Supervisors: Drs Keith Gardner and Alison Bentley

Rotation project: Identifying genes underlying complex traits in crop plants is critical to modern plant breeding. A significant advance in this field has been the generation of multiparent mapping populations, in which NIAB has taken a leading role with development of an eight-founder multiparent advanced generation inter-cross (MAGIC) population for wheat. Surprisingly, about 15% of markers in this population were found to exhibit segregation distortion (SD), despite an absence of intentional selection (Gardner et al. in review). We have mapped about 40 significantly distorted linkage blocks to a range of locations across the genome. Some of the most strongly distorted blocks are long and associated with high marker density. These most likely represent introgression fragments from other grass species which have been incorporated into the wheat gene pool by breeders to broaden the genetic base of the crop and improve specific traits such as disease resistance and yield. We have confirmed this to be the case for two prominent SD linkage blocks. The student will continue this work with other possible introgression fragments and strongly SD blocks. They will investigate the occurrence of each block in the ultra-high density 820K wheat SNP array dataset and in association mapping panels of European wheat at NIAB. The sources of potential introgressions will be tracked using a pedigree of contemporary UK wheat lines developed by NIAB. The student will then develop and validate KASP markers for linkage blocks of interest, to aid wheat breeders in tracking the blocks during breeding.

PhD project: Linkage blocks showing SD in the MAGIC population are possibly subject to viability or fertility selection and negative interactions between linkage blocks from different genetic backgrounds may be of considerable importance. For all SD blocks, including introgressions, plant breeders need to be able to disentangle the loci causing desirable and undesirable phenotypic effects, and hence reduce “linkage drag”. We are currently developing Near Isogenic Lines (NILs) varying only in the presence/absence of the most prominent introgression fragments. These will enable investigation of the phenotypic effects of these linkage blocks in the field and glasshouse. To identify potential causative genetic differences, a targeted exome-sequencing approach will be used. The student will first interrogate both recently published wheat genome sequences (http://www.wheatgenome.org/, http://www.genomebiology.com/2015/16/1/26) using bioinformatics methods to identify all potential genes in the regions of the introgression fragments. This information can then be used to efficiently sequence the NILs and other lines to identify variants unique to the introgression fragments and potentially underlying phenotypic variation.  Overall, the project will develop powerful tools for the ongoing exploitation of favourable introgressions in wheat breeding. The student will receive a thorough training in modern crop genetics, from field phenotyping to state-of-the-art bioinformatics and creation of novel genomics resources.

Supervisor: Mario Caccamo, Head of Crop Bioinformatics

Rotation project: Access to genetic diversity information is one of the pillars underpinning modern crop breeding technologies. The challenge to breed higher-yielding better-quality eco-efficient crops in the context of changing climate conditions will only be met by utilising all available tools and the informed use of genetic diversity will be a crucial one.

This project will be focused on the design and implementation of a computational framework to represent diversity data for several varieties of cereal crops. The work will be initially conducted to effectively call and represent single-nucleotide polymorphisms (SNPs) for rice varieties native to Vietnam. This initial prototype will, however, set the basis to work with other more complex grasses. At 430Mb rice has a smaller and better-characterised genome than other crops such as wheat, which at 17Gb ranks as one of the largest genomes sequenced to date.

During the initial phase (rotation programme) the PhD student will work with current variant calling algorithms. The student will analyse data from whole-genome sequencing reads already generated for ~100 rice lines. This dataset includes a number of samples that have been sequenced deep enough to support first-pass assemblies to capture novel genomic features. These rice varieties have been selected by our collaborators at the Agricultural Genetics Institutes (Hanoi, Vietnam) to study phenotypes relevant to Vietnamese conditions including salt-tolerance and disease resistance. One of the greatest threats to rice production in Vietnam is incursion of sea water, climate change also brings increased threats of flooding, periods of drought and newly emergent pests and pathogens.

PhD project: This work is part of a larger programme to develop novel computational approaches for the representation and access of crop diversity data to enable modern breeding technologies. In particular, as more diversity datasets are generated by the scientific community we will look into the integration of data from other technologies such as optical mapping, and from different sources such as RNA-Seq. The PhD student will have a unique opportunity to work with advanced computing resources in a high-performance environment and be embedded in a team of other students working in crop genomics.

Areas of interest:

• Assembly approaches for variation analysis.
• Complex crops – genomics and bioinformatics.
• Data representation (in the context of large datasets).
• Data presentation tools for modern breeding strategies.

Literature
Huang et al. (2010). Genome-wide association studies of 14 agronomic traits in rice landraces. Nature Genetics.

Iqbal, Z., Caccamo, M., Turner, I., Flicek, P., & McVean, G. (2012). De novo assembly and genotyping of variants using colored de Bruijn graphs. Nature Genetics.

The 3,000 rice genomes project GigaScience. doi:10.1186/2047-217X-3-7

Supervisor: Mario Caccamo, Head of Crop Bioinformatics

Rotation project: A genomic sequence is of little use unless we can identify features such as genes and regulatory elements that are encoded within the long string of nucleotides. A number of sophisticated software tools have been developed over the years to support the annotation and functional characterisation of gene structures. These tools assume a relatively high quality reference genome that is used as the backbone upon which to annotate genes. As more genomes are available, however, the single-genome approach will be substituted by a pangenomics one that can capture the whole-spectrum of genomic diversity within a species. Representing crop diversity data in this way will play a key role in the identification of useful novel diversity for use in modern breeding technologies.

This project will develop a novel strategy for the annotation of gene structures in the context of the pangenome. We will not assume a single linear genome rather a graph-based data structure representing the genomic diversity from a large number of individuals. We will focus attention on areas that are especially relevant to crop genomes such as high-repeat content, the presence of homeologous genes (polyploidy) and integration with genetic information (i.e.markers).

During the initial phase (rotation) the PhD student will work with a high-level representation of the data (e.g Cortex coloured-graph approach). We will first develop a prototype for an RNA-Seq alignment tool that will work directly on the underlying graph structure.

PhD project: Following this we will explore a number of areas that will require the development of novel algorithms:

• Repeat annotation directly on the graph based on k-mer frequency and known repetitive elements.
• Projection of gene structures from annotation performed in a canonical reference.
• The application of hidden- Markov models directly to the coloured graph structure. A priori this is not a computationally tractable problem therefore it will require the development of a strategy to reduced the search space.
• The implementation of splice-aware alignment tools to deal with long RNA-Seq reads. As longer reads are generated by the current sequencing technologies the demand for suitable alignment tools for cDNA sequences will increase.

This work is part of a larger programme to develop novel computational approaches for the representation and access of crop diversity data to support modern breeding technologies. The PhD student will have a unique opportunity to work with advanced computing resources in a high-performance environment and be embedded in a team of other postdocs and students working in crop genomics.

Literature
1      “De novo assembly and genotyping of variants using colored de Bruijn graphs”. Iqbal Z, Caccamo M, et al. Nature Genetics doi 10.1038/ng.1028.

Supervisors: Drs Anna Gordon, Alison Bentley and Lesley Boyd                                        

Infection of grain by fungal pathogens results in yield loss and toxin contamination in cereal crops worldwide. Two important diseases of UK cereal production are caused by fungi with contrasting modes of ear/grain infection. The fungus Claviceps purpurea (Cp) infects wheat ovules, replacing the seed with fungal sclerotia and causing Ergot. Ergot sclerotia are full of a toxic cocktail that in humans causes the medieval disease St Antony’s Fire. The more opportunistic Fusarium pathogen complex (causing Fusarium Head Blight; FHB) infects all parts of the wheat ear, leading to production of harmful mycotoxins within the developing grain.

Ground-breaking research at NIAB indicates that Cp co-opts the plant’s Gibberellic Acid (GA) pathways to establish infection and reproduce. Partial resistance to Ergot has been found to co-locate with the wheat dwarfing genes, Rht-1Bb and Rht-1Db (Gordon et al 2015; TAG in press). These DELLA protein mutants are non-responsive to GA, resulting in growth retardation (Peng et al 1999; Nature 40: 256). Preliminary results in wheat transgenic lines expressing a bean GA2 oxidase1 specifically in ovules indicates that lowering GA levels results in reduced Cp infection and smaller sclerotia. Resistance to FHB, which can be classified by infection type, has also been shown to be linked to the wheat dwarfing genes (Srinivasachary et al 2009; TAG 118: 695), GA being hypothesised to play a role in the ability of the fungus to spread within the ear.

Rotation project: The student will confirm the effect of expressing bean GA2 oxidase1 on Cp resistance and extend these tests to look at resistance to Fusarium spp in the FHB complex. The correlation between ergot and FHB resistance phenotypes with bean GA2 oxidase1 expression levels will be studied using qRT-PCR. The student will undertake bioinformatics analyses to identify the wheat homologues of bean GA2 oxidase1, clone and sequence the homoeologues (3 genomes in hexaploid wheat) from the wheat cv. Fielder (transgenic genotype), and develop primers to determine the background expression of the wheat endogenous GA2 oxidase 1 in wild-type and transgenic lines.

PhD project: Additional work would involve measuring GA levels in wild-type and transgenic wheat lines, correlating GA levels with Cp and FHB infection/resistance. GA assays would be carried out at Rothamsted Research in collaboration with Andy Phillip’s group. If GA levels do prove a significant factor in Cp and FHB infection of wheat the project could explore how GA levels in ovules and ears are manipulated by the pathogen, the effects of the Rht-1Bb/1Db dwarfing alleles on GA levels and how this results in reduced infection. The FHB/GA interaction could be extended to include the use of transgenic Fusarium isolates expressing fluorescent tags (GFP, dsRed) to further elucidate the specificity of the relationship between plant and pathogen.

We have recently sequenced the Cp genome and have identified a partial GA biosynthesis gene cluster, similar to the GA biosynthesis gene cluster in Fusarium fujikori. Transcriptomics analyses shows that this Cp gene cluster is expressed during the first 7 days of infection, so the ability of the pathogens to synthesise GA needs to be further explored.

Additional traits of interest, including reduced grain size also appears to be linked to GA depletion, and given that there is very little known about the ovule GA status in our most important UK crop, there is scope here for the project to deliver exciting new knowledge.

The student will receive training in functional gene analysis, bioinformatics, qRT-PCR and gene expression analysis, GA biochemistry, plant pathology, wheat genetics and genomic characterisation.

Supervisors: Dr Tom Wood and Dr Anne Webb

Rotation project: Chocolate spot, caused by Botrytis fabae, is an important disease of faba bean (Vicia faba) which can cause severe crop losses. Currently there are no resistant commercial cultivars available. Resistant faba bean lines have been identified, but in many cases, replicated trials in different locations failed to reproduce these findings. One explanation could be the existence of strains with different virulence profiles. The genetic diversity of B. fabae and also variation for virulence within the B. fabae population, are currently unknown. The rotation project will explore the genetic diversity within B. fabae, assess for population structure, and ascertain if differences in virulence exist within UK B. fabae isolates.

At NIAB we hold a collection of approx. 200 isolates of B. fabae as well as >900 accessions of Vicia faba of which approx. 125 lines are inbred through at least 6 generations. Within the 10 week DTP rotation project the student will conduct a virulence test of several B. fabae isolates on selected lines of faba bean as well as screening a selection of UK isolates with molecular markers to get an overview of the genetic diversity within the collection. Based on these results isolates will be selected and sequenced using NGS technology. A reference genome for B. fabae will then be assembled and annotated, for use in subsequent comparative genomics studies during the full PhD project.

PhD project: Genetic diversity and virulence patterns in Botrytis fabae, the pathogen causing chocolate spot of faba bean (Vicia faba). The PhD project will focus on investigating for variation in virulence between strains and the genetic diversity between and within populations of Botrytis fabae. Efforts to breed fully resistant cultivars have been unsuccessful to date. Trials at NIAB have previously identified several sources of promising partial resistance to chocolate spot from which we have developed mapping populations with the aim of identifying QTLs conferring partial resistance. The PhD student’s work will be complementary to this work, identifying virulence genes and investigating variation in pathogenicity within B. fabae. This will involve using the B. fabae reference genome as a basis for expression analyses to identify potential virulence genes. Throughout the project the student will acquire a wide range of skills in the areas of microbiology, genetics, molecular biology and bioinformatics. This will allow the student to test fundamental hypotheses whilst also contributing to an applied plant breeding programme to help improve food security.

Supervisor: Dr Phil Howell

NIAB’s pre-breeding programme introduces diversity into elite varieties of hexaploid wheat (T. aestivum, AABBDD) from a range of wild and cultivated diploid and tetraploid relatives (Aegilops tauschii, DD genome; Triticum durum, T. dicoccoides, T. dicoccum, all AABB). This platform of wide crossing and re-synthesis provides the ‘synthetics pillar’ of WISP, the BBSRC’s public-good wheat pre-breeding programme.

A proportion of our pre-breeding recombinant lines display undesirable “weedy” characteristics inherited from these relatives, such as shattering seed heads or adhering glumes. These were bred out long ago during the domestication of wheat, and their presence in pre-breeding lines can inhibit the exploitation of otherwise promising material by commercial breeders. Diploid, tetraploid and hexaploid parental and recombinant materials can be phenotypically characterised for threshability and then screened with published markers linked to the major domestication loci Q, Br, Sog and Tg. Additional SNP-based markers developed specifically for WISP germplasm can also be used to characterise the material. Genetic markers for these domestication traits will greatly aid the selection of improved pre-breeding material and help widen the pool of diversity available to commercial wheat breeders, ultimately leading to improvements in yield stability, pest and disease resistance, and the tolerance of abiotic stresses.

References:
Dvorak et al., 2012. J Hered 103:426-441
Simons et al., 2006. Genetics 172: 547-555

PhD projects: NIAB’s Cereal Pre-Breeding group aims to capture novel diversity and transfer it into the backgrounds of elite UK-adapted varieties for phenotypic evaluation, with the best lines passing into commercial breeding programmes for exploitation. We are developing thousands of recombinant pre-breeding lines which represent a large germplasm resource for subsequent research.

PhD projects would typically involve the dissection of important phenotypes such as domestication traits and yield components. The number, significance and location of genes controlling these characters would be determined through QTL mapping, and validated across different germplasm. Recombinant pre-breeding lines will be used to develop high-resolution maps around the QTLs, including co-dominant markers suitable for high-throughput genotyping. This is likely to involve a bio-informatics approach exploiting synteny with rice, maize and brachypodium. Once very close linkage is established, it should be possible to develop near-isogenic lines for the target loci in order to better understand the underlying mechanisms of each character and how they interact. Where possible, candidate genes will be identified and hypotheses tested through the use of TILLING populations, transformation or genome editing. 

Supervisor: Dr Phil Howell

Grain size, often expressed as Thousand Grain Weight (TGW), is a key yield component in wheat, and many QTLs for TGW have been detected in mapping populations. Digital grain imaging equipment enables the high-throughput analysis of grain shape parameters, revealing that seed size and shape are largely independent traits. Candidate genes for grain length and grain width have been identified in rice, and one of the orthologues, TaGW2, has been associated with grain weight in wheat.

Previous studies have shown that Synthetic Hexaploid Wheat lines (SHWs) can carry alleles for high TGW, and physically large and heavy grains are a common feature of many of the higher-yielding SHW-derived lines selected from NIAB’s pre-breeding work. It is likely that these are novel alleles not already present in the elite germplasm pool commonly used by breeders. Grain samples taken from multiple trials will be screened at NIAB using digital imaging to generate phenotype data. This will then be combined with existing genotype data to detect QTLs for grain size and shape, and look for co-segregation with candidate genes. The role of TGW in absolute yield will be explored, together with trade-offs between grain size and other yield components such as grain number.

References:
Yu et al., 2014. J Integr Agric 13:1835-44
Simmonds et al., BMC Plant Biol 14:191

PhD projects: NIAB’s Cereal Pre-Breeding group aims to capture novel diversity and transfer it into the backgrounds of elite UK-adapted varieties for phenotypic evaluation, with the best lines passing into commercial breeding programmes for exploitation. We are developing thousands of recombinant pre-breeding lines which represent a large germplasm resource for subsequent research.

PhD projects would typically involve the dissection of important phenotypes such as domestication traits and yield components. The number, significance and location of genes controlling these characters would be determined through QTL mapping, and validated across different germplasm. Recombinant pre-breeding lines will be used to develop high-resolution maps around the QTLs, including co-dominant markers suitable for high-throughput genotyping. This is likely to involve a bio-informatics approach exploiting synteny with rice, maize and brachypodium. Once very close linkage is established, it should be possible to develop near-isogenic lines for the target loci in order to better understand the underlying mechanisms of each character and how they interact. Where possible, candidate genes will be identified and hypotheses tested through the use of TILLING populations, transformation or genome editing. 

Supervisors: James Cockram and Ian Mackay

Wheat is the UK’s most important crop. Grain, flour and breadmaking quality are critical traits for suitability of wheat harvests for intended end use. Genetic improvement is the most sustainable approach towards improving wheat quality. Recent advances in wheat genomics, mapping-population design and statistical analyses provide a timely opportunity to perform UK-relevant, high-resolution genetic analyses of wheat quality traits.

Methodology: This project will use a unique wheat resources generated at NIAB: a multi-parent advanced generation inter-cross (MAGIC)  population, generated from eight UK varieties via multiple rounds of intercrossing, resulting in 1,000 progeny (Mackay et al. 2014). Parents include four classified as NABIM quality group 2 or above (Hereward, Xi19, Rialto, Robigus). The population has been genotyped with a high-density 90k SNP array. Along with facilities for quality testing and molecular labs at NIAB, these resources will be used to undertake fine-scale dissection of the genetic regions controlling multiple wheat quality traits.

Project aims are to generate:

1. Fine-scale genetic analysis of multiple grain quality characters within a single high-resolution mapping platform.
2. Breeder friendly genetic markers tagging these traits, and ultimately, map-based cloning of selected QTL.
3. Tools and approaches with which to try to predict quality, and the ability to test these hypotheses via test bakes.

This project represents the first time a UK-relevant MAGIC population has been used to investigate wheat grain quality characteristics. The project is well aligned with industrial and grower interests, and ultimately aims to provide genomics-informed strategies for the development of new varieties with improved quality parameters.

References
Mackay I, Bansept-Basler P, Barber T, Bentley AR, Cockram J, Elderfield J, Gosman N, Greenland AJ, Horsnell R, Howells R, O’Sullivan DM, Rose GA, Howell P (2014). An eight-parent multiparent advanced generation intercross population for winter-sown wheat: creation, properties and validation. G3: Genes Genomes Genetics, 4: 1603-1610.

Supervisor: Dr Alison Bentley

Rotation project: Wheat is Europe’s main crop, essential for food security. With no evidence for decreasing demand, current production must be accelerated, but cannot do so through expanded agricultural area. This priority process of sustainable intensification requires novel approaches to drive increased yield potential. Proposed is the adoption of new genomics tools offering potential for accelerating selection, thereby reducing time, and ultimately, cost. Although yet to be fully validated for its cost versus benefit in commercial plant breeding, genomic selection (GS) is a front-runner: it removes the burden of phenotyping selection candidates, replacing phenotype with genotype to predict breeding value based on a trained model.

The economic and time cost of phenotyping is a current bottleneck to the genetic dissection of complex traits and accurate implementation of GS. For example, physiological and development traits are rarely phenotyped in routine trialling because of their complexity. As a result there is little information describing the genetic basis or predictive potential of physiological traits and many remain elusive beyond empirical breeder selection.

In this project, the student will employ a suite of complementary resources leveraging emerging genomics approaches on physiological targets directly relevant to driving wheat yield and its components. High-density genotypes have already been generated on an elite UK population, and the student will interrogate these using bioinformatic and quantitative genetic approaches. Field data is also available to support the dissection of the genetic control of physiological trait variation for the application of GS.

There is huge potential to use advanced physiological understanding, linked with genomics, to develop resource-efficient tools for wheat breeding.

PhD project: The rotation project can be rapidly scaled to encompass a suite of complementary and commercially relevant wheat populations available at NIAB. These populations are linked by a common parent, and also have contrasting parents with no significant pedigree overlap. Previous evidence supports their contrasting nature for creation of commercially relevant segregating populations. The student will use these populations, alone and in combination to optimise methods for phenotyping physiological development targeted to the application of GS. Descriptive high-density phenotypes will be combined with high density genotypes (and accompanying bioinformatic analyses) for mapping and GS. Extending outwards, the developed tools will be validated and then used in larger, more complex populations. Such populations have an inherent phenotyping bottleneck due to their large size, with mapping precision ultimately limited by accuracy of the phenotype. 

The ability to make accurate predictions on traits influencing yield or its components will be tested via the initiation of a GS-led rapid recurrent selection scheme.

The student will gain experience in a number of key areas, including wheat breeding, field phenotyping, molecular biology, bioinformatics and quantitative genetics. They will have the opportunity to collaborate with a number of industrial and academic partners in an exciting and emerging field of research and application.

Three recent relevant references

Abberton M, Batley J, Bentley A et al. (2015) Global agricultural intensification during climate change: a role for genomics. Plant Biotechnology Journal [in press].

Kole C, Muthamilarasan M, Henry R, Edwards D, Sharma R, Abberton M, Batley J, Bentley A et al. (2015) Application of genomics for generation of climate resilient crops: Progress and prospects. Frontiers in Plant Science [in press].

Bentley A et al. (2014) Applying association mapping and genomic selection to the dissection of key traits in elite European wheat. Theoretical and Applied Genetics 127: 2619-2633.