BACKGROUND: With advances in DNA re-sequencing methods and Next-Generation parallel sequencing approaches, there has been a large increase in genomic efforts to define and analyze the sequence variability present among individuals within a species. For very polymorphic species such as maize, this has lead to a need for intuitive, user-friendly software that aids the biologist, often with naïve programming capability, in tracking, editing, displaying, and exporting multiple individual sequence alignments. To fill this need we have developed a novel DNA alignment editor. RESULTS: We have generated a nucleotide sequence alignment editor (DNAAlignEditor) that provides an intuitive, user-friendly interface for manual editing of multiple sequence alignments with functions for input, editing, and output of sequence alignments. The color-coding of nucleotide identity and the display of associated quality score aids in the manual alignment editing process. DNAAlignEditor works as a client/server tool having two main components: a relational database that collects the processed alignments and a user interface connected to database through universal data access connectivity drivers. DNAAlignEditor can be used either as a stand-alone application or as a network application with multiple users concurrently connected. CONCLUSION: We anticipate that this software will be of general interest to biologists and population genetics in editing DNA sequence alignments and analyzing natural sequence variation regardless of species, and will be particularly useful for manual alignment editing of sequences in species with high levels of polymorphism.

MOTIVATION: Because of the unique biological features, a bioinformatic platform for the integrated genetic and physical map of maize is required for storing, integrating, accessing and visualizing the underlying data. RESULTS: The goal of the Maize Mapping Project is to develop a fully integrated genetic and physical map for maize. To display this integrated map, we have developed iMap. iMap has three main components: a relational database (iMapDB), a map graphic browser (iMap Viewer) and a search utility (iMap Search). iMapDB is populated with current genetic and physical map data, describing relationships among genetic loci, molecular markers and bacterial artificial chromosome (BAC) contigs. The database also contains integrated information produced by applying a set of anchoring rules to assign BAC contigs to specific locations on the genetic map. The iMap Viewer and iMap Search functions are combined in the user interface to allow viewing and retrieving many types of genetic and physical map data. The iMap Viewer features side-by-side chromosome-based displays of the genetic map and associated BAC contigs. For each genetic locus, information about marker type or contig can be viewed via pop-up windows that feature links to external data resources. Searches can be conducted for genetic locus, probe or sequence accession number; search results include relevant map positions, anchored BAC contigs and links to the graphical display of relevant chromosomes. iMap can be accessed at http://www.maizemap.org AVAILABILITY: The iMap utility package is available for non-commercial use upon request from the authors.

Abstract Summary: cMap, a www comparative genetic map graphical utility, has a search capability and provides comparison of two genetic maps within or between species with dynamic links to data resources and text lists of the shared loci, running in a relational database environment. Currently, maps from three species (maize ‘Zea mays L.’, rice‘ Oryza sativa L.’, and sorghum ‘Sorghum bicolor L.’), representing over 13 800 distinct loci, are available for comparison at http://www.agron.missouri.edu/cMapDB/cMap.html Availability: cMap source code is available without cost on request for non-commercial use. Contact: [email protected] * To whom correspondence should be addressed. † Current address: Computer & Information Science & Engineering, University of Florida, Gainesville, FL 32611, USA

MOTIVATION: The development of an integrated genetic and physical map for the maize genome involves the generation of an enormous amount of data. Managing this data requires a system to aid in genotype scoring for different types of markers coming from both local and remote users. In addition, researchers need an efficient way to interact with genetic mapping software and with data files from automated DNA sequencing. They also need ways to manage primer data for mapping and sequencing and provide views of the integrated physical and genetic map and views of genetic map comparisons. RESULTS: The MMP-LIMS system has been used successfully in a high-throughput mapping environment. The genotypes from 957 SSR, 1023 RFLP, 189 SNP, and 177 InDel markers have been entered and verified via MMP-LIMS. The system is flexible, and can be easily modified to manage data for other species. The software is freely available. AVAILABILITY: To receive a copy of the iMap or cMap software, please fill out the form on our website. The other MMP-LIMS software is freely available at http://www.maizemap.org/bioinformatics.htm.