinese with English abstract). | |
[37] | Shafi A, Dogra V, Gill T, Ahuja P S, Sreenivasulu Y . Simultaneous over-expression of PaSOD and RaAPX in transgenic Arabidopsis thaliana confers cold stress tolerance through increase in vascular lignifications. PLoS One, 2014,9:e110302. |
[38] | Wrzaczek M, Brosché M, Salojärvi J, Kangasjärvi S, Idänheimo N, Mersmann S, Robatzek S, Karpiński S, Karpińska B, Kangasjärvi J . Transcriptional regulation of the CRK/DUF26 group of receptor-like protein kinases by ozone and plant hormones in Arabidopsis. BMC Plant Biol, 2010,10:95. |
[1] | 田甜, 陈丽娟, 何华勤. 基于Meta-QTL和RNA-seq的整合分析挖掘水稻抗稻瘟病候选基因[J]. 作物学报, 2022, 48(6): 1372-1388. |
[2] | 郑崇珂, 周冠华, 牛淑琳, 和亚男, 孙伟, 谢先芝. 水稻早衰突变体esl-H5的表型鉴定与基因定位[J]. 作物学报, 2022, 48(6): 1389-1400. |
[3] | 周文期, 强晓霞, 王森, 江静雯, 卫万荣. 水稻OsLPL2/PIR基因抗旱耐盐机制研究[J]. 作物学报, 2022, 48(6): 1401-1415. |
[4] | 郑小龙, 周菁清, 白杨, 邵雅芳, 章林平, 胡培松, 魏祥进. 粳稻不同穗部籽粒的淀粉与垩白品质差异及分子机制[J]. 作物学报, 2022, 48(6): 1425-1436. |
[5] | 颜佳倩, 顾逸彪, 薛张逸, 周天阳, 葛芊芊, 张耗, 刘立军, 王志琴, 顾骏飞, 杨建昌, 周振玲, 徐大勇. 耐盐性不同水稻品种对盐胁迫的响应差异及其机制[J]. 作物学报, 2022, 48(6): 1463-1475. |
[6] | 杨建昌, 李超卿, 江贻. 稻米氨基酸含量和组分及其调控[J]. 作物学报, 2022, 48(5): 1037-1050. |
[7] | 杨德卫, 王勋, 郑星星, 项信权, 崔海涛, 李生平, 唐定中. OsSAMS1在水稻稻瘟病抗性中的功能研究[J]. 作物学报, 2022, 48(5): 1119-1128. |
[8] | 朱峥, 王田幸子, 陈悦, 刘玉晴, 燕高伟, 徐珊, 马金姣, 窦世娟, 李莉云, 刘国振. 水稻转录因子WRKY68在Xa21介导的抗白叶枯病反应中发挥正调控作用[J]. 作物学报, 2022, 48(5): 1129-1140. |
[9] | 王小雷, 李炜星, 欧阳林娟, 徐杰, 陈小荣, 边建民, 胡丽芳, 彭小松, 贺晓鹏, 傅军如, 周大虎, 贺浩华, 孙晓棠, 朱昌兰. 基于染色体片段置换系群体检测水稻株型性状QTL[J]. 作物学报, 2022, 48(5): 1141-1151. |
[10] | 王霞, 尹晓雨, 于晓明, 刘晓丹. 干旱锻炼对B73自交后代当代干旱胁迫记忆基因表达及其启动子区DNA甲基化的影响[J]. 作物学报, 2022, 48(5): 1191-1198. |
[11] | 雷新慧, 万晨茜, 陶金才, 冷佳俊, 吴怡欣, 王家乐, 王鹏科, 杨清华, 冯佰利, 高金锋. 褪黑素与2,4-表油菜素内酯浸种对盐胁迫下荞麦发芽与幼苗生长的促进效应[J]. 作物学报, 2022, 48(5): 1210-1221. |
[12] | 王泽, 周钦阳, 刘聪, 穆悦, 郭威, 丁艳锋, 二宫正士. 基于无人机和地面图像的田间水稻冠层参数估测与评价[J]. 作物学报, 2022, 48(5): 1248-1261. |
[13] | 陈悦, 孙明哲, 贾博为, 冷月, 孙晓丽. 水稻AP2/ERF转录因子参与逆境胁迫应答的分子机制研究进展[J]. 作物学报, 2022, 48(4): 781-790. |
[14] | 王吕, 崔月贞, 吴玉红, 郝兴顺, 张春辉, 王俊义, 刘怡欣, 李小刚, 秦宇航. 绿肥稻秆协同还田下氮肥减量的增产和培肥短期效应[J]. 作物学报, 2022, 48(4): 952-961. |
[15] | 巫燕飞, 胡琴, 周棋, 杜雪竹, 盛锋. 水稻延伸因子复合体家族基因鉴定及非生物胁迫诱导表达模式分析[J]. 作物学报, 2022, 48(3): 644-655. |
|