利用焦磷酸定序法偵測混合DNA樣本池中的未知單一核甘酸多型性--- 一個新演算法的發展與應用

Abstract

在族群遺傳學研究上，尤其是針對人類的常見(複雜)疾病，單一核苷酸多型性(SNPs)扮演了非常重要的角色。當我們想要對大量樣本做篩檢以了解各種對偶基因在族群中所佔的比率時，利用混合DNA樣本池則是一個有效又經濟的做法。另一方面，焦磷酸定序法則可能是近年來最成功的非傳統定序方法。它不只被使用來偵測SNPs以及判斷生物體的不同分離株，同時也因為焦磷酸定序反應發出的光訊號和樣本DNA的量呈高度相關，它也被使用來估計對偶基因的表現量以及分析各對偶基因在混合DNA樣本池中所佔的比率。然而，在進行焦磷酸定序反應時，我們必須很小心的設定dNTPs加入的順序以避免異型合子序列造成的反應不同步，因為這個順序決定了定序反應產生的焦磷酸定序圖譜。雖然焦磷酸定序法很適合用來做為已知SNP的模式比對，它卻很難被應用來發掘新的SNP，因為這是一個很困難的問題，通常需要靠人工的方式才能進行。目前的序列分析軟體仍無法在混合DNA樣本池中找出新的SNP。本研究的目的就是要發展出一種演算法來解決這個問題。這個演算法不只可以在有預期外的突變發生時仍可自動判讀焦磷酸定序圖譜，還可以被應用來篩選尋找混合DNA樣本池中的新SNP。因此本研究應可被廣泛的應用，尤其是在族群遺傳學的研究上。我們也將根據發展出來的演算法建立一個網頁平台，以提供對於利用焦磷酸定序法來研究族群遺傳學有興趣的生物學家使用。最後，我們也會利用這個方法來解決實際的生物問題。最先選擇的是利用台灣草蜥複合種群做為模式生物來研究驗證異域種化、同域種化、鄰域種化、以及梯度種化等假說。

Single nucleotide polymorphisms (SNPs) are extremely important in studying population genetics, especially for human complex disease. When doing a survey in a large number of individuals, DNA pooling is an efficient and economical way to reveal the frequency for each allele in the population. On the other hand, PyrosequencingTM is arguably the most successful non-Sanger method developed in recent years. It not only has been used to detect SNPs and to determine organismal isolates, because the light generated by the PyrosequencingTM reactions is highly proportional to the amount of DNA template, this technique also has been used to measure allelic gene expression and to analyze allele frequencies in DNA pools. However, the dispensing order of dNTPs determines the pyrogram profile, which must be carefully designed to avoid asynchronistic extensions of heterozygous sequences. Although PyrosequencingTM may be suited for pattern matching of known SNP profiles, its application for de novo SNP discovery is less certain. It is because base-calling for de novo SNPs is problematic and still performed manually. Current sequencing software cannot detect new polymorphisms in pooled DNA samples. The aim of this study is to develop an algorithm to resolve this problem. This algorithm will not only be applied to automatically read the pyrogram profile when unexpected mutations occurred, but also be applied to screen novel SNPs in pool DNA samples. This study therefore can be widely applied, especially for population genetics studies. We will also construct a web server based on this algorithm and provide the service for all biologists who are interested in using PyrosequencingTM assays as the tool to study population genetics. In the last year, we will also use this algorithm to resolve a practical biological problem, i.e., use lizard species complex as the model organisms to test allopatric speciation, sympatric speciation, parapatric speciation, and clinal speciation hypotheses. 表