High throughput sequencing reveals novel and abiotic stress-regulated microRNAs in the inflorescences of rice

  • Blanca E Barrera-Figueroa1, 2Email author,

    Affiliated with

    • Lei Gao1Email author,

      Affiliated with

      • Zhigang Wu1,

        Affiliated with

        • Xuefeng Zhou3,

          Affiliated with

          • Jianhua Zhu4,

            Affiliated with

            • Hailing Jin5,

              Affiliated with

              • Renyi Liu1Email author and

                Affiliated with

                • Jian-Kang Zhu6

                  Affiliated with

                  BMC Plant Biology201212:132

                  DOI: 10.1186/1471-2229-12-132

                  Received: 4 April 2012

                  Accepted: 24 July 2012

                  Published: 3 August 2012

                  MicroRNAs (miRNAs) are small RNA molecules that play important regulatory roles in plant development and stress responses. Identification of stress-regulated miRNAs is crucial for understanding how plants respond to environmental stimuli. Abiotic stresses are one of the major factors that limit crop growth and yield. Whereas abiotic stress-regulated miRNAs have been identified in vegetative tissues in several plants, they are not well studied in reproductive tissues such as inflorescences.

                  We used Illumina deep sequencing technology to sequence four small RNA libraries that were constructed from the inflorescences of rice plants that were grown under control condition and drought, cold, or salt stress. We identified 227 miRNAs that belong to 127 families, including 70 miRNAs that are not present in the miRBase. We validated 62 miRNAs (including 10 novel miRNAs) using published small RNA expression data in DCL1, DCL3, and RDR2 RNAi lines and confirmed 210 targets from 86 miRNAs using published degradome data. By comparing the expression levels of miRNAs, we identified 18, 15, and 10 miRNAs that were regulated by drought, cold and salt stress conditions, respectively. In addition, we identified 80 candidate miRNAs that originated from transposable elements or repeats, especially miniature inverted-repeat elements (MITEs).

                  We discovered novel miRNAs and stress-regulated miRNAs that may play critical roles in stress response in rice inflorescences. Transposable elements or repeats, especially MITEs, are rich sources for miRNA origination.

                  Endogenous small RNAs (sRNAs) are 20–30 nt RNA molecules that modulate gene expression at the transcriptional and posttranscriptional levels and have roles in developmental and physiological processes in eukaryotic organisms [13]. In plants, sRNAs are classified into microRNAs (miRNAs) and small interfering RNAs (siRNAs), according to their biogenesis and precursor structures [49]. siRNAs are derived from double stranded RNA precursors and can be further divided into heterochromatic siRNAs (hc-siRNAs), trans-acting siRNAs (ta-siRNAs), long siRNAs (lsiRNAs), and natural antisense transcripts-derived siRNAs (nat-siRNAs). hc-siRNAs are involved in DNA methylation and histone modifications that lead to silencing of target genes at the transcriptional level [10]. ta-siRNAs, lsiRNAs, and nat-siRNAs act at the posttranscriptional level, guiding mRNA cleavage, degradation, or translational repression of target genes. Arabidopsis ta-siRNAs are phased sRNAs generated from a primary transcript that is targeted by a miRNA. The product of this cleavage is then converted to double stranded RNA by RNA-dependent RNA polymerase 6 (RDR6) and processed by Dicer like protein 4 (DCL4) to produce ta-siRNAs [11]. Arabidopsis lsiRNAs are DCL1-dependent sRNAs of 30–40 nt in length, which mediate mRNA decapping and degradation [12]. nat-siRNAs are generated from co-expressed cis-antisense overlapping genes. The transcripts of overlapping genes may hybridize to form double-stranded RNAs and be processed by DCL proteins into sRNAs that target the antisense gene for regulation [1315].

                  miRNAs are distinguished from siRNAs since they are transcribed into a single-stranded pri-miRNA by RNA polymerase II, which folds into a stable, usually imperfect, hairpin structure [16]. This structure is then processed by DCL1 to produce ~21 nt, double-stranded RNA duplex. The duplex is exported into the cytoplasm by HASTY and methylated at the 3’ end by HEN1 [17]. One strand functions as the mature miRNA and is incorporated into the RNA-Induced Silencing Complex (RISC) to target mRNAs for cleavage in a sequence-specific manner. The other strand, called miRNA*, is usually degraded, although some miRNA*s were found to be functional under certain conditions [18]. Plant miRNAs recognize their targets through near-perfect complementarity to direct RISC-mediated cleavage, although in some cases translational inhibition and DNA methylation can be the mode of action of miRNA-mediated gene silencing [1921].

                  Several studies have demonstrated that miRNAs play important roles in the responses to biotic and abiotic stimuli [2224]. Abiotic stress-regulated miRNAs were first investigated in Arabidopsis. Sunkar and Zhu [25] showed that miR393, miR402, miR397b, and miR319c were induced by at least one of the treatments including drought, cold, salt and ABA, whereas miR398 was downregulated. Further study showed that miR398 mediates the post-transcriptional induction of two superoxide dismutase genes involved in the first line of defense against toxic superoxide radicals and is also downregulated by oxidative stress in Arabidopsis[26]. Also in Arabidopsis, miR169 is downregulated by drought through an ABA-dependent pathway to control the expression of the NFYA5 transcription factor, which mediates tolerance to drought [27].

                  To discover stress-regulated miRNAs, it is necessary to compare the expression of miRNAs in plants grown under normal and stress-treated conditions. This was achieved by Northern blot analyses when digital expression analysis was not effective because traditional sequencing technology provided only very low coverage [25]. With the application of next-generation sequencing and microarrays, it became much easier and cost-effective to perform genome-wide expression profiling to identify stress-regulated miRNAs. As a result, discovery of stress-regulated miRNAs has expanded from the model dicot Arabidopsis to model monocot rice and other non-model plants, and many more stress-regulated miRNAs were found [2835].

                  Rice (Oryza sativa) is a staple crop that is cultivated worldwide and constitutes a primary source of human food. Besides its high agricultural importance, rice is a model monocot with a small genome and excellent genomic resources. Recently extensive efforts have been devoted to the discovery of novel miRNAs, as well as the analysis of miRNAs in stress responses in rice [28, 29, 3644]. miRNAs that are regulated by various stresses were identified. For example, a genome-wide study conducted across different developmental stages of rice revealed that 16 miRNAs, including miR156, miR159 and miR168, were downregulated by drought stress, while 14 miRNAs, such as miR169, miR319 and miR395, were upregulated [42].

                  Most of previous studies on miRNAs that are regulated by abiotic stresses in rice have been focused on early growth stages [36, 41, 4446]. However, the onset of abiotic stresses during reproductive stages of rice can dramatically compromise seed production. Seed development requires a series of molecular events that are finely regulated at the transcriptional and posttranscriptional levels [47] and it has been recently demonstrated that miRNAs are involved in those processes [39]. Therefore, there is a need to expand our knowledge on miRNA expression in reproductive tissues under abiotic stresses. In this study we set to identify miRNAs that were involved in the responses to abiotic stresses in rice inflorescences. We applied high-throughput sequencing and bioinformatic analysis to small RNA populations derived from rice inflorescences under control, as well as drought, cold, and salt stresses. We identified 227 miRNAs, including 70 candidate miRNAs that are not in the miRBase. Using stringent criteria, we identified 18, 15, and 10 miRNAs that were differentially regulated by drought, cold, and salt stress, respectively. We validated 62 miRNAs using published small RNA data from DCL1 DCL3 RDR2 RNAi knockdown lines and confirmed 210 miRNA targets using published degradome data. We also identified 80 miRNAs that appear to have originated from transposable elements and repeats.

                  Results and discussion

                  Identification of miRNAs

                  We constructed and sequenced four small RNA libraries using the inflorescences of rice plants that grew under control (untreated) and three abiotic stress treatments. After quality control and adaptor removal, we obtained 5328145, 4186380, 3524691 and 3992166 high quality clean reads from control, drought, cold and salt libraries, respectively (Additional file 1). We removed around 27% of clean reads from each library that matched rice repeats and known rRNAs, tRNAs, snoRNAs, snRNAs, and then mapped the rest of small RNA reads to the rice whole genome sequence. Using an in-house miRNA prediction pipeline that was built according to the updated annotation criteria for plant miRNAs [48, 49], we predicted 227 miRNAs that were classified into 127 families (details of predicted miRNAs are included in Additional file 2).

                  Because rice is an important crop and is the model species for monocotyledons, it has been subject to substantial effort for miRNA discovery. As a result, rice has 491 registered miRNAs in the miRBase [50] (release 17), which is the most for any plant species. We compared the genomic locations and mature miRNAs of our predicted miRNAs to those of known rice miRNAs in the miRBase and found that 145 predicted miRNAs (64 families) had already been included in the database, 12 predicted miRNAs were new homologs of 7 known miRNA families (allowing mature miRNAs to have up to 2 mismatches), and 70 miRNAs (62 families) were new miRNA candidates (Additional file 2; Predicted secondary structures of new miRNA candidates are provided in Additional file 3 and distributions and abundances of all sRNAs that are mapped to each precursor are provided in Additional file 4). Among these new miRNA candidates, osa-cand006, osa-cand021, osa-cand027, osa-cand032, and osa-cand036 were included in release 18 of the miRBase as osa-miR5159, osa-miR2863c, osa-miR5485, osa-5150-3p, and osa-miR5337, respectively.

                  Among 145 miRNA precursors that match registered rice miRNAs in the miRBase, 81 precursors have identical predicted mature miRNAs to those in the miRBase, 40 have predicted mature miRNAs that are highly similar but not identical, and 24 have a mature miRNA that is different from the registered mature miRNA (Additional file 5). For each predicted miRNA precursor, a small RNA is usually chosen as the mature miRNA if it has the highest abundance among all reads that are mapped to the precursor. In some cases, small RNA with highest expression was not chosen because it did not reside in a hairpin structure that meets the stringent structural requirements for miRNA annotation [48, 49]. Because the cleavage of miRNA precursor into miRNA/miRNA* duplex is imprecise at some level [51], generating overlapping but not identical small RNAs with different abundances over the hairpin region, the choice for mature miRNAs may not be clear cut, especially when number of mapped reads is low. Low coverage can be caused by low sequencing depth from early sequencing technologies such as 454 pyrosequencing, comparing to Illumina sequencing that was used in this study. Low coverage can also be caused by the low expression level of some miRNAs in the chosen tissue and under the chosen growth condition. In addition, a miRNA* might have higher abundance than the miRNA in some cases [18, 39].

                  Validation of predicted miRNAs

                  Based on their biogenesis pathway, rice miRNAs can be grouped into two classes. The first class is canonical miRNAs (cmiRNAs), which are usually 21nt in length, cleaved by DCL1, and sorted into Argonaut 1 (AGO1) family proteins [21, 52]. The other class is long miRNAs (lmiRNAs), which are usually 24nt in length, cleaved by DCL3, and sorted into AGO4 family proteins [21]. Both classes of miRNAs do not require RDR2, which is a critical component in the siRNA biogenesis pathway. Therefore, the expression of authentic miRNAs would be significantly reduced in either dcl1 or dcl3 knockdown lines, but not in the rdr2 knockdown line.

                  In order to validate our 227 predicted miRNAs, we compared the abundances of their mature miRNAs in the published small RNA sequencing data from the wild type (WT) and three RNAi knockdown lines (dcl3a-17 rdr2-2, and DCL1IR-2) [21], as well as small RNAs that were pulled down with Argonaut proteins AGO1a, AGO1b, AGO1c, AGO4a, AGO4b, and AGO16 [21, 53]. Using the criteria described in the Methods, we were able to confirm 46 canonical miRNAs that had significantly reduced expression in DCL1IR-2, including six novel miRNAs (osa-cand001, osa-cand039, osa-cand053, osa-cand056, osa-cand059, and osa-cand060). We also confirmed 16 long miRNAs that had significantly reduced expression in dcl3a-17, including four novel miRNAs (osa-cand020, osa-cand021, osa-cand032, and osa-cand054). Five more miRNAs (osa-cand017, osa-cand058, osa-miR1862, osa-miR1862d, and osa-miR440) narrowly missed the list of confirmed lmiRNAs because their expression level in rdr2-2 was slightly less than 50% of that in WT (Additional file 6). As expected, whereas confirmed cmiRNAs have a typical length of 21nt and are predominantly associated with AGO1 proteins, lmiRNAs have a typical length of 24nt and are exclusively associated with AGO4 or AGO16 proteins (Additional file 6).

                  Prediction and confirmation of miRNA targets

                  Because plant miRNAs have near perfect complementarity to their targets, computational prediction has been an effective way to identifying miRNA targets. Using the procedure described in the Methods, we searched rice annotated cDNAs and were able to predict targets for 170 (75%) miRNAs (Additional file 2). Deep sequencing of mRNA cleavage products (degradome sequencing) provides a means for confirmation of miRNA targets [54, 55]. To confirm miRNA targets that were predicted in this study, we searched the two published degradome datasets from Oryza sativa ssp. japonica using the CleaveLand software [56]. We were able to confirm 210 targets for 86 miRNAs (Additional file 7), including 154 targets that were previously verified [46, 53], mostly for known miRNAs. We also confirmed 20 targets for 12 novel miRNAs. For instance, osa-cand041 targets a putative inorganic phosphate transporter, osa-cand046 targets a putative amino acid transporter, and osa-cand026 targets a putative ATP-dependent RNA helicase. We were also able to confirm some targets for new miRNA homologs and for known miRNAs for the first time (Additional file 7).

                  Because many miRNAs and target genes show tissue- or growth condition-specific expression patterns, our ability to verify predicted targets depends highly on the treatments and tissues used to construct the degradome libraries. As more degradome data from a variety of tissues and treatments become available, it will be possible to verify targets for more miRNAs.

                  Abiotic stress-regulated miRNAs

                  The deep coverage of mature miRNAs provided by Illumina sequencing allowed us to compare the normalized count of each miRNA in a stressed library to that in the control library to find miRNAs that were induced or downregulated by the stress. Normalized expression level was calculated as the number of mature miRNAs per ten million clean small RNA reads (transcripts per ten million, TPTM). A miRNA was identified as regulated by a particular stress only if the following three conditions were met: (1) normalized expression was at least 100 TPTM in either control or stress library; (2) log2 ratio of normalized expression under stress or control was greater than 1 or less than −1; (3) test for differential expression in stress versus control library according to the Audic and Claverie (1997) [57, 58] method was significant (p ≤ 0.01). Applying this stringent set of criteria, we identified 18, 15, and 10 miRNAs that were regulated by drought, cold, and salt stress, respectively (Table 1).
                  Table 1

                  Abiotic stress-regulated miRNAs identified in rice inflorescences

                  *Log2 (Drought/Ctrl)

                  *Log2 (Cold/Ctrl)

                  *Log2 (Salt/Ctrl)

                  Putative target

                  Cytochrome c

                  MYB family transcription factor

                  Auxin response factor

                  Auxin response factor

                  START domain containing protein

                  START domain containing protein

                  Auxin response factor

                  Hypotethical protein

                  Glycosyltransferase family protein

                  TCP family transcription factor

                  F-box domain and LRR containing protein

                  MYB family transcription factor

                  F-box domain containing protein

                  Growth regulating factor

                  Growth regulating factor

                  Growth-regulating factor

                  Plastocyanin-like domain containing protein

                  SBP-box gene family

                  Hairpin-induced protein 1 domain containing protein

                  *Log2 ratio of normalized miRNA expression in stress and control libraries. Ctrl: control condition; ↑ and ↓: up- and downregulated in stress, respectively.

                  We observed an apparent difference in how a stress would change the expression of miRNAs. Whereas the majority of stress-regulated miRNAs were upregulated by drought (12 out of 18) or cold stress (12 out of 15), most salt-regulated miRNAs were downregulated (9 out of 10). Whereas 16 miRNAs were regulated with only one of the three abiotic stresses examined, 12 miRNAs were regulated by two or three stresses (Table 1), indicating that they might be involved in a pathway that is shared in the response to different stresses. For example, miR2871b was induced by all three abiotic stresses examined in this study.

                  Among the miRNAs that were identified as stress-regulated miRNAs here, some miRNA families have been previously found to be regulated by certain stress, either in rice or in other plants. For example, miR167, miR393, miR396, miR529 have been shown to be regulated by drought stress [25, 42, 59], miR393 and miR396 were shown to be regulated by cold stress [25, 42, 59], and miR159, miR160, miR319, miR394, miR528, and miR530 were shown to be regulated by salt stress [25, 29, 5961]. To the best of our knowledge, some miRNAs were found to be regulated by certain stress for the first time in this study. This list includes miR1428, miR160, miR1866, miR2275, miR2871, and miR530 that were regulated by drought stress, miR1866, miR2275, miR2871, miR394, and miR529 that were regulated by cold stress, and miR1866 by salt stress. In addition, we identified five novel miRNA candidates (osa-cand027, osa-cand032, osa-cand042, osa-cand-052, and osa-cand056) that were regulated by at least one of the three abiotic stresses in rice inflorescences (Table 1). Among these stress-regulated miRNAs, we randomly chose five miRNAs to confirm their expression patterns with Northern blot assays. In general, the differential expression patterns of miRNAs based on cloning frequencies in small RNA sequencing libraries (Figure 1) were consistent with Northern blot results (Figure 2), although the strong upregulation of miRNA396 was only partially reflected in Northern blots.
                  Figure 1

                  Relative expression level of selected stress-regulated miRNAs in rice inflorescences. Log2 was calculated for the ratio of normalized miRNA counts in each library to that in the control library.

                  Figure 2

                  Northern blot analysis of selected stress-regulated miRNAs in rice inflorescences. Each sample contains 40 μg of total RNAs from inflorescences of plants that were treated with drought (D), cold (C) and salt (S) stress, or control (CRL) conditions, respectively. U6 was used as control of equal loading as shown at the bottom of each hybridization set.

                  Targets for stress-regulated miRNAs were predicted and confirmed based on degradome data analysis. As shown in Table 1, targets of stress-regulated miRNAs have diverse functions, mainly as transcriptional factors such as MYB, auxin responsive factors and proteins with F-box domains. Since miR2871 was upregulated in all stress conditions tested, it is very likely that its target, a glycosyltransferase family protein, is downregulated. Therefore, negative regulation of glycosylation processes may be a common mechanism to respond to a variety of abiotic stresses. On the other hand, miR396 regulates a family of growth factors in rice [42]. Its upregulation in our drought and cold stress libraries suggests the downregulation of growth factors, perhaps to redirect resources to other parts of the plant in response to drought. This confirms that growth regulation is a mechanism highly sensitive to abiotic stresses.

                  Three miRNAs, miR394, miR530-3p and miR2275d were upregulated by cold stress (Figure 1). The predicted targets of miR394 are F-Box proteins of diverse functions [46, 62]. Interestingly, miR530-3p was strongly accumulated in cold treated plants, while it was downregulated by drought and salt stresses as predicted by quantitative analysis and confirmed in Northern blots (Table 1, Figure 2). This suggests a high level of specialization of miRNAs to respond to different abiotic stresses. The expression patterns suggest that some elements need to be regulated by drought and salt treatments, while the same elements are regulated in an opposite way under cold stress to regulate a cold specific mechanism.

                  We used very stringent criteria for determining stress-regulated miRNAs. While it helps us reduce false positives, some true stress-regulated miRNAs may be missed. For example, miR169 has been previously found to be downregulated in drought-stressed Arabidopsis[27] and salt-stressed Nicotiana[60], but induced by drought in Nicotiana[60] and rice [45], and by UV irradiation in Populus tremula[63]. miR169b and miR169c were highly expressed in rice inflorescences and were apparently upregulated by drought and cold stresses (Additional file 2). However, the change of expression was a little bit less than 2-fold in both cases and miR169 was not identified as stress-regulated miRNA based on our criteria.

                  The results of this work confirm that some miRNAs may be involved in response to several abiotic stresses, while others seem to be specific to an individual stress. Differences in expression patterns could also be an effect of the nature and severity of individual stress and the level of impact that it has on the tissue under study. For example, we observed that salt treated plants showed clear symptoms of stress on the leaves, e.g. the rolling of old leaves, while inflorescences did not appear to be affected since the plants were able to recover and produced normal amount of seeds after they were irrigated with NaCl-free nutrient solution. In contrast, cold and drought stress caused apparent damage to the inflorescences. Even though plants were able to recover and continued growing after stress treatments were removed, both development of new inflorescences and production of seeds were reduced, most likely due to stress-induced sterility or permanent damage to floral structures.

                  It is interesting that, in general, we did not find dramatic changes in expression of miRNAs in response to abiotic stresses and only a small fraction of miRNAs showed some level of regulation. Overall, the slight changes observed in the expression of miRNAs points to the existence of a fine-tuning mechanism rather than a dramatic control of expression exerted by miRNAs under drought, cold and salt stress in rice inflorescences. This fine-tuning mechanism may be important in plants to regulate gene expression without impacting negatively growth and development.

                  Other known miRNAs that were regulated by stresses

                  Because we used a stringent set of criteria on miRNA structure and expression pattern [48] for miRNA prediction and identification, it is possible that some real miRNAs were left behind, including some stress-regulated miRNAs. In order to find additional known miRNAs that are regulated by abiotic stresses, we used the mature miRNAs from the miRBase to query our small RNA reads from each library and compared their frequencies. We indeed found a few known miRNAs that appear to be regulated by abiotic stresses (Table 2). We confirmed their expression using Northern blot assays (Figure 2) and the hybridization signals were in general consistent with log2 ratios of mature miRNA counts (Figure 1).
                  Table 2

                  Transposon- or repeat-derived miRNAs and other known miRNAs that were regulated with abiotic stresses

                  *Log2 (Drought/Ctrl)

                  *Log2 (Cold/Ctrl)

                  *Log2 (Salt/Ctrl)

                  Putative target

                  LTPL8 - Protease inhibitor

                  Transposon protein

                  Expressed protein

                  AAA ATPase

                  Glutaredoxin 2, putative

                  Glutaredoxin subgroup II

                  PPR repeat containing protein

                  Transposon- and Repeat-derived miRNAs

                  In order to reduce false positives in miRNA discovery, it is a general practice to remove small RNAs that are highly similar to known transposable elements and repetitive sequences from consideration. In our first round of miRNA prediction, we did not consider small RNA reads as potential mature miRNAs if they match known transposons or repeats, or have a copy number higher than 20 in the genome. However, recent studies have shown that miRNAs could have originated from transposons or repeats [64, 65]. Rice genome is enriched with miniature inverted-repeat transposable elements (MITEs) [66] and other inverted repeats that once transcribed, may form hairpin structures and be cleaved into miRNAs by DCL1 or DCL3. To identify miRNAs that may have been derived from transposons and repeats, we relaxed the requirements in the first round of miRNA prediction and used small RNA reads that did have a match (alignment length ≥ 80% of the length of the small RNA, and identity ≥ 80%) in the rice repeats database (ftp://ftp.plantbiology.msu.edu/pub/data/TIGR_Plant_Repeats) or Repbase [67] or have a copy number (allowing up to 2 mismatches) higher than 20 in the genome, as anchor sequences for miRNA prediction. We predicted 424 potential miRNA precursors (Additional file 8). These precursors met all the criteria for miRNA annotation, including precise cleavage and strand bias in expression.

                  To further check the authenticity of these potential miRNAs, we again examined their expression in the DCL1IR-2, dcl3a-17, and rdr2-2 RNAi lines. Using the same set of criteria for miRNA validation as stated earlier, we found that 29 miRNAs were potentially generated by DCL1 and 51 miRNAs that were generated by DCL3. All these 80 miRNAs did not depend on RDR2 and were sorted into AGO1 or AGO4 family proteins, respectively, as expected. We inspected the types of transposable elements or repeats from which these miRNAs have originated and found that 53 (66%) miRNAs were derived from MITEs, 11 from En/Spm DNA transposons, 7 from non LTR retrotransposon LINE1, and 9 from unclassified repeats (Additional file 9). Compared to the copy number abundance of different classes of TEs in the genome, MITEs are apparently enriched in TEs from which miRNAs were derived (Additional file 10). Stowaway and adh were the two main types of MITEs that contributed to miRNA origination, accounting for 37 and 11 miRNAs, respectively. Both 21nt cmiRNAs and 24nt lmiRNAs originated from the same MITE families such as Stowaway and adh, indicating that once MITEs were transcribed, they could fold into hairpin structures and be cleaved by either DCL1 or DCL3 proteins. This list contains some known miRNAs in the miRBase, including 7 miR166 family miRNAs derived from a LINE element, two miR169 family miRNAs derived from En/Spm transposons, and 19 miR809 family miRNAs derived from MITEs (Additional file 9).

                  We were able to predict at least one target for 78 TE/repeat derived miRNAs, indicating these miRNAs do have biological functions (Additional file 9). Among the targets predicted with high confidence, there are proteins such as 3-ketoacyl-CoA synthases that are targeted by miR809 and are involved in the biosynthesis of cuticular wax [68]. Other TE/repeat derived miRNAs appear to target genes that encode transcriptional activators (osa-cand064, osa-cand076, osa-cand079, and miR809), proteins involved in signaling cascades (osa-cand071 and osa-cand077), and proteins that may be involved in regulation of transposon and retrotransposon activity (miR166, osa-cand063, and osa-cand084). These results suggest a potential role of transposon- and repeat-derived miRNAs in important processes in plant biology.

                  Using the same set of criteria for finding stress-regulated miRNAs, we found that osa-cand066 was upregulated by cold, osa-cand084 downregulated by all three stresses, osa-cand085 downregulated by salt, miR1884 downregulated by drought, some miR809 family miRNAs downregulated by drought or cold (Table 2Additional file 9). It is remarkable that members of the miR809 family are predicted to target F-box-containing proteins and glutarredoxin. Many F-box proteins have been found in the response to drought stress [69], whereas glutarredoxins are proteins involved in the defense against oxidative stress [70]. It is possible that downregulation of miR809 triggers the accumulation of these proteins in a mechanism to cope with the abiotic stresses.

                  High-throughput sequencing is a cost-effective approach for identification of novel miRNAs in the inflorescences of rice. Deep sequencing also allows for comparison of miRNA expression in different growth conditions and for identification of stress-regulated miRNAs. Our results suggest that miRNAs play important roles in rice in response to abiotic stresses not only in vegetative tissues as shown in previous studies, but also in reproductive tissues. Further functional analysis of stress-regulated miRNAs and their targets will allow us to dissect the complex miRNA-mediated pathways and networks in plant stress responses.

                  Plant materials and stress treatments

                  Rice (Oryza sativa spp. japonica cv. Nipponbare) plants were grown in a greenhouse at 28°C, 13 h light until 90 day old and were then randomly divided into four groups. One group was used as untreated control, and other three groups were treated with drought (water withholding for 3 days), cold (5°C for 24 hours) or salt (400 mM NaCl for 24 hours) stresses, respectively. After control and stress treatments were applied, mature inflorescences of 14–17 cm in length, in stage In 9 were collected and stored at −80°C until RNA extraction. Inflorescence tissues, composed by rachis, branches and spikelets from 10 plants per treatment, were used for total RNA extraction with Trizol (Invitrogen). There were no seeds in the collected tissues. The treatments used in this work were set to induce an intermediate level of stress, based on the development of clear, typical stress symptoms in rice, such as leaf rolling and wilting, while plants were still able to recover and resume growth if they were transferred from the stress treatments to normal growth condition.

                  Small RNA library construction and deep sequencing

                  Small RNA libraries were constructed following a standard method [25] with some modifications [71]. In brief, total RNA was run in 15% denaturing polyacrylamide gel and the 18-30nt small RNA fraction was excised and eluted. After an adaptor was added to the 3’ end and another to the 5’ end, small RNA constructs were reverse-transcribed and amplified by PCR for 15 cycles. The products were sequenced with an Illumina Genome Analyzer at the UC Riverside Core Facilities.

                  Prediction of miRNAs

                  Raw reads from four small RNA libraries were first processed to obtain clean reads. Only raw reads that contained clear adaptor sequence were considered. After adaptor sequence was removed, clean reads of at least 18nt long were clustered into unique reads. We first removed reads that match known rice repeats (ftp://ftp.plantbiology.msu.edu/pub/data/TIGR_Plant_Repeats), rRNAs, tRNAs, snRNAs, and snoRNAs and then used an in-house miRNA prediction pipeline to predict miRNAs [49]. We mapped unique reads to the rice genome assembly (version 6.1, ftp://ftp.plantbiology.msu.edu) with SOAP2 [72], requiring perfect matches. To ensure that our miRNA candidates did not come from highly repetitive sequences, we removed unique reads that had more than 20 hits (allowing up to 2 mismatches) in the rice genome. Mapped reads with a minimum count of 10 were used as anchor sequences to extract surrounding DNA segments. These segments had one end at 20nt away from the mapping location on one side and extended across the anchor sequence for 100 to 300nt with a step size of 20nt. Extracted DNA segments were folded into secondary structures using UNAFold [73]. A segment was considered a valid miRNA candidate if its secondary structure met the following criteria according to Meyers et al. [48]: (1) free energy is at most −35 kcal/mol; (2) number of mismatches between putative miRNA and miRNA* is 4 or less; (3) number of asymmetrical bulges in the stem region is no more than 1 and if exist, its size is 2 or less; (4) strand bias ― the ratio of small RNA reads that map to the positive and negative strands of the DNA segment is 5:1 or more (5) precise cleavage ― reads that map to the miRNA and miRNA* regions (defined as miRNA or miRNA* plus 2nt on the 5’ and 3’ ends) account for at least 75% of reads that map to the segment. If more than one segment from the same locus met the above criteria, we chose the segment with highest putative miRNA counts, lowest free energy, or shortest length as the candidate miRNA precursor.

                  We classified predicted miRNAs into families by first comparing mature miRNAs with themselves using the ssearch35 program in the FASTA package (version 3.5) [74]. We then used a single-linkage algorithm to put homologous miRNAs (up to two mismatches were allowed) into clusters. miRNAs from each cluster were then compared to the known plant mature miRNAs in the miRBase (Release 17) [75] using ssearch35. If a cluster had a homologous known miRNA (allowing up to two mismatches in the alignment), the family number of the known miRNA was assigned to the cluster, otherwise the cluster was annotated as a new family.

                  Validation of predicted miRNAs

                  Mature miRNA sequences of predicted miRNAs were searched in the published small RNA sequencing data and their abundances were compared in the wild type (WT) and three RNAi knockdown lines (dcl3a-17 rdr2-2, and DCL1IR-2) [21], as well as small RNAs that were pulled down with Argonaut proteins AGO1a, AGO1b, AGO1c, AGO4a, AGO4b, and AGO16 [21, 53]. A miRNA was considered validated if it met four conditions: (1) its normalized expression level (transcripts per ten million, TPTM) was at least 50 in one of the four libraries (WT, dcl3a-17 rdr2-2, and DCL1IR-2); (2) the ratio of normalized expression in dcl3a-17 or DCL1IR-2 versus WT was less than 0.5; (3) the ratio of normalized expression in dcl3a-17 or DCL1IR-2 versus rdr2-2 was also less than 0.5; (4) the ratio of normalized expression in rdr2-2 versus WT was greater than 0.5.

                  Prediction of miRNA targets

                  We used the predicted mature miRNAs as query to search the annotated rice cDNAs with miRanda [76]. We scored the alignments between miRNAs and potential targets using a position-dependent, mispair penalty system [11, 50, 77]. Each alignment was divided into two regions: a core region that included positions 2–13 from the 5’ end of the miRNA, and a general region that contained other positions. In the general region, a penalty score of 1 was given to a mismatch or a single-nucleotide bulge or gap, and 0.5 to a G:U pair. Penalty scores were doubled in the core region. A gene was considered a valid target if the alignment between miRNA and target met two conditions: (1) the penalty score is 4 or less; (2) total number of bulges and gaps is less than 2. Predicted miRNA-targets were further validated by searching two public degradome datasets from Oryza sativa ssp. japonica [46, 53] using the CleaveLand software [56] with default parameters.

                  Northern blot assays

                  Northern blot assays were performed to confirm a selected set of stress-regulated miRNAs. Briefly, 40 μg of total RNA obtained from inflorescences were loaded in 15% denaturing polyacrylamide gels and transferred to a nylon membrane (Hybond NX). The RNA was then fixed to the membrane by chemical cross-linking [78]. Blots were hybridized to radioactive probes complementary to mature miRNAs at 38°C overnight (probe sequences are provided in Additional file 11). Membranes were then washed twice with 2X SSC, 0.1% SDS solution for 5 minutes each, and exposed to X-ray films for autoradiography.

                  Accession number

                  Deep sequencing data from the four small RNA libraries have been deposited in the NCBI/GEO database with accession number GSE26357.

                  This work was supported by National Institutes of Health grant R01GM059138 and United States Department of Agriculture grant CA-R*-BPS-7806-CG to J-KZ, UCR Initial Complement Fund and A USDA hatch fund (CA-R*-BPS-7754 H) to RL, National Science Foundation grant MCB0950242 to JZ, and UC-MEXUS and CONACYT-Mexico fellowships to BEB-F.

                  Authors’ Affiliations

                  Department of Botany and Plant Sciences and Institute for Integrative Genome Biology, University of California
                  Instituto de Biotecnología, Universidad del Papaloapan
                  Department of Plant Science and Landscape Architecture, University of Maryland
                  Department of Plant Pathology and Microbiology, Center for Plant Cell Biology and Institute for Integrative Genome Biology, University of California
                  Department of Horticulture and Landscape Architecture, Purdue University

                  1. Zamore PD, Haley B: Ribo-gnome: the big world of small RNAs. Science 2005,309(5740):1519–1524.PubMedView Article
                  2. Bonnet E, Van de Peer Y, Rouze P: The small RNA world of plants. New Phytol 2006,171(3):451–468.PubMedView Article
                  3. Zhang B, Pan X, Cobb GP, Anderson TA: Plant microRNA: a small regulatory molecule with big impact. Dev Biol 2006,289(1):3–16.PubMedView Article
                  4. Vazquez F: Arabidopsis endogenous small RNAs: highways and byways. Trends Plant Sci 2006,11(9):460–468.PubMedView Article
                  5. Jin H, Zhu JK: How many ways are there to generate small RNAs? Mol Cell 2010,38(6):775–777.PubMedView Article
                  6. Vazquez F, Legrand S, Windels D: The biosynthetic pathways and biological scopes of plant small RNAs. Trends Plant Sci 2010,15(6):337–345.PubMedView Article
                  7. Vaucheret H: Post-transcriptional small RNA pathways in plants: mechanisms and regulations. Genes Dev 2006,20(7):759–771.PubMedView Article
                  8. Sunkar R, Zhu JK: Micro RNAs and short-interfering RNAs in plants. J Integr Plant Biol 2007,49(6):817–826.View Article
                  9. Ramachandran V, Chen XM: Small RNA metabolism in Arabidopsis. Trends Plant Sci 2008,13(7):368–374.PubMedView Article
                  10. Chinnusamy V, Zhu JK: RNA-directed DNA methylation and demethylation in plants. Sci China C Life Sci 2009,52(4):331–343.PubMedView Article
                  11. Allen E, Xie Z, Gustafson AM, Carrington JC: microRNA-directed phasing during trans-acting siRNA biogenesis in plants. Cell 2005,121(2):207–221.PubMedView Article
                  12. Katiyar-Agarwal S, Gao S, Vivian-Smith A, Jin H: A novel class of bacteria-induced small RNAs in Arabidopsis. Genes Dev 2007,21(23):3123–3134.PubMedView Article
                  13. Borsani O, Zhu J, Verslues PE, Sunkar R, Zhu JK: Endogenous siRNAs derived from a pair of natural cis-antisense transcripts regulate salt tolerance in Arabidopsis. Cell 2005,123(7):1279–1291.PubMedView Article
                  14. Jin H, Vacic V, Girke T, Lonardi S, Zhu JK: Small RNAs and the regulation of cis-natural antisense transcripts in Arabidopsis. BMC Mol Biol 2008, 9:6.PubMedView Article
                  15. Katiyar-Agarwal S, Morgan R, Dahlbeck D, Borsani O, Villegas A, Zhu JK, Staskawicz BJ, Jin H: A pathogen-inducible endogenous siRNA in plant immunity. Proc Natl Acad Sci USA 2006,103(47):18002–18007.PubMedView Article
                  16. Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004,116(2):281–297.PubMedView Article
                  17. Chen X: MicroRNA biogenesis and function in plants. FEBS Lett 2005,579(26):5923–5931.PubMedView Article
                  18. Zhang X, Zhao H, Gao S, Wang WC, Katiyar-Agarwal S, Huang HD, Raikhel N, Jin H: Arabidopsis argonaute 2 regulates innate immunity via miRNA393*-mediated silencing of a golgi-localized SNARE Gene, MEMB12. Mol Cell 2011,42(3):356–366.PubMedView Article
                  19. Chen X: A microRNA as a translational repressor of APETALA2 in Arabidopsis flower development. Science 2004,303(5666):2022–2025.PubMedView Article
                  20. Brodersen P, Sakvarelidze-Achard L, Bruun-Rasmussen M, Dunoyer P, Yamamoto YY, Sieburth L, Voinnet O: Widespread translational inhibition by plant miRNAs and siRNAs. Science 2008,320(5880):1185–1190.PubMedView Article
                  21. Wu L, Zhou H, Zhang Q, Zhang J, Ni F, Liu C, Qi Y: DNA methylation mediated by a microRNA pathway. Mol Cell 2010,38(3):465–475.PubMedView Article
                  22. Dalmay T: Short RNAs in environmental adaptation. Proc Biol Sci 2006,273(1594):1579–1585.PubMedView Article
                  23. Jones-Rhoades MW, Bartel DP, Bartel B: MicroRNAs and their regulatory roles in plants. Annu Rev Plant Biol 2006, 57:19–53.PubMedView Article
                  24. Sunkar R, Chinnusamy V, Zhu J, Zhu JK: Small RNAs as big players in plant abiotic stress responses and nutrient deprivation. Trends Plant Sci 2007,12(7):301–309.PubMedView Article
                  25. Sunkar R, Zhu JK: Novel and stress-regulated microRNAs and other small RNAs from Arabidopsis. Plant Cell 2004,16(8):2001–2019.PubMedView Article
                  26. Sunkar R, Kapoor A, Zhu JK: Posttranscriptional induction of two Cu/Zn superoxide dismutase genes in Arabidopsis is mediated by downregulation of miR398 and important for oxidative stress tolerance. Plant Cell 2006,18(8):2051–2065.PubMedView Article
                  27. Li WX, Oono Y, Zhu J, He XJ, Wu JM, Iida K, Lu XY, Cui X, Jin H, Zhu JK: The Arabidopsis NFYA5 transcription factor is regulated transcriptionally and posttranscriptionally to promote drought resistance. Plant Cell 2008,20(8):2238–2251.PubMedView Article
                  28. Liu Q, Zhang YC, Wang CY, Luo YC, Huang QJ, Chen SY, Zhou H, Qu LH, Chen YQ: Expression analysis of phytohormone-regulated microRNAs in rice, implying their regulation roles in plant hormone signaling. FEBS Lett 2009,583(4):723–728.PubMedView Article
                  29. Ding YF, Chen Z, Zhu C: Microarray-based analysis of cadmium-responsive microRNAs in rice (Oryza sativa). J Exp Bot 2011,62(10):3563–3573.PubMedView Article
                  30. Li BS, Qin YR, Duan H, Yin WL, Xia XL: Genome-wide characterization of new and drought stress responsive microRNAs in Populus euphratica. J Exp Bot 2011,62(11):3765–3779.PubMedView Article
                  31. Valdes-Lopez O, Yang SS, Aparicio-Fabre R, Graham PH, Reyes JL, Vance CP, Hernandez G: MicroRNA expression profile in common bean (Phaseolus vulgaris) under nutrient deficiency stresses and manganese toxicity. New Phytol 2010,187(3):805–818.PubMedView Article
                  32. Kulcheski FR, de Oliveira LFV, Molina LG, Almerao MP, Rodrigues FA, Marcolino J, Barbosa JF, Stolf-Moreira R, Nepomuceno AL, Marcelino-Guimaraes FC, et al.: Identification of novel soybean microRNAs involved in abiotic and biotic stresses. BMC Genomics 2011, 12:307.PubMedView Article
                  33. Xin MM, Wang Y, Yao YY, Xie CJ, Peng HR, Ni ZF, Sun QX: Diverse set of microRNAs are responsive to powdery mildew infection and heat stress in wheat (Triticum aestivum L.). BMC Plant Biol 2010, 10:123.PubMedView Article
                  34. Kantar M, Lucas SJ, Budak H: miRNA expression patterns of Triticum dicoccoides in response to shock drought stress. Planta 2011,233(3):471–484.PubMedView Article
                  35. Ding D, Zhang LF, Wang H, Liu ZJ, Zhang ZX, Zheng YL: Differential expression of miRNAs in response to salt stress in maize roots. Ann Bot 2009,103(1):29–38.PubMedView Article
                  36. Sunkar R, Girke T, Jain PK, Zhu JK: Cloning and characterization of MicroRNAs from rice. Plant Cell 2005,17(5):1397–1411.PubMedView Article
                  37. Nobuta K, Venu RC, Lu C, Belo A, Vemaraju K, Kulkarni K, Wang WZ, Pillay M, Green PJ, Wang GL, et al.: An expression atlas of rice mRNAs and small RNAs. Nat Biotechnol 2007,25(4):473–477.PubMedView Article
                  38. Sunkar R, Zhou XF, Zheng Y, Zhang WX, Zhu JK: Identification of novel and candidate miRNAs in rice by high throughput sequencing. BMC Plant Biol 2008, 8:25.PubMedView Article
                  39. Zhu QH, Spriggs A, Matthew L, Fan LJ, Kennedy G, Gubler F, Helliwell C: A diverse set of microRNAs and microRNA-like small RNAs in developing rice grains. Genome Res 2008,18(9):1456–1465.PubMedView Article
                  40. Huang SQ, Peng J, Qiu CX, Yang ZM: Heavy metal-regulated new microRNAs from rice. J Inorg Biochem 2009,103(2):282–287.PubMedView Article
                  41. Shen J, Xie K, Xiong L: Global expression profiling of rice microRNAs by one-tube stem-loop reverse transcription quantitative PCR revealed important roles of microRNAs in abiotic stress responses. Mol Genet Genomics 2010,284(6):477–488.PubMedView Article
                  42. Zhou L, Liu Y, Liu Z, Kong D, Duan M, Luo L: Genome-wide identification and analysis of drought-responsive microRNAs in Oryza sativa. J Exp Bot 2010,61(15):4157–4168.PubMedView Article
                  43. Lv DK, Bai X, Li Y, Ding XD, Ge Y, Cai H, Ji W, Wu N, Zhu YM: Profiling of cold-stress-responsive miRNAs in rice by microarrays. Gene 2010,459(1–2):39–47.PubMedView Article
                  44. Li T, Li H, Zhang YX, Liu JY: Identification and analysis of seven H2O2-responsive miRNAs and 32 new miRNAs in the seedlings of rice (Oryza sativa L. ssp indica). Nucleic Acids Res 2011,39(7):2821–2833.PubMedView Article
                  45. Zhao BT, Liang RQ, Ge LF, Li W, Xiao HS, Lin HX, Ruan KC, Jin YX: Identification of drought-induced microRNAs in rice. Biochem Biophys Res Commun 2007,354(2):585–590.PubMedView Article
                  46. Li YF, Zheng Y, Addo-Quaye C, Zhang L, Saini A, Jagadeeswaran G, Axtell MJ, Zhang WX, Sunkar R: Transcriptome-wide identification of microRNA targets in rice. Plant J 2010,62(5):742–759.PubMedView Article
                  47. Duan K, Luo YH, Luo D, Xu ZH, Xue HW: New insights into the complex and coordinated transcriptional regulation networks underlying rice seed development through cDNA chip-based analysis. Plant Mol Biol 2005,57(6):785–804.PubMedView Article
                  48. Meyers BC, Axtell MJ, Bartel B, Bartel DP, Baulcombe D, Bowman JL, Cao X, Carrington JC, Chen X, Green PJ, et al.: Criteria for annotation of plant microRNAs. Plant Cell 2008,20(12):3186–3190.PubMedView Article
                  49. Barrera-Figueroa BE, Gao L, Diop NN, Wu Z, Ehlers JD, Roberts PA, Close TJ, Zhu JK, Liu R: Identification and comparative analysis of drought-associated microRNAs in two cowpea genotypes. BMC Plant Biol 2011, 11:127.PubMedView Article
                  50. Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ: miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 2006, 34:D140-D144.PubMedView Article
                  51. Jiao Y, Song W, Zhang M, Lai J: Identification of novel maize miRNAs by measuring the precision of precursor processing. BMC Plant Biol 2011, 11:141.PubMedView Article
                  52. Liu B, Li P, Li X, Liu C, Cao S, Chu C, Cao X: Loss of function of OsDCL1 affects microRNA accumulation and causes developmental defects in rice. Plant Physiol 2005,139(1):296–305.PubMedView Article
                  53. Wu L, Zhang QQ, Zhou HY, Ni FR, Wu XY, Qi YJ: Rice microRNA effector complexes and targets. Plant Cell 2009,21(11):3421–3435.PubMedView Article
                  54. German MA, Pillay M, Jeong DH, Hetawal A, Luo SJ, Janardhanan P, Kannan V, Rymarquis LA, Nobuta K, German R, et al.: Global identification of microRNA-target RNA pairs by parallel analysis of RNA ends. Nat Biotechnol 2008,26(8):941–946.PubMedView Article
                  55. Addo-Quaye C, Eshoo TW, Bartel DP, Axtell MJ: Endogenous siRNA and miRNA targets identified by sequencing of the Arabidopsis degradome. Curr Biol 2008,18(10):758–762.PubMedView Article
                  56. Addo-Quaye C, Miller W, Axtell MJ: CleaveLand: a pipeline for using degradome data to find cleaved small RNA targets. Bioinformatics 2009,25(1):130–131.PubMedView Article
                  57. Audic S, Claverie JM: The significance of digital gene expression profiles. Genome Res 1997,7(10):986–995.PubMed
                  58. Gonzalez-Ballester D, Casero D, Cokus S, Pellegrini M, Merchant SS, Grossman AR: RNA-seq analysis of sulfur-deprived Chlamydomonas cells reveals aspects of acclimation critical for cell survival. Plant Cell 2010,22(6):2058–2084.PubMedView Article
                  59. Liu HH, Tian X, Li YJ, Wu CA, Zheng CC: Microarray-based analysis of stress-regulated microRNAs in Arabidopsis thaliana. RNA 2008,14(5):836–843.PubMedView Article
                  60. Frazier TP, Sun G, Burklew CE, Zhang B: Salt and drought stresses induce the aberrant expression of microRNA genes in tobacco. Mol Biotechnol 2011,49(2):159–165.PubMedView Article
                  61. Jia X, Wang WX, Ren L, Chen QJ, Mendu V, Willcut B, Dinkins R, Tang X, Tang G: Differential and dynamic regulation of miR398 in response to ABA and salt stress in Populus tremula and Arabidopsis thaliana. Plant Mol Biol 2009,71(1–2):51–59.PubMedView Article
                  62. Dai X, Zhuang Z, Zhao PX: Computational analysis of miRNA targets in plants: current status and challenges. Brief Bioinform 2010,12(2):115–121.PubMedView Article
                  63. Jia X, Ren L, Chen QJ, Li R, Tang G: UV-B-responsive microRNAs in Populus tremula. J Plant Physiol 2009,166(18):2046–2057.PubMedView Article
                  64. Piriyapongsa J, Jordan IK: Dual coding of siRNAs and miRNAs by plant transposable elements. RNA 2008,14(5):814–821.PubMedView Article
                  65. Li Y, Li CQ, Xia J, Jin YX: Domestication of transposable elements into microRNA genes in plants. PLoS One 2011,6(5):e19212.PubMedView Article
                  66. Feschotte C, Jiang N, Wessler SR: Plant transposable elements: where genetics meets genomics. Nat Rev Genet 2002,3(5):329–341.PubMedView Article
                  67. Jurka J, Kapitonov VV, Pavlicek A, Klonowski P, Kohany O, Walichiewicz J: Repbase update, a database of eukaryotic repetitive elements. Cytogenet Genome Res 2005,110(1–4):462–467.PubMedView Article
                  68. Lee SB, Jung SJ, Go YS, Kim HU, Kim JK, Cho HJ, Park OK, Suh MC: Two Arabidopsis 3-ketoacyl CoA synthase genes, KCS20 and KCS2/DAISY, are functionally redundant in cuticular wax and root suberin biosynthesis, but differentially controlled by osmotic stress. Plant J 2009,60(3):462–475.PubMedView Article
                  69. Yan YS, Chen XY, Yang K, Sun ZX, Fu YP, Zhang YM, Fang RX: Overexpression of an F-box protein gene reduces abiotic stress tolerance and promotes root growth in rice. Mol Plant 2011,4(1):190–197.PubMedView Article
                  70. Garg R, Jhanwar S, Tyagi AK, Jain M: Genome-wide survey and expression analysis suggest diverse roles of glutaredoxin gene family members during development and response to various stimuli in rice. DNA Res 2010,17(6):353–367.PubMedView Article
                  71. Ghildiyal M, Seitz H, Horwich MD, Li CJ, Du TT, Lee S, Xu J, Kittler ELW, Zapp ML, Weng ZP, et al.: Endogenous siRNAs derived from transposons and mRNAs in Drosophila somatic cells. Science 2008,320(5879):1077–1081.PubMedView Article
                  72. Li R, Yu C, Li Y, Lam TW, Yiu SM, Kristiansen K, Wang J: SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 2009,25(15):1966–1967.PubMedView Article
                  73. Markham NR, Zuker M: UNAFold: software for nucleic acid folding and hybriziation. In Bioinformatics, Volume II Structure, Function and Applications. Edited by: Keith JM. Humana Press, Totowa, NJ; 2008:3–31.
                  74. Pearson WR: Flexible sequence similarity searching with the FASTA3 program package. Methods Mol Biol 2000, 132:185–219.PubMed
                  75. Kozomara A, Griffiths-Jones S: miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res 2011,39(Database issue):D152-D157.PubMedView Article
                  76. Enright AJ, John B, Gaul U, Tuschl T, Sander C, Marks DS: MicroRNA targets in Drosophila. Genome Biol 2003,5(1):R1.PubMedView Article
                  77. Fahlgren N, Howell MD, Kasschau KD, Chapman EJ, Sullivan CM, Cumbie JS, Givan SA, Law TF, Grant SR, Dangl JL, et al.: High-throughput sequencing of Arabidopsis microRNAs: evidence for frequent birth and death of MIRNA genes. PLoS One 2007,2(2):e219.PubMedView Article
                  78. Pall GS, Hamilton AJ: Improved northern blot method for enhanced detection of small RNA. Nat Protoc 2008,3(6):1077–1084.PubMedView Article

                  © Barrera-Figueroa et al.; licensee BioMed Central Ltd. 2012


Cutting deficits without damaging growth - Daily News Egypt

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Cutting deficits without damaging growth

Average public debt in MENA countries is more than 78% of GDP, and slower than projected growth or higher interest rates could put debt on an unsustainable path.

7-2 IMF blog By Masood Ahmed – IMF Blog

Governments in a number of countries in the Middle East and North Africa region face a growing need to take politically difficult steps to reduce large fiscal deficits. Reducing deficits is, of course, not an end in itself. But in many countries, deficits are so large that they will begin to hurt growth and financial stability. At the same time, measures to trim the deficit can have a negative effect on economic growth in the short run. So, the question is: what measures can policymeasures take to reduce budget deficits whilst minimising their negative impact on economic growth and vulnerable members of society?

In response to social demands and rising food and fuel prices, governments across the region have increased spending on subsidies and wages significantly over the past two years. Public revenues, however, have been declining for a variety of reasons, including the slowdown in regional economic activity. As a result, oil-importing countries in the Middle East and North Africa (MENA) have seen a large increase in their chronic budget deficits, which grew to an average of more than 8.5% of GDP in 2012 from about 5.5% in 2010.

Such an increase in fiscal imbalances is quite difficult to sustain over a long period of time. In fact, looking ahead, there is little room for additional government spending. Average public debt in MENA countries is more than 78% of GDP, and slower than projected growth or higher interest rates could put debt on an unsustainable path.

 Choosing the best path

Typically, deficit reduction calls for, on one hand, measures to increase government revenue and, on the other, measures cutting spending. Revenues can be increased either by raising tax rates or by broadening the tax base. The latter can be achieved by implementing reform measures to make the tax system more efficient and to address tax evasion and tax avoidance. Reducing government expenditure entails cuts in both current (non-interest) and capital spending.

Rebalancing the composition of revenues and expenditures may help lessen the adverse side effects of deficit cuts on growth. Figures 1 and 2 show selected tax and expenditure measures in MENA oil–importing countries, ranked by their short-term effect on output, with rankings derived from previous IMF analyses of advanced economies.

On the revenue side, property and sales taxes are the most growth-friendly measures for raising revenues. Trade and income taxes are the least growth-friendly. Egypt is among those oil-importing economies in the region with the greatest scope to rebalance taxes towards more growth-friendly instruments. Djibouti, Jordan, and Morocco are among those with less scope.

On the expenditure side, social benefits and subsidies are the least growth-friendly measures, whereas capital spending tends to be the most growth-friendly instrument. Spending, especially on subsidies, is largest in Egypt, Jordan, Lebanon, Morocco, and Tunisia, suggesting that there is scope to lower such spending as a growth-friendly instrument for fiscal consolidation. In contrast, productive capital spending is smallest for Lebanon, Sudan, and Tunisia, suggesting that there is space to increase such spending.

A key fiscal priority for the MENA region is to replace generalised subsidies with more targeted social safety net instruments. Besides being very costly, generalised subsidies do not support the poor effectively. For example, one-third of energy subsidies in Egypt benefit the wealthiest one-fifth of the population. Our research suggests that the situation is similar in many other countries in the region.

 Quality also matters

Improving the quality of government spending more generally is critical for responding to the aspirations and social needs of populations across MENA. This would help make room to boost investment spending and reduce fiscal deficits that are increasing debt levels and crowding out lending to the private sector.

Structural reform policies that aim to enhance the overall productivity of the economy and hence raise growth potential could also offset the negative impact of fiscal consolidation.

Successful implementation of these initiatives to both enhance the quality of spending and rebalance the composition of revenue-raising and expenditure should help create more and better employment opportunities, and lead to faster economic growth in the MENA region that would benefit all its inhabitants.

Masood Ahmed is Director of the IMF’s Middle East and Central Asia Department

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Short film explains why shoes dangle from electric wires

Have you ever seen shoes dangling from electric wire where you live? They’re a common phenomenon in many parts of the world. This interesting 14 minute documentary aims to get to the heart of this perplexing matter.

About the author

Gem is an explorer and documenter of the urban landscape.


Parents May Sue Over Yoga Lessons in Public Schools

Last month, half of the students attending classes in the Encinitas Union School District K-6 elementary schools in San Diego North County began taking Ashtanga (Sanskrit for "eight-limbed") yoga for 30 minutes twice per week. In January, the other half will begin the lessons.

Concerned parents have now retained constitutional first amendment attorney Dean Broyles, who says that Ashtanga yoga is a religious form of yoga, and that religious aspects have been introduced into the schools.

"The poses and positions are acknowledged by Ashtanga and Hindi yoga as forms of worship and prayers to Hindu deities," he told ABC News. "They have a spiritual and religious meaning behind them."

Broyles says that he brought up the matter at a Encinitas Union School District (EUSD) trustees meeting, along with 60 concerned parents, on October 9. Now the EUSD trustees will be reviewing whether the grant money violates the religious freedom of students and parents.

The yoga, which is being taught in all nine of the schools in the district, is being funded by a $533,000 grant from the Jois Foundation, a nonprofit that promotes Ashtanga yoga across the world. All of the instructors teaching the students are certified and trained by the Jois Foundation in Ashtanga yoga.

Broyles points to hedge-fund billionaire Paul Tudor Jones and his wife Sonia Jones, who is a known dedicated disciple of Sri Pattabhi Jois, the recently deceased master of Ashtanga yoga, as the money behind the EUSD yoga program. The district's program will be studied by the University of Virginia and University of San Diego to look at benefits of Ashtanga yoga, as outlined in a letter sent to parents by EUSD Superintendent Tim Baird.

The Tudor Joneses, Broyles says, were instrumental in the founding of the Jois Foundation and put up the money for the EUSD Ashtanga yoga grant. He says that parents are now not only questioning Hindu religion entering their schools, but the validity if this study being undertaken.

Baird told ABC News that he completely disagree that the school district is teaching religion.

"Yoga is a physical activity that's completely mainstream," Baird told ABC News. "It's done in universities and churches around the world. I understand it has a cultural heritage coming from India, and there are people that use yoga in their religious practices … We are creating lesson plans in kid-friendly language that is really redesigning the program. We are not using cultural references. We are not using Sanskrit. We've changed the names to gorilla pose, and mountain pose."

Broyles says that though it has been argued that the in-school yoga programs have been stripped of their spirituality, he thinks that kids in EUSD are being exposed to Hindu thought and belief within the school.

"On the wall there was a poster that showed the Ashtanga. There are words showing what the limbs are," he said. "The ultimate goal is to be absorbed into the universe, which is called Samadhi. They had a poster depicting that. Fundamentally it is a Hindu religion being taught through Ashtanga yoga."

Baird told ABC News that there are no Hindu figures on the wall.

Parents also raised specific concerns about the program aside from the religious aspects, saying that the fact that kids are taking 60 minutes of the 100 minutes per week allotted for physical education to do yoga is inappropriate. Broyles said that for 40 minutes per week the kids are not getting PE, and that they're not offering anything for kids that are opting out of the program.

Baird told ABC News that only 3 to 4 families at each school have opted their child out of the program, and that those students are using the time for a variety of other activities that differs from school to school.

Broyles says that there are some yoga enthusiasts in favor of the program; he says that people in the district don't really understand eastern mysticism, yoga's roots in Hinduism, and what's being taught.

"If we were introducing Christian worship of bowing, there would be outcry in the community," he said. "Allowing our public schools to actively promote the beliefs and practices of one religion over others to young impressionable children sets a dangerous precedent."


Governor’s Budget Earns High Marks, But Active Transportation Shutout from Cap and Trade Funds

Yesterday, Governor Jerry Brown officially unveiled his budget after days of speculation and leaked reports to newspapers. One of the highlights of the budget is how Brown proposes to spend the “Cap and Trade”* funds. Last year, the state borrowed against these funds to fill a gap in the general operating budget. This year, with $100 million “borrowed” from last year returned, the Cap and Trade allocation was a cool $850 million for projects that will improve air quality through green energy initiatives.*

The Natural Resources Defense Council was similarly excited by the proposed budget. In a post entitled “Carbon Pollution Funds Poised to Deliver on Clean Energy in California” on the Switchboard blog site, Alex Jackson praises the budget for spending Cap and Trade funds in a variety of ways that will reduce pollution and the state’s carbon footprint.

But not everyone was thrilled with the budget. Despite spending the Cap and Trade funds on promoting clean energy, the cleanest forms of transportation, walking and bicycling don’t have their own budget line in the Cap and Trade allocation. True the overall proposed state budget includes a $9 million allocation for the Active Transportation Program, but when it comes to Cap and Trade, bicycle and pedestrian programs will compete for a slice of the $100 million for “Implementing Regional Sustainable Communities Strategies” with housing, planning, land-use, transit oriented development and other worthy livability programs.

“The Transportation Agency has worked productively with statewide walking and biking organizations to create a new Active Transportation Program that is prepared to invest in these modes at a scale never seen before in California,” writes Eric Bruins with the Los Angeles County Bicycle Coalition. “It is disappointing that no cap-and-trade funds are allocated to the ATP, despite everyone’s work to set it up for that purpose.  Hopefully the Legislature will again support walking and biking by directing significant cap-and-trade revenues to the most cost-effective, green transportation modes.”

There are three possible strategies to help close the bicycle and pedestrian gap in state funding. A paltry $9 million of a $1.7 billion seems like an awfully minor investment for a state with 60 million documented residents. Sadly, the $9 million is actually an increase from past budget proposals.

The first would be to create a budget line for active transportation projects in the Cap and Trade allocation. This is the preferred option for many bicycle and pedestrian advocacy groups as it locks in these funds which are often a lower priority for decision makers at the state level.

 The other option is to increase the funding to the “Implementing Regional Sustainable Community Strategies” budget line. Not all of the funds “borrowed” last year for the general fund were returned, and the state still owes the Cap and Trade programs a $400 million. Returning those funds would make a huge difference in the state’s eventual bicycle and pedestrian program for the next fiscal year.
A third option would be to move funds from another Cap and Trade Budget line in to the Implementing Regional Sustainable Community Strategies from somewhere else. Here is a breakdown of how Brown wants to spend those funds, again from the NRDC:

The largest pot of funds is the “rail modernization” budget, a quarter of a billion of which is set to go to High Speed Rail implementation. At the independent California High Speed Rail Blog, Robert Cruikshank is happy to see the state stepping up for High Speed Rail and is angry at some of the pushback, he writes:

So why on earth would environmentalists help their enemies attack a major method of reducing carbon emissions? Why would they hand the right and climate deniers a new line of attack, that it’s somehow inappropriate to use cap-and-trade funds for anything that lasts beyond 2020 when the entire point of AB 32 and cap-and-trade is to achieve long-term reductions?

I am truly stunned at this. California environmentalists should be smarter than this. They need to abandon these claims that it’s somehow wrong for cap-and-trade funds to be used on HSR. And Governor Jerry Brown needs to stick to his guns on this, because he is absolutely right.

While Streetsblog has never been interested in dividing sustainable community and high speed rail advocates, there is a valid argument that High Speed Rail shouldn’t absorb so much funds to the detriment of local programs. Earlier this week Niall Huffman addressed this issue in an op/ed published by Streetsblog.

To have HSR stifle potential increases in bike, pedestrian and transit funding would be a missed opportunity, because HSR generally doesn’t serve the neighborhoods and jobs corridors where we do the vast majority of our daily travel. According to a report  (pdf link) by Safe Routes to School National Partnership, about half of all trips in Los Angeles County are three miles or less. Shouldn’t we be putting at least as much of our resources into shifting these trips away from driving as we are into providing another option for the occasional LA-to-San Francisco haul, which for most people is a once- or twice-a-year proposition?

In the end, there is little argument that the current proposed budget, with Cap and Trade Funds restored with some payback from past raids and an increased Active Transportation Program is a step forward from previous efforts. However, with the state facing self-ipmosed deadlines to reduce greenhouse gas emissions by 2020, the question is whether it made a big enough step and if it’s moving in the most efficient direction.

The “cap” in “cap and trade” sets a limit on emissions, which is lowered over time to reduce the amount of pollutants released into the atmosphere. The “trade” creates a market for carbon allowances, helping companies innovate in order to meet, or come in under, their allocated limit. The less they emit, the less they pay. Cap and trade theoretically  creates an economic incentive to pollute less and creates a new revenue stream that California uses to promote other green energy programs.


Energy and the Environment (AMME5101)

This unit is suitable for any engineering discipline student who is interested in developing an understanding of analysis and design in energy, power generation, environment and relevant economic issues. The aim is to acquaint students with the methods engineers use to design and evaluate the thermal processes used for the production of electricity. It also assesses and deals with the environmental consequences of power generation. At the end of this unit students will be able to carry out preliminary design and economic impact analyses for electrical power generation systems.
A series of topics will be covered in relation to energy and electricity and relevant issues. The course contents will include:

1. Economic analysis of energy systems;
2. Environmental impact of power generation;
3. Principles of thermodynamics;
4. First law analysis of power cycles;
5. Design and simulation of power generation cycles;
6. Second law efficiency and availability;
7. Energy efficiency;
8. CO2 capture and sequestration;
9. Design of various components of thermal power plants.

Our courses that offer this unit of study

Further unit of study information

Lecture 2 hrs/week; Tutorial 2 hrs/week; Project Work - own time 2 hrs/week.

Through semester assessment (100%)

Faculty/department permission required?

Unit of study rules

Prerequisites and assumed knowledge

24 credits of 3000-level or above units of study

Study this unit outside a degree

Non-award/non-degree study

Cross-institutional study


Castle Battle

Destroy enemy's castle or build your castle to 100 points to win.

You have three types of units: builders, warriors and wizards.
Builders produce bricks, warriors make weapons and wizards create scrolls.
Each unit creates one item every turn so it's important to have as many units as you can.

You can play one card per turn to recruit new units, collect more resources, improve your defense or attack your enemy. If you cannot (or don't want to) play any card you can discard up to three cards instead.
Good luck!

Tags: castle conflict , castle wars , castle war , battle castle , castle battle , castle war español , castle , castlewars , how to beat castle wars

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Contrary (logic)

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Halls max drops

Active Ingredients   (in each drop): Benzocaine 6mg, Menthol 10mg

Purpose:   Oral anesthetic

Uses:   temporarily relieves occasional: ·minor irritation ·sore throat

Stop use and ask a doctor if ·sore mouth symptoms do not improve in 7 days ·irritation, pain or redness persists or worsens

Keep out of reach of children. In case of overdose, get medical help or contact a Poison Control Center right away. If you are pregnant or breast feeding ask a health professional before use.

Directions:   ·adults and children 5 years and over: dissolve 1 or 2 drops (one at a time) slowly in the mouth. Repeat every 2 hours as needed. ·children under 5 years of age: ask a doctor

Inactive Ingredients:   MENTHOL: corn syrup, FD&C blue no. 1, FD&C red no. 40, propylene glycol, sodium bicarbonate, sucrose, water. CHERRY: corn syrup, flavor, propylene glycol, sodium bicarbonate, sucrose, water. HONEY-LEMON: beta carotene, corn syrup, flavors, propylene glycol, sodium bicarbonate, soy lecithin, sucrose, water.

How Supplied

Halls Max™ Menthol/Benzocaine Oral Anesthetic are available in packages of 18. They are available in three flavors: Cherry, Menthol and Honey-Lemon.


Nasal Cartilage Cells Can Replace Joint Cartilage

Cartilage regeneration and tissue engineering has proven more difficult than initially expected. It is a tissue with a deceptively complex structure, in which important mechanical properties necessary to its load-bearing role are derived from the details of that structure. Simply culturing cartilage cells is far from enough to produce a useful end result, and researchers have only recently made inroads into producing tissue engineered cartilage that is somewhat like the real thing. In this work a novel approach is taken to produce grafts for injured joint cartilage:

Cartilage lesions in joints often appear in older people as a result of degenerative processes. However, they also regularly affect younger people after injuries and accidents. Such defects are difficult to repair and often require complicated surgery and long rehabilitation times. A new treatment option has now been presented by a research team: nasal cartilage cells can replace cartilage cells in joints.

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