a1111111111 a1111111111 Micro RNAs (miRNAs) are small single strand non-coding RNAs that regulate gene expres- a1111111111 a1111111111 sion at the post-transcriptional level, either by translational inhibition or mRNA degradation based on the extent of complementarity between the miRNA and its target mRNAs. Potato (Solanum tuberosum L.) is the most important horticultural crop in Argentina. Achieving an integrated control of diseases is crucial for this crop, where frequent agrochemical applica- tions, particularly fungicides, are carried out. A promising strategy is based on promoting OPENACCESS induced resistance through the application of environmentally friendly compounds such as Citation: Rey-Burusco MF, Daleo GR, Feldman ML phosphites, inorganic salts of phosphorous acid. The use of phosphites in disease control (2019) Identification of potassium phosphite responsive miRNAs and their targets in potato. management has proven to be effective. Although the mechanisms underlying their effect PLoS ONE 14(9): e0222346. https://doi.org/ remain unclear, we postulated that miRNAs could be involved. Therefore we performed 10.1371/journal.pone.0222346 next generation sequencing (NGS) in potato leaves treated and non treated with potassium Editor: Yun Zheng, Kunming University of Science phosphite (KPhi). We identified 25 miRNAs that were expressed differentially, 14 already and Technology, CHINA annotated in miRBase and 11 mapped to the potato genome as potential new miRNAs. A Received: April 18, 2019 prediction of miRNA targets showed genes related to pathogen resistance, transcription fac- Accepted: August 27, 2019 tors, and oxidative stress. We also analyzed in silico stress and phytohormone responsive cis-acting elements on differentially expressed pre miRNAs. Despite the fact that some of Published: September 12, 2019 the differentially expressed miRNAs have been already identified, this is to our knowledge Copyright:© 2019 Rey-Burusco et al. This is an the first report identifying miRNAs responsive to a biocompatible stress resistance inducer open access article distributed under the terms of the Creative Commons Attribution License, which such as potassium phosphite, in plants. Further characterization of these miRNAs and their permits unrestricted use, distribution, and target genes might help to elucidate the molecular mechanisms underlying KPhi-induced reproduction in any medium, provided the original resistance. author and source are credited. Data Availability Statement: All relevant data are within the manuscript and its Supporting Information files. Files are available from the GEO database, Accession number: GSE132232. Introduction Funding: This work was supported by: GRD and MLF-PICT 2015-1354-Agencia Nacional de Potato (Solanum tuberosum L.) is the fourth food crop worldwide and the most important hor- ´ ´ ´ Promocion Cientıfica y Tecnologica-https://www. ticultural crop in Argentina, where 80,000 hectares of potatoes are planted per year, mainly in argentina.gob.ar/ciencia/agencia; GRD and MLF the provinces of Co ´ rdoba and Buenos Aires . Integrated control of diseases is crucial for -PIP Nº0854-2015-Consejo Nacional de this crop, where frequent agrochemical applications, particularly fungicides, are carried out to ´ ´ Investigaciones Cientıficas y Tecnicas -https:// manage late blight disease caused by Phytophthora infestans [2,3]. An alternative strategy is www.conicet.gov.ar/; GRD and MLF- UNMdP EXA 762/16- Universidad Nacional de Mar del Plata- based on promoting induced resistance through the application of environmentally friendly PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 1 / 15 Potassium phosphite responsive miRNAs in potato http://www.mdp.edu.ar/. MLF is an established compounds. In this context, phosphites have been extensively used as biocompatible inducers researcher from CONICET (Consejo Nacional de of defense responses . Investigaciones Cientı´ficas y Te´cnicas). GRD is an The role of phosphites in disease control management has been studied extensively, and established researcher from CIC (Comisio ´n de previous results have shown many promising properties associated with these compounds: the Investigaciones Cientı´ficas). MFRB is a post- stimulation of plant defense mechanisms such as enhanced production of reactive oxygen spe- doctoral fellow from Agencia Nacional de Promocio ´n Cientı´fica y Tecnolo ´gica. cies (ROS), the induction of pathogenesis related proteins (PRs) and the reinforcement of the cell wall [5–7]. It has also been demonstrated that KPhi primes an intense and rapid response Competing interests: The authors have declared to infection, involving heightened activation of a range of defense responses [8–10]. Addition- that no competing interests exist. ally, KPhi has been proven to be an effective protective agent against UV-B stress . How- ever the mechanisms underlying KPhi protective effect remain unclear, the complexity of defense mechanisms and the plethora of pathways involved, suggest that miRNAs might be involved. miRNAs can target and subsequently regulate the expression of multiple genes simultaneously, providing a rapid and efficient way of regulating plant responses to stress. miRNAs are small single-stranded, non-coding RNAs present both in animals and plants, that regulate gene expression at the post-transcriptional level, either by repressing mRNA translation or mediating the degradation of the targeted mRNAs depending on their degree of complementarity . Specifically in plants, this class of ~22 nt RNAs play crucial roles in plant biological processes and responses to disease and environmental stresses [13–15]. Many plant miRNAs and their targets have been identified by computational and experimental approaches, in various species [16,17]. Several conserved miRNA families have been described in potato, some of them targeting transcription factors with diverse roles in plant growth and development, genes involved in signal transduction, and hormone signaling pathways. miRNA families such as mir172, miR156, miR164, miR166, miR167, miR171, miR390, miR394, miR395, miR399, miR530, miR829, mir395, mir398, miR414, miR778, among others, appear to be involved in potato response to various disease and environmental stresses [18– 20]. We have hypothesized that one or more miRNAs might control the key-steps that lead to defense reactions mediated by KPhi in potato. In this scenario, the present work aims to iden- tify miRNAs involved in the regulation of potato defense responses after potassium phosphite treatment. Materials and methods Plant material and phosphite treatment S. tuberosum seed tubers (cv. Shepody) were planted in pots containing a pasteurized mixture of soil and vermiculite (3:1, v/v). Pots were maintained under greenhouse conditions (18˚C day-night temperature, 16 h of light per day). Potassium phosphite (KPhi), 1% (v/v) water solution of the commercial product (Afital Potassium Phosphite, Agro-EMCODI SA) was applied to the foliage at 5 mL per plant (3 L/ha) by using an atomizer (ESAC SA) operating at 200 kPa, 21 days after emergence. Control plants were sprayed with distilled water. Leaf tissue was collected after 72 hs of KPhi or water treatment. Experiments were performed at least three times for each condition. RNA isolation Total RNA from each treatment was isolated from 0.1 g of fresh leaf tissue using the RNeasy kit (Qiagen), following the manufacturer’s protocol. The purified RNAs were analyzed using a Thermo Scientific NanoDropOne spectrophotometer. RNA integrity was checked by 1% aga- rose gel electrophoresis. Three biological replicates were performed for each condition: control (C) and KPhi treated (T). PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 2 / 15 Potassium phosphite responsive miRNAs in potato Next generation sequencing Total RNA (1 ug) was used to prepare small RNA libraries according to the TruSeq Small RNA Sample Prep Kits protocol (Illumina, San Diego, USA). Purified cDNA libraries were 50bp sin- gle-end sequenced on an Illumina Hiseq 2500 at LC Sciences (Houston, Texas, USA) following the vendor’s recommended protocol. Identification of known and novel miRNAs Raw reads were subjected to an in-house program, ACGT101-miR (LC Sciences, Houston, Texas, USA) to remove adapter dimers, contaminating sequences with no 3’ adapters (3ADT), low com- plexity regions, common RNA families (rRNA, tRNA, snRNA, snoRNA) and repeats. Subse- quently, unique sequences with 18~25 nucleotides length were mapped to Solanum tuberosum (specific species) precursors in miRBase 21.0 by BLAST search to identify known miRNAs and novel 3p- and 5p- derived miRNAs. Length variation at both 3’ and 5’ ends and one mismatch inside of the sequence were allowed in the alignment. The unique sequences mapping to specific species mature miRNAs in hairpin arms were identified as known miRNAs. The unique sequences mapping to the other arm of known specific species precursor hairpin opposite to the annotated mature miRNA-containing arm were considered to be novel 5p- or 3p derived miRNA candidates. The remaining sequences were mapped to Solanum lycopersicum precursors (selected species of Solanaceae family) in miRBase 21.0 by BLAST search, and the mapped pre-miRNAs were further BLASTed against the specific species genomes to determine their genomic locations. The above two were defined as known miRNAs. The unmapped sequences were BLASTed against the spe- cific genomes, and the hairpin RNA structures containing sequences were predicted from the flank 120 nt sequences using RNAfold software (http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/ RNAfold.cgi). According to the mapping performed and secondary structure prediction reads were assigned to different groups (as described in detail in Fig 1). The naming system of miRNAs identified in this study is as follows: the miRNA name is composed of the first known miR name in a cluster, an underscore, and a matching annota- tion: L–n means the miRNA_seq (detected) is n base less than known rep_miRSeq in the left side; R–n means the miRNA_seq (detected) is n base less than known rep_miRSeq in the right side; L+n means the miRNA_seq (detected) is n base more than known rep_miRSeq in the left side; R+n means the miRNA_seq (detected) is n base more than known rep_miRSeq in the right side; 1ss8GA means 1 substitution (ss), which is G to A at position 8. If there is no matching annotation, the miRNA_seq (detected) is exactly the same as known rep_miRSEq. miRNAs located on the other arms of hairpin structures are annotated as p5/p3 to distinguish from the reported 5/3 sequences. Differential expression analysis Differential expression of miRNAs based on normalized deep-sequencing counts was analyzed using Student’s t-test. The significance threshold was set to 0.01 and 0.05 in each test. Sequence reads of the six libraries were normalized to 1 million by the total number of clean small RNA reads in each sample. The log ratio formula was as follows: log ratio = log (miRNA reads in 2 2 2 KPhi treated/miRNA reads in control). Target prediction and GO analysis Target predictions were performed with psRNATarget web server (http://plantgrn.noble.org/ psRNATarget/analysis) using default parameters with a maximum of 3 expectation cut-off . To better understand their function, the putative target genes of the differentially PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 3 / 15 Potassium phosphite responsive miRNAs in potato Fig 1. Flow chart of data analysis. https://doi.org/10.1371/journal.pone.0222346.g001 expressed miRNAs were subjected to GO analysis. Significant GO terms were calculated by a Hypergeometric equation, and those GO terms with p-value<0.05 were defined as significant. qRT-PCR analysis of miRNAs and their predicted targets The expression level of miRNAs was detected by stem-loop based reverse transcription and quantitative real time PCR (qRT-PCR) . miRNAs and mRNAs were reverse transcribed to PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 4 / 15 Potassium phosphite responsive miRNAs in potato cDNAs with stem-loop specific primers and oligo dT primers, respectively, using the GoScript (TM) Reverse Transcriptase (Promega). cDNA was generated from 1ug of total RNA, with both miRNA specific stem-loop primers and oligo dT primers in each reaction tube at 16˚C for 30 minutes, 42˚C for 30 minutes, 50˚C for 60 minutes and 70˚C for 15 minutes. The expression levels of miRNAs and mRNAs were analyzed by quantitative real-time PCR (qPCR) using an Applied Biosystems StepOneTM Plus Real-Time PCR System (Applied Bio- systems, Waltham, MA, United States) and FastStart Universal SYBR Green Master mix (Roche). For miRNAs, samples were incubated at 95˚C for 5 minutes, and the amplification was set at 45 cycles of denaturation at 95˚C for 15 seconds, annealing at 60˚C for 30 seconds, and an extension step at 72˚C for 20 seconds. For miRNA target genes, samples were incu- bated at 95˚C for 10 minutes, and amplification was set at 40 cycles of denaturation at 95˚C for 15 seconds and an annealing step at 60˚C for 1 minute. miRNA and target-gene specific prim- ers were designed using NGS data and available databases (http://www.mirbase.org/, http:// solgenomics.net/) (S1 Table). EF1α was employed as an internal control for mRNAs and miR- NAs. Reactions were performed with three biological replicates and relative gene expression ΔΔ level was analyzed using the comparative 2 CT method . Pair-wise fixed reallocation ran- domization test statistical analysis was performed with REST software (Relative Expression Software Tool) . Analysis of cis-acting elements The presence of well characterized cis-acting elements in the promoters of pre-miRNAs was analyzed in silico using the web available software PlantCARE (http://bioinformatics.psb. ugent.be/webtools/plantcare/html/search_CARE.html) . Upstream sequences of potato pre-miRNAs (1000 bp) were retrieved from the PGSC v4.03 database (http://solanaceae. plantbiology.msu.edu/). Availability of supporting data The data supporting this work are available in the public database: Gene Expression Omnibus (GEO), under the accession number GSE132232. Results High throughput sequencing of small RNAs Total RNA from potassium phosphite treated (T2, T4, T6) and non treated leaves (C1, C3, C5) was isolated, and six small RNA libraries were constructed to perform high throughput sequencing. RNAseq from the libraries generated 58,391,355 total raw reads. In particular, C1 library yielded 8,599,726 reads, while C3 and C5 libraries yielded 8,051,010 and 8,175,531 reads, respectively. T2, T4, and T6 yielded 12,864,315, 10,563,970 and 10,136,803 reads, respec- tively (S2 Table). After low-quality reads, adapters, poly A sequences and short RNAs shorter than 15 nucleo- tides were removed, 32,677,778 unique small RNA reads (56% of the total raw reads) remained (Fig 2A). RNA length ranged between 15–32 nt, with the highest proportion corresponding to 21 nt (Fig 2B). Reliable reads were divided into 4 groups as described in Fig 1. A total of 206 S. tuberosum known miRNAs (group 1a) were identified along with additional 42 Solanaceae miRNAs (group 1b), novel to potato. Interestingly, 388 reads that mapped to the potato genome, presented extended sequences that potentially form hairpins constituting potential novel miRNAs (group 4a) (Table 1). PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 5 / 15 Potassium phosphite responsive miRNAs in potato Fig 2. Data filtering and length distribution of mappable reads. Raw reads were filtered to remove sequences with no 3’ adapters (3ADT), junk reads and reads shorter than 15 and longer than 32 nucleotides; and were subsequently mapped to specific and selected genomes. (A) Pie plot of data filtering. (B) Length distribution of mappable reads. https://doi.org/10.1371/journal.pone.0222346.g002 Differential expression analysis of known and novel miRNAs after KPhi treatment To identify differentially expressed miRNAs after KPhi treatment, six small RNA libraries were constructed from treated and non treated plants and sequenced independently. Statistical analysis showed that 25 miRNAs were differentially expressed after KPhi treatment (Fig 3, S3 Table). Among them, 14 were already annotated in the miRBase, and 11 were mapped to the potato genome as potential novel miRNAs (PCs). From these 14 known miRNAs, 3 were up- regulated (stu-miR398b-3p, sly-miR167b-5p and stu-miR4376-5p L-1R+2) and 11 were down- regulated (stu-miR166b, stu-miR482c, stu-miR482a-3p, sly-miR159-p5, stu-miR171a-5p, stu- MIR7985-p5, sly-miR166c-3p_R+1, sly-miR166a_R+1, sly-miR171d_R+1_1ss8GA, stu- miR530_L-2R+2, sly-MIR166b-p5). Among the 11 potentially new miRNAs, 8 were up regulated (PC-3p-48036_37, PC-3p- 26055_79, PC-5p-1305_1307, PC-3p-2979_661, PC-3p-6013_346, PC-3p-40282_47, PC-5p- PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 6 / 15 Potassium phosphite responsive miRNAs in potato Table 1. Summary of data analysis results. Group # of sequences # of unique miRNAs Raw 58,391,355 Total mappable reads 32,677,778 Known miRNAs of specific species 1a 3,506,752 206 of selected species , but novel to specific species Group 1b 113,297 42 Predicted miRNAs Mapped to known miRNAs of selected species and genome; within hairpins 2a 1,515,585 38 Mapped to known miRNAs of selected species and genome; no hairpins 2b 871 132 Mapped to known miRNAs and miRNAs of selected species but unmapped to genome 3a 1,230 52 Mapped to known miRNAs of selected species but unmapped to genome 3b 550 52 Unmapped to known miRNAs but mapped to genome and within hairpins 4a 185,614 388 Overall 910 Others (mapped to mRNAs, RFam, or repbase) 7,554,022 Nohit 7,916,889 Solanum tuberosum Solanaceae https://doi.org/10.1371/journal.pone.0222346.t001 14130_152, PC-5p-4138_490) and 3 were down regulated (PC-5p-30841_65, PC-5p- 10686_200, PC-3p-14680_147). To confirm the high-throughput sequencing data, stem loop qRT-PCR was performed for 7 of the differentially expressed miRNAs. A comparison of the results from qPCR with those from NGS revealed similar patterns of expression (Fig 4). Target prediction and GO analysis To elucidate the biological functions of KPhi differentially expressed miRNAs, mRNA sequence complementarity was assessed using the psRNATarget software. A total of 211 potential target genes were identified for the 14 conserved miRNAs, based on their perfect or near-perfect complementarity to their target mRNA sequences. For most of the differentially expressed miRNAs, more than one potential target gene was predicted. Additionally, several target genes (a total of 118) were identified for most of the potentially novel miRNAs. Most of the predicted targets belong to transcription factor gene families, such as bZip, GRAS, AP2, REV HD-ZipIII, ARF, among others. Other miRNAs were predicted to target genes involved in the regulation of plant metabolism and stress responses. Detailed annotations of these results are presented in S4 Table. Some of the miRNA predicted targets were analyzed by qPCR (Fig 4, Table 2). These results showed that 6 of the analyzed targets followed a negatively correlated expression pattern with their miRNAs. However, miRNA171a-5p target (methylketone synthase Ib) expression, was not consistent with its miRNA down-regulation (Fig 4). To further analyze the biological function of miRNA targets, GO analysis was performed. The highest percentage of genes falls into defense response, regulation of transcription, and sig- nal transduction categories (biological process group). Cellular components and molecular func- tions of most of the genes are consistent with their biological process group (Fig 5, S5 Table) In-silico analysis of cis-elements present in KPhi responsive miRNA promoters Several stress responsive cis-elements were identified in-silico in promoters of potassium phos- phite differentially expressed miRNAs (Fig 6): anaerobic response element (ARE), element PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 7 / 15 Potassium phosphite responsive miRNAs in potato Fig 3. Heat map of differentially expressed miRNAs. KPhi treated (T2, T4, T6) and non treated (C1, C3, C5) replicates were analyzed. Differential expression of miRNAs based on normalized deep-sequencing counts, was analyzed using a Student’s t-test. Up-regulated and down-regulated miRNAs are represented in red and green, respectively. https://doi.org/10.1371/journal.pone.0222346.g003 sensitive to the fungal inducer (Box-W1), MYB binding site related to the abiotic stress (MBS) and its stress-related binding site MYBHv1 (CCAAT-box), MYB binding site involved in the regulation of flavonoid biosynthetic genes (MBSII), enhancer element involved in specific anoxic inducibility (GC-motif), cis-acting element involved in heat stress response (HSE), low temperature response element (LTR), repetitions rich in TC involved in defense and response to stress (TC-reach repeats), wound-sensitive element (WUN), UV light stress related cis-ele- ments (box I and box G). All miRNAs presented more than one stress related cis-elements in PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 8 / 15 Potassium phosphite responsive miRNAs in potato Fig 4. Validation of next generation sequencing (NGS) results for selected differentially expressed miRNAs and analysis of selected target genes. Quantitative real time PCR (qPCR) was performed to validate differentially expressed miRNAs (stu-miR482a-3p, stu-miR482c, stu-miR166b, stu-miR171a-5p, stu-miR530_L-2R+2, stu- MIR7985-p5, PC-5p-1305_1307) and targets (TIR-NBS-LRR resistance protein, Resistance protein PSH-RGH7, BZIP domain class transcription factor, Methylketone synthase Ib, Zinc knuckle (CCHC-type) family protein, Spotted leaf protein, F-box protein family). The EF1α gene was used as housekeeping. Three biological replicates were employed. Vertical bars represent the standard deviation of the mean (n = 3). https://doi.org/10.1371/journal.pone.0222346.g004 their promoter regions, suggesting they might participate in multiple stress response signaling pathways, and some of them were in multiple copy numbers. In addition to stress-related ele- ments, most of the KPhi differentially expressed miRNAs presented motifs associated to phy- tohormones: element sensitive to abscisic acid (ABRE), cis-acting regulatory element involved in the methyl jasmonic acid response (TGACG-motif), ethylene sensitive element (ERE), cis- acting element involved in the response to salicylic acid (TCA element), auxin-sensitive ele- ment (TGA element), cis-acting elements involved gibberellin response (GARE motif, P- box and TATC box). Table 2. Selected differentially expressed miRNAs after KPhi treatment and targets. miRNA Differential expression under KPhi treatment Target accession Target description stu-miR482a-3p Down-regulation PGSC0003DMT400053047 TIR-NBS-LRR resistance protein stu-miR482c Down-regulation PGSC0003DMT400012486 Resistance protein PSH-RGH7 stu-miR166b Down-regulation PGSC0003DMT400074934 BZIP domain class transcription factor stu-miR171a-5p Down-regulation PGSC0003DMT400066685 Methylketone synthase Ib stu-miR530_L-2R+2 Down-regulation PGSC0003DMT400002883 Zinc knuckle (CCHC-type) family protein stu-MIR7985-p5 Down-regulation PGSC0003DMT400062931 Spotted leaf protein PC-5p-1305_1307 Up-regulation PGSC0003DMT400027717 F-box family protein https://doi.org/10.1371/journal.pone.0222346.t002 PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 9 / 15 Potassium phosphite responsive miRNAs in potato Fig 5. Gene ontology analysis of differentially expressed miRNA targets. All identified target genes were classified according to their Biological process (BP), Molecular function (MF), and Cellular component (CC) based on GO enrichment analysis. Statistical significance was set to p<0.05. https://doi.org/10.1371/journal.pone.0222346.g005 Discussion Despite the available information about the stress protective effect of KPhi on different crops, the mode of action is unclear and the target/effector molecules in the plant are still unknown. Fig 6. In silico identification of cis-elements in the promoters of KPhi differentially expressed miRNAs. The promoters of pre-miRNAs were analyzed in silico using the web available program PlantCARE (bioinformatics.psb. ugent.be/webtools/plantcare/html). Down-regulated and up-regulated miRNAs are shown in black and grey, respectively. The numbers represent total well characterized cis-acting elements per miRNA. https://doi.org/10.1371/journal.pone.0222346.g006 PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 10 / 15 Potassium phosphite responsive miRNAs in potato The present study aimed to gain an insight into the complex mechanisms of action of KPhi. To achieve this objective, we performed a sequencing analysis to determine changes in miRNA expression and analyzed their targets in potato leaves treated with KPhi. Additionally, to iden- tify common cis-elements involved in miRNA regulation, we analyzed their promoters in-silico. High-throughput sequencing results revealed the presence of 206 unique miRNAs belong- ing to potato, and 42 unique miRNAs from tomato, but not previously described in potato. Additionally, a total of 288 potential new miRNAs were identified. Differential expression analysis showed changes in the relative abundance of 25 miRNAs after KPhi treatment, 14 of them belonging to known Solanaceae miRNA families and 11 of them being potential novel miRNAs. qPCR results were consistent with NGS differential expression analysis for 7 miR- NAs (stu-miR482a-3p, stu-miR482c, stu-miR166b, stu-miR171a-5p, stu-miR530_L-2R+2, stu- MIR7985-p5, PC-5p-1305_1307). The analysis of putative target genes of miRNAs responsive to KPhi treatment gave an insight into the potential mechanisms and effectors of this compound. In this context, we ana- lyzed the expression of 7 target genes: TIR-NBS-LRR resistance protein, Resistance protein PSH-RGH7, BZIP domain class transcription factor, Methylketone synthase Ib, Zinc knuckle (CCHC-type) family protein, Spotted leaf protein and, F-box family protein (Table 2). qPCR results showed that these genes were negatively correlated with the expression pattern of their complementary miRNA, with the exception of the putative target of miR171a-5p (methylke- tone synthase Ib). The unexpected behavior of the analyzed methylketone synthase gene might indicate that other regulatory mechanisms prevail over miR171 regulation, in the conditions of the present study (KPhi treatment), or that methylketone synthase is not a miRNA171 target in this system thus, miR171 might exert its action through other untested target genes. The target genes analyzed in this work are mainly involved in plant defense mechanisms. For instance, it is known that bZIP transcription factors (miR166b targets) are involved in both abiotic and biotic stress responses . Zhou et al. (2018) have described a potato bZIP tran- scription factor (StbZIP61) that regulates the biosynthesis of salicylic acid (SA) in the defense response against P. infestans . Moreover, putative targets of miR482a-3p and miR482c PSH-RGH7 resistance and TIR-NBS-LRR resistance proteins, respectively, belong to the class of characterized disease resistance genes (R genes). Plant R genes encode nucleotide-binding site leucine-rich repeat (NBS-LRR) proteins postulated to be involved in the detection of diverse specialized effectors from pathogens such as bacteria, viruses, fungi, nematodes, insects and oomycetes [28–31]. Despite the fact that in various plant species, computational analyses pre- dicted a high number of genes regulated by miRNAs, a few of them were validated in potato. In this work, we validated in potato, one of the predicted targets genes for stu-miR530_L-2R+2, a Zinc Knuckle (CCHC-type) family protein. Zinc Knuckle are zinc finger proteins containing a characteristic motif with two shortβ-strands joined by a turn. The expression of a potato zinc finger protein gene, StZFP1, has been reported to increase upon biotic and abiotic stress, and after exogenous ABA application . Although miR530 has been shown to target a zinc knuckle protein in rice , there are no previous reports available in potato. stu-MIR7985-p5 was differentially expressed after KPhi treatment and targeted a Spotted Leaf protein (SLp). Spotted Leaf proteins are U-box domain proteins that have been described to participate in the regulation of cell death and defense response mechanisms [34,35]. Zhang et al. (2013) have identified miR7985 in Solanum tuberosum by high-throughput sequencing , however, we report for the first time that this miRNA targets an SLp protein in potato. We have validated the differential expression of PC-5p-1305_1307, a putative novel miRNA that was up-regulated after KPhi treatment. This potential miRNA targets, and negatively reg- ulates an F-box protein. F-box proteins are key factors in phytohormone perception and stress signaling, photoperiodism, and metabolism regulation . Our results are in accordance PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 11 / 15 Potassium phosphite responsive miRNAs in potato with previous works that have reported, in Arabidopsis plants exposed to UV-B radiation, the suppressed expression of 4 F-box proteins, resulting in enhanced polyphenol levels, suggesting that they are involved in tolerance mechanisms against UV-B abiotic stress . Interestingly, most of the predicted target genes for the potential novel miRNAs described in this work belong to genes involved in plant defense reactions (S4 Table) and might play an important role in the regulation of the molecular events mediated by KPhi. Further experi- ments such as the validation of the potential new miRNAs and, a degradome analysis must be performed to analyze the battery of target genes that are differentially expressed after KPhi treatment. In order to gain information about the possible regulation of KPhi responsive miRNAs, the presence of well characterized cis-acting elements in the promoters of pre-miRNAs was ana- lyzed in-silico. We focused on cis-elements involved in biotic and abiotic stress and phytohor- mone responsiveness. Noteworthy, cis-elements that respond to phytohormones, fungal elicitors and stress were found in the promoters of most pre-miRNAs. A few stress-related cis- elements were found in most of KPhi responsive miRNAs (ARE, MBS, TC rich repeat, I box, and G-box). Regarding phytohormone responsiveness, TCA, a cis-element responsive to phy- tohormones, was present in most differentially expressed miRNAs. Interestingly, stu- miR530_L-2R+2 has 8 light-responsive elements (G-box and I-box) and 5 ABA-regulated sites. stu-MIR7985-p5 has 4 abscisic acid inducible cis-elements (MBS), while miRNAs stu- miR166b, sly-miR159, stu-miR482c, stu-miR398b, and sly-miR167b have a Box-W1, a motif responsive to, a motif responsive to fungal elicitors and wounding. The results presented in this work are consistent with the protective function of KPhi in potato described previously elsewhere. The diversity of differentially expressed miRNAs and the variety of cis-elements present in their promoters suggest that miRNAs are likely to partici- pate in KPhi-dependent induction of a plethora of defense pathways [5–7,11,38–40]. It has also been reported that these responses are dependent on the action of phytohormones such as SA, jasmonic acid (JA), auxins, and ethylene [10,41,42]. The cross-talk between hormone sig- naling pathways in plants has been extensively documented [43,44]. In this scenario, phos- phites might be a part of the intricate network of hormones/effectors activated as a defensive response upon stress. In summary, miRNAs that respond to KPhi treatment have a wide range of functions in plants, as their predicted target genes. These results are consistent with the number and diver- sity of responses that KPhi triggers in potato. In this work, we provide evidence that the ampli- tude of responses associated with KPhi treatment can be, at least in part, explained by the diversity of miRNAs that are differentially expressed. This is to our knowledge the first analysis of responsive miRNAs to a biocompatible stress resistance inducer as KPhi in potato. Additionally, we validated for the first time two predicted targets for potato miRNAs and a potential novel miRNA. Further characterization of these miRNAs and their target genes, might help to elucidate the molecular mechanisms underlying KPhi-induced resistance. This might in turn, aid in the design of genetically engineered pota- toes to achieve a product with enhanced resistance to environmental stress. Supporting information S1 Table. miRNAs and target genes primers. (DOC) S2 Table. RNA seq library reads. (XLS) PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 12 / 15 Potassium phosphite responsive miRNAs in potato S3 Table. miRNAs differential expression. (XLS) S4 Table. Target prediction. (XLS) S5 Table. GO analysis. (XLS) Acknowledgments We want to thank Dr. Milagros Machinadiarena and Dr. Marı ´a Vero ´ nica Beligni for their sug- gestions in the writing and improvement of the manuscript. Author Contributions Formal analysis: Marıa Florencia Rey-Burusco, Mariana Laura Feldman. Funding acquisition: Gustavo Raul Daleo, Mariana Laura Feldman. Investigation: Marıa Florencia Rey-Burusco, Mariana Laura Feldman. Methodology: Marıa Florencia Rey-Burusco. Project administration: Mariana Laura Feldman. Resources: Mariana Laura Feldman. Supervision: Gustavo Raul Daleo, Mariana Laura Feldman. Visualization: Marıa Florencia Rey-Burusco, Mariana Laura Feldman. Writing – original draft: Marıa Florencia Rey-Burusco, Mariana Laura Feldman. ´ ´ Writing – review & editing: Marıa Florencia Rey-Burusco, Gustavo Raul Daleo, Mariana Laura Feldman. References 1. FAO STAT Food and Agriculture Organization: Crops statistics database. FAO Prod Stat. 2017. www. fao.org/faostat 2. Arora RK, Sharma S, Singh BP. Late blight disease of potato and its management. Potato J. 2014; 4: 16–40. 3. Importance of potato late blight in Argentina, and the effect of fungicide treatments on yield increments over twenty years. Cien Inv Agr. 2009; 36: 115–122. https://doi.org/10.4067/S0718- 4. Trejo-Te ´ llez LI, Go ´ mez-Merino FC. Phosphite as an inductor of adaptive responses to stress and stimu- lator of better plant performance. In: Vats S, editor. Biotic and Abiotic Stress Tolerance in Plants. Springer, Singapore. 2018. https://doi.org/10.1007/978-981-10-9029-5_8 5. Lobato MC, Olivieri FP, Altamiranda EAG, Wolski EA, Daleo GR, Caldiz DO, et al. Phosphite com- pounds reduce disease severity in potato seed tubers and foliage. Eur J Plant Pathol. 2008; 122: 349– 358. https://doi.org/10.1007/s10658-008-9299-9 6. Lobato MC, Machinandiarena MF, Tambascio C, Dosio GAA, Caldiz DO, Daleo GR, et al. Effect of foliar applications of phosphite on post-harvest potato tubers. Eur J Plant Pathol. 2011; 130: 155–163. https://doi.org/10.1007/s10658-011-9741-2 7. Olivieri FP, Feldman ML, Machinandiarena MF, Lobato MC, Caldiz DO, Daleo GR, et al. Phosphite applications induce molecular modifications in potato tuber periderm and cortex that enhance resis- tance to pathogens. Crop Prot. 2012; 32: 1–6. https://doi.org/10.1016/j.cropro.2011.08.025 PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 13 / 15 Potassium phosphite responsive miRNAs in potato 8. Burra DD, Berkowitz O, Hedley PE, Morris J, Resjo ¨ S, Levander F, et al. Phosphite-induced changes of the transcriptome and secretome in Solanum tuberosum leading to resistance against Phytophthora infestans. BMC Plant Biol. 2014; 14: 1–17. https://doi.org/10.1186/1471-2229-14-1 9. Eshraghi L, Anderson J, Aryamanesh N, Shearer B, Mccomb J, Hardy GESJ, et al. Phosphite primed defense responses and enhanced expression of defense genes in Arabidopsis thaliana infected with Phytophthora cinnamomi. Plant Pathol. 2011; 60: 1086–1095. https://doi.org/10.1111/j.1365-3059. 2011.02471.x 10. Machinandiarena MF, Lobato MC, Feldman ML, Daleo GR, Andreu AB. Potassium phosphite primes defense responses in potato against Phytophthora infestans. J Plant Physiol. 2012; 169: 1417–1424. https://doi.org/10.1016/j.jplph.2012.05.005 PMID: 22727804 11. Oyarburo NS, Machinandiarena MF, Feldman ML, Daleo GR, Andreu AB, Olivieri FP. Potassium phos- phite increases tolerance to UV-B in potato. Plant Physiol Biochem. 2015; 88: 1–8. https://doi.org/10. 1016/j.plaphy.2015.01.003 PMID: 25596554 12. Dugas D V., Bartel B. MicroRNA regulation of gene expression in plants. Curr Opin Plant Biol. 2004; 7: 512–520. https://doi.org/10.1016/j.pbi.2004.07.011 PMID: 15337093 13. Sunkar R. MicroRNAs with macro-effects on plant stress responses. Semin Cell Dev Biol. 2010; 21: 805–811. https://doi.org/10.1016/j.semcdb.2010.04.001 PMID: 20398781 14. Jones-Rhoades MW, Bartel DP, Bartel B. MicroRNAS and their regulatory roles in plants. Annu Rev Plant Biol. 2006; 57: 19–53. https://doi.org/10.1146/annurev.arplant.57.032905.105218 PMID: 15. Song X, Li Y, Cao X, Qi Y. microRNAs and their regulatory roles in plant-environment interactions. Annu Rev Plant Biol. 2019; 70: 1–37. https://doi.org/10.1146/annurev-arplant-050718-100143 16. Jones-Rhoades MW, Bartel DP. Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Mol Cell. 2004; 14: 787–799. https://doi.org/10.1016/j.molcel.2004. 05.027 PMID: 15200956 17. Devi KJ, Chakraborty S, Deb B, Rajwanshi R. Computational identification and functional annotation of microRNAs and their targets from expressed sequence tags (ESTs) and genome survey sequences (GSSs) of coffee (Coffea arabica L.). Plant Gene. 2016; 6: 30–42. https://doi.org/10.1016/j.plgene. 2016.03.001 18. Zhang R, Marshall D, Bryan GJ, Hornyik C. Identification and characterization of miRNA transcriptome in potato by high-throughput sequencing. PLoS One. 2013; 8. https://doi.org/10.1371/journal.pone. 0057233 PMID: 23437348 19. Lakhotia N, Joshi G, Bhardwaj AR, Katiyar-Agarwal S, Agarwal M, Jagannath A, et al. Identification and characterization of miRNAome in root, stem, leaf and tuber developmental stages of potato (Solanum tuberosum L.) by high-throughput sequencing. BMC Plant Biol. 2014; 14: 1–16. https://doi.org/10.1186/ 1471-2229-14-1 20. Zhang W, Luo Y, Gong X, Zeng W, Li S. Computational identification of 48 potato microRNAs and their targets. Comput Biol Chem. 2009; 33: 84–93. https://doi.org/10.1016/j.compbiolchem.2008.07.006 PMID: 18723398 21. Dai X, Zhao PX. PsRNATarget: A plant small RNA target analysis server. Nucleic Acids Res. 2011; 39: 155–159. https://doi.org/10.1093/nar/gkq766 22. Varkonyi-Gasic E, Wu R, Wood M, Walton EF, Hellens RP. Protocol: A highly sensitive RT-PCR method for detection and quantification of microRNAs. Plant Methods. 2007; 3: 1–12. https://doi.org/10. 1186/1746-4811-3-1 23. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real time quantitative PCR and the 2ΔΔC(T) Method. Methods. 2001; 25(4): 402–408. https://doi.org/10.1006/meth.2001.1262 PMID: 11846609 24. Pfaffl MW, Horgan GW, Dempfle L. Relative expression software tool (REST) for group-wise compari- son and statistical analysis of relative expression results in real-time PCR. Nucleic Acids Res. 2002; 30: e36. https://doi.org/10.1093/nar/30.9.e36 PMID: 11972351 25. Lescot M. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in sil- ico analysis of promoter sequences. Nucleic Acids Res. 2002; 30: 325–327. https://doi.org/10.1093/ nar/30.1.325 PMID: 11752327 26. Alves MS, Dadalto SP, Gonc ¸ alves AB, De Souza GB, Barros VA, Fietto LG. Plant bZIP transcription factors responsive to pathogens: A review. Int J Mol Sci. 2013; 14: 7815–7828. https://doi.org/10.3390/ ijms14047815 PMID: 23574941 27. Zhou XT, Jia LJ, Wang HY, Zhao P, Wang WY, Liu N, et al. The potato transcription factor StbZIP61 regulates dynamic biosynthesis of salicylic acid in defense against Phytophthora infestans infection. Plant J. 2018; 95: 1055–1068. https://doi.org/10.1111/tpj.14010 PMID: 29952082 PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 14 / 15 Potassium phosphite responsive miRNAs in potato 28. Nandety RS, Caplan JL, Cavanaugh K, Perroud B, Wroblewski T, Michelmore RW, et al. The role of TIR-NBS and TIR-X proteins in plant basal defense responses. Plant Physiol. 2013; 162: 1459–1472. https://doi.org/10.1104/pp.113.219162 PMID: 23735504 29. Lee JJ, Park KW, Kwak YS, Ahn JY, Jung YH, Lee BH, et al. Comparative proteomic study between tuberous roots of light orange- and purple-fleshed sweetpotato cultivars. Plant Sci. 2012; 193–194: 120–129. https://doi.org/10.1016/j.plantsci.2012.06.003 PMID: 22794925 30. Slootweg E, Koropacka K, Roosien J, Dees R, Overmars H, Lankhorst RK, et al. Sequence exchange between homologous NB-LRR genes converts virus resistance into nematode resistance, and vice versa. Plant Physiol. 2017; 175: 498–510. https://doi.org/10.1104/pp.17.00485 PMID: 28747428 31. Jiang N, Meng J, Cui J, Sun G, Luan Y. Function identification of miR482b, a negative regulator during tomato resistance to Phytophthora infestans. Hortic Res. Springer US. 2018; 5. https://doi.org/10.1038/ s41438-018-0017-2 PMID: 29507733 32. Tian ZD, Zhang Y, Liu J, Xie CH. Novel potato C2H2-type zinc finger protein gene, StZFP1, which responds to biotic and abiotic stress, plays a role in salt tolerance. Plant Biology. 2010; 12: 689–697. https://doi.org/10.1111/j.1438-8677.2009.00276.x PMID: 20701691 33. Sun W, Xu XH, Wu X, Wang Y, Lu X, et al. Genome-wide identification of microRNAs and their targets in wild type and phyB mutant provides a key link between microRNAs and the phyB-mediated light sig- naling pathway in rice. Front Plant Sci. 2015; 6: 372. https://doi.org/10.3389/fpls.2015.00372 PMID: 34. Zeng LR, Qu S, Bordeos A, Yang C, Baraoidan M, Yan H, et al. Spotted leaf11, a negative regulator of plant cell death and defense, encodes a U-Box/Armadillo repeat protein endowed with E3 ubiquitin ligase activity. Plant Cell Online. 2004; 16: 2795–2808. https://doi.org/10.1105/tpc.104.025171 PMID: 35. Yamanouchi U, Yano M, Lin H, Ashikari M, Yamada K. A rice spotted leaf gene, Spl7, encodes a heat stress transcription factor protein. 2002; 99: 7530–7535. https://doi.org/10.1073/pnas.112209199 36. Zhang X, Gonzalez-Carranza ZH, Zhang S, Miao Y, Liu C-J, Roberts JA. F-Box proteins in plants. Annu Plant Rev. 2019; 1–21. https://doi.org/10.1002/9781119312994.apr0701 37. Zhang X, Gou M, Guo C, Yang H, Liu C-J. Down-regulation of Kelch domain-containing F-Box protein in Arabidopsis enhances the production of (poly)phenols and tolerance to ultraviolet radiation. Plant Phy- siol. 2014; 167: 337–350. https://doi.org/10.1104/pp.114.249136 PMID: 25502410 38. Bengtsson T, Weighill D, Proux-We ´ ra E, Levander F, Resjo ¨ S, Burra DD, et al. Proteomics and tran- scriptomics of the BABA-induced resistance response in potato using a novel functional annotation approach. BMC Genomics. 2014; 15: 1–19. https://doi.org/10.1186/1471-2164-15-1 39. Lim S. Analysis of changes in the potato leaf proteome triggered by phosphite reveals functions associ- ated with induced resistance against Phytophthora infestans. Thesis. Dalhousie University. 2012; Avail- able from: http://dalspace.library.dal.ca/handle/10222/15859 40. Lim S, Borza T, Peters RD, Coffin RH, Al-Mughrabi KI, Pinto DM, et al. Proteomics analysis suggests broad functional changes in potato leaves triggered by phosphites and a complex indirect mode of action against Phytophthora infestans. J Proteom. 2013; 93: 207–23. https://doi.org/10.1016/j.jprot. 2013.03.010 41. Eshraghi L, Anderson JP, Aryamanesh N, McComb JA, Shearer B, Hardy GSJE. Suppression of the auxin response pathway enhances susceptibility to Phytophthora cinnamomi while phosphite-mediated resistance stimulates the auxin signalling pathway. BMC Plant Biol. 2014; 14: 1–15. https://doi.org/10. 1186/1471-2229-14-1 42. Massoud K, Barchietto T, Le Rudulier T, Pallandre L, Didierlaurent L, Garmier M, et al. Dissecting phos- phite-induced priming in Arabidopsis infected with Hyaloperonospora arabidopsidis. Plant Physiol. 2012; 159: 286–298. https://doi.org/10.1104/pp.112.194647 PMID: 22408091 43. Tsuda K, Somssich IE. Transcriptional networks in plant immunity. New Phytol. 2015; 206: 932–947. https://doi.org/10.1111/nph.13286 PMID: 25623163 44. Checker VG, Kushwaha HR, Kumari P, Yadav S. Role of phytohormones in plant defense: Signaling and cross talk. Mol Asp Plant-Pathogen Interact. 2018; 159–184. https://doi.org/10.1007/978-981-10- 7371-7_7 PLOS ONE | https://doi.org/10.1371/journal.pone.0222346 September 12, 2019 15 / 15
PLoS ONE – Public Library of Science (PLoS) Journal
Published: Sep 12, 2019
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera