|SEETAN, RAED - North Dakota State University|
|DENTON, ANNE - North Dakota State University|
|AL-AZZAM, OMAR - University Of Minnesota|
|KUMAR, AJAY - University Of Minnesota|
|STURDIVAN, JAZARAI - Virginia State University|
Submitted to: Society for Industrial and Applied Mathematics
Publication Type: Proceedings
Publication Acceptance Date: 1/24/2014
Publication Date: 4/1/2014
Citation: Seetan, R.I., Denton, A.M., Al-Azzam, O., Kumar, A., Sturdivan, J., Kianian, S. 2014. Iterative framework radiation hybrid mapping. Society for Industrial and Applied Mathematics. Available: http://www.siam.org/meetings.sdm14.
Interpretive Summary: Genome maps show the order of markers on the chromosomes of a species and the estimated distances between markers. The genome map information is valuable in genome sequencing projects for ordering clones and contigs. Radiation Hybrid (RH) mapping is a widely used mapping technique in animal species but one that has recently been applied to plant genomes, in particular wheat, by our group. In this approach a chromosome is broken into random fragments using radiation. Then, the presence or absence of a marker is screened to generate a radiation hybrid population. Markers can be genes or any simple short fragments of DeoxyriboNucleic Acid (DNA) sequence that appear only once in the genome. Development of maps following molecular analysis by traditional mathematical methods can be computionally expensive and time consuming. In here we provide an approach that circumvents many of the issues with traditional approach and provides an accurate map quickly.
Technical Abstract: Building comprehensive radiation hybrid maps for large sets of markers is a computationally expensive process, since the basic mapping problem is equivalent to the traveling salesman problem. The mapping problem is also susceptible to noise, and as a result, it is often beneficial to remove markers that are not trustworthy. The resulting framework maps are typically more reliable but don't provide information about as many markers. We present an approach to mapping most markers by frst creating a framework map and then incrementally adding the remaining markers. We consider chromosomes of the human genome, for which the correct ordering is known, and compare the performance of our two-stage algorithm with the Carthagene radiation hybrid mapping software. We show that our approach is not only much faster than mapping the complete genome in one step, but that the quality of the resulting maps is also much higher.