The construction of comparative genome maps allows us to exploit the collective research accumulated for each of the species under consideration to gain new insights into their biology and evolution. Comparative genome maps are used for predicting the location of orthologous genes, for understanding chromosome evolution and inferring phylogenetic relationships, and for examining hypotheses about the evolution of gene families and gene function in diverse organisms. Construction of any genetic map is laborious, but compiling comparative maps across multiple species requires a large investment of manual effort on the part of biologists. Additionally, biologists from different labs tend to use differing rules which are often not quantified or made precise in the literature, making it difficult to understand how the various comparative maps relate to one another.
We have formalized the concept of a comparative map in a way that is broadly applicable to infer common ancestral linkage segments. These segments are predicted by identifying regions of homeology or synteny along the chromosomes of pairs of organisms. To achieve this goal, we offer a rigorous yet simple definition for the process of constructing comparative maps that is based on the fundamental principles of accuracy (the data should be explained well by the map) and parsimony (the number of homeologous segments should be minimized so that only syntenic relationships above our confidence threshold are labeled). From this we have developed robust, efficient algorithms that use dynamic programming techniques to construct comparative maps with an optimal balance of accuracy and parsimony.
A preliminary version of DeCAL (Detecting Common Ancestral Linkage-segments), an open source product based on these algorithms, is now available. For input, it requires the positions of the markers of one species, as well as the location of homologs to each marker in the second species. Output is given both graphically and in text form. Only a single parameter is required, which carries a simple biological explanation. Our program allows comparative maps to be constructed in a few minutes. Results have been evaluated for diverse pairs of species, and closely approximate prior manual expert analyses.
We have received a number of inquiries from biologists who wish to use DeCAL with their data. The challenge now is to expand DeCAL so it can reliably process the variety of data in common use. We have also received several inquiries from commercial software providers. We remain committed to the development of an open source product, and we also welcome collaborative opportunities to integrate our algorithm into other software packages.