The identification and characterization of novel transcripts from RNA-seq data

The lncRNA Malat1 inhibits miR-15/16 to enhance cytotoxic T cell activation and memory cell formation

Proper activation of cytotoxic T cells via the T cell receptor and the costimulatory receptor CD28 is essential for adaptive immunity against viruses, intracellular bacteria, and cancers. Through biochemical analysis of RNA:protein interactions, we uncovered a non-coding RNA circuit regulating activation and differentiation of cytotoxic T cells composed of the long non-coding RNA Malat1 (Metastasis Associated Lung Adenocarcinoma Transcript 1) and the microRNA family miR-15/16. miR-15/16 is a widely and highly expressed tumor suppressor miRNA family important for cell proliferation and survival. miR-15/16 play important roles in T cell responses to viral infection, including the regulation of antigen-specific T cell expansion and memory. Comparative Argonaute-2 high-throughput sequencing of crosslinking immunoprecipitation (AHC) combined with gene expression profiling in normal and miR-15/16-deficient mouse T cells revealed a large network of hundreds of direct miR-15/16 target mRNAs, many with functional relevance for T cell activation, survival and memory formation. Among these targets, Malat1 contained the largest absolute magnitude miR-15/16-dependent AHC peak. This binding site was among the strongest lncRNA:miRNA interactions detected in the T cell transcriptome. We used CRISPR targeting with homology directed repair to generate mice with a 5-nucleotide mutation in the miR-15/16-binding site in Malat1. This mutation interrupted Malat1:miR-15/16 interaction, and enhanced the repression of other miR-15/16 target genes, including CD28. Interrupting Malat1 interaction with miR-15/16 decreased cytotoxic T cell activation, including the expression of interleukin 2 (IL-2) and a broader CD28-responsive gene program. Accordingly, Malat1 mutation diminished memory cell persistence in mice following LCMV Armstrong and Listeria monocytogenes infection. This study marks a significant advance in the study of long non-coding RNAs in the immune system by ascribing cell-intrinsic, sequence-specific in vivo function to Malat1. These findings have implications for T cell-mediated autoimmune diseases, antiviral and anti-tumor immunity, as well as lung adenocarcinoma and other malignancies where Malat1 is overexpressed.

Differential lncRNA/mRNA expression profiling and ceRNA network analyses in amniotic fluid from foetuses with ventricular septal defects

Background

Long noncoding RNAs (lncRNAs) have been shown to be involved in the regulation of numerous biological processes in embryonic development. We aimed to explore lncRNA expression profiles in ventricular septal defects (VSDs) and reveal their potential roles in heart development.

Methods

Microarray analyses were performed to screen differentially expressed lncRNAs (DE-lncRNAs) and mRNAs (DE-mRNAs) in the amniotic fluid between the VSD group and the control group. Bioinformatics analyses were further used to identify the functional enrichment and signaling pathways of important mRNAs. Then, a coding-noncoding gene coexpression (CNC) network and competitive endogenous RNAs (ceRNA) network were drawn. Finally, qRT‒PCR was performed to verify several hub lncRNAs and mRNAs in the network.

Results

A total of 710 DE-lncRNAs and 397 DE-mRNAs were identified in the VSD group. GO and KEGG analyses revealed that the DE-mRNAs were enriched in cardiac development-related biological processes and pathways, including cell proliferation, cell apoptosis, and the Sonic Hedgehog signaling pathway. Four VSD related mRNAs was used to construct the CNC network, which included 149 pairs of coexpressing lncRNAs and mRNAs. In addition, a ceRNA network, including 15 lncRNAs, 194 miRNAs, and four mRNAs, was constructed to reveal the potential regulatory relationship between lncRNAs and protein-coding genes. Finally, seven RNAs in the ceRNA network were validated, including IDS, NR2F2, GPC3, LINC00598, GATA3-AS1, PWRN1, and LINC01551.

Conclusion

Our study identified some lncRNAs and mRNAs may be potential biomarkers and therapeutic targets for foetuses with VSD, and described the lncRNA-associated ceRNA network in the progression of VSD.

Systematic Analysis of Long Non-Coding RNA Genes in Nonalcoholic Fatty Liver Disease

The largest solid organ in humans, the liver, performs a variety of functions to sustain life. When damaged, cells in the liver can regenerate themselves to maintain normal liver physiology. However, some damage is beyond repair, which necessitates liver transplantation. Increasing rates of obesity, Western diets (i.e., rich in processed carbohydrates and saturated fats), and cardiometabolic diseases are interlinked to liver diseases, including non-alcoholic fatty liver disease (NAFLD), which is a collective term to describe the excess accumulation of fat in the liver of people who drink little to no alcohol. Alarmingly, the prevalence of NAFLD extends to 25% of the world population, which calls for the urgent need to understand the disease mechanism of NAFLD. Here, we performed secondary analyses of published RNA sequencing (RNA-seq) data of NAFLD patients compared to healthy and obese individuals to identify long non-coding RNAs (lncRNAs) that may underly the disease mechanism of NAFLD. Similar to protein-coding genes, many lncRNAs are dysregulated in NAFLD patients compared to healthy and obese individuals, suggesting that understanding the functions of dysregulated lncRNAs may shed light on the pathology of NAFLD. To demonstrate the functional importance of lncRNAs in the liver, loss-of-function experiments were performed for one NAFLD-related lncRNA, LINC01639, which showed that it is involved in the regulation of genes related to apoptosis, TNF/TGF, cytokine signaling, and growth factors as well as genes upregulated in NAFLD. Since there is no lncRNA database focused on the liver, especially NAFLD, we built a web database, LiverDB, to further facilitate functional and mechanistic studies of hepatic lncRNAs.

LncRNA-UC.25 + shRNA Alleviates P2Y14 Receptor-Mediated Diabetic Neuropathic Pain via STAT1

Diabetic neuropathic pain (DNP) is a common complication of diabetes, and its complicated pathogenesis, as well as clinical manifestations, has brought great trouble to clinical treatment. The spinal cord is an important part of regulating the occurrence and development of DNP. Spinal microglia can regulate the activity of spinal cord neurons and have a regulatory effect on chronic pain. P2Y₁₂ receptor is involved in DNP. P2Y₁₄ and P2Y₁₂ receptors belong to the Gi subtype of P2Y receptors, but there is no report that the P2Y₁₄ receptor is involved in DNP. Closely related to many human diseases, the dysregulation of long noncoding RNA (lncRNA) has the effect of promoting or inhibiting the occurrence and development of diseases. The aim of this research is to investigate the function of the spinal cord P2Y₁₄ receptor in type 2 DNP and to understand the function as well as the possible mechanism of lncRNA-UC.25 + (UC.25 +) in rat spinal cord P2Y₁₄ receptor-mediated DNP. Our results showed that P2Y₁₄ shRNA can reduce the expression of P2Y₁₄ in DNP rats, thereby restraining the activation of microglia, decreasing the expression of inflammatory factors and the level of p38 mitogen-activated protein kinase (p38 MAPK) phosphorylation. At the same time, UC.25 + shRNA can downregulate the expression of the P2Y₁₄ receptor, reduce the release of inflammatory factors, and diminish the p38 MAPK phosphorylation, indicating that UC.25 + can alleviate spinal cord P2Y₁₄ receptor-mediated DNP. The RNA immunoprecipitation result showed that UC.25 + enriched signal transducers and activators of transcription1 (STAT1) and positively regulated its expression. The chromatin immunoprecipitation result indicated that STAT1 combined with the promoter region of the P2Y₁₄ receptor and positively regulated the expression of the P2Y₁₄ receptor. Therefore, we infer that UC.25 + may alleviate DNP in rats by regulating the expression of the P2Y₁₄ receptor in spinal microglia via STAT1.

Genome-wide profiling of long non-coding RNA of the rice blast fungus Magnaporthe oryzae during infection

Background

Long non-coding RNAs (lncRNAs) play essential roles in developmental processes and disease development at the transcriptional and post-transcriptional levels across diverse taxa. However, only few studies have profiled fungal lncRNAs in a genome-wide manner during host infection.

Results

Infection-associated lncRNAs were identified using lncRNA profiling over six stages of host infection (e.g., vegetative growth, pre-penetration, biotrophic, and necrotrophic stages) in the model pathogenic fungus, Magnaporthe oryzae. We identified 2,601 novel lncRNAs, including 1,286 antisense lncRNAs and 980 intergenic lncRNAs. Among the identified lncRNAs, 755 were expressed in a stage-specific manner and 560 were infection-specifically expressed lncRNAs (ISELs). To decipher the potential roles of lncRNAs during infection, we identified 365 protein-coding genes that were associated with 214 ISELs. Analysis of the predicted functions of these associated genes suggested that lncRNAs regulate pathogenesis-related genes, including xylanases and effectors.

Conclusions

The ISELs and their associated genes provide a comprehensive view of lncRNAs during fungal pathogen-plant interactions. This study expands new insights into the role of lncRNAs in the rice blast fungus, as well as other plant pathogenic fungi.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08380-4.

Elucidating the Functions of Non-Coding RNAs from the Perspective of RNA Modifications

It is now commonly accepted that most of the mammalian genome is transcribed as RNA, yet less than 2% of such RNA encode for proteins. A majority of transcribed RNA exists as non-protein-coding RNAs (ncRNAs) with various functions. Because of the lack of sequence homologies among most ncRNAs species, it is difficult to infer the potential functions of ncRNAs by examining sequence patterns, such as catalytic domains, as in the case of proteins. Added to the existing complexity of predicting the functions of the ever-growing number of ncRNAs, increasing evidence suggests that various enzymes modify ncRNAs (e.g., ADARs, METTL3, and METTL14), which has opened up a new field of study called epitranscriptomics. Here, we examine the current status of ncRNA research from the perspective of epitranscriptomics.

Landscape of the long non-coding RNA transcriptome in human heart

Long non-coding RNAs (lncRNAs) have been revealed to play essential roles in the human cardiovascular system. However, information about their mechanisms is limited, and a comprehensive view of cardiac lncRNAs is lacking from a multiple tissues perspective to date. Here, the landscape of the lncRNA transcriptome in human heart was summarized. We summarized all lncRNA transcripts from publicly available human transcriptome resources (156 heart samples and 210 samples from 29 other tissues) and systematically analysed all annotated and novel lncRNAs expressed in heart. A total of 7485 lncRNAs whose expression was elevated in heart (HE lncRNAs) and 453 lncRNAs expressed in all 30 analysed tissues (EIA lncRNAs) were extracted. Using various bioinformatics resources, methods and tools, the features of these lncRNAs were discussed from various perspectives, including genomic structure, conservation, dynamic variation during heart development, cis-regulation, differential expression in cardiovascular diseases and cancers as well as regulation at transcriptional and post-transcriptional levels. Afterwards, all the features discussed above were integrated into a user-friendly resource named CARDIO-LNCRNAS (http://bio-bigdata.hrbmu.edu.cn/CARDIO-LNCRNAS/ or http://www.bio-bigdata.net/CARDIO-LNCRNAS/). This study represents the first global view of lncRNAs in the human cardiovascular system based on multiple tissues and sheds light on the role of lncRNAs in developments and heart disorders.

Identifying functions and prognostic biomarkers of network motifs marked by diverse chromatin states in human cell lines

Epigenetic modifications play critical roles in modulating gene expression, yet their roles in regulatory networks in human cell lines remain poorly characterized. We integrated multiomics data to construct directed regulatory networks with nodes and edges labeled with chromatin states in human cell lines. We observed extensive association of diverse chromatin states and network motifs. The gene expression analysis showed that diverse chromatin states of coherent type-1 feedforward loop (C1-FFL) and incoherent type-1 feedforward loops (I1-FFL) contributed to the dynamic expression patterns of targets. Notably, diverse chromatin state compositions could help C1- or I1-FFL to control a large number of distinct biological functions in human cell lines, such as four different types of chromatin state compositions cooperating with K562-associated C1-FFLs controlling “regulation of cytokinesis,” “G1/S transition of mitotic cell cycle,” “DNA recombination,” and “telomere maintenance,” respectively. Remarkably, we identified six chromatin state-marked C1-FFL instances (HCFC1-NFYA-ABL1, THAP1-USF1-BRCA2, ZNF263-USF1-UBA52, MYC-ATF1-UBA52, ELK1-EGR1-CCT4, and YY1-EGR1-INO80C) could act as prognostic biomarkers of acute myelogenous leukemia though influencing cancer-related biological functions, such as cell proliferation, telomere maintenance, and DNA recombination. Our results will provide novel insight for better understanding of chromatin state-mediated gene regulation and facilitate the identification of novel diagnostic and therapeutic biomarkers of human cancers.

Mapping non-host resistance to the stem rust pathogen in an interspecific barberry hybrid

BACKGROUND

Non-host resistance (NHR) presents a compelling long-term plant protection strategy for global food security, yet the genetic basis of NHR remains poorly understood. For many diseases, including stem rust of wheat [causal organism Puccinia graminis (Pg)], NHR is largely unexplored due to the inherent challenge of developing a genetically tractable system within which the resistance segregates. The present study turns to the pathogen's alternate host, barberry (Berberis spp.), to overcome this challenge.

RESULTS

In this study, an interspecific mapping population derived from a cross between Pg-resistant Berberis thunbergii (Bt) and Pg-susceptible B. vulgaris was developed to investigate the Pg-NHR exhibited by Bt. To facilitate QTL analysis and subsequent trait dissection, the first genetic linkage maps for the two parental species were constructed and a chromosome-scale reference genome for Bt was assembled (PacBio + Hi-C). QTL analysis resulted in the identification of a single 13 cM region (~ 5.1 Mbp spanning 13 physical contigs) on the short arm of Bt chromosome 3. Differential gene expression analysis, combined with sequence variation analysis between the two parental species, led to the prioritization of several candidate genes within the QTL region, some of which belong to gene families previously implicated in disease resistance.

CONCLUSIONS

Foundational genetic and genomic resources developed for Berberis spp. enabled the identification and annotation of a QTL associated with Pg-NHR. Although subsequent validation and fine mapping studies are needed, this study demonstrates the feasibility of and lays the groundwork for dissecting Pg-NHR in the alternate host of one of agriculture's most devastating pathogens.

Navigating the non-coding genome in heart development and Congenital Heart Disease

Congenital Heart Disease (CHD) is characterised by a wide range of cardiac defects, from mild to life-threatening, which occur in babies worldwide. To date, there is no cure to CHD, however, progress in surgery has reduced its mortality allowing children affected by CHD to reach adulthood. In an effort to understand its genetic basis, several studies involving whole-genome sequencing (WGS) of patients with CHD have been undertaken and generated a great wealth of information. The majority of putative causative mutations identified in WGS studies fall into the non-coding part of the genome. Unfortunately, due to the lack of understanding of the function of these non-coding mutations, it is challenging to establish a causal link between the non-coding mutation and the disease. Thus, here we review the state-of-the-art approaches to interpret non-coding mutations in the context of CHD and address the following questions: What are the non-coding sequences important for cardiac function? Which technologies are used to identify them? Which resources are available to analyse them? What mutations are expected in these non-coding sequences? Learning from developmental process, what is their expected role in CHD?

Transcriptome-wide analysis of differentially expressed chemokine receptors, SNPs, and SSRs in the age-related macular degeneration

Background

Age-related macular degeneration (AMD) is the most common, progressive, and polygenic cause of irreversible visual impairment in the world. The molecular pathogenesis of the primary events of AMD is poorly understood. We have investigated a transcriptome-wide analysis of differential gene expression, single-nucleotide polymorphisms (SNPs), indels, and simple sequence repeats (SSRs) in datasets of the human peripheral retina and RPE-choroid-sclera control and AMD.

Methods and results

Adaptors and unbiased components were removed and checked to ensure the quality of the data sets. Molecular function, biological process, cellular component, and pathway analyses were performed on differentially expressed genes. Analysis of the gene expression datasets identified 5011 upregulated genes, 11,800 downregulated genes, 42,016 SNPs, 1141 indels, and 6668 SRRs between healthy controls and AMD donor material. Enrichment categories for gene ontology included chemokine activity, cytokine activity, cytokine receptor binding, immune system process, and signal transduction respectively. A functional pathways analysis identified that chemokine receptors bind chemokines, complement cascade genes, and create cytokine signaling in immune system pathway genes (p value < 0.001). Finally, allele-specific expression was found to be significant for Chemokine (C-C motif) ligand (CCL) 2, 3, 4, 13, 19, 21; C-C chemokine receptor (CCR) 1, 5; chemokine (C-X-C motif) ligand (CXCL) 9, 10, 16; C-X-C chemokine receptor type (CXCR) 6; as well as atypical chemokine receptor (ACKR) 3,4 and pro-platelet basic protein (PPBP).

Conclusions

Our results improve our overall understanding of the chemokine receptors’ signaling pathway in AMD conditions, which may lead to potential new diagnostic and therapeutic targets.

Electronic supplementary material

The online version of this article (10.1186/s40246-019-0199-1) contains supplementary material, which is available to authorized users.

Logic programming to infer complex RNA expression patterns from RNA-seq data

To meet the increasing demand in the field, numerous long noncoding RNA (lncRNA) databases are available. Given many lncRNAs are specifically expressed in certain cell types and/or time-dependent manners, most lncRNA databases fall short of providing such profiles. We developed a strategy using logic programming to handle the complex organization of organs, their tissues and cell types as well as gender and developmental time points. To showcase this strategy, we introduce 'RenalDB' (http://renaldb.uni-frankfurt.de), a database providing expression profiles of RNAs in major organs focusing on kidney tissues and cells. RenalDB uses logic programming to describe complex anatomy, sample metadata and logical relationships defining expression, enrichment or specificity. We validated the content of RenalDB with biological experiments and functionally characterized two long intergenic noncoding RNAs: LOC440173 is important for cell growth or cell survival, whereas PAXIP1-AS1 is a regulator of cell death. We anticipate RenalDB will be used as a first step toward functional studies of lncRNAs in the kidney.

Genome-wide identification of long non-coding RNAs in tomato plants irradiated by neutrons followed by infection with Tomato yellow leaf curl virus

Long non-coding RNAs (lncRNAs) play an important role in regulating many biological processes. In this study, tomato seeds were first irradiated by neutrons. Eight tomato mutants were then selected and infected by Tomato yellow leaf curl virus (TYLCV). RNA sequencing followed by bioinformatics analyses identified 1,563 tomato lncRNAs. About half of the lncRNAs were derived from intergenic regions, whereas antisense lncRNAs accounted for 35%. There were fewer lncRNAs identified in our study than in other studies identifying tomato lncRNAs. Functional classification of 794 lncRNAs associated with tomato genes showed that many lncRNAs were associated with binding functions required for interactions with other molecules and localized in the cytosol and membrane. In addition, we identified 19 up-regulated and 11 down-regulated tomato lncRNAs by comparing TYLCV infected plants to non-infected plants using previously published data. Based on these results, the lncRNAs identified in this study provide important resources for characterization of tomato lncRNAs in response to TYLCV infection.

Long noncoding RNA (lncRNA): a target in neuropathic pain

INTRODUCTION

Current treatments for neuropathic pain are limited in part due to the incomplete understanding of its underlying mechanisms. Recent evidence reveals the dysregulated expression of long non-coding RNAs (lncRNAs) in the damaged nerve, dorsal root ganglion (DRG), and spinal cord dorsal horn following peripheral nerve injury. However, the role of the majority of lncRNAs in neuropathic pain genesis is still elusive. Unveiling the mechanisms of how lncRNAs participate in neuropathic pain may develop new strategies to prevent and/or treat this disorder. Areas covered: This review focuses on the dysregulation of lncRNAs in the DRG, dorsal horn, and the injured nerves from preclinical models of neuropathic pain. We provide evidence of how peripheral nerve injury causes the dysregulation of lncRNAs in these pain-related regions. The potential mechanisms of how dysregulated lncRNAs contribute to the pathogenesis of neuropathic pain are discussed. Expert opinion: The investigation on the role of the dysregulated lncRNAs in neuropathic pain might open up a novel avenue for therapeutic treatment of this disorder. However, current investigation is at the infancy stage, which challenges the translation of preclinical findings. More intensive studies on lncRNAs are required before the preclinical findings are translated into therapeutic management for neuropathic pain.

Short and Long Noncoding RNAs Regulate the Epigenetic Status of Cells

SIGNIFICANCE

The concepts of junk DNA and transcriptional noise are long gone as the existence of noncoding RNAs (ncRNAs) has been tested extensively in recent years. Given that the epigenetic status of cells affects many biological processes, how ncRNAs mechanistically contribute to these processes is of great interest. Recent Advances: Recent studies show that various ncRNAs interact with epigenetic and/or transcription factors to modulate the epigenetic status of cells directly and/or indirectly. There exists growing interest in the field of cardiovascular research to understand the roles of ncRNAs. Due to the large number of ncRNAs in the mammalian genome, only a handful of ncRNAs have been functionally elucidated, which makes it difficult to understand how ncRNAs interact with protein-coding genes and their encoded proteins.

CRITICAL ISSUES

Although the canonical function of microRNAs (miRNAs) to inhibit the translation of protein-coding genes is well established, the number of functionally annotated long noncoding RNAs (lncRNAs) is still small, which is especially true in the heart.

FUTURE DIRECTIONS

Future studies must connect the epigenetic controls of various cellular phenomena by incorporating both miRNAs and lncRNAs. Antioxid. Redox Signal. 29, 832-845.

Developmental Dynamics of Long Noncoding RNA Expression during Sexual Fruiting Body Formation in Fusarium graminearum

Long noncoding RNA (lncRNA) plays important roles in sexual development in eukaryotes. In filamentous fungi, however, little is known about the expression and roles of lncRNAs during fruiting body formation. By profiling developmental transcriptomes during the life cycle of the plant-pathogenic fungus Fusarium graminearum, we identified 547 lncRNAs whose expression was highly dynamic, with about 40% peaking at the meiotic stage. Many lncRNAs were found to be antisense to mRNAs, forming 300 sense-antisense pairs. Although small RNAs were produced from these overlapping loci, antisense lncRNAs appeared not to be involved in gene silencing pathways. Genome-wide analysis of small RNA clusters identified many silenced loci at the meiotic stage. However, we found transcriptionally active small RNA clusters, many of which were associated with lncRNAs. Also, we observed that many antisense lncRNAs and their respective sense transcripts were induced in parallel as the fruiting bodies matured. The nonsense-mediated decay (NMD) pathway is known to determine the fates of lncRNAs as well as mRNAs. Thus, we analyzed mutants defective in NMD and identified a subset of lncRNAs that were induced during sexual development but suppressed by NMD during vegetative growth. These results highlight the developmental stage-specific nature and functional potential of lncRNA expression in shaping the fungal fruiting bodies and provide fundamental resources for studying sexual stage-induced lncRNAs.

Fusarium graminearum is the causal agent of the head blight on our major staple crops, wheat and corn. The fruiting body formation on the host plants is indispensable for the disease cycle and epidemics. Long noncoding RNA (lncRNA) molecules are emerging as key regulatory components for sexual development in animals and plants. To date, however, there is a paucity of information on the roles of lncRNAs in fungal fruiting body formation. Here we characterized hundreds of lncRNAs that exhibited developmental stage-specific expression patterns during fruiting body formation. Also, we discovered that many lncRNAs were induced in parallel with their overlapping transcripts on the opposite DNA strand during sexual development. Finally, we found a subset of lncRNAs that were regulated by an RNA surveillance system during vegetative growth. This research provides fundamental genomic resources that will spur further investigations on lncRNAs that may play important roles in shaping fungal fruiting bodies.

Long Non-coding RNAs in Endothelial Biology

In recent years, the role of RNA has expanded to the extent that protein-coding RNAs are now the minority with a variety of non-coding RNAs (ncRNAs) now comprising the majority of RNAs in higher organisms. A major contributor to this shift in understanding is RNA sequencing (RNA-seq), which allows a largely unconstrained method for monitoring the status of RNA from whole organisms down to a single cell. This observational power presents both challenges and new opportunities, which require specialized bioinformatics tools to extract knowledge from the data and the ability to reuse data for multiple studies. In this review, we summarize the current status of long non-coding RNA (lncRNA) research in endothelial biology. Then, we will cover computational methods for identifying, annotating, and characterizing lncRNAs in the heart, especially endothelial cells.

Epigenomic and transcriptomic approaches in the post-genomic era: path to novel targets for diagnosis and therapy of the ischaemic heart? Position Paper of the European Society of Cardiology Working Group on Cellular Biology of the Heart

Despite advances in myocardial reperfusion therapies, acute myocardial ischaemia/reperfusion injury and consequent ischaemic heart failure represent the number one cause of morbidity and mortality in industrialized societies. Although different therapeutic interventions have been shown beneficial in preclinical settings, an effective cardioprotective or regenerative therapy has yet to be successfully introduced in the clinical arena. Given the complex pathophysiology of the ischaemic heart, large scale, unbiased, global approaches capable of identifying multiple branches of the signalling networks activated in the ischaemic/reperfused heart might be more successful in the search for novel diagnostic or therapeutic targets. High-throughput techniques allow high-resolution, genome-wide investigation of genetic variants, epigenetic modifications, and associated gene expression profiles. Platforms such as proteomics and metabolomics (not described here in detail) also offer simultaneous readouts of hundreds of proteins and metabolites. Isolated omics analyses usually provide Big Data requiring large data storage, advanced computational resources and complex bioinformatics tools. The possibility of integrating different omics approaches gives new hope to better understand the molecular circuitry activated by myocardial ischaemia, putting it in the context of the human ‘diseasome’. Since modifications of cardiac gene expression have been consistently linked to pathophysiology of the ischaemic heart, the integration of epigenomic and transcriptomic data seems a promising approach to identify crucial disease networks. Thus, the scope of this Position Paper will be to highlight potentials and limitations of these approaches, and to provide recommendations to optimize the search for novel diagnostic or therapeutic targets for acute ischaemia/reperfusion injury and ischaemic heart failure in the post-genomic era.

RNAseq analysis of α-proteobacterium Gluconobacter oxydans 621H

Background

The acetic acid bacterium Gluconobacter oxydans 621H is characterized by its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. The metabolism of this α-proteobacterium has been characterized to some extent, yet little is known about its transcriptomes and related data. In this study, we applied two different RNAseq approaches. Primary transcriptomes enriched for 5′-ends of transcripts were sequenced to detect transcription start sites, which allow subsequent analysis of promoter motifs, ribosome binding sites, and 5´-UTRs. Whole transcriptomes were sequenced to identify expressed genes and operon structures.

Results

Sequencing of primary transcriptomes of G. oxydans revealed 2449 TSSs, which were classified according to their genomic context followed by identification of promoter and ribosome binding site motifs, analysis of 5´-UTRs including validation of predicted cis-regulatory elements and correction of start codons. 1144 (41%) of all genes were found to be expressed monocistronically, whereas 1634 genes were organized in 571 operons. Together, TSSs and whole transcriptome data were also used to identify novel intergenic (18), intragenic (328), and antisense transcripts (313).

Conclusions

This study provides deep insights into the transcriptional landscapes of G. oxydans. The comprehensive transcriptome data, which we made publicly available, facilitate further analysis of promoters and other regulatory elements. This will support future approaches for rational strain development and targeted gene expression in G. oxydans. The corrections of start codons further improve the high quality genome reference and support future proteome analysis.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4415-x) contains supplementary material, which is available to authorized users.

Data integration and predictive modeling methods for multi-omics datasets

We provide an overview of opportunities and challenges in multi-omics predictive analytics with particular emphasis on data integration and machine learning methods.

Alignment-free comparative genomic screen for structured RNAs using coarse-grained secondary structure dot plots

Background

Structured non-coding RNAs play many different roles in the cells, but the annotation of these RNAs is lacking even within the human genome. The currently available computational tools are either too computationally heavy for use in full genomic screens or rely on pre-aligned sequences.

Methods

Here we present a fast and efficient method, DotcodeR, for detecting structurally similar RNAs in genomic sequences by comparing their corresponding coarse-grained secondary structure dot plots at string level. This allows us to perform an all-against-all scan of all window pairs from two genomes without alignment.

Results

Our computational experiments with simulated data and real chromosomes demonstrate that the presented method has good sensitivity.

Conclusions

DotcodeR can be useful as a pre-filter in a genomic comparative scan for structured RNAs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4309-y) contains supplementary material, which is available to authorized users.

Resolving the problem of multiple accessions of the same transcript deposited across various public databases

Maintaining the consistency of genomic annotations is an increasingly complex task because of the iterative and dynamic nature of assembly and annotation, growing numbers of biological databases and insufficient integration of annotations across databases. As information exchange among databases is poor, a 'novel' sequence from one reference annotation could be annotated in another. Furthermore, relationships to nearby or overlapping annotated transcripts are even more complicated when using different genome assemblies. To better understand these problems, we surveyed current and previous versions of genomic assemblies and annotations across a number of public databases containing long noncoding RNA. We identified numerous discrepancies of transcripts regarding their genomic locations, transcript lengths and identifiers. Further investigation showed that the positional differences between reference annotations of essentially the same transcript could lead to differences in its measured expression at the RNA level. To aid in resolving these problems, we present the algorithm 'Universal Genomic Accession Hash (UGAHash)' and created an open source web tool to encourage the usage of the UGAHash algorithm. The UGAHash web tool (http://ugahash.uni-frankfurt.de) can be accessed freely without registration. The web tool allows researchers to generate Universal Genomic Accessions for genomic features or to explore annotations deposited in the public databases of the past and present versions. We anticipate that the UGAHash web tool will be a valuable tool to check for the existence of transcripts before judging the newly discovered transcripts as novel.

High-Throughput Methods to Detect Long Non-Coding RNAs

Increasing evidence suggests that the numbers of long non-coding RNAs (lncRNAs) are more than those of protein-coding genes in various organisms. Although the detection methods for lncRNAs are being increasingly established, there are advantages and disadvantages that exist for each method. In this opinion article, I highlight the differences between microarrays and RNA sequencing (RNA-seq) for the detection of lncRNAs. Compared to RNA-seq, microarrays are limited to the known sequences. However, the detection method as well as data analysis workflow is more established, which makes it easier to analyze the data for bench scientists without extensive knowledge about computer programming. In order to highlight the usage of microarrays over RNA-seq for the detection of lncRNAs, we are organizing a special issue for High-Throughput called “Microarrays in Non-Coding RNAs Profiling”, which will include the specific usages of microarrays for lncRNAs.

ANGIOGENES: knowledge database for protein-coding and noncoding RNA genes in endothelial cells

Increasing evidence indicates the presence of long noncoding RNAs (lncRNAs) is specific to various cell types. Although lncRNAs are speculated to be more numerous than protein-coding genes, the annotations of lncRNAs remain primitive due to the lack of well-structured schemes for their identification and description. Here, we introduce a new knowledge database “ANGIOGENES” (http://angiogenes.uni-frankfurt.de) to allow for in silico screening of protein-coding genes and lncRNAs expressed in various types of endothelial cells, which are present in all tissues. Using the latest annotations of protein-coding genes and lncRNAs, publicly-available RNA-seq data was analyzed to identify transcripts that are expressed in endothelial cells of human, mouse and zebrafish. The analyzed data were incorporated into ANGIOGENES to provide a one-stop-shop for transcriptomics data to facilitate further biological validation. ANGIOGENES is an intuitive and easy-to-use database to allow in silico screening of expressed, enriched and/or specific endothelial transcripts under various conditions. We anticipate that ANGIOGENES serves as a starting point for functional studies to elucidate the roles of protein-coding genes and lncRNAs in angiogenesis.

Clinical Interpretation of Genomic Variations

Novel high-throughput sequencing technologies generate large-scale genomic data and are used extensively for disease mapping of monogenic and/or complex disorders, personalized treatment, and pharmacogenomics. Next-generation sequencing is rapidly becoming routine tool for diagnosis and molecular monitoring of patients to evaluate therapeutic efficiency. The next-generation sequencing platforms generate huge amounts of genetic variation data and it remains a challenge to interpret the variations that are identified. Such data interpretation needs close collaboration among bioinformaticians, clinicians, and geneticists. There are several problems that must be addressed, such as the generation of new algorithms for mapping and annotation, harmonization of the terminology, correct use of nomenclature, reference genomes for different populations, rare disease variant databases, and clinical reports.