| Summary: | 碩士 === 國立臺灣大學 === 生醫電子與資訊學研究所 === 105 === 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.
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