Muhammad J. Iqbal

Physical mapping resources for large plant genomes: radiation hybrids for wheat D-genome progenitor Aegilops tauschii

BackgroundDevelopment of a high quality reference sequence is a daunting task in crops like wheat with large (~17Gb), highly repetitive (>80%) and polyploid genome. To achieve complete sequence assembly of such genomes, development of a high quality physical map is a necessary first step. However, due to the lack of recombination in certain regions of the chromosomes, genetic mapping, which uses recombination frequency to map marker loci, alone is not sufficient to develop high quality marker scaffolds for a sequence ready physical map. Radiation hybrid (RH) mapping, which uses radiation induced chromosomal breaks, has proven to be a successful approach for developing marker scaffolds for sequence assembly in animal systems. Here, the development and characterization of a RH panel for the mapping of D-genome of wheat progenitor Aegilops tauschii is reported.ResultsRadiation dosages of 350 and 450 Gy were optimized for seed irradiation of a synthetic hexaploid (AABBDD) wheat with the D-genome of Ae. tauschii accession AL8/78. The surviving plants after irradiation were crossed to durum wheat (AABB), to produce pentaploid RH1s (AABBD), which allows the simultaneous mapping of the whole D-genome. A panel of 1,510 RH1 plants was obtained, of which 592 plants were generated from the mature RH1 seeds, and 918 plants were rescued through embryo culture due to poor germination (<3%) of mature RH1 seeds. This panel showed a homogenous marker loss (2.1%) after screening with SSR markers uniformly covering all the D-genome chromosomes. Different marker systems mostly detected different lines with deletions. Using markers covering known distances, the mapping resolution of this RH panel was estimated to be <140kb. Analysis of only 16 RH lines carrying deletions on chromosome 2D resulted in a physical map with cM/cR ratio of 1:5.2 and 15 distinct bins. Additionally, with this small set of lines, almost all the tested ESTs could be mapped. A set of 399 most informative RH lines with an average deletion frequency of ~10% were identified for developing high density marker scaffolds of the D-genome.ConclusionsThe RH panel reported here is the first developed for any wild ancestor of a major cultivated plant species. The results provided insight into various aspects of RH mapping in plants, including the genetically effective cell number for wheat (for the first time) and the potential implementation of this technique in other plant species. This RH panel will be an invaluable resource for mapping gene based markers, developing a complete marker scaffold for the whole genome sequence assembly, fine mapping of markers and functional characterization of genes and gene networks present on the D-genome.

Radiation Hybrids: A valuable Tool for Genetic, Genomic and Functional Analysis of Plant Genomes

Radiation has been used as a mean to break and transfer fragments of DNA from one plant species to another. Early examples include the experiments by Sears, (Brookhaven Symp Biol 9:1–22, 1956) to transfer rust resistance genes from Aegilops umbellulata to wheat. Radiation found its niche as a mutagen due to advances in nuclear technology and formation of the International Atomic Energy Agency and their sponsorship of developing mutation breeding through “Mutation Enhanced Technologies for Agriculture”. Mutation breeding has resulted in the release of several important cultivars. Although radiation was used in plants for the mutation and introgression of genes from related species (Sears, Brookhaven Symp Biol 9:1–22, 1956; Driscoll and Jensen, Genetics 48:459–468, 1963; Riley and Law, Stadler Genet Symp 16:301–322, 1984; Sears, Crop Sci 33:897–901, 1993), this approach was not used for mapping. This aspect of radiation application was first utilized in animal cell culture lines to generate radiation hybrid (RH) panels. In the beginning these panels were generated for single chromosomes but evolved to the development of whole genome panels. This technology matured in animal systems with the onset of genomics era by its use in the development of high resolution RH-based physical maps for many species before or during the development of complete genome sequence information. The advantages of this system are: (1) radiation-induced breaks are independent of recombination events providing higher and more uniform resolution, (2) radiation dosage could be adjusted to provide varied resolution without greatly affecting the population size and (3) all markers regardless of their polymorphism can be mapped on RH panels. Plant scientists followed these studies by the development of RH panels for individual chromosomes or whole genomes. However, early RH panels in plant systems were of low to medium resolution and of limited use in physical mapping. Recently, RH panels have been produced resulting in map resolutions of 200–400 Kb. These high resolution panels promise the same value as animal systems in helping generate a complete genome sequence with a fraction of the cost of traditional methods. But the use of radiation in plants has matured to go beyond physical mapping by its application to gene cloning and forward/reverse genetic studies. These applications take advantage of plasticity offered by many plant species in tolerating radiation to produce seed and live progeny. This ability allows scientists to phenotype RH lines and to associate the phenotypic data with the genotypic data. The great potential of this system is just being realized.

Network-Based Filtering of Unreliable Markers in Genome Mapping

Genome mapping, or the experimental determination of the ordering of DNA markers on a chromosome, is an important step in genome sequencing and ultimate assembly of sequenced genomes. The presented research addresses the problem of identifying markers that cannot be placed reliably. If such markers are included in standard mapping procedures they can result in an overall poor mapping. Traditional techniques for identifying markers that cannot be placed consistently are based on resampling, which requires an already computationally expensive process to be done for a large ensemble of resampled populations. We propose a network-based approach that uses pair wise similarities between markers and demonstrate that the results from this approach largely match the more computationally expensive conventional approaches. The evaluation of the proposed approach is done on data from the radiation hybrid mapping of the wheat genome.

Frequent Substring-Based Sequence Classification with an Ensemble of Support Vector Machines Trained Using Reduced Amino Acid Alphabets

We propose a frequent pattern-based algorithm for predicting functions and localizations of proteins from their primary structure (amino acid sequence). We use reduced alphabets that capture the higher rate of substitution between amino acids that are physiochemically similar. Frequent sub strings are mined from the training sequences, transformed into different alphabets, and used as features to train an ensemble of SVMs. We evaluate the performance of our algorithm using protein sub-cellular localization and protein function datasets. Pair-wise sequence-alignment-based nearest neighbor and basic SVM k-gram classifiers are included as comparison algorithms. Results show that the frequent sub string-based SVM classifier demonstrates better performance compared with other classifiers on the sub-cellular localization datasets and it performs competitively with the nearest neighbor classifier on the protein function datasets. Our results also show that the use of reduced alphabets provides statistically significant performance improvements for half of the classes studied.

Molecular mapping and breeding with microsatellite markers.

In genetics databases for crop plant species across the world, there are thousands of mapped loci that underlie quantitative traits, oligogenic traits, and simple traits recognized by association mapping in populations. The number of loci will increase as new phenotypes are measured in more diverse genotypes and genetic maps based on saturating numbers of markers are developed. A period of locus reevaluation will decrease the number of important loci as those underlying mega-environmental effects are recognized. A second wave of reevaluation of loci will follow from developmental series analysis, especially for harvest traits like seed yield and composition. Breeding methods to properly use the accurate maps of QTL are being developed. New methods to map, fine map, and isolate the genes underlying the loci will be critical to future advances in crop biotechnology. Microsatellite markers are the most useful tool for breeders. They are codominant, abundant in all genomes, highly polymorphic so useful in many populations, and both economical and technically easy to use. The selective genotyping approaches, including genotype ranking (indexing) based on partial phenotype data combined with favorable allele data and bulked segregation event (segregant) analysis (BSA), will be increasingly important uses for microsatellites. Examples of the methods for developing and using microsatellites derived from genomic sequences are presented for monogenic, oligogenic, and polygenic traits. Examples of successful mapping, fine mapping, and gene isolation are given. When combined with high-throughput methods for genotyping and a genome sequence, the use of association mapping with microsatellite markers will provide critical advances in the analysis of crop traits.

Multiple Sources Classification of Gene Position on Chromosomes Using Statistical Significance of Individual Classification Results

In data mining applications it is common to have more than one data source available to describe the same record. For example, in biological sciences, the same genes may be characterized through many types of experiments. Which of the data sources proves to be most reliable in predictions may depend on the record in question. For some records pieces of information may be unavailable because an experiment has not yet been done, or certain type of inferences may not be applicable, such as when a gene does not have a homologue in some species. We demonstrate how multi-classifier systems can allow classification in cases where any individual source is scarce or unreliable to provide an accurate prediction model by itself. We propose a method to predict a class label using statistical significance of individual classification results. We show that the proposed approach increases the accuracy of results compared with conventional techniques in a problem related to gene mapping in wheat.