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摘要：【目的】本研究通过对水稻响应赤霉素的小RNA进行鉴定与分析，构建了由小RNA、靶基因、生物学功能组成的基因表达调控GRN网络图，为阐明小RNA在水稻赤霉素信号通路中的调控作用奠定了基础。【方法】通过对赤霉素处理水稻幼苗的小RNA测序数据分析，鉴定水稻中与赤霉素相关的小RNA，并利用miRDeep-P软件包预测新microRNA，通过借助降解组测序数据对预测结果进行验证，最后进行GO和通路分析并构建出GRN网络图。【结果】鉴定得到483个已知miRNA(miRBase21.0)和305个新miRNA；通过差异表达分析、靶基因预测及降解组验证发现空白对照与赤霉素处理之间16个差异表达microRNA和6条差异表达小RNA及对应的51个靶基因，空白对照与赤霉素抑制剂多效唑处理之间23个差异表达microRNA和8条差异表达小RNA及对应的71个靶基因；靶基因分别富集到8个和30个显著的GO term(agriGO, FDR<0.05),其中4个已经注释为与赤霉素相关；构建了两幅分别含有36个节点、80条边和105个节点、730条边的网络图。28735
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毕业论文关键词：水稻；赤霉素；小RNA；调控网络
The identification and analysis of the small RNA responded to gibberellins in rice
Abstract：[Object] Our research take gibberellins as the entry point to identify and analyze the GAs responsive small RNAs in rice. The gene regulation networks consisting of GAs- or paclobatrazol- (PAC) responsive small RNAs, target genes and biological functions were constructed. This result will lay a foundation for clarifying the function that the small RNA regulated in gibberellins’ signal pathway. [Methods] To determine the regulation of gibberellins, we screened the GAs-responsive small RNAs by small RNA and degradome sequencing. The whole analysis process includes the identification of the small RNA, the prediction of novel microRNA using miRDeep-P package, the verification of the predicted result by degradome sequencing, the analysis of gene ontology and pathway enrichment with the help of agriGO, and finally the construction of the GRN(Gene Regulatory Network) network with Cytoscape.[Results]We identified 483 known miRNAs(miRBase21.0) and 305 novel miRNAs. After finding the differentially expressed small RNAs, target genes prediction and verification with degradome data, we found 16 differentially expressed microRNA and 6 sRNA (P<0.05,Time>2), as well as 51 corresponding target genes between CK and GA3 treatment, we also found 23 differentially expressed microRNA and 8 sRNA (P<0.05, Time>2), as well as 71 corresponding target genes between CK and PAC treatment. These two part of targets were then processed by agriGO GO annotation analysis, and we respectively obtain 8 and 30 significant differential GO term (false discovery rate q<0.05), in which 4 are annotated relating to GAs. Finally, we constructed two small RNA regulatory network respectively containing 36 nodes, 80 edges and 105 nodes, 730 edges.
Key words: oryza sative；gibberellin；small RNA；regulatory network
目 录
摘要3
关键词3
Abstract3
Key words3
引言3
1材料与方法4
1.1材料4
1.2方法4
1.2.1赤霉素处理4
1.2.2总RNA的提取与质量检测5
1.2.3 small RNA提取与胶回收5
1.2.4 small RNA的cDNA文库构建与测序6
1.2.5测序数据处理与生物信息学分析6
1.2.6预测新的miRNA7
1.2.7降解组测序验证法7
1.2.8靶基因相关GO term和通路分析8
1.2.9 small RNA与靶基因的互作网络构建9
2结果与分析9
2.1 small RNA-seq 原始数据质控10
2.2全基因组比对结果10
2.3新miRNA预测结果11
2.4 miRNA差异表达分析11
2.5靶基因预测结果12
2.6其他sRNA响应赤霉素的信息挖掘12
2.7降解组数据验证分析13
2.8生物学功能预测13
2.9 sRNA-Gene-Function互作网络图15