Introduction

Blackleg (stem canker), caused by the ascomycete fungus Leptosphaeria maculans (Desmaz.) Ces. et De Not. [anamorph: Phoma lingam (Tode ex Fr.) Desmaz.], is one of the most important diseases of canola and rapeseed in many parts of the world1,2. It has been suggested that L. maculans can cause severe infection in a field and reduce the seed yield by more than 50%3. Improving resistance to L. maculans is one of the major objectives in canola breeding programs worldwide, especially due to the fact that the disease is difficult to control with fungicides4.

Efforts have been made to identify and map blackleg R genes in B. napus. The R genes LEM15, LmFr16, LmR1/CLmR17,8, Rlm1, Rlm3, Rlm4, Rlm7 and Rlm96,7,8,9 have been mapped to the B. napus linkage group A07, and Rlm2 to A109. Four additional R genes, LepR1, LepR2, LepR3 and LepR4, originating from an accession of wild B. rapa subsp. sylvestris, have been identified in B. napus or progenies from B. napus x B. rapa subsp. sylvestris. LepR1 and LepR2 were mapped to B. napus linkage groups A02 and A10, respectively10. LepR3, derived from B. rapa subsp. sylvestris and present in the B. napus cultivar Surpass 400, was mapped to the B. napus linkage group A1011. LepR3 and Rlm2 have been cloned with a map‐based cloning strategy, and encode a receptor-like protein (RLP)12,13. Blackleg R genes previously mapped in B. napus are generally the dominant type, except LepR4 (Brassica A-genome), which was mapped to the B. napus linkage group A0614. The R genes BLMR1 and BLMR2 were mapped to the B. napus linkage group A10 in the B. napus cultivar Surpass 40015. All these blackleg R genes were identified through genetic mapping with a marker system, such as RFLPs, Simple Sequence Repeats (SSRs), Amplified Fragment Length Polymorphisms (AFLPs), Cleaved Amplified Polymorphic Sequences (CAPSs), or Sequence Related Amplified Polymorphisms (SRAPs). Developing and genotyping these types of molecular marker can be laborious and time consuming.

Bulk segregant analysis (BSA), which consists of genotyping two bulks of individual plants with extreme phenotypes, was developed to rapidly identify genetic markers linked to genomic regions associated with selected phenotypes16. Presently, the pipelines of BSA and high throughput sequencing have been developed to locate and identify candidate genes associated with selected phenotypes, using BSA RNA sequencing (BSR-Seq)17,18,19.

Canola is the most important oilseed crop in Canada. ‘Quinta’, a winter oilseed rape originating from Europe, was found to be highly resistant to lots of Canadian isolates and was widely used as a differential cultivar for the classification of pathogenicity groups20,21,22,23,24. The first genetic evidence for a gene-for-gene interaction between Brassica and L. maculans was observed between the resistance (R) gene Rlm1 in ‘Quinta’ and the corresponding avirulence gene AvrLm1.25. Delourme et al. (2004) roughly mapped Rlm1 in ‘Quinta’ to linkage group A07. The R gene was further mapped using SSR and CAPS markers in a large genetic interval26.

In western Canada, AvrLm1 was detected in 46% of the L. maculans isolates collected from infested canola stubble between 1997 and 200527. Although recent data showed lower presence of AvrLm1 in L. maculans populations28,29 due to use of Rlm1 in canola cultivars extensively30, Rlm1 could still be valuable for effective control of blackleg disease in Canada as a strategy through rotation of R genes that has been recently implemented.

The objectives of the current study were to: (i) identify genome wide DNA variants to map Rlm1 through BSR-Seq; (ii) determine the precise location of Rlm1; (iii) identify the most probable candidates for Rlm1; and (iv) develop SNP markers tightly linked to Rlm1 in use of marker assisted selection. In this study, Rlm1 was located on chromosome A07 using a modified popoolation2 pipeline withBSR-Seq. To the best of our knowledge, this is the first report on mapping of a blackleg resistance gene using BSR-Seq in Brassica spp..

Materials and Methods

Plant materials

Two doubled haploid lines, DH24288 (resistant, R) from the B. napus cultivar ‘Quinta’ and DH16516 (susceptible, S) from B. napus cultivar ‘Topas’, were kindly provided by Dr. G Séguin-Swartz at Saskatoon Research and Development Centre, Agriculture and Agri-Food Canada. A DH24288 plant (male) was crossed with a DH16516 plant (female) to produce a F1 population. A F1 plant was backcrossed with a DH16516 plant to obtain a BC1 population. The F1 plant was self-pollinated to produce a F2 population.

Plant growth conditions, preparation of L. maculans isolates and plant inoculations

L. maculans inoculum and plant inoculation followed the protocols described previously10. The parents, F1, F2, and BC1 were inoculated with isolate L. maculans SC006 (carrying AvrLm1). The reaction to inoculation on cotyledon was rated 10 to 14 days post-inoculation (dpi) using the 0 to 9 scale described by Williams31. Disease ratings of 0 to 5 and 6 to 9 were considered as resistant and susceptible interactions, respectively. Segregation for resistance and susceptibility in the BC1 population was analyzed using the Chi-square (χ2) test for goodness-of-fit32. B. napus susceptible cultivar ‘Westar’ was used as a susceptible check in this study.

RNA isolation and RNA-seq

The BC1 population was used for RNA-Seq. At 10 dpi, leaf samples from 30 R plants and 30 S plants were combined to form R and S bulks, respectively; each bulk was treated as one biological replicate. Three replicates, consisting of a total of 90 R or 90 S plants, were used. RNA from each sample replicate was isolated using an RNeasy Plant Mini Kit (Qiagen; Toronto, ON) with on-column deoxyribonuclease (DNase) digestion using a Qiagen RNase-Free DNase kit, following manufacturer’s instructions. The RNA concentration and quality were checked using a NanoDrop 2000c Spectrophotometer (Thermo Scientific; Waltham, MA) and an Agilent Bioanalyzer 2100 (Agilent Technologies; Mississauga, ON), to ensure that the RNA integrity number (RIN) was >8 for each sample. The preparation of cDNA library and RNA-seq were performed at Databio2 LLC (Ames, IA).

Sequence alignment, SNP calling and filtration

Raw RNA-Seq reads were trimmed to remove low-quality nucleotides with FASTX-Toolkit (Version 0.0.13)33. GSNAP (Genomic Short-read Nucleotide Alignment Program, version 2016-11-07)34 was performed to map the trimmed reads to the B. napus reference genome35, allowing gap alignment including intron-spanning alignment. SNP calling and filtration for BSR-Seq was performed following the same parameters as previously described by Liu et al.17. The SNP discovery pipeline (123SNP) was downloaded from http://schnablelab.plantgenomics.iastate.edu/software/123SNP/. Reads of the R and S bulks were more than 90% of the total reads aligned to each SNP site. Each SNP site had ≥3 reads with a quality score of SNP base ≥15, and the reads accounted for 20% of the total reads at that SNP site. Moreover, each SNP site for the BSR-Seq analysis was required to have at least five sequencing reads in both the R and S bulks. In addition, two methods for SNP calling were used as previously described18; the single sample alignment (SSA), in which short reads from three biological replicates of R and S plants were aligned to a reference genome. The other was called the pooled sample alignment (PSA), in which short reads from a pool of three R bulks and a pool of three S bulks were aligned to the reference genome as described by Yu et al.18.

Identification of SNP markers tightly linked to Rlm1

In order to verify SNP markers and the target region, an improved PoPoolation236 was employed to analyze the linked SNP markers. (Fig. 1A). Firstly, the same files of R and S bulks were obtained as previously described using GSNAP34. Then, Picard tools (Version 1.96, http://broadinstitute.github.io/picard/) was performed to remove duplicate and ambiguously mapped reads. Finally, the allele frequencies of R and S bulks were compared using PoPoolation236. All analyses used the SSA and PSA methods described previously18 with reference B. napus Darmor-bzh genome (v4.1,http://www.genoscope.cns.fr/brassicanapus/data/)35.

Figure 1
figure 1

Schematic flowchart and disease ratings. (A) Schematic flowchart of the experimental procedure. (B) Average disease ratings of B. napus cultivars ‘Quinta’ and its DH line DH24288. Westar is the susceptible control. The L. maculans isolate SC006 carries AvrLm1. The disease reaction on cotyledons was rated at 10 dpi using the 0 to 9 scale31. Mini bars indicate the standard deviation from three biological replicates of three independent repetitions (n = 9). Letters indicate significant difference based on the Least Significant Difference (LSD) (P < 0.05).

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Identification of Rlm1 candidate genes

In order to identify the candidates for Rlm1 in the target region, all genes in this region were analyzed using the following steps:

  1. 1.

    We annotated all proteins to the target region using InterProScan37.

  2. 2.

    The variation of R genes in the target region was identified using samtools38 and SNPeff 4.139. The variant frequency of Rlm1 was approximately 0.5 in the R bulks and 1 in S bulks, since the resistance genotype would be Rr and susceptible genotype be rr in the BC1 population.

  3. 3.

    Resistance gene prediction

The plant resistance genes were identified using RGAugury pipeline40 with reference B. napus Darmor-bzh genome (v4.1,http://www.genoscope.cns.fr/brassicanapus/data/)35,41.

Gene expression analysis using RNA-Seq

All trimmed RNA-seq reads were aligned18 with reference B. napus Darmor-bzh genome (v4.1,http://www.genoscope.cns.fr/brassicanapus/data/)35 using Tophat 242,43. Tophat2 alignment parameters were set to allow a maximum of two mismatches and exclude reads mapping to more than one position on the reference. Transcriptome assembly and differential expression analysis for RNA-Seq were conducted using cufflink, with FDR < 0.05 and minimum fold change ≥2.

Genotyping SNP and InDel markers

Selected SNPs identified in the target region were confirmed using the Kompetitive Allele Specific PCR (KASP) method (http://www.lgcgroup.com), following manufacturer’s instructions. The primer sequences of KASP assay were presented in Table S1. The PCR reaction was performed using StepOne Plus Real Time PCR system (Applied Biosystem, Mississauga, ON).

Phylogenetic tree construction and sequence alignment

The protein sequences of STN7 were searched using Blastp with default parameters in the nr database of NCBI. Alignment was performed using MAFFAT44 with distance correction off, gaps excluded. Then the alignment sequence computed the residue-wise confidence scores and extracted well-aligned residues using GUIDANCE245. The neighbor-joining (NJ) clustering method46 was performed to build a phylogeny tree with bootstrap 1000. Visualization was performed using Interactive tree of life (iTOL) v4 (https://itol.embl.de/)47.

Results

Identification of Rlm1 in the B. napus DH line DH24288

DH24288 was derived from a single microspore of the cultivar ‘Quinta’ (B. napus). Its resistance to the L. maculans isolate SC006 (AvrLm1) was compared with its donor (Quinta) and the susceptible cultivar ‘Westar’ (Fig. 1B) based on cotyledon inoculation. As expected, ‘Westar’ was highly susceptible whileDH24288 and ‘Quinta’ showed a high level of resistance, implying that DH24288 carries Rlm1.

RNA-Seq and sequence alignment

In order to identify the resistance gene in the DH line, we tested the BC1 segregating population and their parental lines with the isolate SC006. DH16516 was highly susceptible (Fig. 2). The BC1 population consisted of 571 R and 596 S plants, which would fit a 1:1 ratio (χ2 = 0.54, P = 0.46). Furthermore, the F2 population showed 2,216 R and 696 S plants, which would fit a 3:1 ratio (X2 = 1.88, P = 2.37), confirming that Rlm1 is a single dominant gene in DH24288. A total of 180 plants with a clear R (DR ≤ 2) and S (DR ≥ 8) designation, consisting of 90 R and 90 S (Fig. 2) were selected from the population for mapping of Rlm1 using BSR-Seq.

Figure 2
figure 2

Frequency distributions of resistance phenotypes in the BC1 population derived from DH16516 x DH24288/’Quinta’. Parents and BC1 plants were inoculated with L. maculans isolate SC006. The symptoms on cotyledons was rated at 10–14 dpi using the 0 to 9 scale31. Disease ratings of 0 to 4 and 5 to 9 were considered as resistant and susceptible interactions, respectively. The lines in the red boxes were selected as R and S bulks for RNA-seq analysis.

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More than 90 million 101 paired-end reads were obtained, including 47 million from R bulks and 45 million from S bulks. After quality control and clipping of adapters, more than 99% of the reads were retained for both bulks, with the average length reduced to about 98 bp (Table S2).

The average short read counts and accumulated short read lengths were 30.6 million (M) and 3003 Mb for R bulks, and 29.6 M and 2897 Mb for S bulks, using the SSA method (Table S3). This provided an average depth of coverage for the transcripts of reference genome at 30 folds in R bulks and 29 folds in S bulks. More short reads were aligned to the longer chromosomes A09, C03, C04, and C09, while fewer short reads were assembled in the shorter chromosomes A08 and A10 (Fig. 3). Short reads from three R bulks and three S bulks were further aligned using PSA. As observed previously with the SSA method, more sequences were aligned to A09, C03, C04, and C09, and fewer to A08 and A10 (Fig. 3). A total of 91.9 M short reads were aligned to the B. napus reference genome, resulting in an alignment of 9008 Mb in length and a coverage of 90 folds of transcripts of the reference genome from the pool of three R bulks, and 88.6 M short reads were aligned, resulting in an alignment 8691 Mb in length and an 87-fold coverage from the pool of three S bulks (Table S3).

Figure 3
figure 3

Counts of short reads aligned to chromosomes of the B. napus reference B. napus Damor-bzh genome35 in single sample alignment (SSA) and pooled sample alignment (PSA), respectively.

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Identification of variants in R and S bulks

About 106K SNPs and 9K InDels were identified in R bulks and 116K SNPs and 9K InDels in S bulks were identified using the SSA method (Table S4). The counts of SNPs and InDels identified using PSA were higher than those using the SSA method, with 288K SNPs and 20K InDels in R bulks and 281K SNPs and 19K InDels in the S bulks (Table S4). There was a strong positive correlation between the numbers of SNPs and InDels (r = 0.97) within R and S bulks using either SSA or PSA. The number of SNPs and InDels varied among chromosomes (Fig. 4), with chromosomes A03 and C03 carrying more variants than others. However, SNPs and InDels seemed to show a similar distribution pattern on different chromosomes among the R and S bulks based on both SSA (Fig. S1) and PSA (Fig. S2).

Figure 4
figure 4

Counts of SNPs and InDels in single sample alignment (SSA) and pooled sample alignment (PSA). (A) Counts of SNPs and InDels in SSA method, (B) counts of SNPs and InDels in PSA.

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Comparison and annotation of variants in R and S bulks

Common or monomorphic (mono) variants which were present in both R and S bulks, and unique or polymorphic (poly) variants observed only in R or S bulks were identified. The percentage of mono and poly variants identified using PSA was more than those of SSA on each chromosome, although the ratio of mono and poly variants identified with the two methods were similar (Fig. 5). The mono variants comprised of 51.7% (48.1–54.9%) of the variants identified across the B. napus genome using PSA, while poly variants comprised of 48.3% (45.1–51.9%) (Table S5). There were no differences among chromosomes in terms of the number of mono and poly variants found in R and S bulks except on chromosome A07, where more poly variants were found in R bulks than in S bulks (Fig. 5B)

Figure 5
figure 5

Number of variants (SNPs and Indels) per Mb identified in R and S bulks in comparison with the reference genome of B. napus. (A) Number of monomorphic variants in R and S bulks by SSA and PSA methods. (B) Number of plolymorphic variants in R or S bulks by SSA and PSA methods.

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In order to investigate the effects caused by the variants, all low-quality sequence reads were filtered out using the B. napus reference genome35. Only the variants identified with PSA were annotated using SNPeff because they included all variants identified through SSA. In total, 18,857 InDels and 272,837 SNPs were annotated in R bulks and 18,816 InDels and 266,772 SNPs in S bulks. The percentage of variant effect by gene regions was almost the same between R and S bulks (Fig. 6); more than 60% of variants were identified in regions down- and up-stream of the gene Rlm1, with about 10% of InDels and 20% of SNPs in the gene exon region. Additionally, around 10% of the variants were located in the intergenic region and several variants were in the gene intron region.

Figure 6
figure 6

Percentage of variant effects by region using SNPeff analysis. (A) Percentage of InDel. (B) Percentage of SNP.

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Refining the interval of Rlm1 using SNP markers identified through BSR-Seq

Rlm1 was located on chromosome A07 within a region of 13.07 Mb to 22.11 Mb based on significant SNPs (P value < 10−8; Fst value > 0.2) using modified popoolation2 (Figs 7A,B, Fig. S5). A total of 18,035 variants were identified within this region using PSA, including 16,967 SNPs, 563 insertions and 599 deletions.

Figure 7
figure 7

Rlm1 was located on chromosome A07 using Popoolation2 with window slide (window size = 1000 bp, slide size 100 bp). (A) Significant variants by substantial Fisher’s exact values in whole genome (-log (P value) > 8)). (B) Significant variants by substantial Fisher’s exact values in chromosome A07 (-log (P value) > 8). Green dots indicate the significant variants in the Rlm1 interval. (C) Fine mapping of Rlm1 between 19.93 Mb and 20.03 Mb on chromosome A07 using KASP assays with the BC1 population (a total of 1,022 plants) and F2 population (a total of 2,912 plants). (D) BnaA07g27460D gene structure and variants.

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In order to narrow down the interval of Rlm1, a total of 1,022 BC1 plants and 2,912 F2 plants, including the 90 R and 90 S plants used for RNA-Seq, were inoculated with the isolate SC006 and genotyped with two flanking SNP markers designed based on SNP information in the Rlm1 region (Fig. 7C). A total of 13 recombinant lines were identified, and these recombinants were further confirmed to be within the genetic interval with an additional 13 SNP markers (Fig. 7C and Table S1). As a result, Rlm1 was narrowed down to a 100 Kb region (19.93–20.03 Mb) flanked by markers SNP_A07_12_19.93 and SNP_A07_11_20.03 on chromosome A07 (Fig. 7C). A total of 152 variants (Table S7) could be annotated to 19 B. napus genes (Table S6) in the Rlm1 region, including 62 variants identified in both R and S bulks. The variants in the Rlm1 region were examined using the Integrative Genomics Viewer (IGV)48. One gene (BnaA07g27460D) showed similar frequencies of DNA variants at about 50% in R bulks and 100% in S bulks (Fig. S5 and Table S7). A total of 11 polymorphic SNPs in BnaA07g27460D were identified, including 1 downstream, 9 synonymous, and two missense SNPs. BnaA07g27460D (19,986,679–19,989,481 bp) encodes Serine/threonine dual specificity protein kinase with a catalytic domain. The full-length protein sequence was used to search for homologous proteins in the NCBI database, which was aligned using MAFFT and used to construct a neighbor-joining tree with UPGMA clustering (Fig. S6). The results indicated that BnaA07g27460D was homologous to STN7 in predicted genes of B. rapa and B. oleracea, and A. thaliana (Fig. S6).

Analysis of differential expression genes (DEGs) in R and S bulks

The expression of genes in the Rlm1 region may provide additional molecular evidence for the confirmation of the candidate R gene. A total of 153 DEGs were identified in comparing R bulks with S bulks using cufflink with FDR < 0.05 (Table S8), and18 of them were located within the Rlm1 region. However, the gene expression level for BnaA07g27460D was not significantly different between R and S bulks.

Discussion

In this study, a BSR-Seq strategy was used to map Rlm1 to B. napus chromosome A07 in a 9-Mb region. More than 18,000 variants were identified in this region. Selected SNP loci in the interval were analyzed using KASP assay. A total of 1,022 plants in BC1 and and 2,912 plants in F2) were analyzed with 13 KASP markers. The Rlm1 interval was eventually narrowed within an interval of 100 kb through linkage analysis. Previously, Rlm1 was predicted to be in an interval of approximately 920 kb between a SSR marker (sN9539) and a CAPS marker (Ind07-02) though Blast search26. The results indicate that BSR-Seq in combination with KASP assay is much more powerful technology than using marker systems for fine mapping of blackleg resistance genes49,50,51,52,53,54,55, which marker systems, such as RFLPs56, AFLPs57, SSRs58, CAPSs59, and SRAPs60, are laborious, time consuming, and low efficiency for identification of QTLs or for marker-assisted selection (MAS). BSR-seq has been used for fine mapping of several resistance genes to clubroot in Brassica species18,61,62. However, the application and efficacy of the modified popoolation2 comparing with other mapping by sequencing methods still needs to be determined.

There were more DNA variants identified in chromosomes A03 and C03 than the other chromosomes. The number of variants is usually associated with chromosome length18. C03 is the longest chromosome with 60.6 Mb in length in the sequencedreference B. napus Darmor-bzh genome35. In addition, these two chromosomes carry higher numbers of genes although A03 is only 29.8 Mb in length (Table S2).Therefore, it is not surprising that more DNA variants were identified based on BSR-Seq.

In this study, Rlm1 was located within a range of 100 Kb on chromosome A07. A total of eight blackleg R genes (LEM15, LmFr16, LmR1/CLmR17,8, Rlm1, Rlm3, Rlm4, Rlm7 and Rlm96,7,8,9) have been reported previously on chromosome A07 (linkage group N7),. LmR1/CLmR1 was found to co-segregate with three molecular markers, which were located around the 15.8 Mb of chromosome A07, by blasting the marker sequences against the B. napus genome database8. The homologous region of LEM1 and LmFr1 cannot be identified based on the genomic information available. The genetic position of Rlm3, Rlm4, Rlm7, and Rlm9 were clearly different from that of Rlm19. In our study, Rlm1 was fine mapped to an interval between 19.93 Mb and 20.03 Mb with flanking markers SNP9_A07_12_19.93 and SNP8_A07_11_20.03 on chromosome A07, indicating that Rlm1 is unlikely allelic to LmR1/CLmR1.

In the mapping interval, no RLP genes described as blackleg resistance genes35 were identified. DNA variants were only identified in gene BnaA07g27460D (Fig. S5 and Table S7). Hence, it is possible that BnaA07g27460D was a candidate for Rlm1. BnaA07g27460D is homologous to STN7 in predicted genes of B. rapa and B. oleracea, and A. thaliana. Earlier studies on Arabidopsis clearly demonstrated that thylakoid phosphorylation is predominantly mediated by the protein kinases STN763,64 and STN865. However, several recent studies have revealed that light intensity or quality induces the reduction/oxidation (redox) state of the photosynthetic electron chain66. STN7 has been verified to operate in retrograde signaling through controlling redox balance in the electron transfer chain67. These confirmations indicate that STN7 is involved in plant defense reactions by regulating the excitation of energy distribution between PSII and PSI via the phosphorylation of thylakoid membrane to control cell signaling and systemic response via ROS-induced, hormone-mediated signaling networks67,68. In this study, although BnaA07G27460D was considered as the candidate gene for Rlm1, other candidates may exist. Firstly, the coverage of the sequence reads for several genes in the Rlm1 region was insufficient for definitive inference of Rlm1 based only on BSR-Seq. Secondly, the genomic sequence of Darmor-bzh was not complete in the Rlm1 region. Four gaps were found between 19.93 Mb and 20.03 Mb, form 19,922,209 to 19923154 bp, from 19,949,953 to19,960,559 bp, from 19,968,763 to 19,974,252 bp, and from 20,017,902 to 20,020,342. Thirdly, the sequence of Darmor-bzh does not carry Rlm1 gene69. Hence, gene cloning and transformation are necessary to confirm the candidate gene of Rlm1, but that is out of the scope of the current study. More biochemical and molecular confirmations can be used to confirm the involvement of STN7 in blackleg resistance.

A total of 153 DEGs were identified in comparing R bulks with S bulks, and18 of them were located within the Rlm1 region. However, the gene expression level for BnaA07g27460D was not significantly different between R and S bulks although DNA variants were identified in the gene. The reason for this is to be determined. No significant difference in R gene expression was previously observed during fungal infection between R and S materials18.

Breeding for blackleg resistance in canola is one of the most important objectives in many parts of the world. Use of highly specific markers in MAS could be useful to accurate assess the reaction of lines under controlled conditions. KASP offers cost-effective and scalable flexibility in applications. A large number of SNP sites associated with Rlm1 were identified based on BSR-Seq. In total, 13 robust SNP markers were confirmed to be associated with Rlm1 using KASP assay. The closely linked markers shown in Table S7 could be used in MAS for Rlm1.