Integration of multiple genomic maps provides a higher density of markers and greater genome coverage, which not only facilitates the identification and positioning of QTLs and candidate genes, but it also provides a basic structure for the genome sequence assembly. However, the diversity in markers and populations used in individual mapping studies limits the ability to fully integrate the available data. By concentrating on marker orders rather than marker distances, published map data could be used to produce a comprehensive reference map (CRM) that includes a majority of known markers with optimally estimated order of those markers across the genome. In this study, a tetraploid cotton genome-wide CRM was constructed from 28 public cotton genetic maps. The initial CRM contained 7,424 markers and represented over 93% of the combined mapping information from the 28 individual maps. The current output is stored and displayed through CottonDB (http://www.cottondb.org), the public cotton genome database.
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