CGDSNPdb: a database resource for error-checked and imputed mouse SNPs

Lucie N. Hutchins 1 Yueming Ding 1 Jin P. Szatkiewicz 1 Randy Von Smith 1 Hyuna Yang 1 Fernando Pardo-Manuel de Villena 0 1 Gary A. Churchill 1 Joel H. Graber 1 0 Department of Genetics, School of Medicine, University of North Carolina , Chapel Hill, NC 27599, USA 1 Center for Genome Dynamics, The Jackson Laboratory , 600 Main Street, Bar Harbor, ME 04609 The Center for Genome Dynamics Single Nucleotide Polymorphism Database (CGDSNPdb) is an open-source value-added database with more than nine million mouse single nucleotide polymorphisms (SNPs), drawn from multiple sources, with genotypes assigned to multiple inbred strains of laboratory mice. All SNPs are checked for accuracy and annotated for properties specific to the SNP as well as those implied by changes to overlapping protein-coding genes. CGDSNPdb serves as the primary interface to two unique data sets, the 'imputed genotype resource' in which a Hidden Markov Model was used to assess local haplotypes and the most probable base assignment at several million genomic loci in tens of strains of mice, and the Affymetrix Mouse Diversity Genotyping Array, a high density microarray with over 600 000 SNPs and over 900 000 invariant genomic probes. CGDSNPdb is accessible online through either a web-based query tool or a MySQL public login. Database URL: http://cgd.jax.org/cgdsnpdb/ Introduction Single nucleotide polymorphisms (SNPs) are variable single base positions within a genome that represent the simplest and possibly most common type of genetic variation. Accordingly, SNPs have emerged as a powerful tool for tracking heredity and genetic variation, and have become especially popular for phenotype genome-wide association studies (1, 2). The critical role of the laboratory mouse has led to several efforts aimed at large-scale collection and analysis of mouse SNPs (37). The Center for Genome Dynamics Single Nucleotide Polymorphism database (CGDSNPdb) was designed to bring together multiple sources of mouse SNP data, while checking them for accuracy and consistency among sources. CGDSNPdb is distinguished by the inclusion of two unique data sets: The Imputed SNP Genotype Resource (IGR) (8) generated by a Hidden Markov Model (HMM) that assigns probable genotype and associated confidence levels for over 8 million SNPs in 74 strains of mice. Data collected from over 140 strains of laboratory mice (filtered to 72 inbred strains in the current release, version 1.3) with the Mouse Diversity Genotyping Array [MusDiv; (9)], a high density microarray with probes that target 623 124 SNPs and over 900 000 invariant genomic regions targeting features such as exons and copy number variations. MusDiv SNP data will also be submitted to dbSNP following publication of an analysis manuscript (in preparation). The CGDSNPdb search engine facilitates a number of different queries, including search by chromosome region(s), nearby gene annotations, or SNP identifiers. Results can be returned as dynamic html or in flat-text commaseparated-value (CSV) format. Annotations in CGDSNPdb include characteristics of the SNP (e.g. presence in CpG dinucleotide, major/minor allele frequencies), along with functional characteristics of protein-coding genes affected by the SNP (e.g. changes in amino-acid physical and chemical characteristics, changes in codon usage, and overlapping or closest neighboring genes). All annotations were generated using an automated analysis pipeline with subsequent quality controls, described below. CGDSNPdb was constructed primarily as a resource to support the imputation and mouse diversity array projects, however, it is being made available as a somewhat reduced size, but high confidence, collection of mouse SNPs. Database updates will be driven by the availability of new or updated genome assemblies, updated releases of major external SNP data sets, new SNP data sources, and maintenance. Future growth of the database will be targeted primarily at large-scale projects such as the mouse genomes project (http://www.sanger.ac.uk/resources/mouse/ genomes/) as well as data sets that can increase the represented strain diversity. Minor releases of CGDSNPdb may also be generated for improved data visualization or underlying quality control procedures. This manuscript provides a high-level overview of the main components of CGDSNPdb, as of version 1.3 (January 2010). Implementation details The database CGDSNPdb was implemented using the open source MySQL relational database management system. The database consists of the core tables, containing all pertinent data for the SNP, including all data from the source download, and gene related tables that facilitate associations between SNPs and neighboring genes. Database schemas are available as Supplementary Figures S1 and S2. Original SNP files from sources and genome assembly files for flanking sequence data are retained and stored separately from the database. Automated load programs, written in Perl and C++ with SQL queries, integrate data sets from various external sources into the database. These data files have, in general, been obtained directly from the generating source rather than another accumulative resource, such as dbSNP at NCBI (10) or the Mouse Phenome Database (MPD) (11). The load process (Supplementary Figure S3) includes a number of quality control checks that identify problems or ambiguities with SNPs and correct them, if possible. Quality control checks include comparison of the provided SNP call in C57BL/6J with the same position within the reference genome, genomic comparison of the provided flanking sequences (typically 50-nt up and downstream, with a requirement of at least 60% sequence identity in each direction), identification and resolution of duplicate entries (as defined by chromosome and position), and comparison of genotype calls (strain and genotype) among the different data sources. Genomic coordinates provided by the SNP source were assumed to be correct, and only challenged and further tested if the checks of the SNP or flanking sequence failed. No minimum length requirements were placed on the length of the flanking sequences, but SNP correction was only possible if flanking sequences were provided with the source data. MusDiv (9) SNPs were subjected to additional quality tests intended to assist in the interpretation of the microarray hybridization patterns. The MusDiv SNPs hybridization probes are primarily 25-mers, with the SNP typically centered within the probe. Probes included both forward and reverse sense probes for both the reference C57BL6/J base and the known variant. Alignment of the flanking and probe sequences to the reference C57BL6/J genome was made using PASS (12), as it provided the best tradeoff of speed and alignment sensitivity (data not shown), especially for the analysis of near matches necessary for the mouse diversity array probes. PASS was used to align all four variants classes of probes, identifying all (...truncated)