Funct Integr Genomics DOI 10.1007/s10142-015-0452-1

ORIGINAL ARTICLE

miRNA-based drought regulation in wheat Guray Akdogan 1 & Ebru Derelli Tufekci 1,2 & Serkan Uranbey 1 & Turgay Unver 2

Received: 2 March 2015 / Revised: 20 June 2015 / Accepted: 23 June 2015 # Springer-Verlag Berlin Heidelberg 2015

Abstract MicroRNAs (miRNAs) are a class of small noncoding regulatory RNAs that regulate gene expression by guiding target mRNA cleavage or translational inhibition. Drought is a common environmental stress influencing crop growth and development. To date, it has been reported that a number of plant miRNA are involved in drought stress response. In this study, we comparatively investigated drought stress-responsive miRNAs in the root and leaf of bread wheat (Triticum aestivum cv. Sivas 111/33) by miRNA microarray screening. miRNA microarray analysis showed that 285 miRNAs (207 upregulated and 78 downregulated) and 244 miRNAs (115 upregulated and 129 downregulated) were differentially expressed in leaf and root tissues, respectively. Among the differentially expressed miRNAs, 23 miRNAs were only expressed in the leaf and 26 miRNAs were only expressed in the root of wheat growth under drought stress. Upon drought treatment, expression of miR159, miR160, miR166, miR169, miR172, miR395, miR396, miR408, miR472, miR477, miR482, miR1858, miR2118, and miR5049 were found to be significantly differentiated in bread wheat. The regulatory network analysis showed that miR395 has connections with a number of target transcripts, and miR159 and miR319 share a number of target genes. Electronic supplementary material The online version of this article (doi:10.1007/s10142-015-0452-1) contains supplementary material, which is available to authorized users. * Turgay Unver [email protected] 1

Department of Field Crops, Faculty of Agriculture, Ankara University, 06110 Ankara, Turkey

2

Department of Biology, Faculty of Science, Çankırı Karatekin University, 18100 Çankırı, Turkey

Drought-tolerant and drought-sensitive wheat cultivars showed altered expression pattern upon drought stress in terms of investigated miRNA and their target transcript expression level. Keywords Drought stress . microRNA . Microarray . Triticum aestivum

Introduction Hexaploid bread wheat (Triticum aestivum L., AABBDD, 2n=42) is one of the main staple crops. Together with maize and rice, wheat provides >60 % of the average daily diet for humans (faostat.fao.org). Crop species including wheat are challenged by several biotic and abiotic factors affecting agronomic production (Xin et al. 2010; Pandey et al. 2014). Moreover, several abiotic stress factors such as droughts, floods, and salinity become more common as a result of global climate change (Shanker et al. 2014). Drought negatively affects vegetative and reproductive plant development causing severe reductions in plant productivity. Additionally, it can cause a series of physiological and biochemical changes in plants (Wu et al. 2014; Li et al. 2015; Zhang 2015). To cope with the challenging aspects of drought, plants use several mechanisms and produce response at physiological and molecular levels (Shiriga et al. 2014). Plant microRNAs (miRNAs) are a highly conserved class of small (21–24 nucleotides), non-coding RNAs that regulate gene expression by post-transcriptional degradation or translational repression (Liu et al. 2008; Unver et al. 2009; Eldem et al. 2013; Zhang 2015). miRNAs have emerged as important players in post-transcriptional gene regulation. After discovery of miRNAs as a post-transcriptional regulator, it has led to the understanding of the expression behavior of

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genes at post-transcriptional level (Gupta et al. 2014). In recent years, several studies showed that miRNAs are involved in response to abiotic stress (Sunkar et al. 2007; Lu and Huang 2008; Zhou et al. 2010; Eldem et al. 2012; Wang et al. 2013; Eren et al. 2015; Hajyzadeh et al. 2015). Several miRNA families have been reported to be differentially regulated in response to drought stress in various plant species, including rice (Zhao et al. 2007), tomato (Solanum lycopersicum (Zhang et al. 2011), Arabidopsis (Liu et al. 2008), Medicago truncatula (Trindade et al. 2010), peach (Eldem, et al. 2012), barley (Kantar et al. 2010), and wheat (Gupta, et al. 2014; Pandey, et al. 2014). There are several studies documenting expression levels of various miRNAs in T. aestivum L. (Xin, et al. 2010; Inal et al. 2014; Pandey, et al. 2014), but none of these miRNAs are experimentally verified. Moreover, the biological functions of miRNAs upon drought stress have been identified experimentally in plants, but the number of studies is very limited. For example, overexpression of Os-miR319a in transgenic creeping bentgrass (Agrostis stolonifera) showed an enhanced drought and salt tolerance (Zhou et al. 2013). Overexpressing Sly-miR169c in transgenic tomato plant displayed reduced stomatal opening, decreased transpiration rate, lowered leaf water loss, and enhanced drought tolerance compared to those of non-transgenic tomato plant (Zhang, et al. 2011). In chickpea, induced tolerance was observed in the plants with enhanced miR408 expression upon 17-day water deficiency (Hajyzadeh, et al. 2015). In this study, we aimed to measure and identify the expression patterns of tissue-specific drought stress-responsive wheat miRNAs by using miRNA array analysis. Differentially expressed miRNAs in response to drought stress were determined in leaves and roots of wheat. The predicted target genes of regulated miRNAs were classified by using gene ontology and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to understand their function in response to drought stress. Moreover, we investigated regulation of some selected miRNAs and their target genes in drought-tolerant and drought-sensitive wheat cultivars subjected to drought stress. This study provides a comprehensive analysis of the miRNAs differentially expressed in leaves and roots of bread wheat in response to drought stress.

Materials and methods Plant materials, growth, and stress conditions Drought-tolerant (cv. Sivas 111/33) and droughtsusceptible (cv. Atay 85) bread wheat (T. aestivum L.) cultivars were kindly provided by the Central Research Institute for Field Crops (TARM) in Ankara, Turkey. Surface sterilization of seeds was performed with

70 % (v/v) ethanol for 2 min, and in 10 % (v/v) sodium hypochloride for 10 min, and then rinsed three times with sterile distilled H2O. The sterilized seeds were germinated in Petri dishes on two layers of filter papers at room temperature. After 4 days, the germinated seedlings were transferred to Murashige and Skoog (MS) medium (pH 5.7) containing 0.3 % agar and 3 % sucrose, and growth under controlled conditions (16/8 h photoperiod, 25±1 °C, 60 % relative humidity, and photon flux density of 200 μmol m−2 s−1). Ten-day-old plants were exposed to dehydration stress in plastic pots containing MS medium and 20 % polyethylene glycol (PEG) 6000 for 24 h. Control plants were kept in fresh MS medium. Fifteen seedlings were included in each treatment and control group. sRNA and total RNA isolation For miRNA microarray analysis, total RNA samples enriched for small RNAs were isolated from uppermost leaves and root tissues of cv. Sivas 111/33 using mirVan miRNA Isolation Kit (Life Technologies, Carlsbad, CA, USA) according to the manufacturer’s instructions. For qRT-PCR analysis, total RNA from uppermost leaves and roots of the cultivars Sivas 111/33 and Atay 85 was isolated using TRIzol (Ambion, TX, USA) reagent according to the manufacturer’s instructions. The RNA quality was checked on 1.5 % agarose gel, and the concentration of the RNA was determined using a NanoDrop ND-2000c spectrophotometer (Thermo Fisher Scientific, USA). miRNA microarray assay and data analysis The synthesis and hybridization of miRNA microarray chip were performed by LC Sciences Company (Houston, TX, USA, ). The miRNA microarray chip involved triplicates of 4025 unique mature miRNA probes corresponding to miRNA transcripts listed in Sanger miRBase release 20.0 (http://www.mirbase.org) belonging to 72 species including wheat (40 probes), rice (553 probes), and barley (65 probes), with multiple control probes. The numbers of miRNA probes belonging to various plants were listed in Supplementary Table 1. Five micrograms of small RNA-enriched total RNA samples from treated and untreated leaf and root tissues of cv. Sivas 111/33 were used in the microarray assay. Here, sRNAs of fifteen seedlings were included in each treatment and control group and mixed accordingly. Axon GenePix 4000B Microarray Scanner was used for data collection, and ArrayPro image analysis software (Media Cybernetics, MD, USA) was utilized for data extraction and image processing. Background fluorescence signal was subtracted, and hybridization target

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signal is considered detectable when it is significantly a bo v e b a c kg r o u n d ( C a s e l l a a nd B e rge r 2 0 0 2) . Normalization on background-subtracted data was performed using the locally weighted scatterplot smoothing (LOWESS) method (Cleveland 1979) to remove system-related variations, such as sample amount variations, labeling dye differences, signal gain differences of scanners, and nonlinear signal intensity response to target concentration so that biological variations are faithfully revealed. Differential analysis was performed to reveal significantly differentiated miRNAs between treated and untreated samples as well as leaf and root tissues. The degree of significance was evaluated by comparing between-group variation with within-group variation via ANOVA and T test; differentially detected signals with p < 0.01 were listed as significant (Unver et al. 2010; Boke et al. 2015). Validation of drought-responsive miRNA expression by quantitative RT-PCR The expression levels of 10 miRNAs, identified as drought-responsive according to miRNA microarray results, were analyzed in treated and control leaf and root tissues of T. aestivum cv. Sivas 111/33 and cv. Atay 85. The miRNA stem-loop reverse transcription (RT) was carried out using 1 μg of total RNA sample, 0.5 μl 10 mM dNTP mix, 1 μM stem-loop RT primer, and 11.15 μl of nuclease-free distilled H2O. The mix was incubated at 65 °C for 5 min and then put on ice for 2 min. Afterwards, 4 μl of first-strand buffer (5X), 2 μl of 0.1 M dithiothreitol, 4 U RNAseOUT, and 50 U SuperScript III (Invitrogen) were added into each tube, and the RT reaction was performed at 16 °C for 30 min followed by 60 cycles of 30 °C for 30 s, 42 °C for 30 s, and 50 °C for 1 s, and the reaction was terminated at 85 °C for 5 min. Three control reactions containing all components without RT primer, RNA template, or SuperScript III were also performed. qRT-PCR was conducted using SYBR Green I Master Kit (Roche) on a Light Cycler 480 II Real-Time PCR System (Roche, Germany). For qRT-PCR analysis, 10 μl 2X Master mix, 100 pmol forward and reverse primers, 7.8 mL nucleasefree distilled H2O, and 2 μl cDNA (miRNA RT product) were used. The sequences of forward primers, specifically designed for each individual miRNA, and the universal reverse primer were listed in Supplementary Table 2. The qRT-PCR was performed at 95 °C for 5 min, followed by 45 cycles of 95 °C for 5 s, 56 °C for 10 s, and 72 °C for 1 s. The melting curves were adjusted as 95 °C for 1 s and 40 °C for 2 min. The expression levels were calculated as the mean-signal intensity across the three replicates (Unver, et al. 2010; Boke, et al. 2015).

Validation of wheat miRNA targets by quantitative RT-PCR The potential targets of differentially expressed wheat miRNAs were determined using psRNATarget Server with default parameters. Mature miRNA sequences were used as queries to search against T. aestivum (wheat), unigene, Dana Farber Cancer Institute (DFCI) Gene Index (TAGI), version 12. Total RNA for quantitative qRT-PCR analysis was prepared from leaf and root tissues of cv. Sivas 111/33 and cv. Atay 85 growth under drought condition as described above. cDNA was primed with OligodT in a 20-μl reaction mix using M-MuLV Reverse Transcriptase (Thermo Scientific, USA) following the manufacturer’s instructions. The qRT-PCR was conducted in 96-well optical plates using 100 pmol forward and reverse primers (Supplementary Table 3), 2 μl cDNA, 10 μl FastStart SYBR Green I Master Mix (Roche, Germany) and to make final volume of 20 μl, nuclease-free distilled H2O was added. The qRT-PCR was performed on LightCycler 480 Instrument II (Roche, Germany), and the conditions were set up as follows: preheating at 95 °C for 5 min followed by 50 cycles of 95 °C for 10 s, 55 °C for 20 s, and 72 °C for 10 s. The melting curves were adjusted as 95 °C for 5 s and 55 °C for 1 min and then cooled to 40 °C for 30 s. All reactions were repeated three times, and 18 s rRNA gene was used as internal control (Inal, et al. 2014). Network visualization Regulatory network between miRNAs and their target genes were constructed and visualized by using Cytoscape v2.8.3 (http://www.cytoscape.org) (Shannon et al. 2003). Functional annotation of the potential miRNA target genes The potential target transcripts of miRNAs differentially expressed in leaves and roots of wheat were subjected to InterProScan (BLASTP < 1e − 5), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to investigate their biological functions. InterProScan analyzes (v5) were performed using the TRAPID transcript annotation tool (Van Bel et al. 2013), and the output from InterProScan was used to obtain GO categories of each target. Gene ontology classification (biological process, molecular function, and cellular component) of predicted target genes was generated using agriGO web tool based on GO terms (Du et al. 2010) and plant GO slim categorization (Clark et al. 2005). KEGG analysis was performed using the online KEGG Automatic Annotation Server (KAAS) with bidirectional best hit-assignment (BBH) mode (Moriya et al. 2007).

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Results Drought-responsive miRNAs in wheat In order to identify the drought-responsive miRNAs in leaves and roots of wheat, expression level of miRNAs was compared between control samples and stress treatment samples by using miRNA microarray. Microarray results revealed that 285 and 244 miRNAs were differentially regulated at statistically significant level (p value