miRNATissueAtlas2: an update to the human miRNA tissue atlas.

Small non-coding RNAs (sncRNAs) are pervasive regulators of physiological and pathological processes. We previously developed the human miRNA Tissue Atlas, detailing the expression of miRNAs across organs in the human body. Here, we present an updated resource containing sequencing data of 188 tissue samples comprising 21 organ types retrieved from six humans. Sampling the organs from the same bodies minimizes intra-individual variability and facilitates the making of a precise high-resolution body map of the non-coding transcriptome. The data allow shedding light on the organ- and organ system-specificity of piwi-interacting RNAs (piRNAs), transfer RNAs (tRNAs), microRNAs (miRNAs) and other non-coding RNAs. As use case of our resource, we describe the identification of highly specific ncRNAs in different organs. The update also contains 58 samples from six tissues of the Tabula Muris collection, allowing to check if the tissue specificity is evolutionary conserved between Homo sapiens and Mus musculus. The updated resource of 87 252 non-coding RNAs from nine non-coding RNA classes for all organs and organ systems is available online without any restrictions (https://www.ccb.uni-saarland.de/tissueatlas2).

Pol3Base: a resource for decoding the interactome, expression, evolution, epitranscriptome and disease variations of Pol III-transcribed ncRNAs.

RNA polymerase III (Pol III) transcribes hundreds of non-coding RNA genes (ncRNAs), which involve in a variety of cellular processes. However, the expression, functions, regulatory networks and evolution of these Pol III-transcribed ncRNAs are still largely unknown. In this study, we developed a novel resource, Pol3Base (http://rna.sysu.edu.cn/pol3base/), to decode the interactome, expression, evolution, epitranscriptome and disease variations of Pol III-transcribed ncRNAs. The current release of Pol3Base includes thousands of regulatory relationships between ∼79 000 ncRNAs and transcription factors by mining 56 ChIP-seq datasets. By integrating CLIP-seq datasets, we deciphered the interactions of these ncRNAs with >240 RNA binding proteins. Moreover, Pol3Base contains ∼9700 RNA modifications located within thousands of Pol III-transcribed ncRNAs. Importantly, we characterized expression profiles of ncRNAs in >70 tissues and 28 different tumor types. In addition, by comparing these ncRNAs from human and mouse, we revealed about 4000 evolutionary conserved ncRNAs. We also identified ∼11 403 tRNA-derived small RNAs (tsRNAs) in 32 different tumor types. Finally, by analyzing somatic mutation data, we investigated the mutation map of these ncRNAs to help uncover their potential roles in diverse diseases. This resource will help expand our understanding of potential functions and regulatory networks of Pol III-transcribed ncRNAs.

tsRFun: a comprehensive platform for decoding human tsRNA expression, functions and prognostic value by high-throughput small RNA-Seq and CLIP-Seq data.

tRNA-derived small RNA (tsRNA), a novel type of regulatory small noncoding RNA, plays an important role in physiological and pathological processes. However, the understanding of the functional mechanism of tsRNAs in cells and their role in the occurrence and development of diseases is limited. Here, we integrated multiomics data such as transcriptome, epitranscriptome, and targetome data, and developed novel computer tools to establish tsRFun, a comprehensive platform to facilitate tsRNA research (http://rna.sysu.edu.cn/tsRFun/ or http://biomed.nscc-gz.cn/DB/tsRFun/). tsRFun evaluated tsRNA expression profiles and the prognostic value of tsRNAs across 32 types of cancers, identified tsRNA target molecules utilizing high-throughput CLASH/CLEAR or CLIP sequencing data, and constructed the interaction networks among tsRNAs, microRNAs, and mRNAs. In addition to its data presentation capabilities, tsRFun offers multiple real-time online tools for tsRNA identification, target prediction, and functional enrichment analysis. In summary, tsRFun provides a valuable data resource and multiple analysis tools for tsRNA investigation.

Transfer- or 'transmission'-RNA fragments? The roles of tsRNAs in the reproductive system.

Transfer-RNAs (tRNAs) help ribosomes decode mRNAs and synthesize proteins; however, tRNA fragments produced under certain conditions, known as tRNA-derived small RNAs (tsRNAs), have been found to play important roles in pathophysiological processes. In the reproductive system, tsRNAs are abundant in gametes and embryos and at the maternal-fetal interface, as well as in microvesicles like epididymosomes, seminal plasma exosomes, and syncytiotrophoblast-derived extracellular vesicles. tsRNAs can affect gamete cell maturation, zygote activation, and early embryonic development. tsRNAs can transmit epigenetic information to later generations. In particular, exposure to environmental factors such as nutrition, isoproterenol, and poly(I:C) may allow tsRNAs to transfer information to the gametes or placenta to alter offspring phenotype. The underlying mechanisms of tsRNAs action include transposon silencing, translation regulation, and target mRNA degradation. Herein, we review the currently reported tsRNAs in the reproductive system, their validated functions, and potential roles. A better understanding of this field may help to provide useful recommendations or develop strategies to increase fertility and conception of healthy babies.

Comprehensive annotation and characterization of planarian tRNA and tRNA-derived fragments (tRFs).

tRNA-derived fragments (tRFs) have recently gained a lot of scientific interest due to their diverse regulatory roles in several cellular processes. However, their function in dynamic biological processes such as development and regeneration remains unexplored. Here, we show that tRFs are dynamically expressed during planarian regeneration, suggesting a possible role for these small RNAs in the regulation of regeneration. In order to characterize planarian tRFs, we first annotated 457 tRNAs in S. mediterranea combining two tRNA prediction algorithms. Annotation of tRNAs facilitated the identification of three main species of tRFs in planarians-the shorter tRF-5s and itRFs, and the abundantly expressed 5'-tsRNAs. Spatial profiling of tRFs in sequential transverse sections of planarians revealed diverse expression patterns of these small RNAs, including those that are enriched in the head and pharyngeal regions. Expression analysis of these tRF species revealed dynamic expression of these small RNAs over the course of regeneration suggesting an important role in planarian anterior and posterior regeneration. Finally, we show that 5'-tsRNA in planaria interact with all three SMEDWI proteins and an involvement of AGO1 in the processing of itRFs. In summary, our findings implicate a novel role for tRFs in planarian regeneration, highlighting their importance in regulating complex systemic processes. Our study adds to the catalog of posttranscriptional regulatory systems in planaria, providing valuable insights on the biogenesis and the function of tRFs in neoblasts and planarian regeneration.

Characterization of the complete mitochondrial genome of Macrotocinclus affinis (Siluriformes; Loricariidae) and phylogenetic studies of Siluriformes.

The vertebrate mitochondrial genome is typically circular molecules made up of 14,000 to 16,000 bp, including 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), two ribosomal RNA genes (12 s rRNA and 16 s rRNA) and a control region. Compared with nuclear DNA, mitochondrial DNA has a higher mutation rate, so it is one of the most effective and reliable molecular markers in fish phylogeny. Macrotocinclus affinis was the only species in Macrotocinclus (it was classified as Otocinclus in the past) and currently lacks genetic information. Most of the current researches are based on the mitochondrial Cytb gene and RAG1 and RAG2 nuclear genes to study the phylogenetic analysis of Siluriformes. So, the study provides the characteristic features of the Macrotocinclus affinis mitochondrial genome and this is the first time that the phylogenetic relationship of Siluriformes has been reconstructed based on COI. We aimed to sequence the entire mitochondrial genome of Macrotocinclus affinis using conventional PCR techniques and to clarify its phylogenetic status in Siluriformes by using the COI sequence of mitochondria. In this study, we sequenced the whole mitochondrial genome of this species yielding a 16,632 bp circular assembly composed of the typical vertebrate mitochondrial features. It contains 13 protein-coding genes, two rRNA genes, 22 tRNA genes, a putative control region, and one origin of replication on the light-strand. The overall base composition includes A (30.07%), T (24.43%), C (29.43%) and G (16.01%). The genome composition is A + T biased (54.5%), and exhibits AT-skew (0.1036) and GC-skew (-0.2962). Moreover, the 13 PCGs encode 3850 amino acids in total. The result of the phylogenetic tree supports Macrotocinclus affinis has a closest relationship with Otocinclus cf. hoppei far. These results will help to understand the characteristics of the mitochondrial genome of Macrotocinclus affinis and provide molecular basis for the evolutionary relationship of Loricariidae.

cncRNAdb: a manually curated resource of experimentally supported RNAs with both protein-coding and noncoding function.

RNA endowed with both protein-coding and noncoding functions is referred to as 'dual-function RNA', 'binary functional RNA (bifunctional RNA)' or 'cncRNA (coding and noncoding RNA)'. Recently, an increasing number of cncRNAs have been identified, including both translated ncRNAs (ncRNAs with coding functions) and untranslated mRNAs (mRNAs with noncoding functions). However, an appropriate database for storing and organizing cncRNAs is still lacking. Here, we developed cncRNAdb, a manually curated database of experimentally supported cncRNAs, which aims to provide a resource for efficient manipulation, browsing and analysis of cncRNAs. The current version of cncRNAdb documents about 2600 manually curated entries of cncRNA functions with experimental evidence, involving more than 2,000 RNAs (including over 1300 translated ncRNAs and over 600 untranslated mRNAs) across over 20 species. In summary, we believe that cncRNAdb will help elucidate the functions and mechanisms of cncRNAs and develop new prediction methods. The database is available at http://www.rna-society.org/cncrnadb/.

Small RNA Sequencing Reveals Transfer RNA-derived Small RNA Expression Profiles in Retinal Neovascularization.

Retinal neovascularization (RNV) is characterized in retinopathy of prematurity (ROP), diabetic retinopathy (DR), and retinal vein occlusion (RVO), which leads to severe vision loss and even blindness. To reveal the altered transfer RNA-derived small RNA (tsRNA)s in RNV, and to investigate the underlying mechanisms of the altered tsRNAs involved in RNV, we carried out a small RNA sequencing to profile tsRNA expressions in the retinas of mice with oxygen-induced retinopathy (OIR) and control mice. A total of 45 tsRNAs were significantly changed (fold change ≥ 1.5 and P < 0.05) in the retinas of OIR mice compared with controls. Validation by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) in four selected tsRNAs was consistent with the results of small RNA sequencing. Bioinformatics analyses identified 153 altered target genes of the four validated tsRNAs. These altered target genes were largely enriched in developmental process, cell periphery and protein binding, as well as Th1 and Th2 cell differentiation pathway. Our study suggests tsRNAs play key roles in the pathogenesis of RNV, indicating their therapeutic potential to treat patients with RNV. Moreover, small RNA sequencing is a useful tool to identify changes in tsRNA expression, an important indicator of the progress of retinal diseases.

Extracellular tRNAs and tRNA-derived fragments.

Fragmentation of tRNAs generates a family of small RNAs collectively known as tRNA-derived fragments. These fragments vary in sequence and size but have been shown to regulate many processes involved in cell homoeostasis and adaptations to stress. Additionally, the field of extracellular RNAs (exRNAs) is rapidly growing because exRNAs are a promising source of biomarkers in liquid biopsies, and because exRNAs seem to play key roles in intercellular and interspecies communication. Herein, we review recent descriptions of tRNA-derived fragments in the extracellular space in all domains of life, both in biofluids and in cell culture. The purpose of this review is to find consensus on which tRNA-derived fragments are more prominent in each extracellular fraction (including extracellular vesicles, lipoproteins and ribonucleoprotein complexes). We highlight what is becoming clear and what is still controversial in this field, in order to stimulate future hypothesis-driven studies which could clarify the role of full-length tRNAs and tRNA-derived fragments in the extracellular space.

Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA.

The study of RNA expression is the fastest growing area of genomic research. However, despite the dramatic increase in the number of sequenced transcriptomes, we still do not have accurate estimates of the number and expression levels of non-coding RNA genes. Non-coding transcripts are often overlooked due to incomplete genome annotation. In this study, we use annotation-independent detection of RNA reads generated using a reverse transcriptase with low structure bias to identify non-coding RNA. Transcripts between 20 and 500 nucleotides were filtered and crosschecked with non-coding RNA annotations revealing 111 non-annotated non-coding RNAs expressed in different cell lines and tissues. Inspecting the sequence and structural features of these transcripts indicated that 60% of these transcripts correspond to new snoRNA and tRNA-like genes. The identified genes exhibited features of their respective families in terms of structure, expression, conservation and response to depletion of interacting proteins. Together, our data reveal a new group of RNA that are difficult to detect using standard gene prediction and RNA sequencing techniques, suggesting that reliance on actual gene annotation and sequencing techniques distorts the perceived architecture of the human transcriptome.

Structural and phylogenetic implications of the complete mitochondrial genome of Ledra auditura.

We sequenced and annotated the first complete mitochondrial genome (mitogenome) of Ledra auditura (Hemiptera: Cicadellidae: Ledrinae) and reconstructed phylogenetic relationships among 47 species (including 2 outgroup species) on the basis of 3 datasets using maximum likelihood (ML) and Bayesian inference (BI) analyses. The complete L. auditura mitogenome (length, 16,094 bp) comprises 37 genes [13 protein-coding genes (PCGs), 22 tRNAs, and 2 rRNAs], 1 control region, and 2 long non-coding regions. The first long non-coding region (length, 211 bp) is located between tRNA-I and tRNA-Q and the second region (length, 994 bp) between tRNA-S2 and ND1. All PCGs show ATN (Met/Ile) as their start codon and TAR as their stop codon. Except tRNA-S1 (AGN), which lacks the dihydrouridine arm, all tRNAs can fold into the typical cloverleaf secondary structure. The complete L. auditura mitogenome shows a base composition bias of 76.3% A + T (A = 29.9%, T = 46.4%, G = 13.3%, and C = 10.5%), negative AT skew of -0.22, and positive GC skew of 0.12. In ML and BI analyses, L. auditura was clustered with Evacanthus heimianus (Hemiptera: Cicadellidae: Evacanthinae) with strong branch support.

Isolation of Yasminevirus, the First Member of Klosneuvirinae Isolated in Coculture with Vermamoeba vermiformis, Demonstrates an Extended Arsenal of Translational Apparatus Components.

The family of giant viruses is still expanding, and evidence of a translational machinery is emerging in the virosphere. The Klosneuvirinae group of giant viruses was first reconstructed from in silico studies, and then a unique member was isolated, Bodo saltans virus. Here we describe the isolation of a new member in this group using coculture with the free-living amoeba Vermamoeba vermiformis This giant virus, called Yasminevirus, has a 2.1-Mb linear double-stranded DNA genome encoding 1,541 candidate proteins, with a GC content estimated at 40.2%. Yasminevirus possesses a nearly complete translational machinery, with a set of 70 tRNAs associated with 45 codons and recognizing 20 amino acids (aa), 20 aminoacyl-tRNA synthetases (aaRSs) recognizing 20 aa, as well as several translation factors and elongation factors. At the genome scale, evolutionary analyses placed this virus in the Klosneuvirinae group of giant viruses. Rhizome analysis demonstrated that the genome of Yasminevirus is mosaic, with ∼34% of genes having their closest homologues in other viruses, followed by ∼13.2% in Eukaryota, ∼7.2% in Bacteria, and less than 1% in Archaea Among giant virus sequences, Yasminevirus shared 87% of viral hits with Klosneuvirinae. This description of Yasminevirus sheds light on the Klosneuvirinae group in a captivating quest to understand the evolution and diversity of giant viruses.IMPORTANCE Yasminevirus is an icosahedral double-stranded DNA virus isolated from sewage water by amoeba coculture. Here its structure and replicative cycle in the amoeba Vermamoeba vermiformis are described and genomic and evolutionary studies are reported. This virus belongs to the Klosneuvirinae group of giant viruses, representing the second isolated and cultivated giant virus in this group, and is the first isolated using a coculture procedure. Extended translational machinery pointed to Yasminevirus among the quasiautonomous giant viruses with the most complete translational apparatus of the known virosphere.

tRNAviz: explore and visualize tRNA sequence features.

Transfer RNAs (tRNAs) are ubiquitous across the tree of life. Although tRNA structure is highly conserved, there is still significant variation in sequence features between clades, isotypes and even isodecoders. This variation not only impacts translation, but as shown by a variety of recent studies, nontranslation-associated functions are also sensitive to small changes in tRNA sequence. Despite the rapidly growing number of sequenced genomes, there is a lack of tools for both small- and large-scale comparative genomics analysis of tRNA sequence features. Here, we have integrated over 150 000 tRNAs spanning all domains of life into tRNAviz, a web application for exploring and visualizing tRNA sequence features. tRNAviz implements a framework for determining consensus sequence features and can generate sequence feature distributions by isotypes, clades and anticodons, among other tRNA properties such as score. All visualizations are interactive and exportable. The web server is publicly available at http://trna.ucsc.edu/tRNAviz/.

DNA damage-induced cell death relies on SLFN11-dependent cleavage of distinct type II tRNAs.

Transcriptome analysis reveals a strong positive correlation between human Schlafen family member 11 (SLFN11) expression and the sensitivity of tumor cells to DNA-damaging agents (DDAs). Here, we show that SLFN11 preferentially inhibits translation of the serine/threonine kinases ATR and ATM upon DDA treatment based on distinct codon usage without disrupting early DNA damage response signaling. Type II transfer RNAs (tRNAs), which include all serine and leucine tRNAs, are cleaved in a SLFN11-dependent manner in response to DDAs. Messenger RNAs encoded by genes with high TTA (Leu) codon usage, such as ATR, display utmost susceptibility to translational suppression by SLFN11. Specific attenuation of tRNA-Leu-TAA sufficed to ablate ATR protein expression and restore the DDA sensitivity of SLFN11-deficient cells. Our study uncovered a novel mechanism of codon-specific translational inhibition via SLFN11-dependent tRNA cleavage in the DNA damage response and supports the notion that SLFN11-deficient tumor cells can be resensitized to DDAs by targeting ATR or tRNA-Leu-TAA.

Convolutional neural networks for classification of alignments of non-coding RNA sequences.

Motivation: The convolutional neural network (CNN) has been applied to the classification problem of DNA sequences, with the additional purpose of motif discovery. The training of CNNs with distributed representations of four nucleotides has successfully derived position weight matrices on the learned kernels that corresponded to sequence motifs such as protein-binding sites. Results: We propose a novel application of CNNs to classification of pairwise alignments of sequences for accurate clustering of sequences and show the benefits of the CNN method of inputting pairwise alignments for clustering of non-coding RNA (ncRNA) sequences and for motif discovery. Classification of a pairwise alignment of two sequences into positive and negative classes corresponds to the clustering of the input sequences. After we combined the distributed representation of RNA nucleotides with the secondary-structure information specific to ncRNAs and furthermore with mapping profiles of next-generation sequence reads, the training of CNNs for classification of alignments of RNA sequences yielded accurate clustering in terms of ncRNA families and outperformed the existing clustering methods for ncRNA sequences. Several interesting sequence motifs and secondary-structure motifs known for the snoRNA family and specific to microRNA and tRNA families were identified. Availability and implementation: The source code of our CNN software in the deep-learning framework Chainer is available at http://www.dna.bio.keio.ac.jp/cnn/, and the dataset used for performance evaluation in this work is available at the same URL.

The first mitochondrial genomes for Pyralinae (Pyralidae) and Glaphyriinae (Crambidae), with phylogenetic implications of Pyraloidea.

In the present study, we report five complete and one nearly complete mitochondrial genomes of the Pyraloidea including the first representatives from the Pyralinae (Pyralidae) and Glaphyriinae (Crambidae). We also conduct a comparative analysis of mitogenomic features of this group. Our results show that Pyraloidea mitogenomes evolved under a common trend found in lepidopteran mitogenomes and share several typical genomic characters. The extra conserved blocks are identified in the Pyraloidea control region, and diverse missing codons formed another unique trait within Pyraloidea mitogenome. Furthermore, we reconstruct the mitogenomic phylogeny of Pyraloidea and confirm the phylogenetic position of Pyralinae and Glaphyriinae within the Pyraloidea using BI and ML method based on multiple mitochondrial datasets.

Draft genome of the milu (Elaphurus davidianus).

Background: Milu, also known as Père David's deer (Elaphurus davidianus), was widely distributed in East Asia but recently experienced a severe bottleneck. Only 18 survived by the end of the 19th century, and the current population of 4500 individuals was propagated from just 11 kept by the 11th British Duke of Bedford. This species is known for its distinguishable appearance, the driving force behind which is still a mystery. To aid efforts to explore these phenomena, we constructed a draft genome of the species. Findings: In total, we generated 321.86 gigabases (Gb) of raw DNA sequence from whole-genome sequencing of a male milu deer using an Illumina HiSeq 2000 platform. Assembly yielded a final genome with a scaffold N50 size of 3.03 megabases (Mb) and a total length of 2.52 Gb. Moreover, we identified 20 125 protein-coding genes and 988.1 Mb of repetitive sequences. In addition, homology-based searches detected 280 rRNA, 1335 miRNA, 1441 snRNA, and 893 tRNA sequences in the milu genome. The divergence time between E. davidianus and Bos taurus was estimated to be about 28.20 million years ago (Mya). We identified 167 species-specific genes and 293 expanded gene families in the milu lineage. Conclusions: We report the first reference genome of milu, which will provide a valuable resource for studying the species' demographic history of severe bottleneck and the genetic mechanism(s) of special phenotypic evolution.

A comparative study of sequence- and structure-based features of small RNAs and other RNAs of bacteria.

Small RNAs (sRNAs) in bacteria have emerged as key players in transcriptional and post-transcriptional regulation of gene expression. Here, we present a statistical analysis of different sequence- and structure-related features of bacterial sRNAs to identify the descriptors that could discriminate sRNAs from other bacterial RNAs. We investigated a comprehensive and heterogeneous collection of 816 sRNAs, identified by northern blotting across 33 bacterial species and compared their various features with other classes of bacterial RNAs, such as tRNAs, rRNAs and mRNAs. We observed that sRNAs differed significantly from the rest with respect to G+C composition, normalized minimum free energy of folding, motif frequency and several RNA-folding parameters like base-pairing propensity, Shannon entropy and base-pair distance. Based on the selected features, we developed a predictive model using Random Forests (RF) method to classify the above four classes of RNAs. Our model displayed an overall predictive accuracy of 89.5%. These findings would help to differentiate bacterial sRNAs from other RNAs and further promote prediction of novel sRNAs in different bacterial species.

The discovery potential of RNA processing profiles.

Small non-coding RNAs (sncRNAs) are highly abundant molecules that regulate essential cellular processes and are classified according to sequence and structure. Here we argue that read profiles from size-selected RNA sequencing capture the post-transcriptional processing specific to each RNA family, thereby providing functional information independently of sequence and structure. We developed SeRPeNT, a new computational method that exploits reproducibility across replicates and uses dynamic time-warping and density-based clustering algorithms to identify, characterize and compare sncRNAs by harnessing the power of read profiles. We applied SeRPeNT to: (i) generate an extended human annotation with 671 new sncRNAs from known classes and 131 from new potential classes, (ii) show pervasive differential processing of sncRNAs between cell compartments and (iii) predict new molecules with miRNA-like behaviour from snoRNA, tRNA and long non-coding RNA precursors, potentially dependent on the miRNA biogenesis pathway. Furthermore, we validated experimentally four predicted novel non-coding RNAs: a miRNA, a snoRNA-derived miRNA, a processed tRNA and a new uncharacterized sncRNA. SeRPeNT facilitates fast and accurate discovery and characterization of sncRNAs at an unprecedented scale. SeRPeNT code is available under the MIT license at https://github.com/comprna/SeRPeNT.

Resolution of the enigmatic phylogenetic relationship of the critically endangered Western Swamp Tortoise Pseudemydura umbrina (Pleurodira: Chelidae) using a complete mitochondrial genome.

Pseudemydura umbrina is one of the most endangered turtle species in the world, and the imperative for its conservation is its distinctive morphology and relict status among the Chelidae. We use Illumina sequencing to obtain the complete mitogenome for resolving its uncertain phylogenetic position. A novel nuclear paralogue confounded the assembly, and resolution of the authentic mitogenome required further Sanger sequencing. The P. umbrina mitogenome is 16,414bp comprising 37 genes organized in a conserved pattern for other vertebrates. The nuclear paralogue is 547bp, 97.8% identity to the corresponding mitochondrial sequence. Particular features of the mitogenome include an nd3 174+1A frameshift, loss of DHC loop in tRNASer (AGN), and a light-strand replication initiation site in Wancy region that extends into an adjacent tRNA gene. Phylogenetic analysis showed that P. umbrina is the monotypic sister lineage to the remaining Australasian Chelidae, a lineage probably dating back to the Cretaceous.