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SomaMutDB:正常人体组织中体细胞突变的数据库。

SomaMutDB: a database of somatic mutations in normal human tissues.

机构信息

Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA.

Laboratory of Applied Genomic Technologies, Voronezh State University of Engineering Technology, Voronezh, Russia.

出版信息

Nucleic Acids Res. 2022 Jan 7;50(D1):D1100-D1108. doi: 10.1093/nar/gkab914.

Abstract

De novo mutations, a consequence of errors in DNA repair or replication, have been reported to accumulate with age in normal tissues of humans and model organisms. This accumulation during development and aging has been implicated as a causal factor in aging and age-related pathology, including but not limited to cancer. Due to their generally very low abundance mutations have been difficult to detect in normal tissues. Only with recent advances in DNA sequencing of single-cells, clonal lineages or ultra-high-depth sequencing of small tissue biopsies, somatic mutation frequencies and spectra have been unveiled in several tissue types. The rapid accumulation of such data prompted us to develop a platform called SomaMutDB (https://vijglab.einsteinmed.org/SomaMutDB) to catalog the 2.42 million single nucleotide variations (SNVs) and 0.12 million small insertions and deletions (INDELs) thus far identified using these advanced methods in nineteen human tissues or cell types as a function of age or environmental stress conditions. SomaMutDB employs a user-friendly interface to display and query somatic mutations with their functional annotations. Moreover, the database provides six powerful tools for analyzing mutational signatures associated with the data. We believe such an integrated resource will prove valuable for understanding somatic mutations and their possible role in human aging and age-related diseases.

摘要

新生突变是 DNA 修复或复制错误的结果,据报道,在人类和模式生物的正常组织中会随着年龄的增长而积累。这种在发育和衰老过程中的积累被认为是衰老和与年龄相关的病理的一个因果因素,包括但不限于癌症。由于突变的丰度通常非常低,因此在正常组织中很难检测到。只有随着单细胞、克隆谱系或小组织活检的超高深度测序的 DNA 测序技术的最新进展,才能在几种组织类型中揭示体细胞突变的频率和图谱。这些数据的快速积累促使我们开发了一个名为 SomaMutDB(https://vijglab.einsteinmed.org/SomaMutDB)的平台,该平台对使用这些先进方法在 19 个人体组织或细胞类型中迄今已鉴定的 242 万个单核苷酸变异(SNVs)和 0.12 万个小插入和缺失(INDELs)进行编目,作为年龄或环境应激条件的函数。SomaMutDB 采用用户友好的界面来显示和查询具有功能注释的体细胞突变。此外,该数据库提供了六个用于分析与数据相关的突变特征的强大工具。我们相信,这样一个集成的资源将有助于理解体细胞突变及其在人类衰老和与年龄相关的疾病中的可能作用。

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