Guilherme Loss-Morais

MicroRNAs play critical roles during plant development and in response to abiotic stresses

MicroRNAs (miRNAs) have been identified as key molecules in regulatory networks. The fine-tuning role of miRNAs in addition to the regulatory role of transcription factors has shown that molecular events during development are tightly regulated. In addition, several miRNAs play crucial roles in the response to abiotic stress induced by drought, salinity, low temperatures, and metals such as aluminium. Interestingly, several miRNAs have overlapping roles with regard to development, stress responses, and nutrient homeostasis. Moreover, in response to the same abiotic stresses, different expression patterns for some conserved miRNA families among different plant species revealed different metabolic adjustments. The use of deep sequencing technologies for the characterisation of miRNA frequency and the identification of new miRNAs adds complexity to regulatory networks in plants. In this review, we consider the regulatory role of miRNAs in plant development and abiotic stresses, as well as the impact of deep sequencing technologies on the generation of miRNA data.

Identifying conserved and novel microRNAs in developing seeds of Brassica napus using deep sequencing.

MicroRNAs (miRNAs) are important post-transcriptional regulators of plant development and seed formation. In Brassica napus, an important edible oil crop, valuable lipids are synthesized and stored in specific seed tissues during embryogenesis. The miRNA transcriptome of B. napus is currently poorly characterized, especially at different seed developmental stages. This work aims to describe the miRNAome of developing seeds of B. napus by identifying plant-conserved and novel miRNAs and comparing miRNA abundance in mature versus developing seeds. Members of 59 miRNA families were detected through a computational analysis of a large number of reads obtained from deep sequencing two small RNA and two RNA-seq libraries of (i) pooled immature developing stages and (ii) mature B. napus seeds. Among these miRNA families, 17 families are currently known to exist in B. napus; additionally 29 families not reported in B. napus but conserved in other plant species were identified by alignment with known plant mature miRNAs. Assembled mRNA-seq contigs allowed for a search of putative new precursors and led to the identification of 13 novel miRNA families. Analysis of miRNA population between libraries reveals that several miRNAs and isomiRNAs have different abundance in developing stages compared to mature seeds. The predicted miRNA target genes encode a broad range of proteins related to seed development and energy storage. This work presents a comparative study of the miRNA transcriptome of mature and developing B. napus seeds and provides a basis for future research on individual miRNAs and their functions in embryogenesis, seed maturation and lipid accumulation in B. napus.

Identifying MicroRNAs and Transcript Targets in Jatropha Seeds

MicroRNAs, or miRNAs, are endogenously encoded small RNAs that play a key role in diverse plant biological processes. Jatropha curcas L. has received significant attention as a potential oilseed crop for the production of renewable oil. Here, a sRNA library of mature seeds and three mRNA libraries from three different seed development stages were generated by deep sequencing to identify and characterize the miRNAs and pre-miRNAs of J. curcas. Computational analysis was used for the identification of 180 conserved miRNAs and 41 precursors (pre-miRNAs) as well as 16 novel pre-miRNAs. The predicted miRNA target genes are involved in a broad range of physiological functions, including cellular structure, nuclear function, translation, transport, hormone synthesis, defense, and lipid metabolism. Some pre-miRNA and miRNA targets vary in abundance between the three stages of seed development. A search for sequences that produce siRNA was performed, and the results indicated that J. curcas siRNAs play a role in nuclear functions, transport, catalytic processes and disease resistance. This study presents the first large scale identification of J. curcas miRNAs and their targets in mature seeds based on deep sequencing, and it contributes to a functional understanding of these miRNAs.

Identification of microRNAs from Eugenia uniflora by high-throughput sequencing and bioinformatics analysis.

Background microRNAs or miRNAs are small non-coding regulatory RNAs that play important functions in the regulation of gene expression at the post-transcriptional level by targeting mRNAs for degradation or inhibiting protein translation. Eugenia uniflora is a plant native to tropical America with pharmacological and ecological importance, and there have been no previous studies concerning its gene expression and regulation. To date, no miRNAs have been reported in Myrtaceae species. Results Small RNA and RNA-seq libraries were constructed to identify miRNAs and pre-miRNAs in Eugenia uniflora. Solexa technology was used to perform high throughput sequencing of the library, and the data obtained were analyzed using bioinformatics tools. From 14,489,131 small RNA clean reads, we obtained 1,852,722 mature miRNA sequences representing 45 conserved families that have been identified in other plant species. Further analysis using contigs assembled from RNA-seq allowed the prediction of secondary structures of 25 known and 17 novel pre-miRNAs. The expression of twenty-seven identified miRNAs was also validated using RT-PCR assays. Potential targets were predicted for the most abundant mature miRNAs in the identified pre-miRNAs based on sequence homology. Conclusions This study is the first large scale identification of miRNAs and their potential targets from a species of the Myrtaceae family without genomic sequence resources. Our study provides more information about the evolutionary conservation of the regulatory network of miRNAs in plants and highlights species-specific miRNAs.

RFMirTarget: Predicting Human MicroRNA Target Genes with a Random Forest Classifier

MicroRNAs are key regulators of eukaryotic gene expression whose fundamental role has already been identified in many cell pathways. The correct identification of miRNAs targets is still a major challenge in bioinformatics and has motivated the development of several computational methods to overcome inherent limitations of experimental analysis. Indeed, the best results reported so far in terms of specificity and sensitivity are associated to machine learning-based methods for microRNA-target prediction. Following this trend, in the current paper we discuss and explore a microRNA-target prediction method based on a random forest classifier, namely RFMirTarget. Despite its well-known robustness regarding general classifying tasks, to the best of our knowledge, random forest have not been deeply explored for the specific context of predicting microRNAs targets. Our framework first analyzes alignments between candidate microRNA-target pairs and extracts a set of structural, thermodynamics, alignment, seed and position-based features, upon which classification is performed. Experiments have shown that RFMirTarget outperforms several well-known classifiers with statistical significance, and that its performance is not impaired by the class imbalance problem or features correlation. Moreover, comparing it against other algorithms for microRNA target prediction using independent test data sets from TarBase and starBase, we observe a very promising performance, with higher sensitivity in relation to other methods. Finally, tests performed with RFMirTarget show the benefits of feature selection even for a classifier with embedded feature importance analysis, and the consistency between relevant features identified and important biological properties for effective microRNA-target gene alignment.

Comprehensive selection of reference genes for quantitative gene expression analysis during seed development in Brassica napus

Key messageMicroRNAs have higher expression stability than protein-coding genes inB. napusseeds and are therefore good reference genes for miRNA and mRNA RT-qPCR analysis.AbstractReverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) has become the “gold standard” to gain insight into function of genes. However, the accuracy of the technique depends on appropriate reference genes for quantification analysis in different experimental conditions. Accumulation of microRNAs (miRNAs) has also been studied by RT-qPCR, but there are no reference genes currently validated for normalization of Brassica napus miRNA expression data. In this study, we selected 43 B. napus miRNAs and 18 previously validated mRNA reference genes. The expression stability of the candidate reference genes was evaluated in different tissue samples (stages of seed development, flowers, and leaves) using geNorm, NormFinder, and RefFinder analysis. The best-ranked reference genes for expression studies during seed development (miR167-1_2, miR11-1, miR159-1 and miR168-1) were used to asses the expression of miR03-1. Since candidate miRNAs showed higher expression stability than protein-coding genes in most of the tested conditions, the expression profile of DGAT1 gene was compared when normalized by the four most stable miRNAs reference genes and by the four most stable mRNA reference genes. The expected expression pattern of DGAT1 during seed development was achieved with the use of miRNA as reference genes. In conclusion, the most stable miRNA reference genes can be employed in the normalization of RT-qPCR quantification of miRNAs and protein-coding genes. This work is the first to perform a comprehensive survey of the stability of miRNA reference genes in B. napus and provides guidelines to obtain more accurate RT-qPCR results in B. napus seeds studies.

Analysis of castor bean ribosome-inactivating proteins and their gene expression during seed development

Ribosome-inactivating proteins (RIPs) are enzymes that inhibit protein synthesis after depurination of a specific adenine in rRNA. The RIP family members are classified as type I RIPs that contain an RNA-N-glycosidase domain and type II RIPs that contain a lectin domain (B chain) in addition to the glycosidase domain (A chain). In this work, we identified 30 new plant RIPs and characterized 18 Ricinus communis RIPs. Phylogenetic and functional divergence analyses indicated that the emergence of type I and II RIPs probably occurred before the monocot/eudicot split. We also report the expression profiles of 18 castor bean genes, including those for ricin and agglutinin, in five seed stages as assessed by quantitative PCR. Ricin and agglutinin were the most expressed RIPs in developing seeds although eight other RIPs were also expressed. All of the RIP genes were most highly expressed in the stages in which the endosperm was fully expanded. Although the reason for the large expansion of RIP genes in castor beans remains to be established, the differential expression patterns of the type I and type II members reinforce the existence of biological functions other than defense against predators and herbivory.

Identification of novel and conserved microRNAs in Coffea canephora and Coffea arabica

As microRNAs (miRNAs) are important regulators of many biological processes, a series of small RNAomes from plants have been produced in the last decade. However, miRNA data from several groups of plants are still lacking, including some economically important crops. Here microRNAs from Coffea canephora leaves were profiled and 58 unique sequences belonging to 33 families were found, including two novel microRNAs that have never been described before in plants. Some of the microRNA sequences were also identified in Coffea arabica that, together with C. canephora, correspond to the two major sources of coffee production in the world. The targets of almost all miRNAs were also predicted on coffee expressed sequences. This is the first report of novel miRNAs in the genus Coffea, and also the first in the plant order Gentianales. The data obtained establishes the basis for the understanding of the complex miRNA-target network on those two important crops.

Diversity and evolution of plant diacylglycerol acyltransferase (DGATs) unveiled by phylogenetic, gene structure and expression analyses.

Abstract Since the first diacylglycerol acyltransferase (DGAT) gene was characterized in plants, a number of studies have focused on understanding the role of DGAT activity in plant triacylglycerol (TAG) biosynthesis. DGAT enzyme is essential in controlling TAGs synthesis and is encoded by different genes. DGAT1 and DGAT2 are the two major types of DGATs and have been well characterized in many plants. On the other hand, the DGAT3 and WS/DGAT have received less attention. In this study, we present the first general view of the presence of putative DGAT3 and WS/DGAT in several plant species and report on the diversity and evolution of these genes and its relationships with the two main DGAT genes (DGAT1 and DGAT2). According to our analyses DGAT1, DGAT2, DGAT3 and WS/DGAT are very divergent genes and may have distinct origin in plants. They also present divergent expression patterns in different organs and tissues. The maintenance of several types of genes encoding DGAT enzymes in plants demonstrates the importance of DGAT activity for TAG biosynthesis. Evolutionary history studies of DGATs coupled with their expression patterns help us to decipher their functional role in plants, helping to drive future biotechnological studies.