MicroRNAs (miRNAs) are a class of extensively studied small RNA population that plays a critical role in eukaryotic gene regulation. In this study, an automated multiple-task web service DSAP was designed to provide a total solution to analyzing deep-sequencing small RNA datasets generated by next-generation sequencing technology. The input data will go through four analysis steps in DSAP: (i) cleanup: removal of adaptors and poly-A/T/C/G/N nucleotides; (ii) clustering: grouping of cleaned sequence tags into unique sequence clusters; (iii) non-coding RNA (ncRNA) matching: sequence homology mapping against a transcribed sequence library from the ncRNA database Rfam (http://rfam.sanger.ac.uk/); and (iv) known miRNA matching: detection of known miRNAs in miRBase (http://www.mirbase.org/) based on sequence homology. The expression levels corresponding to matched ncRNAs and miRNAs are summarized in multi-color clickable bar charts linked to external databases. DSAP is also capable of displaying miRNA expression levels from different jobs using a log2-scaled color matrix. Furthermore, a cross-species comparative function is also provided to show the distribution of identified miRNAs in different species as deposited in miRBase.
In order to validate the functions of DSAP, we used deep-sequencing technology to investigate the miRNA expression pattern in four deep-branching unicellular flagellates: Giardia lamblia, Trichomonas vaginalis, Tritrichomonas foetus, and Pentatrichomonas hominis. In addition to the known miRNAs that have been described in G. lamblia and T. vaginalis, we identified 14 ancient animal miRNA families and 13 plant-specific families from the four unicellular flagellates. Bioinformatics analysis also identified four novel miRNA candidates with reliable precursor structures derived from mature tRNAs. Our results indicated that miRNAs are likely to be a general feature for gene regulation throughout unicellular and multicellular eukaryotes and some of them may derive from unconventional ncRNAs such as snoRNA and tRNA.

微小RNA (microRNA)是一群具有重要基因調控功能且在多細胞真核生物已被廣泛研究的干擾性核醣核酸 (RNAi)。我們為高通量小RNA定序設計了一套多功能線上分析系統，命名為DSAP (Deep-sequencing Small RNA Analysis Pipeline)。DSAP提供了一個友善的使用者操作界面，使用者僅需將定序產生的 RNA 序列與其對應的表現量上傳到伺服器，並選定欲分析的生物物種或使用預設參數，即可進行全自動分析。其分析項目包含：
1. 連接子與低品質序列去除
 2. 合併重覆序列
 3. 非轉譯 RNA 資料庫 (Rfam) 比對
 4. miRBase 資料庫比對。此外，DSAP 還能以顏色矩陣的方式，同時呈現多筆實驗資料間標準化後的 microRNA 差異表現。分析的過程與結果可透過即時互動式圖表來檢視或下載，已完成分析的樣本也可透過伺服器所提供的序號加以追溯。
為了能讓使用者比較來自不同實驗平台 (Solexa、SOLiD、microarray…) 的資料，DSAP 還特地把 microRNA 差異表現的分析模組獨立出來，使用者僅需用剪貼的方式，即可將不同實驗平台的數據輸入 DSAP。最後，DSAP 還有一個最特別的功能，就是能依親緣關係顯示微小RNA 在不同物種間的分佈狀況。
為了進一步驗證DSAP的各種功能，我們選用了四種在演化上具有特殊地位(位於演化樹底層)的單細胞真核生物: 賈第亞蟲(Giardia lamblia)、人類陰道滴蟲(Trichomonas vaginalis)、牛陰道滴蟲(Tritrichomonas foetus) 、腸道道鞭毛蟲(Pentatrichomonas hominis)，並結合高通量定序方法來偵測微小RNA在四種單細胞鞭毛蟲中表現的差異。，我們從高通量定序資料中，除了還原三種在賈第亞蟲和人類陰道滴蟲中已驗證的微小RNA外，我們還找到了14種存在於古老多細胞動物和13種植物特有的微小RNA家族。配合生物資訊預測方法，我們額外發現了四條源自於 tRNA 序列片斷的微小RNA，並利用實驗方法加以驗證。
總之，我們的研究結果指出，微小RNA調控機制確實存在於單細胞生物。然而，它並非全部從典型的微小RNA生成機制而來，它也能從其它非典型的生成機制經由裁切snoRNA或tRNA而生成。

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