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A Comprehensive Database for Genes and Mutations Database, 2016, 1–8 doi: 10.1093/database/baw127 Database Tool Database Tool Skeleton Genetics: a comprehensive database for genes and mutations related to genetic skeletal disorders Chong Chen1,†, Yi Jiang2,†, Chenyang Xu1, Xinting Liu2, Lin Hu3, Yanbao Xiang1, Qingshuang Chen1, Denghui Chen2, Huanzheng Li1, Xueqin Xu1 and Shaohua Tang1,3,* 1Department of Genetics of Dingli Clinical Medical School, Wenzhou Central Hospital, Wenzhou 325000, China, 2Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou 325035, China, 3School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou 325035, China *Corresponding author: Tel/Fax: 86 577 88070197; Email: [email protected] †These authors contributed equally to this work. Citation details: Chen,C., Jiang,J., Xu,C. et al. SkeletonGenetics: a comprehensive database for genes and mutations related to genetic skeletal disorders. Database (2016) Vol. 2016: article ID baw127; doi:10.1093/database/baw127 Received 2 May 2016; Revised 2 August 2016; Accepted 12 August 2016 Abstract Genetic skeletal disorders (GSD) involving the skeletal system arises through disturbances in the complex processes of skeletal development, growth and homeostasis and remain a diagnostic challenge because of their clinical heterogeneity and genetic variety. Over the past decades, tremendous effort platforms have been made to explore the complex het- erogeneity, and massive new genes and mutations have been identified in different GSD, but the information supplied by literature is still limited and it is hard to meet the further needs of scientists and clinicians. In this study, combined with Nosology and Classification of genetic skeletal disorders, we developed the first comprehensive and annotated genetic skeletal disorders database, named ‘SkeletonGenetics’, which contains information about all GSD-related knowledge including 8225 mutations in 357 genes, with detailed informa- tion associated with 481 clinical diseases (2260 clinical phenotype) classified in 42 groups defined by molecular, biochemical and/or radiographic criteria from 1698 publications. Further annotations were performed to each entry including Gene Ontology, pathways analysis, protein–protein interaction, mutation annotations, disease–disease clustering and gene–disease networking. Furthermore, using concise search methods, intuitive graphical displays, convenient browsing functions and constantly updatable features, ‘SkeletonGenetics’ could serve as a central and integrative database for unveiling the gen- etic and pathways pre-dispositions of GSD. Database URL: http://101.200.211.232/skeletongenetics/ VC The Author(s) 2016. Published by Oxford University Press. Page 1 of 8 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unre- stricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. (page number not for citation purposes) Page 2 of 8 Database, Vol. 2016, Article ID baw127 Introduction mutation information and extensive annotations for GSD. The skeleton provides the structural framework in humans Initially, we retrospectively extracted the basic information for muscle attachments, assists movement, protects organs, for each mutation (disease conditions or syndrome, gene and maintains the homeostasis of the vascular systems (1). symbol, number of OMIM, hereditary mode, coding se- Perturbation of development in bone, cartilage and joints quence change, transcript, ethnicity, age, PubMed ID, etc.) could result in human skeletal dysplasias, which affect ap- from open publications. Additionally, extensive annota- proximately 1 in 5000 live births and is one of the common tions were performed, which include gene information, causes of neonatal birth defect in departments of obstetrics Gene Ontology, pathways analysis, protein-protein inter- (2). Genetic skeletal disorders (GSD), which are a group of action, mutations clustering and gene-disease network. As disorders involving gene mutations or genetic susceptibility a result, 42 groups of GSD, 481 diseases or syndromes, to bone disease, account for most of the human skeletal 357 genes, 5884 single nucleotide variations (SNVs), 516 dysplasias, involving a variety of pathogenic factors and insertions, 1427 deletions and 2260 different phenotypes diseases (3). In the Nosology and Classification of Genetic were included. Taken together, ‘SkeletonGenetics’ is con- Skeletal Disorders 2015 revision (hereinafter referred to as structed to be a well-organized, internal-standard and NCGSD-2015), 436 conditions were included and placed comprehensive resource for scientists and clinicians look- in 42 groups, which were associated with mutations in one ing for the clinical correlates of mutations, genes and path- or more of 336 unique genes (4). Till now, especially with ways involved in skeletal biology. the impact the next-generation sequencing technology has made on the study of genetic skeletal disorders, a large amount of mutations and novel GSD-related genes have Methods been identified. Genetic skeletal disorders face similar prob- The standard of data entry group of GSD lems to other complex diseases with exceptional genetic heterogeneity and clinical variety (5). Notably, the same The Nosology Group of the International Skeletal skeletal dysplasia gene can lead to substantially different Dysplasia Society formulated the table of NCGSD-2015 in clinical phenotypes or a specific skeletal phenotype can be September, 2015. The criteria used for genetic skeletal dis- caused by mutations in different genes (6). Therefore, orders were unchanged from NCGSD-2010 revision. They understanding genotype–phenotype correlations and func- were (1) significant skeletal involvement, including skeletal tional diversity remains one of the major challenges for dysplasias, skeletal dysostoses, metabolic bone disorders GSD. and skeletal malformation and/or reduction; (2) publica- The NCGSD-2015 provides an overview of the recog- tion and/or listing in OMIM; (3) genetic basis proven by nized diagnostic entities of GSD by clinical, anatomical site pedigree or very likely based on homogeneity of phenotype and molecular pathogenesis for clinicians, scientists and the in unrelated families; (4) nosologic autonomy confirmed radiology community to diagnose individual cases and by molecular or linkage analysis and/or by the presence of describe novel disorders (5). However, the increasing avail- distinctive diagnostic features and of observation in mul- ability of next-generation sequencing technology and other tiple individuals or families (4). In accordance with the new sequencing platforms will likely result in a rapid identi- standards of NCGSD-2015, 481 different conditions were fication of novel GSD-related genes and mutations, and placed in 42 groups, associated with one or more of 357 novel phenotypes associated with mutations in genes linked different genes. The grouping results and criteria are pre- to other phenotypes has increased dramatically to date (7, sented in Supplementary Table S1. 8). Therefore, the catalog of GSD-related genotype-pheno- type has become so large as to surpass the scope of a ‘Nosology’, so the Nosology must be transformed into an Data collection and content automated annotation and query database. Thus, it is crucial Based on the standards of NCGSD-2015, we performed to integrate the existing data and present an organized com- comprehensive searches for GSD-related publications and prehensive mutation repository to construct an integrative, databases to obtain a complete list of mutation informa- informative and updatable resource for GSD-related genetic tion associated with GSD. Firstly, we retrospectively pre-dispositions which could greatly facilitate the counsel- queried the PubMed database (http://www.ncbi.nih.gov/ ing, diagnosis and therapy for pediatrics and genetics. pubmed) for genes and diseases retrieved in Entrez with In this study, we reviewed three dependent databases terms ‘gene or disease symbol [Title/Abstract] AND muta- and public resources related to genetic skeletal disorders tion [Title/Abstract] OR variant [Title/Abstract]. Secondly, and made the first annotated database about GSD, named other databases were taken as supplementary sources, ‘SkeletonGenetics’, which provides full-scale gene and including Leiden Open Variation Database 3.0 (LOVD3.0, Database, Vol. 2016, Article ID baw127 Page 3 of 8 http://www.lovd.nl/3.0/home) which contained fanconi an- Table 1 Data content and statistics of genetic data in emia relevant genes and the mutations predicted to be be- SkeletonGenetics nign or which did not segregate with phenotype were Data type Data count excluded (9), Clinvar (http://www.ncbi.nlm.nih.gov/clin var/), which contained pathogenic or likely pathogenic Mutation 8225 clinical mutation information. Human Phenotype SNVs 5884 Ontology (HPO, http://human-phenotype-ontology. Deletions 1427 github.io/) (10) and Online Mendelian Inheritance in Man Insertions 516 Block substitution 398 (OMIM) (11) were used to describe phenotypic informa- Genes 357 tion. Patient clinical data have been obtained in accordance Disease group 42 with the tenets of the Declaration of Helsinki. Disease or syndrome 481 Finally, >2000 publications were queried from open re- Phenotypes 2260 source beginning in 1990. After manually screening the ab- GOs 2535 stracts and full-text of these publications, we excluded
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