Develepment And Application Of RGA Markers In Wheat

Compared with conserved exons, introns show more variable. Therefore, development of markers based on intron length polymorphism (ILP) is feasible for resistance gene analogues (RGAs). So that, this new kind of marker, RGA-ILP not only demonstrate more polymorphic than those designed from conserved exons but also show potential resistance gene function in bread wheat. According to known domains of resistance genes, more than 900 wheat RGAs (TC, TA or singleton ESTs) were mined from TIGA databases. 278 intron-containing RGAs candidates were predicted based on rice genomic DNA information. 50 of them were selected for valuation and mapping. A total of 150 RGA-ILP primer pairs were designed which were exon-primed intron-crossing primers to amplify the intronic regions of RGAs.135 pairs amplified successfully with similar or larger than expected product length. Three mapping populations (SOpop, NYpop, and WSpop) were used and 28 pairs of polymorphic ILP primers demonstrated reproducible amplification among the mapping parents. Respectively, 17, 14 and 17 polymorphic loci were amplified from SOpop, NYpop and WSpop. Sixteen loci were integrated into SOpop maps and all the 14 integrated into NYpop maps. However, no locus was mapped onto WSpop genetic map. The present results suggested the efficiency of this approach to develop higher polymorphic makers from intronic regions based on collinearity between grass species, which will be helpful for mapping and cloning disease resistance genes in the future.Although SNPs/Indels are invaluable tools for genetics and breeding, their application is limited by the allopolyploid feature of wheat. The goal of this study was to identify candidate genome-specific SNPs and Indels from expressed sequence tags (ESTs). Three filtering steps were carried out including each variation of a SNP supported by at least 5 ESTs, a haplotype defined by minimum four co-segregating SNPs/Indels spanning more than 8 bases, and SNPs/Indels within a haplotype occurring in diploid and tetra-/hexaploid ESTs. A total of 1 006 017 ESTs were used and 3742 candidate genome-specific haplotypes were discovered which contained 35 215 SNPs and Indels. The frequency of mutations was one per 105bp (1:105) on average with one SNP every 175bp (1:175) and one Indel per 375bp (1:375) respectively. Transition was predominant over transversion (transition/transversion ratio >1) with C<->T the most frequent. No distinct correlation was found in indels between the variation in length and distribution though 1-base indel is preferred. Furthermore, 73% of SNPs occured on the third nucleotide position of genetic code and 62% substitutions were synonymous. More than 50% SNPs/Indels selected randomly were validated. We also found that the frequency of SNPs/Indels did not increase with the increasing of EST numbers in one group. The findings will enrich the marker resources of wheat, give thoroughly up-to-date characteristics of nucleotide variation throughout ESTs, and improve the application of SNPs/Indels in wheat breeding.By sequencing RGAs in 96 wheat lines directly, a total of 46 SNPs and 2 Indels were discovered from approximately 10559bp. The frequency of RGA-SNPs and Indels was one SNP per 240bp and one Indel per 5280bp, respectively. Transition was more aboundant than transversion with a ratio of 1.5 to 1. In the 2 Indels, one showed AT-bases insertion pattern and the other C-base deletions. Based on the RGA-SNP data, gene diversity was calculated for the three groups including wild, landrace and bred varieties. Both He and Fst value confirmed that there existed no significant difference between groups. The results could be explained partly by the biased wheat lines used, but also indicated the similar selection pressure put on the three groups for resistance gene analogs. Genotype and phenotype association analysis detected two SNP mutations P64-232 and P16-469 associated with wheat resistant to yellow rust and powdery mildew, respectively. Comparing the genetic map with physical map, we found there were two R genes Yr24 and Yr9 in the region of P64-232 (C-1BL6-0.32), and Pm1 in the region of P16-469 (7AL18-0.90-1.00).