BDdb: a comprehensive platform for exploration and utilization of birth defect multi-omics data

Abstract

Birth defect, not only poses a major challenge for infant health but also attracts the attention of countless people in the world. Chromosome abnormality directly results in diverse birth defects which are generally deleterious and even lethal. Therefore, gaining molecular regulatory insights into these diseases is important and necessary for effective prenatal screening. Recently, with the advance of next-generation sequencing (NGS) techniques, a myriad of treatises and data associated with these diseases are now constantly produced from different laboratories across the world. To meet the increasing requirements for birth-related data resources, we developed a birth defect multi-omics database (BDdb), freely accessible at http://t21omics.cngb.org and consisting of multi-omics data, circulating free DNA (cfDNA) data, as well as diseases biomarkers. Omics data sets from 138 GSE samples, 5271 GSM samples and 328 entries, and more than 2000 biomarkers of 22 birth-defect diseases in 5 different species were integrated into BDdb, which provides a user-friendly interface for searching, browsing and downloading selected data. Additionally, we re-analyzed and normalized the raw data so that users can also customize the analysis using the data generated from different sources or different High-Throughput Sequencing (HTS) methods. To our knowledge, BDdb is the first comprehensive database associated with birth-defect-related diseases. which would benefit the diagnosis and prevention of birth defects.

Identification of risk variants related to malignant tumors in children with birth defects by whole genome sequencing

“…Variants in coding regions were mapped to 611 genes, variants in non-coding regions were mapped to 1,829 genes/non-coding RNAs, and variants in intergenic regions were mapped to 1,719 genes/ non-coding RNAs after filtering by machine learning models (Supplementary Table 2). The identified genes/ non-coding RNAs were further analyzed using multiple functional enrichment algorithms including Gene Ontology (GO) (9), Kyoto Encyclopedia of Genes and Genomes (KEGG) (10), Wiki Pathways (11), Gene-Disease Associations Dataset (GAD) [8], and BDdb: a comprehensive platform for exploration and utilization of birth defect multi-omics data [9]. Multiple molecular function categories were identified with significantly statistical p values based on genes/noncoding RNAs corresponding to genomic variants in non-coding areas such as intronic, untranslated region (UTR), non-coding RNAs, and intergenic regions.…”