Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/92375
標題: 使用癌症RNA-Seq資料建構全面性轉錄體表現量分析網頁伺服器
Construction of a comprehensive web server for transcript expression profiling using cancer RNA-Seq data
作者: Jian-Rong Li
李建融
關鍵字: RNA-Seq
lncRNAs
Cancer
Transcript isoform
RNA-Seq
lncRNAs
癌症
轉錄異構體
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摘要: Molecular understanding of carcinogenesis is key to know cancer mechanisms and facilitate personalized medicine. RNA Sequencing (RNA-Seq), a fast development and applications of next-generation sequencing technology in recent years, which has promoted genetic research and been used to several cancer research to provide a revolutionary tool to study alternative splicing and quantify gene/isoform expression levels. However, current some network databases provide download NGS data, therefore researchers have to download and analysis the data manually to extract the appropriate information. To fill this gap, we construct the Cancer RNA-Seq Nexus (CRN) database, the first public database providing phenotype-specific coding-transcript/lncRNA expression profiles in cancer cells. We systematically collected RNA-seq datasets from The Cancer Genome Atlas (TCGA) and NCBI Gene Expression Omnibus (GEO). It resulted in 43 cancer RNA-seq datasets including 242 subsets and 9,199 samples. Each dataset has several phenotype-specific subsets, and each subset contained a group of RNA-seq samples with specific phenotypic traits or cancer conditions, e.g. disease state, cell line, cell type, tissue, genotype. To identify phenotype-specific differentially expressed transcripts (DETs) in each dataset, we selected the subsets with at least 3 samples, and then performed t-test between two subsets without overlap samples. To obtain the expression profiles for both coding transcripts and lncRNAs, we align the RNA-seq reads to the Human transcriptome (GENCODE release 21) included 93,139 protein-coding and 26,414 lncRNA transcript sequences. Web interface: When users select a cancer name or a cancer subset, the associated subset pairs are subsequently listed in the subset-pair panel. When users select a subset pair, the web server shows the detailed description of dataset/subsets and the expression profiles of differentially expressed (DE) protein-coding transcripts and DE lncRNAs. The search panel provides the auto-complete function that quickly searches/selects the partially matched terms. Case study: to demonstrate the biological importance of CRN, we used TP63 gene as an example. The upstream promoter of the gene generates the TAp63 isoforms containing N-terminal transactivation (TA) domain, while an alternative internal promoter leads to the structure of the ΔNp63 isoforms lacking the TA domain. ΔNp63 isoforms suggested to be highly specific for squamous cells and overexpress in squamous cell carcinoma (SCC), while TAp63 expression is lost or extremely low in squamous cells and SCC. In CRN, a significant overexpression of ΔNp63 isoforms was observed in the lung SCC, while was not overexpressed and non-significant different between cancer and normal subsets in lung adenocarcinoma. CRN is freely available at http://syslab4.nchu.edu.tw/CRN.
腫瘤為細胞不正常生長發育的現象,而惡性腫瘤又被稱為癌症,迄今癌症已是在全球經濟開發國家中第一的死亡原因;而RNA-Seq是近年快速發展的次世代定序(NGS)技術,能夠偵測特定時間點樣本中RNA存在數量,促進了基因體學研究發展而被廣泛應用於癌症基因表現量研究。然而RNA-Seq的分析對多數生物或醫學實驗室是難以負擔的,而目前卻缺乏一個使用RNA-Seq數據針對癌症全面性進行phenotype-specific的isoform差異表現比較資料庫,為填補此研究空白,我們計畫建立高解析度之癌症isoform表現量分析資料庫。我們從NCBI GEO收集了1190個dataset,16343個sample;從TCGA下載了26個dataset,8968個sample的表現量與臨床資料,資料Curation後,將每dataset中所有包含的樣本歸類於不同phenotype-specific的subsets,即每subset由一群有相同之specific phenotypic特性的RNA-seq 樣本組成。接著以GENCODE v21的protein coding transcripts與lncRNAs為reference,使用Bowtie與eXpress分析isoform表現量,定義subsets pair並統計分析subsets間顯著水準,最後建構完成資料庫的web interface,結果中全部共有31種不同的癌症,包含了43個dataset,總共歸納有242個subset,被分為709個subset pair,涵蓋了9199個samples的全面protein coding transcript isoforms與lncRNAs表現量及差異顯著統計結果。Web資料庫有系統地提供使用者選擇想要了解的癌症之顯著差異表現的coding transcript isoform以及lncRNAs,並且可以調整up-regulation或是down-regulation,提供p-value的篩選,還提供查詢Gene Symbol與isoform ID以及下載結果等功能。而綜合TP63所有isoform在Head and neck squamous cell carcinomas、Lung squamous cell carcinoma、Lung adenocarcinoma的表現量結果符合前人研究趨勢,我們認為在本研究中所完成的結果是可靠的,預期本資料庫能夠提供生物醫學研究者一個重要資源,能藉此探討差異表現isoform以進行研究與預測以了解癌症調控機制或治療模式等等,將對醫學與臨床研究有重要幫助。本研究之資料庫名稱定為Cancer RNA-Seq Nexus (CRN),網址為:http://syslab4.nchu.edu.tw/CRN/。
URI: http://hdl.handle.net/11455/92375
其他識別: U0005-2407201515423700
文章公開時間: 2017-07-30
Appears in Collections:基因體暨生物資訊學研究所

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