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This is a mini-review capturing the views and opinions of selected participants at the 2021 IEEE BIBM 3rd Annual LncRNA Workshop, held in Dubai, UAE. The views and opinions are expressed on five broad themes related to problems in lncRNA, namely, challenges in the computational analysis of lncRNAs, lncRNAs and cancer, lncRNAs in sports, lncRNAs and COVID-19, and lncRNAs in human brain activity.

We present a Raman spectroscopy study of the vibrational properties of free-base meso-tetra(4-pyridyl) porphyrin polycrystals under various temperature and hydrostatic pressure conditions. The combination of experimental results and Density Functional Theory (DFT) calculations allows us to assign most of the observed Raman bands. The modifications in the Raman spectra when excited with 488 nm and 532 nm laser lights indicate that a resonance effect in the Qy band is taking place. The pressure-dependent results show that the resonance conditions change with increasing pressure, probably due to the shift of the electronic transitions. The temperature-dependent results show that the relative intensities of the Raman modes change at low temperatures, while no frequency shifts are observed. The experimental and theoretical analysis presented here suggest that these molecules are well represented by the C2v point symmetry group.

Coffea arabica, an allotetraploid hybrid of Coffea eugenioides and Coffea canephora, is the source of approximately 60% of coffee products worldwide, and its cultivated accessions have undergone several population bottlenecks. We present chromosome-level assemblies of a di-haploid C. arabica accession and modern representatives of its diploid progenitors, C. eugenioides and C. canephora. The three species exhibit largely conserved genome structures between diploid parents and descendant subgenomes, with no obvious global subgenome dominance. We find evidence for a founding polyploidy event 350,000-610,000 years ago, followed by several pre-domestication bottlenecks, resulting in narrow genetic variation. A split between wild accessions and cultivar progenitors occurred ~30.5 thousand years ago, followed by a period of migration between the two populations. Analysis of modern varieties, including lines historically introgressed with C. canephora, highlights their breeding histories and loci that may contribute to pathogen resistance, laying the groundwork for future genomics-based breeding of C. arabica., (© 2024. The Author(s).)

Background: Theobroma grandiflorum (Malvaceae), known as cupuassu, is a tree indigenous to the Amazon basin, valued for its large fruits and seed pulp, contributing notably to the Amazonian bioeconomy. The seed pulp is utilized in desserts and beverages, and its seed butter is used in cosmetics. Here, we present the sequenced telomere-to-telomere genome of cupuassu, disclosing its genomic structure, evolutionary features, and phylogenetic relationships within the Malvaceae family., Findings: The cupuassu genome spans 423 Mb, encodes 31,381 genes distributed in 10 chromosomes, and exhibits approximately 65% gene synteny with the Theobroma cacao genome, reflecting a conserved evolutionary history, albeit punctuated with unique genomic variations. The main changes are pronounced by bursts of long-terminal repeat retrotransposons at postspecies divergence, retrocopied and singleton genes, and gene families displaying distinctive patterns of expansion and contraction. Furthermore, positively selected genes are evident, particularly among retained and dispersed tandem and proximal duplicated genes associated with general fruit and seed traits and defense mechanisms, supporting the hypothesis of potential episodes of subfunctionalization and neofunctionalization following duplication, as well as impact from distinct domestication process. These genomic variations may underpin the differences observed in fruit and seed morphology, ripening, and disease resistance between cupuassu and the other Malvaceae species., Conclusions: The cupuassu genome offers a foundational resource for both breeding improvement and conservation biology, yielding insights into the evolution and diversity within the genus Theobroma., (© The Author(s) 2024. Published by Oxford University Press GigaScience.)

Studies focusing on characterizing circRNAs with the potential to translate into peptides are quickly advancing. It is helping to elucidate the roles played by circRNAs in several biological processes, especially in the emergence and development of diseases. While various tools are accessible for predicting coding regions within linear sequences, none have demonstrated accurate open reading frame detection in circular sequences, such as circRNAs. Here, we present cirCodAn, a novel tool designed to predict coding regions in circRNAs. We evaluated the performance of cirCodAn using datasets of circRNAs with strong translation evidence and showed that cirCodAn outperformed the other tools available to perform a similar task. Our findings demonstrate the applicability of cirCodAn to identify coding regions in circRNAs, which reveals the potential of use of cirCodAn in future research focusing on elucidating the biological roles of circRNAs and their encoded proteins. cirCodAn is freely available at https://github.com/denilsonfbar/cirCodAn., (Copyright © 2024. Published by Elsevier Inc.)

The Rubiaceae plant family, comprising 3 subfamilies and over 13,000 species, is known for producing significant bioactive compounds such as caffeine and monoterpene indole alkaloids. Despite an increase in available genomes from the Rubiaceae family over the past decade, a systematic analysis of the metabolic gene clusters (MGCs) encoded by these genomes has been lacking. In this study, we aim to identify and analyze metabolic gene clusters within complete Rubiaceae genomes through a comparative analysis of eight species. Applying two bioinformatics pipelines, we identified 2372 candidate MGCs, organized into 549 gene cluster families (GCFs). To enhance the reliability of these findings, we developed coexpression networks and conducted orthology analyses. Using genomic data from Solanum lycopersicum (Solanaceae) for comparative purposes, we provided a detailed view of predicted metabolic enzymes, pathways, and coexpression networks. We bring some examples of MGCs and GCFs involved in biological pathways of terpenes, saccharides and alkaloids. Such insights lay the groundwork for discovering new compounds and associated MGCs within the Rubiaceae family, with potential implications in developing more robust crop species and expanding the understanding of plant metabolism. This large-scale exploration also provides a new perspective on the evolution and structure-function relationship of these clusters, offering opportunities for the highly efficient utilization of these unique metabolites. The outcome of this study contributes to a broader comprehension of the biosynthetic pathways, elucidating multiple aspects of specialized metabolism and offering innovative avenues for biotechnological applications., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Introduction: Bisphosphonate (BF) therapy is strongly related to the occurrence of medication-related osteonecrosis of the jaw (ONJ). However, no previous study has evaluated if there are sex-related differences on the ONJ establishment together with bone biomechanical alterations, and if they could have a synergy with the ZA treatment., Materials and Methods: This study aimed to analyze the physicochemical properties of mineralized tissues in a zoledronate (ZA)-related osteonecrosis mouse model, by a 2 × 2-factorial design, considering sex (female/male) and treatment (ZA/Saline) factors (n = 8/group). After three ZA (1.0 mg/kg) or saline administrations (days 0, 7, 14), the lower left second molar was extracted (day 42). Further ZA administration (day 49) and euthanasia (day 70) were conducted. After confirmation of ZA-induced jaw necrosis (histologic and microtomographic analysis), spectroscopic and mechanical parameters were assessed., Results: ZA-treated groups presented lower bone density due to impaired healing of tooth extraction socket. Sex-related alterations were also observed, with lower bone density in females. Regarding biomechanical parameters, sex and treatment exerted independent influences. ZA, although decreasing flexural modulus and yield stress, increases stiffness mainly due to a higher bone volume. Females show less resistance to higher loads compared to males (considering dimension-independent parameters). Additionally, ZA increases crystallinity in bone and dental structure (p < 0.05). In summary, although strongly related to osteonecrosis occurrence, ZA modifies bone and dental mineral matrix, improving bone mechanical properties., Conclusion: Despite sex-dependent differences in bone biomechanics and density, osteonecrosis was established with no sex influence. No synergistic association between sex and treatment factors was observed in this study., (© 2023. The Japanese Society Bone and Mineral Research.)

RNA sequencing (RNA-Seq) and mass-spectrometry-based proteomics data are often integrated in proteogenomic studies to assist in the prediction of eukaryote genome features, such as genes, splicing, single-nucleotide (SNVs), and single-amino-acid variants (SAAVs). Most genomes of parasite nematodes are draft versions that lack transcript- and protein-level information and whose gene annotations rely only on computational predictions. Angiostrongylus costaricensis is a roundworm species that causes an intestinal inflammatory disease, known as abdominal angiostrongyliasis (AA). Currently, there is no drug available that acts directly on this parasite, mostly due to the sparse understanding of its molecular characteristics. The available genome of A. costaricensis , specific to the Costa Rica strain, is a draft version that is not supported by transcript- or protein-level evidence. This study used RNA-Seq and MS/MS data to perform an in-depth annotation of the A. costaricensis genome. Our prediction improved the reference annotation with (a) novel coding and non-coding genes; (b) pieces of evidence of alternative splicing generating new proteoforms; and (c) a list of SNVs between the Brazilian (Crissiumal) and the Costa Rica strain. To the best of our knowledge, this is the first time that a multi-omics approach has been used to improve the genome annotation of A. costaricensis . We hope this improved genome annotation can assist in the future development of drugs, kits, and vaccines to treat, diagnose, and prevent AA caused by either the Brazil strain (Crissiumal) or the Costa Rica strain.

A sensor device based on doped-carbon quantum dots is proposed herein for detection of nitrite in meat products by fluorescence quenching. For the sensing platform, carbon quantum dots doped with boron and functionalized with nitrogen (B,N-Cdot) were synthesized with an excellent 44.3% quantum yield via a one-step hydrothermal route using citric acid, boric acid, and branched polyethylenimine as carbon, boron, and nitrogen sources, respectively. After investigation of their chemical structure and fluorescent properties, the B,N-Cdot at aqueous suspensions showed high selectivity for NO 2 - in a linear range from 20 to 50 mmol L -1 under optimum conditions at pH 7.4 and a 340 nm excitation. Furthermore, the prepared B,N-Cdots successfully detected NO 2 - in a real meat sample with recovery of 91.4-104% within the analyzed range. In this manner, a B,N-Cdot/PVA nanocomposite film with blue emission under excitation at 360 nm was prepared, and a first assay detection of NO 2 - in meat products was tested using a smartphone application. The potential application of the newly developed sensing device containing a highly fluorescent probe should aid in the development of a rapid and inexpensive strategy for NO 2 - detection.

Titanium nanotubes have attractive morphological and physicochemical properties for several applications, such as high surface area, mesoporous structure, good stability, ion exchange capacity, and antibacterial property. Therefore, the field of nanotube applications is increasingly expanding, such as in solar cells sensitized by dye, photocatalysis, and antibacterial activity, among others. Therefore, a study of the antibacterial properties of sodium titanate nanotubes (Na-TiNTs) was carried out together with physicochemical characterizations, such as Raman spectroscopy which shows a peak characteristic of Na-O-Ti from nanotube-agglomerated regions. The XRD diffractogram confirmed the Raman spectra and evidenced the crystalline structure associated to Na-TiNT, which showed the characteristic peaks of the sodium trititanate crystal. SEM and TEM images showed the morphology of hollow nanotubes and forming semispherical particles. EDS shows the percentage values of each of the compounds in the Na-TiNT. The bacterial activity of the Na-TiNT was analyzed in Escherichia coli , Staphylococcus aureus , and Pseudomonas aeruginosa . Na-TiNT modified the activity of the gentamicin and norfloxacin antibiotics against multiresistant strains. Synergistic effects against Gram-positive S. aureus 10 and Gram-negative P. aeruginosa 15 bacteria were observed when the Na-TiNT was associated with gentamicin, reducing the concentration of this antibiotic that is required to inhibit bacterial growth. Another synergic effect was observed for S. aureus 10 with norfloxacin., Competing Interests: The authors declare that there are no conflicts of interest., (Copyright © 2022 Enzo V. H. Agressott et al.)

In this era of big data, sets of methodologies and strategies are designed to extract knowledge from huge volumes of data. However, the cost of where and how to get this information accurately and quickly is extremely important, given the diversity of genomes and the different ways of representing that information. Among the huge set of information and relationships that the genome carries, there are sequences called miRNAs (microRNAs). These sequences were described in the 1990s and are mainly involved in mechanisms of regulation and gene expression. Having this in mind, this chapter focuses on exploring the available literature and providing useful and practical guidance on the miRNA database and tools topic. For that, we organized and present this text in two ways: (a) the update reviews and articles, which best summarize and discuss the theme; and (b) our update investigation on miRNA literature and portals about databases and tools. Finally, we present the main challenge and a possible solution to improve resources and tools., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature.)

Mature microRNAs (miRNAs) are short RNA sequences about 18-24 nucleotide long, which provide the recognition key within RISC for the posttranscriptional regulation of target RNAs. Considering the canonical pathway, mature miRNAs are produced via a multistep process. Their transcription (pri-miRNAs) and first processing step via the microprocessor complex (pre-miRNAs) occur in the nucleus. Then they are exported into the cytosol, processed again by Dicer (dsRNA) and finally a single strand (mature miRNA) is incorporated into RISC (miRISC). The sequence of the incorporated miRNA provides the function of RNA target recognition via hybridization. Following binding of the target, the mRNA is either degraded or translation is inhibited, which ultimately leads to less protein production. Conversely, it has been shown that binding within the 5' UTR of the mRNA can lead to an increase in protein product. Regulation of homeostasis is very important for a cell; therefore, all steps in the miRNA-based regulation pathway, from transcription to the incorporation of the mature miRNA into RISC, are under tight control. While much research effort has been exerted in this area, the knowledgebase is not sufficient for accurately modelling miRNA regulation computationally. The computational prediction of miRNAs is, however, necessary because it is not feasible to investigate all possible pairs of a miRNA and its target, let alone miRNAs and their targets. We here point out open challenges important for computational modelling or for our general understanding of miRNA-based regulation and show how their investigation is beneficial. It is our hope that this collection of challenges will lead to their resolution in the near future., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature.)

Advances in genomic sequencing have recently offered vast opportunities for biological exploration, unraveling the evolution and improving our understanding of Earth biodiversity. Due to distinct plant species characteristics in terms of genome size, ploidy and heterozygosity, transposable elements (TEs) are common characteristics of many genomes. TEs are ubiquitous and dispersed repetitive DNA sequences that frequently impact the evolution and composition of the genome, mainly due to their redundancy and rearrangements. For this study, we provided an atlas of TE data by employing an easy-to-use portal ( APTE website ). To our knowledge, this is the most extensive and standardized analysis of TEs in plant genomes. We evaluated 67 plant genomes assembled at chromosome scale, recovering a total of 49,802,023 TE records, representing a total of 47,992,091,043 (~47,62%) base pairs (bp) of the total genomic space. We observed that new types of TEs were identified and annotated compared to other data repositories. By establishing a standardized catalog of TE annotation on 67 genomes, new hypotheses, exploration of TE data and their influences on the genomes may allow a better understanding of their function and processes. All original code and an example of how we developed the TE annotation strategy is available on GitHub ( Extended data )., Competing Interests: No competing interests were disclosed., (Copyright: © 2021 Pedro DLF et al.)

Silver nanoparticle (AgNPs) toxicity is related to nanoparticle interaction with the cell wall of microorganisms and plants. This interaction alters cell wall conformation with increased reactive oxygen species (ROS) in the cell. With the increase of ROS in the cell, the dissolution of zero silver (Ag0) to ionic silver (Ag+) occurs, which is a strong oxidant agent to the cellular wall. AgNP interaction was evaluated by transmission electron microscopy (TEM) on Lactuca sativa roots, and the mechanism of passage through the outer cell wall (OCW) was also proposed. The results suggest that Ag+ binds to the hydroxyls (OH) present in the cellulose structure, thus causing the breakdown of the hydrogen bonds. Changes in cell wall structure facilitate the passage of AgNPs, reaching the plasma membrane. According to the literature, silver nanoparticles with an average diameter of 15nm are transported across the membrane into the cells by caveolines. This work describes the interaction between AgNPs and the cell wall and proposes a transport model through the outer cell wall.

As consequence of the various genomic sequencing projects, an increasing volume of biological sequence data is being produced. Although machine learning algorithms have been successfully applied to a large number of genomic sequence-related problems, the results are largely affected by the type and number of features extracted. This effect has motivated new algorithms and pipeline proposals, mainly involving feature extraction problems, in which extracting significant discriminatory information from a biological set is challenging. Considering this, our work proposes a new study of feature extraction approaches based on mathematical features (numerical mapping with Fourier, entropy and complex networks). As a case study, we analyze long non-coding RNA sequences. Moreover, we separated this work into three studies. First, we assessed our proposal with the most addressed problem in our review, e.g. lncRNA and mRNA; second, we also validate the mathematical features in different classification problems, to predict the class of lncRNA, e.g. circular RNAs sequences; third, we analyze its robustness in scenarios with imbalanced data. The experimental results demonstrated three main contributions: first, an in-depth study of several mathematical features; second, a new feature extraction pipeline; and third, its high performance and robustness for distinct RNA sequence classification. Availability:https://github.com/Bonidia/FeatureExtraction&#95;BiologicalSequences., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Transposable elements (TEs) are the most represented sequences occurring in eukaryotic genomes. Few methods provide the classification of these sequences into deeper levels, such as superfamily level, which could provide useful and detailed information about these sequences. Most methods that classify TE sequences use handcrafted features such as k-mers and homology-based search, which could be inefficient for classifying non-homologous sequences. Here we propose an approach, called transposable elements pepresentation learner (TERL), that preprocesses and transforms one-dimensional sequences into two-dimensional space data (i.e., image-like data of the sequences) and apply it to deep convolutional neural networks. This classification method tries to learn the best representation of the input data to classify it correctly. We have conducted six experiments to test the performance of TERL against other methods. Our approach obtained macro mean accuracies and F1-score of 96.4% and 85.8% for superfamilies and 95.7% and 91.5% for the order sequences from RepBase, respectively. We have also obtained macro mean accuracies and F1-score of 95.0% and 70.6% for sequences from seven databases into superfamily level and 89.3% and 73.9% for the order level, respectively. We surpassed accuracy, recall and specificity obtained by other methods on the experiment with the classification of order level sequences from seven databases and surpassed by far the time elapsed of any other method for all experiments. Therefore, TERL can learn how to predict any hierarchical level of the TEs classification system and is about 20 times and three orders of magnitude faster than TEclass and PASTEC, respectively https://github.com/muriloHoracio/TERL. Contact:murilocruz@alunos.utfpr.edu.br., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Linear carbon chains (LCCs) are one-dimensional materials with unique properties, including high Debye temperatures and restricted selection rules for phonon interactions. Consequently, their Raman C-band frequency's temperature dependence is a probe to their thermal properties, which are well described within the Debye formalism even at room temperatures. Therefore, with the basis on a semiempirical approach we show how to use the C band to evaluate the LCCs' internal energy, heat capacity, coefficient of thermal expansion, thermal strain, and Grüneisen parameter, providing universal relations for these quantities in terms of the number of carbons atoms and the temperature.

Fossil freshwater carideans are very rare worldwide. Here, we present new taxonomic remarks about Beurlenia araripensis from the Early Cretaceous laminated limestones of the Crato Formation, Araripe Basin, northeastern Brazil. We analyzed five fossil samples, testing the morphological variations such as, rostrum with 5 to 14 supra-rostral spines and 2 to 3 sub-rostral spines, which appears as serrate for Caridea. This variation demonstrates a morphologic plasticity also seen in extant species of the group, such as those of the genera Macrobrachium and Palaemon., Competing Interests: NO authors have competing interests.

This chapter provides two main contributions: (1) a description of computational tools and databases used to identify and analyze transposable elements (TEs) and circRNAs in plants; and (2) data analysis on public TE and circRNA data. Our goal is to highlight the primary information available in the literature on circular noncoding RNAs and transposable elements in plants. The exploratory analysis performed on publicly available circRNA and TEs data help discuss four sequence features. Finally, we investigate the association on circRNAs:TE in plants in the model organism Arabidopsis thaliana.

In the age of big data, obtaining precise information about the research topic of interesting is extremely important. Keeping this in mind, this chapter focuses on providing a practical knowledge guide about computational tools and databases of transposable elements (TE) in plants. For that, we organize and present this text in three sections: (1) a discussion about tools and databases on this theme; (2) hands-on of how to use a few of them; (3) an exploratory data analysis on public TE data. Finally, we are going deep to present the main challenges and possible solutions to improve resources and tools.

Coffea canephora grains are highly traded commodities worldwide. Non-coding RNAs (ncRNAs) are transcriptional products involved in genome regulation, environmental responses, and plant development. There is not an extensive genome-wide analysis that uncovers the ncRNA portion of the C. canephora genome. This study aimed to provide a curated characterization of six ncRNA classes in the Coffea canephora genome. For this purpose, we employed a combination of similarity-based and structural-based computational approaches with stringent curation. Candidate ncRNA loci had expression evidence analyzed using sRNA-seq libraries. We identified 7455 ncRNA loci (6976 with transcriptional evidence) in the C. canephora genome. This comprised of total 115 snRNAs, 1031 snoRNAs, 92 miRNA precursors, 602 tRNAs, 72 rRNAs, and 5064 lncRNAs. For miRNAs, we identified 159 putative high-confidence targets. This study was the most extensive genomic catalog of curated ncRNAs in the Coffea genus. This data might help elaborating more robust hypotheses in future comparative genomic studies as well as gene regulation and genome dynamics, helping to understand the molecular basis of domestication, environmental adaptation, resistance to pests and diseases, and coffee productivity.

Isolated linear carbon chains (LCCs) encapsulated by multiwalled carbon nanotubes are studied under hydrostatic pressure (P) via resonance Raman scattering. The LCCs' spectroscopic signature C band around 1850  cm^{-1} softens linearly with increasing P. A simple anharmonic force-constant model not only describes such softening but also shows that the LCCs' Young's modulus (E), Grüneisen parameter (γ), and strain (ϵ) follow universal P^{-1} and P^{2} laws, respectively. In particular, γ also presents a unified behavior for all LCCs. To the best of our knowledge, these are the first results reported on such isolated systems and the first work to explore universal P-dependent responses for LCCs' E, ϵ, and γ.

Background: Most of our understanding on the social behavior and genomics of bees and other social insects is centered on the Western honey bee, Apis mellifera. The genus Apis, however, is a highly derived branch comprising less than a dozen species, four of which genomically characterized. In contrast, for the equally highly eusocial, yet taxonomically and biologically more diverse Meliponini, a full genome sequence was so far available for a single Melipona species only. We present here the genome sequence of Frieseomelitta varia, a stingless bee that has, as a peculiarity, a completely sterile worker caste., Results: The assembly of 243,974,526 high quality Illumina reads resulted in a predicted assembled genome size of 275 Mb composed of 2173 scaffolds. A BUSCO analysis for the 10,526 predicted genes showed that these represent 96.6% of the expected hymenopteran orthologs. We also predicted 169,371 repetitive genomic components, 2083 putative transposable elements, and 1946 genes for non-coding RNAs, largely long non-coding RNAs. The mitochondrial genome comprises 15,144 bp, encoding 13 proteins, 22 tRNAs and 2 rRNAs. We observed considerable rearrangement in the mitochondrial gene order compared to other bees. For an in-depth analysis of genes related to social biology, we manually checked the annotations for 533 automatically predicted gene models, including 127 genes related to reproductive processes, 104 to development, and 174 immunity-related genes. We also performed specific searches for genes containing transcription factor domains and genes related to neurogenesis and chemosensory communication., Conclusions: The total genome size for F. varia is similar to the sequenced genomes of other bees. Using specific prediction methods, we identified a large number of repetitive genome components and long non-coding RNAs, which could provide the molecular basis for gene regulatory plasticity, including worker reproduction. The remarkable reshuffling in gene order in the mitochondrial genome suggests that stingless bees may be a hotspot for mtDNA evolution. Hence, while being just the second stingless bee genome sequenced, we expect that subsequent targeting of a selected set of species from this diverse clade of highly eusocial bees will reveal relevant evolutionary signals and trends related to eusociality in these important pollinators.

Silver nanoparticles (AgNPs) have a large number of applications in technology and physical and biological sciences. These nanomaterials can be synthesized by chemical and biological methods. The biological synthesis using fungi represents a green approach for nanomaterial production that has the advantage of biocompatibility. This work studies silver nanoparticles (AgNPs) produced by fungi Rhodotorula glutinis and Rhodotorula mucilaginosa found in ordinary soil of the Universidade Federal do Ceará campus (Brazil). The biosynthesized AgNPs have a protein-capping layer involving a metallic Ag core. The focus of this paper is to investigate the size and structure of the capping layer, how it interacts with the Ag core, and how sensitive the system (core + protein) is to visible light illumination. For this, we employed SEM, AFM, photoluminescence spectroscopy, SERS, and dark-field spectroscopy. The AgNPs were isolated, and SEM measurements showed the average size diameter between 58 nm for R. glutinis and 30 nm for R. mucilaginosa . These values are in agreement with the AFM measurements, which also provided the average size diameter of 85 nm for R. glutinis and 56 nm for R. mucilaginosa as well as additional information about the average size of the protein-capping layers, whose found values were 24 and 21 nm for R. mucilaginosa and R. glutinis nanoparticles, respectively. The protein-capping layer structure seemed to be easily disturbed, and the SERS spectra were unstable. It was possible to identify Raman peaks that might be related to α-helix, β-sheet, and protein mixed structures. Finally, dark-field microscopy showed that the silver cores are very stable, but some are affected by the laser energy due to heating or melting., Competing Interests: The authors declare no competing financial interest., (Copyright © 2020 American Chemical Society.)

Motivation: Mirtrons arise from short introns with atypical cleavage by using the splicing mechanism. In the current literature, there is no repository centralizing and organizing the data available to the public. To fill this gap, we developed mirtronDB, the first knowledge database dedicated to mirtron, and it is available at http://mirtrondb.cp.utfpr.edu.br/. MirtronDB currently contains a total of 1407 mirtron precursors and 2426 mirtron mature sequences in 18 species., Results: Through a user-friendly interface, users can now browse and search mirtrons by organism, organism group, type and name. MirtronDB is a specialized resource that provides free and user-friendly access to knowledge on mirtron data., Availability and Implementation: MirtronDB is available at http://mirtrondb.cp.utfpr.edu.br/., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press.)

Motivation: Long noncoding RNAs (lncRNAs) correspond to a eukaryotic noncoding RNA class that gained great attention in the past years as a higher layer of regulation for gene expression in cells. There is, however, a lack of specific computational approaches to reliably predict lncRNA in plants, which contrast the variety of prediction tools available for mammalian lncRNAs. This distinction is not that obvious, given that biological features and mechanisms generating lncRNAs in the cell are likely different between animals and plants. Considering this, we present a machine learning analysis and a classifier approach called RNAplonc (https://github.com/TatianneNegri/RNAplonc/) to identify lncRNAs in plants., Results: Our feature selection analysis considered 5468 features, and it used only 16 features to robustly identify lncRNA with the REPTree algorithm. That was the base to create the model and train it with lncRNA and mRNA data from five plant species (thale cress, cucumber, soybean, poplar and Asian rice). After an extensive comparison with other tools largely used in plants (CPC, CPC2, CPAT and PLncPRO), we found that RNAplonc produced more reliable lncRNA predictions from plant transcripts with 87.5% of the best result in eight tests in eight species from the GreeNC database and four independent studies in monocotyledonous (Brachypodium) and eudicotyledonous (Populus and Gossypium) species., (© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The Ipubi and Romualdo Formations are Cretaceous units of the Araripe Basin (Santana Group). The first and most ancient was deposited in a lake environment, and some fossils were preserved in shales deposited under blackish conditions. The second was deposited in a marine environment, preserving a rich paleontological content in calcareous concretions. Considering that these two environments preserved their fossils under different processes, in this work we investigated the chemical composition of two fossilized specimens, one from each of the studied stratigraphic units, and compared them using vibrational spectroscopy techniques (Raman and IR), X-ray diffraction and large-field energy-dispersive X-ray spectroscopy (EDS) mappings. Calcite was observed as the dominant phase and carbon was observed in the fossils as a byproduct of the decomposition. The preservation of hydroxide calcium phosphate (Ca 10 (PO 4 ) 6 (OH) 2 , hydroxyapatite) was observed in both fossils. In addition, it was observed that there was a smaller amount of pyrite (pyritization) in the Romualdo Formation sample than in the Ipubi one. Large-field EDS measurements showed the major presence of the chemical elements calcium, oxygen, iron, aluminum and fluoride in the Ipubi fossil, indicating a greater influence of inorganic processes in its fossilization. Our results also suggest that the Romualdo Formation fossilization process involved the substitution of the hydroxyl group by fluorine, providing durability to the fossils., Competing Interests: The authors declare there are no competing interests.

In this work we performed several in silico analyses to describe the relevant structural aspects of an enzyme N-Carbamoyl-d-amino acid amidohydrolase (d-NCAase) encoded on the genome of the Brazilian strain CPAC 15 (=SEMIA 5079) of Bradyrhizobium japonicum, a nonpathogenic species belonging to the order Rhizobiales. d-NCAase has wide applications particularly in the pharmaceutical industry, since it catalyzes the production of d-amino acids such as D-p-hydroxyphenylglycine (D-HPG), an intermediate in the synthesis of β-lactam antibiotics. We applied a homology modelling approach and 50 ns of molecular dynamics simulations to predict the structure and the intersubunit interactions of this novel d-NCAase. Also, in order to evaluate the substrate binding site, the model was subjected to 50 ns of molecular dynamics simulations in the presence of N-Carbamoyl-d-p-hydroxyphenylglycine (Cp-HPG) (a d-NCAase canonical substrate) and water-protein/water-substrate interactions analyses were performed. Overall, the structural analysis and the molecular dynamics simulations suggest that d-NCAase of B. japonicum CPAC-15 has a homodimeric structure in solution. Here, we also examined the substrate specificity of the catalytic site of our model and the interactions with water molecules into the active binding site were comprehensively discussed. Also, these simulations showed that the amino acids Lys123, His125, Pro127, Cys172, Asp174 and Arg176 are responsible for recognition of ligand in the active binding site through several chemical associations, such as hydrogen bonds and hydrophobic interactions. Our results show a favourable environment for a reaction of hydrolysis that transforms N-Carbamoyl-d-p-hydroxyphenylglycine (Cp-HPG) into the active compound D-p-hydroxyphenylglycine (D-HPG). This work envisage the use of d-NCAase from the Brazilian Bradyrhizobium japonicum strain CPAC-15 (=SEMIA 5079) for the industrial production of D-HPG, an important intermediate for semi-synthesis of β-lactam antibiotics such as penicillins, cephalosporins and amoxicillin., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.

Coffea arabica L. is an important agricultural commodity, accounting for 60% of traded coffee worldwide. Nitrogen (N) is a macronutrient that is usually limiting to plant yield; however, molecular mechanisms of plant acclimation to N limitation remain largely unknown in tropical woody crops. In this study, we investigated the transcriptome of coffee roots under N starvation, analyzing poly-A+ libraries and small RNAs. We also evaluated the concentration of selected amino acids and N-source preferences in roots. Ammonium was preferentially taken up over nitrate, and asparagine and glutamate were the most abundant amino acids observed in coffee roots. We obtained 34,654 assembled contigs by mRNA sequencing, and validated the transcriptional profile of 12 genes by RT-qPCR. Illumina small RNA sequencing yielded 8,524,332 non-redundant reads, resulting in the identification of 86 microRNA families targeting 253 genes. The transcriptional pattern of eight miRNA families was also validated. To our knowledge, this is the first catalog of differentially regulated amino acids, N sources, mRNAs, and sRNAs in Arabica coffee roots.

The competing endogenous RNA hypothesis has gained increasing attention as a potential global regulatory mechanism of microRNAs (miRNAs), and as a powerful tool to predict the function of many noncoding RNAs, including miRNAs themselves. Most studies have been focused on animals, although target mimic (TMs) discovery as well as important computational and experimental advances has been developed in plants over the past decade. Thus, our contribution summarizes recent progresses in computational approaches for research of miRNA:TM interactions. We divided this article in three main contributions. First, a general overview of research on TMs in plants is presented with practical descriptions of the available literature, tools, data, databases and computational reports. Second, we describe a common protocol for the computational and experimental analyses of TM. Third, we provide a bioinformatics approach for the prediction of TM motifs potentially cross-targeting both members within the same or from different miRNA families, based on the identification of consensus miRNA-binding sites from known TMs across sequenced genomes, transcriptomes and known miRNAs. This computational approach is promising because, in contrast to animals, miRNA families in plants are large with identical or similar members, several of which are also highly conserved. From the three consensus TM motifs found with our approach: MIM166, MIM171 and MIM159/319, the last one has found strong support on the recent experimental work by Reichel and Millar [Specificity of plant microRNA TMs: cross-targeting of mir159 and mir319. J Plant Physiol 2015;180:45-8]. Finally, we stress the discussion on the major computational and associated experimental challenges that have to be faced in future ceRNA studies.

Background: Streptococcus agalactiae, also known as Group B Streptococcus (GBS), is a Gram-positive bacterium that colonizes the gastrointestinal and genitourinary tract of humans. This bacterium has also been isolated from various animals, such as fish and cattle. Non-coding RNAs (ncRNAs) can act as regulators of gene expression in bacteria, such as Streptococcus pneumoniae and Streptococcus pyogenes. However, little is known about the genomic distribution of ncRNAs and RNA families in S. agalactiae., Results: Comparative genome analysis of 27 S. agalactiae strains showed more than 5 thousand genomic regions identified and classified as Core, Exclusive, and Shared genome sequences. We identified 27 to 89 RNA families per genome distributed over these regions, from these, 25 were in Core regions while Shared and Exclusive regions showed variations amongst strains. We propose that the amount and type of ncRNA present in each genome can provide a pattern to contribute in the identification of the clonal types., Conclusions: The identification of RNA families provides an insight over ncRNAs, sRNAs and ribozymes function, that can be further explored as targets for antibiotic development or studied in gene regulation of cellular processes. RNA families could be considered as markers to determine infection capabilities of different strains. Lastly, pan-genome analysis of GBS including the full range of functional transcripts provides a broader approach in the understanding of this pathogen.

The mosquito Aedes aegypti (L.) is vector of several arboviruses including dengue, yellow fever, chikungunya, and more recently zika. Previous transcriptomic studies have been performed to elucidate altered pathways in response to viral infection. However, the intrinsic coupling between alimentation and infection were unappreciated in these studies. Feeding is required for the initial mosquito contact with the virus and these events are highly dependent. Addressing this relationship, we reinterrogated datasets of virus-infected mosquitoes with two different diet schemes (fed and unfed mosquitoes), evaluating the metabolic cross-talk during both processes. We constructed coexpression networks with the differentially expressed genes of these comparison: virus-infected versus blood-fed mosquitoes and virus-infected versus unfed mosquitoes. Our analysis identified one module with 110 genes that correlated with infection status (representing ~0.7% of the A. aegypti genome). Furthermore, we performed a machine-learning approach and summarized the infection status using only four genes (AAEL012128, AAEL014210, AAEL002477, and AAEL005350). While three of the four genes were annotated as hypothetical proteins, AAEL012128 gene is a membrane amino acid transporter correlated with viral envelope binding. This gene alone is able to discriminate all infected samples and thus should have a key role to discriminate viral infection in the A. aegypti mosquito. Moreover, validation using external datasets found this gene as differentially expressed in four transcriptomic experiments. Therefore, these genes may serve as a proxy of viral infection in the mosquito and the others 106 identified genes provides a framework to future studies.

Transposable elements (TEs) play an essential role in the genetic variability of eukaryotic species. In plants, they may comprise up to 90% of the total genome. Non-coding RNAs (ncRNAs) are known to control gene expression and regulation. Although the relationship between ncRNAs and TEs is known, obtaining the organized data for sequenced genomes is not straightforward. In this study, we describe the PlaNC-TE (http://planc-te.cp.utfpr.edu.br), a user-friendly portal harboring a knowledgebase created by integrating and analysing plant ncRNA-TE data. We identified a total of 14 350 overlaps between ncRNAs and TEs in 40 plant genomes. The database allows users to browse, search and download all ncRNA and TE data analysed. Overall, PlaNC-TE not only organizes data and provides insights about the relationship between ncRNA and TEs in plants but also helps improve genome annotation strategies. Moreover, this is the first database to provide resources to broadly investigate functions and mechanisms involving TEs and ncRNAs in plants.

The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status. More recently, a new study of Ae. aegypti infected with Zika virus (ZIKV) was published, providing new data to investigate whether this "infection" gene set is also altered during a ZIKV infection. Our hypothesis is that the infection-associated signature may also serve as a proxy to classify the ZIKV infection in the vector. Raw data associated with the NCBI/BioProject were downloaded and re-analysed. A total of 18 paired-end replicates corresponding to three ZIKV-infected samples and three controls were included in this study. The nMDS technique with a logistic regression was used to obtain the probabilities of belonging to a given class. Thus, to compare both gene sets, we used the area under the curve and performed a comparison using the bootstrap method. Our meta-signature was able to separate the infected mosquitoes from the controls with good predictive power to classify the Zika-infected mosquitoes.

Circulating nucleic acids are found in free form in body fluids and may serve as minimally invasive tools for cancer diagnosis and prognosis. Only a few studies have investigated the potential application of circulating mRNAs and microRNAs (miRNAs) in prostate cancer (PCa). The Cancer Genome Atlas (TCGA) database was used for an in silico analysis to identify circulating mRNA and miRNA as potential markers of PCa. A total of 2,267 genes and 49 miRNAs were differentially expressed between normal and tumor samples. The prediction analyses of target genes and integrative analysis of mRNA and miRNA expression revealed eleven genes and eight miRNAs which were validated by RT-qPCR in plasma samples from 102 untreated PCa patients and 50 cancer-free individuals. Two genes, OR51E2 and SIM2, and two miRNAs, miR-200c and miR-200b, showed significant association with PCa. Expression levels of these transcripts distinguished PCa patients from controls (67% sensitivity and 75% specificity). PCa patients and controls with prostate-specific antigen (PSA) ≤ 4.0 ng/mL were discriminated based on OR51E2 and SIM2 expression levels. The miR-200c expression showed association with Gleason score and miR-200b, with bone metastasis, bilateral tumor, and PSA > 10.0 ng/mL. The combination of circulating mRNA and miRNA was useful for the diagnosis and prognosis of PCa.

Despite the advanced stage of diamond thin-film technology, with applications ranging from superconductivity to biosensing, the realization of a stable and atomically thick two-dimensional diamond material, named here as diamondene, is still forthcoming. Adding to the outstanding properties of its bulk and thin-film counterparts, diamondene is predicted to be a ferromagnetic semiconductor with spin polarized bands. Here, we provide spectroscopic evidence for the formation of diamondene by performing Raman spectroscopy of double-layer graphene under high pressure. The results are explained in terms of a breakdown in the Kohn anomaly associated with the finite size of the remaining graphene sites surrounded by the diamondene matrix. Ab initio calculations and molecular dynamics simulations are employed to clarify the mechanism of diamondene formation, which requires two or more layers of graphene subjected to high pressures in the presence of specific chemical groups such as hydroxyl groups or hydrogens.The synthesis of two-dimensional diamond is the ultimate goal of diamond thin-film technology. Here, the authors perform Raman spectroscopy of bilayer graphene under pressure, and obtain spectroscopic evidence of formation of diamondene, an atomically thin form of diamond.

Transposable elements (TEs) comprise a major fraction of many plant genomes and are known to drive their organization and evolution. Several studies show that these repetitive elements have a prominent role in shaping noncoding regions of the genome such as microRNA (miRNA) loci, which are components of post-transcriptional regulation mechanisms. Although some studies have reported initial formation of miRNA loci from TE sequences, especially in model plants, the approaches that were used did not employ systems that would allow results to be delivered by a user-friendly database. In this study, we identified 152 precursor miRNAs overlapping TEs in 10 plant species. PlanTE-MIR DB was designed to assemble this data and deliver it to the scientific community interested in miRNA origin, evolution, and regulation pathways. Users can browse the database through a web interface and search for entries using various parameters. This resource is cross-referenced with repetitive element (Repbase Update) and miRNA (miRBase) repositories, where sequences can be checked for further analysis. All data in PlanTE-MIR DB are publicly available for download in several file formats to facilitate their understanding and use. The database is hosted at http://bioinfo-tool.cp.utfpr.edu.br/plantemirdb/ .

This report describes the miRQuest - a novel middleware available in a Web server that allows the end user to do the miRNA research in a user-friendly way. It is known that there are many prediction tools for microRNA (miRNA) identification that use different programming languages and methods to realize this task. It is difficult to understand each tool and apply it to diverse datasets and organisms available for miRNA analysis. miRQuest can easily be used by biologists and researchers with limited experience with bioinformatics. We built it using the middleware architecture on a Web platform for miRNA research that performs two main functions: i) integration of different miRNA prediction tools for miRNA identification in a user-friendly environment; and ii) comparison of these prediction tools. In both cases, the user provides sequences (in FASTA format) as an input set for the analysis and comparisons. All the tools were selected on the basis of a survey of the literature on the available tools for miRNA prediction. As results, three different cases of use of the tools are also described, where one is the miRNA identification analysis in 30 different species. Finally, miRQuest seems to be a novel and useful tool; and it is freely available for both benchmarking and miRNA identification at http://mirquest.integrativebioinformatics.me/.

Background: Small non-coding regulatory RNAs control cellular functions at the transcriptional and post-transcriptional levels. Oral squamous cell carcinoma is among the leading cancers in the world and the presence of cervical lymph node metastases is currently its strongest prognostic factor. In this work we aimed at finding small RNAs expressed in oral squamous cell carcinoma that could be associated with the presence of lymph node metastasis., Methods: Small RNA libraries from metastatic and non-metastatic oral squamous cell carcinomas were sequenced for the identification and quantification of known small RNAs. Selected markers were validated in plasma samples. Additionally, we used in silico analysis to investigate possible new molecules, not previously described, involved in the metastatic process., Results: Global expression patterns were not associated with cervical metastases. MiR-21, miR-203 and miR-205 were highly expressed throughout samples, in agreement with their role in epithelial cell biology, but disagreeing with studies correlating these molecules with cancer invasion. Eighteen microRNAs, but no other small RNA class, varied consistently between metastatic and non-metastatic samples. Nine of these microRNAs had been previously detected in human plasma, eight of which presented consistent results between tissue and plasma samples. MiR-31 and miR-130b, known to inhibit several steps in the metastatic process, were over-expressed in non-metastatic samples and the expression of miR-130b was confirmed in plasma of patients showing no metastasis. MiR-181 and miR-296 were detected in metastatic tumors and the expression of miR-296 was confirmed in plasma of patients presenting metastasis. A novel microRNA-like molecule was also associated with non-metastatic samples, potentially targeting cell-signaling mechanisms., Conclusions: We corroborate literature data on the role of small RNAs in cancer metastasis and suggest the detection of microRNAs as a tool that may assist in the evaluation of oral squamous cell carcinoma metastatic potential.

Coffee is one of the most important commodities in the world, and its production relies mainly on two species, Coffea arabica and Coffea canephora. Although there are diverse transcriptome datasets available for coffee trees, few research groups have exploited the potential knowledge contained in these data, especially with respect to fruit and seed development. Here, we present a comparative analysis of the transcriptomes of Coffea arabica and Coffea canephora with a focus on fruit development using publicly available expressed sequence tags (ESTs). Most of the fruit and seed EST data has been obtained from C. canephora. Therefore, we performed a fruit EST analysis of the 5 developmental stages of this species (18, 22, 30, 42, and 46 weeks after flowering) comprising 29,009 sequences. We compared C. canephora fruit ESTs to reference unigenes of C. canephora (7710 contigs and 8955 singletons) and C. arabica (15,656 contigs and 16,351 singletons). Additional analyses included functional annotation based on Gene Onthology, as well as an annotation using PlantCyc, a curated plant protein database. The Coffee Bean EST (CoffeebEST) is a public database available at http://bioinfo-02.cp.utfpr.edu.br/. This database represents an additional resource for the coffee scientific community, offering a user-friendly collection of information for non-specialists in coffee molecular biology to support experimental research on comparative and functional genomics.

MicroRNAs (miRNAs) are small molecules, noncoding proteins that are involved in many biological processes, especially in plants; among these processes is nodulation in the legume. Biological nitrogen fixation is a key process, with critical importance to the soybean crop. This study aimed to identify the potential of novel miRNAs to act during the root nodulation process. We utilized a set of transcripts that were differentially expressed in soybean roots 10 days after inoculation with Bradyrhizobium japonicum, which were obtained in a previous study, and performed a set of computational analyses that led us to select new miRNAs potentially involved in nodulation. Among these analyses, the set of transcripts were submitted to an in silico annotation of noncoding RNAs, including a search of similarity against miRNA public databases, ab initio tools for miRNA identification, structural search against miRNA families, prediction of the secondary structure of miRNA precursors, and prediction of the sequences of mature miRNAs. Subsequently, we applied filter procedures based on miRNA selections described in the literature (e.g., free energy value). In the next step, a manual curation inspection of the annotation was performed and the top candidates were selected and used for prediction of potential target genes, which were later checked manually in the database of the soybean genome. This prediction led us to the identification of 9 potential new miRNAs; among these, 4 were conserved in other plants. Moreover, we predicted their target genes might play important roles in the regulation of nodulation.

This study utilized the confocal Raman microspectroscopy (CRM) technique for the first time to investigate the degree of the penetration of toluidine blue-orto (TBO) in artificial caries lesions produced by two distinct caries-inducing models. The dentin specimens (n = 10) were divided into three groups: control, in vitro and in situ. Thereafter, the lesion depth and the demineralization level were evaluated by cross-sectional microhardness (CSMH). CRM mapping across the dentin surface was assessed after the dye application. The CSMH and CRM data were analyzed by t-test and ANOVA, respectively (P < 0.05). The values of the lesion depth and the demineralization areas were higher for in situ samples (P < 0.05). The TBO penetration values (μm) for the control, in vitro and in situ groups were 44.8 ± 5.6, 46.1 ± 4.5 and 51.2 ± 8.5, respectively. There were no statistically significant differences among the groups (P > 0.05). The rate of TBO penetration was detected up to about <50 μm and the demineralization level did not influence the results. These results have showed promising parameters to develop new protocols for deep caries lesions management using photodynamic antimicrobial chemotherapy., (© 2013 The American Society of Photobiology.)

Background: The implication of post-transcriptional regulation by microRNAs in molecular mechanisms underlying cancer disease is well documented. However, their interference at the cellular level is not fully explored. Functional in vitro studies are fundamental for the comprehension of their role; nevertheless results are highly dependable on the adopted cellular model. Next generation small RNA transcriptomic sequencing data of a tumor cell line and keratinocytes derived from primary culture was generated in order to characterize the microRNA content of these systems, thus helping in their understanding. Both constitute cell models for functional studies of microRNAs in head and neck squamous cell carcinoma (HNSCC), a smoking-related cancer. Known microRNAs were quantified and analyzed in the context of gene regulation. New microRNAs were investigated using similarity and structural search, ab initio classification, and prediction of the location of mature microRNAs within would-be precursor sequences. Results were compared with small RNA transcriptomic sequences from HNSCC samples in order to access the applicability of these cell models for cancer phenotype comprehension and for novel molecule discovery., Results: Ten miRNAs represented over 70% of the mature molecules present in each of the cell types. The most expressed molecules were miR-21, miR-24 and miR-205, Accordingly; miR-21 and miR-205 have been previously shown to play a role in epithelial cell biology. Although miR-21 has been implicated in cancer development, and evaluated as a biomarker in HNSCC progression, no significant expression differences were seen between cell types. We demonstrate that differentially expressed mature miRNAs target cell differentiation and apoptosis related biological processes, indicating that they might represent, with acceptable accuracy, the genetic context from which they derive. Most miRNAs identified in the cancer cell line and in keratinocytes were present in tumor samples and cancer-free samples, respectively, with miR-21, miR-24 and miR-205 still among the most prevalent molecules at all instances. Thirteen miRNA-like structures, containing reads identified by the deep sequencing, were predicted from putative miRNA precursor sequences. Strong evidences suggest that one of them could be a new miRNA. This molecule was mostly expressed in the tumor cell line and HNSCC samples indicating a possible biological function in cancer., Conclusions: Critical biological features of cells must be fully understood before they can be chosen as models for functional studies. Expression levels of miRNAs relate to cell type and tissue context. This study provides insights on miRNA content of two cell models used for cancer research. Pathways commonly deregulated in HNSCC might be targeted by most expressed and also by differentially expressed miRNAs. Results indicate that the use of cell models for cancer research demands careful assessment of underlying molecular characteristics for proper data interpretation. Additionally, one new miRNA-like molecule with a potential role in cancer was identified in the cell lines and clinical samples.

Large-scale transcriptome projects have shown that the number of RNA transcripts not coding for proteins (non-coding RNAs) is much larger than previously recognized. High-throughput technologies, coupled with bioinformatics approaches, have produced increasing amounts of data, highlighting the role of non-coding RNAs (ncRNAs) in biological processes. Data generated by these studies include diverse non-coding RNA classes from organisms of different kingdoms, which were obtained using different experimental and computational assays. This has led to a rapid increase of specialized RNA databases. The fast growth in the number of available databases makes integration of stored information a difficult task. We present here NRDR, a Non-coding RNA Databases Resource for information retrieval on ncRNA databases (www.ncrnadatabases.org). We performed a survey of 102 public databases on ncRNAs and we have introduced four categorizations to classify these databases and to help researchers quickly search and find the information they need: RNA family, information source, information content and available search mechanisms. NRDR is a useful databases searching tool that will facilitate research on ncRNAs.