GENESIS 数据库和工具:孟德尔基因组学的十年发现。

IF 4.6 2区 医学 Q1 NEUROSCIENCES
Matt C. Danzi , Eric Powell , Adriana P. Rebelo , Maike F. Dohrn , Danique Beijer , Sarah Fazal , Isaac R.L. Xu , Jessica Medina , Sitong Chen , Yeisha Arcia de Jesus , Jacquelyn Schatzman , Ray E. Hershberger , Mario Saporta , Jonathan Baets , Marni Falk , David N. Herrmann , Steven S. Scherer , Mary M. Reilly , Andrea Cortese , Wilson Marques , Stephan Zuchner
{"title":"GENESIS 数据库和工具:孟德尔基因组学的十年发现。","authors":"Matt C. Danzi ,&nbsp;Eric Powell ,&nbsp;Adriana P. Rebelo ,&nbsp;Maike F. Dohrn ,&nbsp;Danique Beijer ,&nbsp;Sarah Fazal ,&nbsp;Isaac R.L. Xu ,&nbsp;Jessica Medina ,&nbsp;Sitong Chen ,&nbsp;Yeisha Arcia de Jesus ,&nbsp;Jacquelyn Schatzman ,&nbsp;Ray E. Hershberger ,&nbsp;Mario Saporta ,&nbsp;Jonathan Baets ,&nbsp;Marni Falk ,&nbsp;David N. Herrmann ,&nbsp;Steven S. Scherer ,&nbsp;Mary M. Reilly ,&nbsp;Andrea Cortese ,&nbsp;Wilson Marques ,&nbsp;Stephan Zuchner","doi":"10.1016/j.expneurol.2024.114978","DOIUrl":null,"url":null,"abstract":"<div><div>In the past decade, human genetics research saw an acceleration of disease gene discovery and further dissection of the genetic architectures of many disorders. Much of this progress was enabled via data aggregation projects, collaborative data sharing among researchers, and the adoption of sophisticated and standardized bioinformatics analyses pipelines. In 2012, we launched the GENESIS platform, formerly known as GEM.app, with the aims to 1) empower clinical and basic researchers without bioinformatics expertise to analyze and explore genome level data and 2) facilitate the detection of novel pathogenic variation and novel disease genes by leveraging data aggregation and genetic matchmaking. The GENESIS database has grown to over 20,000 datasets from rare disease patients, which were provided by multiple academic research consortia and many individual investigators. Some of the largest global collections of genome-level data are available for Charcot-Marie-Tooth disease, hereditary spastic paraplegia, and cerebellar ataxia. A number of rare disease consortia and networks are archiving their data in this database. Over the past decade, more than 1500 scientists have registered and used this resource and published over 200 papers on gene and variant identifications, which garnered &gt;6000 citations. GENESIS has supported &gt;100 gene discoveries and contributed to approximately half of all gene identifications in the fields of inherited peripheral neuropathies and spastic paraplegia in this time frame. Many diagnostic odysseys of rare disease patients have been resolved. The concept of genomes-to-therapy has borne out for a number of such discoveries that let to rapid clinical trials and expedited natural history studies. This marks GENESIS as one of the most impactful data aggregation initiatives in rare monogenic diseases.</div></div>","PeriodicalId":12246,"journal":{"name":"Experimental Neurology","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The GENESIS database and tools: A decade of discovery in Mendelian genomics\",\"authors\":\"Matt C. Danzi ,&nbsp;Eric Powell ,&nbsp;Adriana P. Rebelo ,&nbsp;Maike F. Dohrn ,&nbsp;Danique Beijer ,&nbsp;Sarah Fazal ,&nbsp;Isaac R.L. Xu ,&nbsp;Jessica Medina ,&nbsp;Sitong Chen ,&nbsp;Yeisha Arcia de Jesus ,&nbsp;Jacquelyn Schatzman ,&nbsp;Ray E. Hershberger ,&nbsp;Mario Saporta ,&nbsp;Jonathan Baets ,&nbsp;Marni Falk ,&nbsp;David N. Herrmann ,&nbsp;Steven S. Scherer ,&nbsp;Mary M. Reilly ,&nbsp;Andrea Cortese ,&nbsp;Wilson Marques ,&nbsp;Stephan Zuchner\",\"doi\":\"10.1016/j.expneurol.2024.114978\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In the past decade, human genetics research saw an acceleration of disease gene discovery and further dissection of the genetic architectures of many disorders. Much of this progress was enabled via data aggregation projects, collaborative data sharing among researchers, and the adoption of sophisticated and standardized bioinformatics analyses pipelines. In 2012, we launched the GENESIS platform, formerly known as GEM.app, with the aims to 1) empower clinical and basic researchers without bioinformatics expertise to analyze and explore genome level data and 2) facilitate the detection of novel pathogenic variation and novel disease genes by leveraging data aggregation and genetic matchmaking. The GENESIS database has grown to over 20,000 datasets from rare disease patients, which were provided by multiple academic research consortia and many individual investigators. Some of the largest global collections of genome-level data are available for Charcot-Marie-Tooth disease, hereditary spastic paraplegia, and cerebellar ataxia. A number of rare disease consortia and networks are archiving their data in this database. Over the past decade, more than 1500 scientists have registered and used this resource and published over 200 papers on gene and variant identifications, which garnered &gt;6000 citations. GENESIS has supported &gt;100 gene discoveries and contributed to approximately half of all gene identifications in the fields of inherited peripheral neuropathies and spastic paraplegia in this time frame. Many diagnostic odysseys of rare disease patients have been resolved. The concept of genomes-to-therapy has borne out for a number of such discoveries that let to rapid clinical trials and expedited natural history studies. This marks GENESIS as one of the most impactful data aggregation initiatives in rare monogenic diseases.</div></div>\",\"PeriodicalId\":12246,\"journal\":{\"name\":\"Experimental Neurology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Experimental Neurology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0014488624003042\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Experimental Neurology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0014488624003042","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

过去十年间,人类遗传学研究加速了疾病基因的发现,并进一步剖析了许多疾病的基因结构。这些进展在很大程度上得益于数据聚合项目、研究人员之间的协作数据共享,以及先进的标准化生物信息学分析管道的采用。2012 年,我们推出了 GENESIS 平台(前身为 GEM.app),目的是:1)让没有生物信息学专业知识的临床和基础研究人员能够分析和探索基因组水平的数据;2)通过利用数据聚合和基因匹配,促进新型致病变异和新型疾病基因的检测。GENESIS 数据库已发展到 20,000 多个罕见病患者数据集,这些数据集由多个学术研究联盟和许多个人研究者提供。全球最大的基因组水平数据集包括夏科-玛丽-牙病、遗传性痉挛性截瘫和小脑共济失调。一些罕见病联盟和网络正在将其数据归档到该数据库中。在过去十年中,1500 多名科学家注册并使用了这一资源,发表了 200 多篇关于基因和变异体鉴定的论文,获得了超过 6000 次引用。在此期间,GENESIS 为超过 100 个基因的发现提供了支持,并为遗传性周围神经病和痉挛性截瘫领域约一半的基因鉴定做出了贡献。许多罕见病患者的诊断难题已迎刃而解。从基因组到疗法的概念已在许多此类发现中得到证实,从而可以快速开展临床试验和自然病史研究。这标志着 GENESIS 成为罕见单基因疾病领域最具影响力的数据汇总计划之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The GENESIS database and tools: A decade of discovery in Mendelian genomics
In the past decade, human genetics research saw an acceleration of disease gene discovery and further dissection of the genetic architectures of many disorders. Much of this progress was enabled via data aggregation projects, collaborative data sharing among researchers, and the adoption of sophisticated and standardized bioinformatics analyses pipelines. In 2012, we launched the GENESIS platform, formerly known as GEM.app, with the aims to 1) empower clinical and basic researchers without bioinformatics expertise to analyze and explore genome level data and 2) facilitate the detection of novel pathogenic variation and novel disease genes by leveraging data aggregation and genetic matchmaking. The GENESIS database has grown to over 20,000 datasets from rare disease patients, which were provided by multiple academic research consortia and many individual investigators. Some of the largest global collections of genome-level data are available for Charcot-Marie-Tooth disease, hereditary spastic paraplegia, and cerebellar ataxia. A number of rare disease consortia and networks are archiving their data in this database. Over the past decade, more than 1500 scientists have registered and used this resource and published over 200 papers on gene and variant identifications, which garnered >6000 citations. GENESIS has supported >100 gene discoveries and contributed to approximately half of all gene identifications in the fields of inherited peripheral neuropathies and spastic paraplegia in this time frame. Many diagnostic odysseys of rare disease patients have been resolved. The concept of genomes-to-therapy has borne out for a number of such discoveries that let to rapid clinical trials and expedited natural history studies. This marks GENESIS as one of the most impactful data aggregation initiatives in rare monogenic diseases.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Experimental Neurology
Experimental Neurology 医学-神经科学
CiteScore
10.10
自引率
3.80%
发文量
258
审稿时长
42 days
期刊介绍: Experimental Neurology, a Journal of Neuroscience Research, publishes original research in neuroscience with a particular emphasis on novel findings in neural development, regeneration, plasticity and transplantation. The journal has focused on research concerning basic mechanisms underlying neurological disorders.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信