Systematic computational hunting for small RNAs derived from ncRNAs during dengue virus infection in endothelial HMEC-1 cells.

In recent years, a population of small RNA fragments derived from non-coding RNAs (sfd-RNAs) has gained significant interest due to its functional and structural resemblance to miRNAs, adding another level of complexity to our comprehension of small-RNA-mediated gene regulation. Despite this, scientists need more tools to test the differential expression of sfd-RNAs since the current methods to detect miRNAs may not be directly applied to them. The primary reasons are the lack of accurate small RNA and ncRNA annotation, the multi-mapping read (MMR) placement, and the multicopy nature of ncRNAs in the human genome. To solve these issues, a methodology that allows the detection of differentially expressed sfd-RNAs, including canonical miRNAs, by using an integrated copy-number-corrected ncRNA annotation was implemented. This approach was coupled with sixteen different computational strategies composed of combinations of four aligners and four normalization methods to provide a rank-order of prediction for each differentially expressed sfd-RNA. By systematically addressing the three main problems, we could detect differentially expressed miRNAs and sfd-RNAs in dengue virus-infected human dermal microvascular endothelial cells. Although more biological evaluations are required, two molecular targets of the hsa-mir-103a and hsa-mir-494 (CDK5 and PI3/AKT) appear relevant for dengue virus (DENV) infections. Here, we performed a comprehensive annotation and differential expression analysis, which can be applied in other studies addressing the role of small fragment RNA populations derived from ncRNAs in virus infection.

Computational Prediction of RNA-RNA Interactions between Small RNA Tracks from Betacoronavirus Nonstructural Protein 3 and Neurotrophin Genes during Infection of an Epithelial Lung Cancer Cell Line: Potential Role of Novel Small Regulatory RNA.

Whether RNA-RNA interactions of cytoplasmic RNA viruses, such as Betacoronavirus, might end in the biogenesis of putative virus-derived small RNAs as miRNA-like molecules has been controversial. Even more, whether RNA-RNA interactions of wild animal viruses may act as virus-derived small RNAs is unknown. Here, we address these issues in four ways. First, we use conserved RNA structures undergoing negative selection in the genomes of SARS-CoV, MERS-CoV, and SARS-CoV-2 circulating in different bat species, intermediate animals, and human hosts. Second, a systematic literature review was conducted to identify Betacoronavirus-targeting hsa-miRNAs involved in lung cell infection. Third, we employed sophisticated long-range RNA-RNA interactions to refine the seed sequence homology of hsa-miRNAs with conserved RNA structures. Fourth, we used high-throughput RNA sequencing of a Betacoronavirus-infected epithelial lung cancer cell line (Calu-3) to validate the results. We proposed nine potential virus-derived small RNAs: two vsRNAs in SARS-CoV (Bats: SB-vsRNA-ORF1a-3p; SB-vsRNA-S-5p), one vsRNA in MERS-CoV (Bats: MB-vsRNA-ORF1b-3p), and six vsRNAs in SARS-CoV-2 (Bats: S2B-vsRNA-ORF1a-5p; intermediate animals: S2I-vsRNA-ORF1a-5p; and humans: S2H-vsRNA-ORF1a-5p, S2H-vsRNA-ORF1a-3p, S2H-vsRNA-ORF1b-3p, S2H-vsRNA-ORF3a-3p), mainly encoded by nonstructural protein 3. Notably, Betacoronavirus-derived small RNAs targeted 74 differentially expressed genes in infected human cells, of which 55 upregulate the molecular mechanisms underlying acute respiratory distress syndrome (ARDS), and the 19 downregulated genes might be implicated in neurotrophin signaling impairment. These results reveal a novel small RNA-based regulatory mechanism involved in neuropathogenesis that must be further studied to validate its therapeutic use.

RNA structure-altering mutations underlying positive selection on Spike protein reveal novel putative signatures to trace crossing host-species barriers in Betacoronavirus.

Similar to other RNA viruses, the emergence of Betacoronavirus relies on cross-species viral transmission, which requires careful health surveillance monitoring of protein-coding information as well as genome-wide analysis. Although the evolutionary jump from natural reservoirs to humans may be mainly traced-back by studying the effect that hotspot mutations have on viral proteins, it is largely unexplored if other impacts might emerge on the structured RNA genome of Betacoronavirus. In this survey, the protein-coding and viral genome architecture were simultaneously studied to uncover novel insights into cross-species horizontal transmission events. We analysed 1,252,952 viral genomes of SARS-CoV, MERS-CoV, and SARS-CoV-2 distributed across the world in bats, intermediate animals, and humans to build a new landscape of changes in the RNA viral genome. Phylogenetic analyses suggest that bat viruses are the most closely related to the time of most recent common ancestor of Betacoronavirus, and missense mutations in viral proteins, mainly in the S protein S1 subunit: SARS-CoV (G > T; A577S); MERS-CoV (C > T; S746R and C > T; N762A); and SARS-CoV-2 (A > G; D614G) appear to have driven viral diversification. We also found that codon sites under positive selection on S protein overlap with non-compensatory mutations that disrupt secondary RNA structures in the RNA genome complement. These findings provide pivotal factors that might be underlying the eventual jumping the species barrier from bats to intermediate hosts. Lastly, we discovered that nearly half of the Betacoronavirus genomes carry highly conserved RNA structures, and more than 90% of these RNA structures show negative selection signals, suggesting essential functions in the biology of Betacoronavirus that have not been investigated to date. Further research is needed on negatively selected RNA structures to scan for emerging functions like the potential of coding virus-derived small RNAs and to develop new candidate antiviral therapeutic strategies.

Structural Analysis of the Spike Protein of SARS-CoV-2 Variants and Other Betacoronaviruses Using Molecular Dynamics.

A structural analysis over various spike proteins from three highly pathogenic Betacoronavirus was done to understand their structural differences. The proteins were modeled using crystal structures from SARS-CoV, MERS-CoV, and other Betacoronavirus that infect bats and pangolins. The group was split in two sets; the first set corresponds to the non-mutated spike proteins, while the second set corresponds to mutated spike variants alpha, beta, gamma, delta, omicron and mu; five of them classified as variants of concern and the last one as variant of interest. A conformational space exploration was carried out for every protein by using molecular dynamic simulations. Root mean square fluctuations, principal component and cross-correlation analysis were carried out over the dynamics to analyze the flexibility and rigidity of every protein in comparison to the wild type Spike protein from the SARS-CoV-2. The obtained results indicate that the proteins, which are not spread among humans, have smooth movements compared to those of SARS-CoV-2 and its variants. In addition, a relationship between the speed of the virulence and the movement of the protein can explain the behavior of delta and omicron variants.

Evaluation of Conserved RNA Secondary Structures within and between Geographic Lineages of Zika Virus.

Zika virus (ZIKV), without a vaccine or an effective treatment approved to date, has globally spread in the last century. The infection caused by ZIKV in humans has changed progressively from mild to subclinical in recent years, causing epidemics with greater infectivity, tropism towards new tissues and other related symptoms as a product of various emergent ZIKV-host cell interactions. However, it is still unknown why or how the RNA genome structure impacts those interactions in differential evolutionary origin strains. Moreover, the genomic comparison of ZIKV strains from the sequence-based phylogenetic analysis is well known, but differences from RNA structure comparisons have barely been studied. Thus, in order to understand the RNA genome variability of lineages of various geographic distributions better, 410 complete genomes in a phylogenomic scanning were used to study the conservation of structured RNAs. Our results show the contemporary landscape of conserved structured regions with unique conserved structured regions in clades or in lineages within circulating ZIKV strains. We propose these structures as candidates for further experimental validation to establish their potential role in vital functions of the viral cycle of ZIKV and their possible associations with the singularities of different outbreaks that lead to ZIKV populations to acquire nucleotide substitutions, which is evidence of the local structure genome differentiation.

Comprehensive genomic resources related to domestication and crop improvement traits in Lima bean.

Lima bean (Phaseolus lunatus L.), one of the five domesticated Phaseolus bean crops, shows a wide range of ecological adaptations along its distribution range from Mexico to Argentina. These adaptations make it a promising crop for improving food security under predicted scenarios of climate change in Latin America and elsewhere. In this work, we combine long and short read sequencing technologies with a dense genetic map from a biparental population to obtain the chromosome-level genome assembly for Lima bean. Annotation of 28,326 gene models show high diversity among 1917 genes with conserved domains related to disease resistance. Structural comparison across 22,180 orthologs with common bean reveals high genome synteny and five large intrachromosomal rearrangements. Population genomic analyses show that wild Lima bean is organized into six clusters with mostly non-overlapping distributions and that Mesomerican landraces can be further subdivided into three subclusters. RNA-seq data reveal 4275 differentially expressed genes, which can be related to pod dehiscence and seed development. We expect the resources presented here to serve as a solid basis to achieve a comprehensive view of the degree of convergent evolution of Phaseolus species under domestication and provide tools and information for breeding for climate change resiliency.

Dengue virus potentially promotes migratory responses on endothelial cells by enhancing pro-migratory soluble factors and miRNAs.

The most life-threatening effect of the Dengue virus (DENV) infection is an acute destabilization of the microvascular endothelial cell (MEC) barrier leading to plasma leakage, hypovolemic shock and haemorrhage. However, the underlying cellular mechanisms responsible for the dysfunction of MECs are not well understood. To identify potential cellular processes altered during DENV infection of MECs, expression profiles of cytokines/growth factors and microRNAs were measured by Luminex assay and next generation sequencing, respectively. Synchronously DENV2-infected MECs increase the secretion of IL-6, IL-8, FGF-2, GM-CSF, G-CSF, TGF-α, GRO, RANTES, MCP-1 and MCP-3. Conditioned media of infected MECs increased the migration of non-infected MECs. Furthermore, six miRNAs deregulated at 24 hpi were predicted to regulate host genes involved in cell migration and vascular developmental processes such as angiogenesis. These in silico analyses provide insights that support that DENV promotes an acute migratory phenotype in MECs that contributes to the vascular destabilization observed in severe dengue cases.

Buscando agujaseen un pajar: viajes de rnas pequeños in silico e in vitro / Finding for a Neadle in a Haystack: Trips of Small RNAs from in silico to in vitro

Lo que se conoce tradicionalmente como análisis del transcriptoma comprende la caracterización y cuantificación del conjunto de RNAs transcritos en la célula. En los primeros años, los estudios del transcriptoma se enfocaron principalmente a RNA mensajeros o RNA codificantes. Más recientemente, debido a avances en la tecnología de secuenciammiento de última generación, los estudios del transcriptoma se han extendido a RNAs no codificantes. Estas moléculas presentan gran variedad de funciones en la regulación celular. Una caracterización completa del conjunto de ncRNAs no es alcanzable con las aproximaciones disponibles. Hoy en día la identificación de RNAs no codificantes y de sus RNA pequeños derivados, es un tema de vital importancia en el análisis genético. Uno de los avances recientes en el estudio del transcriptoma por ejemplo, se enfoca en la biología de RNA de interferencia y su aplicación clínica. Durante los últimos años se han desarrollado continuamente la capacidad de cómputo, eficiencia y capacidad de almacenamiento para modelar y procesar grandes volúmenes de información producto de secuenciamiento de última generación. Como consecuencia, esta revisión presenta el análisis del transcriptoma desde una perspectiva histórica unida a la modelación computacional de RNA no codificantes de datos de bibliotecas de RNAs pequeños.

What is commonly known about transcriptome studies encompass the characterization and quantification of the complete set of RNA transcripts produced by a cell. In its early days these analysis mainly focused on examination of messenger RNAs or coding RNAs. More recently, due to advances in next-generation sequencing technologies, transcriptome analysis has expanded to non-conding RNAs (ncRNAs). These molecules exhibit high variety of functions in cell regulation. Through characterization of complete sets of ncRNAs is not attainable with current approaches. At present de novo identification of ncRNAs and ncRNA-derived small RNAs is a major issue in genetic analysis. One of the most important recent advances of transcriptome analysis focuses, for example, on RNA interference (RNAi) biology and its clinical application. High-performance computing, storage capability and computational modeling have been continuously developed during last years to process and model large amounts of products of next generation sequencing methods. As consequence this review describes transcriptome sequencing analysis from a historical perspective to its link to computational approaches to model ncRNAs from small RNA library data.