Harnessing landrace diversity empowers wheat breeding.

Harnessing genetic diversity in major staple crops through the development of new breeding capabilities is essential to ensure food security1. Here we examined the genetic and phenotypic diversity of the A. E. Watkins landrace collection2 of bread wheat (Triticum aestivum), a major global cereal, by whole-genome re-sequencing of 827 Watkins landraces and 208 modern cultivars and in-depth field evaluation spanning a decade. We found that modern cultivars are derived from two of the seven ancestral groups of wheat and maintain very long-range haplotype integrity. The remaining five groups represent untapped genetic sources, providing access to landrace-specific alleles and haplotypes for breeding. Linkage disequilibrium-based haplotypes and association genetics analyses link Watkins genomes to the thousands of identified high-resolution quantitative trait loci and significant marker-trait associations. Using these structured germplasm, genotyping and informatics resources, we revealed many Watkins-unique beneficial haplotypes that can confer superior traits in modern wheat. Furthermore, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritized quantitative trait loci in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilizing genetic diversity in crop improvement to achieve sustainable food security.

Einkorn genomics sheds light on history of the oldest domesticated wheat.

Einkorn (Triticum monococcum) was the first domesticated wheat species, and was central to the birth of agriculture and the Neolithic Revolution in the Fertile Crescent around 10,000 years ago1,2. Here we generate and analyse 5.2-Gb genome assemblies for wild and domesticated einkorn, including completely assembled centromeres. Einkorn centromeres are highly dynamic, showing evidence of ancient and recent centromere shifts caused by structural rearrangements. Whole-genome sequencing analysis of a diversity panel uncovered the population structure and evolutionary history of einkorn, revealing complex patterns of hybridizations and introgressions after the dispersal of domesticated einkorn from the Fertile Crescent. We also show that around 1% of the modern bread wheat (Triticum aestivum) A subgenome originates from einkorn. These resources and findings highlight the history of einkorn evolution and provide a basis to accelerate the genomics-assisted improvement of einkorn and bread wheat.

Multiple wheat genomes reveal global variation in modern breeding.

Advances in genomics have expedited the improvement of several agriculturally important crops but similar efforts in wheat (Triticum spp.) have been more challenging. This is largely owing to the size and complexity of the wheat genome1, and the lack of genome-assembly data for multiple wheat lines2,3. Here we generated ten chromosome pseudomolecule and five scaffold assemblies of hexaploid wheat to explore the genomic diversity among wheat lines from global breeding programs. Comparative analysis revealed extensive structural rearrangements, introgressions from wild relatives and differences in gene content resulting from complex breeding histories aimed at improving adaptation to diverse environments, grain yield and quality, and resistance to stresses4,5. We provide examples outlining the utility of these genomes, including a detailed multi-genome-derived nucleotide-binding leucine-rich repeat protein repertoire involved in disease resistance and the characterization of Sm16, a gene associated with insect resistance. These genome assemblies will provide a basis for functional gene discovery and breeding to deliver the next generation of modern wheat cultivars.

A complex receptor locus confers responsiveness to necrosis and ethylene-inducing like peptides in Brassica napus.

Brassica crops are susceptible to diseases which can be mitigated by breeding for resistance. MAMPs (microbe-associated molecular patterns) are conserved molecules of pathogens that elicit host defences known as pattern-triggered immunity (PTI). Necrosis and Ethylene-inducing peptide 1-like proteins (NLPs) are MAMPs found in a wide range of phytopathogens. We studied the response to BcNEP2, a representative NLP from Botrytis cinerea, and showed that it contributes to disease resistance in Brassica napus. To map regions conferring NLP response, we used the production of reactive oxygen species (ROS) induced during PTI across a population of diverse B. napus accessions for associative transcriptomics (AT), and bulk segregant analysis (BSA) on DNA pools created from a cross of NLP-responsive and non-responsive lines. In silico mapping with AT identified two peaks for NLP responsiveness on chromosomes A04 and C05 whereas the BSA identified one peak on A04. BSA delimited the region for NLP-responsiveness to 3 Mbp, containing ~245 genes on the Darmor-bzh reference genome and four co-segregating KASP markers were identified. The same pipeline with the ZS11 genome confirmed the highest-associated region on chromosome A04. Comparative BLAST analysis revealed unannotated clusters of receptor-like protein (RLP) homologues on ZS11 chromosome A04. However, no specific RLP homologue conferring NLP response could be identified. Our results also suggest that BR-SIGNALLING KINASE1 may be involved with modulating the NLP response. Overall, we demonstrate that responsiveness to NLP contributes to disease resistance in B. napus and define the associated genomic location. These results can have practical application in crop improvement.

Pathogen-induced biosynthetic pathways encode defense-related molecules in bread wheat.

Wheat is a widely grown food crop that suffers major yield losses due to attack by pests and pathogens. A better understanding of biotic stress responses in wheat is thus of major importance. The recently assembled bread wheat genome coupled with extensive transcriptomic resources provides unprecedented new opportunities to investigate responses to pathogen challenge. Here, we analyze gene coexpression networks to identify modules showing consistent induction in response to pathogen exposure. Within the top pathogen-induced modules, we identify multiple clusters of physically adjacent genes that correspond to six pathogen-induced biosynthetic pathways that share a common regulatory network. Functional analysis reveals that these pathways, all of which are encoded by biosynthetic gene clusters, produce various different classes of compounds­namely, flavonoids, diterpenes, and triterpenes, including the defense-related compound ellarinacin. Through comparative genomics, we also identify associations with the known rice phytoalexins momilactones, as well as with a defense-related gene cluster in the grass model plant Brachypodium distachyon. Our results significantly advance the understanding of chemical defenses in wheat and open up avenues for enhancing disease resistance in this agriculturally important crop. They also exemplify the power of transcriptional networks to discover the biosynthesis of chemical defenses in plants with large, complex genomes.

Genome sequence and genetic diversity of European ash trees.

Ash trees (genus Fraxinus, family Oleaceae) are widespread throughout the Northern Hemisphere, but are being devastated in Europe by the fungus Hymenoscyphus fraxineus, causing ash dieback, and in North America by the herbivorous beetle Agrilus planipennis. Here we sequence the genome of a low-heterozygosity Fraxinus excelsior tree from Gloucestershire, UK, annotating 38,852 protein-coding genes of which 25% appear ash specific when compared with the genomes of ten other plant species. Analyses of paralogous genes suggest a whole-genome duplication shared with olive (Olea europaea, Oleaceae). We also re-sequence 37 F. excelsior trees from Europe, finding evidence for apparent long-term decline in effective population size. Using our reference sequence, we re-analyse association transcriptomic data, yielding improved markers for reduced susceptibility to ash dieback. Surveys of these markers in British populations suggest that reduced susceptibility to ash dieback may be more widespread in Great Britain than in Denmark. We also present evidence that susceptibility of trees to H. fraxineus is associated with their iridoid glycoside levels. This rapid, integrated, multidisciplinary research response to an emerging health threat in a non-model organism opens the way for mitigation of the epidemic.

Optimizing Rhizobium-legume symbioses by simultaneous measurement of rhizobial competitiveness and N2 fixation in nodules.

Legumes tend to be nodulated by competitive rhizobia that do not maximize nitrogen (N2) fixation, resulting in suboptimal yields. Rhizobial nodulation competitiveness and effectiveness at N2 fixation are independent traits, making their measurement extremely time-consuming with low experimental throughput. To transform the experimental assessment of rhizobial competitiveness and effectiveness, we have used synthetic biology to develop reporter plasmids that allow simultaneous high-throughput measurement of N2 fixation in individual nodules using green fluorescent protein (GFP) and barcode strain identification (Plasmid ID) through next generation sequencing (NGS). In a proof-of-concept experiment using this technology in an agricultural soil, we simultaneously monitored 84 different Rhizobium leguminosarum strains, identifying a supercompetitive and highly effective rhizobial symbiont for peas. We also observed a remarkable frequency of nodule coinfection by rhizobia, with mixed occupancy identified in ∼20% of nodules, containing up to six different strains. Critically, this process can be adapted to multiple Rhizobium-legume symbioses, soil types, and environmental conditions to permit easy identification of optimal rhizobial inoculants for field testing to maximize agricultural yield.

Rust expression browser: an open source database for simultaneous analysis of host and pathogen gene expression profiles with expVIP.

BACKGROUND: Transcriptomics is being increasingly applied to generate new insight into the interactions between plants and their pathogens. For the wheat yellow (stripe) rust pathogen (Puccinia striiformis f. sp. tritici, Pst) RNA-based sequencing (RNA-Seq) has proved particularly valuable, overcoming the barriers associated with its obligate biotrophic nature. This includes the application of RNA-Seq approaches to study Pst and wheat gene expression dynamics over time and the Pst population composition through the use of a novel RNA-Seq based surveillance approach called "field pathogenomics". As a dual RNA-Seq approach, the field pathogenomics technique also provides gene expression data from the host, giving new insight into host responses. However, this has created a wealth of data for interrogation. RESULTS: Here, we used the field pathogenomics approach to generate 538 new RNA-Seq datasets from Pst-infected field wheat samples, doubling the amount of transcriptomics data available for this important pathosystem. We then analysed these datasets alongside 66 RNA-Seq datasets from four Pst infection time-courses and 420 Pst-infected plant field and laboratory samples that were publicly available. A database of gene expression values for Pst and wheat was generated for each of these 1024 RNA-Seq datasets and incorporated into the development of the rust expression browser ( http://www.rust-expression.com ). This enables for the first time simultaneous 'point-and-click' access to gene expression profiles for Pst and its wheat host and represents the largest database of processed RNA-Seq datasets available for any of the three Puccinia wheat rust pathogens. We also demonstrated the utility of the browser through investigation of expression of putative Pst virulence genes over time and examined the host plants response to Pst infection. CONCLUSIONS: The rust expression browser offers immense value to the wider community, facilitating data sharing and transparency and the underlying database can be continually expanded as more datasets become publicly available.

The NLR-Annotator Tool Enables Annotation of the Intracellular Immune Receptor Repertoire.

Disease resistance genes encoding nucleotide-binding and leucine-rich repeat (NLR) intracellular immune receptor proteins detect pathogens by the presence of pathogen effectors. Plant genomes typically contain hundreds of NLR-encoding genes. The availability of the hexaploid wheat (Triticum aestivum) cultivar Chinese Spring reference genome allows a detailed study of its NLR complement. However, low NLR expression and high intrafamily sequence homology hinder their accurate annotation. Here, we developed NLR-Annotator, a software tool for in silico NLR identification independent of transcript support. Although developed for wheat, we demonstrate the universal applicability of NLR-Annotator across diverse plant taxa. We applied our tool to wheat and combined it with a transcript-validated subset of genes from the reference gene annotation to characterize the structure, phylogeny, and expression profile of the NLR gene family. We detected 3,400 full-length NLR loci, of which 1,560 were confirmed as expressed genes with intact open reading frames. NLRs with integrated domains mostly group in specific subclades. Members of another subclade predominantly locate in close physical proximity to NLRs carrying integrated domains, suggesting a paired helper function. Most NLRs (88%) display low basal expression (in the lower 10 percentile of transcripts). In young leaves subjected to biotic stress, we found up-regulation of 266 of the NLRs To illustrate the utility of our tool for the positional cloning of resistance genes, we estimated the number of NLR genes within the intervals of mapped rust resistance genes. Our study will support the identification of functional resistance genes in wheat to accelerate the breeding and engineering of disease-resistant varieties.

An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations.

Advances in genome sequencing and assembly technologies are generating many high-quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimized data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents >78% of the genome with a scaffold N50 of 88.8 kb that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNA-seq and Pacific Biosciences (PacBio) full-length cDNAs to identify 104,091 high-confidence protein-coding genes and 10,156 noncoding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop.

BrAPI-an application programming interface for plant breeding applications.

MOTIVATION: Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. RESULTS: To facilitate interoperability among breeding applications, we present the public plant Breeding Application Programming Interface (BrAPI). BrAPI is a standardized web service API specification. The development of BrAPI is a collaborative, community-based initiative involving a growing global community of over a hundred participants representing several dozen institutions and companies. Development of such a standard is recognized as critical to a number of important large breeding system initiatives as a foundational technology. The focus of the first version of the API is on providing services for connecting systems and retrieving basic breeding data including germplasm, study, observation, and marker data. A number of BrAPI-enabled applications, termed BrAPPs, have been written, that take advantage of the emerging support of BrAPI by many databases. AVAILABILITY AND IMPLEMENTATION: More information on BrAPI, including links to the specification, test suites, BrAPPs, and sample implementations is available at https://brapi.org/. The BrAPI specification and the developer tools are provided as free and open source.

A carbohydrate-binding protein, B-GRANULE CONTENT 1, influences starch granule size distribution in a dose-dependent manner in polyploid wheat.

In Triticeae endosperm (e.g. wheat and barley), starch granules have a bimodal size distribution (with A- and B-type granules) whereas in other grasses the endosperm contains starch granules with a unimodal size distribution. Here, we identify the gene, BGC1 (B-GRANULE CONTENT 1), responsible for B-type starch granule content in Aegilops and wheat. Orthologues of this gene are known to influence starch synthesis in diploids such as rice, Arabidopsis, and barley. However, using polyploid Triticeae species, we uncovered a more complex biological role for BGC1 in starch granule initiation: BGC1 represses the initiation of A-granules in early grain development but promotes the initiation of B-granules in mid grain development. We provide evidence that the influence of BGC1 on starch synthesis is dose dependent and show that three very different starch phenotypes are conditioned by the gene dose of BGC1 in polyploid wheat: normal bimodal starch granule morphology; A-granules with few or no B-granules; or polymorphous starch with few normal A- or B-granules. We conclude from this work that BGC1 participates in controlling B-type starch granule initiation in Triticeae endosperm and that its precise effect on granule size and number varies with gene dose and stage of development.

Uncovering hidden variation in polyploid wheat.

Comprehensive reverse genetic resources, which have been key to understanding gene function in diploid model organisms, are missing in many polyploid crops. Young polyploid species such as wheat, which was domesticated less than 10,000 y ago, have high levels of sequence identity among subgenomes that mask the effects of recessive alleles. Such redundancy reduces the probability of selection of favorable mutations during natural or human selection, but also allows wheat to tolerate high densities of induced mutations. Here we exploited this property to sequence and catalog more than 10 million mutations in the protein-coding regions of 2,735 mutant lines of tetraploid and hexaploid wheat. We detected, on average, 2,705 and 5,351 mutations per tetraploid and hexaploid line, respectively, which resulted in 35-40 mutations per kb in each population. With these mutation densities, we identified an average of 23-24 missense and truncation alleles per gene, with at least one truncation or deleterious missense mutation in more than 90% of the captured wheat genes per population. This public collection of mutant seed stocks and sequence data enables rapid identification of mutations in the different copies of the wheat genes, which can be combined to uncover previously hidden variation. Polyploidy is a central phenomenon in plant evolution, and many crop species have undergone recent genome duplication events. Therefore, the general strategy and methods developed herein can benefit other polyploid crops.

RNA-seq, de novo transcriptome assembly and flavonoid gene analysis in 13 wild and cultivated berry fruit species with high content of phenolics.

BACKGROUND: Flavonoids are produced in all flowering plants in a wide range of tissues including in berry fruits. These compounds are of considerable interest for their biological activities, health benefits and potential pharmacological applications. However, transcriptomic and genomic resources for wild and cultivated berry fruit species are often limited, despite their value in underpinning the in-depth study of metabolic pathways, fruit ripening as well as in the identification of genotypes rich in bioactive compounds. RESULTS: To access the genetic diversity of wild and cultivated berry fruit species that accumulate high levels of phenolic compounds in their fleshy berry(-like) fruits, we selected 13 species from Europe, South America and Asia representing eight genera, seven families and seven orders within three clades of the kingdom Plantae. RNA from either ripe fruits (ten species) or three ripening stages (two species) as well as leaf RNA (one species) were used to construct, assemble and analyse de novo transcriptomes. The transcriptome sequences are deposited in the BacHBerryGEN database (http://jicbio.nbi.ac.uk/berries) and were used, as a proof of concept, via its BLAST portal (http://jicbio.nbi.ac.uk/berries/blast.html) to identify candidate genes involved in the biosynthesis of phenylpropanoid compounds. Genes encoding regulatory proteins of the anthocyanin biosynthetic pathway (MYB and basic helix-loop-helix (bHLH) transcription factors and WD40 repeat proteins) were isolated using the transcriptomic resources of wild blackberry (Rubus genevieri) and cultivated red raspberry (Rubus idaeus cv. Prestige) and were shown to activate anthocyanin synthesis in Nicotiana benthamiana. Expression patterns of candidate flavonoid gene transcripts were also studied across three fruit developmental stages via the BacHBerryEXP gene expression browser (http://www.bachberryexp.com) in R. genevieri and R. idaeus cv. Prestige. CONCLUSIONS: We report a transcriptome resource that includes data for a wide range of berry(-like) fruit species that has been developed for gene identification and functional analysis to assist in berry fruit improvement. These resources will enable investigations of metabolic processes in berries beyond the phenylpropanoid biosynthetic pathway analysed in this study. The RNA-seq data will be useful for studies of berry fruit development and to select wild plant species useful for plant breeding purposes.

Global transcriptome analysis uncovers the gene co-expression regulation network and key genes involved in grain development of wheat (Triticum aestivum L.).

Wheat grain development is a robust biological process that largely determines grain quality and yield. In this study, we investigated the grain transcriptome of winter wheat cv. Xiaoyan-6 at four developmental stages (5, 10, 15, and 20 days post-anthesis), using high-throughput RNA sequencing (RNA-Seq). We identified 427 grain-specific transcription factors (TFs) and 1653 differentially expressed TFs during grain development as well as a grain co-expression regulation network (GrainNet) of the TFs and their predicted co-expressed genes. Our study identified ten putative key TFs and the predicted regulatory genes of these TFs in wheat grain development of Xiaoyan-6. The analysis was given a firm basis through the study of additional wheat tissues, including root, stem, leaf, flag leaf, grain, spikes (from wheat plants at booting or heading stages) to provide a dataset of 92,478 high-confidence protein-coding genes that were mostly evenly distributed among subgenomes, but unevenly distributed across each of the chromosomes or each of the seven homeologous groups. Within this larger framework of the transcriptomes, we identified 4659 grain-specific genes (SEGs) and 26,500 differentially expressed genes (DEGs) throughout grain development stages tested. The SEGs identified mainly associate with regulation and signaling-related biological processes, while the DEGs mainly involve in cellular component organization or biogenesis and nutrient reservoir activity during grain development of Xiaoyan-6. This study establishes new targets for modifying genes related to grain development and yield, to fine-tune expression in different varieties and environments.

Hotspots in the genomic architecture of field drought responses in wheat as breeding targets.

Wheat can adapt to most agricultural conditions across temperate regions. This success is the result of phenotypic plasticity conferred by a large and complex genome composed of three homoeologous genomes (A, B, and D). Although drought is a major cause of yield and quality loss in wheat, the adaptive mechanisms and gene networks underlying drought responses in the field remain largely unknown. Here, we addressed this by utilizing an interdisciplinary approach involving field water status phenotyping, sampling, and gene expression analyses. Overall, changes at the transcriptional level were reflected in plant spectral traits amenable to field-level physiological measurements, although changes in photosynthesis-related pathways were found likely to be under more complex post-transcriptional control. Examining homoeologous genes with a 1:1:1 relationship across the A, B, and D genomes (triads), we revealed a complex genomic architecture for drought responses under field conditions, involving gene homoeolog specialization, multiple gene clusters, gene families, miRNAs, and transcription factors coordinating these responses. Our results provide a new focus for genomics-assisted breeding of drought-tolerant wheat cultivars.

expVIP: a Customizable RNA-seq Data Analysis and Visualization Platform.

The majority of transcriptome sequencing (RNA-seq) expression studies in plants remain underutilized and inaccessible due to the use of disparate transcriptome references and the lack of skills and resources to analyze and visualize these data. We have developed expVIP, an expression visualization and integration platform, which allows easy analysis of RNA-seq data combined with an intuitive and interactive interface. Users can analyze public and user-specified data sets with minimal bioinformatics knowledge using the expVIP virtual machine. This generates a custom Web browser to visualize, sort, and filter the RNA-seq data and provides outputs for differential gene expression analysis. We demonstrate expVIP's suitability for polyploid crops and evaluate its performance across a range of biologically relevant scenarios. To exemplify its use in crop research, we developed a flexible wheat (Triticum aestivum) expression browser (www.wheat-expression.com) that can be expanded with user-generated data in a local virtual machine environment. The open-access expVIP platform will facilitate the analysis of gene expression data from a wide variety of species by enabling the easy integration, visualization, and comparison of RNA-seq data across experiments.

PolyMarker: A fast polyploid primer design pipeline.

UNLABELLED: The design of genetic markers is of particular relevance in crop breeding programs. Despite many economically important crops being polyploid organisms, the current primer design tools are tailored for diploid species. Bread wheat, for instance, is a hexaploid comprising of three related genomes and the performance of genetic markers is diminished if the primers are not genome specific. PolyMarker is a pipeline that generates SNP markers by selecting candidate primers for a specified genome using local alignments and standard primer design tools to test the viability of the primers. A command line tool and a web interface are available to the community. AVAILABILITY AND IMPLEMENTATION: PolyMarker is available as a ruby BioGem: bio-polyploid-tools. Web interface: http://polymarker.tgac.ac.uk.

bio-samtools 2: a package for analysis and visualization of sequence and alignment data with SAMtools in Ruby.

MOTIVATION: bio-samtools is a Ruby language interface to SAMtools, the highly popular library that provides utilities for manipulating high-throughput sequence alignments in the Sequence Alignment/Map format. Advances in Ruby, now allow us to improve the analysis capabilities and increase bio-samtools utility, allowing users to accomplish a large amount of analysis using a very small amount of code. bio-samtools can also be easily developed to include additional SAMtools methods and hence stay current with the latest SAMtools releases. RESULTS: We have added new Ruby classes for the MPileup and Variant Call Format (VCF) data formats emitted by SAMtools and introduced more analysis methods for variant analysis, including alternative allele calculation and allele frequency calling for SNPs. Our new implementation of bio-samtools also ensures that all the functionality of the SAMtools library is now supported and that bio-samtools can be easily extended to include future changes in SAMtools. bio-samtools 2 also provides methods that allow the user to directly produce visualization of alignment data.

RNA-Seq bulked segregant analysis enables the identification of high-resolution genetic markers for breeding in hexaploid wheat.

The identification of genetic markers linked to genes of agronomic importance is a major aim of crop research and breeding programmes. Here, we identify markers for Yr15, a major disease resistance gene for wheat yellow rust, using a segregating F2 population. After phenotyping, we implemented RNA sequencing (RNA-Seq) of bulked pools to identify single-nucleotide polymorphisms (SNP) associated with Yr15. Over 27 000 genes with SNPs were identified between the parents, and then classified based on the results from the sequenced bulks. We calculated the bulk frequency ratio (BFR) of SNPs between resistant and susceptible bulks, selecting those showing sixfold enrichment/depletion in the corresponding bulks (BFR > 6). Using additional filtering criteria, we reduced the number of genes with a putative SNP to 175. The 35 SNPs with the highest BFR values were converted into genome-specific KASP assays using an automated bioinformatics pipeline (PolyMarker) which circumvents the limitations associated with the polyploid wheat genome. Twenty-eight assays were polymorphic of which 22 (63%) mapped in the same linkage group as Yr15. Using these markers, we mapped Yr15 to a 0.77-cM interval. The three most closely linked SNPs were tested across varieties and breeding lines representing UK elite germplasm. Two flanking markers were diagnostic in over 99% of lines tested, thus providing a reliable haplotype for marker-assisted selection in these breeding programmes. Our results demonstrate that the proposed methodology can be applied in polyploid F2 populations to generate high-resolution genetic maps across target intervals.