Target prediction is generally the first step towards recognition of bona fide microRNA-target interactions in living cells. Several target prediction tools are now available, which use distinct criteria and stringency to provide the best set of candidate targets for a single microRNA or a subset of microRNAs. However, there are many false-negative predictions, and consensus about the optimum strategy to select and use the output information provided by the target prediction tools is lacking. We compared the performance of four tools cited in literature—TargetScan, miRanda-mirSVR, Pita, and RNA22, and we determined the most effective approach for analyzing target prediction data (individual, union or intersection). For this purpose, we calculated the sensitivity, specificity, precision, and correlation of these approaches using 10 microRNAs (miR-1-3p, miR-17-5p, miR-21-5p, miR-24-3p, miR-29a-3p, miR-34a-5p, miR-124-3p, miR-125b-5p, miR-145-5p, and miR-155-5p) and 1,400 genes (700 validated and 700 non-validated) as targets of these microRNAs. The four tools provided a subset of high-quality predictions and returned few false-positive predictions; however, they could not identify several known true targets. We demonstrate that union of TargetScan/miRanda-mirSVR and TargetScan/miRanda-mirSVR/RNA22 enhanced the quality of in silico prediction analysis of microRNA targets. We conclude that the union rather than the intersection of the aforementioned tools is the best strategy for maximizing performance while minimizing the loss of time and resources in subsequent in vivo and in vitro experiments for functional validation of microRNA-target interactions.

In the last decade, several studies have been focused on revealing the microRNA (miRNA) repertoire and determining their functions in farm animals such as poultry, pigs, cattle, and fish. These small non-protein coding RNA molecules (18–25 nucleotides) are capable of controlling gene expression by binding to messenger RNA (mRNA) targets, thus interfering in the final protein output. MiRNAs have been recognized as the main regulators of biological features of economic interest, including body growth, muscle development, fat deposition, and immunology, among other highly valuable traits, in aquatic livestock. Currently, the miRNA repertoire of some farmed fish species has been identified and characterized, bringing insights about miRNA functions, and novel perspectives for improving health and productivity. In this review, we summarize the current advances in miRNA research by examining available data on Neotropical and other key species exploited by fisheries and in aquaculture worldwide and discuss how future studies on Neotropical fish could benefit from this knowledge. We also make a horizontal comparison of major results and discuss forefront strategies for miRNA manipulation in aquaculture focusing on forward-looking ideas for forthcoming research.

A class of small non-coding RNAs, the microRNAs (miRNAs), has been shown to be essential for the regulation of specific cell pathways, including skeletal muscle development, maintenance and homeostasis in vertebrates. However, the relative contribution of miRNAs for determining the red and white muscle cell phenotypes is far from being fully comprehended. To better characterize the role of miRNA in skeletal muscle cell biology, we investigated muscle-specific miRNA (myomiR) signatures in Nile tilapia fish. Quantitative (RT-qPCR) and spatial (FISH) expression analyses revealed a highly differential expression (forty-four-fold) of miR-499 in red skeletal muscle compared to white skeletal muscle, whereas the remaining known myomiRs were equally expressed in both muscle cell types. Detailed examination of the miR-499 targets through bioinformatics led us to the sox6 and rod1 genes, which had low expression in red muscle cells according to RT-qPCR, FISH, and protein immunofluorescence profiling experiments. Interestingly, we verified that the high expression of miR-499 perfectly correlates with a low expression of sox6 and rod1 target genes, as verified by a distinctive predominance of mRNA destabilization and protein translational decay to these genes, respectively. Through a genome-wide comparative analysis of SOX6 and ROD1 protein domains and through an in silico gene regulatory network, we also demonstrate that both proteins are essentially similar in vertebrate genomes, suggesting their gene regulatory network may also be widely conserved. Overall, our data shed light on the potential regulation of targets by miR-499 associated with the slow-twitch muscle fiber type phenotype. Additionally the results provide novel insights into the evolutionary dynamics of miRNA and target genes enrolled in a putative constrained molecular pathway in the skeletal muscle cells of vertebrates.

Venom is a key adaptive innovation in snakes, and how nonvenom genes were co-opted to become part of the toxin arsenal is a significant evolutionary question. While this process has been investigated through the phylogenetic reconstruction of toxin sequences, evidence provided by the genomic context of toxin genes remains less explored. To investigate the process of toxin recruitment, we sequenced the genome of Bothrops jararaca, a clinically relevant pitviper. In addition to producing a road map with canonical structures of genes encoding 12 toxin families, we inferred most of the ancestral genes for their loci. We found evidence that 1) snake venom metalloproteinases (SVMPs) and phospholipases A₂ (PLA2) have expanded in genomic proximity to their nonvenomous ancestors; 2) serine proteinases arose by co-opting a local gene that also gave rise to lizard gilatoxins and then expanded; 3) the bradykinin-potentiating peptides originated from a C-type natriuretic peptide gene backbone; and 4) VEGF-F was co-opted from a PGF-like gene and not from VEGF-A. We evaluated two scenarios for the original recruitment of nontoxin genes for snake venom: 1) in locus ancestral gene duplication and 2) in locus ancestral gene direct co-option. The first explains the origins of two important toxins (SVMP and PLA2), while the second explains the emergence of a greater number of venom components. Overall, our results support the idea of a locally assembled venom arsenal in which the most clinically relevant toxin families expanded through posterior gene duplications, regardless of whether they originated by duplication or gene co-option. Significance The jararaca lancehead genome provides a comprehensive road map of the genomic context of pitviper toxin genes. Comparisons of these genomic segments across the phylogeny revealed an unexpectedly high number of toxin families that originated via the direct co-option of preexisting nontoxin genes, indicating that the snake toxin arsenal was mostly assembled from local elements of the ancestral genome. These results support a new perspective in venom evolution in which gene duplications in most toxin families occurred after, rather than before, initial toxin recruitment from nontoxin genes, contributing to the evolutionary optimization of snake venoms. They also emphasize the importance of correctly identifying orthologous loci to accurately trace the genomic pathways that lead to the evolutionary origination of new traits.

Ontogenetic changes in venom composition have been described in Bothrops snakes, but only a few studies have attempted to identify the targeted paralogues or the molecular mechanisms involved in modifications of gene expression during ontogeny. In this study, we decoded B. jararacussu venom gland transcripts from six specimens of varying sizes and analyzed the variability in the composition of independent venom proteomes from 19 individuals. We identified 125 distinct putative toxin transcripts, and of these, 73 were detected in venom proteomes and only 10 were involved in the ontogenetic changes. Ontogenetic variability was linearly related to snake size and did not correspond to the maturation of the reproductive stage. Changes in the transcriptome were highly predictive of changes in the venom proteome. The basic myotoxic phospholipases A₂ (PLA₂s) were the most abundant components in larger snakes, while in venoms from smaller snakes, PIII-class SVMPs were the major components. The snake venom metalloproteinases (SVMPs) identified corresponded to novel sequences and conferred higher pro-coagulant and hemorrhagic functions to the venom of small snakes. The mechanisms modulating venom variability are predominantly related to transcriptional events and may consist of an advantage of higher hematotoxicity and more efficient predatory function in the venom from small snakes.

Characterization of the coding sequences (CDSs) is an essential step in transcriptome annotation. Incorrect identification of CDSs can lead to the prediction of non-existent proteins that can eventually compromise knowledge if databases are populated with similar incorrect predictions made in different genomes. Also, the correct identification of CDSs is important for the characterization of the untranslated regions (UTRs), which are known to be important regulators of the mRNA translation process. Considering this, we present CodAn (Coding sequence Annotator), a new approach to predict confident CDS and UTR regions in full or partial transcriptome sequences in eukaryote species. Our analysis revealed that CodAn performs confident predictions on full-length and partial transcripts with the strand sense of the CDS known or unknown. The comparative analysis showed that CodAn presents better overall performance than other approaches, mainly when considering the correct identification of the full CDS (i.e. correct identification of the start and stop codons). In this sense, CodAn is the best tool to be used in projects involving transcriptomic data. CodAn is freely available at https://github.com/pedronachtigall/CodAn. aland@usp.br Supplementary data are available at Briefings in Bioinformatics online.