154 research outputs found

    Genome-wide profiling of uncapped mRNA

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    Gene transcripts are under extensive posttranscriptional regulation, including the regulation of their stability. A major route for mRNA degradation produces uncapped mRNAs, which can be generated by decapping enzymes, endonucleases, and small RNAs. Profiling uncapped mRNA molecules is important for the understanding of the transcriptome, whose composition is determined by a balance between mRNA synthesis and degradation. In this chapter, we describe a method to profile these uncapped mRNAs at the genome scale

    PlantNATsDB: a comprehensive database of plant natural antisense transcripts

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    Natural antisense transcripts (NATs), as one type of regulatory RNAs, occur prevalently in plant genomes and play significant roles in physiological and pathological processes. Although their important biological functions have been reported widely, a comprehensive database is lacking up to now. Consequently, we constructed a plant NAT database (PlantNATsDB) involving approximately 2 million NAT pairs in 69 plant species. GO annotation and high-throughput small RNA sequencing data currently available were integrated to investigate the biological function of NATs. PlantNATsDB provides various user-friendly web interfaces to facilitate the presentation of NATs and an integrated, graphical network browser to display the complex networks formed by different NATs. Moreover, a ‘Gene Set Analysis’ module based on GO annotation was designed to dig out the statistical significantly overrepresented GO categories from the specific NAT network. PlantNATsDB is currently the most comprehensive resource of NATs in the plant kingdom, which can serve as a reference database to investigate the regulatory function of NATs. The PlantNATsDB is freely available at http://bis.zju.edu.cn/pnatdb/

    A Combined Approach of High-Throughput Sequencing and Degradome Analysis Reveals Tissue Specific Expression of MicroRNAs and Their Targets in Cucumber

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    MicroRNAs (miRNAs) are endogenous small RNAs playing an important regulatory function in plant development and stress responses. Among them, some are evolutionally conserved in plant and others are only expressed in certain species, tissue or developmental stages. Cucumber is among the most important greenhouse species in the world, but only a limited number of miRNAs from cucumber have been identified and the experimental validation of the related miRNA targets is still lacking. In this study, two independent small RNA libraries from cucumber leaves and roots were constructed, respectively, and sequenced with the high-throughput Illumina Solexa system. Based on sequence similarity and hairpin structure prediction, a total of 29 known miRNA families and 2 novel miRNA families containing a total of 64 miRNA were identified. QRT-PCR analysis revealed that some of the cucumber miRNAs were preferentially expressed in certain tissues. With the recently developed ‘high throughput degradome sequencing’ approach, 21 target mRNAs of known miRNAs were identified for the first time in cucumber. These targets were associated with development, reactive oxygen species scavenging, signaling transduction and transcriptional regulation. Our study provides an overview of miRNA expression profile and interaction between miRNA and target, which will help further understanding of the important roles of miRNAs in cucumber plants

    Comparative analysis of miRNAs and their targets across four plant species

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    BACKGROUND: MicroRNA (miRNA) mediated regulation of gene expression has been recognized as a major posttranscriptional regulatory mechanism also in plants. We performed a comparative analysis of miRNAs and their respective gene targets across four plant species: Arabidopsis thaliana (Ath), Medicago truncatula(Mtr), Brassica napus (Bna), and Chlamydomonas reinhardtii (Cre). RESULTS: miRNAs were obtained from mirBase with 218 miRNAs for Ath, 375 for Mtr, 46 for Bna, and 73 for Cre, annotated for each species respectively. miRNA targets were obtained from available database annotations, bioinformatic predictions using RNAhybrid as well as predicted from an analysis of mRNA degradation products (degradome sequencing) aimed at identifying miRNA cleavage products. On average, and considering both experimental and bioinformatic predictions together, every miRNA was associated with about 46 unique gene transcripts with considerably variation across species. We observed a positive and linear correlation between the number miRNAs and the total number of transcripts across different plant species suggesting that the repertoire of miRNAs correlates with the size of the transcriptome of an organism. Conserved miRNA-target pairs were found to be associated with developmental processes and transcriptional regulation, while species-specific (in particular, Ath) pairs are involved in signal transduction and response to stress processes. Conserved miRNAs have more targets and higher expression values than non-conserved miRNAs. We found evidence for a conservation of not only the sequence of miRNAs, but their expression levels as well. CONCLUSIONS: Our results support the notion of a high birth and death rate of miRNAs and that miRNAs serve many species specific functions, while conserved miRNA are related mainly to developmental processes and transcriptional regulation with conservation operating at both the sequence and expression level

    Cloning and Characterization of Maize miRNAs Involved in Responses to Nitrogen Deficiency

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    Although recent studies indicated that miRNAs regulate plant adaptive responses to nutrient deprivation, the functional significance of miRNAs in adaptive responses to nitrogen (N) limitation remains to be explored. To elucidate the molecular biology underlying N sensing/signaling in maize, we constructed four small RNA libraries and one degradome from maize seedlings exposed to N deficiency. We discovered a total of 99 absolutely new loci belonging to 47 miRNA families by small RNA deep sequencing and degradome sequencing, as well as 9 new loci were the paralogs of previously reported miR169, miR171, and miR398, significantly expanding the reported 150 high confidence genes within 26 miRNA families in maize. Bioinformatic and subsequent small RNA northern blot analysis identified eight miRNA families (five conserved and three newly identified) differentially expressed under the N-deficient condition. Predicted and degradome-validated targets of the newly identified miRNAs suggest their involvement in a broad range of cellular responses and metabolic processes. Because maize is not only an important crop but is also a genetic model for basic biological research, our research contributes to the understanding of the regulatory roles of miRNAs in plant adaption to N-deficiency stress

    Computational identification of condition-specific miRNA targets based on gene expression profiles and sequence information

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    <p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are small and noncoding RNAs that play important roles in various biological processes. They regulate target mRNAs post-transcriptionally through complementary base pairing. Since the changes of miRNAs affect the expression of target genes, the expression levels of target genes in specific biological processes could be different from those of non-target genes. Here we demonstrate that gene expression profiles contain useful information in separating miRNA targets from non-targets.</p> <p>Results</p> <p>The gene expression profiles related to various developmental processes and stresses, as well as the sequences of miRNAs and mRNAs in <it>Arabidopsis</it>, were used to determine whether a given gene is a miRNA target. It is based on the model combining the support vector machine (SVM) classifier and the scoring method based on complementary base pairing between miRNAs and mRNAs. The proposed model yielded low false positive rate and retrieved condition-specific candidate targets through a genome-wide screening.</p> <p>Conclusion</p> <p>Our approach provides a novel framework into screening target genes by considering the gene regulation of miRNAs. It can be broadly applied to identify condition-specific targets computationally by embedding information of gene expression profiles.</p

    Detection of MicroRNA processing intermediates through RNA ligation approaches

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    MicroRNAs (miRNA) are small RNAs of 20–22 nt that regulate diverse biological pathways through the modulation of gene expression. miRNAs recognize target RNAs by base complementarity and guide them to degradation or translational arrest. They are transcribed as longer precursors with extensive secondary structures. In plants, these precursors are processed by a complex harboring DICER-LIKE1 (DCL1), which cuts on the precursor stem region to release the mature miRNA together with the miRNA*. In both plants and animals, the miRNA precursors contain spatial clues that determine the position of the miRNA along their sequences. DCL1 is assisted by several proteins, such as the double-stranded RNA binding protein, HYPONASTIC LEAVES1 (HYL1), and the zinc finger protein SERRATE (SE). The precise biogenesis of miRNAs is of utter importance since it determines the exact nucleotide sequence of the mature small RNAs and therefore the identity of the target genes. miRNA processing itself can be regulated and therefore can determine the final small RNA levels and activity. Here, we describe methods to analyze miRNA processing intermediates in plants. These approaches can be used in wild-type or mutant plants, as well as in plants grown under different conditions, allowing a molecular characterization of the miRNA biogenesis from the RNA precursor perspective.Fil: Moro, BelĂ©n. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Rosario. Instituto de BiologĂ­a Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias BioquĂ­micas y FarmacĂ©uticas. Instituto de BiologĂ­a Molecular y Celular de Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias BioquĂ­micas y FarmacĂ©uticas; ArgentinaFil: Rojas, Arantxa Maria Larisa. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Rosario. Instituto de BiologĂ­a Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias BioquĂ­micas y FarmacĂ©uticas. Instituto de BiologĂ­a Molecular y Celular de Rosario; ArgentinaFil: Palatnik, Javier Fernando. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Rosario. Instituto de BiologĂ­a Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias BioquĂ­micas y FarmacĂ©uticas. Instituto de BiologĂ­a Molecular y Celular de Rosario; Argentina. Universidad Nacional de Rosario. Centro de Estudios Interdisciplinarios; Argentin
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