#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Oilseed rape (Brassica napus) resistance to growth of Leptosphaeria maculans in leaves of young plants contributes to quantitative resistance in stems of adult plants


Authors: Yong-Ju Huang aff001;  Sophie Paillard aff002;  Vinod Kumar aff002;  Graham J. King aff003;  Bruce D. L. Fitt aff001;  Régine Delourme aff002
Authors place of work: School of Life and Medical Sciences, University of Hertfordshire, Hatfield, Hertfordshire, England, United Kingdom aff001;  IGEPP, INRA, Agrocampus Ouest, Univ Rennes, BP, France aff002;  Southern Cross University, Lismore, Australia aff003
Published in the journal: PLoS ONE 14(9)
Category: Research Article
doi: https://doi.org/10.1371/journal.pone.0222540

Summary

Key message: One QTL for resistance against Leptosphaeria maculans growth in leaves of young plants in controlled environments overlapped with one QTL detected in adult plants in field experiments.

The fungal pathogen Leptosphaeria maculans initially infects leaves of oilseed rape (Brassica napus) in autumn in Europe and then grows systemically from leaf lesions along the leaf petiole to the stem, where it causes damaging phoma stem canker (blackleg) in summer before harvest. Due to the difficulties of investigating resistance to L. maculans growth in leaves and petioles under field conditions, identification of quantitative resistance typically relies on end of season stem canker assessment on adult plants. To investigate whether quantitative resistance can be detected in young plants, we first selected nine representative DH (doubled haploid) lines from an oilseed rape DY (‘Darmor-bzh’ × ‘Yudal’) mapping population segregating for quantitative resistance against L. maculans for controlled environment experiment (CE). We observed a significant correlation between distance grown by L. maculans along the leaf petiole towards the stem (r = 0.91) in CE experiments and the severity of phoma stem canker in field experiments. To further investigate quantitative trait loci (QTL) related to resistance against growth of L. maculans in leaves of young plants in CE experiments, we selected 190 DH lines and compared the QTL detected in CE experiments with QTL related to stem canker severity in stems of adult plants in field experiments. Five QTL for resistance to L. maculans growth along the leaf petiole were detected; collectively they explained 35% of the variance. Two of these were also detected in leaf lesion area assessments and each explained 10–12% of the variance. One QTL on A02 co-localized with a QTL detected in stems of adult plants in field experiments. This suggests that resistance to the growth of L. maculans from leaves along the petioles towards the stems contributes to the quantitative resistance assessed in stems of adult plants in field experiments at the end of the growing season.

Keywords:

Biology and life sciences – Genetics – Plant science – Organisms – Eukaryota – Plants – Plant pathology – Plant pathogens – People and places – Genetic loci – Quantitative trait loci – Geographical locations – Europe – Agriculture – Earth sciences – Plant anatomy – Leaves – Crop science – Crops – Seasons – Spring – Flowering plants – Brassica – Rapeseed

Introduction

Protecting crops from catastrophic yield losses caused by plant pathogens is a major goal of agriculture to safeguard global food security in response to growing concerns about food shortages and climate change [13]. Use of crop resistance is one of the most economical methods of controlling crop diseases, as it not only reduces input costs for farmers but also reduces risk of environmental damage. Crop resistance is particularly important for small-holder farmers who can not afford to buy expensive fungicides [3]. Furthermore, with a limited range of fungicides available and the development of fungicide insensitivity in pathogen populations [1, 47], identification of effective crop resistance is vital for sustainable crop production.

Plant resistance used to control crop diseases is generally classified as either major gene-determined qualitative resistance or minor gene-determined quantitative resistance [810]. Qualitative resistance, considered as ‘complete’ resistance, is usually controlled by single, dominant resistance (R) genes which are often effective in preventing pathogens from colonising plants [1114]. However, R gene-mediated is race-specific; therefore, it is generally less durable than quantitative resistance because pathogens often evolve rapidly for virulence against the R genes [1519]. By contrast, quantitative resistance is typically controlled by several genes with minor effects. Therefore, quantitative resistance is considered as incomplete or partial resistance that does not prevent pathogens from colonising plants but is able to decrease symptom severity and/or epidemic progress over time [10, 2022]. Combining resistance QTL (quantitative trait loci) with complementary modes of action or combining quantitative resistance with major R genes have proved to be valuable strategies for breeding effective, potentially durable resistance [23]. Therefore, understanding quantitative resistance will contribute to deployment of crop cultivars with more durable resistance.

Phoma stem canker (blackleg) is an economically important disease of oilseed rape (Brassica napus, canola) worldwide, especially in Australia, North America and Europe [24, 25]. Epidemics of phoma stem canker are initiated by air-borne Leptosphaeria maculans ascospores released from pseudothecia produced on stem debris of previous crops [22, 26, 27]. In Europe, ascospores landing on leaf surfaces produce germ tubes that infect the leaves of winter oilseed rape in autumn (October/November), causing phoma leaf spot lesions [22, 28, 29]. From leaf lesions, L. maculans grows symptomlessly along the leaf midrib and petiole to reach the stem, causing damaging phoma stem cankers in spring/summer (April-July) that result in yield losses [12, 25, 30]. Both qualitative resistance and quantitative resistance have been identified in B. napus and related brassica species [9, 31, 32]. R gene-mediated resistance against L. maculans operates at the leaf infection stage through a defence response that causes cell death at the infection site, thus preventing L. maculans growth from leaf to stem and subsequently preventing stem canker development [14, 22, 3335]. Quantitative resistance to L. maculans is a partial resistance that does not prevent leaf lesion development but decreases growth of L. maculans along leaf petioles and into stem tissues, therefore subsequently reduces the severity of stem cankers before harvest [22, 36, 37].

Compared to R-gene mediated resistance against L. maculans, quantitative resistance against L. maculans is less understood. One of the reasons is that R gene-mediated resistance against L. maculans can be selected effectively in young plants by observing necrosis symptoms after inoculation of cotyledons with well-characterised L. maculans isolates [14, 16, 33]. At least 15 R genes have been identified and two of them have been cloned [9, 14, 31, 3840]. Due to the high evolutionary potential through sexual recombination, L. maculans can mutate to overcome R-gene mediated resistance within three cropping seasons of widespread use in commercial cultivars [15, 16, 18, 19]. Recent studies showed that combining R-gene resistance with quantitative resistance in one crop cultivar provides a more robust strategy to control phoma stem canker [22, 30, 41].

Due to the long period of symptomless growth after initial leaf infection, it has been difficult to investigate quantitative resistance [21]. In Europe, it takes at least 6 months from the appearance of phoma leaf spots in autumn to the appearance of phoma stem canker in the following spring [26, 27]. It is difficult to investigate resistance to L. maculans growth in leaves and petioles or in stems before the appearance of stem canker symptoms under field conditions. Currently, selection of cultivars with quantitative resistance has relied on assessment of crop disease severity at the end of growing season [4244]. Previous work showed that resistance against L. maculans growth in the leaf petiole towards the stem in young plants could be a component of quantitative resistance against L. maculans [36]. However, it is not clear whether the measurement of L. maculans growth in the leaf petioles of young plants in controlled environments can be used to detect QTL for resistance against L. maculans in adult plants in field conditions. Coincident resistance QTL detected in both controlled environment experiments in young plants and field experiments in adult plants would represent a valuable step towards identification of underlying resistance genes and provide a practical basis for marker-assisted resistance breeding. We were therefore keen to test the hypothesis that QTL for resistance against L. maculans can be detected in leaf petioles of young plants in controlled environments, and if so, to establish whether they co-localize with resistance QTL detected in stems of adult plants in field experiments. This paper reports work on detection of QTL for resistance against L. maculans growth in leaves of young plants in controlled environment experiments and compares them with QTL detected in stems of adult plants in field experiments using a doubled haploid (DH) segregating population.

Materials and methods

Relationship between L. maculans growth in leaves of young plants in controlled environment experiments and severity of phoma stem canker in stems of adult plants in field experiments (nine DH lines)

In field conditions in Europe, phoma stem cankers on adult plants in summer are usually initiated from phoma leaf lesions on young plants in autumn/winter [25, 27]. Therefore, to investigate whether the ‘field’ quantitative resistance against L. maculans assessed by scoring stem canker at the end of the growing season on adult plants in field experiments can be detected by assessing L. maculans growth in the leaves of young plants in controlled environments, nine DH lines with different levels of resistance to L. maculans were used. The DH lines were from an oilseed rape DY (‘Darmor-bzh’ × ‘Yudal’) mapping population; the parent ‘Darmor-bzh’ is winter oilseed rape with quantitative resistance against L. maculans and the resistance gene Rlm9 while the parent ‘Yudal’ is a susceptible spring oilseed rape [42, 45]. Selection of the nine DH lines was based on stem canker severity assessed in 1995, 1996 and 2007 field experiments in France since there were good correlations between stem canker severities across these three years (S1 Fig; Kumar et al., 2018). The nine DH lines were classified from the most susceptible to the most resistant according to the disease severity index (DI): DY002, DY046, DY052, DY087, DY128, DY071, DY130, DY152 and DY283 [42, 44].

Plants were grown in pots (9 cm diameter) containing a peat-based compost mixed with a soluble fertiliser (WE Hewitt & Sons Ltd, UK). Plants were initially grown in a glasshouse (20–23°C) and transferred to a controlled environment growth room (20ºC day/20°C night, 12 h light/12 h darkness, light intensity 210 μmol m-2s-1) when they had three expanded leaves for inoculation. Ascospores of L. maculans from natural populations in the UK were used as inoculum. Although the parent ‘Darmor-bzh’ has resistance gene Rlm9, the L. maculans populations throughout Europe have been virulent against Rlm9 [11, 30, 46], so there was no Rlm9 effect. The ascospore suspension of L. maculans was prepared from stem base debris of the UK susceptible oilseed cultivar Courage (naturally infected the stems collected after harvest in August 2007, stem pieces with mature pseudothecia were stored at -20°C until required), using the method described by Huang et al. [29]. The concentration of ascospores was adjusted to 104 ascospores mL-1 using a haemocytometer slide.

To investigate the growth of L. maculans from leaf lesions along the leaf petioles towards the stems, leaf laminas were inoculated as described by Huang et al. (2014)[36]. Before inoculation, each leaf lamina was rubbed gently using a wet tissue and a 15 μL droplet of ascospore suspension was placed on the rubbed area. Each leaf had two inoculation sites, one on each side of the main vein as described by Huang et al. [36]. The first two fully expanded leaves of each plant were inoculated. After inoculation, plants in trays were covered with tray covers to maintain high relative humidity for 48h. Two experiments were done in a complete randomised design with 12 plants for each DH line.

The growth of L. maculans in the leaves was measured in terms of size of the phoma leaf spot lesions (i.e. lesion width, length and lesion area) and the growth along the leaf vein/petiole towards the stem (e.g. the visible distance grown along the petiole and the amount of L. maculans DNA in the petiole). At 18 days post inoculation (dpi), the inoculated leaves were detached at the place where the petiole joins the stem. The maximum length and width of each lesion were measured, then the lesion area was estimated by multiplying the lesion length by lesion width. The distance from the inoculation site on the leaf lamina to the furthest visible necrosis on the leaf petiole was measured on each leaf, then a piece of leaf petiole 8 cm long (measured from the inoculation site) was placed in a 15 mL tube to be freeze-dried for DNA extraction and quantitative PCR (qPCR). DNA was extracted from each individual leaf petiole using a DNA extraction kit (DNAMITE Plant Kit, Microzone Ltd, West Sussex, UK). The amount of L. maculans DNA in each leaf petiole was quantified using a SYBR green qPCR with the primers LmacF and LmacR [47] using a Stratagene Mx3000P quantitative PCR machine. The qPCR reaction and thermocycling profile were described by Huang et al. [36].

Statistical analysis

For leaf lamina inoculation experiments with the nine DH lines, the data for leaf lesion area, distance grown by L. maculans along the leaf petiole and the amount of L. maculans DNA in the leaf petiole were analysed using the restricted maximum likelihood procedure (REML). The analysis of variance components was done by fitting each of the response traits to a fixed model (constant + experiment + DH line + experiment × DH line) and a random model (experiment × block) to test the effects of experiment, DH line and the interaction between experiment and DH line. To investigate the relationship between L. maculans growth in leaves in controlled environments and severity of stem canker in field experiments, linear regressions were done for leaf lesion area, distance grown or amount of L. maculans DNA against the mean stem canker severity disease index on the nine DH lines assessed in 1995, 1996 and 2007 field experiments in France. All the analyses were done using GENSTAT statistical software 12th edition [48].

Detection of QTL for resistance against L. maculans growth in leaves of young plants in controlled environment experiments (190 DH lines)

For the nine DH lines, significant correlations between by L. maculans growth in leaves of young plants in controlled environment experiments and the severity of phoma stem canker in field experiments were observed. To further investigate QTL related to resistance against growth of L. maculans in leaves of young plants, we selected 190 DH lines for leaf lamina inoculation. It was difficult to obtain large amounts of ascospore inoculum for the large experiment, so conidia of L. maculans isolate ME24 were used since ME24 was virulent against Rlm9 [36]. There were no differences between ascospores (used for the nine DH lines) and conidia of isolate ME24 in symptoms on Darmor or Yudal (i.e. both the ascospores and the conidia of ME24 caused typical phoma leaf lesions). Therefore, the conidia of ME24 were used as inoculum. Conidial suspensions of isolate ME24 were prepared from 12-day-old cultures on V8 agar and the concentration of conidia was adjusted to 107 conidia mL-1.

Plants of the 190 DH lines and their parents were grown in trays with 40 wells containing a peat-based compost mixed with a soluble fertiliser. Each tray was sown with 16 DH lines with two plants of each DH line. The middle row of wells was not sown to provide gaps between the DH lines. Plants were initially grown in a glasshouse (20–23°C) and were transferred to a controlled environment growth room (20ºC day/20°C night, 12 h light/12 h darkness, light intensity 210 μmol m-2s-1) for 24 h before inoculation. The experiments were designed in a resolvable alpha design with three replicates. The design allowed for sub-blocks of 16 lines, which were fitted into one tray. The allocation of trays to shelves (two trays per shelf) was done systematically following randomization. Plants were inoculated when they had three expanded leaves. Each leaf lamina was rubbed gently using a wet tissue and wounded using a sterile pin, then a 10 μL droplet of conidial suspension was placed over the wound. Each leaf had two inoculation sites, one on each side of the main vein. The first two fully expanded leaves of each plant were inoculated. After inoculation, plants were covered with tray covers to maintain high humidity for 72h since L. maculans conidia take longer to infect the plants than ascospores [36].

At 21 dpi, the inoculated leaves were detached from the place where the petiole joins the stem. The maximum length and width of each lesion were measured, and the lesion area was estimated by multiplying the lesion length by lesion width. The distance from the inoculation site on the leaf lamina to the furthest visible necrosis on the leaf petiole was measured. To assess the effects of leaf lamina size and leaf petiole length on the growth of L. maculans in the leaf, the leaf lamina length and leaf petiole length of each leaf were also measured. The two experiments were done with the 190 DH lines.

QTL detection in controlled environment experiments

Data for each trait of the 190 DH lines and their parents were analysed using REML. Preliminary analysis of the data indicated that a square root transformation was required to stabilise the residual variance for leaf lesion area. Two REML analyses were done for each trait: (a) with DH line effects fitted as random effects using a fixed model and a random model, to enable calculation of heritability; (b) with DH line effects fitted as fixed effects using a fixed model and a random model, to provide predicted means for use in QTL analysis. The Pearson correlation coefficient was calculated using the predicted DH line means for all the traits.

A linkage map generated from the DY population comprising 3767 SNPs (one marker per genetic position) covering 2128.2 cM was used for QTL detection [49]. A multiple QTL mapping model was tested using the R/qtl package [50] for each variable as descripted by Kumar et al. [49]. For each variable, simple interval mapping (SIM) was done using the scanone function. The number of positions with a LOD score ≥ 2.5 was used to declare the number of cofactors in the composite interval analysis (CIM) done using the cim function. In the first model, positions with LOD scores ≥ 2.5 were included as QTL. An ANOVA was fitted to the multiple QTL model using the fitqtl function. QTL were retained in this first model when their effects were significant (α = 0.05). The addqtl function was then used to test for further significant QTLs, followed by an ANOVA fitted to the new model. To obtain the maximum likelihood estimates of the QTL positions, we then applied the refineqtl function, which used an iterative algorithm to refine the locations of QTL in our multiple QTL model. A final ANOVA was fitted to this multiple QTL model. Based on results of the ANOVA, the percentage of the variation explained by the model and the R2 of each QTL was assessed. The LOD value for each QTL was obtained using the fiqtl function. The confidence intervals of each QTL were assessed with a LOD decrease of one (lodint function). QTL positions and marker names at these positions, confidence intervals, percentage of variation explained by each QTL (R2), allelic effect and favourable alleles were scored.

Comparison of QTL detected in controlled environment experiments with those previously detected in field experiments

To investigate whether the resistance QTL detected in leaves of young plants in the controlled environment experiments co-localize with those QTL previously detected in stems of adult plants in field experiments, the positions of those QTL were compared. For QTL detected in field experiments, phoma stem canker severity data from 11 field experiments with three different mapping populations (S2 Table; [49]) were used. Field experiments with the DY segregating population were done in seven years, with five years (1995, 1996, 2007, 2011 and 2012) at Le Rheu, INRA, France [42, 44, 51] and two years (2008 and 2009) at Rothamsted Research, Harpenden, UK [52]. Field experiments were also done for the DS (‘Darmor’ x ‘Samourai’ DH) population in 1998 and 1999 [53] and for the DB (‘Darmor’ x ‘Bristol’ F2:3) population in 2008 and 2010 [54] at Le Rheu, INRA, France. For QTL analysis, in addition to analysis for individual years for each mapping population, the combined data sets using BLUP (best linear unbiased predictions) estimations for these three mapping populations were also used (S3 Table). For QTL on the same chromosome (linkage group), their genetic and physical positions and support intervals were compared to identify QTL detected in both controlled environment experiments in young plants and field experiments in adult plants. Physical positions were deduced from the physical localization of the SNP markers on the B. napus cv. Darmor reference genome sequence assembly (version 4.1) [55, 56].

Results

Relationship between L. maculans growth in leaves of young plants in controlled environment experiments and severity of phoma stem canker in stems of adult plants in field experiments

For the nine DH lines, there were significant differences between DH lines for leaf lesion area (P < 0.001, 8 d.f.), distance grown along the leaf petiole (P < 0.001, 8 d.f.) and the amount of L. maculans DNA in the petiole (P < 0.001, 8 d.f.) (Table 1). There were no differences between experiments or interactions between experiment and DH line for leaf lesion area or distance grown. For the amount of L. maculans DNA in the petiole, there was no difference between experiments but there was an interaction between experiment and DH line; however, the Wald statistic was relatively small for the effect of interaction (33.1) compared to the main effect of DH line (526.8). The heritability was high for distance grown (0.88) and L. maculans DNA (0.96). The measurement of distance grown by L. maculans along the leaf petiole correlated well with the measurement of leaf lesion area (r = 0.90; P < 0.001) or the amount of L. maculans DNA in the petiole (r = 0.89; P < 0.001). There was a smaller correlation between the leaf lesion area and the amount of L. maculans DNA in the petiole (r = 0.68; P < 0.01).

Tab. 1.

Measurements of Leptosphaeria maculans growth in leaves after inoculation of the leaf lamina in two controlled environment experiments and the mean phoma stem canker severity (DI-disease index) in 1995, 1996 and 2007 field experiments in France with nine doubled haploid (DH) lines from the Brassica napus DY (‘Darmor-bzh’ x ‘Yudal’) mapping population.

<h2>Measurements of <i>Leptosphaeria maculans</i> growth in leaves after inoculation of the leaf lamina in two controlled environment experiments and the mean phoma stem canker severity (DI-disease index) in 1995, 1996 and 2007 field experiments in France with nine doubled haploid (DH) lines from the <i>Brassica napus</i> DY (‘Darmor-<i>bzh</i>’ x ‘Yudal’) mapping population.</h2>

There was a significant positive correlation between distance (Gt) grown by L. maculans along the leaf petiole of young plants in controlled environment experiments and mean stem canker disease index (Di) in stems of adult plants of the nine DH lines assessed in 1995, 1996 and 2007 field experiments in France (Di = 2.69Gt—0.42, r = 0.91) (Fig 1A). Similar relationships were obtained for leaf lesion area (La) (Di = 1.48 La + 2, r = 0.76) (Fig 1B) or the amount of L. maculans DNA (d) in the leaf petiole (Di = 0.03d + 3.26, r = 0.77) (Fig 1C).

<h2>Relationships between <i>Leptosphaeria maculans</i> growth in young plants and phoma stem canker severity in adult plants.</h2>
Fig. 1.

Relationships between Leptosphaeria maculans growth in young plants and phoma stem canker severity in adult plants.


The relationships between distance grown by L. maculans in the leaf petiole (Dt) (Di = 2.69Dt -0.42, r = 0.91) (A), phoma leaf lesion area (La) (Di = 1.48La +2, r = 0.76) (B) or amount of L. maculans DNA in petiole (d) (Di = 0.03d +3.26, r = 0.77) (C) of young plants in controlled environment experiments and the mean phoma stem canker severity (Di; disease index) in winter oilseed rape field experiments in 1995, 1996 and 2007 with nine doubled haploid (DH) lines from the Brassica napus DY (‘Darmor-bzh’ x ‘Yudal’) mapping population assessed by linear regression. Data for controlled environment experiments are means of data from two replicate experiments.

Detection of QTL for resistance against L. maculans growth in leaves of young plants in controlled environment experiments

For the 190 DH lines, phoma leaf spot lesions developed on all inoculated leaves. For some of the DH lines, the inoculated leaves had turned yellow by 21 dpi (Fig 2). The frequency distributions for distance grown by L. maculans along the leaf petiole and the phoma leaf spot lesion area were continuous (Fig 3A and 3B). The continuous distributions suggested that the resistance against L. maculans growth in leaves of the DY population was quantitative and probably due to multiple loci with additive effects. There was a wide range in either the phoma leaf spot lesion area (0.19 to 1.31 cm2) or distance grown by L. maculans (1.05 to 3.17 cm) among the 190 DH lines. The broad sense heritability of lesion area (0.44) was greater than that of distance grown along the leaf petiole (0.39). There were significant positive correlations between different measurements of L. maculans growth in leaves of the 190 DH lines (Table 2). There was also a wide range in leaf petiole length (3.54–10.54 cm), leaf lamina length (4.48–9.13 cm) and total leaf length (8.06–18.64 cm) among the 190 DH lines. The distributions of leaf petiole length (Fig 3C) or leaf lamina length (data not presented) were also continuous. The heritability of leaf petiole length (0.81) and leaf lamina length (0.74) was high. These traits were highly correlated with each other and moderately correlated with different measurements of L. maculans growth in leaves (Table 2).

<h2>Phoma leaf spot symptoms produced on different DH lines in controlled environment experiments.</h2>
Fig. 2.

Phoma leaf spot symptoms produced on different DH lines in controlled environment experiments.


Phoma leaf spot symptoms on leaves of four doubled haploid (DH) lines DY413 (A), DY087 (B), DY048 (C) and DY001 (D) inoculated with conidia of Leptosphaeria maculans isolate ME24 at 21 days post inoculation.

<h2>Frequency distributions.</h2>
Fig. 3.

Frequency distributions.


Frequency (number of DH lines) distributions of different variables measured for the 190 lines from the Brassica napus DY (‘Darmor-bzh’ x ‘Yudal’) mapping population in two controlled environment experiments. A, distance grown by Leptosphaeria maculans along the leaf petiole from the inoculation site (cm); B, phoma leaf spot lesion area (cm2); C, leaf petiole length (cm). Arrows indicate the mapping population parents (D = Darmor-bzh, Y = Yudal). Data are means of two controlled environment experiments.

Tab. 2.

Correlation coefficient values for relationships between different measurements of Leptosphaeria maculans growth in leaves and for leaf size of 190 doubled haploid (DH) lines from the Brassica napus DY (‘Darmor-bzh’ x ‘Yudal’) mapping population in two controlled environment experiments.

<h2>Correlation coefficient values for relationships between different measurements of <i>Leptosphaeria maculans</i> growth in leaves and for leaf size of 190 doubled haploid (DH) lines from the <i>Brassica napus</i> DY (‘Darmor-<i>bzh</i>’ x ‘Yudal’) mapping population in two controlled environment experiments.</h2>

Five QTL involved in resistance to L. maculans growth along the leaf petiole (CE-Gt) were detected on linkage groups A02, A03, A10, C01 and C09, respectively (Table 3). The estimated phenotypic variation explained by individual QTL ranged from 3 to 10% and they collectively explained 35% of the variance. In addition, one weak QTL was detected on A04. Two QTL that collectively explained 22% of the variance in phoma leaf spot lesion area (CE-La) were detected on A02 and C01, and were located within support intervals for the two QTL related to L. maculans distance grown along the leaf petiole (Fig 4). The individual QTL each explained 10–12% of the variance (Table 3). The resistance alleles were contributed by ‘Darmor-bzh’ for QTL on A02, A03 and A10 and by ‘Yudal’ for QTL on A04, C01 and C09.

<h2>Comparison of the physical position of QTL.</h2>
Fig. 4.

Comparison of the physical position of QTL.


Comparison of the physical position (in Mb) of QTL on A02, A04 and C01 for resistance against Leptosphaeria maculans detected in controlled environment experiments (CE) in young plants with QTL detected in field experiments in adult plants. CE experiments were done with 190 lines from the Brassica napus DY (‘Darmor-bzh’ x ‘Yudal’ DH) population. Field experiments were done with DY population in 1995, 1996, 2007, 2008, 2009, 2011 and 2012, with DB (‘Darmor’ x ‘Bristol’ F2:3) population in 2008 and 2010 and with DS (‘Darmor’ x ‘Samourai’ DH) population in 1998 and 1999 (for details see S1 and S2 Tables). QTL from CE experiments are in blue; QTL from individual years in field experiments are in pink; QQTL from combined years of field experiments using BLUP (best linear unbiased predictions) estimations are in orange.

Tab. 3.

QTL for resistance against Leptosphaeria maculans detected in controlled environment experiments and neighbouring QTL detected in winter oilseed rape field experiments with the Brassica napus DY (‘Darmor-bzh’ x ‘Yudal’) mapping population.

<h2>QTL for resistance against <i>Leptosphaeria maculans</i> detected in controlled environment experiments and neighbouring QTL detected in winter oilseed rape field experiments with the <i>Brassica napus</i> DY (‘Darmor-<i>bzh</i>’ x ‘Yudal’) mapping population.</h2>

To investigate whether there were any correlations between leaf lamina size or leaf petiole length and the growth of L. maculans in the leaf, the QTL related to leaf lamina length and leaf petiole length were also analysed. Six QTL related to leaf lamina length (CE-Lal) were detected and distributed over six linkage groups (Table 4). The estimated phenotypic variation explained by individual QTL ranged from 5 to 31% and all QTL collectively explained 59% of the variation. A strong effect QTL was detected on A06 where the dwarf gene bzh was located. The alleles for smaller leaf lamina length were from parent ‘Darmor-bzh’ on A06 and A10 and from parent ‘Yudal’ for the other four QTL (Table 4). Six QTL related to leaf petiole length (CE-Pl) were detected and distributed over six linkage groups (Table 4). The estimated phenotypic variation explained by individual QTL ranged from 4 to 40% and all QTL collectively explained 57% of the variation. A strong effect QTL related to leaf petiole length was detected on A06 where the dwarf gene bzh was located. The alleles for shorter petiole length were from parent ‘Darmor-bzh’ on A06 and A09 and from parent ‘Yudal’ for the other four QTL (Table 4). QTL on A01, A06 and C06 related to leaf lamina length and leaf petiole length were at the same location and support intervals overlapped for the other QTL. When compared with QTL detected for leaf lesion length or distance grown by L. maculans in the leaf petiole with QTL detected for leaf laminar length or petiole length, only a partial overlap with a QTL on A10 for leaf lamina length was found. No other co-localization was detected.

Tab. 4.

Information about QTL for leaf lamina size and leaf petiole length detected by composite interval mapping in two controlled environment experiments (CE) with 190 doubled haploid (DH) lines from the Brassica napus DY (‘Darmor-bzh’ x ‘Yudal’) mapping population.

<h2>Information about QTL for leaf lamina size and leaf petiole length detected by composite interval mapping in two controlled environment experiments (CE) with 190 doubled haploid (DH) lines from the <i>Brassica napus</i> DY (‘Darmor-<i>bzh</i>’ x ‘Yudal’) mapping population.</h2>

Comparison of QTL detected in controlled environment experiments with those previously detected in field experiments

All the QTL detected based on the 190 DH lines from the DY (‘Darmor-bzh’ x ‘Yudal’ DH) population in the controlled environment experiments were compared with QTL detected in field experiments with the DY (seven years), DB (‘Darmor’ x ‘Bristol’ F2:3) (two years) and DS (‘Darmor’ x ‘Samourai’ DH) (two years) populations. The comparisons represented either individual years or the combined data sets using BLUP estimations (S4 Table). The QTL on A02 detected for distance grown along the leaf petiole and leaf lesion area co-localized with QTL detected in field experiments in 2007 and 2012, and was also close to the QTL detected using BLUP for the DY population (Table 3; Fig 4). Furthermore, this QTL was also detected in 1998 and BLUP for the DS population (S4 Table; Fig 4). In all cases, the resistance allele was contributed by ‘Darmor-bzh’. A QTL detected on A04 for distance grown along the leaf petiole co-localized with a QTL detected in a field experiment in 2008 and 2011 for the DY population and with BLUP QTL found in the DB population (S4 Table) but the resistance allele was not contributed by the same parent (Fig 4; Table 3). All the other QTL from controlled environment experiments did not colocalize with QTL detected in field experiments either in individual years or in BLUP. A QTL on A03 was detected in 2007, 2012 and BLUP with the DY population and in 2008 with the DB population (S4 Table), but the positions were different from the QTL detected in controlled environment experiments (Table 3; S2 Fig). Similarly, the QTL on C01 detected in field experiments was in a different position from that detected in controlled environment experiments (Table 3; Fig 4). However, the resistant allele of the QTL on C01 was from ‘Yudal’ for both controlled environment experiments and field experiments.

Discussion

Results of this study show that it is possible to detect QTL for resistance to L. maculans in young plants by investigating the growth of the pathogen from leaf lesions along the leaf petiole towards the stem or by measuring leaf lesion area in controlled environment experiments. Five QTL for resistance to L. maculans growth along the leaf petiole were detected and two of these were also detected by measurement of leaf lesion area. This is the first reported study investigating QTL for resistance against L. maculans growth in leaves of young plants in controlled environments. In Europe under natural conditions, the fungal pathogen L. maculans initially infects leaves of oilseed rape in autumn and then grows systemically from leaf lesions along the leaf petiole to the stem, causing damaging phoma stem canker (blackleg) in the following summer [9, 27, 57]. Traditionally, selection for quantitative resistance to the phoma stem canker pathogen has relied on winter oilseed rape field experiments in which phoma stem canker severity is assessed at the end of the cropping season before harvest [22, 42, 44]. Therefore, quantitative resistance against L. maculans has also been referred to as ‘adult plant resistance’ [9]. Because L. maculans has a long period of symptomless growth between the initial development of phoma spot lesions on leaves and the appearance of canker symptoms on stems, it has been difficult to investigate quantitative resistance to L. maculans growth in leaf petioles and stems under field conditions. Results of this work provide evidence that components of quantitative resistance to L. maculans can be detected in controlled conditions.

In the comparison of QTL for resistance against L. maculans growth in leaves of young plants in controlled environments and QTL for resistance against L. maculans growth in stems of adult plants in field experiments, one QTL on A02 was found to co-localize with a QTL detected in field experiments in 2007 and 2012 and was very close to the QTL detected with BLUP. Furthermore, this QTL was also detected in the same population after field phenotyping in Australia [58] and in another mapping population (‘Darmor’ x ‘Samourai’ DH) that shares the same source of quantitative resistance. Consistent detection of this QTL on A02 by measuring L. maculans growth along the leaf petiole or the size of the leaf lesion in controlled environment experiments or by measuring the stem canker severity in field experiments suggests that this QTL might operate to control the rate of L. maculans growth from the leaf to the stem, leading to reduced stem canker severity in adult plants before harvest. In other words, resistance to the growth of L. maculans in leaves of young plants contributes to quantitative resistance in stems of adult plants. Furthermore, this QTL was not affected by petiole length since no QTL for petiole length was detected in this region. This suggests that the growth rate of L. maculans along the leaf petiole towards the stem might be more important than the petiole length. This is partly supported by the poor correlations between L. maculans growth in the leaf petiole and the leaf laminar length or the leaf petiole length (Table 2). Interestingly, although a QTL on C01 detected in controlled environment experiments was at a different position from that detected in field experiments [49], the resistance allele of the QTL was from the susceptible parent ‘Yudal’ for both controlled environment experiments and field experiments. This suggests that the contribution from ‘Yudal’ to this QTL might operate to slow down the growth of L. maculans from the leaf to the stem and subsequently reduce stem canker severity in adult plants before harvest. More precise investigations are needed to test whether the QTL are the same, which would provide further evidence that resistance to the growth of L. maculans in leaves of young plants contributes to quantitative resistance in stems of adult plants.

Although a QTL on A04 detected in controlled environment experiments for distance grown along leaf petiole co-localized with a QTL detected in the field experiment in 2008 and with BLUP QTL for the DB (‘Darmor’ x ‘Bristol’ F2:3) population [49], the resistance allele was contributed by ‘Yudal’ (e.g. resistance to the growth of L. maculans in leaves) for controlled environment experiments and by ‘Darmor-bzh’ (e.g. resistance to the growth of L. maculans in stems) for field experiments. These results also suggest that the QTL operating in the leaf petiole (by slowing down the growth of L. maculans towards the stem) may be different from the QTL operating in the stem (by slowing down the growth of L. maculans in stems to reduce stem canker severity). This is supported by the evidence that QTL on A03, A10, C01 and C09 detected in leaves of young plants in controlled environment experiments are at different positions from those detected in stems of adult plans in field experiments (Fig 4; S1 Fig). Even though QTL operating in leaf petiole can delay the time when L. maculans reaches the stem, once L. maculans has reached the stem, the weather conditions and the QTL operating in the stem are vital in reducing the severity of stem canker. Recent work showed that the increased temperature during stem canker development stage (April–June; i.e. after L. maculans has reached the stem) is associated with increased phoma stem canker severity before harvest [30]. Furthermore, due to the interactions with environment, QTL for quantitative resistance are often inconsistent over locations or seasons [10, 59]. Our previous work showed that many QTL were sensitive to environmental factors [49, 52, 60]. Therefore, quantitative resistance in stems of adult plants in field experiments (assessed at the end of growing season) results not only from resistance to growth of L. maculans in the leaves but also from resistance to growth of L. maculans in the stems. Work on spring oilseed rape also showed that quantitative resistance against growth of L. maculans in stems of adult plants was partly contributed by the growth of L. maculans in cotyledons of seedlings [35, 61]. Only one QTL on C06 related to resistance against growth of L. maculans in cotyledons detected in controlled environment experiments was found to co-localize with a QTL detected in stems of adult plants in field experiments [61] and might correspond to QTL reported in Kumar et al. [49]. Although cotyledon infection is observed in spring oilseed rape in Australia [26, 62], it is not common in Europe where the main source of phoma stem canker is from leaf lesions developed in autumn [25, 26]. Therefore, detection of QTL related to L. maculans growth in leaf petioles is close to what is happening in the field conditions in Europe.

Previous work showed that quantitative resistance to L. maculans could be assessed at two stages: stage 1- growth of the pathogen along leaf petioles towards the stem; and stage 2-growth in stem tissues to produce stem canker symptoms [36]. We showed in this work that resistance QTL related to L. maculans growth at stage 1 can be detected in controlled environments. Assessing resistance QTL in leaves of young plants (L. maculans growth stage 1) in controlled environment experiments is rapid; it takes 40–45 days from sowing to finishing the assessment for leaf lamina inoculation experiments. By contrast, assessing resistance QTL in stems of adult plants in field experiment before harvest takes 10–11 months (from sowing to harvest) for winter oilseed rape. Another advantage is that detection of QTL in controlled conditions can avoid the influence of fluctuations in natural weather conditions. However, only a small number of QTL detected in controlled environment experiments co-localized with QTL detected in field experiments. This suggests that only some components of quantitative resistance as assessed in the field might be detected in controlled environment experiments. The duration of L. maculans growth from the leaf petiole to the stem and L. maculans growth in the stem are other potential components of quantitative resistance. There is a need to investigate resistance QTL related to L. maculans growth in stem tissues to produce stem canker symptoms (L. maculans growth stage 2) and compare the QTL detected at both growth stages in controlled conditions with QTL detected in field conditions, which will help to understand components of quantitative resistance assessed at the end of the growing season in field experiments.

Only one isolate of L. maculans was used in the controlled environment experiments with the 190 DH lines for QTL detection, while in field conditions the plants were exposed to all the available pathogen races. This may be one of the reasons why only one QTL was co-localized with a QTL detected in stems of adult plants in field conditions. Although quantitative resistance against L. maculans is considered race non-specific, there may be differences between isolates in their aggressiveness and thus their ability to cause severe stem canker. There is a need to test more isolates or use a mixture of different isolates to investigate whether more common QTL can be detected in both controlled environments and in field experiments, which will help to develop markers for breeding cultivars with durable quantitative resistance.

Supporting information

S1 Table [xlsx]
Disease severity index and QTL detected in the nine DH (doubled haploid) lines from the Brassica napus DY (‘Darmor-bzh’ x ‘Yudal’) mapping population in seven field experiments.

S2 Table [docx]
List of eleven field experiments which produced QTL based on the phoma stem canker severity data (Kumar et al. 2018) used for comparison with QTL detected in controlled environment experiments with those for 190 DH lines from the DY population.

S3 Table [xlsx]
Phenotypic and genotypic data for the Brassica napus DY (‘Darmor-bzh’ x ‘Yudal’) mapping population used for detection of QTL for resistance against Leptosphaeria maculans in field experiments and controlled environment experiments.

S4 Table [docx]
Linkage groups (LG) where QTL for resistance against Leptosphaeria maculans detected in controlled environment experiments with QTL detected in winter oilseed rape field experiments with the Brassica napus DY (‘Darmor-bzh’ x ‘Yudal’), DB (‘Darmor’ x ‘Bristol’ F2:3) or DS (‘Darmor’ x ‘Samourai’ DH) population.

S1 Fig [dh]
Correlations between disease severity index in different field experiments.

S2 Fig [ce]
Comparison of the physical position of QTL.


Zdroje

1. Beddington J. Food security: contributions from science to a new and greener revolution. Philosophical Transactions of the Royal Society B: Biological Sciences. 2010;365(1537):61–71.

2. Fisher MC, Henk DA, Briggs CJ, Brownstein JS, Madoff LC, McCraw SL, et al. Emerging fungal threats to animal, plant and ecosystem health. Nature. 2012;484(7393):186–94. doi: 10.1038/nature10947 22498624

3. Bebber DP, Ramotowski MA, Gurr SJ. Crop pests and pathogens move polewards in a warming world. Nature Climate Change. 2013;3(11):985–8.

4. Hughes DJ, West JS, Atkins SD, Gladders P, Jeger MJ, Fitt BD. Effects of disease control by fungicides on greenhouse gas emissions by UK arable crop production. Pest Management Science. 2011;67(9):1082–92. doi: 10.1002/ps.2151 21495152

5. Hahn M. The rising threat of fungicide resistance in plant pathogenic fungi: Botrytis as a case study. Journal of Chemical Biology. 2014;7(4):133–41. doi: 10.1007/s12154-014-0113-1 25320647

6. Carter HE, Fraaije BA, West JS, Kelly SL, Mehl A, Shaw MW, et al. Alterations in the predicted regulatory and coding regions of the sterol 14α‐demethylase gene (CYP51) confer decreased azole sensitivity in the oilseed rape pathogen Pyrenopeziza brassicae. Molecular Plant Pathology. 2014;15(5):513–22. doi: 10.1111/mpp.12106 24298976

7. Sewell TR, Hawkins NJ, Stotz HU, Huang Y, Kelly SL, Kelly DE, et al. Azole sensitivity in Leptosphaeria pathogens of oilseed rape: the role of lanosterol 14α-demethylase. Scientific Reports. 2017;7(1):15849. doi: 10.1038/s41598-017-15545-9 29158527

8. Lindhout P. The perspectives of polygenic resistance in breeding for durable disease resistance. Euphytica. 2002;124(2):217–26.

9. Delourme R, Chevre A, Brun H, Rouxel T, Balesdent M, Dias J, et al. Major gene and polygenic resistance to Leptosphaeria maculans in oilseed rape (Brassica napus). European Journal of Plant Pathology. 2006;114(1):41–52.

10. Poland JA, Balint-Kurti PJ, Wisser RJ, Pratt RC, Nelson RJ. Shades of gray: the world of quantitative disease resistance. Trends in Plant Science. 2009;14(1):21–9. doi: 10.1016/j.tplants.2008.10.006 19062327

11. Balesdent M-H, Louvard K, Pinochet X, Rouxel T. A large-scale survey of races of Leptosphaeria maculans occurring on oilseed rape in France. European Journal of Plant Pathology. 2006;114(1):53–65.

12. Huang YJ, Evans N, Li ZQ, Eckert M, Chèvre AM, Renard M, et al. Temperature and leaf wetness duration affect phenotypic expression of Rlm6‐mediated resistance to Leptosphaeria maculans in Brassica napus. New Phytologist. 2006;170(1):129–41. doi: 10.1111/j.1469-8137.2005.01651.x 16539610

13. Bent AF, Mackey D. Elicitors, effectors, and R genes: the new paradigm and a lifetime supply of questions. Annual Review of Phytopathology. 2007;45:399–436. doi: 10.1146/annurev.phyto.45.062806.094427 17506648

14. Larkan NJ, Lydiate DJ, Parkin IAP, Nelson MN, Epp DJ, Cowling WA, et al. The Brassica napus blackleg resistance gene LepR3 encodes a receptor-like protein triggered by the Leptosphaeria maculans effector AVRLm1. New Phytologist. 2013;197(2):595–605. doi: 10.1111/nph.120433. 23206118

15. Rouxel T, Penaud A, Pinochet X, Brun H, Gout L, Delourme R, et al. A 10-year survey of populations of Leptosphaeria maculans in France indicates a rapid adaptation towards the Rlm1 resistance gene of oilseed rape. European Journal of Plant Pathology. 2003;109(8):871–81.

16. Sprague SJ, Balesdent M-H, Brun H, Hayden HL, Marcroft SJ, Pinochet X, et al. Major gene resistance in Brassica napus (oilseed rape) is overcome by changes in virulence of populations of Leptosphaeria maculans in France and Australia. European Journal of Plant Pathology. 2006;1(114):33–40.

17. Soanes DM, Talbot NJ. Moving targets: rapid evolution of oomycete effectors. Trends in Microbiology. 2008;16(11):507–10. doi: 10.1016/j.tim.2008.08.002 18819803

18. Zhang X, Peng G, Kutcher HR, Balesdent M-H, Delourme R, Fernando WD. Breakdown of Rlm3 resistance in the Brassica napus–Leptosphaeria maculans pathosystem in western Canada. European Journal of Plant Pathology. 2016;145(3):659–74.

19. Rouxel T, Balesdent MH. Life, death and rebirth of avirulence effectors in a fungal pathogen of Brassica crops, Leptosphaeria maculans. New Phytologist. 2017;214(2):526–32. doi: 10.1111/nph.14411 28084619

20. Chartrain L, Brading P, Widdowson J, Brown J. Partial resistance to Septoria tritici blotch (Mycosphaerella graminicola) in wheat cultivars Arina and Riband. Phytopathology. 2004;94(5):497–504. doi: 10.1094/PHYTO.2004.94.5.497 18943769

21. Huang YJ, Pirie E, Evans N, Delourme R, King G, Fitt BDL. Quantitative resistance to symptomless growth of Leptosphaeria maculans (phoma stem canker) in Brassica napus (oilseed rape). Plant Pathology. 2009;58(2):314–23.

22. Brun H, Chèvre AM, Fitt BDL, Powers S, Besnard AL, Ermel M, et al. Quantitative resistance increases the durability of qualitative resistance to Leptosphaeria maculans in Brassica napus. New Phytologist. 2010;185(1):285–99. doi: 10.1111/j.1469-8137.2009.03049.x 19814776

23. Pilet-Nayel M-L, Moury B, Caffier V, Montarry J, Kerlan M-C, Fournet S, et al. Quantitative resistance to plant pathogens in pyramiding strategies for durable crop protection. Frontiers in Plant Science. 2017;8:1838. doi: 10.3389/fpls.2017.01838 29163575

24. Howlett BJ. Current knowledge of the interaction between Brassica napus and Leptosphaeria maculans. Canadian Journal of Plant Pathology. 2004;26(3):245–52.

25. Fitt BDL, Brun H, Barbetti MJ, Rimmer SR. World-wide importance of phoma stem canker (Leptosphaeria maculans and L. biglobosa) on oilseed Rape (Brassica napus). European Journal of Plant Pathology. 2006;114(1):3–15. doi: 10.1007/s10658-005-2233-5

26. West JS, Kharbanda P, Barbetti M, Fitt BD. Epidemiology and management of Leptosphaeria maculans (phoma stem canker) on oilseed rape in Australia, Canada and Europe. Plant Pathology. 2001;50(1):10–27.

27. Huang YJ, Fitt BDL, Jedryczka M, Dakowska S, West JS, Gladders P, et al. Patterns of ascospore release in relation to phoma stem canker epidemiology in England (Leptosphaeria maculans) and Poland (Leptosphaeria biglobosa). European Journal of Plant Pathology. 2005;111(3):263–77.

28. Toscano‐Underwood C, West JS, Fitt BD, Todd A, Jedryczka M. Development of phoma lesions on oilseed rape leaves inoculated with ascospores of A‐group or B‐group Leptosphaeria maculans (stem canker) at different temperatures and wetness durations. Plant Pathology. 2001;50(1):28–41.

29. Huang YJ, Toscano‐Underwood C, Fitt BDL, Hu X, Hall A. Effects of temperature on ascospore germination and penetration of oilseed rape (Brassica napus) leaves by A‐or B‐group Leptosphaeria maculans (phoma stem canker). Plant Pathology. 2003;52(2):245–55.

30. Huang YJ, Mitrousia GK, Sidique SNM, Qi A, Fitt BDL. Combining R gene and quantitative resistance increases effectiveness of cultivar resistance against Leptosphaeria maculans in Brassica napus in different environments. PLoS One. 2018;13(5):e0197752. doi: 10.1371/journal.pone.0197752 29791484

31. Yu F, Lydiate DJ, Rimmer SR. Identification and mapping of a third blackleg resistance locus in Brassica napus derived from B. rapa subsp. sylvestris. Genome. 2008;51(1):64–72. doi: 10.1139/g07-103 18356940

32. Zhang X, Fernando WD. Insights into fighting against blackleg disease of Brassica napus in Canada. Crop and Pasture Science. 2018;69(1):40–7.

33. Balesdent M, Attard A, Ansan-Melayah D, Delourme R, Renard M, Rouxel T. Genetic control and host range of avirulence toward Brassica napus cultivars Quinta and Jet Neuf in Leptosphaeria maculans. Phytopathology. 2001;91(1):70–6. doi: 10.1094/PHYTO.2001.91.1.70 18944280

34. Yu F, Lydiate D, Rimmer S. Identification of two novel genes for blackleg resistance in Brassica napus. Theoretical and Applied Genetics. 2005;110(5):969–79. doi: 10.1007/s00122-004-1919-y 15798929

35. Raman R, Taylor B, Marcroft S, Stiller J, Eckermann P, Coombes N, et al. Molecular mapping of qualitative and quantitative loci for resistance to Leptosphaeria maculans causing blackleg disease in canola (Brassica napus L.). Theoretical and Applied Genetics. 2012;125(2):405–18. doi: 10.1007/s00122-012-1842-6 22454144

36. Huang YJ, Qi A, King GJ, Fitt BDL. Assessing quantitative resistance against Leptosphaeria maculans (phoma stem canker) in Brassica napus (oilseed rape) in young plants. PLoS One. 2014;9(1):e84924. doi: 10.1371/journal.pone.0084924 24454767

37. Travadon R, Marquer B, Ribule A, Sache I, Masson J, Brun H, et al. Systemic growth of Leptosphaeria maculans from cotyledons to hypocotyls in oilseed rape: influence of number of infection sites, competitive growth and host polygenic resistance. Plant Pathology. 2009;58(3):461–9.

38. Rimmer SR. Resistance genes to Leptosphaeria maculans in Brassica napus. Canadian Journal of Plant Pathology. 2006;28(S1):S288–S97.

39. Raman H, Raman R, Larkan N. Genetic dissection of blackleg resistance loci in rapeseed (Brassica napus L.). Plant Breeding from Laboratories to Fields: IntechOpen; 2013.

40. Larkan NJ, Ma L, Borhan MH. The Brassica napus receptor-like protein RLM2 is encoded by a second allele of the LepR3/Rlm2 blackleg resistance locus. Plant Biotechnology Journal. 2015;13(7):983–92. doi: 10.1111/pbi.12341 25644479

41. Delourme R, Bousset L, Ermel M, Duffe P, Besnard A-L, Marquer B, et al. Quantitative resistance affects the speed of frequency increase but not the diversity of the virulence alleles overcoming a major resistance gene to Leptosphaeria maculans in oilseed rape. Infection, Genetics and Evolution. 2014;27:490–9. doi: 10.1016/j.meegid.2013.12.019 24394446

42. Pilet M, Delourme R, Foisset N, Renard M. Identification of loci contributing to quantitative field resistance to blackleg disease, causal agent Leptosphaeria maculans (Desm.) Ces. et de Not., in winter rapeseed (Brassica napus L.). Theoretical and Applied Genetics. 1998;96(1):23–30.

43. Delourme R, Piel N, Horvais R, Pouilly N, Domin C, Vallée P, et al. Molecular and phenotypic characterization of near isogenic lines at QTL for quantitative resistance to Leptosphaeria maculans in oilseed rape (Brassica napus L.). Theoretical and Applied Genetics. 2008;117(7):1055–67. doi: 10.1007/s00122-008-0844-x 18696043

44. Jestin C, Vallée P, Domin C, Manzanares-Dauleux MJ, Delourme R. Assessment of a new strategy for selective phenotyping applied to complex traits in Brassica napus. Open Journal of Genetics. 2012;2(4):190.

45. Foisset N, Delourme R, Barret P, Hubert N, Landry B, Renard M. Molecular-mapping analysis in Brassica napus using isozyme, RAPD and RFLP markers on a doubled-haploid progeny. Theoretical and Applied Genetics. 1996;93(7):1017–25. doi: 10.1007/BF00230119 24162475

46. Stachowiak A, Olechnowicz J, Jedryczka M, Rouxel T, Balesdent M-H, Happstadius I, et al. Frequency of avirulence alleles in field populations of Leptosphaeria maculans in Europe. European Journal of Plant Pathology. 2006;114(1):67–75.

47. Liu S, Liu Z, Fitt BD, Evans N, Foster S, Huang Y, et al. Resistance to Leptosphaeria maculans (phoma stem canker) in Brassica napus (oilseed rape) induced by L. biglobosa and chemical defence activators in field and controlled environments. Plant Pathology. 2006;55(3):401–12.

48. Payne RW, Harding SA, Murray DA, Soutar DM, Baird DB, Glaser AI, et al. The guide to Genstat release 10, part 2: Statistics. VSN International: Hemel Hempstead, UK. 2011.

49. Kumar V, Paillard S, Fopa-Fomeju B, Falentin C, Deniot G, Baron C, et al. Multi-year linkage and association mapping confirm the high number of genomic regions involved in oilseed rape quantitative resistance to blackleg. Theoretical and Applied Genetics. 2018;131(8):1627–43. doi: 10.1007/s00122-018-3103-9 29728747

50. Broman KW, Wu H, Sen Ś, Churchill GA. R/qtl: QTL mapping in experimental crosses. Bioinformatics. 2003;19(7):889–90. doi: 10.1093/bioinformatics/btg112 12724300

51. Fopa Fomeju B, Falentin C, Lassalle G, Manzanares-Dauleux MJ, Delourme R. Comparative genomic analysis of duplicated homoeologous regions involved in the resistance of Brassica napus to stem canker. Frontiers in Plant Science. 2015;6:772. doi: 10.3389/fpls.2015.00772 26442081

52. Huang YJ, Jestin C, Welham S, King GJ, Manzanares-Dauleux M, Fitt BDL, et al. Identification of environmentally stable QTL for resistance against Leptosphaeria maculans in oilseed rape (Brassica napus). Theoretical and Applied Genetics. 2016;129(1):169–80. doi: 10.1007/s00122-015-2620-z 26518572

53. Pilet M, Duplan G, Archipiano M, Barret P, Baron C, Horvais R, et al. Stability of QTL for field resistance to blackleg across two genetic backgrounds in oilseed rape. Crop Science. 2001;41(1):197–205.

54. Jestin C, Bardol N, Lode M, Duffe P, Domin C, Vallée P, et al. Connected populations for detecting quantitative resistance factors to phoma stem canker in oilseed rape (Brassica napus L.). Molecular Breeding. 2015;35(8):167.

55. Chalhoub B, Denoeud F, Liu S, Parkin IAP, Tang H, Wang X, et al. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. Science. 2014;345(6199):950–3. doi: 10.1126/science.1253435 25146293

56. Clarke WE, Higgins EE, Plieske J, Wieseke R, Sidebottom C, Khedikar Y, et al. A high-density SNP genotyping array for Brassica napus and its ancestral diploid species based on optimised selection of single-locus markers in the allotetraploid genome. Theoretical and Applied Genetics. 2016;129(10):1887–99. doi: 10.1007/s00122-016-2746-7 27364915

57. West JS, Biddulph J, Fitt BD, Gladders P. Epidemiology of Leptosphaeria maculans in relation to forecasting stem canker severity on winter oilseed rape in the UK. Annals of Applied Biology. 1999;135(2):535–46.

58. Raman H, Raman R, Diffey S, Qiu Y, McVittie B, Barbulescu DM, et al. Stable quantitative resistance loci to blackleg disease in canola (Brassica napus L.) over continents. Frontiers in Plant Science. 2018;9. doi: 10.3389/fpls.2018.00009 29403519

59. McDonald B. How can we achieve durable disease resistance in agricultural ecosystems? New Phytologist. 2010;185(1):3–5. doi: 10.1111/j.1469-8137.2009.03108.x 20088970

60. Delourme R, Brun H, Ermel M, Lucas M, Vallee P, Domin C, et al. Expression of resistance to Leptosphaeria maculans in Brassica napus double haploid lines in France and Australia is influenced by location. Annals of Applied Biology. 2008;153(2):259–69.

61. Larkan NJ, Raman H, Lydiate DJ, Robinson SJ, Yu F, Barbulescu DM, et al. Multi-environment QTL studies suggest a role for cysteine-rich protein kinase genes in quantitative resistance to blackleg disease in Brassica napus. BMC Plant Biology. 2016;16(1):183. doi: 10.1186/s12870-016-0877-2 27553246

62. Li H, Sivasithamparam K, Barbetti M. Soilborne ascospores and pycnidiospores of Leptosphaeria maculans can contribute significantly to blackleg disease epidemiology in oilseed rape (Brassica napus) in Western Australia. Australasian Plant Pathology. 2007;36(5):439–44.


Článok vyšiel v časopise

PLOS One


2019 Číslo 9
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Získaná hemofilie - Povědomí o nemoci a její diagnostika
nový kurz

Eozinofilní granulomatóza s polyangiitidou
Autori: doc. MUDr. Martina Doubková, Ph.D.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#