Comparative sequence analysis of the potato cyst nematode resistance locus H1 reveals a major lack of co-linearity between three haplotypes in potato (Solanum tuberosum ssp.)

The H1 locus confers resistance to the potato cyst nematode Globodera rostochiensis pathotypes 1 and 4. It is positioned at the distal end of chromosome V of the diploid Solanum tuberosum genotype SH83-92-488 (SH) on an introgression segment derived from S. tuberosum ssp. andigena. Markers from a high-resolution genetic map of the H1 locus (Bakker et al. in Theor Appl Genet 109:146–152, 2004) were used to screen a BAC library to construct a physical map covering a 341-kb region of the resistant haplotype coming from SH. For comparison, physical maps were also generated of the two haplotypes from the diploid susceptible genotype RH89-039-16 (S. tuberosum ssp. tuberosum/S. phureja), spanning syntenic regions of 700 and 319 kb. Gene predictions on the genomic segments resulted in the identification of a large cluster consisting of variable numbers of the CC-NB-LRR type of R genes for each haplotype. Furthermore, the regions were interspersed with numerous transposable elements and genes coding for an extensin-like protein and an amino acid transporter. Comparative analysis revealed a major lack of gene order conservation in the sequences of the three closely related haplotypes. Our data provide insight in the evolutionary mechanisms shaping the H1 locus and will facilitate the map-based cloning of the H1 resistance gene

Sequence‐based SNP genotyping in durum wheat

Summary: Marker development for marker-assisted selection in plant breeding is increasingly based on next-generation sequencing (NGS). However, marker development in crops with highly repetitive, complex genomes is still challenging. Here we applied sequence-based genotyping (SBG), which couples AFLP®-based complexity reduction to NGS, for de novo single nucleotide polymorphisms (SNP) marker discovery in and genotyping of a biparental durum wheat population. We identified 9983 putative SNPs in 6372 contigs between the two parents and used these SNPs for genotyping 91 recombinant inbred lines (RILs). Excluding redundant information from multiple SNPs per contig, 2606 (41%) markers were used for integration in a pre-existing framework map, resulting in the integration of 2365 markers over 2607 cM. Of the 2606 markers available for mapping, 91% were integrated in the pre-existing map, containing 708 SSRs, DArT markers, and SNPs from CRoPS technology, with a map-size increase of 492 cM (23%). These results demonstrate the high quality of the discovered SNP markers. With this methodology, it was possible to saturate the map at a final marker density of 0.8 cM/marker. Looking at the binned marker distribution (Figure 2), 63 of the 268 10-cM bins contained only SBG markers, showing that these markers are filling in gaps in the framework map. As to the markers that could not be used for mapping, the main reason was the low sequencing coverage used for genotyping. We conclude that SBG is a valuable tool for efficient, high-throughput and high-quality marker discovery and genotyping for complex genomes such as that of durum wheat

Whole Genome Profiling provides a robust framework for physical mapping and sequencing in the highly complex and repetitive wheat genome

<p>Abstract</p> <p>Background</p> <p>Sequencing projects using a clone-by-clone approach require the availability of a robust physical map. The SNaPshot technology, based on pair-wise comparisons of restriction fragments sizes, has been used recently to build the first physical map of a wheat chromosome and to complete the maize physical map. However, restriction fragments sizes shared randomly between two non-overlapping BACs often lead to chimerical contigs and mis-assembled BACs in such large and repetitive genomes. Whole Genome Profiling (WGP™) was developed recently as a new sequence-based physical mapping technology and has the potential to limit this problem.</p> <p>Results</p> <p>A subset of the wheat 3B chromosome BAC library covering 230 Mb was used to establish a WGP physical map and to compare it to a map obtained with the SNaPshot technology. We first adapted the WGP-based assembly methodology to cope with the complexity of the wheat genome. Then, the results showed that the WGP map covers the same length than the SNaPshot map but with 30% less contigs and, more importantly with 3.5 times less mis-assembled BACs. Finally, we evaluated the benefit of integrating WGP tags in different sequence assemblies obtained after Roche/454 sequencing of BAC pools. We showed that while WGP tag integration improves assemblies performed with unpaired reads and with paired-end reads at low coverage, it does not significantly improve sequence assemblies performed at high coverage (25x) with paired-end reads.</p> <p>Conclusions</p> <p>Our results demonstrate that, with a suitable assembly methodology, WGP builds more robust physical maps than the SNaPshot technology in wheat and that WGP can be adapted to any genome. Moreover, WGP tag integration in sequence assemblies improves low quality assembly. However, to achieve a high quality draft sequence assembly, a sequencing depth of 25x paired-end reads is required, at which point WGP tag integration does not provide additional scaffolding value. Finally, we suggest that WGP tags can support the efficient sequencing of BAC pools by enabling reliable assignment of sequence scaffolds to their BAC of origin, a feature that is of great interest when using BAC pooling strategies to reduce the cost of sequencing large genomes.</p

High resolution mapping of a novel late blight resistance gene Rpi-avll, from the wild Bolivian species Solanum avilesii

Both Mexico and South America are rich in Solanum species that might be valuable sources of resistance (R) genes to late blight (Phytophthora infestans). Here, we focus on an R gene present in the diploid Bolivian species S. avilesii. The genotype carrying the R gene was resistant to eight out of 10 Phytophthora isolates of various provenances. The identification of a resistant phenotype and the generation of a segregating population allowed the mapping of a single dominant R gene, Rpi-avl1, which is located in an R gene cluster on chromosome 11. This R gene cluster is considered as an R gene “hot spot”, containing R genes to at least five different pathogens. High resolution mapping of the Rpi-avl1 gene revealed a marker co-segregating in 3890 F1 individuals, which may be used for marker assisted selection in breeding programs and for further cloning of Rpi-avl

Effector Genomics Accelerates Discovery and Functional Profiling of Potato Disease Resistance and Phytophthora Infestans Avirulence Genes

Potato is the world's fourth largest food crop yet it continues to endure late blight, a devastating disease caused by the Irish famine pathogen Phytophthora infestans. Breeding broad-spectrum disease resistance (R) genes into potato (Solanum tuberosum) is the best strategy for genetically managing late blight but current approaches are slow and inefficient. We used a repertoire of effector genes predicted computationally from the P. infestans genome to accelerate the identification, functional characterization, and cloning of potentially broad-spectrum R genes. An initial set of 54 effectors containing a signal peptide and a RXLR motif was profiled for activation of innate immunity (avirulence or Avr activity) on wild Solanum species and tentative Avr candidates were identified. The RXLR effector family IpiO induced hypersensitive responses (HR) in S. stoloniferum, S. papita and the more distantly related S. bulbocastanum, the source of the R gene Rpi-blb1. Genetic studies with S. stoloniferum showed cosegregation of resistance to P. infestans and response to IpiO. Transient co-expression of IpiO with Rpi-blb1 in a heterologous Nicotiana benthamiana system identified IpiO as Avr-blb1. A candidate gene approach led to the rapid cloning of S. stoloniferum Rpi-sto1 and S. papita Rpi-pta1, which are functionally equivalent to Rpi-blb1. Our findings indicate that effector genomics enables discovery and functional profiling of late blight R genes and Avr genes at an unprecedented rate and promises to accelerate the engineering of late blight resistant potato varieties