Overexpression of miR169o, an Overlapping MicroRNA in Response to Both Nitrogen Limitation and Bacterial Infection, Promotes Nitrogen Use Efficiency and Susceptibility to Bacterial Blight in Rice

Overexpression of miR169o, an Overlapping MicroRNA in Response to Both Nitrogen Limitation and... Abstract Limiting nitrogen (N) supply contributes to improved resistance to bacterial blight (BB) caused by Xanthomonas oryzae pv. oryzae (Xoo) in susceptible rice (Oryza sativa). To understand the regulatory roles of microRNAs (miRNAs) in this phenomenon, 63 differentially expressed overlapping miRNAs in response to Xoo infection and N limitation stress in rice were identified through deep RNA sequencing and stem–loop quantitative real-time PCR. Among these, miR169o was further assessed as a typical overlapping miRNA through the overexpression of the miR169o primary gene. Osa-miR169o-OX plants were taller, and had more biomass accumulation with significantly increased nitrate and total amino acid contents in roots than the wild type (WT). Transcript level assays showed that under different N supply conditions, miR169o oppositely regulated NRT2, and this is reduced under normal N supply conditions but remarkably induced under N-limiting stress. On the other hand, osa-miR169o-OX plants also displayed increased disease lesion lengths and reduced transcriptional levels of defense gene (PR1b, PR10a, PR10b and PAL) compared with the WT after inoculation with Xoo. In addition, miR169o impeded Xoo-mediated NRT transcription. Therefore, the overlapping miR169o contributes to increase N use efficiency and negatively regulates the resistance to BB in rice. Consistently, transient expression of NF-YA genes in rice protoplasts promoted the transcripts of PR genes and NRT2 genes, while it reduced the transcripts of NRT1 genes. Our results provide novel and additional insights into the co ordinated regulatory mechanisms of cross-talk between Xoo infection and N deficiency responses in rice. Introduction Nitrogen (N) is an essential mineral nutrient for normal plant growth, and the use of N fertilizers has led to dramatically increased yields in recent decades (Tilman et al. 2002). However, excessive N fertilizer usage has led to considerable environmental problems which seriously threaten global ecosystems (Nosengo 2003, Giles 2005). The ideal way to decrease N application rates while maintaining yields is to improve N use efficiency (NUE) in crops (Bi et al. 2009). In addition to the ecological harm due to use of excessive N fertilizer, there is also a link between the level of N availability and disease resistance, with the application of high N concentrations being shown to promote plant susceptibility to disease. For example, tomato plants were more susceptible to Pseudomonas syringae pv. tomato (Pst) infection with increasing N concentrations (Hoffland et al. 2000), and fungal blast disease caused by Magnaporthe grisea became more severe with increasing N application in rice (Oryza sativa) (Mukherjee et al. 2005). Bacterial blight (BB) of rice caused by Xanthomonas oryzae pv. oryzae (Xoo) is one of the most important bacterial diseases in the world and can even cause up to a 70% yield loss (http://www.knowledgebank.irri.org/decision-tools/rice-doctor/rice-doctor-fact-sheets/item/bacterial-blight). Moreover, the transcriptomic response to Xoo infection showed a large overlap among the responses to drought, salt, cold and heat stress, based on the analysis of nearly 100 microarrays in rice (Narsai et al. 2013). Our previous work demonstrated that rice plants grown under an N limitation condition had a reduced susceptibility to bacterial blight caused by Xoo compared with those grown under normal N supply (Yu et al. 2015). Subsequent genome-wide transcriptional analysis discovered 248 overlapping genes that responded to both Xoo infection and N limitation stress (Yu et al. 2015). However, the intrinsic regulatory mechanisms controlling these genes are still unclear. MicroRNAs (miRNAs) are a highly conserved class of small non-coding RNAs that cause cleavage or translational repression of their target mRNAs, and their roles in gene regulation are essential for normal growth and development (Reinhart et al. 2002, Bartel 2004). With the development of deep sequencing technology, a large number of plant miRNAs responsive to biotic and abiotic stresses have been identified and characterized. For instance, 25 conserved miRNA families and 15 novel miRNAs responding to the diazotrophic bacterium Herbaspirillum seropedicae were identified in maize (Thiebaut et al. 2014). N deficiency-responsive miRNAs in Arabidopsis (Liang et al. 2012) and maize (Zhao et al. 2012), phosphate deficiency-responsive miRNAs in soybean (Xu et al. 2013) and Rice stripe virus-responsive miRNAs in rice (Guo et al. 2012) were identified through deep sequencing. Quantitative real-time PCR (qRT-PCR) validation of several miRNA profiles under drought and rust infection stress showed that these miRNAs were responsive to either stress in soybeans (Kulcheski et al. 2011). Recently, miRNAs involved in the uptake, assimilation and translocation of nutrients in plants have also been reported. Well-studied miR167 and miR393 have been reported to participate in the regulation of nitrate signaling in root growth in soybean and Arabidopsis, respectively (Vidal et al. 2010, Wang et al. 2015). Also Pi deprivation-induced miR827 post-transcriptionally repressed its target gene NITROGEN LIMITATION ADAPTATION (NLA) and affected the adaption to N-limiting stress in Arabidopsis (Peng et al. 2007, Kant et al. 2011). In addition, overexpression of miR444a improved nitrate accumulation and enhanced the expression of nitrate transporter genes under high nitrate concentration conditions in rice (Yan et al. 2014). Ath-miR5090, a new miRNA from the complementary transcript of the miR826 gene, is induced by N starvation. The transcript level of AOP2 (alkenyl hydroxalkyl producing2, AOP2) is negatively correlated with miR826 and miR5090 under N starvation. Overexpression of miR5090 in Arabidopsis enhanced the tolerance to N starvation, including high biomass, more lateral roots, increased Chl and up-regulated N starvation-responsive genes (He et al. 2014). These observations clearly show that miRNAs play significant roles in adaption to biotic and abiotic stresses in plants. The miR169 family is one of the largest conserved miRNA families in Oryza sativa and is encoded by 18 members (http://www.mirbase.org/). Some of these members have been annotated with specific functions in previous studies. For example, miR169a and c were down-regulated by drought stress, while miR169a, b, d and h were up-regulated at low temperature in Arabidopsis (Li et al. 2008, Lee et al. 2010). In addition, the expression of miR169a and b was suppressed by N deficiency in maize (Zhao et al. 2011). The main predicted targets of miR169 encode subunit A of nuclear factor Y (NF-YA), which has been linked to development and response to abiotic stresses in plants (Rhoades et al. 2002, Combier et al. 2006, Nelson et al. 2007, Liu and Howell 2010). Overexpression of miR169 in Arabidopsis changed flowering time and root architecture by repressing the AtNF-YA2 transcription factor (Sorin et al. 2014, Xu et al. 2014). Osa-miR169g and osa-miR169n/o were up-regulated by high salinity, and selectively cleaved NF-YA8 (LOC_Os03g29760) in response to high salinity stress (Zhao et al. 2009). However, the role of miR169 and its target genes in response to biotic stress have rarely been reported. Here, 63 potential overlapping miRNAs in response to both Xoo infection and N limitation stress were identified by deep sequencing technology and qRT-PCR. Moreover, genetic analysis showed that overexpression of overlapping osa-miR169o increased the susceptibility to bacterial blight caused by Xoo infection and enhanced NUE in rice. Therefore, the results provide additional insights into dissection of the complex and diverse regulatory mechanisms in response to various environmental stress. Results miRNA sequencing in rice under Xoo infection and N limitation conditions In our previous work, rice plants showed less susceptibility to bacterial BB by Xoo under N limitation conditions, and some overlapping genes were found to be regulated by both Xoo infection and N limitation (Yu et al. 2015). Transcriptional levels of disease resistance-related and nitrate transporter-related genes in response to Xoo infection, N limiting and combined stress were measured. The results showed that resistance-related genes such as PR1b, PR10a, PR10b and PAL (Supplementary Fig. S1A), and nitrate transporter genes such as OsNPF2.4, OsNRT2.1 and OsNRT2.2 (Supplementary Fig. S1B) were up-regulated in response to individual and combined stress, respectively. In view of the significant regulatory roles of miRNAs in response to various biotic and abiotic stresses, we hypothesized that miRNAs may be involved in the regulatory response to Xoo infection and N limitation stress. To test this hypothesis, four RNA libraries were constructed from rice leaves with four treatments [distilled water/normal N (HN), Xoo/normal N (XN), distilled water/limiting N (HL) and Xoo/limiting N (XL)] and sequenced using Solexa high-throughput sequencing technology. About 22.7, 18.1, 19.3 and 16.7 million raw reads were generated for the HN, XN, HL and XL libraries, respectively, with 3.57, 2.39, 2.40 and 2.17 million unique miRNA reads cleaned and mapped to the rice genome (Table 1). After alignment with the 592 known miRNAs in 336 families in rice from miRBase 20 (http://www.mirbase.org/) (Griffiths-Jones et al. 2006, Griffiths-Jones et al. 2008, Kozomara and Griffiths-Jones 2011), 504, 474, 489 and 459 unique miRNAs were identified from these sequenced libraries, respectively (Table 1). Nomalized reads of tested miRNAs in HN, XN, HL and XL libraries are listed in Supplementary Table S1. Table 1 Summary of sequencing data Sample Raw reads Clean reads >17 nt Mapped reads (%) Unique miRNA reads Mapped unique miRNA reads (%) Oas miRNA number HN 22,662,024 22,484,805 15,522,796 13,253,015 (85.38) 3,570,263 2,588,945 (72.51) 504 XN 18,071,689 17,941,119 11,966,528 9,799,043 (81.89) 2,385,370 1,588,041 (66.57) 474 HL 19,319,548 19,180,255 12,214,690 10,279,782 (84.16) 2,396,089 1,648,137 (68.78) 489 XL 16,727,349 16,598,675 11,105,747 9,209,403 (82.92) 2,171,498 1,455,981 (67.05) 459 Sample Raw reads Clean reads >17 nt Mapped reads (%) Unique miRNA reads Mapped unique miRNA reads (%) Oas miRNA number HN 22,662,024 22,484,805 15,522,796 13,253,015 (85.38) 3,570,263 2,588,945 (72.51) 504 XN 18,071,689 17,941,119 11,966,528 9,799,043 (81.89) 2,385,370 1,588,041 (66.57) 474 HL 19,319,548 19,180,255 12,214,690 10,279,782 (84.16) 2,396,089 1,648,137 (68.78) 489 XL 16,727,349 16,598,675 11,105,747 9,209,403 (82.92) 2,171,498 1,455,981 (67.05) 459 HN, distilled water/normal N; XN, Xoo/normal N; HL, distilled water/N limitation; XL, Xoo/N limitation. Table 1 Summary of sequencing data Sample Raw reads Clean reads >17 nt Mapped reads (%) Unique miRNA reads Mapped unique miRNA reads (%) Oas miRNA number HN 22,662,024 22,484,805 15,522,796 13,253,015 (85.38) 3,570,263 2,588,945 (72.51) 504 XN 18,071,689 17,941,119 11,966,528 9,799,043 (81.89) 2,385,370 1,588,041 (66.57) 474 HL 19,319,548 19,180,255 12,214,690 10,279,782 (84.16) 2,396,089 1,648,137 (68.78) 489 XL 16,727,349 16,598,675 11,105,747 9,209,403 (82.92) 2,171,498 1,455,981 (67.05) 459 Sample Raw reads Clean reads >17 nt Mapped reads (%) Unique miRNA reads Mapped unique miRNA reads (%) Oas miRNA number HN 22,662,024 22,484,805 15,522,796 13,253,015 (85.38) 3,570,263 2,588,945 (72.51) 504 XN 18,071,689 17,941,119 11,966,528 9,799,043 (81.89) 2,385,370 1,588,041 (66.57) 474 HL 19,319,548 19,180,255 12,214,690 10,279,782 (84.16) 2,396,089 1,648,137 (68.78) 489 XL 16,727,349 16,598,675 11,105,747 9,209,403 (82.92) 2,171,498 1,455,981 (67.05) 459 HN, distilled water/normal N; XN, Xoo/normal N; HL, distilled water/N limitation; XL, Xoo/N limitation. Identification of Xoo infection-responsive or/and N-limitation-responsive miRNAs A number of plant miRNAs have been identified in response to individual pathogen infection (Navarro et al. 2006, Li et al. 2010, Xin et al. 2010, Guo et al. 2012) and N deficiency (Liang et al. 2012, Zhao et al. 2012). In the current study, comparisons of three sets of miRNA expression profiles [XN vs. HN (Xoo stress), HL vs. HN (N limitation stress) and XL vs. HN (the combined stress)] were performed, and the candidate stress-responsive miRNAs with different expression profiles were defined using a P-value <0.05 and a fold change >1.5 as the cut-off. As shown in Fig.1A, 150 Xoo-responsive (XN vs. HN, 75 up-regulated, 75 down-regulated), 157 N limitation-responsive (HL vs. HN, 39 up-regulated, 118 down-regulated) and 224 combined stress-responsive (XL vs. HN, 48 up-regulated, 176 down-regulated) miRNAs were identified (Fig. 1A). Analysis of the unique and overlapping miRNAs showed that the expression of 63 miRNAs responded to Xoo infection, N limitation and the combined stress (Fig.1B). Among these, 36 miRNAs displayed down-regulated expression, while 15 miRNAs displayed up-regulated expression in response to the individual and combined stress conditions (Fig. 1C, a and b). To verify the RNA-sequencing data, expression patterns of 30 randomly selected miRNAs, representing Xoo infection-responsive, N limitation-responsive and combined stress-responsive miRNAs, were determined based on stem–loop qRT-PCR (Supplementary Fig. S2). All the assayed expression patterns were consistent with that from RNA-sequencing analyses, although slight changes in fold expression were observed (Supplementary Fig. S2). Fig. 1 View largeDownload slide Numbers of Xoo-, N limitation- and combined stress-responsive miRNAs. (A) Changes in miRNA expression with different treatments. Numbers of up- and down-regulated miRNAs with different treatments are summarized. HN, distilled water/normal N; XN, Xoo/normal N; HL, distilled water/N limitation (HL); XL, Xoo/N limitation. (B) Unique and overlapping rice miRNAs responding to Xoo infection and N limitation. Data represent the number of miRNAs. (C) Expression profile distribution of 63 overlapping miRNAs: 36 up-regulated (a) and 15 down-regulated (b) miRNAs under both single and combined stresses. Nine miRNAs were up-regulated under Xoo infection but down-regulated under N limitation and combined stresses (c), and other expression patterns under either single or combined stresses (d). Fig. 1 View largeDownload slide Numbers of Xoo-, N limitation- and combined stress-responsive miRNAs. (A) Changes in miRNA expression with different treatments. Numbers of up- and down-regulated miRNAs with different treatments are summarized. HN, distilled water/normal N; XN, Xoo/normal N; HL, distilled water/N limitation (HL); XL, Xoo/N limitation. (B) Unique and overlapping rice miRNAs responding to Xoo infection and N limitation. Data represent the number of miRNAs. (C) Expression profile distribution of 63 overlapping miRNAs: 36 up-regulated (a) and 15 down-regulated (b) miRNAs under both single and combined stresses. Nine miRNAs were up-regulated under Xoo infection but down-regulated under N limitation and combined stresses (c), and other expression patterns under either single or combined stresses (d). Functional prediction and classification of overlapping miRNA target genes To reveal the regulatory functions of these potential overlapping miRNAs, their putative targets were predicted using TarScan (Lewis et al. 2005) and miRanda (Enright et al. 2003) (Supplementary Table S2). To analyze their functions and associations with metabolic regulatory networks, these potential target genes were classified into different functional groups by Gene Ontology (GO), based on three ontologies, namely biological process, cellular component and molecular function. These terms were defined using a P-value <0.01 as the cut-off. A total of 259 predicted targets were classified into 16 biological processes (Fig. 2, top). Among them, the N compound metabolic process was the most dominant group with 31 components, followed by the response to stress and stimulus with 19 components each, and then the cell death and defense response with 17 and 16 components, respectively. In addition, many target genes were found to be involved in the amine, the amino acid and other metabolic processes. Based on cellular components (Fig. 2, middle), the cell and the cell part were the largest enriched groups. Based on molecular function (Fig. 2, bottom), the target genes associated with nucleotide binding, ATP binding, nucleoside binding and nucleic acid binding were enriched, along with those involved in kinase activity, transcription regulator activity and other activity-associated groups (Fig. 2, bottom). These observations indicated that these miRNAs target a variety of functions in response to bacterial infection and N limitation in rice. Fig. 2 View largeDownload slide Histograms showing GO analysis of potential overlapping miRNA targets. The number indicates the number of genes in a category. Categorization of overlapping miRNA target genes was performed according to biological process, cellular component and molecular function. The term was defined using a P-value <0.01 as a cut-off. Fig. 2 View largeDownload slide Histograms showing GO analysis of potential overlapping miRNA targets. The number indicates the number of genes in a category. Categorization of overlapping miRNA target genes was performed according to biological process, cellular component and molecular function. The term was defined using a P-value <0.01 as a cut-off. Verification of the overlapping miR169o and target gene The candidate overlapping miR169o is a member of the conserved miR169 family, whose members have been identified to be implicated in not only the response to drought stress in plants (Li et al. 2008, Zhao et al. 2011), but also the response to N starvation stress in Arabidopsis (Zhao et al. 2011). To validate the predicted target genes further, the transcription of miR169o and its predicted target genes was analyzed by qRT-PCR assays under individual and combined stress conditions. As shown in Fig. 3A, miR169o displayed a down-regulated expression pattern in response to Xoo infection, N limitation stress and combined stress, respectively (Fig. 3A), which is consistent with the result of the miRNAs sequence. Only the predicted target genes LOC_Os03g07880 and LOC_Os03g48970, encoding NF-YA1 and NF-YA4, respectively, showed complete inverse expression patterns to miR169o under both individual and combined stresses (Fig. 3A). Other predicted targets, NF-YA2 (LOC_Os03g29760), NF-YA3 (LOC_Os03g44540), NF-YA5 (LOC_Os07g06470), NF-YA6 (LOC_Os07g41720), NF-YA10 (LOC_Os12g42400) and a tyrosine aminotransferase (TRA; LOC_Os02g19970), showed imperfect reverse expression pattern to miR169o in response to individual and combined stress (Supplementary Fig. S3). NF-YA5 displayed remarkable up-regulation in response to Xoo infection but not to LN and combined stress. NF-YA3 and NF-YA10 displayed a certain degree of up-regulation in response to LN and combined stress, but not to Xoo infection. TRA displayed a similar pattern to miR169o in response to N deficiency and combined stress (Supplementary Fig. S3). Fig. 3 View largeDownload slide Validation of the target gene of overlapping miR169o by qRT-PCR and 5' RACE. (A) The expression levels of miR169o and its predicted target genes. Expression levels were measured by qRT-PCR and normalized to U6 and actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. (B) Validation of cleavage sites of miR169o targets. The miRNA (bottom) and its target gene (top) are shown aligned. Matches are indicated with straight lines and arrows show the site of cleavage, with the frequency of validated events in the sequenced products to the total number of events. Fig. 3 View largeDownload slide Validation of the target gene of overlapping miR169o by qRT-PCR and 5' RACE. (A) The expression levels of miR169o and its predicted target genes. Expression levels were measured by qRT-PCR and normalized to U6 and actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. (B) Validation of cleavage sites of miR169o targets. The miRNA (bottom) and its target gene (top) are shown aligned. Matches are indicated with straight lines and arrows show the site of cleavage, with the frequency of validated events in the sequenced products to the total number of events. To test the accuracy of the predicted target NF-YA4 and confirm its cleavage location, 5' rapid amplification of cDNA ends (RACE) was performed. With a frequency of 10/10, RACE sequencing results confirmed the target site of miR169o on NF-YA4 (Fig. 3B). The cleavage site was observed at the 10th and 11th residues of the NF-YA4 mRNA from the 5'-terminus of miR169o (Fig. 3B). miR169o contributes to rice growth under either normal or limiting N conditions miR169 is involved in the adaption to drought stress in Arabidopsis (Li et al. 2008, Zhao et al. 2011). Here, miR169o is shown to be down-regulated in response to Xoo infection, N limitation and the combined stresses in rice. To explore further its biological function, we overexpressed the miR169o primary gene in rice by Agrobacterium-mediated transformation. A 444 bp MIR169o gene sequence (surrounding the miRNA sequence) driven by the ubiquitin promoter was transformed into Nipponbare. Expression levels of miR169o and its targets in wild-type (WT) and overexpressing (OX) lines are analyzed. The results showed that the level of miR169o was much higher in miR169o-OX lines than that in the WT under normal N supply conditions (Fig. 4A). Consistent with this, the predicted targets of miR169, namely NF-YA1, NF-YA4, NF-YA10, NF-YA11 and TRA, were kept at very low transcriptional levels in miR169o-OX lines compared with those in the WT (Fig. 4A). One-month-old miR169o-OX plants under different nitrate supply conditions were analyzed phenotypically (Fig. 4B). The miR169o-OX plants were taller than WT plants under either normal or limiting N conditions (Fig. 4C). Furthermore, the biomass analysis showed that both fresh and dry weights of roots and shoots in miR169o-OX plants are heavier than those in WT plants (Table 2). Compared with those in the WT, total weights in miR169o-OX plants were significantly increased by 29.94% in FW and 33.71% in DW under N limitation conditions, and 21.56% in FW and 28.99% in DW under N-sufficient conditions, respectively (Table 2). These results indicated that miR169o promotes the accumulation of biomass especially under N limitation stress. Table 2 Biomass accumulation in miR169o-OX plantsa NO3− (mM) Weight Plant name Weight of tissue (g ± SD) Root:shoot Total weight (g) Ratio (%)b Root Shoot 0.3 FW WT 0.169 ± 0.007 0.302 ± 0.012 0.560 0.471 ± 0.019 39.98 OX 0.222 ± 0.013 0.390 ± 0.024 0.570 0.612 ± 0.031 42.72 DW WT 0.025 ± 0.001 0.064 ± 0.009 0.394 0.089 ± 0.009 52.37 OX 0.034 ± 0.003 0.085 ± 0.003 0.404 0.119 ± 0.003 54.65 3 FW WT 0.329 ± 0.008 0.849 ± 0.021 0.388 1.178 ± 0.025 – OX 0.411 ± 0.028 1.020 ± 0.015 0.403 1.432 ± 0.034 – DW WT 0.038 ± 0.002 0.131 ± 0.003 0.290 0.169 ± 0.005 – OX 0.054 ± 0.005 0.164 ± 0.005 0.332 0.218 ± 0.008 – NO3− (mM) Weight Plant name Weight of tissue (g ± SD) Root:shoot Total weight (g) Ratio (%)b Root Shoot 0.3 FW WT 0.169 ± 0.007 0.302 ± 0.012 0.560 0.471 ± 0.019 39.98 OX 0.222 ± 0.013 0.390 ± 0.024 0.570 0.612 ± 0.031 42.72 DW WT 0.025 ± 0.001 0.064 ± 0.009 0.394 0.089 ± 0.009 52.37 OX 0.034 ± 0.003 0.085 ± 0.003 0.404 0.119 ± 0.003 54.65 3 FW WT 0.329 ± 0.008 0.849 ± 0.021 0.388 1.178 ± 0.025 – OX 0.411 ± 0.028 1.020 ± 0.015 0.403 1.432 ± 0.034 – DW WT 0.038 ± 0.002 0.131 ± 0.003 0.290 0.169 ± 0.005 – OX 0.054 ± 0.005 0.164 ± 0.005 0.332 0.218 ± 0.008 – aThe data represent the mean value of four different experiments. bThe ratio represents the total weight ratio of plants grown under N limitation conditions to that under normal N conditions. Table 2 Biomass accumulation in miR169o-OX plantsa NO3− (mM) Weight Plant name Weight of tissue (g ± SD) Root:shoot Total weight (g) Ratio (%)b Root Shoot 0.3 FW WT 0.169 ± 0.007 0.302 ± 0.012 0.560 0.471 ± 0.019 39.98 OX 0.222 ± 0.013 0.390 ± 0.024 0.570 0.612 ± 0.031 42.72 DW WT 0.025 ± 0.001 0.064 ± 0.009 0.394 0.089 ± 0.009 52.37 OX 0.034 ± 0.003 0.085 ± 0.003 0.404 0.119 ± 0.003 54.65 3 FW WT 0.329 ± 0.008 0.849 ± 0.021 0.388 1.178 ± 0.025 – OX 0.411 ± 0.028 1.020 ± 0.015 0.403 1.432 ± 0.034 – DW WT 0.038 ± 0.002 0.131 ± 0.003 0.290 0.169 ± 0.005 – OX 0.054 ± 0.005 0.164 ± 0.005 0.332 0.218 ± 0.008 – NO3− (mM) Weight Plant name Weight of tissue (g ± SD) Root:shoot Total weight (g) Ratio (%)b Root Shoot 0.3 FW WT 0.169 ± 0.007 0.302 ± 0.012 0.560 0.471 ± 0.019 39.98 OX 0.222 ± 0.013 0.390 ± 0.024 0.570 0.612 ± 0.031 42.72 DW WT 0.025 ± 0.001 0.064 ± 0.009 0.394 0.089 ± 0.009 52.37 OX 0.034 ± 0.003 0.085 ± 0.003 0.404 0.119 ± 0.003 54.65 3 FW WT 0.329 ± 0.008 0.849 ± 0.021 0.388 1.178 ± 0.025 – OX 0.411 ± 0.028 1.020 ± 0.015 0.403 1.432 ± 0.034 – DW WT 0.038 ± 0.002 0.131 ± 0.003 0.290 0.169 ± 0.005 – OX 0.054 ± 0.005 0.164 ± 0.005 0.332 0.218 ± 0.008 – aThe data represent the mean value of four different experiments. bThe ratio represents the total weight ratio of plants grown under N limitation conditions to that under normal N conditions. Fig. 4 View largeDownload slide miR169o enhances the adaption to limiting nitrogen. (A) miR169o level and targets levels in miR169o-OX plants. Expression levels were measured by qRT-PCR and normalized to U6 and actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. (B). The growth status of miR169o-OX plants under normal N and N limitation conditions. (C) Quantitative analysis of the height of plants grown under normal N and N limitation conditions. The experiment was repeated three times with similar results. Error bars represent the SD (n >15). Asterisks denote a significant difference between transgenic plants and the WT (Student’s t-test, **P < 0.01, *P < 0.05). One-month old seedlings grown in a hydroponic system with optimal or limiting N conditions were photographed and their height was measured. Fig. 4 View largeDownload slide miR169o enhances the adaption to limiting nitrogen. (A) miR169o level and targets levels in miR169o-OX plants. Expression levels were measured by qRT-PCR and normalized to U6 and actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. (B). The growth status of miR169o-OX plants under normal N and N limitation conditions. (C) Quantitative analysis of the height of plants grown under normal N and N limitation conditions. The experiment was repeated three times with similar results. Error bars represent the SD (n >15). Asterisks denote a significant difference between transgenic plants and the WT (Student’s t-test, **P < 0.01, *P < 0.05). One-month old seedlings grown in a hydroponic system with optimal or limiting N conditions were photographed and their height was measured. miR169o enhances nitrate and total amino acid accumulation in roots To investigate whether miR169o-improved plant growth is NO3− dependent, the nitrate content and total amino acid content were measured in different rice tissues. The roots of miR169o-OX plants had a higher nitrate content than those of WT plants under either normal or limiting N conditions (Fig. 5A). In shoots and leaves, there is no significant difference in nitrate content in miR169o-OX and WT plants under normal nitrate supply conditions (Fig. 5B, C). However, under limiting N conditions, the nitrate content in miR169o-OX plants was obviously higher than that in WT plants (Fig. 5B, C). Similarly, total amino acid content in roots was much higher in miR169o-OX plants than that in WT plants under either normal or limiting N supply (Fig. 5D). However, no significant difference was found in shoots and leaves between miR169o-OX and WT plants (Fig. 5E, F). The increased contents of nitrate and total amino acid in miR169o-OX plants suggested that miR169o might enhance nitrate uptake and total amino acid accumulation at least in roots. Fig. 5 View largeDownload slide miR169o increases nitrate and total amino acid under N limitation conditions. The nitrate (A–C) and total amino acid (D–F) content in root, stem and leaf of WT and miR169o-OX plants under N sufficiency and limitation conditions. Plants were grown continuously with 3 or 0.3 mM KNO3. The experiment was repeated three times, independently. Error bars represent the SD (n >8). An asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, *P < 0.05). Fig. 5 View largeDownload slide miR169o increases nitrate and total amino acid under N limitation conditions. The nitrate (A–C) and total amino acid (D–F) content in root, stem and leaf of WT and miR169o-OX plants under N sufficiency and limitation conditions. Plants were grown continuously with 3 or 0.3 mM KNO3. The experiment was repeated three times, independently. Error bars represent the SD (n >8). An asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, *P < 0.05). miR169o regulates NRT1 and NRT2 expression in roots Nitrate is the most important N source for most crops, and nitrate uptake from soil and transport into plants occur mainly through the action of low-affinity NRT1s (nitrate transporter 1 family, NRT1) and high-affinity NRT2s (nitrate transporter 2 family, NRT2) (Tsay et al. 2007). In order to dissect the internal mechanism of miR169o-mediated adaption to N limitation stress, the expression pattern of the NRT1 (OsNRT1.1 and OsNPF2.4) and NRT2 (OsNRT2.1, OsNRT2.2 and OsNAR2.1) families in roots was measured under normal N and limiting N supply, respectively. Compared with the WT, osa-miR169o-OX plants showed an up-regulated OsNRT1.1 and OsNPF2.4 level under both normal N and limiting N supply conditions (Fig. 6A). Under normal N supply conditions, the NRT2 genes OsNRT2.1, OsNRT2.2 and OsNAR2.1 were down-regulated in miR169o-OX plants compared with the WT (Fig. 6B). In contrast, under long-term N limitation stress, OsNRT2.1 was induced up to 4-fold in miR169o-OX plants, while OsNRT2.2 and OsNAR2.1 were induced up to 27- and 57-fold, respectively, in miR169o-OX plants (Fig. 6B). These data suggested that miR169o contributes to the expression of NRT1 regardless of N conditions. However, miR169o represses the NRT2 transcript under the normal N condition, but induces it under long-term N limitation stress. Fig. 6 View largeDownload slide Expression of NRT-related genes in root of miR169o-OX plants under normal N and N limitation condition. OsNRT1.1 and OsNPF2.4 represent the NRT1 family (A), while OsNRT2.1, OsNRT2.2 and OsNAR2.1 represent the NRT2 family (B). Expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. Fig. 6 View largeDownload slide Expression of NRT-related genes in root of miR169o-OX plants under normal N and N limitation condition. OsNRT1.1 and OsNPF2.4 represent the NRT1 family (A), while OsNRT2.1, OsNRT2.2 and OsNAR2.1 represent the NRT2 family (B). Expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. miR169o negatively regulates resistance to bacterial blight in rice To investigate the function of miR169o in the defense response, lesion lengths and bacterial populations in miR169o-OX and WT plants were measured at 14 d after inoculation with Xoo. The lengths of lesions caused by Xoo infection on miR169o-OX were much greater than those on WT plants under both normal and limiting N supply conditions (Fig. 7A). Bacterial populations in miR169o-OX plants at 14 d after inoculation with Xoo were significant higher than in the WT under both normal and limiting N supply conditions (Fig. 7B). Consistently, the transcriptional levels of pathogen defense genes, namely PR1b, PR10a, PR10b and PAL, were much lower in the miR169o-OX plants than in the WT under normal N conditions (Fig. 7C). Although defense genes were induced by N limitation stress, the levels of defense genes in miR169o-OX were still much lower than those in the WT under N limitation conditions (Fig. 7C). These results indicated that miR169o negatively regulates the resistance against Xoo in rice. Fig. 7 View largeDownload slide miR169o enhances the susceptibility to bacterial blight in rice. (A) Length of the lesion caused by Xoo infection on plants under normal N and low N conditions, respectively. Lesion lengths were measured 14 d after inoculation with Xoo. A double asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, **P < 0.01, n >15). (B) Bacterial growth on WT and miR169o-OX plants. An asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, *P < 0.05, n >6). (C) Expression levels of PR1b, PR10a, PR10b and PAL genes in WT and miR169o-OX plants. Gene expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between transgenic plants and the WT under normal N conditions (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. Fig. 7 View largeDownload slide miR169o enhances the susceptibility to bacterial blight in rice. (A) Length of the lesion caused by Xoo infection on plants under normal N and low N conditions, respectively. Lesion lengths were measured 14 d after inoculation with Xoo. A double asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, **P < 0.01, n >15). (B) Bacterial growth on WT and miR169o-OX plants. An asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, *P < 0.05, n >6). (C) Expression levels of PR1b, PR10a, PR10b and PAL genes in WT and miR169o-OX plants. Gene expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between transgenic plants and the WT under normal N conditions (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. miR169o impedes Xoo-mediated NRT transcription Osa-miR169o negatively regulates disease resistance to bacterial blight on rice caused by Xoo infection (Fig. 7) and enhances adaption to N deficiency stress (Fig. 4; Table 2). Transcriptional levels of NRT1 and NRT2 were further tested in miR169o-OX plants after inoculation with Xoo. The results showed that OsNRT1.1 and OsNRT1.2 were induced, but OsNRT2.1 was reduced by bacterial infection in the WT (Fig. 8). However, in miR169o-OX plants, OsNRT1.2 was reduced markedly and OsNRT2.1 was induced at 24 h after inoculation with Xoo (Fig. 8). The opposite expression pattern of NRT1 and NRT2 between WT and miR169o-OX plants after Xoo infection indicates that miR169o impedes the expression of NRT genes modulated by Xoo infection. Fig. 8 View largeDownload slide NRT levels in miR169o-OX plants after inoculation with Xoo. Expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between 0 h and 24 h after inoculation with Xoo (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. Fig. 8 View largeDownload slide NRT levels in miR169o-OX plants after inoculation with Xoo. Expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between 0 h and 24 h after inoculation with Xoo (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. NF-YA genes promote the transcription of PR genes and NRT genes To identify whether target genes contribute to osa-miR169o-regulated disease resistance and NUE, NF-YA genes were transiently expressed in rice protoplasts and the transcriptional levels of PR genes and NRT genes were measured. Transcription assay showed that NF-YA genes were maintained at a considerable high level afer transient expression in rice protoplasts (Fig. 9A). Compared with transient expression of empty vector, transient expression of the NF-YA genes NF-YA4, NF-YA10 and NF-YA11 resulted in the significant up-regulation of PR genes PR10a, PR10b and PAL (Fig. 9B). Meanwhile, NRT2 family members OsNRT2.1, OsNRT2.2 and OsNAR2.1 were significantly induced after transient expression of NF-YA genes, respectively, while NRT1 family members including OsNRT1.1 and OsNPF2.4 were slightly reduced (Fig. 9C). Fig. 9 View largeDownload slide NF-YA genes affect the transcriptional levels of PR genes and NRT genes. (A) Transcriptional levels of NF-YA genes in rice protoplasts. (B) Transcriptional levels of PR genes in rice protoplasts after transient expression of NF-YAs. (C) Transcriptional levels of NRT genes in rice protoplasts after transient expression of NF-YA genes. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between NF-YA-overexpressing plants and empty vector (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. Fig. 9 View largeDownload slide NF-YA genes affect the transcriptional levels of PR genes and NRT genes. (A) Transcriptional levels of NF-YA genes in rice protoplasts. (B) Transcriptional levels of PR genes in rice protoplasts after transient expression of NF-YAs. (C) Transcriptional levels of NRT genes in rice protoplasts after transient expression of NF-YA genes. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between NF-YA-overexpressing plants and empty vector (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. Discussion miR169 is involved in the response to N starvation and bacterial infection When grown under low N conditions (LN), rice that is normally sensitive to BB is more resistant than when grown on higher N (Yu et al. 2015). However, the underlying regulatory mechanism of the LN-mediated disease resistance is still unclear. One possible mode of cross-regulation is through the action of miRNAs. MiRNAs involved in response to pathogen infection (Baldrich et al. 2015, Feng et al. 2015) or N limitation stress (Zhao et al. 2011, Zhao et al. 2012) have been reported. However, little was known about the function and regulation of overlapping miRNAs in response to Xoo infection and N-limiting conditions or from combining these stress conditions. A total of 63 overlapping miRNAs regulated by Xoo infection, N deficiency stress and combined stress were identified based on deep RNA sequencing and stem–loop qRT-PCR. Among them, 10 miR169 isoforms were reduced by Xoo infection, N limiting and combined stress. Only four isoforms, i.e. miR169b/c/e/i, were responsive to limiting N stress specifically. No Xoo-responsive specific miR169 isoform was found in our results (Supplementary Table S2). This implied that the conserved miR169 may play significant roles in the cross-talk in response to Xoo infection and N-limiting stress. Osa-miR169o showed the greatest down-regulation in response to different stresses (Supplementary Table S2). To characterize further the biological function of osa-miR169o on NUE and resistance to Xoo, the osa-miR169o primary gene driven by the constitutive ubiquitin promoter was transformed into the susceptible Nipponbare variety, and a series of assays were carried out on miR169o-OX plants. miR169o enhances NUE in rice As a highly conserved miRNA family, miR169 is involved in the developmental regulation and adaption to various environmental stresses. In Arabidopsis, miR169a was down-regulated by drought stress through an ABA-dependent pathway. Overexpression of ath-miR169a increased leaf water loss and sensitivity to drought stress through repressing the crucial target NF-YA5 (Li et al. 2008, Zhang et al. 2011). In contrast, overexpression of sly-miR169c led to reduced stomatal opening, lowered leaf water loss and enhanced drought tolerance in tomato (Zhang et al. 2011). The opposite effect of miR169 on tolerance to drought stress indicated that miR169 plays diverse roles in different plants. In Arabidopsis, miR169a in both roots and shoots was down-regulated by N starvation, and overexpression of ath-miR169a resulted in less N accumulation and enhanced the sensitivity to N starvation stress (Zhao et al. 2011). Here, our results showed that osa-miR169o, similarly to ath-miR169a, was down-regulated in response to N-limiting conditions. However, inconsistent with overexpression of ath-miR169a, overexpression of osa-miR169o in rice promoted plant growth and increased biomass accumulation under either normal or limiting N conditions (Fig. 4B, C;Table 2). The nitrate and total amino acid contents in root of miR169o-OX plants were also much higher than those in the WT (Fig. 5). Nitrate uptake from soil and transport in plants are mainly done by low-affinity NRT1s and high-affinity NRT2s (Tsay et al. 2007). NRT1.1/CHL1 is a nitrate sensor and a dual affinity member in Arabidopsis (Liu et al. 1999, Ho et al. 2009). Its affinity activity is switched on by a Thr101 phosphorylation-controlled dimerization in Arabidopsis (Sun et al. 2014). OsNPF2.4 is an NPF (nitrate transporter 1/peptide transporter family, formerly NRT1/PTR) member with low affinity. Overexpression of OsNPF2.4 increased nitrate acquisition in roots and upward transfer from root to shoot. In comntrast, disruption of OsNPF2.4 decreased nitrate uptake and transfer (Xia et al. 2015). As for the NRT2 family with high nitrate affinity, there are at least five genes belonging to the NRT2 family in the rice genome (Feng et al. 2011). Among those, OsNRT2.1 and OsNRT2.2 are responsible for nitrate uptake and transfer. The molecular partner OsNAR2.1 interacts with OsNRT2.1 and OsNRT2.2 and is required for the function of OsNRT2.1 and OsNRT2.2 (Yan et al. 2011). Transcriptional assay results showed that overexpression of osa-miR169o induced the OsNRT1 transcript and repressed the OsNRT2 transcript in rice under normal N conditions, while it induced both OsNRT1 and OsNRT2 transcripts under N-limiting conditions (Fig. 6). Under N-sufficient conditions, OsNRT1, a low-affinity nitrate transporter, plays the predominant role while OsNRT2 plays a negligible role in N uptake. In response to N deficiency stress, osa-miR169o induced the high-affinity nitrate transporter NRT2 up to >10-fold and low-affinity NRT1 up to almost 10-fold. Therefore, osa-miR169o may positively regulate NUE and increase nitrate content through controlling NRT1 and NRT2 mRNA levels under both N-sufficient and -deficient conditions in rice. miR169 is involved in plant immunity to Xoo infection miRNAs play important roles in plant immunity. Recently, miR169a has been reported as a negative regulator of the resistance against the rice blast pathogen M. oryzae in rice (Li et al. 2017). Inconsistent with the accumulation of miR169 upon M. oryzae infection, 10 miR169 isoforms, namely miR169o/n and miR169f.1/g/h/i/j/k/l/m, were down-regulated in response to Xoo infection (Supplementary Table S2). Intriguingly, all 10 Xoo-responsive miR169 isoforms can also be reduced by N-limiting stress and the combined stress. No Xoo-responsive specific miR169 isoform was found in our results. Constitutive overexpression of miR169o plants showed a longer lesion length, higher bacterial population and lower transcript levels of defense genes such as PR10b, PR1b, PR10a and PAL than control plants under both N-sufficient and -deficient conditions (Fig. 7). This result indicates that miR169o negatively regulates the resistance against Xoo in rice. However, considering the different expression pattern in response to M. oryzae and Xoo infection, miR169 isoforms are predominantly modulated by the pathogen or host, respectively, in response to M. oryzae or Xoo infection. During M. oryzae infection, the pathogen induces the biogenesis of miR169 and facilitates the successful infection in susceptible rice species. This modulation was weakened in resistant rice lines (Li et al. 2017). When suffering from Xoo infection, rice actively reduced the production of miR169 to weaken miR169-mediated susceptibility to Xoo. Therefore, miR169 could be regulated by the pathogen and host, respectively, in response to fungal and bacterial infection. NF-YA genes contribute to plant immunity and NUE in rice miR169 negatively regulates the tolerance to drought stress by inhibiting the NF-YA5 transcription and post-transcription level (Li et al. 2008). miR169a and miR169i from 18 miR169 isoforms have been reported to regulate tolerance to drought stress through targeting NF-YA5 mRNA in Arabidopsis (Du et al. 2017). In addition, miR169 also regulates plant flowering time through targeting NF-YA in Arabidopsis. However, only palnts overexpressing NF-YA2 and NF-YA6 consistently flowered earlier than the WT (Siriwardana et al. 2016), while overexpression of NF-YA1 and NF-YA4 led to later flowering in Arabidopsis (Wenkel et al. 2006). The above showed that miRNA isoforms display functional differences and target specific genes in response to different stresses or biological functions. Although all test-predicted targets were down-regulated in osa-miR169o-OX lines compared with control plants (Fig. 4A), only NF-YA1 and NF-YA4 but not six other predicted target genes displayed a perfect reverse expression pattern to osa-miR169o in response to Xoo infection, N deficiency and combined stress (Fig. 3A;Supplementary Fig. S3). After transient expression of NF-YA genes in the rice protoplast, the PR genes PR10a, PR10b and PAL, and the NRT2 genes OsNRT2.1, OsNRT2.2 and OsNAR2.1 were significantly induced, while the NRT1 genes OsNRT1.1 and OsNPF2.4 were reduced (Fig. 9). This indicates that NF-YA genes must be involved in the regulation by osa-miR169o of plant immunity and NUE in rice. Which NF-YA is dominant in response to individual and combined stress still requires further detailed study in the future. The trade-off between enhanced growth with added N vs. the sensitivity to pathogens The highly conserved miR169 family displays diverse regulatory mechanism in plants on adaption to various environmental stresses including biotic and abiotic stress. Osa-miR169o is involved in the cross-talk between response to Xoo infection and N-limiting stress. There is clearly a genetic linkage between the response to N limitation stress and pathogen resistance, with the miR169o overexpression lines showing both a higher level of NUE and a higher sensitivity to BB. It will be of interest to see if the overexpression of miR169o also affects pathogen resistance in a resistant variety. Li et al. (2017) reported that osa-miR169b/c displayed different expression patterns in susceptible and resistant varieties in response to M. oryzae infection. Osa-miR169b/c only responds to N-limiting stress in our study system (Supplementary Table S2). Therefore, it would be very worthwhile to overexpress osa-miR169b/c in a resistant variety which may show enhanced growth without the downside of being more sensitive to the pathogen. Further, there are a large number of other miRNAs which respond to both N limitation and pathogen stress at the transcriptional level, and it will be of interest to see if any of these have a role in determining plant response to these stress conditions. Materials and methods   Plant materials and stress treatments Seeds of rice were germinated for 2 d in turface. Individual germinated seeds were planted in small pots containing rockwool and covered with turface, and the pots were placed in a tray to grow for 1 week. These plants were then transferred to the hydroponic tank that contains 30 liters of Hoagland solution (Bi et al. 2009), with each tank containing 24 pots. The nutrient solution pH was maintained at 5.5–6 using 50% phosphoric acid, by measuring the pH every 3 d. The growth conditions are 16 h light (29°C) and 8 h dark (23°C). The N stress treatments involved a normal nitrate concentration (3 mM KNO3) and a nitrate limitation condition (0.3 mM KNO3) (Coneva et al. 2014, Yu et al. 2015). For the biotic stress treatments, Xoo cultured cells (OD600=0.8) were inoculated on 1-month-old plants by the scissors-clipping method (Song et al. 1995), and ddH2O was inoculated as the negative control. Rice leaves were harvested 6 h post-inoculation for each sample, which was pooled from five plants, frozen in liquid N and stored at –80°C. Construction of miRNA libraries for high-throughput sequencing Total RNA samples were extracted from rice leaves treated with Xoo and normal N (XN), Xoo and N limitation (XL), ddH2O and N limitation (HL), and ddH2O and normal N (HN) as control using Trizol (Invitrogen). miRNA libraries were constructed as reported (Wang et al. 2011). For each sample, small RNAs of 18–30 nt were separated by electrophoresis in a 15% TBE-urea denaturing polyacrylamide gel, and then 5' and 3' adaptors were added with T4 RNA ligase (TAKARA). cDNA was synthesized using Superscript II reverse transcriptase (Invitrogen), and then enriched through PCR. The purified DNA was sequenced on a Solexa sequencer (Illumina). Analysis of small RNA sequencing data The raw sequencing data were deposited in NCBI’s Sequence Read Archive (SRA) and are accessible through the SRA series accession number PRJNA238154. The accession numbers of HN, XN, HL and XL libraries were SRR1257322, SRR1257323, SRR1257324 and SRR1257325, respectively (http://www.ncbi.nlm.nih.gov/bioproject/? term=PRJNA238154). Raw data from Solexa sequencing were cleaned by removing the low quality tags and contaminants including null adaptors and improper sizes (<18 bp), and unique small RNAs were acquired by removing adaptor and primer sequences of clean data using miRExpress (Wang et al. 2009). Thereafter the reads were mapped to the rice genome sequence (Ensemble) downloaded from the website ftp://ftp.ensemblgenomes.org/pub/plants/release-16/fasta/oryza_sativa/dna/ using Bowtie (Flicek et al. 2012), and then aligned with known miRNAs from miRBase 20 (ftp://mirbase.org/pub/mirbase/20/) (Griffiths-Jones et al. 2008). Prediction and functional analysis of putative target genes of miRNAs Target predictions of miRNAs were performed by both TarScan (Lewis et al. 2005) and maRanda (Enright et al. 2003). The intersections of two kinds of predicted results were taken as putative target genes for subsequent analysis. To reveal the functions of the predicted target genes of the overlapping miRNAs, 259 potential target genes were mapped to GO terms in the database (http://www.geneontology.org/), and gene numbers were calculated for each term (using P < 0.01 as the cut-off). Examination of mature miRNAs and their target genes by qRT-PCR Total RNAs were extracted from rice tissues with TRIzol reagent (Invitrogen). Mature miRNAs were reverse transcribed by stem–loop reverse transcriptase primers, and the reverse transcription products were amplified using a universal reverse primer and a miRNA-specific forward primer as described (Chen et al. 2005). The specific primers of mature miRNAs and their predicted target genes were designed and are listed in Supplementary Tables S3 and S4. The rice U6 and actin genes were selected as the reference for miRNAs and genes in the qRT-PCR assay. qRT-PCR analysis was carried out using SYBR Green detection reagents (Quanta Biosciences) in Applied Biosystem’s 7500 Sequence Detection System (Applied Biosystems), and a 20 µl PCR contained about 100 ng of cDNA. All components in the reaction were mixed gently and incubated at 95°C for 3 min, and then 40 cycles at 95°C for 10 s, 60°C for 30 s, followed by a dissociation stage. All samples were performed in three biological replicates and triplicate PCR. The relative expression ratio was calculated using the 2−ΔΔCt method. 5' RACE analysis The identification of miRNA cleavage sites on their target genes involved RNA ligation-mediated 5' RACE (RLM-5' RACE). Total RNA (5 µg) was obtained as described above. According to the protocol of the GeneRacer kit (Invitrogen), total RNAs were directly ligated to the 5' RACE RNA adaptor, and then the ligated RNAs were reverse transcribed by the GeneRace Oligo(dT) primer. The GeneRacer™ 5' primer and outer gene-specific reverse primers were used for the first round of PCR, and GeneRacer™ 5' nested primer and inner gene-specific reverse primers were used for nested PCR. PCR products were gel purified, cloned (TAKARA), and 10 independent clones from each reaction were sequenced. The sequences of primers are shown in Supplementary Table S5. Constructions for transgenic plants or transient expression in rice protoplast The 444 bp osa-miR169o precursor sequence was amplified using the specific primers forward 5'-CAACCACCTCTGCATCTTCTACTTCC-3' and reverse 5'-ATTACGCCCCAGAGAGCCAAAAAC-3'. The PCR product was inserted into pCXUN digested by XcmI (Chen et al. 2009). The construct was transformed into rice by the Agrobacterium-mediated method. The positive transgenic plants were screened by hygromycin resistance and miR169o level. As described above, the transgenic and WT plants were grown in Hoagland solution under normal or low N conditions. To express NF-YAs transiently in rice protoplasts, corresponding NF-YA fragments cleaved by SacI and SalI were inserted into pUC-cLUC (Chen et al. 2008) cleaved by the same restriction enzymes. The primers using for amplifing NF-YA fragments are listed in Supplementary Table S4. Analysis of plant biomass The biomass was detected as described previously (Yu et al. 2015). As shown above, 1-month-old transgenic and WT rice plants grown under normal or low nitrate conditions were harvested. The fresh and the dry weights were measured before or after shoots and roots were dried at 50°C for 7 d, respectively. Five plants were analyzed in an experiment, and each experiment was repeated four times. Nitrate and total amino acid concentration measurements Nitrate and total amino acid concentrations were measured as described previously (Moore and Stein 1954, Yan et al. 2014). Briefly, the roots, stems and leaves of 1-month-old transgenic and WT rice plants grown in two different nitrate conditions were collected and weighed. Then the samples were ground to a powder in liquid N, resuspended in 10 ml of deionized water and incubated at 45°C for 1 h. The supernatant was obtained after centrifugation at 5,000×g for 15 min. For measurement of the nitrate concentration, 100 µl of supernatant and 400 µl of 5% (w/v) salicylic acid (dissolved in concentrated H2SO4) were mixed gently. After 20 min at room temperature, 9.5 ml of 2 N NaOH was added slowly to the mixture. Then 200 µl of mixture was taken to determine the nitrate concentration at a wavelength of 410 nm. For measurement of total amino acids, the supernatant was mixed with 0.3% ninhydrin solution (dissolved in 95% ethanol) and acetic acid (1:3:1, pH 5.4) in a 2 ml tube. Then, the tubes were boiled for 20 min. An equal amount of 60% ethanol was added after cooling to room temperature, and the total amino acid concentration was determined at a wavelength of 570 nm. These experiments were repeated at least three times. Lesion length and bacterial growth assay PXO99A, a virulent Xoo strain on Nipponbare, was grown for 72 h at 28°C in M210 medium (0.8% casein enzymatic hydrolysate, 0.5% sucrose, 0.5% yeast extract, 0.3% K2HPO4, 0.03% MgSO4·7H2O, pH 7.0). The cells were collected by centrifugation and resuspended in ddH2O up to OD600 = 0.8. One-month-old seedlings were inoculated with Xoo by the leaf-clipping method. Lesion lengths were recorded at 14 d after inoculation. For the bacterial growth assay, three inoculated leaves were ground in ddH2O with a mortar and pestle and were considered as one sample. The mixture was then diluted to 103, 104, and 105, and spread 100 mL onto PSA plates (1% tryptone, 1% Sucrose, 0.1% L-glutamic acid, 1.5% agar, pH7.0), respectively. The colonies of bacteria were counted at 72 h after incubation at 28°C. The experiment was repeated at least three times. Rice protoplast transient expression and RNA extraction Rice protoplasts were isolated from 10-day-old seedlings of the Nipponbare variety growing on Murashige and Skoog (MS) medium. Protoplast preparation and transfection were carried out by following described procedures (Chen et al. 2006). After transfection, protoplasts were incubated in light for about 16 h at room temperature. For RNA extraction from protoplasts, rice protoplasts were collected by centrifugation and resuspended with 300 µL of TRIzol reagent (Invitrogen). Then the standard protocol of RNA extraction from plant samples was followed. Supplementary Data Supplementary data are available at PCP online. Funding This study was supported by the National Key Research and Development Program of China [ No. 2017YFD0200900]; the National GMO New Variety Breeding Program of China [No. 2016ZX08001-002]; the National Natural Science Foundation of China [No. 30970310]; the Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences; and the China Postdoctoral Science Foundation [No. 2017T100120]. Acknowledgments We sincerely thank Dr. Guo-Liang Wang for supplying the binary vector pCXUN. Disclosures The authors have no conflicts of interest to declare. References Baldrich P. , Campo S. , Wu M.T. , Liu T.T. , Hsing Y.I. , San Segundo B. ( 2015 ) MicroRNA-mediated regulation of gene expression in the response of rice plants to fungal elicitors . RNA Biol . 12 : 847 – 863 . Google Scholar CrossRef Search ADS PubMed Bartel D.P. 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Google Scholar CrossRef Search ADS PubMed Abbreviations Abbreviations AOP2 alkenyl hydroxalkyl producing 2 BB bacterial blight GO Gene Ontology HL treatment with ddH2O and N deficiency HN treatment with ddH2O and normal miRNA microRNA N nitrogen NF-YA nuclear factor-Y subunit A NLA nitrogen-limiting adaption NPF nitrate transporter 1/peptide transporter family (formerly NRT1/PTR) NRT nitrate transporter family NUE nitrogen use efficiency Pst Pseudomonas syringae pv. tomato qRT-PCR quantitative real-time PCR RLM-5' RACE RNA ligation-mediated 5' rapid amplification of cDNA ends TRA tyrosine aminotransferase WT wild type XL treatment with Xoo inoculation and N deficiency XN treatment with Xoo inoculation and normal N Xoo Xanthomonas oryzae pv. oryzae © The Author(s) 2018. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Plant and Cell Physiology Oxford University Press

Overexpression of miR169o, an Overlapping MicroRNA in Response to Both Nitrogen Limitation and Bacterial Infection, Promotes Nitrogen Use Efficiency and Susceptibility to Bacterial Blight in Rice

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com
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0032-0781
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1471-9053
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10.1093/pcp/pcy060
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Abstract

Abstract Limiting nitrogen (N) supply contributes to improved resistance to bacterial blight (BB) caused by Xanthomonas oryzae pv. oryzae (Xoo) in susceptible rice (Oryza sativa). To understand the regulatory roles of microRNAs (miRNAs) in this phenomenon, 63 differentially expressed overlapping miRNAs in response to Xoo infection and N limitation stress in rice were identified through deep RNA sequencing and stem–loop quantitative real-time PCR. Among these, miR169o was further assessed as a typical overlapping miRNA through the overexpression of the miR169o primary gene. Osa-miR169o-OX plants were taller, and had more biomass accumulation with significantly increased nitrate and total amino acid contents in roots than the wild type (WT). Transcript level assays showed that under different N supply conditions, miR169o oppositely regulated NRT2, and this is reduced under normal N supply conditions but remarkably induced under N-limiting stress. On the other hand, osa-miR169o-OX plants also displayed increased disease lesion lengths and reduced transcriptional levels of defense gene (PR1b, PR10a, PR10b and PAL) compared with the WT after inoculation with Xoo. In addition, miR169o impeded Xoo-mediated NRT transcription. Therefore, the overlapping miR169o contributes to increase N use efficiency and negatively regulates the resistance to BB in rice. Consistently, transient expression of NF-YA genes in rice protoplasts promoted the transcripts of PR genes and NRT2 genes, while it reduced the transcripts of NRT1 genes. Our results provide novel and additional insights into the co ordinated regulatory mechanisms of cross-talk between Xoo infection and N deficiency responses in rice. Introduction Nitrogen (N) is an essential mineral nutrient for normal plant growth, and the use of N fertilizers has led to dramatically increased yields in recent decades (Tilman et al. 2002). However, excessive N fertilizer usage has led to considerable environmental problems which seriously threaten global ecosystems (Nosengo 2003, Giles 2005). The ideal way to decrease N application rates while maintaining yields is to improve N use efficiency (NUE) in crops (Bi et al. 2009). In addition to the ecological harm due to use of excessive N fertilizer, there is also a link between the level of N availability and disease resistance, with the application of high N concentrations being shown to promote plant susceptibility to disease. For example, tomato plants were more susceptible to Pseudomonas syringae pv. tomato (Pst) infection with increasing N concentrations (Hoffland et al. 2000), and fungal blast disease caused by Magnaporthe grisea became more severe with increasing N application in rice (Oryza sativa) (Mukherjee et al. 2005). Bacterial blight (BB) of rice caused by Xanthomonas oryzae pv. oryzae (Xoo) is one of the most important bacterial diseases in the world and can even cause up to a 70% yield loss (http://www.knowledgebank.irri.org/decision-tools/rice-doctor/rice-doctor-fact-sheets/item/bacterial-blight). Moreover, the transcriptomic response to Xoo infection showed a large overlap among the responses to drought, salt, cold and heat stress, based on the analysis of nearly 100 microarrays in rice (Narsai et al. 2013). Our previous work demonstrated that rice plants grown under an N limitation condition had a reduced susceptibility to bacterial blight caused by Xoo compared with those grown under normal N supply (Yu et al. 2015). Subsequent genome-wide transcriptional analysis discovered 248 overlapping genes that responded to both Xoo infection and N limitation stress (Yu et al. 2015). However, the intrinsic regulatory mechanisms controlling these genes are still unclear. MicroRNAs (miRNAs) are a highly conserved class of small non-coding RNAs that cause cleavage or translational repression of their target mRNAs, and their roles in gene regulation are essential for normal growth and development (Reinhart et al. 2002, Bartel 2004). With the development of deep sequencing technology, a large number of plant miRNAs responsive to biotic and abiotic stresses have been identified and characterized. For instance, 25 conserved miRNA families and 15 novel miRNAs responding to the diazotrophic bacterium Herbaspirillum seropedicae were identified in maize (Thiebaut et al. 2014). N deficiency-responsive miRNAs in Arabidopsis (Liang et al. 2012) and maize (Zhao et al. 2012), phosphate deficiency-responsive miRNAs in soybean (Xu et al. 2013) and Rice stripe virus-responsive miRNAs in rice (Guo et al. 2012) were identified through deep sequencing. Quantitative real-time PCR (qRT-PCR) validation of several miRNA profiles under drought and rust infection stress showed that these miRNAs were responsive to either stress in soybeans (Kulcheski et al. 2011). Recently, miRNAs involved in the uptake, assimilation and translocation of nutrients in plants have also been reported. Well-studied miR167 and miR393 have been reported to participate in the regulation of nitrate signaling in root growth in soybean and Arabidopsis, respectively (Vidal et al. 2010, Wang et al. 2015). Also Pi deprivation-induced miR827 post-transcriptionally repressed its target gene NITROGEN LIMITATION ADAPTATION (NLA) and affected the adaption to N-limiting stress in Arabidopsis (Peng et al. 2007, Kant et al. 2011). In addition, overexpression of miR444a improved nitrate accumulation and enhanced the expression of nitrate transporter genes under high nitrate concentration conditions in rice (Yan et al. 2014). Ath-miR5090, a new miRNA from the complementary transcript of the miR826 gene, is induced by N starvation. The transcript level of AOP2 (alkenyl hydroxalkyl producing2, AOP2) is negatively correlated with miR826 and miR5090 under N starvation. Overexpression of miR5090 in Arabidopsis enhanced the tolerance to N starvation, including high biomass, more lateral roots, increased Chl and up-regulated N starvation-responsive genes (He et al. 2014). These observations clearly show that miRNAs play significant roles in adaption to biotic and abiotic stresses in plants. The miR169 family is one of the largest conserved miRNA families in Oryza sativa and is encoded by 18 members (http://www.mirbase.org/). Some of these members have been annotated with specific functions in previous studies. For example, miR169a and c were down-regulated by drought stress, while miR169a, b, d and h were up-regulated at low temperature in Arabidopsis (Li et al. 2008, Lee et al. 2010). In addition, the expression of miR169a and b was suppressed by N deficiency in maize (Zhao et al. 2011). The main predicted targets of miR169 encode subunit A of nuclear factor Y (NF-YA), which has been linked to development and response to abiotic stresses in plants (Rhoades et al. 2002, Combier et al. 2006, Nelson et al. 2007, Liu and Howell 2010). Overexpression of miR169 in Arabidopsis changed flowering time and root architecture by repressing the AtNF-YA2 transcription factor (Sorin et al. 2014, Xu et al. 2014). Osa-miR169g and osa-miR169n/o were up-regulated by high salinity, and selectively cleaved NF-YA8 (LOC_Os03g29760) in response to high salinity stress (Zhao et al. 2009). However, the role of miR169 and its target genes in response to biotic stress have rarely been reported. Here, 63 potential overlapping miRNAs in response to both Xoo infection and N limitation stress were identified by deep sequencing technology and qRT-PCR. Moreover, genetic analysis showed that overexpression of overlapping osa-miR169o increased the susceptibility to bacterial blight caused by Xoo infection and enhanced NUE in rice. Therefore, the results provide additional insights into dissection of the complex and diverse regulatory mechanisms in response to various environmental stress. Results miRNA sequencing in rice under Xoo infection and N limitation conditions In our previous work, rice plants showed less susceptibility to bacterial BB by Xoo under N limitation conditions, and some overlapping genes were found to be regulated by both Xoo infection and N limitation (Yu et al. 2015). Transcriptional levels of disease resistance-related and nitrate transporter-related genes in response to Xoo infection, N limiting and combined stress were measured. The results showed that resistance-related genes such as PR1b, PR10a, PR10b and PAL (Supplementary Fig. S1A), and nitrate transporter genes such as OsNPF2.4, OsNRT2.1 and OsNRT2.2 (Supplementary Fig. S1B) were up-regulated in response to individual and combined stress, respectively. In view of the significant regulatory roles of miRNAs in response to various biotic and abiotic stresses, we hypothesized that miRNAs may be involved in the regulatory response to Xoo infection and N limitation stress. To test this hypothesis, four RNA libraries were constructed from rice leaves with four treatments [distilled water/normal N (HN), Xoo/normal N (XN), distilled water/limiting N (HL) and Xoo/limiting N (XL)] and sequenced using Solexa high-throughput sequencing technology. About 22.7, 18.1, 19.3 and 16.7 million raw reads were generated for the HN, XN, HL and XL libraries, respectively, with 3.57, 2.39, 2.40 and 2.17 million unique miRNA reads cleaned and mapped to the rice genome (Table 1). After alignment with the 592 known miRNAs in 336 families in rice from miRBase 20 (http://www.mirbase.org/) (Griffiths-Jones et al. 2006, Griffiths-Jones et al. 2008, Kozomara and Griffiths-Jones 2011), 504, 474, 489 and 459 unique miRNAs were identified from these sequenced libraries, respectively (Table 1). Nomalized reads of tested miRNAs in HN, XN, HL and XL libraries are listed in Supplementary Table S1. Table 1 Summary of sequencing data Sample Raw reads Clean reads >17 nt Mapped reads (%) Unique miRNA reads Mapped unique miRNA reads (%) Oas miRNA number HN 22,662,024 22,484,805 15,522,796 13,253,015 (85.38) 3,570,263 2,588,945 (72.51) 504 XN 18,071,689 17,941,119 11,966,528 9,799,043 (81.89) 2,385,370 1,588,041 (66.57) 474 HL 19,319,548 19,180,255 12,214,690 10,279,782 (84.16) 2,396,089 1,648,137 (68.78) 489 XL 16,727,349 16,598,675 11,105,747 9,209,403 (82.92) 2,171,498 1,455,981 (67.05) 459 Sample Raw reads Clean reads >17 nt Mapped reads (%) Unique miRNA reads Mapped unique miRNA reads (%) Oas miRNA number HN 22,662,024 22,484,805 15,522,796 13,253,015 (85.38) 3,570,263 2,588,945 (72.51) 504 XN 18,071,689 17,941,119 11,966,528 9,799,043 (81.89) 2,385,370 1,588,041 (66.57) 474 HL 19,319,548 19,180,255 12,214,690 10,279,782 (84.16) 2,396,089 1,648,137 (68.78) 489 XL 16,727,349 16,598,675 11,105,747 9,209,403 (82.92) 2,171,498 1,455,981 (67.05) 459 HN, distilled water/normal N; XN, Xoo/normal N; HL, distilled water/N limitation; XL, Xoo/N limitation. Table 1 Summary of sequencing data Sample Raw reads Clean reads >17 nt Mapped reads (%) Unique miRNA reads Mapped unique miRNA reads (%) Oas miRNA number HN 22,662,024 22,484,805 15,522,796 13,253,015 (85.38) 3,570,263 2,588,945 (72.51) 504 XN 18,071,689 17,941,119 11,966,528 9,799,043 (81.89) 2,385,370 1,588,041 (66.57) 474 HL 19,319,548 19,180,255 12,214,690 10,279,782 (84.16) 2,396,089 1,648,137 (68.78) 489 XL 16,727,349 16,598,675 11,105,747 9,209,403 (82.92) 2,171,498 1,455,981 (67.05) 459 Sample Raw reads Clean reads >17 nt Mapped reads (%) Unique miRNA reads Mapped unique miRNA reads (%) Oas miRNA number HN 22,662,024 22,484,805 15,522,796 13,253,015 (85.38) 3,570,263 2,588,945 (72.51) 504 XN 18,071,689 17,941,119 11,966,528 9,799,043 (81.89) 2,385,370 1,588,041 (66.57) 474 HL 19,319,548 19,180,255 12,214,690 10,279,782 (84.16) 2,396,089 1,648,137 (68.78) 489 XL 16,727,349 16,598,675 11,105,747 9,209,403 (82.92) 2,171,498 1,455,981 (67.05) 459 HN, distilled water/normal N; XN, Xoo/normal N; HL, distilled water/N limitation; XL, Xoo/N limitation. Identification of Xoo infection-responsive or/and N-limitation-responsive miRNAs A number of plant miRNAs have been identified in response to individual pathogen infection (Navarro et al. 2006, Li et al. 2010, Xin et al. 2010, Guo et al. 2012) and N deficiency (Liang et al. 2012, Zhao et al. 2012). In the current study, comparisons of three sets of miRNA expression profiles [XN vs. HN (Xoo stress), HL vs. HN (N limitation stress) and XL vs. HN (the combined stress)] were performed, and the candidate stress-responsive miRNAs with different expression profiles were defined using a P-value <0.05 and a fold change >1.5 as the cut-off. As shown in Fig.1A, 150 Xoo-responsive (XN vs. HN, 75 up-regulated, 75 down-regulated), 157 N limitation-responsive (HL vs. HN, 39 up-regulated, 118 down-regulated) and 224 combined stress-responsive (XL vs. HN, 48 up-regulated, 176 down-regulated) miRNAs were identified (Fig. 1A). Analysis of the unique and overlapping miRNAs showed that the expression of 63 miRNAs responded to Xoo infection, N limitation and the combined stress (Fig.1B). Among these, 36 miRNAs displayed down-regulated expression, while 15 miRNAs displayed up-regulated expression in response to the individual and combined stress conditions (Fig. 1C, a and b). To verify the RNA-sequencing data, expression patterns of 30 randomly selected miRNAs, representing Xoo infection-responsive, N limitation-responsive and combined stress-responsive miRNAs, were determined based on stem–loop qRT-PCR (Supplementary Fig. S2). All the assayed expression patterns were consistent with that from RNA-sequencing analyses, although slight changes in fold expression were observed (Supplementary Fig. S2). Fig. 1 View largeDownload slide Numbers of Xoo-, N limitation- and combined stress-responsive miRNAs. (A) Changes in miRNA expression with different treatments. Numbers of up- and down-regulated miRNAs with different treatments are summarized. HN, distilled water/normal N; XN, Xoo/normal N; HL, distilled water/N limitation (HL); XL, Xoo/N limitation. (B) Unique and overlapping rice miRNAs responding to Xoo infection and N limitation. Data represent the number of miRNAs. (C) Expression profile distribution of 63 overlapping miRNAs: 36 up-regulated (a) and 15 down-regulated (b) miRNAs under both single and combined stresses. Nine miRNAs were up-regulated under Xoo infection but down-regulated under N limitation and combined stresses (c), and other expression patterns under either single or combined stresses (d). Fig. 1 View largeDownload slide Numbers of Xoo-, N limitation- and combined stress-responsive miRNAs. (A) Changes in miRNA expression with different treatments. Numbers of up- and down-regulated miRNAs with different treatments are summarized. HN, distilled water/normal N; XN, Xoo/normal N; HL, distilled water/N limitation (HL); XL, Xoo/N limitation. (B) Unique and overlapping rice miRNAs responding to Xoo infection and N limitation. Data represent the number of miRNAs. (C) Expression profile distribution of 63 overlapping miRNAs: 36 up-regulated (a) and 15 down-regulated (b) miRNAs under both single and combined stresses. Nine miRNAs were up-regulated under Xoo infection but down-regulated under N limitation and combined stresses (c), and other expression patterns under either single or combined stresses (d). Functional prediction and classification of overlapping miRNA target genes To reveal the regulatory functions of these potential overlapping miRNAs, their putative targets were predicted using TarScan (Lewis et al. 2005) and miRanda (Enright et al. 2003) (Supplementary Table S2). To analyze their functions and associations with metabolic regulatory networks, these potential target genes were classified into different functional groups by Gene Ontology (GO), based on three ontologies, namely biological process, cellular component and molecular function. These terms were defined using a P-value <0.01 as the cut-off. A total of 259 predicted targets were classified into 16 biological processes (Fig. 2, top). Among them, the N compound metabolic process was the most dominant group with 31 components, followed by the response to stress and stimulus with 19 components each, and then the cell death and defense response with 17 and 16 components, respectively. In addition, many target genes were found to be involved in the amine, the amino acid and other metabolic processes. Based on cellular components (Fig. 2, middle), the cell and the cell part were the largest enriched groups. Based on molecular function (Fig. 2, bottom), the target genes associated with nucleotide binding, ATP binding, nucleoside binding and nucleic acid binding were enriched, along with those involved in kinase activity, transcription regulator activity and other activity-associated groups (Fig. 2, bottom). These observations indicated that these miRNAs target a variety of functions in response to bacterial infection and N limitation in rice. Fig. 2 View largeDownload slide Histograms showing GO analysis of potential overlapping miRNA targets. The number indicates the number of genes in a category. Categorization of overlapping miRNA target genes was performed according to biological process, cellular component and molecular function. The term was defined using a P-value <0.01 as a cut-off. Fig. 2 View largeDownload slide Histograms showing GO analysis of potential overlapping miRNA targets. The number indicates the number of genes in a category. Categorization of overlapping miRNA target genes was performed according to biological process, cellular component and molecular function. The term was defined using a P-value <0.01 as a cut-off. Verification of the overlapping miR169o and target gene The candidate overlapping miR169o is a member of the conserved miR169 family, whose members have been identified to be implicated in not only the response to drought stress in plants (Li et al. 2008, Zhao et al. 2011), but also the response to N starvation stress in Arabidopsis (Zhao et al. 2011). To validate the predicted target genes further, the transcription of miR169o and its predicted target genes was analyzed by qRT-PCR assays under individual and combined stress conditions. As shown in Fig. 3A, miR169o displayed a down-regulated expression pattern in response to Xoo infection, N limitation stress and combined stress, respectively (Fig. 3A), which is consistent with the result of the miRNAs sequence. Only the predicted target genes LOC_Os03g07880 and LOC_Os03g48970, encoding NF-YA1 and NF-YA4, respectively, showed complete inverse expression patterns to miR169o under both individual and combined stresses (Fig. 3A). Other predicted targets, NF-YA2 (LOC_Os03g29760), NF-YA3 (LOC_Os03g44540), NF-YA5 (LOC_Os07g06470), NF-YA6 (LOC_Os07g41720), NF-YA10 (LOC_Os12g42400) and a tyrosine aminotransferase (TRA; LOC_Os02g19970), showed imperfect reverse expression pattern to miR169o in response to individual and combined stress (Supplementary Fig. S3). NF-YA5 displayed remarkable up-regulation in response to Xoo infection but not to LN and combined stress. NF-YA3 and NF-YA10 displayed a certain degree of up-regulation in response to LN and combined stress, but not to Xoo infection. TRA displayed a similar pattern to miR169o in response to N deficiency and combined stress (Supplementary Fig. S3). Fig. 3 View largeDownload slide Validation of the target gene of overlapping miR169o by qRT-PCR and 5' RACE. (A) The expression levels of miR169o and its predicted target genes. Expression levels were measured by qRT-PCR and normalized to U6 and actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. (B) Validation of cleavage sites of miR169o targets. The miRNA (bottom) and its target gene (top) are shown aligned. Matches are indicated with straight lines and arrows show the site of cleavage, with the frequency of validated events in the sequenced products to the total number of events. Fig. 3 View largeDownload slide Validation of the target gene of overlapping miR169o by qRT-PCR and 5' RACE. (A) The expression levels of miR169o and its predicted target genes. Expression levels were measured by qRT-PCR and normalized to U6 and actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. (B) Validation of cleavage sites of miR169o targets. The miRNA (bottom) and its target gene (top) are shown aligned. Matches are indicated with straight lines and arrows show the site of cleavage, with the frequency of validated events in the sequenced products to the total number of events. To test the accuracy of the predicted target NF-YA4 and confirm its cleavage location, 5' rapid amplification of cDNA ends (RACE) was performed. With a frequency of 10/10, RACE sequencing results confirmed the target site of miR169o on NF-YA4 (Fig. 3B). The cleavage site was observed at the 10th and 11th residues of the NF-YA4 mRNA from the 5'-terminus of miR169o (Fig. 3B). miR169o contributes to rice growth under either normal or limiting N conditions miR169 is involved in the adaption to drought stress in Arabidopsis (Li et al. 2008, Zhao et al. 2011). Here, miR169o is shown to be down-regulated in response to Xoo infection, N limitation and the combined stresses in rice. To explore further its biological function, we overexpressed the miR169o primary gene in rice by Agrobacterium-mediated transformation. A 444 bp MIR169o gene sequence (surrounding the miRNA sequence) driven by the ubiquitin promoter was transformed into Nipponbare. Expression levels of miR169o and its targets in wild-type (WT) and overexpressing (OX) lines are analyzed. The results showed that the level of miR169o was much higher in miR169o-OX lines than that in the WT under normal N supply conditions (Fig. 4A). Consistent with this, the predicted targets of miR169, namely NF-YA1, NF-YA4, NF-YA10, NF-YA11 and TRA, were kept at very low transcriptional levels in miR169o-OX lines compared with those in the WT (Fig. 4A). One-month-old miR169o-OX plants under different nitrate supply conditions were analyzed phenotypically (Fig. 4B). The miR169o-OX plants were taller than WT plants under either normal or limiting N conditions (Fig. 4C). Furthermore, the biomass analysis showed that both fresh and dry weights of roots and shoots in miR169o-OX plants are heavier than those in WT plants (Table 2). Compared with those in the WT, total weights in miR169o-OX plants were significantly increased by 29.94% in FW and 33.71% in DW under N limitation conditions, and 21.56% in FW and 28.99% in DW under N-sufficient conditions, respectively (Table 2). These results indicated that miR169o promotes the accumulation of biomass especially under N limitation stress. Table 2 Biomass accumulation in miR169o-OX plantsa NO3− (mM) Weight Plant name Weight of tissue (g ± SD) Root:shoot Total weight (g) Ratio (%)b Root Shoot 0.3 FW WT 0.169 ± 0.007 0.302 ± 0.012 0.560 0.471 ± 0.019 39.98 OX 0.222 ± 0.013 0.390 ± 0.024 0.570 0.612 ± 0.031 42.72 DW WT 0.025 ± 0.001 0.064 ± 0.009 0.394 0.089 ± 0.009 52.37 OX 0.034 ± 0.003 0.085 ± 0.003 0.404 0.119 ± 0.003 54.65 3 FW WT 0.329 ± 0.008 0.849 ± 0.021 0.388 1.178 ± 0.025 – OX 0.411 ± 0.028 1.020 ± 0.015 0.403 1.432 ± 0.034 – DW WT 0.038 ± 0.002 0.131 ± 0.003 0.290 0.169 ± 0.005 – OX 0.054 ± 0.005 0.164 ± 0.005 0.332 0.218 ± 0.008 – NO3− (mM) Weight Plant name Weight of tissue (g ± SD) Root:shoot Total weight (g) Ratio (%)b Root Shoot 0.3 FW WT 0.169 ± 0.007 0.302 ± 0.012 0.560 0.471 ± 0.019 39.98 OX 0.222 ± 0.013 0.390 ± 0.024 0.570 0.612 ± 0.031 42.72 DW WT 0.025 ± 0.001 0.064 ± 0.009 0.394 0.089 ± 0.009 52.37 OX 0.034 ± 0.003 0.085 ± 0.003 0.404 0.119 ± 0.003 54.65 3 FW WT 0.329 ± 0.008 0.849 ± 0.021 0.388 1.178 ± 0.025 – OX 0.411 ± 0.028 1.020 ± 0.015 0.403 1.432 ± 0.034 – DW WT 0.038 ± 0.002 0.131 ± 0.003 0.290 0.169 ± 0.005 – OX 0.054 ± 0.005 0.164 ± 0.005 0.332 0.218 ± 0.008 – aThe data represent the mean value of four different experiments. bThe ratio represents the total weight ratio of plants grown under N limitation conditions to that under normal N conditions. Table 2 Biomass accumulation in miR169o-OX plantsa NO3− (mM) Weight Plant name Weight of tissue (g ± SD) Root:shoot Total weight (g) Ratio (%)b Root Shoot 0.3 FW WT 0.169 ± 0.007 0.302 ± 0.012 0.560 0.471 ± 0.019 39.98 OX 0.222 ± 0.013 0.390 ± 0.024 0.570 0.612 ± 0.031 42.72 DW WT 0.025 ± 0.001 0.064 ± 0.009 0.394 0.089 ± 0.009 52.37 OX 0.034 ± 0.003 0.085 ± 0.003 0.404 0.119 ± 0.003 54.65 3 FW WT 0.329 ± 0.008 0.849 ± 0.021 0.388 1.178 ± 0.025 – OX 0.411 ± 0.028 1.020 ± 0.015 0.403 1.432 ± 0.034 – DW WT 0.038 ± 0.002 0.131 ± 0.003 0.290 0.169 ± 0.005 – OX 0.054 ± 0.005 0.164 ± 0.005 0.332 0.218 ± 0.008 – NO3− (mM) Weight Plant name Weight of tissue (g ± SD) Root:shoot Total weight (g) Ratio (%)b Root Shoot 0.3 FW WT 0.169 ± 0.007 0.302 ± 0.012 0.560 0.471 ± 0.019 39.98 OX 0.222 ± 0.013 0.390 ± 0.024 0.570 0.612 ± 0.031 42.72 DW WT 0.025 ± 0.001 0.064 ± 0.009 0.394 0.089 ± 0.009 52.37 OX 0.034 ± 0.003 0.085 ± 0.003 0.404 0.119 ± 0.003 54.65 3 FW WT 0.329 ± 0.008 0.849 ± 0.021 0.388 1.178 ± 0.025 – OX 0.411 ± 0.028 1.020 ± 0.015 0.403 1.432 ± 0.034 – DW WT 0.038 ± 0.002 0.131 ± 0.003 0.290 0.169 ± 0.005 – OX 0.054 ± 0.005 0.164 ± 0.005 0.332 0.218 ± 0.008 – aThe data represent the mean value of four different experiments. bThe ratio represents the total weight ratio of plants grown under N limitation conditions to that under normal N conditions. Fig. 4 View largeDownload slide miR169o enhances the adaption to limiting nitrogen. (A) miR169o level and targets levels in miR169o-OX plants. Expression levels were measured by qRT-PCR and normalized to U6 and actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. (B). The growth status of miR169o-OX plants under normal N and N limitation conditions. (C) Quantitative analysis of the height of plants grown under normal N and N limitation conditions. The experiment was repeated three times with similar results. Error bars represent the SD (n >15). Asterisks denote a significant difference between transgenic plants and the WT (Student’s t-test, **P < 0.01, *P < 0.05). One-month old seedlings grown in a hydroponic system with optimal or limiting N conditions were photographed and their height was measured. Fig. 4 View largeDownload slide miR169o enhances the adaption to limiting nitrogen. (A) miR169o level and targets levels in miR169o-OX plants. Expression levels were measured by qRT-PCR and normalized to U6 and actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. (B). The growth status of miR169o-OX plants under normal N and N limitation conditions. (C) Quantitative analysis of the height of plants grown under normal N and N limitation conditions. The experiment was repeated three times with similar results. Error bars represent the SD (n >15). Asterisks denote a significant difference between transgenic plants and the WT (Student’s t-test, **P < 0.01, *P < 0.05). One-month old seedlings grown in a hydroponic system with optimal or limiting N conditions were photographed and their height was measured. miR169o enhances nitrate and total amino acid accumulation in roots To investigate whether miR169o-improved plant growth is NO3− dependent, the nitrate content and total amino acid content were measured in different rice tissues. The roots of miR169o-OX plants had a higher nitrate content than those of WT plants under either normal or limiting N conditions (Fig. 5A). In shoots and leaves, there is no significant difference in nitrate content in miR169o-OX and WT plants under normal nitrate supply conditions (Fig. 5B, C). However, under limiting N conditions, the nitrate content in miR169o-OX plants was obviously higher than that in WT plants (Fig. 5B, C). Similarly, total amino acid content in roots was much higher in miR169o-OX plants than that in WT plants under either normal or limiting N supply (Fig. 5D). However, no significant difference was found in shoots and leaves between miR169o-OX and WT plants (Fig. 5E, F). The increased contents of nitrate and total amino acid in miR169o-OX plants suggested that miR169o might enhance nitrate uptake and total amino acid accumulation at least in roots. Fig. 5 View largeDownload slide miR169o increases nitrate and total amino acid under N limitation conditions. The nitrate (A–C) and total amino acid (D–F) content in root, stem and leaf of WT and miR169o-OX plants under N sufficiency and limitation conditions. Plants were grown continuously with 3 or 0.3 mM KNO3. The experiment was repeated three times, independently. Error bars represent the SD (n >8). An asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, *P < 0.05). Fig. 5 View largeDownload slide miR169o increases nitrate and total amino acid under N limitation conditions. The nitrate (A–C) and total amino acid (D–F) content in root, stem and leaf of WT and miR169o-OX plants under N sufficiency and limitation conditions. Plants were grown continuously with 3 or 0.3 mM KNO3. The experiment was repeated three times, independently. Error bars represent the SD (n >8). An asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, *P < 0.05). miR169o regulates NRT1 and NRT2 expression in roots Nitrate is the most important N source for most crops, and nitrate uptake from soil and transport into plants occur mainly through the action of low-affinity NRT1s (nitrate transporter 1 family, NRT1) and high-affinity NRT2s (nitrate transporter 2 family, NRT2) (Tsay et al. 2007). In order to dissect the internal mechanism of miR169o-mediated adaption to N limitation stress, the expression pattern of the NRT1 (OsNRT1.1 and OsNPF2.4) and NRT2 (OsNRT2.1, OsNRT2.2 and OsNAR2.1) families in roots was measured under normal N and limiting N supply, respectively. Compared with the WT, osa-miR169o-OX plants showed an up-regulated OsNRT1.1 and OsNPF2.4 level under both normal N and limiting N supply conditions (Fig. 6A). Under normal N supply conditions, the NRT2 genes OsNRT2.1, OsNRT2.2 and OsNAR2.1 were down-regulated in miR169o-OX plants compared with the WT (Fig. 6B). In contrast, under long-term N limitation stress, OsNRT2.1 was induced up to 4-fold in miR169o-OX plants, while OsNRT2.2 and OsNAR2.1 were induced up to 27- and 57-fold, respectively, in miR169o-OX plants (Fig. 6B). These data suggested that miR169o contributes to the expression of NRT1 regardless of N conditions. However, miR169o represses the NRT2 transcript under the normal N condition, but induces it under long-term N limitation stress. Fig. 6 View largeDownload slide Expression of NRT-related genes in root of miR169o-OX plants under normal N and N limitation condition. OsNRT1.1 and OsNPF2.4 represent the NRT1 family (A), while OsNRT2.1, OsNRT2.2 and OsNAR2.1 represent the NRT2 family (B). Expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. Fig. 6 View largeDownload slide Expression of NRT-related genes in root of miR169o-OX plants under normal N and N limitation condition. OsNRT1.1 and OsNPF2.4 represent the NRT1 family (A), while OsNRT2.1, OsNRT2.2 and OsNAR2.1 represent the NRT2 family (B). Expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). The experiment was repeated at least three times with similar results. miR169o negatively regulates resistance to bacterial blight in rice To investigate the function of miR169o in the defense response, lesion lengths and bacterial populations in miR169o-OX and WT plants were measured at 14 d after inoculation with Xoo. The lengths of lesions caused by Xoo infection on miR169o-OX were much greater than those on WT plants under both normal and limiting N supply conditions (Fig. 7A). Bacterial populations in miR169o-OX plants at 14 d after inoculation with Xoo were significant higher than in the WT under both normal and limiting N supply conditions (Fig. 7B). Consistently, the transcriptional levels of pathogen defense genes, namely PR1b, PR10a, PR10b and PAL, were much lower in the miR169o-OX plants than in the WT under normal N conditions (Fig. 7C). Although defense genes were induced by N limitation stress, the levels of defense genes in miR169o-OX were still much lower than those in the WT under N limitation conditions (Fig. 7C). These results indicated that miR169o negatively regulates the resistance against Xoo in rice. Fig. 7 View largeDownload slide miR169o enhances the susceptibility to bacterial blight in rice. (A) Length of the lesion caused by Xoo infection on plants under normal N and low N conditions, respectively. Lesion lengths were measured 14 d after inoculation with Xoo. A double asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, **P < 0.01, n >15). (B) Bacterial growth on WT and miR169o-OX plants. An asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, *P < 0.05, n >6). (C) Expression levels of PR1b, PR10a, PR10b and PAL genes in WT and miR169o-OX plants. Gene expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between transgenic plants and the WT under normal N conditions (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. Fig. 7 View largeDownload slide miR169o enhances the susceptibility to bacterial blight in rice. (A) Length of the lesion caused by Xoo infection on plants under normal N and low N conditions, respectively. Lesion lengths were measured 14 d after inoculation with Xoo. A double asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, **P < 0.01, n >15). (B) Bacterial growth on WT and miR169o-OX plants. An asterisk denotes a significant difference between transgenic plants and the WT (Student’s t-test, *P < 0.05, n >6). (C) Expression levels of PR1b, PR10a, PR10b and PAL genes in WT and miR169o-OX plants. Gene expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between transgenic plants and the WT under normal N conditions (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. miR169o impedes Xoo-mediated NRT transcription Osa-miR169o negatively regulates disease resistance to bacterial blight on rice caused by Xoo infection (Fig. 7) and enhances adaption to N deficiency stress (Fig. 4; Table 2). Transcriptional levels of NRT1 and NRT2 were further tested in miR169o-OX plants after inoculation with Xoo. The results showed that OsNRT1.1 and OsNRT1.2 were induced, but OsNRT2.1 was reduced by bacterial infection in the WT (Fig. 8). However, in miR169o-OX plants, OsNRT1.2 was reduced markedly and OsNRT2.1 was induced at 24 h after inoculation with Xoo (Fig. 8). The opposite expression pattern of NRT1 and NRT2 between WT and miR169o-OX plants after Xoo infection indicates that miR169o impedes the expression of NRT genes modulated by Xoo infection. Fig. 8 View largeDownload slide NRT levels in miR169o-OX plants after inoculation with Xoo. Expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between 0 h and 24 h after inoculation with Xoo (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. Fig. 8 View largeDownload slide NRT levels in miR169o-OX plants after inoculation with Xoo. Expression levels were measured by qRT-PCR and normalized to actin. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between 0 h and 24 h after inoculation with Xoo (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. NF-YA genes promote the transcription of PR genes and NRT genes To identify whether target genes contribute to osa-miR169o-regulated disease resistance and NUE, NF-YA genes were transiently expressed in rice protoplasts and the transcriptional levels of PR genes and NRT genes were measured. Transcription assay showed that NF-YA genes were maintained at a considerable high level afer transient expression in rice protoplasts (Fig. 9A). Compared with transient expression of empty vector, transient expression of the NF-YA genes NF-YA4, NF-YA10 and NF-YA11 resulted in the significant up-regulation of PR genes PR10a, PR10b and PAL (Fig. 9B). Meanwhile, NRT2 family members OsNRT2.1, OsNRT2.2 and OsNAR2.1 were significantly induced after transient expression of NF-YA genes, respectively, while NRT1 family members including OsNRT1.1 and OsNPF2.4 were slightly reduced (Fig. 9C). Fig. 9 View largeDownload slide NF-YA genes affect the transcriptional levels of PR genes and NRT genes. (A) Transcriptional levels of NF-YA genes in rice protoplasts. (B) Transcriptional levels of PR genes in rice protoplasts after transient expression of NF-YAs. (C) Transcriptional levels of NRT genes in rice protoplasts after transient expression of NF-YA genes. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between NF-YA-overexpressing plants and empty vector (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. Fig. 9 View largeDownload slide NF-YA genes affect the transcriptional levels of PR genes and NRT genes. (A) Transcriptional levels of NF-YA genes in rice protoplasts. (B) Transcriptional levels of PR genes in rice protoplasts after transient expression of NF-YAs. (C) Transcriptional levels of NRT genes in rice protoplasts after transient expression of NF-YA genes. Bars depict the mean expression level ± SD (n = 3). Asterisks denote a significant difference between NF-YA-overexpressing plants and empty vector (Student’s t-test, **P < 0.01, *P < 0.05). This experiment was repeated at least three times with similar results. Discussion miR169 is involved in the response to N starvation and bacterial infection When grown under low N conditions (LN), rice that is normally sensitive to BB is more resistant than when grown on higher N (Yu et al. 2015). However, the underlying regulatory mechanism of the LN-mediated disease resistance is still unclear. One possible mode of cross-regulation is through the action of miRNAs. MiRNAs involved in response to pathogen infection (Baldrich et al. 2015, Feng et al. 2015) or N limitation stress (Zhao et al. 2011, Zhao et al. 2012) have been reported. However, little was known about the function and regulation of overlapping miRNAs in response to Xoo infection and N-limiting conditions or from combining these stress conditions. A total of 63 overlapping miRNAs regulated by Xoo infection, N deficiency stress and combined stress were identified based on deep RNA sequencing and stem–loop qRT-PCR. Among them, 10 miR169 isoforms were reduced by Xoo infection, N limiting and combined stress. Only four isoforms, i.e. miR169b/c/e/i, were responsive to limiting N stress specifically. No Xoo-responsive specific miR169 isoform was found in our results (Supplementary Table S2). This implied that the conserved miR169 may play significant roles in the cross-talk in response to Xoo infection and N-limiting stress. Osa-miR169o showed the greatest down-regulation in response to different stresses (Supplementary Table S2). To characterize further the biological function of osa-miR169o on NUE and resistance to Xoo, the osa-miR169o primary gene driven by the constitutive ubiquitin promoter was transformed into the susceptible Nipponbare variety, and a series of assays were carried out on miR169o-OX plants. miR169o enhances NUE in rice As a highly conserved miRNA family, miR169 is involved in the developmental regulation and adaption to various environmental stresses. In Arabidopsis, miR169a was down-regulated by drought stress through an ABA-dependent pathway. Overexpression of ath-miR169a increased leaf water loss and sensitivity to drought stress through repressing the crucial target NF-YA5 (Li et al. 2008, Zhang et al. 2011). In contrast, overexpression of sly-miR169c led to reduced stomatal opening, lowered leaf water loss and enhanced drought tolerance in tomato (Zhang et al. 2011). The opposite effect of miR169 on tolerance to drought stress indicated that miR169 plays diverse roles in different plants. In Arabidopsis, miR169a in both roots and shoots was down-regulated by N starvation, and overexpression of ath-miR169a resulted in less N accumulation and enhanced the sensitivity to N starvation stress (Zhao et al. 2011). Here, our results showed that osa-miR169o, similarly to ath-miR169a, was down-regulated in response to N-limiting conditions. However, inconsistent with overexpression of ath-miR169a, overexpression of osa-miR169o in rice promoted plant growth and increased biomass accumulation under either normal or limiting N conditions (Fig. 4B, C;Table 2). The nitrate and total amino acid contents in root of miR169o-OX plants were also much higher than those in the WT (Fig. 5). Nitrate uptake from soil and transport in plants are mainly done by low-affinity NRT1s and high-affinity NRT2s (Tsay et al. 2007). NRT1.1/CHL1 is a nitrate sensor and a dual affinity member in Arabidopsis (Liu et al. 1999, Ho et al. 2009). Its affinity activity is switched on by a Thr101 phosphorylation-controlled dimerization in Arabidopsis (Sun et al. 2014). OsNPF2.4 is an NPF (nitrate transporter 1/peptide transporter family, formerly NRT1/PTR) member with low affinity. Overexpression of OsNPF2.4 increased nitrate acquisition in roots and upward transfer from root to shoot. In comntrast, disruption of OsNPF2.4 decreased nitrate uptake and transfer (Xia et al. 2015). As for the NRT2 family with high nitrate affinity, there are at least five genes belonging to the NRT2 family in the rice genome (Feng et al. 2011). Among those, OsNRT2.1 and OsNRT2.2 are responsible for nitrate uptake and transfer. The molecular partner OsNAR2.1 interacts with OsNRT2.1 and OsNRT2.2 and is required for the function of OsNRT2.1 and OsNRT2.2 (Yan et al. 2011). Transcriptional assay results showed that overexpression of osa-miR169o induced the OsNRT1 transcript and repressed the OsNRT2 transcript in rice under normal N conditions, while it induced both OsNRT1 and OsNRT2 transcripts under N-limiting conditions (Fig. 6). Under N-sufficient conditions, OsNRT1, a low-affinity nitrate transporter, plays the predominant role while OsNRT2 plays a negligible role in N uptake. In response to N deficiency stress, osa-miR169o induced the high-affinity nitrate transporter NRT2 up to >10-fold and low-affinity NRT1 up to almost 10-fold. Therefore, osa-miR169o may positively regulate NUE and increase nitrate content through controlling NRT1 and NRT2 mRNA levels under both N-sufficient and -deficient conditions in rice. miR169 is involved in plant immunity to Xoo infection miRNAs play important roles in plant immunity. Recently, miR169a has been reported as a negative regulator of the resistance against the rice blast pathogen M. oryzae in rice (Li et al. 2017). Inconsistent with the accumulation of miR169 upon M. oryzae infection, 10 miR169 isoforms, namely miR169o/n and miR169f.1/g/h/i/j/k/l/m, were down-regulated in response to Xoo infection (Supplementary Table S2). Intriguingly, all 10 Xoo-responsive miR169 isoforms can also be reduced by N-limiting stress and the combined stress. No Xoo-responsive specific miR169 isoform was found in our results. Constitutive overexpression of miR169o plants showed a longer lesion length, higher bacterial population and lower transcript levels of defense genes such as PR10b, PR1b, PR10a and PAL than control plants under both N-sufficient and -deficient conditions (Fig. 7). This result indicates that miR169o negatively regulates the resistance against Xoo in rice. However, considering the different expression pattern in response to M. oryzae and Xoo infection, miR169 isoforms are predominantly modulated by the pathogen or host, respectively, in response to M. oryzae or Xoo infection. During M. oryzae infection, the pathogen induces the biogenesis of miR169 and facilitates the successful infection in susceptible rice species. This modulation was weakened in resistant rice lines (Li et al. 2017). When suffering from Xoo infection, rice actively reduced the production of miR169 to weaken miR169-mediated susceptibility to Xoo. Therefore, miR169 could be regulated by the pathogen and host, respectively, in response to fungal and bacterial infection. NF-YA genes contribute to plant immunity and NUE in rice miR169 negatively regulates the tolerance to drought stress by inhibiting the NF-YA5 transcription and post-transcription level (Li et al. 2008). miR169a and miR169i from 18 miR169 isoforms have been reported to regulate tolerance to drought stress through targeting NF-YA5 mRNA in Arabidopsis (Du et al. 2017). In addition, miR169 also regulates plant flowering time through targeting NF-YA in Arabidopsis. However, only palnts overexpressing NF-YA2 and NF-YA6 consistently flowered earlier than the WT (Siriwardana et al. 2016), while overexpression of NF-YA1 and NF-YA4 led to later flowering in Arabidopsis (Wenkel et al. 2006). The above showed that miRNA isoforms display functional differences and target specific genes in response to different stresses or biological functions. Although all test-predicted targets were down-regulated in osa-miR169o-OX lines compared with control plants (Fig. 4A), only NF-YA1 and NF-YA4 but not six other predicted target genes displayed a perfect reverse expression pattern to osa-miR169o in response to Xoo infection, N deficiency and combined stress (Fig. 3A;Supplementary Fig. S3). After transient expression of NF-YA genes in the rice protoplast, the PR genes PR10a, PR10b and PAL, and the NRT2 genes OsNRT2.1, OsNRT2.2 and OsNAR2.1 were significantly induced, while the NRT1 genes OsNRT1.1 and OsNPF2.4 were reduced (Fig. 9). This indicates that NF-YA genes must be involved in the regulation by osa-miR169o of plant immunity and NUE in rice. Which NF-YA is dominant in response to individual and combined stress still requires further detailed study in the future. The trade-off between enhanced growth with added N vs. the sensitivity to pathogens The highly conserved miR169 family displays diverse regulatory mechanism in plants on adaption to various environmental stresses including biotic and abiotic stress. Osa-miR169o is involved in the cross-talk between response to Xoo infection and N-limiting stress. There is clearly a genetic linkage between the response to N limitation stress and pathogen resistance, with the miR169o overexpression lines showing both a higher level of NUE and a higher sensitivity to BB. It will be of interest to see if the overexpression of miR169o also affects pathogen resistance in a resistant variety. Li et al. (2017) reported that osa-miR169b/c displayed different expression patterns in susceptible and resistant varieties in response to M. oryzae infection. Osa-miR169b/c only responds to N-limiting stress in our study system (Supplementary Table S2). Therefore, it would be very worthwhile to overexpress osa-miR169b/c in a resistant variety which may show enhanced growth without the downside of being more sensitive to the pathogen. Further, there are a large number of other miRNAs which respond to both N limitation and pathogen stress at the transcriptional level, and it will be of interest to see if any of these have a role in determining plant response to these stress conditions. Materials and methods   Plant materials and stress treatments Seeds of rice were germinated for 2 d in turface. Individual germinated seeds were planted in small pots containing rockwool and covered with turface, and the pots were placed in a tray to grow for 1 week. These plants were then transferred to the hydroponic tank that contains 30 liters of Hoagland solution (Bi et al. 2009), with each tank containing 24 pots. The nutrient solution pH was maintained at 5.5–6 using 50% phosphoric acid, by measuring the pH every 3 d. The growth conditions are 16 h light (29°C) and 8 h dark (23°C). The N stress treatments involved a normal nitrate concentration (3 mM KNO3) and a nitrate limitation condition (0.3 mM KNO3) (Coneva et al. 2014, Yu et al. 2015). For the biotic stress treatments, Xoo cultured cells (OD600=0.8) were inoculated on 1-month-old plants by the scissors-clipping method (Song et al. 1995), and ddH2O was inoculated as the negative control. Rice leaves were harvested 6 h post-inoculation for each sample, which was pooled from five plants, frozen in liquid N and stored at –80°C. Construction of miRNA libraries for high-throughput sequencing Total RNA samples were extracted from rice leaves treated with Xoo and normal N (XN), Xoo and N limitation (XL), ddH2O and N limitation (HL), and ddH2O and normal N (HN) as control using Trizol (Invitrogen). miRNA libraries were constructed as reported (Wang et al. 2011). For each sample, small RNAs of 18–30 nt were separated by electrophoresis in a 15% TBE-urea denaturing polyacrylamide gel, and then 5' and 3' adaptors were added with T4 RNA ligase (TAKARA). cDNA was synthesized using Superscript II reverse transcriptase (Invitrogen), and then enriched through PCR. The purified DNA was sequenced on a Solexa sequencer (Illumina). Analysis of small RNA sequencing data The raw sequencing data were deposited in NCBI’s Sequence Read Archive (SRA) and are accessible through the SRA series accession number PRJNA238154. The accession numbers of HN, XN, HL and XL libraries were SRR1257322, SRR1257323, SRR1257324 and SRR1257325, respectively (http://www.ncbi.nlm.nih.gov/bioproject/? term=PRJNA238154). Raw data from Solexa sequencing were cleaned by removing the low quality tags and contaminants including null adaptors and improper sizes (<18 bp), and unique small RNAs were acquired by removing adaptor and primer sequences of clean data using miRExpress (Wang et al. 2009). Thereafter the reads were mapped to the rice genome sequence (Ensemble) downloaded from the website ftp://ftp.ensemblgenomes.org/pub/plants/release-16/fasta/oryza_sativa/dna/ using Bowtie (Flicek et al. 2012), and then aligned with known miRNAs from miRBase 20 (ftp://mirbase.org/pub/mirbase/20/) (Griffiths-Jones et al. 2008). Prediction and functional analysis of putative target genes of miRNAs Target predictions of miRNAs were performed by both TarScan (Lewis et al. 2005) and maRanda (Enright et al. 2003). The intersections of two kinds of predicted results were taken as putative target genes for subsequent analysis. To reveal the functions of the predicted target genes of the overlapping miRNAs, 259 potential target genes were mapped to GO terms in the database (http://www.geneontology.org/), and gene numbers were calculated for each term (using P < 0.01 as the cut-off). Examination of mature miRNAs and their target genes by qRT-PCR Total RNAs were extracted from rice tissues with TRIzol reagent (Invitrogen). Mature miRNAs were reverse transcribed by stem–loop reverse transcriptase primers, and the reverse transcription products were amplified using a universal reverse primer and a miRNA-specific forward primer as described (Chen et al. 2005). The specific primers of mature miRNAs and their predicted target genes were designed and are listed in Supplementary Tables S3 and S4. The rice U6 and actin genes were selected as the reference for miRNAs and genes in the qRT-PCR assay. qRT-PCR analysis was carried out using SYBR Green detection reagents (Quanta Biosciences) in Applied Biosystem’s 7500 Sequence Detection System (Applied Biosystems), and a 20 µl PCR contained about 100 ng of cDNA. All components in the reaction were mixed gently and incubated at 95°C for 3 min, and then 40 cycles at 95°C for 10 s, 60°C for 30 s, followed by a dissociation stage. All samples were performed in three biological replicates and triplicate PCR. The relative expression ratio was calculated using the 2−ΔΔCt method. 5' RACE analysis The identification of miRNA cleavage sites on their target genes involved RNA ligation-mediated 5' RACE (RLM-5' RACE). Total RNA (5 µg) was obtained as described above. According to the protocol of the GeneRacer kit (Invitrogen), total RNAs were directly ligated to the 5' RACE RNA adaptor, and then the ligated RNAs were reverse transcribed by the GeneRace Oligo(dT) primer. The GeneRacer™ 5' primer and outer gene-specific reverse primers were used for the first round of PCR, and GeneRacer™ 5' nested primer and inner gene-specific reverse primers were used for nested PCR. PCR products were gel purified, cloned (TAKARA), and 10 independent clones from each reaction were sequenced. The sequences of primers are shown in Supplementary Table S5. Constructions for transgenic plants or transient expression in rice protoplast The 444 bp osa-miR169o precursor sequence was amplified using the specific primers forward 5'-CAACCACCTCTGCATCTTCTACTTCC-3' and reverse 5'-ATTACGCCCCAGAGAGCCAAAAAC-3'. The PCR product was inserted into pCXUN digested by XcmI (Chen et al. 2009). The construct was transformed into rice by the Agrobacterium-mediated method. The positive transgenic plants were screened by hygromycin resistance and miR169o level. As described above, the transgenic and WT plants were grown in Hoagland solution under normal or low N conditions. To express NF-YAs transiently in rice protoplasts, corresponding NF-YA fragments cleaved by SacI and SalI were inserted into pUC-cLUC (Chen et al. 2008) cleaved by the same restriction enzymes. The primers using for amplifing NF-YA fragments are listed in Supplementary Table S4. Analysis of plant biomass The biomass was detected as described previously (Yu et al. 2015). As shown above, 1-month-old transgenic and WT rice plants grown under normal or low nitrate conditions were harvested. The fresh and the dry weights were measured before or after shoots and roots were dried at 50°C for 7 d, respectively. Five plants were analyzed in an experiment, and each experiment was repeated four times. Nitrate and total amino acid concentration measurements Nitrate and total amino acid concentrations were measured as described previously (Moore and Stein 1954, Yan et al. 2014). Briefly, the roots, stems and leaves of 1-month-old transgenic and WT rice plants grown in two different nitrate conditions were collected and weighed. Then the samples were ground to a powder in liquid N, resuspended in 10 ml of deionized water and incubated at 45°C for 1 h. The supernatant was obtained after centrifugation at 5,000×g for 15 min. For measurement of the nitrate concentration, 100 µl of supernatant and 400 µl of 5% (w/v) salicylic acid (dissolved in concentrated H2SO4) were mixed gently. After 20 min at room temperature, 9.5 ml of 2 N NaOH was added slowly to the mixture. Then 200 µl of mixture was taken to determine the nitrate concentration at a wavelength of 410 nm. For measurement of total amino acids, the supernatant was mixed with 0.3% ninhydrin solution (dissolved in 95% ethanol) and acetic acid (1:3:1, pH 5.4) in a 2 ml tube. Then, the tubes were boiled for 20 min. An equal amount of 60% ethanol was added after cooling to room temperature, and the total amino acid concentration was determined at a wavelength of 570 nm. These experiments were repeated at least three times. Lesion length and bacterial growth assay PXO99A, a virulent Xoo strain on Nipponbare, was grown for 72 h at 28°C in M210 medium (0.8% casein enzymatic hydrolysate, 0.5% sucrose, 0.5% yeast extract, 0.3% K2HPO4, 0.03% MgSO4·7H2O, pH 7.0). The cells were collected by centrifugation and resuspended in ddH2O up to OD600 = 0.8. One-month-old seedlings were inoculated with Xoo by the leaf-clipping method. Lesion lengths were recorded at 14 d after inoculation. For the bacterial growth assay, three inoculated leaves were ground in ddH2O with a mortar and pestle and were considered as one sample. The mixture was then diluted to 103, 104, and 105, and spread 100 mL onto PSA plates (1% tryptone, 1% Sucrose, 0.1% L-glutamic acid, 1.5% agar, pH7.0), respectively. The colonies of bacteria were counted at 72 h after incubation at 28°C. The experiment was repeated at least three times. Rice protoplast transient expression and RNA extraction Rice protoplasts were isolated from 10-day-old seedlings of the Nipponbare variety growing on Murashige and Skoog (MS) medium. Protoplast preparation and transfection were carried out by following described procedures (Chen et al. 2006). After transfection, protoplasts were incubated in light for about 16 h at room temperature. For RNA extraction from protoplasts, rice protoplasts were collected by centrifugation and resuspended with 300 µL of TRIzol reagent (Invitrogen). 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Google Scholar CrossRef Search ADS PubMed Abbreviations Abbreviations AOP2 alkenyl hydroxalkyl producing 2 BB bacterial blight GO Gene Ontology HL treatment with ddH2O and N deficiency HN treatment with ddH2O and normal miRNA microRNA N nitrogen NF-YA nuclear factor-Y subunit A NLA nitrogen-limiting adaption NPF nitrate transporter 1/peptide transporter family (formerly NRT1/PTR) NRT nitrate transporter family NUE nitrogen use efficiency Pst Pseudomonas syringae pv. tomato qRT-PCR quantitative real-time PCR RLM-5' RACE RNA ligation-mediated 5' rapid amplification of cDNA ends TRA tyrosine aminotransferase WT wild type XL treatment with Xoo inoculation and N deficiency XN treatment with Xoo inoculation and normal N Xoo Xanthomonas oryzae pv. oryzae © The Author(s) 2018. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Plant and Cell PhysiologyOxford University Press

Published: Mar 15, 2018

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