Detecting microsatellite instability by length comparison of microsatellites in the 3' untranslated region with RNA-seq.

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Jin-Wook Choi, Jin-Ok Lee, Sejoon Lee
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引用次数: 0

Abstract

Microsatellite instability (MSI), a phenomenon caused by deoxyribonucleic acid (DNA) mismatch repair system deficiencies, is an important biomarker in cancer research and clinical diagnostics. MSI detection often involves next-generation sequencing data, with many studies focusing on DNA. Here, we introduce a novel approach by measuring microsatellite lengths directly from ribonucleic acid sequencing (RNA-seq) data and comparing its distribution to detect MSI. Our findings reveal distinct instability patterns between MSI-high (MSI-H) and microsatellite stable samples, indicating the efficacy of RNA-based MSI detection. Additionally, microsatellites in the 3'-untranslated regions showed the greatest predictive value for MSI detection. Notably, this efficacy extends to detecting MSI-H samples even in tumors not commonly associated with MSI. Our approach highlights the utility of RNA-seq data in MSI detection, facilitating more precise diagnostics through the integration of various biological data.

利用 RNA-seq 对 3' 非翻译区的微卫星进行长度比较,检测微卫星的不稳定性。
微卫星不稳定性(MSI)是一种由脱氧核糖核酸(DNA)错配修复系统缺陷引起的现象,是癌症研究和临床诊断中的重要生物标志物。MSI 检测通常涉及下一代测序数据,许多研究侧重于 DNA。在这里,我们引入了一种新方法,直接从核糖核酸测序(RNA-seq)数据中测量微卫星长度,并比较其分布以检测 MSI。我们的发现揭示了MSI-高(MSI-H)和微卫星稳定样本之间不同的不稳定性模式,表明基于RNA的MSI检测是有效的。此外,3'-非翻译区的微卫星对 MSI 检测具有最大的预测价值。值得注意的是,即使在不常伴有MSI的肿瘤中,这种功效也能延伸到检测MSI-H样本。我们的方法凸显了 RNA-seq 数据在 MSI 检测中的作用,通过整合各种生物数据促进了更精确的诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
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