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Non-coding RNAs have remarkable roles in acute lung injury (ALI) initiation. Nevertheless, the significance of long non-coding RNAs (lncRNAs) in ALI is still unknown. Herein, we purposed to identify potential key genes in ALI and create a competitive endogenous RNA (ceRNA) modulatory network to uncover possible molecular mechanisms that affect lung injury. We generated a lipopolysaccharide-triggered ALI mouse model, whose lung tissue was subjected to RNA sequencing, and then we conducted bioinformatics analysis to select genes showing differential expression (DE) and to build a lncRNA-miRNA (microRNA)- mRNA (messenger RNA) modulatory network. Besides, GO along with KEGG assessments were conducted to identify major biological processes and pathways, respectively, involved in ALI. Then, RT-qPCR assay was employed to verify levels of major RNAs. A protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and the hub genes were obtained with the Molecular Complex Detection plugin. Finally, a key ceRNA subnetwork was built from major genes and their docking sites. Overall, a total of 8,610 lncRNAs were identified in the normal and LPS groups. Based on the 308 DE lncRNAs [p-value < 0.05, |log2 (fold change) | > 1] and 3,357 DE mRNAs [p-value < 0.05, |log2 (fold change) | > 1], lncRNA-miRNA and miRNA-mRNA pairs were predicted using miRanda. The lncRNA-miRNA-mRNA network was created from 175 lncRNAs, 22 miRNAs, and 209 mRNAs in ALI. The RT-qPCR data keep in step with the RNA sequencing data. GO along with KEGG analyses illustrated that DE mRNAs in this network were mainly bound up with the inflammatory response, developmental process, cell differentiation, cell proliferation, apoptosis, and the NF-kappa B, PI3K-Akt, HIF-1, MAPK, Jak-STAT, and Notch signaling pathways. A PPI network on the basis of the 209 genes was established, and three hub genes (Nkx2-1, Tbx2, and Atf5) were obtained from the network. Additionally, a lncRNA-miRNA-hub gene subnetwork was built from 15 lncRNAs, 3 miRNAs, and 3 mRNAs. Herein, novel ideas are presented to expand our knowledge on the regulation mechanisms of lncRNA-related ceRNAs in the pathogenesis of ALI.

Wheat streak mosaic (WSM), a viral disease affecting cereals and grasses, causes substantial losses in crop yields. Wheat streak mosaic virus (WSMV) is the main causal agent of the complex, but mixed infections with Triticum mosaic virus (TriMV) and High plains wheat mosaic emaravirus (HPWMoV) were reported as well. Although resistant varieties are effective for the disease control, a WSMV resistance-breaking isolate and several potential resistance-breaking isolates have been reported, suggesting that viral populations are genetically diverse. Previous phylogenetic studies of WSMV were conducted by focusing only on the virus coat protein (CP) sequence, while there is no such study for either TriMV or HPWMoV. Here, we studied the genetic variation and evolutionary mechanisms of natural populations of WSM-associated viruses mainly in Kansas fields and fields in some other parts of the Great Plains using high-throughput RNA sequencing. In total, 28 historic and field samples were used for total RNA sequencing to obtain full genome sequences of WSM-associated viruses. Field survey results showed WSMV as the predominant virus followed by mixed infections of WSMV + TriMV. Phylogenetic analyses of the full genome sequences demonstrated that WSMV Kansas isolates are widely distributed in sub-clades. In contrast, phylogenetic analyses for TriMV isolates showed no significant diversity. Recombination was identified as the major evolutionary force of WSMV and TriMV variation in KS fields, and positive selection was detected in some encoding genomic regions in the genome of both viruses. Furthermore, the full genome sequence of a second Kansas HPWMoV isolate was reported. Here, we also identified previously unknown WSMV isolates in the Great Plains sharing clades and high nucleotide sequence similarities with Central Europe isolates. The findings of this study will provide more insights into the genetic structure of WSM-associated viruses and, in turn, help in improving strategies for disease management.

Long non-coding RNAs (lncRNAs) were found to widely exist in eukaryotes and play important roles in most biological processes. Trees belonging to Populus spp. are economically important because of their fast-growing characteristics and wide use for wood, pulp, paper, and fuel. However, the prevalence of leaf rust disease caused by Melampsora spp. on some species of Populus severely affects their growth and decreases wood production. Therefore, the identification and characterization of lncRNAs involved in the defense of Melampsora spp. would not only help us to understand plant-pathogen interactions but also provide genetic elements for producing disease-resistant poplars. In the present study, an RNA-Seq transcriptome analysis was performed for poplar leaves in response to early infection by M. larici-populina. The hybrid variety “NL895” (P. × euramericana) was used as plant material. A total of 3994 lncRNAs were identified by mining the RNA-Seq data. The identified lncRNAs had lower abundance, fewer exons, and shorter lengths when compared to protein-coding genes. In addition, 53 lncRNAs were differentially expressed between treatments and controls. Two of these 53 lncRNAs were predicted to compete to be the target of miRNAs. Moreover, the differentially expressed lncRNAs were found to be preferentially located in close proximity to the protein-coding genes they co-expressed. In this study, we were able to show that lncRNAs may play important roles in plant-pathogen interactions in the poplar. This study also improves our understanding of how plants deploy their defense system when encountering biotic stresses.

The onion maggot Delia antiqua is a major insect pest of cultivated vegetables, especially the onion, and a good model to investigate the molecular mechanisms of diapause. To better understand the biology and diapause mechanism of the insect pest species, D. antiqua, the transcriptome was sequenced using Illumina paired-end sequencing technology. Approximately 54 million reads were obtained, trimmed, and assembled into 29,659 unigenes, with an average length of 607 bp and an N50 of 818 bp. Among these unigenes, 21,605 (72.8%) were annotated in the public databases. All unigenes were then compared against Drosophila melanogaster and Anopheles gambiae. Codon usage bias was analyzed and 332 simple sequence repeats (SSRs) were detected in this organism. These data represent the most comprehensive transcriptomic resource currently available for D. antiqua and will facilitate the study of genetics, genomics, diapause, and further pest control of D. antiqua.

To explore the mechanisms controlling erythroid differentiation and development, we analyzed the genome-wide transcription dynamics occurring during the differentiation of human embryonic stem cells (HESCs) into the erythroid lineage and development of embryonic to adult erythropoiesis using high throughput sequencing technology. HESCs and erythroid cells at three developmental stages: ESER (embryonic), FLER (fetal), and PBER (adult) were analyzed. Our findings revealed that the number of expressed genes decreased during differentiation, whereas the total expression intensity increased. At each of the three transitions (HESCs–ESERs, ESERs–FLERs, and FLERs–PBERs), many differentially expressed genes were observed, which were involved in maintaining pluripotency, early erythroid specification, rapid cell growth, and cell–cell adhesion and interaction. We also discovered dynamic networks and their central nodes in each transition. Our study provides a fundamental basis for further investigation of erythroid differentiation and development, and has implications in using ESERs for transfusion product in clinical settings.

The study of gene regulation in cells has recently begun to shift from a period dominated by the study of transcription factor-DNA interactions to a new focus on RNA regulation. This was sparked by the still-emerging recognition of the central role for RNA in cellular complexity emanating from the RNA World hypothesis, and has been facilitated by technologic advances, in particular high throughput RNA sequencing and crosslinking methods (RNA-Seq, CLIP, and HITS-CLIP). This study will place these advances in context, and, focusing on CLIP, will explain the method, what it can be used for, and how to approach using it. Examples of the successes, limitations, and future of the technique will be discussed. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website

Though powerful, short-read high throughput RNA sequencing is limited in its ability to directly measure exon connectivity in mRNAs containing multiple alternative exons located farther apart than the maximum read lengths. Here, we use the Oxford Nanopore MinION™ sequencer to identify 7,899 ‘full-length’ isoforms expressed from four Drosophila genes, Dscam1, MRP, Mhc, and Rdl. These results demonstrate that nanopore sequencing can be used to deconvolute individual isoforms and that it has the potential to be an important method for comprehensive transcriptome characterization.

The emergence of next-generation high-throughput RNA sequencing (RNA-Seq) provides tremendous opportunities for researchers to analyze alternative splicing on a genome-wide scale. However, accurate identification of alternative splicing events from RNA-Seq data has remained an unresolved challenge in next-generation sequencing (NGS) studies. Identifying exon skipping (ES) events is an essential part in genome-wide alternative splicing event identification. In this paper, we propose a novel method ESFinder, a random forest classifier to identify ES events from RNA-Seq data. ESFinder conducts thorough studies on predicting features and figures out proper features according to their relevance for ES event identification. Experimental results on real human skeletal muscle and brain RNA-Seq data show that ESFinder could effectively predict ES events with high predictive accuracy. The codes of ESFinder are available at http://mlg.hit.edu.cn/ybai/ES/ESFinder.html.

Wool is an important material in textile manufacturing. In order to investigate the intrinsic factors that regulate wool follicle cycling and wool fiber properties, Illumina sequencing was performed on wool follicle bulb samples from the middle anagen, catagen and late telogen/early anagen phases. In total, 13,898 genes were identified. KRTs and KRTAPs are the most highly expressed gene families in wool follicle bulb. In addition, 438 and 203 genes were identified to be differentially expressed in wool follicle bulb samples from the middle anagen phase compared to the catagen phase and the samples from the catagen phase compared to the late telogen/early anagen phase, respectively. Finally, our data revealed that two groups of genes presenting distinct expression patterns during the phase transformation may have important roles for wool follicle bulb regression and regeneration. In conclusion, our results demonstrated the gene expression patterns in the wool follicle bulb and add new data towards an understanding of the mechanisms involved in wool fiber growth in sheep.

We provide a detailed protocol for preparing cDNA libraries suitable for high throughput sequencing that are derived specifically from the 5′ ends of RNA (5′ specific RNA-seq). The protocol describes how cDNA libraries for 5′ specific RNA-seq can be tailored to analyze specific classes of RNAs based upon the phosphorylation status of the 5′ end. Thus, the analysis of cDNA libraries generated by these methods provides information regarding both the sequence and phosphorylation status of the 5′ ends of RNAs. 5′ specific RNA-seq can be used to analyze transcription initiation and post-transcriptional processing of RNAs with single base pair resolution on a genome-wide level.

In this study, we report the first use of RNA-sequencing to gain insight into the wide range of transcriptional events that are associated with leafy head development in Chinese cabbage. We generated 53.5 million sequence reads (90 bp in length) from the rosette and heading leaves. The sequence reads were aligned to the recently sequenced Chiifu genome and were analyzed to measure the gene expression levels, to detect alternative splicing events and novel transcripts, to determine the expression of single nucleotide polymorphisms, and to refine the annotated gene structures. The analysis of the global gene expression pattern suggests two important concepts, which govern leafy head formation. Firstly, some stimuli, such as carbohydrate levels, light intensity and endogenous hormones might play a critical role in regulating the leafy head formation. Secondly, the regulation of transcription factors, protein kinases and calcium may also be involved in this developmental process.

High-throughput RNA sequencing (RNA-seq) continues to provide unparalleled insight into transcriptome complexity. Now the “gold standard” for assessing global transcript levels, RNA-seq is poised to revolutionize our understanding of transcription and posttranscriptional regulation of RNA. Despite significant advantages over prior experimental strategies, RNA-seq is not without pitfalls. We have identified a number of confounding factors that significantly affect sequencing coverage. These include regional GC content, preferential sites of fragmentation, and read “pile-up” due to primer affinity and transcript end effects. Independent of cell type and laboratory, when ignored, these factors can bias analyses. Understanding the underlying principles responsible for producing these artifacts is key to recognizing both their presence and how their effects may be controlled. Here we outline the causes of and strategies to avoid several previously unreported complicating factors common to RNA-seq experiments.

RNA is a polymeric molecule implicated in various biological processes, such as the coding, decoding, regulation, and expression of genes. Numerous studies have examined RNA features using whole transcriptome sequencing (RNA-seq) approaches. RNA-seq is a powerful technique for characterizing and quantifying the transcriptome and accelerates the development of bioinformatics software. In this review, we introduce routine RNA-seq workflow together with related software, focusing particularly on transcriptome reconstruction and expression quantification.

Long intergenic non-coding RNAs (lincRNAs) have historically been ignored in cancer biology. However, thousands of lincRNAs have been identified in mammals using recently developed genomic tools, including microarray and high-throughput RNA sequencing (RNA-seq). Several of the lincRNAs identified have been well characterized for their functions in carcinogenesis. Here we performed RNA-seq experiments comparing gastric cancer with normal tissues to find differentially expressed transcripts in intergenic regions. By analyzing our own RNA-seq and public microarray data, we identified 31 transcripts, including a known expressed sequence tag, BM742401. BM742401 was downregulated in cancer, and its downregulation was associated with poor survival in gastric cancer patients. Ectopic overexpression of BM742401 inhibited metastasis-related phenotypes and decreased the concentration of extracellular MMP9. These results suggest that BM742401 is a potential lincRNA marker and therapeutic target.

The rapid expansion in the quantity and quality of RNA-Seq data requires the development of sophisticated high-performance bioinformatics tools capable of rapidly transforming this data into meaningful information that is easily interpretable by biologists. Currently available analysis tools are often not easily installed by the general biologist and most of them lack inherent parallel processing capabilities widely recognized as an essential feature of next-generation bioinformatics tools. We present here a user-friendly and fully automated RNA-Seq analysis pipeline (R-SAP) with built-in multi-threading capability to analyze and quantitate high-throughput RNA-Seq datasets. R-SAP follows a hierarchical decision making procedure to accurately characterize various classes of transcripts and achieves a near linear decrease in data processing time as a result of increased multi-threading. In addition, RNA expression level estimates obtained using R-SAP display high concordance with levels measured by microarrays.

As the most efficient natural enemy of mealybugs, the ladybird Cryptolaemus montrouzieri Mulsant plays an important role in integrated pest management. We report here a profiling analysis of C. montrouzieri under insecticide stress to gain a deeper view of insecticide resistance in ladybirds. For transcriptome sequencing, more than 26million sequencing reads were produced. These reads were assembled into 38,369 non-redundant transcripts (mean size=453 nt). 23,248 transcripts were annotated with their gene description. Using a tag-based DGE (Digital gene expression) system, over 5.7million tags were sequenced in both the insecticide stress group and the control group, and mapped to 38,369 transcripts. We obtained 993 genes that were significantly up- or down-regulated under insecticide stress in the ladybird transcriptome. These results can contribute to in-depth research into the molecular mechanisms of resistance and enhance our current understanding of the effects of insecticides on natural enemies.

Background The marine medaka Oryzias melastigma has been demonstrated as a novel model for marine ecotoxicological studies. However, the lack of genome and transcriptome reference has largely restricted the use of O. melastigma in the assessment of in vivo molecular responses to environmental stresses and the analysis of biological toxicity in the marine environment. Although O. melastigma is believed to be phylogenetically closely related to Oryzias latipes, the divergence between these two species is still largely unknown. Using Illumina high-throughput RNA sequencing followed by de novo assembly and comprehensive gene annotation, we provided transcriptomic resources for the brain, liver, ovary and testis of O. melastigma. We also investigated the possible extent of divergence between O. melastigma and O. latipes at the transcriptome level. Results More than 14,000 transcripts across brain, liver, ovary and testis in marine medaka were annotated, of which 5880 transcripts were orthologous between O. melastigma and O. latipes. Tissue-enriched genes were identified in O. melastigma, and Gene Ontology analysis demonstrated the functional specificity of the annotated genes in respective tissue. Lastly, the identification of marine medaka-enriched transcripts suggested the necessity of generating transcriptome dataset of O. melastigma. Conclusions Orthologous transcripts between O. melastigma and O. latipes, tissue-enriched genes and O. melastigma-enriched transcripts were identified. Genome-wide expression studies of marine medaka require an assembled transcriptome, and this sequencing effort has generated a valuable resource of coding DNA for a non-model species. This transcriptome resource will aid future studies assessing in vivo molecular responses to environmental stresses and those analyzing biological toxicity in the marine environment. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1325-7) contains supplementary material, which is available to authorized users.