利用次世代定序資料探討等位基因表現不平衡之分析方法

Abstract

等位基因表現不平衡是指兩個等位基因有顯著差異的基因表現程度，而近期也已經在癌症生物學上有研究價值的一席之地，然而目前對等位基因表現不平衡的實際機制與影響尚未完全了解，因此從現有資料去萃取等位基因表現的資訊便是很重要的事情。而隨著次世代定序的技術進步，能夠透過生物資訊的方法來找出發生等位基因表現不平衡的基因，因此我們提出了一個方法從核酸與核苷酸的次世代定序的資料裡找出等位基因不平衡現象的基因群。方法上主要是藉由異型合子的單一變異位點來定位兩個等位基因的表現數值，透過來自核酸與核苷酸兩次世代定序資料的比值差異計算兩個等位基因表現不平衡的程度，以數學模型來找出顯著差異的基因，並且，我們將此方法應用到兩個資料集上來看等位基因表現的研究。 結果上，我們以GSE48216資料集去討論等位基因表現不平衡的資料型態以及在組織的亞型分群的關係，首先在16個ER顯性細胞株中，每個細胞株平均有119個等位基因表現不平衡的基因。大多數的基因來自X染色體，是女性其中一套X染色體失去活性的現象，也作為我們方法的陽性控制。而這些基因之中，雖然大多數基因都是以主要等位基因形式表現，我們看到少數以次要等位基因形式表現的基因上有潛在危險性非同義單一變異點與ER和癌症的生物途徑有關，如HSD17B7、IRAK、XIAP等基因，因此我們認為部分發生等位基因表現不平衡的基因可能與癌症發生有關。除此之外，我們也看到不同組織的亞型間有不同等位基因表現表現不平衡的資料型態，顯示了亞群分類可能會影響到等位基因的分析。另一方面，我們從肝內膽管細胞癌的資料集(GSE63420)中去看只發生在癌症組織的等位基因表現不平衡的基因，平均每個病人收到573個基因內，我們也看到了有等位基因表現不平衡的熱點與危險性非同義單一變異點的基因，如與過去被報導與該疾病有關的IDH1，會不斷表現出具風險的錯義突變位點R132的核酸序列。結合以上來看，我們的結果也暗指部分發生等位基因表現不平衡的基因可能藉由其他機制來影響癌症生成。 在此我們建立了一個方法來找出發生等位基因表現不平衡的基因，我們的結果也顯示出等位基因表現不平衡的現象可能影響了癌症的調控失衡，這樣的方法與分析能夠提供未來在等位基因的基礎研究以及在基因體的變異點研究上有更多的資訊。

Allelic imbalance, which means different expression abundance between two alleles, recently has become a special landmark on cancer biology. However, the present of allelic imbalance has not been fully understood yet. Taking the advantages of next generation sequencing, allelic imbalance can be identified and quantified through bioinformatics algorithms. Here, we developed a mathematical method to identify with allelic imbalance by concurrently analyzing RNA-Seq and DNA-Seq. First we called heterozygous SNVs from both RNA-Seq and Exome-Seq data. The allele ratio is counted by the ratio of read depth between two alleles after integrating SNVs into gene level. Next, we identified allelic imbalance genes by differences of RNA and DNA allele ratios. Here, we applied our method to 2 current datasets to study the issue of allelic imbalance. As results, we used GSE48216 to discuss the profiles and consistency of allelic imbalance between breast cancer subtypes. We identified 119 genes on average which are significantly allelic imbalance in 16 ER positive breast cancer cell lines. Some allelic imbalance genes were belonged to X-chromosome as our positive controls, which are resulted from X-inactivation in female cells. Among these genes, although the transcripts in allelic imbalance genes were from major alleles, some non-synonymous SNVs in allelic imbalance genes were associated with ER and cancer pathway, such as HSD17B7, IRAK, XIAP. We suggested that they had potential risk to tumorigenesis. Besides, we found different allelic imbalance profiles and consistency between ER+ and ER- breast cancer cell line. It suggested that the subtype is an important factor for allele-expression study. On the other hand, we also screened 7 patients NGS data of intrahepatic cholangiocarcinoma (GSE63420) to study the profiles of tumor-specific allelic imbalance genes. Among 573 genes on average in each patient, we also found the hotspots of allelic imbalance and genes with potential risk non-synonymous SNVs, such as the dominant transcript of missense mutation on R132 of IDH1 protein. Taking together, the results indicated that partial genes of allelic imbalance might potentially influence tumorigenesis by another unknown mechanism. To sum up, we proposed a method to call allelic imbalance genes. Our results also demonstrated the role of allelic imbalance of dysregulation of tumor. Moreover, our method and analysis can be applied to uncover more basic mechanisms on allelic imbalance and provide more information on variant studies.