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      Genome-wide comparison of microRNAs and their targeted transcripts among leaf, flower and fruit of sweet orange

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          Abstract

          Background

          In plants, microRNAs (miRNAs) regulate gene expression mainly at the post-transcriptional level. Previous studies have demonstrated that miRNA-mediated gene silencing pathways play vital roles in plant development. Here, we used a high-throughput sequencing approach to characterize the miRNAs and their targeted transcripts in the leaf, flower and fruit of sweet orange.

          Results

          A total of 183 known miRNAs and 38 novel miRNAs were identified. An in-house script was used to identify all potential secondary siRNAs derived from miRNA-targeted transcripts using sRNA and degradome sequencing data. Genome mapping revealed that these miRNAs were evenly distributed across the genome with several small clusters, and 69 pre-miRNAs were co-localized with simple sequence repeats (SSRs). Noticeably, the loop size of pre-miR396c was influenced by the repeat number of CUU unit. The expression pattern of miRNAs among different tissues and developmental stages were further investigated by both qRT-PCR and RNA gel blotting. Interestingly, Csi-miR164 was highly expressed in fruit ripening stage, and was validated to target a NAC transcription factor. This study depicts a global picture of miRNAs and their target genes in the genome of sweet orange, and focused on the comparison among leaf, flower and fruit tissues.

          Conclusions

          This study provides a global view of miRNAs and their target genes in different tissue of sweet orange, and focused on the identification of miRNA involved in the regulation of fruit ripening. The results of this study lay a foundation for unraveling key regulators of orange fruit development and ripening on post-transcriptional level.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1471-2164-15-695) contains supplementary material, which is available to authorized users.

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          Most cited references 50

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          A diverse and evolutionarily fluid set of microRNAs in Arabidopsis thaliana.

          To better understand the diversity of small silencing RNAs expressed in plants, we employed high-throughput pyrosequencing to obtain 887,000 reads corresponding to Arabidopsis thaliana small RNAs. They represented 340,000 unique sequences, a substantially greater diversity than previously obtained in any species. Most of the small RNAs had the properties of heterochromatic small interfering RNAs (siRNAs) associated with DNA silencing in that they were preferentially 24 nucleotides long and mapped to intergenic regions. Their density was greatest in the proximal and distal pericentromeric regions, with only a slightly preferential propensity to match repetitive elements. Also present were 38 newly identified microRNAs (miRNAs) and dozens of other plausible candidates. One miRNA mapped within an intron of DICER-LIKE 1 (DCL1), suggesting a second homeostatic autoregulatory mechanism for DCL1 expression; another defined the phase for siRNAs deriving from a newly identified trans-acting siRNA gene (TAS4); and two depended on DCL4 rather than DCL1 for their accumulation, indicating a second pathway for miRNA biogenesis in plants. More generally, our results revealed the existence of a layer of miRNA-based control beyond that found previously that is evolutionarily much more fluid, employing many newly emergent and diverse miRNAs, each expressed in specialized tissues or at low levels under standard growth conditions.
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            Specific effects of microRNAs on the plant transcriptome.

            Most plant microRNAs (miRNAs) have perfect or near-perfect complementarity with their targets. This is consistent with their primary mode of action being cleavage of target mRNAs, similar to that induced by perfectly complementary small interfering RNAs (siRNAs). However, there are natural targets with up to five mismatches. Furthermore, artificial siRNAs can have substantial effects on so-called off-targets, to which they have only limited complementarity. By analyzing the transcriptome of plants overexpressing different miRNAs, we have deduced a set of empirical parameters for target recognition. Compared to artificial siRNAs, authentic plant miRNAs appear to have much higher specificity, which may reflect their coevolution with the remainder of the transcriptome. We also demonstrate that miR172, previously thought to act primarily by translational repression, can efficiently guide mRNA cleavage, although the effects on steady-state levels of target transcripts are obscured by strong feedback regulation. This finding unifies the view of plant miRNA action.
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              Protocol: a highly sensitive RT-PCR method for detection and quantification of microRNAs

              MicroRNAs (miRNAs) are a class of small non-coding RNAs with a critical role in development and environmental responses. Efficient and reliable detection of miRNAs is an essential step towards understanding their roles in specific cells and tissues. However, gel-based assays currently used to detect miRNAs are very limited in terms of throughput, sensitivity and specificity. Here we provide protocols for detection and quantification of miRNAs by RT-PCR. We describe an end-point and real-time looped RT-PCR procedure and demonstrate detection of miRNAs from as little as 20 pg of plant tissue total RNA and from total RNA isolated from as little as 0.1 μl of phloem sap. In addition, we have developed an alternative real-time PCR assay that can further improve specificity when detecting low abundant miRNAs. Using this assay, we have demonstrated that miRNAs are differentially expressed in the phloem sap and the surrounding vascular tissue. This method enables fast, sensitive and specific miRNA expression profiling and is suitable for facilitation of high-throughput detection and quantification of miRNA expression.
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                Author and article information

                Contributors
                whitepig1989@163.com
                wanglun@webmail.hzau.edu.cn
                chendijun@zju.edu.cn
                ema@webmail.hzau.edu.cn
                hdh016@126.com
                llchen@mail.hzau.edu.cn
                ll37@cornell.edu
                xxdeng@mail.hzau.edu.cn
                xuqiang@mail.hzau.edu.cn
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                20 August 2014
                20 August 2014
                2014
                : 15
                : 1
                Affiliations
                [ ]Key Laboratory of Horticultural Plant Biology of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070 China
                [ ]Center for Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
                [ ]Robert W. Holley Center for Agriculture and Health, Cornell University, Ithaca, NY 14853 USA
                Article
                6413
                10.1186/1471-2164-15-695
                4158063
                25142253
                © Liu et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

                Genetics

                fruit ripening, genome-wide comparison, degraded transcript, mirna, citrus sinensis

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