Abstract

BackgroundThe mapping of quantitative trait loci in rat and mouse has been extremely successful in identifying chromosomal regions associated with human disease-related phenotypes. However, identifying the specific phenotype-causing DNA sequence variations within a quantitative trait locus has been much more difficult. The recent availability of genomic sequence from several mouse inbred strains (including C57BL/6J, 129X1/SvJ, 129S1/SvImJ, A/J, and DBA/2J) has made it possible to catalog DNA sequence differences within a quantitative trait locus derived from crosses between these strains. However, even for well-defined quantitative trait loci (<10 Mb) the identification of candidate functional DNA sequence changes remains challenging due to the high density of sequence variation between strains.DescriptionTo help identify functional DNA sequence variations within quantitative trait loci we have used the Ensembl annotated genome sequence to compile a database of mouse single nucleotide polymorphisms (SNPs) that are predicted to cause missense, nonsense, frameshift, or splice site mutations (available at ). For missense mutations we have used the PolyPhen and PANTHER algorithms to predict whether amino acid changes are likely to disrupt protein function.ConclusionWe have developed a database of mouse SNPs predicted to cause missense, nonsense, frameshift, and splice-site mutations. Our analysis revealed that 20% and 14% of missense SNPs are likely to be deleterious according to PolyPhen and PANTHER, respectively, and 6% are considered deleterious by both algorithms. The database also provides gene expression and functional annotations from the Symatlas, Gene Ontology, and OMIM databases to further assess candidate phenotype-causing mutations. To demonstrate its utility, we show that Mouse SNP Miner successfully finds a previously identified candidate SNP in the taste receptor, Tas1r3, that underlies sucrose preference in the C57BL/6J strain. We also use Mouse SNP Miner to derive a list of candidate phenotype-causing mutations within a previously uncharacterized QTL for response to morphine in the 129/Sv strain.

Highlights

  • The mapping of quantitative trait loci in rat and mouse has been extremely successful in identifying chromosomal regions associated with human disease-related phenotypes

  • We have developed a database of mouse single nucleotide polymorphisms (SNPs) predicted to cause missense, nonsense, frameshift, and splice-site mutations

  • Our analysis revealed that 20% and 14% of missense SNPs are likely to be deleterious according to PolyPhen and PANTHER, respectively, and 6% are considered deleterious by both algorithms

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Summary

Conclusion

The Mouse SNP Miner database contains mouse SNPs predicted to cause missense, STOP-gain, STOP-lost, frameshift, and splice-site mutations. The database provides several annotations for each SNP, including PolyPhen and PANTHER predictions of missense mutation consequence and gene expression data from Symatlas. Our database allows convenient searching of mouse functional SNPs by strain, chromosomal location, type, predicted functional consequence, gene expression, GO and OMIM terms. The database provides an overview of the extent of functional coding sequence variation between mouse inbred strains and will help to speed the identification of candidate genetic variations that underlie mouse QTL. CG and ER conceived of the database; CG participated in its design and coordinated the work; ER designed and assembled the database and web interface and processed the PANTHER algorithm; VR carried out the PolyPhen analysis of mouse sequences; CG and ER drafted the manuscript.

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