Estimating the size of long tandem repeat expansions from short reads with ScatTR

IF 5.5 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Rashid Al-Abri, Gamze Gursoy
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引用次数: 0

Abstract

Tandem repeats (TRs) are sequences of DNA where two or more base pairs are repeated back-to-back at specific locations in the genome. TR expansions, where the number of repeat units exceeds the normal range, have been implicated in over 50 conditions. However, accurately measuring the copy number of TRs is challenging, especially when their expansions are larger than the fragment sizes used in standard short-read genome sequencing. Here, we introduce ScatTR, a novel computational method that leverages a maximum likelihood framework to estimate the copy number of large TR expansions from short-read sequencing data. ScatTR calculates the likelihood of different alignments between sequencing reads and reference sequences that represent various TR lengths and employs a Monte Carlo technique to find the best match. In simulated data, ScatTR outperforms state-of-the-art methods, particularly for TRs with longer motifs and those with lengths that greatly exceed typical sequencing fragment sizes. When applied to data from the 1000 Genomes Project, ScatTR detects potential large TR expansions that other methods missed, highlighting its ability to better characterize genome-wide TR variation.
用ScatTR估计短读长串联重复扩增的大小
串联重复序列(TRs)是DNA序列,其中两个或多个碱基对在基因组的特定位置连续重复。在超过50种情况下,重复单位数量超过正常范围的TR扩展已被涉及。然而,准确测量TRs的拷贝数是具有挑战性的,特别是当它们的扩增量大于标准短读基因组测序中使用的片段大小时。在这里,我们介绍了ScatTR,一种新的计算方法,利用最大似然框架来估计短读测序数据中大TR扩展的拷贝数。ScatTR计算测序读数和代表不同TR长度的参考序列之间不同排列的可能性,并采用蒙特卡罗技术找到最佳匹配。在模拟数据中,ScatTR优于最先进的方法,特别是对于具有较长基序和长度大大超过典型测序片段大小的TRs。当应用于1000基因组计划的数据时,ScatTR检测到其他方法遗漏的潜在的大TR扩增,突出了其更好地表征全基因组TR变异的能力。
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
Genome research
Genome research 生物-生化与分子生物学
CiteScore
12.40
自引率
1.40%
发文量
140
审稿时长
6 months
期刊介绍: Launched in 1995, Genome Research is an international, continuously published, peer-reviewed journal that focuses on research that provides novel insights into the genome biology of all organisms, including advances in genomic medicine. Among the topics considered by the journal are genome structure and function, comparative genomics, molecular evolution, genome-scale quantitative and population genetics, proteomics, epigenomics, and systems biology. The journal also features exciting gene discoveries and reports of cutting-edge computational biology and high-throughput methodologies. New data in these areas are published as research papers, or methods and resource reports that provide novel information on technologies or tools that will be of interest to a broad readership. Complete data sets are presented electronically on the journal''s web site where appropriate. The journal also provides Reviews, Perspectives, and Insight/Outlook articles, which present commentary on the latest advances published both here and elsewhere, placing such progress in its broader biological context.
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