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本文引用的文献

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Rett Syndrome: A Genetic Update and Clinical Review Focusing on Comorbidities.雷特综合征:遗传更新与临床综述,关注共病。
ACS Chem Neurosci. 2018 Feb 21;9(2):167-176. doi: 10.1021/acschemneuro.7b00346. Epub 2017 Dec 15.
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RettBASE: Rett syndrome database update.雷特综合征数据库(RettBASE):雷特综合征数据库更新
Hum Mutat. 2017 Aug;38(8):922-931. doi: 10.1002/humu.23263. Epub 2017 Jun 9.
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Improving genetic diagnosis in Mendelian disease with transcriptome sequencing.通过转录组测序改善孟德尔疾病的基因诊断。
Sci Transl Med. 2017 Apr 19;9(386). doi: 10.1126/scitranslmed.aal5209.
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dbVar structural variant cluster set for data analysis and variant comparison.用于数据分析和变异比较的数据库变异(dbVar)结构变异簇集
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The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies.人类基因突变数据库:致力于打造一个全面的遗传性突变数据仓库,服务于医学研究、基因诊断及新一代测序研究。
Hum Genet. 2017 Jun;136(6):665-677. doi: 10.1007/s00439-017-1779-6. Epub 2017 Mar 27.
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DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants.DisGeNET:一个整合人类疾病相关基因和变异信息的综合平台。
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Rett syndrome - biological pathways leading from MECP2 to disorder phenotypes.雷特综合征——从MECP2到疾病表型的生物学途径。
Orphanet J Rare Dis. 2016 Nov 25;11(1):158. doi: 10.1186/s13023-016-0545-5.
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Rett Syndrome and the Ongoing Legacy of Close Clinical Observation.雷特综合征与持续的密切临床观察的影响
Cell. 2016 Oct 6;167(2):293-297. doi: 10.1016/j.cell.2016.09.039.
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From Wet-Lab to Variations: Concordance and Speed of Bioinformatics Pipelines for Whole Genome and Whole Exome Sequencing.从湿实验室到变异:全基因组和全外显子组测序的生物信息学流程的一致性和速度
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MECP2 变异在雷特综合征中的作用——现有数据库中遗传和表型数据的现有覆盖范围概述。

MECP2 variation in Rett syndrome-An overview of current coverage of genetic and phenotype data within existing databases.

机构信息

Rett Expertise Centre Netherlands - GKC, Maastricht University Medical Center, Maastricht, The Netherlands.

Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands.

出版信息

Hum Mutat. 2018 Jul;39(7):914-924. doi: 10.1002/humu.23542. Epub 2018 May 21.

DOI:10.1002/humu.23542
PMID:29704307
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6033003/
Abstract

Rett syndrome (RTT) is a monogenic rare disorder that causes severe neurological problems. In most cases, it results from a loss-of-function mutation in the gene encoding methyl-CPG-binding protein 2 (MECP2). Currently, about 900 unique MECP2 variations (benign and pathogenic) have been identified and it is suspected that the different mutations contribute to different levels of disease severity. For researchers and clinicians, it is important that genotype-phenotype information is available to identify disease-causing mutations for diagnosis, to aid in clinical management of the disorder, and to provide counseling for parents. In this study, 13 genotype-phenotype databases were surveyed for their general functionality and availability of RTT-specific MECP2 variation data. For each database, we investigated findability and interoperability alongside practical user functionality, and type and amount of genetic and phenotype data. The main conclusions are that, as well as being challenging to find these databases and specific MECP2 variants held within, interoperability is as yet poorly developed and requires effort to search across databases. Nevertheless, we found several thousand online database entries for MECP2 variations and their associated phenotypes, diagnosis, or predicted variant effects, which is a good starting point for researchers and clinicians who want to provide, annotate, and use the data.

摘要

雷特综合征(RTT)是一种单基因罕见疾病,会导致严重的神经问题。在大多数情况下,它是由编码甲基-CPG 结合蛋白 2(MECP2)的基因突变引起的。目前,已经鉴定出大约 900 种独特的 MECP2 变异(良性和致病性),并且怀疑不同的突变导致不同程度的疾病严重程度。对于研究人员和临床医生来说,获得基因型-表型信息非常重要,这有助于识别致病突变以进行诊断,辅助疾病的临床管理,并为父母提供咨询。在这项研究中,我们调查了 13 个基因型-表型数据库,以了解它们的一般功能以及 RTT 特异性 MECP2 变异数据的可用性。对于每个数据库,我们调查了可发现性和互操作性以及实际用户功能,以及遗传和表型数据的类型和数量。主要结论是,除了难以找到这些数据库以及其中包含的特定 MECP2 变体之外,互操作性的发展还很差,需要努力在数据库之间进行搜索。尽管如此,我们还是找到了数千个 MECP2 变异及其相关表型、诊断或预测变异效应的在线数据库条目,这对于希望提供、注释和使用这些数据的研究人员和临床医生来说是一个很好的起点。