The Identification of QTL Controlling Ergot Sclerotia Size in Hexaploid Wheat Implicates a Role for the Rht Dwarfing Alleles

The identification of QTL controlling ergot sclerotia size in hexaploid wheat implicates a role for the Rht dwarfing alleles

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Gordon, A., Basler, R., Bansept-Basler, P., Fanstone, V., Harinarayan, L., Grant, P. K., Birchmore, R., Bayles, R. A., Boyd, L. A. and O'Sullivan, D. M. (2015) The identification of QTL controlling ergot sclerotia size in hexaploid wheat implicates a role for the Rht dwarfing alleles. Theoretical and Applied Genetics, 128 (12). pp. 2447-2460. ISSN 1432-2242 doi: https://doi.org/10.1007/s00122-015-2599-5 Available at http://centaur.reading.ac.uk/42600/

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Reading’s research outputs online The identification of QTL controlling ergot sclerotia size in hexaploid wheat implicates a role for the Rht dwarfing alleles

Anna Gordon1,*, Ryan Basler1, Pauline Bansept Basler1,2, Vicky Fanstone1, Lakshmi Harinarayan1,3, Paul K

Grant4, Richard Birchmore1, Rosemary A Bayles1,5, Lesley A Boyd1, Donal M. O’Sullivan1,6

1. NIAB, Huntingdon Road, Cambridge, CB3 0LE, UK

2. Syngenta France, Route de Moyencourt, 78910 Orgerus, France

3. Bayer CropScience, Department Technologiepark 38, 9052, Gent, Belgium

4. Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, U.K

5. Woodgate Farm, Cascob, Presteigne, Powys, LD8 2NT, UK

6. School of Agriculture, Policy and Development, University of Reading, Reading RG6 6AR, UK

*Corresponding author

Dr Anna Gordon

E-mail: [email protected]

Telephone: 01 223 342485

Fax: 01 223 277602

Compliance with Ethical Standards.

All authors have consented to submit this paper. All authors have followed scientifically good practice as outlined in the Instructions for Authors. This work did not involve human or animal participants.

Conflict of interest

The authors declare that they have no conflict of interest.

Author’s contribution statement

AG wrote the paper, led much of the experimental work, and analysed genotypic, QTL and phenotypic data. RB

(Basler) assisted with field experiments and population handing, and carried out initial QTL analyses of the

Year 1 data. AG and RB (Basler) developed the NIAB Ergot Sclerotia Sizing scale. PBB helped with field

1 experiments and assisted AG with the generation of the ‘Robigus’ x ‘Solstice’ genetic map. RB (Birchmore) helped with field experiments and seed multiplication. VF and PG helped with field experiments. LH generated additional marker data for the ‘Robigus’ x ‘Solstice’ population. LB co-wrote the manuscript and contributed to statistical analyses. RAB led the HGCA-Defra LINK project LK0963 that undertook the initial screening of UK winter wheat varieties for ergot resistance. DOS conceived and obtained funding for the study - BBSRC and

Defra Government Partnership Award (BB/GO20418/1) - led the project team, conducted experiments and co- wrote the manuscript.

Acknowledgements

The work was funded by the Biotechnology and Biological Sciences research Council (BBSRC) and the

Department for Environment Food and Rural Affairs (Defra) Government Partnership Award (BB/GO20418/1) to DOS, RAB and AG entitled “Integrated transcriptome and genetic analysis of early events determining tissue susceptibility in the Claviceps purpurea - wheat interaction”, and the Home Grown Cereals Authority (HGCA)-

Defra LINK project LK0963 entitled “Towards a sustainable whole-farm approach to the control of Ergot” to

RAB. We acknowledge Dr Chris Burt, then at JIC, for the screening of the ‘Robigus’ x ‘Solstice’ DH population with the chromosome 4DS Kaspar markers, 10920_kasp9 and HV132-1_kasp9. Thanks go to Dr Paul Nicholson for his critical reading of the manuscript, and in conjunction with Dr Chris Burt for useful discussions. The field trials were thanks in part to the NIAB field trials team and we would also like to acknowledge Kate Parsley,

Emily Smith, Beth Dickson, and Dan Smith who were additional helpers in inoculating and/or threshing, and scoring of the ergot sclerotia.

Abstract

Key message

Four QTL conferring resistance to ergot were identified in the UK winter wheat varieties ‘Robigus’ and

‘Solstice’. Two QTL co-located with semi-dwarfing alleles at the Rht loci Rht-1B and Rht-1D implicating a role of these DELLA proteins in infection success of Claviceps purpurea.

Abstract

The fungal pathogen Claviceps purpurea infects ovaries of a broad range of temperate grasses and cereals, including hexaploid wheat, causing a disease commonly known as ergot. Sclerotia produced in place of seed carry a cocktail of harmful alkaloid compounds that result in a range of symptoms in humans and animals, causing ergotism. Following a field assessment of C. purpurea infection in winter wheat, two varieties

‘Robigus’ and ‘Solstice’ were selected which consistently produced the largest differential effect on ergot sclerotia weights. They were crossed to produce a doubled haploid mapping population, and a marker map, consisting of 714 genetic loci and a total length of 2895 cM was produced. Four ergot reducing QTL were identified using both sclerotia weight and size as phenotypic parameters; QCp.niab.2A and QCp.niab.4B being detected in the wheat variety ‘Robigus’, and QCp.niab.6A and QCp.niab.4D in the variety ‘Solstice’. The ergot resistance QTL QCp.niab.4B and QCp.niab.4D peaks mapped to the same markers as the known reduced height

(Rht) loci on chromosomes 4B and 4D, Rht-B1 and Rht-D1, respectively. In both cases the reduction in sclerotia weight and size were associated with the semi-dwarfing alleles, Rht-B1b from ‘Robigus’ and Rht-D1b from

‘Solstice’. Two-dimensional, two-QTL scans identified significant additive interactions between QTL

QCp.niab.4B and QCp.niab.4D, and between QCp.niab.2A and QCp.niab.4B when looking at sclerotia size, but not between QCp.niab.2A and QCp.niab.4D. The two plant height QTL, QPh.niab.4B and QPh.niab.4D, which mapped to the same locations as QCp.niab.4B and QCp.niab.4D, displayed both epistatic and additive interactions.

Keywords

Claviceps purpurea, dwarfing alleles, ergot sclerotia, Rht, Triticun aestivum, wheat

Introduction

The ergot fungus Claviceps purpurea infects the ovaries of many species of cereals and grasses, including the economically important cereals wheat, barley, oats, triticale, rye and millet (Tenberge 1999). Conidiospores and ascospores germinate on receptive stigma producing hyphae which grow down the lumen of the stigma towards the ovule tissue, following the route that would normally be taken by pollen tubes (Tudzynski et al. 2004).

Within 24 hours of spore germination the fungal germ tube enters the transmitting tissue of the ovule and continues to the ovule base, where the xylem and phloem enter from the rachis. Three to four days post infection, when the hyphae have surrounded the ovary, hyphae become more branched. At 5 days post infection there is complete host cell collapse and the fungus enters the sphacelial stage, where it becomes soft, white and porous, and begins to generate asexual conidiospores. Around 6-7 days post infection an exudate, known as honeydew, is produced consisting of plant sap and C. purpurea asexual, haploid conidia which are believed to be dispersed by rain drops and insects (Tenberge 1999).

The infected ovary is eventually replaced by a purplish-black sclerotium, commonly referred to as an ergot, a hardened mass of white fungal mycelia that is covered with a purplish black outer surface. These overwintering sclerotia eventually give rise to sexual reproductive structures, stroma or apothecia, from which wind-borne ascospores are produced (Mantle and Shaw 1976). Sclerotia contain a wide range of toxic alkaloids produced by the fungus, including ergometrine, ergotamine, ergosine, ergocristine, ergocryptine (which is a mixture of α- and

β- isomers), ergocornine, and the corresponding -inine epimers. The alkaloids found within sclerotia can cause severe health problems in both humans and animals, responsible for the disease known as ergotism. Ergot alkaloids are classified as tryptophan derived alkaloids with physiological effects occurring from the absorption in the gastrointestinal tract. Toxicity associated with ergot alkaloids occurs through their action on neurotransmitters which can affect the nervous system (De Costa 2002) and at higher doses negatively impact the reproductive system in animals (De Groot et al. 1993).

C. purpurea infection and sclerotia production therefore cause serious quality issues for cereal production. The

European Union has imposed limits on the amount of ergot sclerotia allowed in grain destined for human and animal consumption to 0.01% (1g per kg) (Alexander et al. 2012). As C. purpurea enters the ovary via the stigma and style, incidents of infection are more common in open flowering cereals, with rye and Triticale often being heavily infected. As wheat is a closed-flowering cereal, the window of opportunity for infection is small.

Consequently only 1-5% of seed lots examined between 2002 and 2005 by the UK’s Official Seeds Testing

Station were found to contain ergot sclerotia. However, male sterility, whether genetic or as a consequence of environmental factors such as copper deficiency or drought, results in the flowers gaping open and presents an increased risk of infection. The production of hybrid cereal seed on cytoplasmic male sterile (CMS) mother plants is therefore particularly at risk. Further work completed within populations of CMS lines however, suggests that there are differences in ergot sensitivity which have a genetic basis rather than differences in floral morphology (Miedaner et al 2010).

Complete resistance to C. purpurea infection is unknown and a hypersensitive response to this fungus has not been observed in floral tissue (Tenberge 1999). A source of partial resistance was identified in the hexaploid wheat line ‘Kenya Farmer’ in the 1970s (Platford and Bernier 1970), which resulted in the production of smaller sclerotia (Platford and Bernier 1970, Pageau and Lajeunesse 2006). A reduction in sclerotial size may have an epidemiological impact, resulting in fewer ascospores germinating in the following season (Cooke and Mitchell

1966). Good partial resistance was identified in the tetraploid durum wheat line 9260B-172A, where there was both a reduction in sclerotia size and in the amount of honeydew produced (Menzies 2004). In sorghum nine

QTL were identified that affect percentage infection by C. africana (Parh et al. 2008).

As few sources of resistance to C. purpurea have been reported in wheat, this study set out to identify UK wheat varieties that differed in their ability to support sclerotia development and then determine the genetic components accounting for these differences. Significant differences were identified between winter wheat varieties in the average weights of sclerotia produced in manually inoculated florets. As the varieties ‘Robigus’ and ‘Solstice’ represented the extremes of this variation a doubled haploid population was made from their F1 cross. Phenotypic data was gathered over multiple years of replicated, inoculated field trials to identify the QTL responsible for the differences in sclerotia weight and size seen between ‘Robigus’ and ‘Solstice’.

Materials and Methods

Plant materials and Doubled Haploid mapping population

Fourteen wheat varieties were tested over multiple years (Table 1) as part of the HGCA-Defra LINK project

LK0963, “Towards a sustainable whole-farm approach to the control of Ergot” (Bayles et al. 2008). In each year the wheat varieties were sown in replicate field trials at sites near NIAB, Cambridge, UK.

‘Robigus’, a soft biscuit wheat (KWS UK, Ltd) and ‘Solstice’, a hard bread wheat (Limagrain UK) were crossed and a doubled haploid (DH) population of 159 lines produced by Saaten Union (Saaten-Union GmbH,

Hovedisser Str. 92 D - 33818 Leopoldshoehe, Germany). This DH population was screened for C. purpurea resistance in field trials in 2009/10 and again in 2010/11 at sites near NIAB, Cambridge, UK.

Preparation of Claviceps purpurea isolates

C. purpurea conidia were obtained by culture on potato dextrose agar (PDA) and on wheat ears of the spring wheat variety ‘Paragon’. Ergot sclerotia were surface sterilized for 4 minutes in 5% sodium hypochlorite and washed four times in sterile distilled water. After surface sterilization the sclerotia were cut in half and placed on

90-mm Petri plates with PDA (Merk 39g/l) with 125mg streptomycin/l. Colonies were sub-cultured on PDA, without antibiotic, after approximately 10 days of culture at 25oC in the dark. The resulting C. purpurea colonies were confirmed based on conidial morphology and grown at 20oC in the dark for 14 days to harvest conidia. Conidia were scraped from the centre of the colony and suspended in sterile distilled water.

Conidia, collected as honeydew, were produced by inoculating florets of the wheat variety ‘Paragon’. ‘Paragon’ was grown in the glasshouse in Levingtons M2 compost with slow-release osmacote fertilizer, with a 16h day length, 6000 Lux and day/night temperatures of 18oC/10oC. Ears were inoculated before anthesis with a suspension of conidia from individual isolates (Table 2), using either a hypodermic needle to fill the space between the lemma and palea of each floret (approximately 0.025ml of suspension at 106 conidia/ml), or by dipping wounded ears in the conidia suspension.

Honeydew produced by inoculating ‘Paragon’ was collected approximately 10 days after inoculation using either a Pasteur pipette or an inoculation loop and suspended in water. Honeydew was collected every 2-3 days

6 and the suspensions stored at 5oC between collections. Conidial collections were bulked and stored as individual isolates in 10% glycerol at -20oC. Frozen suspensions were found to retain pathogenicity for at least two years.

Claviceps purpurea inoculated field trials

For the UK winter wheat variety field assessments equal amounts of the five C. purpurea isolates (Table 2), at a final concentration of 106 conidia ml-1 were used. For the field inoculation of the ‘Robigus’ x ‘Solstice’ DH population one isolate, 04-97 was selected based on the differential ergot sclerotia size produced on ‘Robigus’ and ‘Solstice’ in glasshouse tests and a single spore inoculum was produced and used in all subsequent experiments (called 04-97.1). In 2009/10, due to variable seed set on the primary doubled haploid plants, just

105 DH lines and the parental varieties were sown in 1m double-row plots. There were two replicates for all but

17 of the DH lines where seed quantity was limited. The ears from six primary tillers (6 plants) per plot were inoculated with the C. purpurea isolate 04-97.1 between 1st and 7th June 2010. Twenty florets per ear were hand- inoculated with a conidia suspension by syringe. In 2010/11 three randomized blocks of all 159 DH lines and the parental varieties were sown in 1m plots. Again 20 florets per ear, on the primary tiller of six plants were inoculated per line in each plot. Inoculations were carried out by hand between 18th and 27th May 2011.

Inoculum was prepared daily from newly emerging honeydew exuding from ‘Paragon’. The honeydew was diluted with water to a concentration of 6 x 106 conidia/ml. Ears were inoculated when anthers in the middle third of the ear had begun to turn yellow i.e. 1-2 days prior to anthesis. The first fully formed spikelet at the base of each ear was removed to identify the start of the inoculated region. The inoculum was delivered between the lemma and palea of the outer two florets of each spikelet using a 2ml syringe and needle until the void was full of inoculum. Twenty florets on each ear were inoculated (10 on each side) and the ear labelled with a coloured tag, dated and initialled by the researcher who undertook the inoculation. Ears were harvested 7-8 weeks after anthesis and before the mature ergots began to drop from the ears. Ears were left to dry before removing ergot sclerotia. This inoculation protocol routinely achieved infection in 70-100% of inoculated spikelets and was designed to minimise the chances for differences in ear morphology or effectiveness of pollen competition to influence the results, as we were more interested in post-infection resistance than ‘escape’ mechanisms.

Phenotypic assessment of ergot sclerotia development

Ergot sclerotia were removed by hand from the 20 inoculated florets of each ear and the following parameters measured:

(1) Total sclerotia weight per ear – The weight of all sclerotia collected from one ear.

(2) Average sclerotia weight per ear – The total sclerotia weight per ear/ the total number of sclerotia

collected from that ear.

(3) Sclerotia size was determined using a numerical value according to the sclerotia’s size within the seed

cavity. The NIAB Ergot Scale index points are as follows (Online Resource 1): 0: Dried-out ovule

(ovule was infected, but no sclerotia formed); 1: Sclerotia < 2 mm in length; 2: Sclerotia < 3 mm in

length; 3: < 5 x 2 mm in size ; 4: Sclerotia > 5 x 2 mm in size; 5: > 8 x 5 mm in size ; 6: > 10 x 5 mm

in size; and 7: > 17 x 5 mm in size.

(4) Average sclerotia size was calculated as follows, where ni= is the number of sclerotia assigned to each

NIAB scale from 0 to 7 and nj is the total number of sclerotia.

 (ni x NIAB scale [0 to 7])

Plant height

Just before harvest plant heights were recorded for each of the DH lines of the ‘Robigus’ x ‘Solstice’ DH population. Plant height was measured as the height from the base of the plant to the bottom of the primary ear.

These measurements were taken on ten random plants per line in each plot.

Statistical data analysis

Analysis of variance (ANOVA) of total sclerotia weight per ear, average sclerotia weight, average sclerotia size and plant heights were undertaken using Restricted Maximum Likelihood (REML). Predicted means for the DH lines were extracted from the REML analyses for each phenotypic data set. Where required, data were transformed using log or square root transformation to achieve near normality and independence of the means and variances. The effects of test replications and genotypes were accounted for in the model. For the 2010 field trial data each inoculated ear was treated as a replicate to derive the predicted means. All analyses were performed using the statistical package Genstat for Windows, release 12 (Payne et al, 2009). Variance

8 components for Vg and Ve were calculated by REML analysis in Genstat and were used to calculate heritability

(Holland et al, 2010) using the following formula: h2 = Vg/(Vg+Ve) Vg = Estimated genetic variance between lines Ve = environmental error from DH.reps + residual error r (r*n)

Where r is number of replicates, n is number of plants per rep.

Genotyping of the ‘Robigus’ x ‘Solstice’ Doubled Haploid population

Genomic DNA was extracted from leaf tissue using a modified Tanksley method (Fulton et al. 1995), which included an RNase digestion step. Genomic DNA was genotyped by Diversity Arrays Technology Ltd (Akbari et al. 2006) using the DArT array version 2 and by Victoria Agri-Biosciences Centre, Australia for SNPs using the Infinium iSelect 9k chip. In addition, the DH population was screened with two chromosome 4D Kaspar markers, 10920_kasp9 and HV132-1_kasp9 developed for improving marker coverage of the 4D short arm by

Dr Chris Burt, and two PCR markers developed for the SNPs causing the Rht-B1b and Rht-D1b allele mutations

(Wilhelm 2011).

Construction of a DNA marker linkage map for the ‘Robigus’ x ‘Solstice’ DH population

MapDisto version 1.7.5 Beta 4 (Lorieux 2012) was used to construct a linkage map from 700 DArT, 1902

Infinium iSelect 9k chip SNP markers and the 4 additional Kaspar/PCR markers. Markers that significantly differed from the expected 1:1 segregation ratio were removed from the genotype file before mapping. The

Haldane mapping function, with a maximum recombination fraction of 0.3 and LOD of 6 was used to create the map. Several rounds of remapping were undertaken, where co-segregant markers were removed. The “order sequence” function was run using ripple option and bootstrap analysis.

In order to assign linkage groups to physical chromosomes linkage groups were aligned with existing wheat consensus maps. In total 78.4% of the mapped DArT markers were assigned a chromosomal location (218 out of

278) by reference to the consensus DArT map (Huang et al. 2012) and by searching the DArT BIN maps on the

CerealsDB website (Wilkinson et al. 2012). For the Infinium iSelect SNPs markers 72.7% (314 out of 432) could be assigned a chromosomal location by comparison with the Wang consensus map (Wang et al. 2014).

QTL analyses

QTL analyses were carried out using the QTL package R/qtl, version 1.33-7 (Broman et al. 2003). Predicted means were obtained for each phenotypic data set from the REML analysis, and used as additional data sets in the QTL analyses. Single marker regression (SMR), interval mapping (IM) and composite interval mapping

(CIM) were performed with all ergot phenotypic data sets and plant height. 1000 permutation tests were performed for each phenotypic data set to obtain the 5% LOD significance thresholds. Peak markers identified by SMR and IM were used as co-factors in CIM analyses. Any significant additional QTL were noted and were examined further using a two-dimensional, two-QTL approach.

Two-dimensional, two-QTL scans

Two-dimensional genome scans (Broman et al. 2009) were carried out for the C. purpurea and plant height traits to identify QTL interactions. Where a pair of loci is identified this analysis is able to diagnose additive and/or epistatic interactions. In addition this analysis confirms the presence of two or more loci, especially if the additional loci have a more modest effect. By comparing the outputs of the scantwo function in R/qtl, one emerges with a pair-wise model which can be illustrated graphically using effect plot and dot plot functions within R. All phenotypic traits analysed by the scantwo function were subjected to 1000 permutation tests, and instead of thresholds, significance p-values are presented.

Results

Field assessment of ergot resistance

Fourteen UK winter wheat varieties were assessed for resistance to C. purpurea in inoculated field trials over four growing seasons from 2005 to 2008. Between four and ten varieties were tested every year, some over more than one growing season (Table 1). The total and average sclerotia weight for the wheat varieties ‘Xi-19’,

‘Robigus’, ‘Solstice’, ‘Glasgow’ and ‘Rialto’ are shown in Fig. 1.

While there were some differences in ergot sclerotium formation across the different growing seasons (Year, F prob. < 0.001 for both phenotypic data sets) the wheat varieties showed consistent, significant differences in total and average sclerotial weights, implying an underlying genetic response. The variety ‘Robigus’ produced significantly lower total and average sclerotia weights to ‘Solstice’ (P < 0.001)’, ‘Rialto’ (P < 0.001) and ‘Xi19’

(P = 0.001), but not ‘Glasgow’ (total weight, P = 0.263 and average weight, P = 0.347). As the biggest difference in ergot sclerotia sizes was between ‘Robigus’ and ‘Solstice’, these varieties were selected for genetic mapping to locate loci influencing ergot sclerotial development in hexaploid wheat.

Frequency distributions across the ‘Robigus’ x ‘Solstice’ DH population indicated a normal, quantitative distribution for average sclerotia size (Fig. 2), while the frequency distributions of total and average sclerotia weight were positively skewed, (Fig. 2). Plant height was bi-modally distributed and confirms the postulated presence of different Rht dwarfing alleles in ‘Robigus’ and ‘Solstice’, ‘Robigus’ carrying the Rht-B1b allele at locus Rht-B1 on chromosome 4B, while ‘Solstice’ carries the Rht-D1b allele on chromosome 4D (Figure 5).

Analysis of variance indicated significant differences (F prob. < 0.001) between the parents and the DH lines for all ergot sclerotial phenotypes . Transgressive segregation was apparent for all sclerotial phenotypes, with five

DH lines having significantly (t-test < 0.001) lower sclerotial weights than ‘Robigus’ and 13 lines showing smaller sclerotia at a t-test probability of < 0.001. Heritability values indicated that all three sclerotia phenotypes and plant height had a relatively high genetic component contributing to the phenotypes. The highest h2 values were obtained for average sclerotia weight (h2 = 0.7616) and average sclerotia size (h2 = 0.7242), with total sclerotia weight having a slightly lower h2 value of 0.6212 (all values shown calculated using 2011 field data).

Plant height had an h2 value of 0.9138. The full set of h2 values can be found in Online Resource 2.

Identification of QTL underlying the response to ergot infection in the ‘Robigus’ x ‘Solstice’ cross

A genetic marker map, total length 2895 cM, consisting of 38 linkage groups and representing all 21 chromosomes of hexaploid wheat was constructed for the ‘Robigus’ x ‘Solstice’ cross. The map consisted of

714 loci; 432 Infinium iSelect SNPs and 278 DArTs markers, plus two PCR markers which distinguished the

Rht mutant alleles from the wild type; Rht-D1a/b and Rht-B1a/b (Willhelm 2011), and two additional SNP markers tightly linked to the Rht locus on 4DS. Details of all markers and their positions can be found in Online

Resources 3 and 4.

The QTL reported are those identified using the predicted means and having a LOD value above the global threshold given in Table 3. Three QTL, QCp.niab.2A, QCp.niab.4B and QCp.niab.4D were consistently identified in ‘Robigus’ on chromosomes 2A, 4B and 4D, respectively using the phenotypic data sets for average sclerotia size and average sclerotia weight (Fig. 3). The QTL regions on 4B and 4D were also detected using total sclerotia weight per ear. In general, the percentage phenotypic variance explained by individual QTL was relatively small, ranging from a maximum of 4.76% for QCp.niab.2A, 5.88% for QCp.niab.4B and 13.94% for

QCp.niab.4D. While some QTL were not significant using IM in either 2010 or 2011, all three QTL were significant in both years using CIM (Table 3). A smaller effect QTL, QCp.niab.6A, was detected with the 2010 total sclerotia weight per ear data set in ‘Solstice’ on chromosome 6A. QCp.niab.6A had a LOD of 3.49 and a percentage variance of 3.14%.

As ‘Robigus’ and ‘Solstice’ were known to carry different semi-dwarfing alleles, ‘Robigus’ having Rht-B1b

(located on chromosome 4B) and ‘Solstice’ having Rht-D1b (located on chromosome 4D), plant height was mapped in the ‘Robigus’ x ‘Solstice’ DH population. CIM identified two QTL for plant height, QPh.niab.4B and QPh.niab.4D on chromosomes 4B and 4D, respectively, where the PCR markers Rht-B1b and Rht-D1b were the peak markers. In 2010 QPh.niab.4B and QPh.niab.4D accounted for 6.95% and 13.79% of the phenotypic variance in plant height, while in 2011 they accounted for 24.01% and 31.70%, respectively.

Interestingly, a QTL for plant height was also identified with the 2010 plant height data set in the same region as

QCp.niab.6A, with the height-reducing allele and the resistance allele both coming from ‘Solstice’ (Online

Resource 5).

Two-dimensional, two-QTL scans were undertaken to identify pair-wise interactions between QTLs (Online

Resource 6). These analyses identify additive effects (LODav1) between QTL, where the presence of two genes

(usually from different pathways) has a straightforward additive effect on the phenotype. They also identify epistatic-interacting effects (LODi) where the effect of one QTL can only be shown in the presence of another, usually explained by their sequential action in the same pathway. These analyses were undertaken using the average sclerotia size and plant height data sets. Additive effects were seen with the QTL for average sclerotia size, the largest effect being seen with the 2010 data set between QTL QCp.niab.4B and QCp.niab.4D (LODav1

= 6.81; P < 0.001). With the 2011 average sclerotia size data set, the same QTL interaction had a LODav1 = 3.01; however this was just over the significance threshold with a p-value of 0.172. An additive interaction was also seen between QCp.niab.2A and QCp.niab.4B, with both the 2010 (LODav1 = 3.03; P = 0.072) and 2011 (LODav1

= 3.93; P = 0.037) data sets, however no interaction was identified between QCp.niab.2A and QCp.niab.4D. To visualise the QTL additive effects for average sclerotia size dot plots of the phenotypic averages of the lines carrying the QTL QCp.niab.2A, QCp.niab.4B and QCp.niab.4D alone or in combination are presented (Fig. 4).

Two-dimensional, two-QTL scans suggested that the relationship between the plant height QTL QPh.niab.4B and QPh.niab.4D is both epistatic (2010, LODi = 16.01; P < 0.001 and 2011, LODi = 7.84; P < 0.001) and additive (2010, LODav1 = 23.97; P < 0.001 and 2011, LODav1 = 11.79; P < 0.001) (Online Resource 6). An additional height QTL to QPh.niab.4B and QPh.niab.4D was identified using two-dimensional two-QTL analysis on chromosome 2B, designated QPh.niab.2B, which has an epistatic interaction with QPh.niab.4B

(LODi = 7.37; P < 0.001), further reducing the height of Rht-B1b carrying plants (Online Resource 5). The dependence of expression of a phenotype for QPh.niab.2B on the presence of QPh.niab.4B may indicate why

QPh.niab.2B was not detected by IM alone.

Discussion

Ergot is a plant disease of considerable importance to human and animal health due to the toxic effects of alkaloids present in the sclerotia (De Costa 2002). Few sources of genetic resistance to C. purpurea have been reported, with the best source of resistance identified to date being found in a durum wheat genotype (Menzies

2004). In this study we report genetic variation in the response of hexaploid wheat varieties to C. purpurea and identify interacting QTL in the varieties ‘Robigus’ and ‘Solstice’ that influence the size and weight of sclerotia produced by C. purpurea.

Together the three QTL QCp.niab.2A, QCp.niab.4B and QCp.niab.4D at best only explained 24.6% of the phenotypic variation for sclerotial weight (2010 data set), while dividing the percentage phenotypic variance by its corresponding heritability value (h2 = 0.78) gave a maximum genetic variation of 31.7%. This implies that the majority of the genetic variation affecting ergot development and sclerotium formation in the ‘Robigus’ x

‘Solstice’ population was not detectable. This is likely due to the presence of many small genetic influences affecting sclerotial development, each genetic locus producing a phenotypic effect below the current resolution of QTL analysis, which is limited by the modest size of the population.

The QTL with the largest effect, QCp.niab.4B and QCp.niab.4D, mapped to the same location as the Reduced

Height (Rht) loci Rht-B1 and Rht-D1 (Peng et al. 1999), with the resistance effect co-segregating with the dwarfing alleles Rht-B1b (from ‘Robigus’) and Rht-D1b (from ‘Solstice’), respectively. As a result, the general trend was for shorter DH lines to produce smaller sclerotia, although there was significant overlap in the sclerotial size distributions of tall, semi-dwarf and double-dwarf plant size classes indicating the presence of additional genes, not linked to height, influencing sclerotia size (Fig. 5).

Rht-B1 and Rht-D1 encode for DELLA proteins (Peng et al. 1999). In Arabidopsis DELLA proteins have been shown to be nuclear-located and are putative transcriptional regulators that interact with the gibberellic acid receptor protein GID1 (GA-Insensitive Dwarf), resulting in growth repression. In the presence of gibberellic acid (GA) the DELLA proteins are degraded via the 26S proteasome SCF complex, resulting in subsequent stimulation of plant growth (Dill et al. 2004). The gain-of-function dwarfing alleles Rht-B1b and Rht-D1b produce GA-insensitive mutant DELLA proteins, resulting in a partially stable pool of DELLA protein that continues to suppress plant growth, producing semi-dwarfed plants (Pearce et al. 2011).

The association between QCp.niab.4B and Rht-B1b, and QCp.niab.4D and Rht-D1b may be pleiotropic, i.e. the same locus affects both sclerotium formation and plant height, or could be due to close genetic linkage of functionally independent genes. In the latter case, height and ergot resistance should be genetically separable if a sufficiently high resolution mapping approach was brought to bear. If the former is the case, attention should be devoted to testable hypotheses that might flow from a postulated pleiotropy between wheat DELLA function and ergot sclerotia size. Although neither scenario can be ruled out, some further observations lend more weight to the pleiotropy scenario.

Firstly, wheat DELLA/Rht genes have been demonstrated to have potential pleiotropic effects on disease resistance to multiple pathogens, with gain-of-function mutant alleles conferring increased susceptibility to biotrophic pathogens and increased resistance to necrotrophic pathogens (Saville et al. 2011). In Arabidopsis,

DELLA mutants have been shown to suppress hypersensitive cell death, leading to increased resistance to necrotrophic pathogens and increased susceptibility towards pathogens with a biotrophic life stage (Navarro et al. 2008). In the wheat-Fusarium Head Blight (FHB) pathosystem, the semi-dwarfing alleles Rht-B1b and Rht-

D1b were associated with decreased resistance to primary infection (Type I resistance) of wheat florets by

Fusarium species, with the early stages of Fusarium infection currently thought to represent a biotrophic phase

(Hilton et al. 1999; Draeger et al. 2007, Srinivasachary et al. 2009). However, while C. purpurea is considered a biotroph, in the present study the Rht gain-of-function mutant alleles were associated with increased resistance and not susceptibility. The Rht alleles therefore have contrasting effects on the infection of florets and ovules by

C. purpurea and Fusarium species.

Secondly, the association between ergot resistance and GA-regulated plant height may not be confined to the

Rht-D1 and Rht–B1 loci, as the small effect QTL QCp.niab.6A was detected with both the plant height and total sclerotia weight per ear phenotypic data sets, with the ‘Solstice’ allele being responsible for both reduced sclerotia and reduced height. Previous studies have identified plant height genes on chromosome 6A (Watanabe

2008), the alleles Rht14, Rht16 and Rht18 at this locus conferring GA-sensitive reduced plant height.

Unfortunately, we were not able to confirm a common location for QCp.niab.6A and the plant height QTL reported on chromosome 6A (Watanabe 2008).

Thirdly, there seems to be a more general association between hormone signalling and quantitative development of ear diseases in wheat. A QTL for Type I FHB resistance has also been reported on chromosome 2A, however common markers were not available to compare the position of this QTL with the ergot resistance QTL

QCp.niab.2A found in this study (Lin et al. 2006, Diethelm et al. 2014). Characterisation of the peak marker for the 2A FHB QTL suggests that the gene underlying the QTL may be a wheat homologue of NPR1 (non- expresser of pathogenesis related protein 1) (Diethelm et al. 2014). NPR1 is at the heart of hormonal cross-talk between the salicylic acid (SA) and jasmonic acid (JA) pathways, being involved in the SA-mediated suppression of the JA pathway (Spoel et al. 2003). The functional annotation of transcripts differentially expressed between ovaries inoculated with C. purpurea versus mock-inoculated ovaries in RNA-Seq experiments also highlights hormone signalling as one of the most responsive functional categories (unpublished data).

Gibberellins play a crucial role in many aspects of plant development. Active forms of these phytohormones are known to control processes such as seed germination, stem elongation, floral development and anther extrusion

(Cheng et al. 2004, Peng et al. 1997). C. purpurea may have evolved an ability to manipulate the endogenous host hormone signalling pathways to command the resources necessary to produce sclerotia many times the fresh weight of a fully developed grain. Mutations in key hormone signalling pathway genes, such as the Rht-

B1b and Rht-D1b alleles, are therefore attractive candidates that could explain how the ability to re-programme host resource allocation is partly compromised in the absence of any symptoms resembling a typical immune response. In the case of the Rht mutants one may speculate that perturbed GA levels may interact with normal mechanisms by which C. purpurea colonise floral tissues, resulting in altered levels of colonisation. In semi- dwarf and dwarf lines GA levels increase in expanding leaf tissues (Appleford and Lenton 1991, Wu et al.

2011), but to our knowledge GA levels in ovule tissue pre-pollination have never been measured and are a potential avenue of further investigation.

An alternative hypothesis is that C. purpurea produces and exudes its own GA which acts as a pathogenicity factor (for example by triggering an increase in the nutrient flow into the ovule tissue resulting in larger sclerotia). In this regards, it is noteworthy perhaps that the reference Claviceps purpurea genome (reference

Helmholtz genome dB and Schardl et al, 2013)possesses a duplicated GA synthesis gene cluster with similarity to that found in the GA-synthesizing pathogen Fusarium fujikori (Tudzynski & Hölter, 1998, Tudzynski 2005). We have shown that these genes are highly expressed in the first 7 days of infection (A. Gordon, manuscript in

16 preparation). So in the case of the Rht mutants one may speculate that host GA insensitivity has the serendipitous consequence of reducing response to an exogenous pathogen-derived GA signal required to develop full potential sclerotial size.

Figure Legends

Fig. 1 Inoculated field trial data showing the mean across replicates for total sclerotia weight per ear and average sclerotia weight for five UK winter wheat varieties. Data was collected from replicated field trials over

4 years, from 2005 to 2008. Error bars show the standard error between replicates, apart from 2006, where all replicates of sclerotia were pooled together before weighing

Fig. 2 Distribution of total sclerotia weight per ear, average sclerotia size, average sclerotia weight and plant height phenotypes in the ‘Robigus’ x ‘Solstice’ double haploid population. Arrowheads indicate the phenotypic averages of the parents

Fig. 3 QTL positions for ergot sclerotia total and average weights, sclerotia size and plant height in the

‘Robigus’ x ‘Solstice’ cross following CIM or IM analysis. QTL positions are shown to the right of the linkage maps on chromosomes 2A, 4B, 4D and 6A. QTL bars represent 1.5 LOD support intervals around the peak score marker. Marker locations are shown to the left of each linkage map, along with marker number, chromosome identifier and position in centimorgans from the top of the linkage group. The full marker names can be found in Table S1

Fig. 4 Phenotypic distribution for sclerotia size in ‘Robigus’ x ‘Solstice’ doubled haploid lines carrying one or more of the three major QTL contributing to reduced sclerotia size, QCp.niab.2A, QCp.niab.4B and

QCp.niab.4D. The peak marker used to identify each QTL, the QTL parental origin and chromosomal location are indicated above each plot. Phenotypic data from 2010 and 2011 field trials is shown. Error bars are ± 1 standard errors

Fig. 5 Relationship between ergot sclerotia size and plant height in doubled haploid lines from the cross

‘Robigus’ x ‘Solstice’, 2011 data set. The Rht-B1 and Rht-D1 a (wild-type) and b (dwarf mutant) alleles carried by each line are indicated. ‘Robigus’ genotype Rht-B1b/Rht-D1a and ‘Solstice’ genotype Rht-1Ba/Rht-1Db

Table 1 UK winter wheat varieties screened for ergot resistance in inoculated field trials

Table 2 Claviceps purpurea isolates

Table 3 QTL identified in the ‘Robigus’ x ‘Solstice’ cross for ergot sclerotia development and plant height

Electronic Supplementary Material / Online Resources

Online Resource 1 The NIAB ergot sclerotia sizing scale

Online Resource 2 Heritability of all traits recorded from the Robigus x Solstice population over two years of field trials. h2 = Vg/(Vg+Ve). Variance components were estimated by REML as implemented within GenStat (Payne et al 2009)

Online Resource 3 ‘Robigus’ x ‘Solstice’ genetic map, including co-segregating markers. Online Resource 4 Complete linkage map of the ‘Robigus’ x ‘Solstice’ doubled haploid population, consisting of 38 linkage groups, representing all 21 chromosomes of hexaploid wheat and having a total length of 2895 cM. Marker locations are shown to the right of each linkage group along with marker number, chromosome identifier and position in centimorgans from the top

Online Resource 5 (a) Dot plots showing the effect of QCp.niab.6A on total sclerotia weight and

QPh.niab.6A on plant height in 2010. Doubled haploid lines with the ‘Solstice’ allele at the QTL positions on chromosome 6A have lower total sclerotia weights and are shorter. (b) Effect plot and dot plot for QPh.niab.4B and its interacting partner QPh.niab.2B showing epistatic effects on plant height. QPh.niab.2B only reduces height in the presence of QPh.niab.4B

Online Resource 6 Summary of outputs from two-dimensional, two-QTL scans

Table 1 Winter wheat varieties screened for ergot resistance in inoculated field trials

Year of Number of ears per variety Wheat varieties screened field trial inoculated with Claviceps purpurea

10 ears (2 reps) Caphorn, Drifter, Paragon, Rialto, Robigus, 2004/05 Variable number of florets inoculated Solstice, Tommi, Welford, Xi19 per ear

3 ears (4 reps) Apache, Caphorn, Drifter, Paragon, Rialto, 2005/06 20 florets inoculated per ear Robigus, Solstice, Tommi, Welford, Xi19

12 ears (2 reps) Brompton, Cordiale, Glasgow, Mascot, 2006/07 10 florets inoculated per ear Rialto, Robigus, Solstice, Xi19

10 ears (1 rep) 2007/08 Glasgow, Robigus, Solstice, Xi19 20 florets inoculated per ear

Table 2 Claviceps purpurea isolates used in inoculated field trials (Bayles et al, 2008)

Isolate Year of Location Plant host name collection

04-02 2004 Cambridge Blackgrass (Alopecurus myosuroides)

04-29 2004 Little Saxham, Suffolk Wheat (cv. Hereward)

04-97 2004 Long Hoos IV, Rothamsted Blackgrass (Alopecurus myosuroides)

03-20 2003 Elm Farm, Cirencester Wheat (cv. Chablis) 03-43 2003 Elm Farm, Wakelyn’s, Suffolk Wheat (cv. Claire)

Table 3 QTL identified in the ‘Robigus’ x ‘Solstice’ cross for ergot sclerotia development and plant height

QTL Chromosome Peak Marker Position LOD %Variance aParental bPhenotypic cQTL Analysis designation location (cM) value explained Allele data set QCp.niab.2A 2A wsnp_BQ168780B_Ta_2_1 108 4.631 4.17 R 2010-SS SMR,IM,CIM wsnp_Ex_c2337_4379619 134 3.899 2.47 2011-SS SMR,IM, CIM wsnp_BQ168780B_Ta_2_1 108 5.28 4.76 2010-SW SMR,IM, CIM QCp.niab.4B 4B Rht-B1b 72.76 4.827 4.35 R 2010-SS CIM wsnp_CAP12_c13_8078 70.9 6.497 4.11 2011-SS SMR,IM, CIM Rht-B1b 72.0 6.527 5.88 2010-SW CIM wsnp_CAP12_c13_8078 70.9 8.52 5.39 2011-SW SMR,IM, CIM wsnp_CAP12_c13_8078 70.9 5.1 4.62 2010-TW CIM QPh.niab.4B Rht-B1b 72.75 11.67 6.95 2010-PH CIM Rht-B1b 72.75 24.25 24.0 2011-PH SMR,IM, CIM QCp.niab.4D 4D Rht-D1b 13 13.53 12.19 S 2010-SS SMR,IM, CIM Rht-D1b 8 3.45 2.19 2011-SS CIM Rht-D1b 14 15.4 13.94 2010-SW SMR,IM, CIM Rht-D1b 12 12.07 10.87 2010-TW SMR,IM, CIM QPh.niab.4D Rht-D1b 9 23.16 13.79 2010-PH SMR,IM, CIM Rht-D1b 9 32.01 31.70 2011-PH CIM QCp.niab.6A 6A wPt-665636_NA 0 3.49 3.14 S 2010-TW SMR

QPh.niab.6A wPt-665636_NA 0 4.76 2.83 2010-PH SMR, IM aThe contributing parental alleles, R = ‘Robigus’ and S = ‘Solstice’ confer smaller sclerotia and shorter plants. bPhenotypic data codes: SS - Average Sclerotia Size; SW - Average Sclerotia Weight; TW - Total Sclerotial Weight per Ear; and PH - Plant Height. cQTL analyses were performed using single marker regression (SMR), Interval Mapping (IM) and Composite Interval Mapping (CIM). The position of the QTL is shown in centimorgans (cM).

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Figure 2 Click here to download Figure: Fig 2.pptx

Total Sclerotia Weight per Ear 2010 / g Total Sclerotia Weight per Ear 2011 / g

Robigus: 0.147 g Robigus: 0.296 g

Solstice: 0.212 g

Solstice: 0.461 g

Average Sclerotia Size 2010 Average Sclerotia Size 2011 Robigus 3.38 Robigus 4.07 Solstice 4.5 Solstice: 4.24

Average Sclerotia Weight 2010 / mg Average Sclerotia Weight 2011 / mg

Robigus 14.33 Robigus 27.5

Solstice 40.96

Solstice 37.5

Plant Height 2010 / cm Plant Height 2011 / cm

Solstice 67.5 Solstice 62.0

Robigus 58.46

Robigus 73.5 Figure 3 Click here to download Figure: Fig 3.pptx

2A 6A 4B 4D

2010 2010 1_2A_0 1_6A_0 1_4B_0.0 1_4D_0.0

2_2A_0.6 2_4B_2.0

2010 2011 2010 2010 2010 3_2A_1.2 2011 4_2A_1.8 2_6A_6.6 2_4D_5.5 5_2A_3.8 3_6A_7.9 4_6A_8.5 3_4D_10.3 Rht-D1 6_2A_4.4 5_6A_9.2 6_6A_11.3 7_6A_13.5 8_6A_14.1 9_6A_14.7 4_4D_19.7 10_6A_15.4 11_6A_16.1 12_6A_16.9 5_4D_24.7 7_2A_31.8 13_6A_17.7 3_4B_30.1 8_2A_32.4 14_6A_23.4 6_4D_33.5 7_4D_34.1 8_4D_40.3

15_6A_42.9 2010 16_6A_44.9 9_4D_43.6 17_6A_48.6 4_4B_50.5 18_6A_49.2 5_4B_51.1 19_6A_49.8

6_4B_58.2 2011 20_6A_50.4 7_4B_58.9 2010 21_6A_52.2 2011 22_6A_52.8 8_4B_60.2

9_2A_64.6 23_6A_53.5 9_4B_60.8

2010 2010 24_6A_54.7 2011 25_6A_55.4 10_4B_68.5

10_2A_72.4 26_6A_56.9 11_4B_69.7 2010

11_2A_74.9 2010 27_6A_58.3 12_4B_70.9 28_6A_58.9 12_2A_77.6 29_6A_59.6 13_4B_72.8 Rht-B1 30_6A_61 14_4B_80.7 31_6A_63.7 15_4B_82.6 32_6A_65 33_6A_65.6 16_4B_87.7 13_2A_90.6 34_6A_66.2 14_2A_94.8 35_6A_66.9 17_4B_92.8 15_2A_96.7 36_6A_69.8 37_6A_72.1 16_2A_97.3 38_6A_82.7 17_2A_98.5 18_2A_101 19_2A_112.4 2011 18_4B_109.8 20_2A_113.6 21_2A_114.2 19_4B_115.0 22_2A_119 23_2A_120.2 24_2A_126.6 Total Sclerotia weight per ear 25_2A_127.9 26_2A_128.5 Sclerotia weight 27_2A_129.1 28_2A_129.7 29_2A_130.9 Sclerotia size 30_2A_134 31_2A_136.5 32_2A_138.4 Plant height 33_2A_148.6 34_2A_156.5 35_2A_158.3 36_2A_164.3

37_2A_183.6 Figure 4 Click here to download Figure: Fig 4.pptx 2A Origin: Robigus Peak marker: wsnp_BQ168780B_Ta_2_1 4B Origin: Robigus Peak marker: Rht-B1 4D Origin: Solstice Peak marker: Rht-D1

QCp.niab.2A QCp.niab.2A QCp.niab.2A QCp.niab.2A QCp.niab.2B QCp.niab.4B NULL QCp.niab.4D QCp.niab.4B QCp.niab.4B QCp.niab.4D QCp.niab.4D QCp.niab.4D

2A Origin: Robigus Peak marker: wsnp_Ex_c2337_4379619 4B Origin: Robigus Peak marker: wsnp_CAP12_c138078 4D Origin: Solstice Peak marker: Rht-D1

QCp.niab.2A QCp.niab.2A QCp.niab.2A QCp.niab.2A QCp.niab.2B QCp.niab.4B NULL QCp.niab.4D QCp.niab.4B QCp.niab.4B QCp.niab.4D QCp.niab.4D QCp.niab.4D Figure 5 Click here to download Figure: Fig 5.pptx

B1bD1a Robigus genotype 60

B1aD1a Tall genotype Plant height cm /

50 B1aD1b Solstice genotype

B1bD1b Double dwarf genotype 40

30 2 2.5 3 3.5 4 4.5 5 5.5 Ergot Sclerotia Size Online Resource 1 Click here to download Supplementary Material (builds into PDF): ESM_1.pptx Online Resource 3 2A 5A 6A 1ALClick here to download Supplementary Material3A (builds into PDF):4A ESM_3.pptx 7AS Map size : 183.61 cM Map size : 212.63 cM Map size : 251.75 cM Map size : 31.52 cM Map size : 12.51 cM Map size : 165.36Loci cM Map size : 82.69 cM 1_2A_0 1_3A_0 2_2A_0.6 1_4A_0 1_5A_0 3_2A_1.2 2_3A_3.9 1_6A_0 1_7AS_0 1_1AL_0 4_2A_1.8 3_3A_4.6 2_7AS_1.2 2_1AL_2.1 4_3A_6 3_7AS_3.1 3_1AL_2.7 5_2A_3.8 5_3A_8.7 2_6A_6.6 6_3A_10.8 3_6A_7.9 4_1AL_3.3 6_2A_4.4 4_6A_8.5 5_1AL_4.5 5_6A_9.2 4_7AS_11 6_1AL_12.5 6_6A_11.3 2_5A_17 7_6A_13.5 5_7AS_15.7 8_6A_14.1 2_4A_22.6 3_5A_22.4 9_6A_14.7 7_3A_25.3 3_4A_23.2 4_5A_25.1 10_6A_15.4 6_7AS_21.2 1AL 8_3A_27.4 4_4A_26.9 11_6A_16.1 7_7AS_21.9 12_6A_16.9 8_7AS_22.5 9_3A_29.9 5_5A_30.8 13_6A_17.7 9_7AS_23.2 Map size : 19.38 cM 7_2A_31.8 5_4A_31.9 14_6A_23.4 10_7AS_23.8 8_2A_32.4 11_7AS_25.2 12_7AS_26 6_5A_38 13_7AS_27.4 14_7AS_28.8 7_1AL_0 7_5A_43.2 15_7AS_29.4 8_1AL_0.7 10_3A_44.7 15_6A_42.9 16_7AS_31.5 9_1AL_2 11_3A_48.1 6_4A_46.5 8_5A_47.7 16_6A_44.9 10_1AL_3.4 9_5A_48.3 11_1AL_4 17_6A_48.6 18_6A_49.2 19_6A_49.8 7A 20_6A_50.4 12_3A_58.3 21_6A_52.2 22_6A_52.8 Map size : 143.65 cM 12_1AL_19.4 13_3A_65.4 10_5A_63.3 23_6A_53.5 11_5A_64.6 24_6A_54.7 9_2A_64.6 25_6A_55.4 26_6A_56.9 10_2A_72.4 27_6A_58.3 1_7A_0 14_3A_74.1 28_6A_58.9 11_2A_74.9 29_6A_59.6 12_2A_77.6 15_3A_78.8 30_6A_61 2_7A_6.3 1A 12_5A_79.4 31_6A_63.7 3_7A_7 13_5A_81.2 32_6A_65 14_5A_83.1 33_6A_65.6 4_7A_11.4 Map size : 124.54 cM 16_3A_85.7 34_6A_66.2 5_7A_12.6 17_3A_86.3 15_5A_86.1 35_6A_66.9 6_7A_13.8 18_3A_86.9 7_4A_88.3 36_6A_69.8 7_7A_15.1 19_3A_90.6 8_4A_88.9 8_7A_15.7 13_2A_90.6 20_3A_92 16_5A_91.9 37_6A_72.1 21_3A_92.7 9_4A_92.6 38_6A_82.7 9_7A_17 1_1A_0 10_4A_94.5 10_7A_20.4 2_1A_2.1 14_2A_94.8 22_3A_94 11_7A_22.3 15_2A_96.7 23_3A_94.6 12_7A_22.9 3_1A_2.8 16_2A_97.3 24_3A_95.2 4_1A_3.4 17_2A_98.5 25_3A_95.8 11_4A_101.7 13_7A_30 5_1A_4.8 18_2A_101 26_3A_97 12_4A_103.7 14_7A_31.3 6_1A_8.7 27_3A_105.2 13_4A_105.6 15_7A_32.5 28_3A_108.4 14_4A_108 16_7A_33.1 17_7A_34.3 29_3A_110.4 15_4A_108.6 18_7A_34.9 7_1A_18.8 19_2A_112.4 16_4A_113.1 19_7A_35.5 8_1A_20.2 20_2A_113.6 17_4A_113.7 20_7A_36.1 9_1A_21 21_2A_114.2 21_7A_39.3 10_1A_22.3 22_2A_119 18_4A_119.4 17_5A_122.5 22_7A_40.5 11_1A_23.6 23_2A_120.2 19_4A_121.9 23_7A_41.1 12_1A_24.8 24_7A_43.6 13_1A_26.1 25_7A_46.1 24_2A_126.6 18_5A_125.8 26_7A_46.7 25_2A_127.9 20_4A_129.3 27_7A_48 26_2A_128.5 28_7A_48.6 27_2A_129.1 30_3A_135.5 21_4A_134.6 19_5A_132.9 29_7A_49.9 28_2A_129.7 20_5A_133.5 30_7A_50.5 22_4A_135.2 31_7A_51.2 14_1A_43.2 29_2A_130.9 23_4A_135.9 21_5A_136.7 30_2A_134 31_3A_141.3 24_4A_138.1 22_5A_137.3 32_7A_53.3 15_1A_46.7 31_2A_136.5 33_7A_60.6 32_2A_138.4 34_7A_70.9 23_5A_144.4 35_7A_74.8 32_3A_148.7 25_4A_148 24_5A_145.6 36_7A_76 33_2A_148.6 26_4A_148.7 25_5A_147.4 16_1A_56.2 27_4A_149.4 26_5A_149.8 28_4A_150.1 17_1A_60.3 29_4A_152.1 34_2A_156.5 30_4A_153.3 27_5A_156.4 35_2A_158.3 31_4A_153.9 32_4A_154.5 18_1A_68.8 36_2A_164.3 33_3A_165.4 33_4A_155.1 37_7A_92.7 19_1A_70.6 34_3A_166 34_4A_157.1 38_7A_93.3 20_1A_71.8 35_3A_167.3 35_4A_157.8 39_7A_94.7 21_1A_74.6 36_4A_165.4 40_7A_96.7 22_1A_75.3 41_7A_97.4 23_1A_78 28_5A_172.4 42_7A_101.5 24_1A_78.6 29_5A_173.1 25_1A_79.9 30_5A_173.7 26_1A_81.2 31_5A_174.3 27_1A_83.3 32_5A_175.6 28_1A_84.5 37_2A_183.6 29_1A_85.1 43_7A_115.3 30_1A_88.5 31_1A_90.6 44_7A_120.1 32_1A_98.5 36_3A_195.9 45_7A_120.7 33_1A_101.3 33_5A_195.2 46_7A_124.4 37_3A_200.1 34_5A_196.5 47_7A_126.9 34_1A_103.9 48_7A_128.9 35_1A_104.5 38_3A_204.1 49_7A_130.2 36_1A_105.8 50_7A_132 37_1A_106.4 39_3A_206.1 38_1A_107.6 40_3A_209.2 39_1A_108.3 40_1A_110.2 41_3A_212.6 41_1A_113.4 51_7A_143.7

42_1A_124.5 35_5A_220

36_5A_225.2 37_5A_225.8

38_5A_251.1 39_5A_251.7 3BS 1BS 2B 3BL 4B 5BS 6B 7B Map size : 55.95 cM Map size : 193.59 cM Map size : 178.40 cM Map size : 76.56 cM Map size : 115.0 cM Map size : 127.94 cM Map size : 108.28 cM Map size : 118.25 cM

1_7B_0 1_1BS_0 1_2B_0 1_3BL_0 1_4B_0.0 1_5BS_0 1_6B_0 2_2B_0.7 1_3BS_0 2_4B_2.0 2_5BS_1.2 3_2B_2.2 3_5BS_1.8 4_2B_2.9 2_3BS_4.3 2_3BL_6.9 3_3BS_6.2 2_7B_8.4 5_2B_3.5 3_3BL_7.6 4_5BS_9 6_2B_4.2 4_3BL_10.5 5_5BS_11.6 2_6B_10.9 7_2B_4.9 4_3BS_11.3 3_6B_11.5 8_2B_5.6 5_3BL_13.2 6_5BS_13 6_3BL_13.8 5_3BS_11.9 4_6B_12.9 9_2B_7.7 6_3BS_14.9 7_5BS_16.1 2_1BS_17.6 7_3BL_17.6 5_6B_13.6 10_2B_8.3 7_3BS_17.3 8_5BS_18.9 6_6B_15.6 3_1BS_20.5 11_2B_11.4 8_3BL_18.2 8_3BS_18.7 4_1BS_21.1 9_3BL_20.1 7_6B_16.3 12_2B_12 9_5BS_23.3 5_1BS_23.9 13_2B_19.1 10_3BL_20.7 6_1BS_24.6 11_3BL_21.3 9_3BS_23.7 10_5BS_25.3 7_1BS_26.7 12_3BL_21.9 8_1BS_28 13_3BL_27.7 3_4B_30.1 14_3BL_28.9 8_6B_32.4 15_3BL_30.2 11_5BS_35.5 9_6B_34.4 16_3BL_30.9 10_6B_35.1 9_1BS_37.9 17_3BL_32.2 10_1BS_38.5 11_6B_35.7 3_7B_39.5 18_3BL_33.5 12_5BS_39.9 12_6B_36.3 19_3BL_34.1 4_7B_42.3 13_6B_36.9 5_7B_42.9 11_1BS_44 20_3BL_34.7 14_6B_37.5 12_1BS_45.3 21_3BL_35.3 15_6B_39.3 6_7B_47 22_3BL_36.5 13_5BS_47.7 7_7B_48.4 14_5BS_48.3 16_6B_39.9 23_3BL_37.1 4_4B_50.5 17_6B_40.5 24_3BL_37.7 10_3BS_50.3 5_4B_51.1 15_5BS_48.9 16_5BS_50.1 18_6B_41.2 25_3BL_38.3 11_3BS_51 19_6B_42.6 13_1BS_55.3 26_3BL_38.9 6_4B_58.2 17_5BS_52.1 14_1BS_55.9 18_5BS_52.8 20_6B_48.3 8_7B_57.6 14_2B_58.2 27_3BL_39.5 7_4B_58.9 21_6B_49 28_3BL_40.2 19_5BS_56.4 9_7B_60 15_2B_61.5 29_3BL_40.9 12_3BS_59.9 8_4B_60.2 20_5BS_57.8 10_7B_61.5 30_3BL_41.5 13_3BS_60.6 9_4B_60.8 21_5BS_63.3 22_6B_63.5 11_7B_62.2 31_3BL_42.1 14_3BS_62.6 22_5BS_64.1 23_6B_65.4 12_7B_65.3 32_3BL_42.7 10_4B_68.5 23_5BS_64.8 13_7B_69.1 24_5BS_65.5 33_3BL_43.3 15_3BS_69.1 11_4B_69.7 24_6B_69.8 1BL 34_3BL_50.6 16_3BS_69.8 25_5BS_71.9 25_6B_71.7 14_7B_72.5 35_3BL_51.2 17_3BS_70.4 12_4B_70.9 36_3BL_53.4 18_3BS_71.6 13_4B_72.8 Map size : 73.80 cM 37_3BL_56.6 19_3BS_73.4 38_3BL_58.1 20_3BS_75.2 14_4B_80.7 26_6B_79.7 15_7B_81.1 39_3BL_61.6 21_3BS_76.6 27_6B_80.9 40_3BL_71.6 15_4B_82.6 41_3BL_74.1 28_6B_85.5 42_3BL_81.9 16_4B_87.7 29_6B_86.7 1_1BL_0 43_3BL_86.4 26_5BS_89.8 17_4B_92.8 27_5BS_91.7 16_2B_93 2_1BL_5.4 30_6B_95.3 44_3BL_96.7 3_1BL_6 17_2B_97.6 4_1BL_7.9 5_1BL_11.6 18_2B_100.6 6_1BL_12.2 19_2B_101.2 7_1BL_13.4 20_2B_101.8 16_7B_106.7 21_2B_104.3 8_1BL_14 31_6B_108.3 17_7B_107.3 9_1BL_14.6 22_2B_107.4 18_4B_109.8 18_7B_110 10_1BL_15.2 23_2B_108.1 28_5BS_111.2 19_7B_112.6 11_1BL_16.5 24_2B_109.4 19_4B_115.0 12_1BL_17.7 25_2B_110 13_1BL_18.3 26_2B_110.6 29_5BS_117.5 20_7B_118.2 14_1BL_18.9 27_2B_111.9 15_1BL_19.5 28_2B_112.5 16_1BL_22 29_2B_113.2 17_1BL_25.3 30_2B_114.4 18_1BL_28.8 31_2B_115 30_5BS_127.9 19_1BL_31.3 32_2B_116.5 20_1BL_32.5 33_2B_117.2 21_1BL_34.5 34_2B_123.7 45_3BL_132.7 22_1BL_38.1 35_2B_124.9 46_3BL_133.4 6BS 23_1BL_39.5 36_2B_126.7 47_3BL_135.5 7BS 24_1BL_43.5 37_2B_127.3 48_3BL_136.9 25_1BL_45.4 38_2B_128.6 49_3BL_138.9 5BL Map size : 5.85 cM Map size : 5.39 cM 26_1BL_46 39_2B_132.4 40_2B_133.8 27_1BL_47.2 50_3BL_146.1 Map size : 63.48 cM 28_1BL_53 41_2B_141.8 29_1BL_56.3 42_2B_146.7 51_3BL_148.9 30_1BL_61.9 52_3BL_150.9 1_6BS_0 1_5BL_0 2_6BS_0.7 1_7BS_0 3_6BS_2 31_1BL_65.6 2_5BL_3.7 2_7BS_2.1 32_1BL_67.7 4_6BS_5.2 3_7BS_3.4 33_1BL_68.3 5_6BS_5.9 4_7BS_5.4 34_1BL_70.4 35_1BL_73.8

43_2B_174.3 53_3BL_174.7 44_2B_174.9 45_2B_177 46_2B_178.3 54_3BL_178.4 3_5BL_27.2 47_2B_181.4 4_5BL_29.1 5_5BL_29.8 48_2B_186.5 6_5BL_33.3 7_5BL_35.4 49_2B_190.2 8_5BL_36.7 50_2B_190.8 9_5BL_38 51_2B_191.4 52_2B_192.9 53_2B_193.6

10_5BL_61.6 11_5BL_62.2 12_5BL_63.5 1D 2D 3D 4D 5D 6D 7D Map size : 118.34 cM Map size : 80.89A cM Map size : 43.6 cM Map size : 49.31 cM Map size : 62.12 cM Map size : 10.56 cM Map size : 43.90 cM

1_2D_0 1_1D_0 2_2D_0.7 1_3D_0 1_4D_0.0 1_6D_0 1_5D_0 2_3D_4.6 1_7D_0 2_4D_5.5 2_5D_2.9 2_7D_1.3 3_3D_6.8 2_6D_5.8 3_7D_2 2_1D_7.7 4_3D_7.4 3_6D_6.4 4_7D_2.6 3_1D_8.9 5_3D_8.1 3_4D_10.3 4_6D_10.6 4_1D_11.6 6_3D_9.5 5_7D_8.9 5_1D_12.9 3_2D_17.4 7_3D_10.1 3_5D_12.5 4_2D_19.4 8_3D_11.5 4_5D_13.9 9_3D_12.1 10_3D_13.6 4_4D_19.7 6_1D_21 5_2D_24.5 11_3D_14.4 12_3D_15.2 5_4D_24.7 7_1D_26.1 13_3D_17.4

5_5D_29 8_1D_32.8 6_4D_33.5 9_1D_36 6_2D_39.3 7_4D_34.1 7_2D_40 10_1D_40.5 8_4D_40.3 11_1D_41.8 9_4D_43.6 12_1D_42.4 13_1D_47.1 6_7D_43.9 14_1D_48.4 14_3D_49.3

15_1D_55.7 16_1D_58.4 17_1D_59.1 18_1D_61.7 6_5D_62.1

8_2D_80.9 5DL 19_1D_79.9 20_1D_80.5 Map size : 28.00 cM 21_1D_81.1 22_1D_83.2

1_5DL_0

2_5DL_5.8 3_5DL_7.1 2DL

Map size : 11.92 cM 4_5DL_17.8 23_1D_109.6 5_5DL_20.3

6_5DL_26.7 24_1D_118.3 1_2DL_0 7_5DL_28 2_2DL_4.8 3_2DL_8.1 4_2DL_11.9 Online Resource 4 Click here to download Supplementary Material (builds into PDF): ESM_4.pptx

A QCp.niab.6A QPh.niab.6A

Robigus Solstice Robigus Solstice

B Interaction plot for QPh.niab.2B and QPh.niab.4B Dot plot for QPh.niab.2B and QPh.niab.4B

R S

Robigus Solstice RR SR RS SS @Rht-B1 @Rht-B1 Online Resource 5 Click here to download Supplementary Material (builds into PDF): ESM_5.docx

QTL LODf P P Chromosomal Position Position P Position Position Relationship Phenotype (v LODfv1 value LODi LODav1 value between the locations QTL1 full QTL2 full value QTL1 add QTL2 add null) fv1 av1 QTL pairs QCp.niab.2A QCp.niab.4B 2A:4B 100 12.5 12.2 3.11 0.974 0.0724 1 100 12.5 3.03 0.072 Additive Ergot size 2010 QCp.niab.4B QCp.niab.4D 4B:4D 75 12.5 16.2 7.06 0 0.2468 1 75 12.5 6.81 0 Additive QCp.niab.2A QCp.niab.4B 2A:4B 132 70 10.8 4.35 0.344 0.419 1 132 70 3.93 0.037 Additive Ergot size 2011 QCp.niab.4B QCp.niab.4D 4B:4D 67.5 25 10.7 4.21 0.421 1.199 1 70 2.5 3.01 0.172 Additive

QPh.niab.2B QPh.niab.4B 2B:4B 40 75 19.16 8.15 0 7.37 0 110 72.5 0.78 1 Interacting plant height QPh.niab.4B 2010 Both QPh.niab.4D 4B:4D 75 12.5 57.66 39.97 0 16.01 0 72.5 10 23.968 0 interacting and additive QPh.niab.4B Both plant height QPh.niab.4D 4B:4D 75 10 32.1 19.63 0 7.84 0 72.5 10 11.79 0 interacting 2011 and additive

Online Resource 2 Click here to download Supplementary Material (download option from within PDF): ESM_2.xlsx