https://orcid.org/0000-0001-6891-0471
Figures
Abstract
The genetic background of the immune response of rye to leaf rust (LR), although extensively studied, is still not well understood. The recent publication of the genome of rye line Lo7 and the development of efficient transcriptomic methods has aided the search for genes that confer resistance to this disease. In this study, we investigated the potential role of rye orthologs of wheat Lr genes (Lr1, Lr10, Lr21, Lr22a, and RGA2/T10rga2-1A) in the LR seedling-stage resistance of inbred rye lines D33, D39, and L318. Bioinformatics analysis uncovered numerous Lr orthologs in the Lo7 genome, namely, 14 ScLr1, 15 ScRga2, and 2 ScLr21 paralogs, and 1 each of ScLr10 and ScLr22a genes. The paralogs of ScLr1, ScRga2, and ScLr21 were structurally different from one another and their wheat counterparts. According to an RNA sequencing analysis, only four wheat Lr gene orthologs identified in the Lo7 genome (ScLr1_3, ScLr1_4, ScLr1_8, and ScRga2_6) were differentially expressed; all four were downregulated after infection with compatible or incompatible isolates of Puccinia recondita f. sp. secalis (Prs). Using a more precise tool, RT-qPCR, we found that two genes were upregulated at 20 h post-infection, namely, ScLr1_4 and ScLr1_8 in lines D33 and D39, respectively, both of which have been found to be resistant to LR under field conditions and after treatment with a semi-compatible Prs strain. We were unable to discern any universal pattern of gene expression after Prs infection; on the contrary, all detected relationships were plant genotype-, Prs isolate-, or time-specific. Nevertheless, at least some Lr orthologs in rye (namely, ScLr1_3 ScLr1_4, ScLr1_8, and ScRga2_6), even though mainly downregulated, may play an important role in the response of rye to LR.
Citation: Krępski T, Olechowski M, Samborska-Skutnik I, Święcicka M, Grądzielewska A, Rakoczy-Trojanowska M (2023) Identification and characteristics of wheat Lr orthologs in three rye inbred lines. PLoS ONE 18(7): e0288520. https://doi.org/10.1371/journal.pone.0288520
Editor: Shailender Kumar Verma, University of Delhi, INDIA
Received: October 17, 2022; Accepted: June 27, 2023; Published: July 13, 2023
Copyright: © 2023 Krępski et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: (http://www.ncbi.nlm.nih.gov/bioproject/888031; BioProject ID PRJNA888031.
Funding: This study was financially supported by National Science Centre, grant no. 2018/31/B/NZ9/00439. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Rye (Secale cereale L.), one of the most economically important cereals in Central and Eastern Europe, is strongly resistant to various biotic and abiotic stresses. Although regarded as disease tolerant, this crop can be attacked by up to 37 diseases, namely, 2 bacterial and 35 fungal ones (https://www.apsnet.org/edcenter/resources/commonnames/Pages/Rye.aspx). Among these diseases, leaf rust (LR; also termed brown rust), is caused by an airborne pathogen, the obligate biotrophic basidiomycete Puccinia recondita f. sp. secalis (Prs) [1,2]. Estimated yield losses due to leaf rust are typically up to 40% [3]; under conditions favorable for the development of infection, however, losses can be as high as 80% [4]. These losses are most often associated with decreases in the number of kernels per head and kernel weight, which are reduced by an average of 14% [3].
In rye, resistance to LR is usually controlled by a single, or occasionally two or three, dominant gene(s) [5]. These genes are referred to as Pr genes to distinguish them from their Lr counterparts, which confer resistance to LR in wheat. To date, 17 dominant Pr genes, including Pr1-5, Pr-d–f, Pr-i–l, Pr-n, Pr-p, Pr-r, and Pr-t [6,7], have been identified by Mendelian methods on both the long and short arms of five of the seven rye chromosomes (1R, 2R, 4R, 6R, and 7R). Most Pr genes have been mapped to chromosome 1R, which has been widely used as a chromatin source in wheat breeding [8]. This set complements the recently identified Pr6 gene, located on chromosome 7RS [9].
Most of these genes, specifically, Pr1–Pr5, Pr-d–f, Pr-n, Pr-p, and Pr-r, protect rye against disease development [7] and may therefore be considered all-stage resistance genes [10]. Molecular studies focused on rye Pr genes are limited to two recently published reports by Vendelbo et al. [9,11]. Using a genome-wide association study, the authors mapped five LR resistance-associated quantitative trait loci on chromosome arms 1RS, 1RL, 2RL, 5RL, and 7RS, of which two located on chromosome arms 1RS and 7RS were of particular importance. The resistance-associated marker on chromosome arm 1RS was physically co-localized with molecular markers for Pr3. The region on chromosome arm 7RS contained a large number of nucleotide-binding leucine-rich repeat (NLR) genes, one of which, provisionally denoted Pr6, was similar (at the protein level) to the wheat LR resistance gene Lr1 situated on chromosome arm 5DL. In contrast to these results, Milczarski et al. [12] identified chromosome 5R as the location of LR resistance-related quantitative trait loci with the highest impact on resistance to this disease.
The molecular aspects of rye response to LR have also been analyzed in relation to secondary metabolism. Święcicka et al. [13] recently found a relationship between expression patterns and levels of genes controlling benzoxazinoid (BX) biosynthesis and rye response to infection with LR. One of the examined genes, ScBx4 encoding a cytochrome P450 monooxygenase, was induced in infected and mock-treated plants at all-time points (8, 17, 24, and 48 h post-treatment [hpt]). Because this observation was fully in line with an earlier finding that a single nucleotide polymorphism (ScBx4_1583) in the ScBx4 gene is stably associated with the field resistance of adult plants to LR [14], the authors suggested that the identified polymorphism, ScBx4_1583, is associated with both non-race-specific adult-plant and seedling-stage resistance.
In general, the plant immune system includes two layers of pathogen–host interaction. The first layer generates pathogen-associated molecular pattern-triggered immunity (PTI) in host plants. To suppress PTI, pathogens secrete effectors into host plants. The R genes of host plants can recognize these effectors, thereby initiating the second layer: intracellular effector-triggered immunity (ETI) [15]. Plant resistance to disease (including LR) may be (1) pathogen race-specific, (2) non-race- and non-pathogen-specific, or (3) characterized by non-host resistance [16]. Consistent with the gene-for-gene model, the first class of resistance depends on single dominant R genes. The R genes encode proteins belonging to immune receptors of the nucleotide-binding leucine-rich repeat (NBS-LRR) class, which recognize Avr proteins produced by pathogens [17,18]. Most R genes have three or four exons. Exons one and two respectively encode the toll/interleukin-1 receptor (TIR)/coiled-coil (CC) domain (TIR mainly present in dicots, and CC in both di- and monocots) and the NBS domain (also called the NB-ARC domain, for nucleotide-binding adaptor shared by APAF-1, R proteins, and CED-4) on the C terminal, whereas the third (and fourth) exon(s) encode the leucine-rich repeat (LRR) domain on the N terminal [19]. Exceptions exist, however; for example, Andersen et al. [20] discovered five NB-ARC-encoding genes with a TIR domain but no LRR domain in wheat. In cereals, the NBS domain is composed of six conserved motifs: P-loop, RNBS-A, Kinase-2, Kinase-3a, RNBS-C, and GLPL [21].
Plant R genes activate a defense response and are differentially expressed (usually upregulated) after pathogen infection, regardless of the plant–pathogen interaction [22]. Nevertheless, R-gene downregulation has occasionally been observed, such as in Arabidopsis after infection with two pathogens (Hyaloperonospora parasitica and Erisyphe cichoracearum) [23], and in hops and tobacco in compatible reactions with Verticillium albo-atrum [24] and Ralstonia solanacearum [25], respectively. An analysis performed by Peng and Yang [26] revealed that R genes may not be induced at all, especially in the incompatible reaction between wheat and Puccinia triticina.
Unlike the scenario in rye, several R genes in wheat (the closest relative of rye) that confer resistance to LR at the seedling stage have been sequenced and molecularly characterized. These genes are as follows: Lr1 on chromosome 5DL [27], Lr10 on chromosome 1AS (together with an additional gene essential to its function, RGA2/T10rga2-1A [28,29]), Lr13/LrLC10 on chromosome 2BS [30], Lr21 on chromosome 1DS [31,32], and Lr22a on chromosome 2DS [33]. Investigation of their differential expression is limited to several works but none employed RNA-sequencing (RNA-seq) or quantitative reverse transcription PCR (RT-qPCR) methods. As shown by Cloutier et al. [27], the expression level of Lr1, as determined by reverse transcription PCR (RT-PCR) analysis, corresponded with the phenotype (resistant or susceptible). Kumar et al. [34], using the Affymetrix GeneChip® Wheat Genome Array, demonstrated that Lr1 triggers early initiation of a set of signaling cascades that leads to activation of defense- and stress response-related genes. Information on the expression of the T10rga1/Lr10 gene has been reported by Feuillet et al. [28], who observed that overexpression of Lr10, as measured by northern blotting, was correlated with enhanced resistance to LR and complete suppression of rust sporulation. No expressional data are available for three other aforementioned genes.
The aim of this study was to identify and characterize orthologs of wheat genes with a confirmed role in the immune response to LR in the newly released rye Lo7 genome [35] and in three rye inbred lines (D39, D33, and L318). We also conducted structural and expression analyses to determine if the orthologous genes are affected by LR at the seedling stage.
Materials and methods
Plant materials
We used three unrelated rye inbred lines as plant materials in experiments: L318, bred by the Department of Plant Genetics, Breeding and Biotechnology, Warsaw University of Life Sciences (Warsaw, Poland), and D33 and D39, both developed by Danko Plant Breeding, Ltd. (Poland). The inbred lines were selected according to the results of experiments described in two published studies, namely, measurements of BX contents of field-grown plants after a natural vernalization period [14] (S1 Table) and comparisons of seedling-stage responses to artificial infection with a partially compatible strain of Prs [13].
Pathogen selection
In experiments in this study, rye inbred lines were infected with four Prs isolates selected by preliminary screening of 15 single-spore isolates. The selections were based on detached-leaf inoculations (performed as described by Święcicka et al. 2020 [13]) followed by confirmation in planta. Each isolate was re-tested on twenty-four 20-day-old seedlings (3 pots × 8 plants) of each inbred line cultivated under a 16-h/8-h photoperiod, 50% humidity, and 22°C (day) and 18°C (night) temperatures. Immediately after infection, plants were transferred to a room maintained at 18°C, covered with black boxes to preserve darkness and 100% humidity, and incubated for 24 h. The specificity of the plant–pathogen interaction, that is, whether the interaction between the plant and the pathogen was compatible (medium to large uredinia, with chlorosis; or medium to large uredinia, with little or no chlorosis; infection types 3 and 4 according to the Murphy scale [36] (S1 Fig) or non-compatible (no visible signs of infection, chlorosis, and necrotic flecking; infection types 0 and 0; according to the Murphy scale [36] (S1 Fig) was evaluated 10 days after inoculation.
Finally, four isolates derived from single spores were selected for the main experiment. Two isolates, no. 1/1.6 (non-compatible) and no. 83/2/2.2_5x (compatible), were used for inoculating lines D33 and D39. Two other isolates, no. 81/r/5_5x (non-compatible) and no. 88/o/1_5x (compatible), were applied to line L318. The infection scheme and plant–pathogen interactions are presented in Table 1.
Experimental design
Seeds of the three rye inbred lines (D33, D39, and L318) were initially sown in Petri dishes lined with wet tissue paper and left in the dark for 2 days at 22°C. Germinating seeds were then transferred into 12-cm diameter plastic pots (10 seedlings per pot) filled with sterilized peat substrate and maintained for 10 days in a growth chamber at 22°C under a 16-h light/8-h dark photoperiod at an illumination intensity of 60 μmol m−2 s−1.
Experiments were performed with three biological replicates, each comprising one pot with 10 plants, and two time points (20 hours post treatment, hpt and 36 hpt). The time points were selected based on our previous research [13] which showed that the highest number of spores forming haustorium mother cells (HMC) are observed between 20th and 36th hpt. Each rye inbred line was represented by 18 pots: 6 with mock-treated controls, 6 inoculated with a compatible Prs isolate, and 6 treated with a non-compatible isolate.
Prs- and mock treatments
Spores from a single-spore isolate of Prs were suspended in Novec-7100 engineered fluid (at a density of 1 mg cm−3). Plant infection was carried out using brown glass diffusers (Roth, Basel, Switzerland). Control (mock) plants were treated in the same way as plants inoculated with Prs, except that the applied Novec-7100 engineered fluid lacked Prs spores. After treatment, plants were maintained as described above.
Sampling of plant materials
Plant material was collected two times: 20 hpt and 36 hpt. After sampling, plant tissue was immediately frozen in liquid nitrogen and stored in a freezer at −80°C.
DNA extraction for ScLr gene identification and sequencing
To identify wheat Lr orthologs in rye (hereafter termed ScLr genes), DNA was isolated from young leaves of the three rye lines (D33, D39, and L318) using a Plant and Fungi DNA Purification kit (EurX, Gdańsk, Poland). DNA quantity and quality were checked on a NanoDrop 2000 spectrophotometer and by visualization on 1% agarose gels.
RNA extraction for expression analysis
Total RNA was extracted from approximately 100 mg of frozen leaves of mock- and Prs-treated rye lines (D33, D39, and L318) using a mirVana miRNA Isolation kit plus Plant RNA Isolation Aid (Thermo Fisher Scientific, Waltham, MA, USA). The isolated RNA was dissolved in 50 μl RNase-free water, and RNA yield and purity were estimated using a NanoDrop 2000 spectrophotometer and a Qubit 4 fluorometer. Subsequently, the extracted RNA was treated with DNase I (Thermo Fisher Scientific, Waltham, MA, USA) for removal of genomic DNA contamination in accordance with the manufacturer’s protocol and stored at −80°C.
Identification and characterization of rye Lr orthologs by bioinformatics analysis
To identify rye Lr orthologs, coding sequences (CDSs) of known wheat Lr genes, including Lr1, Lr10, RGA2/T10rga2-1A, Lr21, and Lr22a, were first aligned with the genome of rye line Lo7 [35] using the standalone NCBI BLAST+ v2.9.0 program. The best matches (dc-megablast: e-value ≤ 1 × 10−6, sequence identity ≥ 70%, and query coverage per HSP ≥ 30%) were chosen for further analysis. The identified rye Lr orthologs were named by prefixing Sc to the Lr gene name used as a query in the BLAST search and appending numbers that successively increased as the bit score parameter for the BLAST results decreased. In other words, the number 1 always corresponded to the most similar ortholog to the wheat Lr gene, whereas the highest number was assigned to the ortholog with the lowest similarity. The structures of the identified wheat Lr gene orthologs in rye (ScLr genes) were collected from the gff3 file (the version containing all predicted genes) available at the same site as the above-mentioned rye Lo7 genome. In addition, conserved domains of each analyzed ScLr gene were identified using the NCBI Conserved Domains Database [37] and visualized together with exon–intron structures using GSDS v2.0 [38]. A phylogenetic tree of ScLr proteins was reconstructed by maximum likelihood using the Phylogeny.fr platform [39]. ScLr protein transmembrane domains and subcellular locations were predicted using the TMHMM v2.0 server (http://www.cbs.dtu.dk/services/TMHMM/) and TargetP v2.0 (Organism: Plant) [40], respectively.
RNA-sequencing analysis
Total RNAs extracted as described above from rye plants were sent to Genomed S.A. (Warsaw, Poland) for RNA-seq, assembly, and primary gene expression analysis. In brief, RNA-seq libraries were prepared using a NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (NEB, USA). In total, 54 cDNA libraries were sequenced (S2 and S8B Tables) in PE150 mode on a NovaSeq 6000 system (Illumina). The resulting sequencing reads were filtered in Cutadapt v3.0 (with the parameters: minimum-length = 15 and quality-cutoff = 25) [41], and quality reports were generated using FASTQC v0.11.8 [42]. After trimming with Cutadapt, the average transcriptome coverage by RNA-seq was 110× per library with an average read length of 136 bp. All reads ≥ 20 bp were then mapped to the S. cereale Lo7 reference genome [35] using Hisat2 v2.2.0 [43] with the library preparation option ‘rna-strandness RF’. Next, paired reads mapped to individual genes were counted in HTseq [44] using the ‘—stranded = reverse’ option to differentiate transcript strands. For all other HTseq settings the default option was used. Gene annotations were assigned according to the gene description file (gff3 file, the version containing all predicted genes) from the Lo7 S. cereale genome [35], and final results were compiled in R v3.6.3 [45] (R Core Team 2020) using DESeq2 v1.26.0 [46]. Finally, significant differentially expressed genes (DEGs) were identified, grouped, and analyzed using Microsoft Excel v2016 (Microsoft, USA).
The following criteria were used for identification of significant DEGs: |log2 fold change| ± 0.5 and false discovery rate < 0.05. No cut-off parameter for the average value of the raw read counts was used, because some NBS domain-containing genes are known to be extremely weakly expressed [26] and thus it was not intended to exclude these genes from the analysis. RNAseq (fastq) data has been deposited in NCBI (http://www.ncbi.nlm.nih.gov/bioproject/888031; BioProject 208 ID PRJNA888031).
Primer design and gene sequencing
Primers for amplification, sequencing, and RT-qPCR analysis of the studied genes (ScLr1_3, ScLr1_4, ScLr1_8, and ScRga2_6) in the three rye lines (D33, D39, and L318) were designed using NCBI Primer-BLAST [47]. The rye Lo7 genome assembly (GenBank: GCA_902687465.1) was used as a target template for designing primers and checking primer-pair specificity. To assess designed primer quality, we used PCR Primer Stats [48] to test for the presence of hairpins and OligoAnalyzer Tool (Integrated DNA Technologies, USA) to check for potential homo- and heterodimer formation. The complete list of primers used in this study is provided in S4 Table. The PCR amplicons (ranging from 837 to 1087 bp) obtained from rye lines D33, D39, and L318 were sent to Genomed S.A. for DNA sequencing by the Sanger method. The generated sequences were analyzed and manually annotated in SnapGene Viewer 5.2.4 (GSL Biotech, USA), and sequence comparisons and DNA fragment assembly were carried out in Clustal Omega [49]. Primers for RT-qPCR were then designed to amplify the sequenced gene regions.
RT-qPCR analysis of selected orthologs of wheat Lr genes
The RNA-seq-based expressions of four selected Lr gene orthologs in rye (ScLr1_3, ScLr1_4, ScLr1_8, and ScRga2_6) were validated by RT-qPCR. For the RT-qPCR analysis, 1 μg of total RNA (extracted as described in section RNA extraxction for expression analysis) was used as the template for cDNA synthesis with a RevertAid First Strand cDNA Synthesis kit (Roche, Basel, Switzerland). The analysis was performed in 96-well plates, with three biological and two technical replicates, on a LightCycler 96 Real Time System (Roche). The RT-qPCR cycling conditions were as follows: 10 min of denaturation at 95°C followed by 35 amplification cycles (10 s at 95°C, 10 s at 57°C, and 15 s at 72°C). The amplifications were performed in 20-μl reaction volumes consisting of 4 μl cDNA (5 ng/μl), 1 μl of each gene-specific primer (5 mM), 4 μl RNase-free water, and 10 μl FastStart Essential DNA Green Master Mix (Roche). Relative expression levels were calculated according to the 2−ΔΔCt method [50] using the expressions of the barley actin gene HvAct (GenBank: AY145451 [13]) and the ADP-ribosylation factor (arf) gene TaADP-RF (GenBank: BJ242826.1; primer pairs designed by Giménez et al. [51]) as references. Significant differences in gene expression between Prs-treated rye plants and controls (untreated plants) were identified using the REST tool [52].
A graphical presentation of all experiments is shown on S3 Fig.
Results
Identification and characterization of Lr orthologs in the Lo7 genome
Orthologs of the following wheat R genes conferring seedling-stage resistance to LR were identified in the rye Lo7 genome: Lr1, Lr10, RGA2/T10rga2-1A, Lr21, and Lr22a. Our bioinformatics analysis uncovered several orthologs of Lr1 (ScLr1_1–ScLr1_14) and Rga2 genes (ScRga2_1–ScRga2_15), two orthologs of Lr21 (ScLr21_1 and ScLr21_2), and one ortholog each of Lr10 (ScLr10) and Lr22a (ScLr22a) (Table 2).
Rye orthologs DNA sequence identity ≥ 70% and e-value ≤ 10−6, query coverage per HSP ≥ 30%. Abbreviation “qcov” refers to query coverage per HSP (High Scoring Pair).
Most ScLr1 genes were found to have one exon in the CDS region, similar to wheat Lr1. The exceptions were ScLr1_3, ScLr1_8, and ScLr1_11, with an intron near the end of the CDS (Fig 1). Wheat Lr1 genes also have an intron; however, this intron in wheat is located after the stop codon, at the beginning of the 3′ UTR [27]. Although most ScLr1 genes had CDSs of similar size to those of Lr1 genes, the CDSs of three (ScLr1_9, ScLr1_10, and ScLr1_14) were definitely shorter than in their wheat orthologs (S5 Table). Bioinformatic analysis indicated that several rye ScLr1 paralogs (ScLr1_1, ScLr1_2, ScLr1_4, ScLr1_6, and ScLr1_7) encode a signal peptide in their N-terminal, similar to Lr1 gene (S7 Table). The identified amino acid sequences forming the signal peptide in proteins encoded by the Lr1 gene and ScLr genes are highly conserved (S4 Fig). No signal peptide was detected in the remaining ScLr1 genes. In addition, in silico analysis revealed that the protein encoded by the ScLr1_7 gene is a transmembrane protein (S6 Table).
Conserved domains localization for each gene was marked: CC–Coiled-coil domain, NB-ARC–NB-ARC domain, PLN03210 –PLN03210 domain (Resistant to P. syringae 6; Provisional), LRR–Leucine-rich repeat domain, NEAT–NEAr Transport domain, AP2—AP2 domain, PHA03269—PHA03269 domain, PHA03269—PHA03269 domain, EEP—Exonuclease-Endonuclease-Phosphatase domain, GHB—Glycoprotein hormone beta chain homologues domain, RVT_2—Reverse transcriptase domain, RT_nLTR—Non-LTR (long terminal repeat) retrotransposon and non-LTR retrovirus reverse transcriptase (RT) domain, zf-RVT—zinc-binding in reverse transcriptase, rve—Integrase core domain, Exo_endo_phos—Endonuclease/Exonuclease/phosphatase family domain, RNase_H—Ribonuclease H domain, RNase_HI_RT_Ty1—Ty1/Copia family of RNase HI in long-term repeat retroelements domain, Transposase_28—transposase 28 domain, gag_pre-integrs—GAG-pre-integrase domain.
We found that the rye ScLr10 gene was structurally different from its wheat ortholog: it had a very small intron (55 bp long), whereas the Lr10 intron had a total length of 1,172 bp (S5 Table). Moreover, the Lr10 gene sequence was approximately twice the size of the ScLr10 gene. ScLr10 also lacked CC and LRR domains and only possessed the NB-ARC domain (Fig 1). Despite these differences, the CDSs of the two genes shared approximately 70% DNA sequence similarity.
Similar to wheat Rga2 genes, all but four rye ScRga2 gene paralogs had two introns. In particular, ScRga2_7, ScRga2_8, ScRga2_11, and ScRga2_13 had four, three, one, and no introns, respectively. ScRga2 genes varied significantly in length but could be divided into two groups on the basis of CDS length: 1) ScRga2_1–ScRga2_10, with CDSs ranging from 3,186 to 3,927 bp, similar to Rga2 (3,510 bp), and 2) ScRga2_11–ScRga2_15, with much smaller CDSs ranging from 1,125 to 1,590 bp. The length of the entire Rga2 gene region varied greatly among paralogs, from 1,080 to 13,329 bp, mainly because of the presence or absence of large introns typically harboring protein domains related to transposable elements. Unlike other identified ScLr genes, which have one NB-ARC domain, all ScRga2 paralogs except for ScRga2_11, ScRga2_13, ScRga2_14, and ScRga2_15 had two (the first one fragmented) (Fig 1). In addition, all rye ScRga2 genes except for ScRga2_11 had a CC domain like wheat Rga2 genes.
The first paralog of ScLr21 (ScLr21_1) was structurally much more similar to Lr21 in comparison with the second one (ScLr21_2). ScLr21_1 had a size similar to that of Lr21 and, like the Lr21 gene, was predicted to encode a transmembrane peptide (S2 Fig). Lr21 has two introns, whereas ScLr21 had only one. ScLr21_2 lacked introns and was approximately half the length of Lr21. Both ScLr21 paralogs and Lr21 had one NB-ARC domain; in ScLr21_2, however, this domain was located at the beginning of the gene.
Lr22a and its homolog, ScLr22a, were found to be canonical CNL genes, both having CC, NB-ARC, and LRR domains. These two genes had similar sizes and possessed only one exon, but their CDS similarity was not very high (approximately 73%).
A phylogenetic analysis revealed that the paralogs of each ScLr protein were more closely related to one another than to other ScLr proteins, thus suggesting their status as independent gene families (S5 Fig). The same situation was observed for Lr proteins, which were more similar to their rye orthologs than to other wheat Lr proteins. According to our phylogenetic tree, however, the Rga2 clade was most similar to the Lr10 clade, whereas the ScLr21 clade was most closely related to the ScLr1 protein family. The results of the phylogenetic analysis were compatible with our BLAST-based DNA sequence comparison (Table 2) except that the protein encoded by the Rga2 gene was more to similar to ScRga2_2 and ScRga2_11 proteins than to the ScRga2_1 protein according to the phylogenetic analysis.
RNA-seq-based gene expressions
Among the orthologs of wheat Lr genes identified in the Lo7 genome, four genes (ScLr1_3, ScLr1_4, ScLr1_8, and ScRga2_6) were differentially expressed. In total, DEGs were detected in six different comparisons, most often at 36 hpt (Table 3). Expression levels of all four genes decreased after infection with Prs, both with compatible (D33 C vs. MT at 20 hpt and L318 C vs. MT at 36 hpt) and non-compatible (L318 NC vs. MT at 36 hpt and D33 NC vs. MT at 20 hpt) isolates. In both cases, expression level reductions were more pronounced following infection with the compatible isolate than the non-compatible one. The expression of any of the other rye orthologs of the Lr genes (including Lr10, Lr21 and Lr22a) was not significantly changed.
Full RNA-seq results for Lr genes orthologs in all three rye lines are provided in the S8A Table.
Each treatment included three biological replicates. Gene expression was analyzed in two time points (20 hpt and 36 hpt). For identification of significant DEGs, the following criteria were used: |log2 fold change| ± 0.5 and false discovery rate < 0.05.
Identification of selected differentially expressed ScLr1 and ScRga2 variants in genomes of rye inbred lines L318, D33, and D39
Identification of the genes that were differentially expressed in response to LR infection, as determined by RNA-seq, in the genomes of the inbred lines D33, D39, and L318 by PCR amplification was conducted (Table 3). ScLr1_3, which was differentially expressed in line L318 according to RNA-seq, could only be amplified from gDNA in this same line, whereas ScLr1_4 was amplified in all tested lines. The variant ScLr1_8, identified by RNA-seq in line D33, could not be amplified from the gDNA template of this line but was detected in the other two lines. The reasons for this result will be discussed later. The final gene, ScRga2_6, was identified both by RNA-seq and gDNA sequencing, but only in line L318 (Table 4).
RT-qPCR validation of in vivo expressions of DEGs identified by RNA-seq analysis
The expressions of genes differentially expressed in all 18 Prs treatment comparisons according to RNA-seq (S3 Table) were validated by RT-qPCR. Gene variants that were absent from the genomes of particular rye lines were excluded.
The RT-qPCR analysis confirmed that ScLr1_3 expression was significantly downregulated in line L318 at 36 hpt after treatment with a non-compatible Prs strain (Fig 2). Unlike the RNA-seq results, however, the RT-qPCR analysis revealed that this gene was also downregulated at this same time point in L318 after treatment with a compatible strain. No significant differences in ScLr1_3 expression were observed between the mock treatment and Prs treatments, regardless of strain type, at 20 hpt, which was consistent with the RNA-seq data. With respect to the two strain types, ScLr1_3 gene expression was significantly higher at 20 hpt and lower at 36 hpt in line L318 infected with a non-compatible strain compared with a compatible strain. Because ScLr1_3 was not present in D33 and D39, RT-qPCR verification of this gene was not performed in those lines.
The ScLr1_3 gene was absent from rye lines D33 and D39. Plant material for the expression analysis was collected twice: At 20 and 36 hpt. Asterisks indicate significant differences in expression within a given comparison (p < 0.05).
In contrast to RT-qPCR results showing that ScLr1_4 gene expression was significantly upregulated at 20 hpt in D33 treated with a non-compatible Prs strain, RNA-seq uncovered no differences in expression levels between mock and either Prs treatment, regardless of strain type (Fig 3). In a few cases, however, a significant difference in ScLr1_4 expression was observed between compatible and non-compatible strain treatments. The gene was upregulated in two comparisons (D33 C vs. NC at 36 hpt, and L318 C vs. NC at 36 hpt) and downregulated in one (D39 C vs. NC at 20 hpt). In line D39 at 36 hpt, ScLr1_4 expression was reduced after treatment with a compatible strain relative to non-compatible strain, similar to the RNA-seq results, but this difference was not statistically significant.
Plant material for the expression analysis was collected twice: At 20 and 36 hpt. Asterisks indicate significant differences in expression within a given comparison (p < 0.05).
The expression of ScLr1_8 was downregulated in rye line D33, relative to the mock-treated control, after treatment with either of the Prs strains (Fig 4). According to the RNA-seq analysis, however, significant downregulation of this gene was observed only at 20 hpt, whereas RT-qPCR also revealed significant downregulation at 36 hpt, but only in the case of compatible-strain treatment. The opposite was true according to the RNA-seq data for line D39, where treatment with a non-compatible strain upregulated ScLr1_8 gene expression compared with the control. The RNA-seq analysis also indicated that Prs treatment had no significant effect on ScLr1_8 expression in L318 compared with the mock treatment. Noteworthily, the two Prs strains had significantly different effects on ScLr1_8 gene expression in all tested lines, but only at some time points. In lines D33 and D39, the expression of ScLr1_8 after treatment with a compatible strain was significantly lower compared with the effect of a non-compatible strain, but only at 20 hpt (D33) and 36 hpt (D39). In line L318, in contrast, ScLr1_8 expression was significantly higher after treatment with a compatible strain vs. a non-compatible strain, but only at 36 hpt.
Plant material for the expression analysis was collected twice: At 20 and 36 hpt. Asterisks indicate significant differences in expression within a given comparison (p < 0.05).
The RT-qPCR analysis indicated that Rga2_6 gene expression was downregulated in rye line L318 after treatment with Prs, an observation similar to the overall RNA-seq results (Fig 5). Unlike the findings of the RNA-seq analysis, however, the decreased expression of this gene was significant only for two comparisons (L318 C vs. MT at 36 hpt, and L318 NC vs. MT at 36 hpt). Furthermore, the type of Prs strain (compatible vs. non-compatible) had no significant effect on gene expression based on the RT-qPCR analysis, whereas a significant difference was found at 36 hpt according to the RNA-seq data. Similar to the ScLr1_3 gene, the expression of Rga2_6 was analyzed by RT-qPCR only in line L318, as this gene was absent from the other two tested rye lines.
The Rga2_6 gene was absent from rye lines D33 and D39. Plant material for the expression analysis was collected twice: At 20 and 36 hpt. Asterisks indicate significant differences in expression within a given comparison (p < 0.05).
Discussion
Despite the major economic importance of LR and many years of research devoted to the genetic background of rye resistance to this disease, most relevant genes identified thus far have not been molecularly characterized. In this study, we focused on selected R genes, key elements of PTI, that potentially confer LR resistance on rye. All analyzed genes were orthologs of the wheat genes Lr1, Lr10, Lr21, Lr22a, and RGA2/T10rga2-1A, which all belong to the NBS-LRR or NLR classes and have a proven role in the immune response to LR.
To achieve our study goal, we used three methods: identification of these orthologs in the recently published rye genome [35] followed by their characterization using various tools and algorithms, transcriptome sequencing (RNA-seq), and validation of the RNA-seq data by RT-qPCR analysis. Such a comprehensive approach was used to study the R-type genes associated with LR in rye for the first time.
One of the most popular bioinformatics tools for finding gene orthologs between different species is NCBI BLAST/BLAST+. In published studies, however, various cut-off criteria for the BLAST results have been used to find gene orthologs. The most commonly used parameter is the percentage of sequence identity. Even if a BLAST hit has approximately 100% identity with a query sequence, however, this similarity often only applies to a small portion, sometimes just a tiny fraction, of the alignment. The returned hit is also usually supported by a low e-value, but this parameter is highly dependent on gene length and database size and may thus generate false positives. To recognize rye orthologs among BLAST hits in this study, we therefore used generally accepted criteria, including DNA sequence identity ≥ 70% and e-value ≤ 10−6 [53]; in addition, we used query coverage per HSP ≥ 30% as a cut-off parameter to eliminate BLAST hits with significant but short alignments, which are often restricted to conserved domain regions.
Using the above criteria, we identified 14 Lr1 gene orthologs in rye. Similar to wheat Lr1 genes [27], the ScLr1 gene family has many members located on different chromosomes. Lr1 and ScLr1 genes also have similar structures, NB-ARC domain locations, and sizes. Moreover, ScLr genes on chromosome 7R have been previously identified by Vendelbo et al. [9] using resistance-associated markers as candidates for rye orthologs of wheat Lr1 genes. Lr1 genes possess a signal peptide, as also has been observed in the closest gene orthologs in rye (ScLr1_1–ScLr1_7, excluding ScLr1_6). Taking all of this information into account, one or more ScLr genes very likely have the same function as Lr1 genes; however, as proposed by Vendelbo et al. [9], this idea still needs to be verified.
In contrast to our discovery of multiple Lr1 genes, we only found one potential Lr10 ortholog in the Lo7 rye genome. This ScLr10 gene is structurally different from its wheat ortholog, as the two genes vary significantly in terms of intron size and encoded protein sequence. ScLr10 is also missing CC and LRR domains and contains only the NB-ARC domain. Moreover, the functional Lr10 gene in hexaploid wheat is always located on chromosome 1AS [29], whereas ScLr10 in rye is located on chromosome 6R; no synteny between these chromosomes was observed [54]. Despite these differences, the CDSs of the two genes share approximately 70% DNA sequence similarity. Like Lr10, ScLr10 is not closely related to any other wheat Lr genes [28].
To our surprise, we found 15 gene paralogs of Rga2 in the rye Lo7 genome. In wheat, a closely related species but with a much more complex genome, only two variants of this gene have been detected [28,29]. Similar to wheat Rga2, most ScRga2 genes are longer than the Lr10 gene and have a partially duplicated NB-ARC domain [55]. All rye ScRga2 genes (except for ScRga2_11) contain a CC domain in the N-terminal, as in the wheat Rga2 gene. Both the CDS and the genomic sequence of ScRga2 genes exhibit extensive length variation. The genomic sequence ranges from 1,080 to 13,329 bp, a difference mainly due to the absence or presence of a large intron frequently containing protein domains related to transposable elements.
Of the remaining genes, only two wheat Lr21 paralogs: the variants ScLr21_1 and ScLr21_2 (however, only the second one codes, probably, for LR21 transmembrane protein) and one Lr22a paralog were found in the Lo7 genome.
Given that we aimed to determine if, and to what extent, rye orthologs of wheat R genes are induced by infection, we conducted RNA-seq and RT-qPCR analyses. The RNA-seq approach has been widely used to study genes induced by pathogens, including leaf rust [22,56,57] in wheat, which is a close relative of rye. Unfortunately, neither of the aforementioned studies described in detail the genes that we were interested in, i.e., Lr1, Lr10, Lr21, Lr22a, and RGA2/T10rga2-1A. To date, research on the expression of R genes that confer resistance to LR in wheat is limited to several chromosomal positions and two genes (Lr1 and T10rga1/Lr10 [27,28,34]) and none of these studies used the methods used in the present investigation, i.e. RNA-seq and qRT-PCR.
Four of the ScLr genes identified in the Lo7 genome in our study (ScLr1_3, ScLr1_4, ScLr1_8, and ScRga2_6) were differentially expressed according to the RNA-seq analysis. Among the three studied rye lines, L318 was the only one carrying all four DEGs. This result is not surprising, as a similar observation has been made in wheat, namely, only 16 of 65 tested European wheat accessions in one study possessed the Lr1 gene [58]. Moreover, Rga2 (together with Lr10) have been found to be mostly absent in the wheat gene pool [28]. The R genes found in the Lo7 genome in our study include orthologs of wheat Lr10 and T10rga2-1A genes, namely, ScLr10 and ScRga2, respectively, which likely correspond to the same H1 haplotype (Lr10+/T10rga2-1A+) identified in wheat [28]. In the three rye inbred lines analyzed in this study, however, only one variant, ScRga2_6, was differentially expressed—in line L318, and no ScLr10 paralogs were DEGs. Given the present RNA-seq results, we assume that L318 is the only line among the three tested lines that may harbor a functional ScRga2 gene and that none of these lines have a ScLr10 gene, or, alternatively, its expression is blocked. Such a haplotype, i.e., ScLr10-/ScRga2+, has not yet been identified and may, like the H2 haplotype in wheat, be associated with disease susceptibility. According to our previous field- and phytotron-based assessments [13,14], line L318 has a very low level of LR resistance. The role of ScLr10 and ScRga2 genes in the specific immune response of rye to RB infection thus requires further discussion.
According to the RNA-seq analysis and applied criteria, only two variants of ScLr1 (ScLr1_3 and ScLr1_8) and one variant of ScRga2 (ScRga2_6) were significantly differentially expressed in six comparisons; in all cases, these genes were downregulated, usually at 36 hpt, after infection with either compatible or incompatible Prs isolates. In addition, one variant of ScLr1, namely, ScLr1_4, was overexpressed in plants of line D39 infected with an incompatible Prs isolate compared with plants exposed to a compatible strain. This result is inconsistent with most studies of R genes and their roles in the plant immune system. R genes are the main “players” in the second layer (ETI) of the plant immune system, in which proteins encoded by R genes recognize specific pathogen effectors [15]. Therefore, R genes are usually upregulated after pathogen infection, thereby enhancing their potency in pathogen recognition and defense induction [59], even in incompatible relationships [22]. Nevertheless, as stated in the Introduction, R genes may sometimes be downregulated [23–25] or may not be induced at all, especially in incompatible interactions [26].
One possible explanation for the decreased expression of the studied genes after Prs treatment is related to the amount of time from inoculation to plant tissue sampling, which was only 20 and 36 hpt. At this early stage, the effectors secreted by a fungus can reduce the level of R-gene expression. In the case of Prs, the period between 20 and 36 hpt is characterized by the highest the number of haustorial mother cells (note: haustoria are specialized feeding structures from which pathogens secrete effectors, including proteins recognized by R genes [16,60,61]). Evidence confirming this hypothesis is that relatively less downregulation of the studied genes occurred after infection with incompatible Prs isolates; in particular, the compatible strain caused a greater decrease in expression than the incompatible one in two cases involving Prs strains of different pathogenicity: ScLr1_4 in line D39 at 36 hpt, and ScRga2_6 in line L318 at 36 hpt. Similarly, Li et al. [22] found that the expression level of the gene TaLr35PR5 in wheat after infection with Puccinia triticina was higher in an incompatible interaction than that in a compatible interaction. The same conclusion was made by Bozkurt et al. [62] with regard to Puccinia striiformis f. sp. tritici. Incompatible strains either do not produce specific effectors or are less effective against R genes. Other causes, such as small RNA-mediated transcript silencing, alternative splicing (AS), and other transcript modifications, cannot be ruled out, but testing these possibilities requires further research. However, it should be noted that AS is a fundamental mechanism of plant stress tolerance. It may be induced both by biotic and abiotic stresses which allow to activate a rapid defense response. This phenomenon has been observed both in dicots and monocots [63,64]. At present, we can neither exclude nor acknowledge AS as a cause of the decreased expression of the studied genes. We examined, by RT-PCR followed by sequencing of the amplified products, the expression of one gene potentially triggering resistance to LR, ScLr21_1, and found that in two unrelated rye inbred lines it undergoes AS (S6 Fig); however, we did not look for this phenomenon in any other identified ScLr genes.
The variant ScLr1_8, identified as a DEG by RNA-seq of line D33, was not amplified from the gDNA template of this line. This unexpected result is possibly due to some difference in the genomic sequence or structure of this gene between lines D33 and Lo7. Similar to some ScRGA2 gene paralogs, for instance, the ScLr1_8 gene in line D33 may contain a long intron with incorporated transposons that prevents DNA amplification. Further research is needed to explain this phenomenon. An analysis of ScLr1_8 will be complicated, however, because this gene is located on an unknown chromosome (ChrUn) containing contigs in the rye reference genome, and its chromosomal location and surrounding sequences are unknown. Moreover, the ScLr1 gene family contains many genes with very similar nucleotide sequences.
To validate the results of the RNA-seq analysis of the four R genes, we carried out qRT-PCR. This highly sensitive tool for targeted analysis has been broadly used for validation of transcriptomic data, including those produced by the RNA-seq approach [65–69]. We observed a high convergence between RNA-seq- and qRT-PCR-generated results, similar to the findings of many other researchers [66,67,69]. For example, an independent benchmarking study uncovered a high correlation between the results of RNA-seq and qRT-PCR-produced data, and some authors have even questioned the absolute need for such validation. In particular, Coenye [70] has concluded that “RNA-seq methods and data analysis approaches are robust enough to not always require validation by RT-qPCR and/or other approaches, although there are situations where this may be of added value.” An example of this latter situation occurred in a study of wheat Rf genes by Tyrka et al. [68], who observed discrepancies between expression levels of several DEGs determined by RNA-seq vs. RT-qPCR that were possibly due to insufficient designed-primer specificity.
As stated above, all DEGs identified by RNA-seq in the present study were positively verified by qRT-PCR, but many more DEGs were uncovered by the latter method than by the former. For the RT-qPCR analysis, we chose to examine gene expression at two time points and analyzed all comparisons, not just those exhibiting differential expression according to RNA-seq. This approach allowed us to identify 14 new cases of significant differential gene expression, namely, six and eight cases of increased and decreased expression, respectively. Among them, five involved comparisons between control plants and plants infected with either compatible or non-compatible Prs isolates. Most DEGs in the comparisons C vs. MT and NC vs. MT were downregulated, which supports our hypothesis that pathogen effectors are responsible for the decreased expression of host genes occurring very early after infection.
One of the genes with significant differential expression according to qRT-PCR, but not RNA-seq, was ScRga2_6, which was downregulated in line L318 after infection with a compatible Prs strain and especially an incompatible strain. Even though ScRga2_6 expression was downregulated post-infection, this result indicates the important role of this gene in immune response—at least in the specific interaction of plant genotype × Prs strain × time point (hpt). A further insight into the involvement of ScRga2 can be gleaned from the research of Feuillet et al. [28], who assigned an important role to the Lr10 gene in the expression of Lr10-mediated resistance to LR, as well as the claim of Loutre et al. [29] that the T10rga2/RGA2 gene plays only an auxiliary role in this process. In addition, lowering the expression of ScRga2 may favor disease development because the ScRga2/ScLr10 gene pair will not “work” properly in such a case, which may be manifested by the lack of drastic reduction of its expression.
Several factors may be responsible for the differences between RNA-seq and RT-qPCR results described above. First, RT-qPCR is much more specific than RNA-seq, particularly in regard to newly sequenced, incompletely understood genomes, such as the Lo7 rye genome on which our analyses were based. This divergence in sensitivity is especially true of chromosomes labeled Un, which may be mis-mapped. Additionally, in the case of multigene families, like most of our studied genes, they may be enriched for mis-mapped reads. In such cases, verification by RT-qPCR is crucial. We thus do not share the opinion of Coenye [70] that RNA-seq methods do not require RT-qPCR validation; on the contrary, RT-qPCR can be, as in our case, an essential supplement to RNA-seq data.
Second, we did not observe a universal pattern of gene expression across RNA-seq or RT-qPCR analyses—neither for a given rye genotype, nor for a given gene, time point, or isolate pathogenicity. The relationships uncovered were rather specific to a particular set of factors: plant genotype × Prs isolate × time after infection. Such dependencies were expected given the applied, unique, experimental design comprising three different, unrelated rye lines and specific Prs strains that were compatible or non-compatible in relation to a given genotype.
In conclusion, we can state the following on the basis of our study results: at least some of the analyzed wheat orthologs (namely, ScLr1_3, ScLr1_4, ScLr1_8, and ScRga2_6) participate in the response of rye to LR, despite being mainly downregulated. During disease development, Avr proteins are secreted by LR across the haustorial membrane and can suppress multiple plant defense responses, including the hypersensitive response based on R genes [71]. Bi et al. [72] have reported that the effector PNPi from Puccinia striiformis f. sp. tritici. suppresses the expressions of two plant defense-responsive genes following infection with Pseudomonas syringae [72]. The same interaction may be expected for LR effectors and ScLr genes after infection with Prs.
Among the aforementioned genes, ScLr1_4 and ScLr1_8 may play important roles in the early response (20 hpi) of lines D33 and D39, respectively, to LR. These lines are considered to be resistant to LR under field conditions [14] and after treatment with a semi-compatible Prs strain in the laboratory [13]. The lines D33 and D39, bred by Danko Plant Breeding, Ltd., belong to the pool of Polish rye breeding materials prevalently used in current breeding programs focused mainly on fertility; these lines can also serve as a source of resistance to LR. It should be noted that, for many years, Polish rye varieties accounted for a large percentage of the cultivars grown in Europe. The function of these genes should be confirmed (for which both genetic transformation and CRISPR/Cas9-mediated gene editing are required), but in the case of rye, an in-vitro-culture recalcitrant species, this represents a major challenge. Nevertheless, in the future, we intend to attempt this using the virus-induced gene silencing technique, which has previously been verified as effective in rye [73].
Supporting information
S1 Fig. LR infection symptoms in D33 rye inbred line infected with leaf rust isolate 83/2/2.2_5x (compatible) and 1/1.6 (non-compatible), 10 dpi.
Dankowskie Skand is used as a control.
https://doi.org/10.1371/journal.pone.0288520.s001
(DOCX)
S2 Fig. Graphical presentation of identified in silico transmembrane helices in Lr21 and ScLr21_1 proteins.
The graph was created in TMHMM 2.0.
https://doi.org/10.1371/journal.pone.0288520.s002
(DOCX)
S3 Fig. Graphical presentation of all experiments.
https://doi.org/10.1371/journal.pone.0288520.s003
(DOCX)
S4 Fig. Graphical presentation of subcellular locations of wheat reference Lr1 and rye ScLr1_1, ScLr1_2, ScLr1_4 ScLr1_6, and ScL1_7 proteins predicted using TargetP v2.0 (Organism: Plant).
https://doi.org/10.1371/journal.pone.0288520.s004
(DOCX)
S5 Fig. Phylogenetic tree of rye ScLr and wheat Lr proteins reconstructed by maximum likelihood using the Phylogeny.fr platform [39].
Branch support values (%) were marked in red and only branches with minimum 50% support were shown. The bar at the bottom of the figure indicate the proportion of site changes along each branch.
https://doi.org/10.1371/journal.pone.0288520.s005
(DOCX)
S6 Fig. Alternative splicing of ScLr21_1 gene in two unrelated rye inbred lines (L310, SE104).
DNA Ladder (M) and the samples comes from the same gel image (irrelevant gel lanes between them were intentionally removed). Prior to the experiment, seeds of two rye inbred lines (L310 and SE104) were initially sown in Petri dishes lined with wet tissue paper and left in the dark for 2 days at 22°C. Germinating seeds were then transferred into 12-cm diameter plastic pots (10 seedlings per pot) filled with sterilized peat substrate and maintained for 10 days in a growth chamber at 22°C under a 16-h light/8-h dark photoperiod at an illumination intensity of 60 μmol m-2 s-1. RNA isolation and cDNA synthesis was performed as it was written in Material and Methods section. The RT-PCR was performed in Mastercycler® nexus gradient (Eppendorf). The reaction conditions were as follows: 3 min of denaturation at 95°C followed by 35 amplification cycles (30 s at 95°C, 30 s at 60°C and 60 s at 72°C), then 10 min at 72°C and finally–pause at 15°C. Each reaction was done in 20-μl reaction volume consisting of 10 μl of DreamTaq Green PCR Master Mix 2x (Thermo ScientificTM), 8 μl of cDNA (2.5 ng μl-1), 0.5 μl of each primer and 1 μl of nuclease-free water. Products were electrophoretically separated on 2% agarose gel for 75 min at 115 V.
https://doi.org/10.1371/journal.pone.0288520.s006
(DOCX)
S1 Table. Benzoxazinoid (BX) contents of inbred rye lines D33, D39, and L318.
https://doi.org/10.1371/journal.pone.0288520.s007
(DOCX)
S2 Table. List of RNA-seq libraries.
Each RNA-seq library group consisted of three independent libraries, which were biological replicates.
https://doi.org/10.1371/journal.pone.0288520.s008
(DOCX)
S3 Table. Detailed description of RNA-seq comparisons used to calculate gene expression fold changes.
In each RNA-seq comparison below, fold change was calculated as the ratio of the difference between the expression value of component I over the expression value of component II. Each comparison consisted of three biological replicates. Gene expression was analyzed at two time points (20 hpt and 36 hpt).
https://doi.org/10.1371/journal.pone.0288520.s009
(DOCX)
S5 Table. Detailed structural information on wheat Lr and rye ScLr genes.
https://doi.org/10.1371/journal.pone.0288520.s011
(DOCX)
S6 Table. Prediction of transmembrane helices (TMHs) in predicted amino acid sequence of Lr and ScLr genes by TMHMM 2.0.
https://doi.org/10.1371/journal.pone.0288520.s012
(DOCX)
S7 Table. Prediction of subcellular locations of ScLr proteins with TargetP v2.0 (Organism: Plant).
Annotations are as follows: SP, signal peptide; MT, mitochondrial transit peptide (mTP); CH, chloroplast transit peptide (cTP); TH, thylakoidal lumen composite transit peptide (lTP); OTHER, no targeting peptide.
https://doi.org/10.1371/journal.pone.0288520.s013
(DOCX)
S8 Table.
a. Full RNA-seq results for Lr genes orthologs (ScLr) in all three rye lines. b. Data statistics summary for RNA-seq libraries based on FASTQC v0.11.8 analysis (before adapter trimming).
https://doi.org/10.1371/journal.pone.0288520.s014
(XLSX)
Acknowledgments
We thank Edanz (https://www.edanz.com/ac) for editing the English text of a draft of this manuscript.
References
- 1. Roux SR, Wehling P. Nature of mixed infection type 2(5) observed in rye (Secale cereale L.) plants carrying the Pr1 leaf-rust resistance gene. J. Kulturpflanzen. 2010; 62:29–34. https://doi.org/10.5073/JfK.2010.02.01.
- 2. Miedaner T, Klocke B, Flath K, Geiger HH, Weber WE. Diversity, spatial variation, and temporal dynamics of virulences in the German brown rust (Puccinia recondita f. sp. secalis) population in winter rye. Eur. J. Plant Pathol. 2012; 132:23–35. https://doi.org/10.1007/s10658-011-9845-8.
- 3. Wehling P, Linz A, Hackauf B, Roux SR, Ruge B, Klocke B. Leaf-rust resistance in rye (Secale cereale L.). 1. Genetic analysis and mapping of resistance genes Pr1 and Pr2. Theor. Appl. Genet. 2003; 107:432–438. https://doi.org/10.1007/s00122-003-1263-7.
- 4. Solodukhina OV. Genetic characterization of rye accessions with regard to leaf rust resistance. Russ. J. Genet. 2002; 38:399–407. https://doi.org/10.1023/A:1015202303392.
- 5. Solodukhina OV, Kobylyanskij VD. Problems of winter rye breeding for resistance to leaf and stem rusts. Plant Breeding and Seed Science. 2003; 48:87–96.
- 6.
Klocke B. Virulenzstruktur und -dynamik des Roggenbraunrostes (Puccinia recondita f. sp. secalis) in der Bundesrepublik Deutschland. PhD thesis, Martin Luther University, Halle-Wittenberg, Germany. 2004.
- 7. Roux S, Hackauf B, Ruge-Wehling B, Linz A, Wehling P. Exploitation and comprehensive characterization of leaf-rust resistance in rye. Vortr Pflanzenzüchtung. 2007; 71:144–150.
- 8. Jung WJ, Seo YW. Employment of wheat-rye translocation in wheat improvement and broadening its genetic basis. J. Crop Sci. Biotechnol. 2014; 17:305–313. https://doi.org/10.1007/s12892-014-0086-1.
- 9. Vendelbo NM, Mahmood K, Sarup P, Hovmøller MS, Justesen AF, Kristensen PS, et al. Discovery of a Novel Leaf Rust (Puccinia recondita) Resistance Gene in Rye (Secale cereale L.) Using Association Genomics. Cells. 2022; 11:64. https://doi.org/10.3390/cells11010064.
- 10. Wu H, Kang Z, Li X, Li Y, Li Y, Wang S, et al. Identification of wheat leaf rust resistance genes in Chinese wheat cultivars and the improved germplasms. Plant Dis. 2020; 104:2669–2680. pmid:32729796
- 11. Vendelbo NM, Mahmood K, Steuernagel B, Wulff BBH, Sarup P, Hovmøller MS, et al. Discovery of Resistance Genes in Rye by Targeted Long-Read Sequencing and Association Genetics. Cells. 2022; 11:1273. pmid:35455953
- 12. Milczarski P, Masojć P, Krajewski P, Stochmal A, Kowalczyk M, Angelov M, et al. QTL mapping for benzoxazinoid content, preharvest sprouting, α-amylase activity, and leaf rust resistance in rye (Secale cereale L.). PLoS ONE. 2017; 12:e0189912. https://doi.org/10.1371/journal.pone.0189912.
- 13. Święcicka M, Dmochowska-Boguta M, Orczyk W, Grądzielewska A, Stochmal A, Kowalczyk M, et al. Changes in benzoxazinoid contents and the expression of the associated genes in rye (Secale cereale L.) due to brown rust and the inoculation procedure. PLoS ONE. 2020; 15:e0233807. https://doi.org/10.1371/journal.pone.0233807.
- 14. Rakoczy-Trojanowska M, Krajewski P, Bocianowski J, Schollenberger M, Wakuliński W, Milczarski P, et al. Identification of single nucleotide polymorphisms associated with brown rust resistance, α-amylase activity and pre-harvest sprouting in rye (Secale cereale L.). Plant Mol. Biol. Rep. 2017; 35:366–378. https://doi.org/10.1007/s11105-017-1030-6.
- 15. Kumar D, Dutta S, Singh D, Prabhu KV, Kumar M, Mukhopadhyay K. Uncovering leaf rust responsive miRNAs in wheat (Triticum aestivum L.) using high-throughput sequencing and prediction of their targets through degradome analysis. Planta. 2017; 245:161–182.
- 16. Periyannan S, Milne RJ, Figueroa M, Lagudah ES, Dodds PN. An overview of genetic rust resistance: From broad to specific mechanisms. PLoS Pathogens. 2017; 13:e1006380. pmid:28704545
- 17. DeYoung BJ, Innes RW. Plant NBS-LRR proteins in pathogen sensing and host defense. Nature Immunology. 2006; 7:1243–1249. pmid:17110940
- 18. Jones JDG, Vance RE, Dangl JL. Intracellular innate immune surveillance devices in plants and animals. Science. 2016; 354:aaf6395. pmid:27934708
- 19. Yang S, Tang F, Zhu H. Alternative splicing in plant immunity. Int. J. Mol. 2014; 15:10424–10445. pmid:24918296
- 20. Andersen EJ, Nepal MP, Purintun JM, Nelson D, Mermigka G, Sarris PF. Wheat disease resistance genes and their diversification through integrated domain fusions. Front. Genet. 2020; 11:898. pmid:32849852
- 21. Bouktila D, Khalfallah Y, Habachi-Houimli Y, Mezghani-Khemakhem M, Makni M, Makni H. Large-scale analysis of NBS domain-encoding resistance gene analogs in Triticeae. Genet. Mol. Biol. 2014; 37:598–610. pmid:25249784
- 22. Li X, Gao L, Zhang W, Liu J, Zhang Y, Wang H, et al. Characteristic expression of wheat PR5 gene in response to infection by the leaf rust pathogen, Puccinia triticina. J. Plant Interact. 2015; 10:132–141. https://doi.org/10.1080/17429145.2015.1036140.
- 23. MacQueen A, Bergelson J. Modulation of R-gene expression across environments. J. Exp. Bot. 2016; 67:2093–2105. pmid:26983577
- 24. Cregeen S, Radisek S, Mandelc S, Turk B, Stajner N, Jakse J, et al. Different Gene Expressions of Resistant and Susceptible Hop Cultivars in Response to Infection with a Highly Aggressive Strain of Verticillium albo-atrum. Plant Mol. Biol. Rep. 2015; 33:689–704. pmid:25999664
- 25. Li YY, Wang L, Sun GW, Li XH, Chen ZG, Feng J, et al. Digital gene expression analysis of the response to Ralstonia solanacearum between resistant and susceptible tobacco varieties. Sci. Rep. 2021; 11:3887. pmid:33594109
- 26. Peng FY, Yang RC. Prediction and analysis of three gene families related to leaf rust (Puccinia triticina) resistance in wheat (Triticum aestivum L.). BMC Plant Biol. 2017; 17:108. https://doi.org/10.1186/s12870-017-1056-9.
- 27. Cloutier S, McCallum BD, Loutre C, Banks TW, Wicker T, Feuillet C, et al. Leaf rust resistance gene Lr1, isolated from bread wheat (Triticum aestivum L.) is a member of the large psr567 gene family. Plant Mol. Biol. 2007; 65:93–106. https://doi.org/10.1007/s11103-007-9201-8.
- 28. Feuillet C, Travella S, Stein N, Albar L, Nublat A, Keller B. Map-based isolation of the leaf rust disease resistance gene Lr10 from the hexaploid wheat (Triticum aestivum L.) genome. Proc. Natl. Acad. Sci. U.S.A. 2003; 100:15253–15258. https://doi.org/10.1073/pnas.2435133100.
- 29. Loutre C, Wicker T, Travella S, Galli P, Scofield S, Fahima T, et al. Two different CC-NBS-LRR genes are required for Lr10-mediated leaf rust resistance in tetraploid and hexaploid wheat. Plant J. 2009; 60:1043–1054. pmid:19769576
- 30. Qiu L, Wang H, Li Y, Wang W, Liu Y, Mu J, et al. Fine Mapping of the Wheat Leaf Rust Resistance Gene LrLC10 (Lr13) and Validation of Its Co-segregation Markers. Front. Plant Sci. 2020; 11:470. https://doi.org/10.3389/fpls.2020.00470.
- 31. Huang L, Brooks SA, Li W, Fellers JP, Trick HN, Gill BS. Map-based cloning of leaf rust resistance gene Lr21 from the large and polyploid genome of bread wheat. Genetics. 2003; 164:655–664. pmid:12807786
- 32. Naz AA, Bungartz A, Serfling A, Kamruzzaman M, Schneider M, Wulff BBH, et al. Lr21 diversity unveils footprints of wheat evolution and its new role in broad-spectrum leaf rust resistance. Plant Cell Environ. 2021; 44:3445–3458. https://doi.org/10.1111/pce.14144.
- 33. Thind AK, Wicker T, Šimková H, Fossati D, Moullet O, Brabant C, et al. Rapid cloning of genes in hexaploid wheat using cultivar-specific long-range chromosome assembly. Nat. Biotechnol. 2017; 35:793–796. pmid:28504667
- 34. Kumar S, Wang Z, Banks TW, McCallum BD, Cloutier S. Lr1-mediated leaf rust resistance pathways of transgenic wheat lines revealed by a gene expression study using the Affymetrix GeneChip® Wheat Genome Array. Mol Breeding. 2014; 34:127–141. https://doi.org/10.1007/s11032-014-0022-6.
- 35. Rabanus-Wallace MT, Hackauf B,…, Stein N. Chromosome-scale genome assembly provides insights into rye biology, evolution and agronomic potential. Nature Genetics. 2021; 53:564–573. pmid:33737754
- 36. Murphy HC. Physiologic specialization in Puccinia coronata avenae. US Dep. Agric. Tech. Bull. 1935; 433:48.
- 37. Lu S, Wang J, Chitsaz F, Derbyshire MK, Geer RC, Gonzales NR, et al. CDD/SPARCLE: the conserved domain database in 2020. Nucl. Acids Res. 2020; 48(D1):D265–D268. pmid:31777944
- 38. Hu B, Jin J, Guo A-Y, Zhang H, Luo J, Gao G. GSDS 2.0: an upgraded gene feature visualization server. Bioinformatics. 2015; 31:1296–1297. pmid:25504850
- 39. Dereeper A, Guignon V, Blanc G, Audic S, Buffet S, Chevenet F, et al. Phylogeny.fr: robust phylogenetic analysis for the non-specialist. Nucl. Acids Res. 2008; 36:W465–W469. pmid:18424797
- 40. Armenteros JJA, Salvatore M, Emanuelsson O, Winther O, von Heijne G, Elofsson A, et al. Detecting sequence signals in targeting peptides using deep learning. Life science alliance. 2019; 2:e201900429. pmid:31570514
- 41. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal. 2011; 17:10–12. https://doi.org/10.14806/ej.17.1.200.
- 42. Andrews S. FASTQC. A quality control tool for high throughput sequence data. 2010. Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc.
- 43. Kim D, Paggi JM, Park C, Bennett Ch, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 2019; 37:907–915. pmid:31375807
- 44. Anders S, Pyl PT, Huber W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015; 31:166–169. pmid:25260700
- 45.
R Core Team, R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria. 2020. URL https://www.R-project.org/.
- 46. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology. 2014; 15:550. pmid:25516281
- 47. Coulouris Y, Zaretskaya I, Cutcutache I, Rozen S, Madden T. Primer-BLAST: A tool to design target-specific primers for polymerse chain reaction. BMC Bioinform. 2012; 13:134. https://doi.org/10.1186/1471-2105-13-134.
- 48. Stothard P. The sequence manipulation suite: JavaScript programs for analyzing and formatting protein and DNA sequences. Biotechniques. 2000; 28:1102–1104. pmid:10868275
- 49. Madeira F, Park YM, Lee J, Buso N, Gur T, Madhusoodanan N, et al. The EMBL-EBI search and sequence analysis tools APIs in 2019. Nucl. Acids Research. 2019; 47(W1):W636–W641. pmid:30976793
- 50. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and 2−ΔΔCT method. Methods. 2001; 25:402–408. https://doi.org/10.1006/meth.2001.1262.
- 51. Giménez MJ, Piston F, Atienza SG. Identification of suitable reference genes for normalization of qPCR data in comparative transcriptomics analyses in the Triticeae. Planta. 2011; 233:163–173. pmid:20960006
- 52. Pfaffl MW, Horgan GW, Dempfle L. Relative expression software tool (REST) for group–wise comparison and statistical analysis of relative expression results in real-time PCR Nucl. Acids Res. 2002; 30:e36. https://doi.org/10.1093/nar/30.9.e36.
- 53.
Baxevanis AD. Assessing Pairwise Sequence Similarity: BLAST and FASTA. Bioinformatics. Editor: Baxevanis AD, Bader GD; Wishart DS. 4. ed. Wiley; 2020. p. 61.
- 54. Li G, Wang L, Yang J. et al. A high-quality genome assembly highlights rye genomic characteristics and agronomically important genes. Nat Genet. 2021; 53:574–584. pmid:33737755
- 55. van Ooijen G, Mayr G, Kasiem MMA, Albrecht M, Cornelissen BJC, Takken FLW. Structure–function analysis of the NB-ARC domain of plant disease resistance proteins. J Exp. Bot. 2008; 59:1383–1397. pmid:18390848
- 56. Poretti M, Sotiropoulos AG, Graf J, Jung E, Bourras S, Krattinger SG, et al. Comparative Transcriptome Analysis of Wheat Lines in the Field Reveals Multiple Essential Biochemical Pathways Suppressed by Obligate Pathogens. Front Plant Sci. 2021; 12:720462. pmid:34659291
- 57. Ji X, Liu T, Xu S, Wang Z, Han H, Zhou S, et al. Comparative Transcriptome Analysis Reveals the Gene Expression and Regulatory Characteristics of Broad-Spectrum Immunity to Leaf Rust in a Wheat–Agropyron cristatum 2P Addition Line. Int. J. Mol. Sci. 2022; 23:7370. pmid:35806373
- 58. Dakouri A, McCallum BD, Radovanovic N, Cloutier S. Molecular and phenotypic characterization of seedling and adult plant leaf rust resistance in a world wheat collection. Mol. Breed. 2013; 32:663–677. pmid:24078786
- 59. Lai Y, Eulgem T. Transcript-level expression control of plant NLR genes. Mol. Plant Pathol. 2018; 19:1267–1281. pmid:28834153
- 60. Jones JDG, Dangl JL. The plant immune system. Nature. 2006; 444:323–329. pmid:17108957
- 61.
Kolmer JA, Ordonez ME, Groth JV. The rust fungi, In: Encyclopedia of Life Sciences (ELS). John Wiley & Sons, Ltd: Chichester, 2009.
- 62. Bozkurt TO, McGrann GR, MacCormack R, Boyd LA, Akkaya MS. Cellular and transcriptional responses of wheat during compatible and incompatible race-specific interactions with Puccinia striiformis f. sp. tritici. Mol. Plant Pathol. 2010; 11:625–640. https://doi.org/10.1111/j.1364-3703.2010.00633.x.
- 63. Yang S, Tang F, Zhu H. Alternative splicing in plant immunity. Int. J Mol. 2014; 15:10424–10445. pmid:24918296
- 64. Laloum T, Guiomar M, Duque P. Alternative splicing control of abiotic stress responses. Trends in Plant Science. 2018; 23:140–150. pmid:29074233
- 65. Yim AKY, Wong JWH, Ku YS, Qin H, Chan TF, Lam HM. Using RNA-Seq Data to Evaluate Reference Genes Suitable for Gene Expression Studies in Soybean. PLoS ONE. 2015; 10:e0136343. pmid:26348924
- 66. Everaert C, Luypaert M, Maag JLV, Cheng QX, Dinger ME, Hellemans J, et al. Benchmarking of RNA-sequencing analysis workflows using whole-transcriptome RT-qPCR expression data. Sci. Rep. 2017; 7:1559. pmid:28484260
- 67. Zeng F, Biligetu B, Coulman B, Schellenberg MP, Fu Y-B. RNA-Seq analysis of gene expression for floral development in crested wheatgrass (Agropyron cristatum L.). PLoS ONE. 2017; 12:e0177417. https://doi.org/10.1371/journal.pone.0177417.
- 68. Tyrka M, Bakera B, Szeliga M, Święcicka M, Krajewski P, Mokrzycka M, et al. Identification of Rf genes in hexaploid wheat (Triticum aestivum L.) by RNA-Seq and paralog analyses. Int. J. Mol. Sci. 2021; 22:9146. https://doi.org/10.3390/ijms22179146.
- 69. Chu C, Wang S, Paetzold L, Wang Z, Hui K, Rudd JC, et al. RNA-seq analysis reveals different drought tolerance mechanisms in two broadly adapted wheat cultivars ‘TAM 111’ and ‘TAM 112’. Sci. Rep. 2021; 11:4301. https://doi.org/10.1038/s41598-021-83372-0.
- 70. Coenye T. Do results obtained with RNA-sequencing require independent verification? Biofilm. 2021; 3:100043. pmid:33665610
- 71. Ramachandran SR, Yin C, Kud J, Tanaka K, Mahoney AK, Xiao F, et al. Effectors from Wheat Rust Fungi Suppress Multiple Plant Defense Responses. Phytopathol. 2017; 107:75–83. pmid:27503371
- 72. Bi W, Zhao S, Zhao J, Su J, Yu X, Liu D, et al. Rust effector PNPi interacting with wheat TaPR1a attenuates plant defense response. Phytopathol. Res. 2020; 2:34. https://doi.org/10.1186/s42483-020-00075-6.
- 73. Groszyk J, Kowalczyk M, Yanushevska Y, Stochmal A, Rakoczy-Trojanowska M, Orczyk W. Identification and VIGS-based characterization of Bx1 ortholog in rye (Secale cereale L.). PLoS ONE. 2017; 12(2):e0171506. https://doi.org/10.1371/journal.pone.0171506).