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Large-scale sequencing experiments are complex and require a wide spectrum of computational tools to extract and interpret relevant biological information. This is especially true in projects where individual processing and integrated analysis of both small RNA and complementary RNA data is needed. Such studies would benefit from a computational workflow that is easy to implement and standardizes the processing and analysis of both sequenced data types.
The L RNA of three Lassa virus strains originating from Nigeria, Ghana/Ivory Coast, and Sierra Leone was sequenced and the data subjected to structure predictions and phylogenetic analyses. The L gene products had 2218-2221 residues, diverged by 18% at the amino acid level, and contained several conserved regions. Only one region of 504 residues (positions 1043-1546) could be assigned a function, namely that of an RNA polymerase. Secondary structure predictions suggest that this domain is very similar to RNA-dependent RNA polymerases of known structure encoded by plus-strand RNA viruses, permitting a model to be built. Outside the polymerase region, there is little structural data, except for regions of strong alpha-helical content and probably a coiled-coil domain at the N terminus. No evidence for reassortment or recombination during Lassa virus evolution was found. The secondary structure-assisted alignment of the RNA polymerase region permitted a reliable reconstruction of the phylogeny of all negative-strand RNA viruses, indicating that Arenaviridae are most closely related to Nairoviruses. In conclusion, the data provide a basis for structural and functional characterization of the Lassa virus L protein and reveal new insights into the phylogeny of negative-strand RNA viruses.
Transcription in all cellular organisms is performed by multisubunit, DNA-dependent RNA polymerases that synthesize RNA from DNA templates. Previous sequence and structural studies have elucidated the importance of shared regions common to all multisubunit RNA polymerases. In addition, RNA polymerases contain multiple lineage-specific domain insertions involved in protein-protein and protein-nucleic acid interactions. We have created comprehensive multiple sequence alignments using all available sequence data for the multisubunit RNA polymerase large subunits, including the bacterial beta and beta' subunits and their homologs from archaebacterial RNA polymerases, the eukaryotic RNA polymerases I, II, and III, the nuclear-cytoplasmic large double-stranded DNA virus RNA polymerases, and plant plastid RNA polymerases. To overcome technical difficulties inherent to the large-subunit sequences, including large sequence length, small and large lineage-specific insertions, split subunits, and fused proteins, we created an automated and customizable sequence retrieval and processing system. In addition, we used our alignments to create a more expansive set of shared sequence regions and bacterial lineage-specific domain insertions. We also analyzed the intergenic gap between the bacterial beta and beta' genes.
Circular RNAs (circRNAs), as a burgeoning sort of non-coding RNAs (ncRNAs), can regulate the expression of parental genes as miRNA sponges. This study was designed to explore the circRNA expression profile of nasopharyngeal carcinoma (NPC). High-throughput sequencing was performed to identify the circRNA expression profile of NPC patients compared with healthy controls. A total of 93 upregulated circRNAs and 77 downregulated circRNAs were identified. The expression levels of the top three upregulated and three downregulated circRNAs annotated by circBase were validated by quantitative real-time PCR (qRT-PCR). GO and KEGG analyses showed that these differentially expressed circRNAs were potentially implicated in NPC pathogenesis. CircRNA-miRNA-target gene network analysis revealed a potential mechanism that hsa_circ_0002375 (circKITLG) may be involved in NPC through sponging up miR-3198 and interfering with its downstream targets. Silencing of circKITLG inhibited NPC cell proliferation, migration, and invasion in vitro. This study provides a leading and fundamental circRNA expression profile of NPC.
Peronospora destructor (Berk.) is an important biotrophic oomycete that causes downy mildew on onion (Allium Cepa L.) worldwide, especially in humid and temperate regions. The disease attacks bulb and seed production of onion, resulting in losses in yield and quality of bulbs. Epidemiological studies have increased our understanding and control of downy mildew on onion; however, little is known about the molecular aspects of P. destructor behavior during infection. Here, we isolated RNA from four samples of sporangia and sporangiophores of P. destructor, which were maintained by spore inoculation onto onions in a growth chamber. We then used an Ion PGM next generation sequencer to acquire and assemble the RNA sequences of P. destructor. By transcriptome shotgun assembly, we obtained 2335 contigs (N50, 884 nucleotides (nt); mean length, 881.6 nt). The data are accessible at NCBI (BioProject PRJNA391849). Our data resource will facilitate further studies of the molecular events during P. destructor infection.
Next-generation sequencing (NGS) technologies-based transcriptomic profiling method often called RNA-seq has been widely used to study global gene expression, alternative exon usage, new exon discovery, novel transcriptional isoforms and genomic sequence variations. However, this technique also poses many biological and informatics challenges to extracting meaningful biological information. The RNA-seq data analysis is built on the foundation of high quality initial genome localization and alignment information for RNA-seq sequences. Toward this goal, we have developed RNASEQR to accurately and effectively map millions of RNA-seq sequences. We have systematically compared RNASEQR with four of the most widely used tools using a simulated data set created from the Consensus CDS project and two experimental RNA-seq data sets generated from a human glioblastoma patient. Our results showed that RNASEQR yields more accurate estimates for gene expression, complete gene structures and new transcript isoforms, as well as more accurate detection of single nucleotide variants (SNVs). RNASEQR analyzes raw data from RNA-seq experiments effectively and outputs results in a manner that is compatible with a wide variety of specialized downstream analyses on desktop computers.
The identification of full length transcripts entirely from short-read RNA sequencing data (RNA-seq) remains a challenge in the annotation of genomes. Here we describe an automated pipeline for genome annotation that integrates RNA-seq and gene-boundary data sets, which we call Generalized RNA Integration Tool, or GRIT. Applying GRIT to Drosophila melanogaster short-read RNA-seq, cap analysis of gene expression (CAGE) and poly(A)-site-seq data collected for the modENCODE project, we recovered the vast majority of previously annotated transcripts and doubled the total number of transcripts cataloged. We found that 20% of protein coding genes encode multiple protein-localization signals and that, in 20-d-old adult fly heads, genes with multiple polyadenylation sites are more common than genes with alternative splicing or alternative promoters. GRIT demonstrates 30% higher precision and recall than the most widely used transcript assembly tools. GRIT will facilitate the automated generation of high-quality genome annotations without the need for extensive manual annotation.
It is well known that dermal papilla cells (DPCs) are crucial for hair follicle growth and regeneration. However, dermal papilla cells in 2D culture could lose their ability of regeneration after several passage intervals. As opposed to DPCs in 2D culture, the DPCs in 3D culture could passage extensively. However, the molecular mechanisms of DPCs' regeneration in 3D culture remain unclear. Accordingly, gene sequencing is recommended for the investigation of hair regeneration between 2D and 3D culture, the three groups were established including DPCs in passage 2 in 2D culture, DPCs in passage 8 in 2D culture and DPCs in passage 8 in 3D culture. The differentially expressed genes (DEGs) were identified using the Venn diagram of these three groups, which included 1642 known and 359 novel genes, respectively. A total of 1642 known genes were used for Gene Ontology (GO), Kyoto Gene, Genomic Encyclopedia (KEGG) pathway enrichment and protein-protein interaction (PPI) analyses, respectively. The functions and pathways of DEGs were enriched in biological regulation, signal transduction and immune system, etc. The key module and the top 10 hub genes (IL1B, CXCL12, HGF, EGFR, APP, CCL2, PTGS2, MMP9, NGF and SPP1) were also identified using the Cytoscape application. Furthermore, the qRT-PCR results of the three groups validated that the hub genes were crucial for hair growth. In conclusion, the ten identified hub genes and related pathways in the current study can be used to understand the molecular mechanism of hair growth, and those provided a possibility for hair regeneration.
The dramatic increase in the number of single-cell RNA-sequence (scRNA-seq) investigations is indeed an endorsement of the new-fangled proficiencies of next generation sequencing technologies that facilitate the accurate measurement of tens of thousands of RNA expression levels at the cellular resolution. Nevertheless, missing values of RNA amplification persist and remain as a significant computational challenge, as these data omission induce further noise in their respective cellular data and ultimately impede downstream functional analysis of scRNA-seq data. Consequently, it turns imperative to develop robust and efficient scRNA-seq data imputation methods for improved downstream functional analysis outcomes. To overcome this adversity, we have designed an imputation framework namely deep generative autoencoder network [DGAN]. In essence, DGAN is an evolved variational autoencoder designed to robustly impute data dropouts in scRNA-seq data manifested as a sparse gene expression matrix. DGAN principally reckons count distribution, besides data sparsity utilizing a gaussian model whereby, cell dependencies are capitalized to detect and exclude outlier cells via imputation. When tested on five publicly available scRNA-seq data, DGAN outperformed every single baseline method paralleled, with respect to downstream functional analysis including cell data visualization, clustering, classification and differential expression analysis. DGAN is executed in Python and is accessible at https://github.com/dikshap11/DGAN .
Structural analysis of RNA is an important and versatile tool to investigate the function of this type of molecules in the cell as well as in vitro. Several robust and reliable procedures are available, relying on chemical modification inducing RT stops or nucleotide misincorporations during reverse transcription. Others are based on cleavage reactions and RT stop signals. However, these methods address only one side of the RT stop or misincorporation position. Here, we describe Led-Seq, a new approach based on lead-induced cleavage of unpaired RNA positions, where both resulting cleavage products are investigated. The RNA fragments carrying 2', 3'-cyclic phosphate or 5'-OH ends are selectively ligated to oligonucleotide adapters by specific RNA ligases. In a deep sequencing analysis, the cleavage sites are identified as ligation positions, avoiding possible false positive signals based on premature RT stops. With a benchmark set of transcripts in Escherichia coli, we show that Led-Seq is an improved and reliable approach based on metal ion-induced phosphodiester hydrolysis to investigate RNA structures in vivo.
Macrophages respond to inflammatory stimuli by modulating the expression of hundreds of genes in a defined temporal cascade, with diverse transcriptional and posttranscriptional mechanisms contributing to the regulatory network. We examined proinflammatory gene regulation in activated macrophages by performing RNA-seq with fractionated chromatin-associated, nucleoplasmic, and cytoplasmic transcripts. This methodological approach allowed us to separate the synthesis of nascent transcripts from transcript processing and the accumulation of mature mRNAs. In addition to documenting the subcellular locations of coding and noncoding transcripts, the results provide a high-resolution view of the relationship between defined promoter and chromatin properties and the temporal regulation of diverse classes of coexpressed genes. The data also reveal a striking accumulation of full-length yet incompletely spliced transcripts in the chromatin fraction, suggesting that splicing often occurs after transcription has been completed, with transcripts retained on the chromatin until fully spliced.
Stem Leydig cells (SLCs) play a critical role in the development and maintenance of the adult Leydig cell (ALC) population. SLCs also are present in the adult testis. Their identification, characteristics, and regulation in the adult testis remain uncertain. Using single-cell RNA-seq, we found that the mesenchymal stromal population may be involved in ALC regeneration. Upon ALC elimination, a fraction of stromal cells begins to proliferate while a different fraction begins to differentiate to ALCs. Transcriptomic analysis identified five stromal clusters that can be classified into two major groups representing proliferation and differentiation populations. The proliferating group represents stem cells expressing high levels of CD90, Nes, Lum, Fn and Gap43. The differentiating group represents a progenitor stage that is ready to form ALCs, and specifically expresses Vtn, Rasl11a, Id1 and Egr2. The observation that the actively dividing cells after ALC loss were not those that formed ALCs suggests that stem cell proliferation and differentiation are regulated separately, and that the maintenance of the stromal stem cell pool occurs at the population level. The study also identified specific markers for the major interstitial cell groups and potential paracrine factors involved in the regulation of SLCs. Our data suggest a new theory about SLC identity, proliferation, differentiation, and regulation.
Yellow head virus (YHV) is a pathogen of the black tiger shrimp (Penaeus monodon) and, with gill-associated virus (GAV), is one of two known invertebrate nidoviruses. We describe sequences of the large replicase gene (ORF1a) and 5'- and 3'-terminal UTRs, completing the 26,662 nt sequence of the YHV genome. ORF1a (12,219 nt) encodes a approximately 462,662 Da polypeptide containing a putative 3C-like protease and a putative papain-like protease with the canonical C/H catalytic dyad and alpha+beta fold. The read-through pp1ab polyprotein contains putative uridylate-specific endoribonuclease and ribose-2'-O-methyl transferase domains, and an exonuclease domain incorporating unusual dual Zn2+-binding fingers. Upstream of ORF1a, the 71 nt 5'-UTR shares 82.4% identity with the 68 nt 5'-UTR of GAV. The 677 nt 3'-terminal region contains a single 60 nt ORF, commencing 298 nt downstream of ORF3, that is identical to N-terminal coding region of the 249 nt GAV ORF4. Northern blots using RNA from YHV-infected shrimp and probes directed at ORF1a, ORF1b, ORF2 and ORF3 identified a nested set of 3'-coterminal RNAs comprising the full-length genomic RNA and two sub-genomic (sg) mRNAs. Intergenic sequences upstream of ORF2 and ORF3 share high identity with GAV, particularly in the conserved domains predicted to mediate sgmRNA transcription.
The post-transcriptional sequence modification of transcripts through RNA editing is an important mechanism for regulating protein function and is associated with human disease phenotypes. The identification of RNA editing or RNA-DNA difference (RDD) sites is a fundamental step in the study of RNA editing. However, a substantial number of false-positive RDD sites have been identified recently. A major challenge in identifying RDD sites is to distinguish between the true RNA editing sites and the false positives. Furthermore, determining the location of condition-specific RDD sites and elucidating their functional roles will help toward understanding various biological phenomena that are mediated by RNA editing. The present study developed RNA-sequence comparison and annotation for RNA editing (RCARE) for searching, annotating, and visualizing RDD sites using thousands of previously known editing sites, which can be used for comparative analyses between multiple samples. RCARE also provides evidence for improving the reliability of identified RDD sites. RCARE is a web-based comparison, annotation, and visualization tool, which provides rich biological annotations and useful summary plots. The developers of previous tools that identify or annotate RNA-editing sites seldom mention the reliability of their respective tools. In order to address the issue, RCARE utilizes a number of scientific publications and databases to find specific documentations respective to a particular RNA-editing site, which generates evidence levels to convey the reliability of RCARE. Sequence-based alignment files can be converted into VCF files using a Python script and uploaded to the RCARE server for further analysis. RCARE is available for free at http://www.snubi.org/software/rcare/.
Nicotiana benthamiana has been widely used for transient gene expression assays and as a model plant in the study of plant-microbe interactions, lipid engineering and RNA silencing pathways. Assembling the sequence of its transcriptome provides information that, in conjunction with the genome sequence, will facilitate gaining insight into the plant's capacity for high-level transient transgene expression, generation of mobile gene silencing signals, and hyper-susceptibility to viral infection.
Honeybees (Apis mellifera) are constantly subjected to many biotic stressors including parasites. This study examined honeybees infected with Nosema ceranae (N. ceranae). N. ceranae infection increases the bees energy requirements and may contribute to their decreased survival. RNA-seq was used to investigate gene expression at days 5, 10 and 15 Post Infection (P.I) with N. ceranae. The expression levels of genes, isoforms, alternative transcription start sites (TSS) and differential promoter usage revealed a complex pattern of transcriptional and post-transcriptional gene regulation suggesting that bees use a range of tactics to cope with the stress of N. ceranae infection. N. ceranae infection may cause reduced immune function in the bees by: (i)disturbing the host amino acids metabolism (ii) down-regulating expression of antimicrobial peptides (iii) down-regulation of cuticle coatings and (iv) down-regulation of odorant binding proteins.
Human adenoviruses (HAds) encode for one or two highly abundant virus-associated RNAs, designated VA RNAI and VA RNAII, which fold into stable hairpin structures resembling miRNA precursors. Here we show that the terminal stem of the VA RNAs originating from Ad4, Ad5, Ad11 and Ad37, all undergo Dicer dependent processing into virus-specific miRNAs (so-called mivaRNAs). We further show that the mivaRNA duplex is subjected to a highly asymmetric RISC loading with the 3'-strand from all VA RNAs being the favored strand, except for the Ad37 VA RNAII, where the 5'-mivaRNAII strand was preferentially assembled into RISC. Although the mivaRNA seed sequences are not fully conserved between the HAds a bioinformatics prediction approach suggests that a large fraction of the VA RNAII-, but not the VA RNAI-derived mivaRNAs still are able to target the same cellular genes. Using small RNA deep sequencing we demonstrate that the Dicer processing event in the terminal stem of the VA RNAs is not unique and generates 3'-mivaRNAs with a slight variation of the position of the 5' terminal nucleotide in the RISC loaded guide strand. Also, we show that all analyzed VA RNAs, except Ad37 VA RNAI and Ad5 VA RNAII, utilize an alternative upstream A start site in addition to the classical +1 G start site. Further, the 5'-mivaRNAs with an A start appears to be preferentially incorporated into RISC. Although the majority of mivaRNA research has been done using Ad5 as the model system our analysis demonstrates that the mivaRNAs expressed in Ad11- and Ad37-infected cells are the most abundant mivaRNAs associated with Ago2-containing RISC. Collectively, our results show an unexpected variability in Dicer processing of the VA RNAs and a serotype-specific loading of mivaRNAs into Ago2-based RISC.
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