以加權性基因共表現網絡分析確認與水稻低溫、高鹽逆境及植物荷爾蒙反應相關之基因模組

Identification of Gene Modules Associated with Chilling, High Salinity Stresses and Phytohormones Response in Rice by Weighted Gene Co-expression Network Analysis (WGCNA)

陳鈺元(Yu-Yuan Chen)

指導教授 ： 張孟基

共同指導教授 ： 劉力瑜

國立臺灣大學/生物資源暨農學院/農藝學研究所/碩士(2015年)

https://doi.org/10.6342/NTU.2015.11271

摘要

水稻為世界主要糧食作物之一，供養全球逾半之人口數。近年來氣候變遷影響水稻之產量與質量，因此提升水稻非生物性逆境之耐受性相當重要。為了解非生性逆境下水稻的調控機制與植物荷爾蒙所扮演的角色，本研究利用實驗室現有之低溫與鹽處理水稻的微陣列基因表現數據，並由NCBI之GEO(Gene Expression Omnibus)資料庫下載不同植物荷爾蒙處理水稻的基因表現資料，利用加權性基因共表現網絡分析(Weighted gene co-expression network analysis)此統計套件，依每個基因的表現模式，建構基因群模組(Module construction)並且找出埠基因(Hub gene)。以藉此系統性分析之生物資訊的方法，瞭解可能影響水稻非生物性逆境耐受性以及植物荷爾蒙反應之基因群組與可能生物調控路徑及重要基因。本研究由荷爾蒙資料組與非生物性逆境資料組個別篩選出5743與3130個差異表現基因(Differentially expressed genes, DEGs)，並分出七個與五個模組，依序為模組1至7與模組I至V，其中在非生物性逆境資料組中，找到含有243個基因之模組Ｖ在對低溫鈍感(TNG67)與敏感(TCN1)之兩水稻品種皆受到低溫誘導，且TCN1之基因群受到低溫而擾動的幅度較高。模組Ｖ經基因富集分析顯示與基因表達與RNA生合成作用相關。含有725個基因之模組II 與1094個基因之模組IV與受到鹽處理誘導，模組II之基因分群為轉錄調控與蛋白質胺基酸之磷酸化作用。模組IV之基因參與RNA之生合成與代謝作用。對照至荷爾蒙之模組分群，與模組5具有最多之相同基因富集分群，而模組5為在生長素處理下之擾動幅度最高。依富集分群篩選出OsARF14, OsHOX13 和 OsWOX13三個基因同時受到生長素與高鹽誘導，且與皆與基因表達相關，進而推測此三個基因可能調控水稻受到高鹽下之下游基因表現，且生長素可能是其中一個負責之植物荷爾蒙，與鹽害之耐受機制有關。

關鍵字

非生物性逆境 ； 低溫逆境 ； 植物荷爾蒙 ； 鹽害逆境 ； 加權性基因共表現網絡分析

並列摘要

Rice is one of the major cereal crop which provides the main calories for more than 50% of the world population. Since the global weather change, abiotic stresses severely affect and reduce the productivity and yield of rice. Thus, to understand the mechanism of rice abiotic stress tolerance is extremely important. Meanwhile, various phtohormones participate in the regulation of rice growth and development. In particular, phytohormones can cross talk with different abiotic stresses and affect the final survival rate of rice. Hence, to further dissect the abiotic stress tolerance mechanism in rice must accompany with the knowledge regards to how phytohormones regulate rice growth and development. To reach this purpose, we took the available microarray data sets of cold- and salinity-treatment and downloaded the microarray data sets of various phtohormones treatments of rice seedlings from NCE (GEO), then using Weighted Gene Co-expression Network Analysis (WGCNA) algorithm to identify co-expressed genes that are differentially expressed in response to low temperature, salt stresses and multiple phytohormones. We expected to use this bioinformatics approach with system biology to characterize the gene modules, possible biological processes and candidate genes that may involve in the abiotic stress tolerance of rice. From the genes expression data sets, first we identified 5743 and 3130 rice genes (differential expressed genes; DEGs) under cold/ salt treatments and phytohormone. After WGCNA analysis, 5 ( I to V) and 7 (1 to 7) modules were identified from cold/ or salt treatments and phytohormone data sets, respectively. We observed that module V consisting of 243 genes was significantly associated with cold response in both cold-tolerant (TNG 67) and cold-sensitive (TCN1) rice varieties. This module is enriched for genes involved in gene expression and RNA biosynthetic process. Two gene modules, II and IV, consisting of 725 and 1094 genes were significantly associated with salt response. Module II is enriched with genes involved in regulation of transcription and protein amino acid phosphorylation. Module IV is enriched with genes involved in RNA metabolic and biosynthetic process. In general, salt-responsive gene modules are shown with enrichments for genes in gene expression, gene expression, RNA metabolic process and cellular component biogenesis. Cold-responsive gene modules are shown with enrichments for genes in regulation of transcription, protein amino acid phosphorylation, regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolic process and regulation of nitrogen compound metabolic process. Phytohormone-responsive gene modules are shown with enrichments for genes in common functional categories, stress response changes, tissue-specific expression and transcription factor binding sites. Besides, module II and IV have a close or similar relationship with phytohormone module 5 which are highly associated with auxin treatment. These three modules share similar GO terms, including DNA-dependent regulation of transcription, regulation of RNA metabolic and biosynthetic process and gene expression. The above results suggested that genes in these 3 modules may play a vital role in phytohormone-dependent salt tolerant pathway, especially for auxin. Finally, we also found three genes that involved in RNA metabolic process, OsARF14, OsHOX13 and OsWOX13. The relationship between these genes may provide a key to understand the mechanism of salt tolerance in rice.

並列關鍵字

Abiotic stress ； Cold ； Phytohormone ； Salinity ； WGCNA

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