• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

用于系统挖掘与罕见疾病相关的基因组和蛋白质组变异的生物信息学管道：以单基因糖尿病为例。

Bioinformatics pipeline for the systematic mining genomic and proteomic variation linked to rare diseases: The example of monogenic diabetes.

机构信息

Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway.

Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway.

出版信息

PLoS One. 2024 Apr 18;19(4):e0300350. doi: 10.1371/journal.pone.0300350. eCollection 2024.

DOI:10.1371/journal.pone.0300350
PMID:38635808
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11025945/
Abstract

Monogenic diabetes is characterized as a group of diseases caused by rare variants in single genes. Like for other rare diseases, multiple genes have been linked to monogenic diabetes with different measures of pathogenicity, but the information on the genes and variants is not unified among different resources, making it challenging to process them informatically. We have developed an automated pipeline for collecting and harmonizing data on genetic variants linked to monogenic diabetes. Furthermore, we have translated variant genetic sequences into protein sequences accounting for all protein isoforms and their variants. This allows researchers to consolidate information on variant genes and proteins linked to monogenic diabetes and facilitates their study using proteomics or structural biology. Our open and flexible implementation using Jupyter notebooks enables tailoring and modifying the pipeline and its application to other rare diseases.

摘要

单基因糖尿病的特征是由单个基因中的罕见变异引起的一组疾病。与其他罕见疾病一样，多个基因与单基因糖尿病相关，其致病性的衡量标准也不同，但不同资源之间的基因和变异信息并不统一，这使得对其进行信息处理具有挑战性。我们开发了一个自动化的管道，用于收集和协调与单基因糖尿病相关的遗传变异数据。此外，我们还将变异基因序列翻译成包含所有蛋白质同工型及其变体的蛋白质序列。这使得研究人员能够整合与单基因糖尿病相关的变异基因和蛋白质的信息，并使用蛋白质组学或结构生物学来促进对其的研究。我们使用 Jupyter 笔记本的开放和灵活的实现方式，使得对管道及其在其他罕见疾病中的应用进行定制和修改成为可能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/6e6982a868fb/pone.0300350.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/2e399ba61f06/pone.0300350.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/fd29b684aa05/pone.0300350.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/fea6d321c51d/pone.0300350.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/7067df08541f/pone.0300350.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/6e6982a868fb/pone.0300350.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/2e399ba61f06/pone.0300350.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/fd29b684aa05/pone.0300350.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/fea6d321c51d/pone.0300350.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/7067df08541f/pone.0300350.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/584d/11025945/6e6982a868fb/pone.0300350.g005.jpg

相似文献

1
Bioinformatics pipeline for the systematic mining genomic and proteomic variation linked to rare diseases: The example of monogenic diabetes.用于系统挖掘与罕见疾病相关的基因组和蛋白质组变异的生物信息学管道：以单基因糖尿病为例。
PLoS One. 2024 Apr 18;19(4):e0300350. doi: 10.1371/journal.pone.0300350. eCollection 2024.
2
Clinical usefulness of multigene screening with phenotype-driven bioinformatics analysis for the diagnosis of patients with monogenic diabetes or severe insulin resistance.基于表型驱动的生物信息学分析的多基因筛查对单基因糖尿病或严重胰岛素抵抗患者的诊断的临床应用。
Diabetes Res Clin Pract. 2020 Nov;169:108461. doi: 10.1016/j.diabres.2020.108461. Epub 2020 Sep 22.
3
GeneVetter: a web tool for quantitative monogenic assessment of rare diseases.GeneVetter：一个用于罕见病定量单基因评估的网络工具。
Bioinformatics. 2015 Nov 15;31(22):3682-4. doi: 10.1093/bioinformatics/btv432. Epub 2015 Jul 23.
4
Cohort-driven variant burden analysis and pathogenicity identification in monogenic autoinflammatory disorders.队列驱动的单基因自身炎症性疾病变异负担分析和致病性鉴定。
J Allergy Clin Immunol. 2023 Aug;152(2):517-527. doi: 10.1016/j.jaci.2023.03.028. Epub 2023 Apr 7.
5
PhyreRisk: A Dynamic Web Application to Bridge Genomics, Proteomics and 3D Structural Data to Guide Interpretation of Human Genetic Variants.PhyreRisk：一个动态的 Web 应用程序，将基因组学、蛋白质组学和 3D 结构数据联系起来，指导人类遗传变异的解释。
J Mol Biol. 2019 Jun 14;431(13):2460-2466. doi: 10.1016/j.jmb.2019.04.043. Epub 2019 May 7.
6
Integrating medical and genomic data: a successful example for rare diseases.整合医学与基因组数据：罕见病的一个成功范例。
Stud Health Technol Inform. 2006;124:125-30.
7
Delineation of the genetic and clinical spectrum, including candidate genes, of monogenic diabetes: a multicenter study in South Korea.单基因糖尿病的遗传和临床谱系（包括候选基因）的描绘：韩国的一项多中心研究
J Pediatr Endocrinol Metab. 2020 Oct 8;33(12):1539-1550. doi: 10.1515/jpem-2020-0336. Print 2020 Dec 16.
8
Next-generation sequencing and bioinformatics in rare movement disorders.下一代测序和罕见运动障碍的生物信息学。
Nat Rev Neurol. 2024 Feb;20(2):114-126. doi: 10.1038/s41582-023-00909-9. Epub 2024 Jan 3.
9
Functional genomics and proteomics in the clinical neurosciences: data mining and bioinformatics.临床神经科学中的功能基因组学和蛋白质组学：数据挖掘与生物信息学
Prog Brain Res. 2006;158:83-108. doi: 10.1016/S0079-6123(06)58004-5.
10
Automated reanalysis application to assist in detecting novel gene-disease associations after genome sequencing.自动化重分析应用程序，有助于在基因组测序后检测新的基因-疾病关联。
Genet Med. 2022 Apr;24(4):811-820. doi: 10.1016/j.gim.2021.11.021. Epub 2021 Nov 27.

引用本文的文献

1
Co-inheritance of Rare Variants of Maturity-Onset Diabetes of the Young (MODY): A Case Report and Review of the Literature.青年发病的成年型糖尿病（MODY）罕见变异的共遗传：一例病例报告及文献综述
Cureus. 2024 Sep 9;16(9):e69039. doi: 10.7759/cureus.69039. eCollection 2024 Sep.

本文引用的文献

1
Finding haplotypic signatures in proteins.寻找蛋白质中的单倍型特征。
Gigascience. 2022 Dec 28;12. doi: 10.1093/gigascience/giad093. Epub 2023 Oct 31.
2
Accurate proteome-wide missense variant effect prediction with AlphaMissense.使用 AlphaMissense 进行精确的全蛋白质错义变异效应预测。
Science. 2023 Sep 22;381(6664):eadg7492. doi: 10.1126/science.adg7492.
3
Monogenic diabetes.单基因糖尿病。
Nat Rev Dis Primers. 2023 Mar 9;9(1):12. doi: 10.1038/s41572-023-00421-w.
4
Structural and biophysical characterization of transcription factor HNF-1A as a tool to study MODY3 diabetes variants.转录因子 HNF-1A 的结构和生物物理特性分析，可作为研究 MODY3 糖尿病变异体的工具。
J Biol Chem. 2022 Apr;298(4):101803. doi: 10.1016/j.jbc.2022.101803. Epub 2022 Mar 4.
5
Genetic associations of protein-coding variants in human disease.人类疾病相关蛋白编码变异的遗传关联。
Nature. 2022 Mar;603(7899):95-102. doi: 10.1038/s41586-022-04394-w. Epub 2022 Feb 23.
6
Evaluation of Evidence for Pathogenicity Demonstrates That BLK, KLF11, and PAX4 Should Not Be Included in Diagnostic Testing for MODY.致病性证据评估表明，BLK、KLF11 和 PAX4 不应包含在 MODY 的诊断测试中。
Diabetes. 2022 May 1;71(5):1128-1136. doi: 10.2337/db21-0844.
7
Generation of ENSEMBL-based proteogenomics databases boosts the identification of non-canonical peptides.基于 ENSEMBL 的蛋白质基因组学数据库的生成提高了非规范肽的鉴定能力。
Bioinformatics. 2022 Feb 7;38(5):1470-1472. doi: 10.1093/bioinformatics/btab838.
8
Ensembl 2022.Ensembl 2022.
Nucleic Acids Res. 2022 Jan 7;50(D1):D988-D995. doi: 10.1093/nar/gkab1049.
9
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.AlphaFold 蛋白质结构数据库：用高精度模型极大地扩展蛋白质序列空间的结构覆盖范围。
Nucleic Acids Res. 2022 Jan 7;50(D1):D439-D444. doi: 10.1093/nar/gkab1061.
10
Causal variants in Maturity Onset Diabetes of the Young (MODY) - A systematic review.青年发病型糖尿病（MODY）的因果变体：系统评价。
BMC Endocr Disord. 2021 Nov 11;21(1):223. doi: 10.1186/s12902-021-00891-7.