Background: An organism can be described by its observable features (phenotypes) and the genes and genomic information (genotypes) that cause these phenotypes. For many decades, researchers have tried to find relationships between genotypes and phenotypes, and great strides have been made. However, improved methods and tools for discovering and visualizing these phenotypic relationships are still needed. The maize genetics and genomics database (MaizeGDB, www.maizegdb.org) provides an array of useful resources for diverse data types including thousands of images related to mutant phenotypes in Zea mays ssp. mays (maize). To integrate mutant phenotype images with genomics information, we implemented and enhanced the web-based software package BioDIG (Biological Database of Images and Genomes). Findings: We developed a genotype-phenotype database for maize called MaizeDIG. MaizeDIG has several enhancements over the original BioDIG package. MaizeDIG, which supports multiple reference genome assemblies, is seamlessly integrated with genome browsers to accommodate custom tracks showing tagged mutant phenotypes images in their genomic context and allows for custom tagging of images to highlight the phenotype. This is accomplished through an updated interface allowing users to create image-to-gene links and is accessible via the image search tool. Conclusions: We have created a user-friendly and extensible web-based resource called MaizeDIG. MaizeDIG is preloaded with 2,396 images that are available on genome browsers for 10 different maize reference genomes. Approximately 90 images of classically defined maize genes have been manually annotated. MaizeDIG is available at http://maizedig.maizegdb.org/. The code is free and open source and can be found at https://github.com/Maize-Genetics-and-Genomics-Database/maizedig.
Keywords: BioDIG; MaizeDIG; MaizeGDB; QTL; gene model; genes; phenotype.
MaizeGDB 2018: the maize multi-genome genetics and genomics database.Nucleic Acids Res. 2019 Jan 8;47(D1):D1146-D1154. doi: 10.1093/nar/gky1046. Nucleic Acids Res. 2019. PMID: 30407532 Free PMC article.
MaizeGDB update: new tools, data and interface for the maize model organism database.Nucleic Acids Res. 2016 Jan 4;44(D1):D1195-201. doi: 10.1093/nar/gkv1007. Epub 2015 Oct 1. Nucleic Acids Res. 2016. PMID: 26432828 Free PMC article.
MaizeGDB, the community database for maize genetics and genomics.Nucleic Acids Res. 2004 Jan 1;32(Database issue):D393-7. doi: 10.1093/nar/gkh011. Nucleic Acids Res. 2004. PMID: 14681441 Free PMC article.
Mitochondrial Disease Sequence Data Resource (MSeqDR): a global grass-roots consortium to facilitate deposition, curation, annotation, and integrated analysis of genomic data for the mitochondrial disease clinical and research communities.Mol Genet Metab. 2015 Mar;114(3):388-96. doi: 10.1016/j.ymgme.2014.11.016. Epub 2014 Dec 4. Mol Genet Metab. 2015. PMID: 25542617 Free PMC article. Review.
Progress in maize gene discovery: a project update.Funct Integr Genomics. 2003 Mar;3(1-2):25-32. doi: 10.1007/s10142-002-0078-y. Epub 2002 Oct 1. Funct Integr Genomics. 2003. PMID: 12590340 Review.
Cited by 1 article
Genome-wide association analysis for maize stem Cell Wall-bound Hydroxycinnamates.BMC Plant Biol. 2019 Nov 27;19(1):519. doi: 10.1186/s12870-019-2135-x. BMC Plant Biol. 2019. PMID: 31775632 Free PMC article.