Department of Biosciences, University of Milan, Milan, Italy; Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari, Italy.
Department of Biosciences, University of Milan, Milan, Italy.
J Mol Biol. 2021 May 28;433(11):166829. doi: 10.1016/j.jmb.2021.166829. Epub 2021 Jan 26.
In diploid organisms, two copies of each allele are normally inherited from parents. Paternal and maternal alleles can be regulated and expressed unequally, which is referred to as allele-specific expression (ASE). In this work, we present aScan, a novel method for the identification of ASE from the analysis of matched individual genomic and RNA sequencing data. By performing extensive analyses of both real and simulated data, we demonstrate that aScan can correctly identify ASE with high accuracy and sensitivity in different experimental settings. Additionally, by applying our method to a small cohort of individuals that are not included in publicly available databases of human genetic variation, we outline the value of possible applications of ASE analysis in single individuals for deriving a more accurate annotation of "private" low-frequency genetic variants associated with regulatory effects on transcription. All in all, we believe that aScan will represent a beneficial addition to the set of bioinformatics tools for the analysis of ASE. Finally, while our method was initially conceived for the analysis of RNA-seq data, it can in principle be applied to any quantitative NGS assay for which matched genotypic and expression data are available. AVAILABILITY: aScan is currently available in the form of an open source standalone software package at: https://github.com/Federico77z/aScan/. aScan version 1.0.3, available at https://github.com/Federico77z/aScan/releases/tag/1.0.3, has been used for all the analyses included in this manuscript. A Docker image of the tool has also been made available at https://github.com/pmandreoli/aScanDocker.
在二倍体生物中，每个等位基因通常从父母那里遗传两个拷贝。父本和母本的等位基因可以被调控和表达不均等，这被称为等位基因特异性表达（ASE）。在这项工作中，我们提出了一种Scan，这是一种从匹配个体基因组和 RNA 测序数据分析中识别 ASE 的新方法。通过对真实和模拟数据进行广泛的分析，我们证明了 aScan 可以在不同的实验设置下以高精度和高灵敏度正确识别 ASE。此外，通过将我们的方法应用于一小部分个体，这些个体不包含在人类遗传变异的公共数据库中，我们概述了 ASE 分析在个体中应用的潜在价值，以便更准确地注释与转录调控效应相关的“私有”低频遗传变异。总之，我们相信 aScan 将成为分析 ASE 的生物信息学工具集的有益补充。最后，虽然我们的方法最初是为 RNA-seq 数据的分析而构思的，但它原则上可以应用于任何具有匹配基因型和表达数据的定量 NGS 检测。可用性：aScan 目前以开源独立软件包的形式提供：https://github.com/Federico77z/aScan/。用于本文中包含的所有分析的 aScan 版本 1.0.3 可在 https://github.com/Federico77z/aScan/releases/tag/1.0.3 获得。该工具的 Docker 镜像也可在 https://github.com/pmandreoli/aScanDocker 获得。
