Background: Wheat (Triticumssp.) is an important food source for humans in many regions around the world. However, the ability to understand and modify gene function for crop improvement is hindered by the lack of available genomic resources. TILLING is a powerful reverse genetics approach that combines chemical mutagenesis with a high-throughput screen for mutations. Wheat is specially well-suited for TILLING due to the high mutation densities tolerated by polyploids, which allow for very efficient screens. Despite this, few TILLING populations are currently available. In addition, current TILLING screening protocols require high-throughput genotyping platforms, limiting their use.Results: We developed mutant populations of pasta and common wheat and organized them for TILLING. To simplify and decrease costs, we developed a non-denaturing polyacrylamide gel set-up that uses ethidium bromide to detect fragments generated by crude celery juice extract digestion of heteroduplexes. This detection method had similar sensitivity as traditional LI-COR screens, suggesting that it represents a valid alternative. We developed genome-specific primers to circumvent the presence of multiple homoeologous copies of our target genes. Each mutant library was characterized by TILLING multiple genes, revealing high mutation densities in both the hexaploid (~1/38 kb) and tetraploid (~1/51 kb) populations for 50% GC targets. These mutation frequencies predict that screening 1,536 lines for an effective target region of 1.3 kb with 50% GC content will result in ~52 hexaploid and ~39 tetraploid mutant alleles. This implies a high probability of obtaining knock-out alleles (P= 0.91 for hexaploid,P= 0.84 for tetraploid), in addition to multiple missense mutations. In total, we identified over 275 novel alleles in eleven targeted gene/genome combinations in hexaploid and tetraploid wheat and have validated the presence of a subset of them in our seed stock.Conclusion: We have generated reverse genetics TILLING resources for pasta and bread wheat and achieved a high mutation density in both populations. We also developed a modified screening method that will lower barriers to adopt this promising technology. We hope that the use of this reverse genetics resource will enable more researchers to pursue wheat functional genomics and provide novel allelic diversity for wheat improvement.

A durum wheat consensus linkage map was developed by combining segregation data from six mapping populations. All of the crosses were derived from durum wheat cultivars, except for one accession of T. ssp. dicoccoides. The consensus map was composed of 1,898 loci arranged into 27 linkage groups covering all 14 chromosomes. The length of the integrated map and the average marker distance were 3,058.6 and 1.6 cM, respectively. The order of the loci was generally in agreement with respect to the individual maps and with previously published maps. When the consensus map was aligned to the deletion bin map, 493 markers were assigned to specific bins. Segregation distortion was found across many durum wheat chromosomes, with a higher frequency for the B genome. This high-density consensus map allowed the scanning of the genome for chromosomal rearrangements occurring during the wheat evolution. Translocations and inversions that were already known in literature were confirmed, and new putative rearrangements are proposed. The consensus map herein described provides a more complete coverage of the durum wheat genome compared with previously developed maps. It also represents a step forward in durum wheat genomics and an essential tool for further research and studies on evolution of the wheat genome.

Starch is the largest component of the wheat (Triticum aestivum L.) grain and consists of approximately 70-80% amylopectin and 20-30% amylose. Amylopectin is a highly-branched, readily digested polysaccharide, whereas amylose has few branches and forms complexes that resist digestion and mimic dietary fiber (resistant starch). Down-regulation of the starch branching enzyme II (SBEII) gene by RNA interference (RNAi) was previously shown to increase amylose content in both hexaploid and tetraploid wheat. We generated ethyl methane sulphonate (EMS) mutants for the SBEIIa-A and SBEIIa-B homoeologs in the tetraploid durum wheat variety Kronos (T. turgidum ssp. durum L.). Single-gene mutants showed non-significant increases in amylose and resistant starch content, but a double mutant combining a SBEIIa-A knock-out mutation with a SBEIIa-B splice-site mutation showed a 22% increase in amylose content (P<0.0001) and a 115% increase in resistant starch content (P<0.0001). In addition, we obtained mutants for the A and B genome copies of the paralogous SBEIIb gene, mapped them 1-2 cM from SBEIIa, and generated double SBEIIa-SBEIIb mutants to study the effect of the SBEIIb gene in the absence of SBEIIa. These mutants are available to those interested in increasing amylose content and resistant starch in durum wheat.

High-density genetic linkage maps of crop species are particularly useful in detecting qualitative and quantitative trait loci for important agronomic traits and in improving the power of classical approaches to identify candidate genes. The aim of this study was to develop a high-density genetic linkage map in a durum wheat recombinant inbred lines population (RIL) derived from two elite wheat cultivars and to identify, characterize and correlate Quantitative Trait Loci (QTL) for β-glucan, protein content, grain yield per spike and heading time. A dense map constructed by genotyping the RIL population with the wheat 90K iSelect array included 5444 single nucleotide polymorphism (SNP) markers distributed in 36 linkage groups. Data for β-glucan and protein content, grain yield per spike and heading time were obtained from replicated trials conducted at two locations in southern Italy. A total of 19 QTL were detected in different chromosome regions. In particular, three QTL for β-glucan content were detected on chromosomes 2A and 2B (two loci); eight QTL controlling grain protein content were detected on chromosomes 1B, 2B, 3B (two loci), 4A, 5A, 7A and 7B; seven QTL for grain yield per spike were identified on chromosomes 1A, 2B, 3A (two loci), 3B (two loci) and 6B; and one marker-trait association was detected on chromosome 2A for heading time. The last was co-located with a β-glucan QTL, and the two QTL appeared to be negatively correlated. A genome scan for genomic regions controlling the traits and SNP annotated sequences identified five putative candidate genes involved in different biosynthesis pathways (β-glucosidase, GLU1a; APETALA2, TaAP2; gigantea 3, TaGI3; 14-3-3 protein, Ta14A; and photoperiod sensitivity, Ppd-A1). This study provides additional information on QTL for important agronomic traits that could be useful for marker-assisted breeding to obtain new genotypes with commercial and nutritional relevance.