Premium
LOVD–DASH: A comprehensive LOVD database coupled with diagnosis and an at‐risk assessment system for hemoglobinopathies
Author(s) -
Zhang Li,
Zhang Qianqian,
Tang Yaohua,
Cong Peikuan,
Ye Yuhua,
Chen Shiping,
Zhang Xinhua,
Chen Yan,
Zhu Baosheng,
Cai Wangwei,
Chen Shaoke,
Cai Ren,
Guo Xiaoling,
Zhang Chonglin,
Zhou Yuqiu,
Zou Jie,
Liu Yanhui,
Chen Biyan,
Yan Shanhuo,
Chen Yajun,
Zhou Yuehong,
Ding Hongmei,
Li Xiarong,
Chen Dianyu,
Zhong Jianmei,
Shang Xuan,
Liu Xuanzhu,
Qi Ming,
Xu Xiangmin
Publication year - 2019
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.23863
Subject(s) - dash , biology , genotyping , genetics , genotype phenotype distinction , population , computational biology , genotype , bioinformatics , database , medicine , gene , computer science , environmental health , operating system
Hemoglobinopathies are the most common monogenic disorders worldwide. Substantial effort has been made to establish databases to record complete mutation spectra causing or modifying this group of diseases. We present a variant database which couples an online auxiliary diagnosis and at‐risk assessment system for hemoglobinopathies (DASH). The database was integrated into the Leiden Open Variation Database (LOVD), in which we included all reported variants focusing on a Chinese population by literature peer review‐curation and existing databases, such as HbVar and IthaGenes. In addition, comprehensive mutation data generated by high‐throughput sequencing of 2,087 hemoglobinopathy patients and 20,222 general individuals from southern China were also incorporated into the database. These sequencing data enabled us to observe disease‐causing and modifier variants responsible for hemoglobinopathies in bulk. Currently, 371 unique variants have been recorded; 265 of 371 were described as disease‐causing variants, whereas 106 were defined as modifier variants, including 34 functional variants identified by a quantitative trait association study of this high‐throughput sequencing data. Due to the availability of a comprehensive phenotype‐genotype data set, DASH has been established to automatically provide accurate suggestions on diagnosis and genetic counseling of hemoglobinopathies. LOVD‐DASH will inspire us to deal with clinical genotyping and molecular screening for other Mendelian disorders.