Reliable Radiation Hybrid Maps: An Efficient Scalable Clustering-Based Approach.

The process of mapping markers from radiation hybrid mapping (RHM) experiments is equivalent to the traveling salesman problem and, thereby, has combinatorial complexity. As an additional problem, experiments typically result in some unreliable markers that reduce the overall quality of the map. We propose a clustering approach for addressing both problems efficiently by eliminating unreliable markers without the need for mapping the complete set of markers. Traditional approaches for eliminating markers use resampling of the full data set, which has an even higher computational complexity than the original mapping problem. In contrast, the proposed approach uses a divide-and-conquer strategy to construct framework maps based on clusters that exclude unreliable markers. Clusters are ordered using parallel processing and are then combined to form the complete map. We present three algorithms that explore the trade-off between the number of markers included in the map and placement accuracy. Using an RHM data set of the human genome, we compare the framework maps from our proposed approaches with published physical maps and with the results of using the Carthagene tool. Overall, our approaches have a very low computational complexity and produce solid framework maps with good chromosome coverage and high agreement with the physical map marker order.

A radiation hybrid map of chromosome 1D reveals synteny conservation at a wheat speciation locus.

The species cytoplasm specific (scs) genes affect nuclear-cytoplasmic interactions in interspecific hybrids. A radiation hybrid (RH) mapping population of 188 individuals was employed to refine the location of the scs (ae) locus on Triticum aestivum chromosome 1D. "Wheat Zapper," a comparative genomics tool, was used to predict synteny between wheat chromosome 1D, Oryza sativa, Brachypodium distachyon, and Sorghum bicolor. A total of 57 markers were developed based on synteny or literature and genotyped to produce a RH map spanning 205.2 cR. A test-cross methodology was devised for phenotyping of RH progenies, and through forward genetic, the scs (ae) locus was pinpointed to a 1.1 Mb-segment containing eight genes. Further, the high resolution provided by RH mapping, combined with chromosome-wise synteny analysis, located the ancestral point of fusion between the telomeric and centromeric repeats of two paleochromosomes that originated chromosome 1D. Also, it indicated that the centromere of this chromosome is likely the result of a neocentromerization event, rather than the conservation of an ancestral centromere as previously believed. Interestingly, location of scs locus in the vicinity of paleofusion is not associated with the expected disruption of synteny, but rather with a good degree of conservation across grass species. Indeed, these observations advocate the evolutionary importance of this locus as suggested by "Maan's scs hypothesis."

Wheat Zapper: a flexible online tool for colinearity studies in grass genomes.

In the course of evolution, the genomes of grasses have maintained an observable degree of gene order conservation. The information available for already sequenced genomes can be used to predict the gene order of nonsequenced species by means of comparative colinearity studies. The "Wheat Zapper" application presented here performs on-demand colinearity analysis between wheat, rice, Sorghum, and Brachypodium in a simple, time efficient, and flexible manner. This application was specifically designed to provide plant scientists with a set of tools, comprising not only synteny inference, but also automated primer design, intron/exon boundaries prediction, visual representation using the graphic tool Circos 0.53, and the possibility of downloading FASTA sequences for downstream applications. Quality of the "Wheat Zapper" prediction was confirmed against the genome of maize, with good correlation (r > 0.83) observed between the gene order predicted on the basis of synteny and their actual position on the genome. Further, the accuracy of "Wheat Zapper" was calculated at 0.65 considering the "Genome Zipper" application as the "gold" standard. The differences between these two tools are amply discussed, making the point that "Wheat Zapper" is an accurate and reliable on-demand tool that is sure to benefit the cereal scientific community. The Wheat Zapper is available at http://wge.ndsu.nodak.edu/wheatzapper/ .