Development of an integrated genome informatics, data management and workflow infrastructure: A toolbox for the study of complex disease genetics

Abstract

The genetic dissection of complex disease remains a significant challenge. Sample-tracking and the recording, processing and storage of high-throughput laboratory data with public domain data, require integration of databases, genome informatics and genetic analyses in an easily updated and scaleable format. To find genes involved in multifactorial diseases such as type 1 diabetes (T1D), chromosome regions are defined based on functional candidate gene content, linkage information from humans and animal model mapping information. For each region, genomic information is extracted from Ensembl, converted and loaded into ACeDB for manual gene annotation. Homology information is examined using ACeDB tools and the gene structure verified. Manually curated genes are extracted from ACeDB and read into the feature database, which holds relevant local genomic feature data and an audit trail of laboratory investigations. Public domain information, manually curated genes, polymorphisms, primers, linkage and association analyses, with links to our genotyping database, are shown in Gbrowse. This system scales to include genetic, statistical, quality control (QC) and biological data such as expression analyses of RNA or protein, all linked from a genomics integrative display. Our system is applicable to any genetic study of complex disease, of either large or small scale.

T1DBase: integration and presentation of complex data for type 1 diabetes research

“…T1DBase () (1,2) is a public website and database that supports researchers working on the molecular genetics and biology of type 1 diabetes (T1D) susceptibility and pathogenesis. The system collates and organizes data relevant to T1D research from public and private sources, and integrates this information in a research-accessible manner, presenting the results in a form that is useful and enabling for T1D researchers.…”

Construction and analysis of tag single nucleotide polymorphism maps for six human-mouse orthologous candidate genes in type 1 diabetes

“…Annotation of NRAMP1 (European Molecular Biology Laboratory [EMBL] accession numbers D50402, D50403, BC041787, L32185, BC033754), FRAP1 (UO88966), 4-1BB (UO3387), CD101 (Z33642), B2M (BC032589) and VAV3 (AF118887, VAV3 ; AF118886, VAV3β ; AF118887, VAV3.1 ) was performed by importing Ensembl information into a temporary ACeDB database as described in Burren et al [33]. After confirmation of gene structures by BLAST analysis, these were re-extracted in GFF format and submitted to a local Gbrowse database (National Center for Biotechnology Information build 34) (DIL annotations viewable at T1DBase [34].…”

Investigating the utility of combining Φ29 whole genome amplification and highly multiplexed single nucleotide polymorphism BeadArray™ genotyping

“…We separated phenotypic and pedigree information, which is associated with a sample, from genotype data, which is associated with a DNA plate and well position, with a link table to relate the two. Sample aliases are also supported, so that no recoding of identifiers is required, either to export or import Illumina data [19]. …”