TRAPLINE: a standardized and automated pipeline for RNA sequencing data analysis, evaluation and annotation

Genetic marker: a genome mapping tool to decode genetic diversity of livestock animals

Genotyping is the process of determining the genetic makeup of an organism by examining its DNA sequences using various genetic markers. It has been widely used in various fields, such as agriculture, biomedical and conservation research, to study genetic diversity, inheritance, the genetic basis of disease-associated traits, evolution, adaptation, etc., Genotyping markers have evolved immensely and are broadly classified as random markers (RFLP, RAPD, AFLP, etc.) and functional markers (SCoT, CDDP, SRAP, etc.). However, functional markers are very limited in genotype studies, especially in animal science, despite their advantages in overcoming the limitations of random markers, which are directly linked with phenotypic traits, high specificity, and similar logistic requirements. The current review surveyed the available random and functional markers for genotyping applications, focusing on livestock including plant and microbe domains. This review article summarises the application, advantages, and limitations of developed markers and methods for genotyping applications. This review aims to make the reader aware of all available markers, their design principles, and methods, and we discuss the marker inheritance patterns of RLFP and AFLP. The review further outlines the marker selection for particular applications and endorses the application of functional markers in genotyping research.

Curare and GenExVis: a versatile toolkit for analyzing and visualizing RNA-Seq data

Even though high-throughput transcriptome sequencing is routinely performed in many laboratories, computational analysis of such data remains a cumbersome process often executed manually, hence error-prone and lacking reproducibility. For corresponding data processing, we introduce Curare, an easy-to-use yet versatile workflow builder for analyzing high-throughput RNA-Seq data focusing on differential gene expression experiments. Data analysis with Curare is customizable and subdivided into preprocessing, quality control, mapping, and downstream analysis stages, providing multiple options for each step while ensuring the reproducibility of the workflow. For a fast and straightforward exploration and visualization of differential gene expression results, we provide the gene expression visualizer software GenExVis. GenExVis can create various charts and tables from simple gene expression tables and DESeq2 results without the requirement to upload data or install software packages. In combination, Curare and GenExVis provide a comprehensive software environment that supports the entire data analysis process, from the initial handling of raw RNA-Seq data to the final DGE analyses and result visualizations, thereby significantly easing data processing and subsequent interpretation.

The identification of new roles for nicotinamide mononucleotide after spinal cord injury in mice: an RNA-seq and global gene expression study

Background

Nicotinamide mononucleotide (NMN), an important transforming precursor of nicotinamide adenine dinucleotide (NAD+). Numerous studies have confirmed the neuroprotective effects of NMN in nervous system diseases. However, its role in spinal cord injury (SCI) and the molecular mechanisms involved have yet to be fully elucidated.

Methods

We established a moderate-to-severe model of SCI by contusion (70 kdyn) using a spinal cord impactor. The drug was administered immediately after surgery, and mice were intraperitoneally injected with either NMN (500 mg NMN/kg body weight per day) or an equivalent volume of saline for seven days. The central area of the spinal cord was harvested seven days after injury for the systematic analysis of global gene expression by RNA Sequencing (RNA-seq) and finally validated using qRT-PCR.

Results

NMN supplementation restored NAD+ levels after SCI, promoted motor function recovery, and alleviated pain. This could potentially be associated with alterations in NAD+ dependent enzyme levels. RNA sequencing (RNA-seq) revealed that NMN can inhibit inflammation and potentially regulate signaling pathways, including interleukin-17 (IL-17), tumor necrosis factor (TNF), toll-like receptor, nod-like receptor, and chemokine signaling pathways. In addition, the construction of a protein-protein interaction (PPI) network and the screening of core genes showed that interleukin 1β (IL-1β), interferon regulatory factor 7 (IRF 7), C-X-C motif chemokine ligand 10 (Cxcl10), and other inflammationrelated factors, changed significantly after NMN treatment. qRT-PCR confirmed the inhibitory effect of NMN on inflammatory factors (IL-1β, TNF-α, IL-17A, IRF7) and chemokines (chemokine ligand 3, Cxcl10) in mice following SCI.

Conclusion

The reduction of NAD+ levels after SCI can be compensated by NMN supplementation, which can significantly restore motor function and relieve pain in a mouse model. RNA-seq and qRT-PCR systematically revealed that NMN affected inflammation-related signaling pathways, including the IL-17, TNF, Toll-like receptor, NOD-like receptor and chemokine signaling pathways, by down-regulating the expression of inflammatory factors and chemokines.

Exploring the Role of Circulating Cell-Free RNA in the Development of Colorectal Cancer

Circulating tumor RNA (ctRNA) has recently emerged as a novel and attractive liquid biomarker. CtRNA is capable of providing important information about the expression of a variety of target genes noninvasively, without the need for biopsies, through the use of circulating RNA sequencing. The overexpression of cancer-specific transcripts increases the tumor-derived RNA signal, which overcomes limitations due to low quantities of circulating tumor DNA (ctDNA). The purpose of this work is to present an up-to-date review of current knowledge regarding ctRNAs and their status as biomarkers to address the diagnosis, prognosis, prediction, and drug resistance of colorectal cancer. The final section of the article discusses the practical aspects involved in analyzing plasma ctRNA, including storage and isolation, detection technologies, and their limitations in clinical applications.

transXpress: a Snakemake pipeline for streamlined de novo transcriptome assembly and annotation

BACKGROUND

RNA-seq followed by de novo transcriptome assembly has been a transformative technique in biological research of non-model organisms, but the computational processing of RNA-seq data entails many different software tools. The complexity of these de novo transcriptomics workflows therefore presents a major barrier for researchers to adopt best-practice methods and up-to-date versions of software.

RESULTS

Here we present a streamlined and universal de novo transcriptome assembly and annotation pipeline, transXpress, implemented in Snakemake. transXpress supports two popular assembly programs, Trinity and rnaSPAdes, and allows parallel execution on heterogeneous cluster computing hardware.

CONCLUSIONS

transXpress simplifies the use of best-practice methods and up-to-date software for de novo transcriptome assembly, and produces standardized output files that can be mined using SequenceServer to facilitate rapid discovery of new genes and proteins in non-model organisms.

GEMmaker: process massive RNA-seq datasets on heterogeneous computational infrastructure

Background

Quantification of gene expression from RNA-seq data is a prerequisite for transcriptome analysis such as differential gene expression analysis and gene co-expression network construction. Individual RNA-seq experiments are larger and combining multiple experiments from sequence repositories can result in datasets with thousands of samples. Processing hundreds to thousands of RNA-seq data can result in challenges related to data management, access to sufficient computational resources, navigation of high-performance computing (HPC) systems, installation of required software dependencies, and reproducibility. Processing of larger and deeper RNA-seq experiments will become more common as sequencing technology matures.

Results

GEMmaker, is a nf-core compliant, Nextflow workflow, that quantifies gene expression from small to massive RNA-seq datasets. GEMmaker ensures results are highly reproducible through the use of versioned containerized software that can be executed on a single workstation, institutional compute cluster, Kubernetes platform or the cloud. GEMmaker supports popular alignment and quantification tools providing results in raw and normalized formats. GEMmaker is unique in that it can scale to process thousands of local or remote stored samples without exceeding available data storage.

Conclusions

Workflows that quantify gene expression are not new, and many already address issues of portability, reusability, and scale in terms of access to CPUs. GEMmaker provides these benefits and adds the ability to scale despite low data storage infrastructure. This allows users to process hundreds to thousands of RNA-seq samples even when data storage resources are limited. GEMmaker is freely available and fully documented with step-by-step setup and execution instructions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04629-7.

Single-Cell Analysis of the In Vivo Dynamics of Host Circulating Immune Cells Highlights the Importance of Myeloid Cells in Avian Flaviviral Infection

Ducks are an economically important waterfowl but a natural reservoir for some zoonotic pathogens, such as influenza virus and flaviviruses. Our understanding of the duck immune system and its interaction with viruses remains incomplete. In this study, we constructed the transcriptomic landscape of duck circulating immune cells, the first line of defense in the arthropod-borne transmission of arboviruses, using high-throughput single-cell transcriptome sequencing, which defined 14 populations of peripheral blood leukocytes (PBLks) based on distinct molecular signatures and revealed differences in the clustering of PBLks between ducks and humans. Taking advantage of in vivo sex differences in the susceptibility of duck PBLks to avian tembusu virus (TMUV) infection, a mosquito-borne flavivirus newly emerged from ducks with a broad host range from mosquitos to mammals, a comprehensive comparison of the in vivo dynamics of duck PBLks upon TMUV infection between sexes was performed at the single-cell level. Using this in vivo model, we discovered that TMUV infection reprogrammed duck PBLks differently between sexes, driving the expansion of granulocytes and priming granulocytes and monocytes for antiviral immune activation in males but decreasing the antiviral immune activity of granulocytes and monocytes by restricting their dynamic transitions from steady states to antiviral states with a decrease in the abundance of circulating monocytes in females. This study provides insights into the initial immune responses of ducks to arthropod-borne flaviviral infection and provides a framework for studying duck antiviral immunity.

Music of metagenomics-a review of its applications, analysis pipeline, and associated tools

This humble effort highlights the intricate details of metagenomics in a simple, poetic, and rhythmic way. The paper enforces the significance of the research area, provides details about major analytical methods, examines the taxonomy and assembly of genomes, emphasizes some tools, and concludes by celebrating the richness of the ecosystem populated by the "metagenome."

RNASeqR: An R Package for Automated Two-Group RNA-Seq Analysis Workflow

RNA-Seq analysis has revolutionized researchers' understanding of the transcriptome in biological research. Assessing the differences in transcriptomic profiles between tissue samples or patient groups enables researchers to explore the underlying biological impact of transcription. RNA-Seq analysis requires multiple processing steps and huge computational capabilities. There are many well-developed R packages for individual steps; however, there are few R/Bioconductor packages that integrate existing software tools into a comprehensive RNA-Seq analysis and provide fundamental end-to-end results in pure R environment so that researchers can quickly and easily get fundamental information in big sequencing data. To address this need, we have developed the open source R/Bioconductor package, RNASeqR. It allows users to run an automated RNA-Seq analysis with only six steps, producing essential tabular and graphical results for further biological interpretation. The features of RNASeqR include: six-step analysis, comprehensive visualization, background execution version, and the integration of both R and command-line software. RNASeqR provides fast, light-weight, and easy-to-run RNA-Seq analysis pipeline in pure R environment. It allows users to efficiently utilize popular software tools, including both R/Bioconductor and command-line tools, without predefining the resources or environments. RNASeqR is freely available for Linux and macOS operating systems from Bioconductor (https://bioconductor.org/packages/release/bioc/html/RNASeqR.html).

Searchlight: automated bulk RNA-seq exploration and visualisation using dynamically generated R scripts

BACKGROUND

Once bulk RNA-seq data has been processed, i.e. aligned and then expression and differential tables generated, there remains the essential process where the biology is explored, visualized and interpreted. Without the use of a visualisation and interpretation pipeline this step can be time consuming and laborious, and is often completed using R. Though commercial visualisation and interpretation pipelines are comprehensive, freely available pipelines are currently more limited.

RESULTS

Here we demonstrate Searchlight, a freely available bulk RNA-seq visualisation and interpretation pipeline. Searchlight provides: a comprehensive statistical and visual analysis, focusing on the global, pathway and single gene levels; compatibility with most differential experimental designs irrespective of organism or experimental complexity, via three workflows; reports; and support for downstream user modification of plots via user-friendly R-scripts and a Shiny app. We show that Searchlight offers greater automation than current best tools (VIPER and BioJupies). We demonstrate in a timed re-analysis study, that alongside a standard bulk RNA-seq processing pipeline, Searchlight can be used to complete bulk RNA-seq projects up to the point of manuscript quality figures, in under 3 h.

CONCLUSIONS

Compared to a manual R based analysis or current best freely available pipelines (VIPER and BioJupies), Searchlight can reduce the time and effort needed to complete bulk RNA-seq projects to manuscript level. Searchlight is suitable for bioinformaticians, service providers and bench scientists. https://github.com/Searchlight2/Searchlight2 .

RNA-Seq Data for Reliable SNP Detection and Genotype Calling: Interest for Coding Variant Characterization and Cis-Regulation Analysis by Allele-Specific Expression in Livestock Species

In addition to their common usages to study gene expression, RNA-seq data accumulated over the last 10 years are a yet-unexploited resource of SNPs in numerous individuals from different populations. SNP detection by RNA-seq is particularly interesting for livestock species since whole genome sequencing is expensive and exome sequencing tools are unavailable. These SNPs detected in expressed regions can be used to characterize variants affecting protein functions, and to study cis-regulated genes by analyzing allele-specific expression (ASE) in the tissue of interest. However, gene expression can be highly variable, and filters for SNP detection using the popular GATK toolkit are not yet standardized, making SNP detection and genotype calling by RNA-seq a challenging endeavor. We compared SNP calling results using GATK suggested filters, on two chicken populations for which both RNA-seq and DNA-seq data were available for the same samples of the same tissue. We showed, in expressed regions, a RNA-seq precision of 91% (SNPs detected by RNA-seq and shared by DNA-seq) and we characterized the remaining 9% of SNPs. We then studied the genotype (GT) obtained by RNA-seq and the impact of two factors (GT call-rate and read number per GT) on the concordance of GT with DNA-seq; we proposed thresholds for them leading to a 95% concordance. Applying these thresholds to 767 multi-tissue RNA-seq of 382 birds of 11 chicken populations, we found 9.5 M SNPs in total, of which ∼550,000 SNPs per tissue and population with a reliable GT (call rate ≥ 50%) and among them, ∼340,000 with a MAF ≥ 10%. We showed that such RNA-seq data from one tissue can be used to (i) detect SNPs with a strong predicted impact on proteins, despite their scarcity in each population (16,307 SIFT deleterious missenses and 590 stop-gained), (ii) study, on a large scale, cis-regulations of gene expression, with ∼81% of protein-coding and 68% of long non-coding genes (TPM ≥ 1) that can be analyzed for ASE, and with ∼29% of them that were cis-regulated, and (iii) analyze population genetic using such SNPs located in expressed regions. This work shows that RNA-seq data can be used with good confidence to detect SNPs and associated GT within various populations and used them for different analyses as GTEx studies.

RNAdetector: a free user-friendly stand-alone and cloud-based system for RNA-Seq data analysis

Background

RNA-Seq is a well-established technology extensively used for transcriptome profiling, allowing the analysis of coding and non-coding RNA molecules. However, this technology produces a vast amount of data requiring sophisticated computational approaches for their analysis than other traditional technologies such as Real-Time PCR or microarrays, strongly discouraging non-expert users. For this reason, dozens of pipelines have been deployed for the analysis of RNA-Seq data. Although interesting, these present several limitations and their usage require a technical background, which may be uncommon in small research laboratories. Therefore, the application of these technologies in such contexts is still limited and causes a clear bottleneck in knowledge advancement.

Results

Motivated by these considerations, we have developed RNAdetector, a new free cross-platform and user-friendly RNA-Seq data analysis software that can be used locally or in cloud environments through an easy-to-use Graphical User Interface allowing the analysis of coding and non-coding RNAs from RNA-Seq datasets of any sequenced biological species.

Conclusions

RNAdetector is a new software that fills an essential gap between the needs of biomedical and research labs to process RNA-Seq data and their common lack of technical background in performing such analysis, which usually relies on outsourcing such steps to third party bioinformatics facilities or using expensive commercial software.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04211-7.

Global gene expression analysis using RNA-seq reveals the new roles of Panax notoginseng Saponins in ischemic cardiomyocytes

ETHNOPHARMACOLOGICAL RELEVANCE

Panax notoginseng saponins (PNS), the main active ingredients of Panax notoginseng (Burkill) F.H.Chen, have been clinically used for cardiovascular diseases treatment in China as the Traditional Chinese Medicine (TCM) (Duan et al., 2017). Evidence demonstrated that PNS protected cardiomyocytes from myocardial ischemia, but the more underlying molecular mechanisms of the protective effect are still unclear. The aims of this study are to systematically know the function of PNS and discover new roles of PNS in ischemic cardiomyocytes.

MATERIALS AND METHODS

To confirm PNS function on ischemic cardiomyopathy, we established in vitro myocardial ischemia model on H9C2 cardiomyocyte line, which was induced by oxygen-glucose depletion (OGD). Then RNA-seq was carried out to systematically analyze global gene expression. This study was aimed to systematically investigate the protective effect and more potential molecular mechanisms of PNS on H9C2 cardiomyocytes in vitro through whole-transcriptome analysis with total RNA sequencing (RNA-Seq).

RESULTS

PNS exhibited anti-apoptotic effect in H9C2 cardiomyocytes in OGD-induced myocardial ischemia model. Through RNA-seq, we found that OGD affected expression profiling of many genes, including upregulated and downregulated genes. PNS inhibited cardiomyocyte apoptosis and death through rescuing cell cycle arrest, the DNA double-strand breakage repair process and chromosome segregation. Interestingly, for the canonical signaling pathways regulation, RNA-seq showed PNS could inhibit cardiac hypertrophy, MAPK signaling pathway, and re-activate PI3K/AKT and AMPK signaling pathways. Experimental data also confirmed the PNS could protect cardiomyocytes from OGD-induced apoptosis through activating PI3K/AKT and AMPK signaling pathways. Moreover, RNA-seq demonstrated that the expression levels of many non-coding RNAs, such as miRNAs and lncRNAs, were significantly affected after PNS treatment, suggesting that PNS could protect cardiomyocytes through regulating non-coding RNAs.

CONCLUSION

RNA-seq systematically revealed different novel roles of Panax Notoginseng Saponins (PNS) in protecting cardiomyocytes from apoptosis, induced by myocardial ischemia, through rescuing cell cycle arrest and cardiac hypertrophy, re-activating the DNA double-strand breakage repair process, chromosome segregation, PI3K/Akt and AMPK signaling pathways and regulating non-coding RNAs.

A Streamlined Approach to Pathway Analysis from RNA-Sequencing Data

The reduction in costs associated with performing RNA-sequencing has driven an increase in the application of this analytical technique; however, restrictive factors associated with this tool have now shifted from budgetary constraints to time required for data processing. The sheer scale of the raw data produced can present a formidable challenge for researchers aiming to glean vital information about samples. Though many of the companies that perform RNA-sequencing provide a basic report for the submitted samples, this may not adequately capture particular pathways of interest for sample comparisons. To further assess these data, it can therefore be necessary to utilize various enrichment and mapping software platforms to highlight specific relations. With the wide array of these software platforms available, this can also present a daunting task. The methodology described herein aims to enable researchers new to handling RNA-sequencing data with a streamlined approach to pathway analysis. Additionally, the implemented software platforms are readily available and free to utilize, making this approach viable, even for restrictive budgets. The resulting tables and nodal networks will provide valuable insight into samples and can be used to generate high-quality graphics for publications and presentations.

De Novo Profiling of Long Non-Coding RNAs Involved in MC-LR-Induced Liver Injury in Whitefish: Discovery and Perspectives

Microcystin-LR (MC-LR) is a potent hepatotoxin for which a substantial gap in knowledge persists regarding the underlying molecular mechanisms of liver toxicity and injury. Although long non-coding RNAs (lncRNAs) have been extensively studied in model organisms, our knowledge concerning the role of lncRNAs in liver injury is limited. Given that lncRNAs show low levels of sequence conservation, their role becomes even more unclear in non-model organisms without an annotated genome, like whitefish (Coregonus lavaretus). The objective of this study was to discover and profile aberrantly expressed polyadenylated lncRNAs that are involved in MC-LR-induced liver injury in whitefish. Using RNA sequencing (RNA-Seq) data, we de novo assembled a high-quality whitefish liver transcriptome. This enabled us to find 94 differentially expressed (DE) putative evolutionary conserved lncRNAs, such as MALAT1, HOTTIP, HOTAIR or HULC, and 4429 DE putative novel whitefish lncRNAs, which differed from annotated protein-coding transcripts (PCTs) in terms of minimum free energy, guanine-cytosine (GC) base-pair content and length. Additionally, we identified DE non-coding transcripts that might be 3′ autonomous untranslated regions (3′UTRs) of mRNAs. We found both evolutionary conserved lncRNAs as well as novel whitefish lncRNAs that could serve as biomarkers of liver injury.

RNAflow: An Effective and Simple RNA-Seq Differential Gene Expression Pipeline Using Nextflow

RNA-Seq enables the identification and quantification of RNA molecules, often with the aim of detecting differentially expressed genes (DEGs). Although RNA-Seq evolved into a standard technique, there is no universal gold standard for these data's computational analysis. On top of that, previous studies proved the irreproducibility of RNA-Seq studies. Here, we present a portable, scalable, and parallelizable Nextflow RNA-Seq pipeline to detect DEGs, which assures a high level of reproducibility. The pipeline automatically takes care of common pitfalls, such as ribosomal RNA removal and low abundance gene filtering. Apart from various visualizations for the DEG results, we incorporated downstream pathway analysis for common species as Homo sapiens and Mus musculus. We evaluated the DEG detection functionality while using qRT-PCR data serving as a reference and observed a very high correlation of the logarithmized gene expression fold changes.

GLP: A requirement in cell therapies - perspectives for the cardiovascular field

In biomedical research, enormous progress is being made and new candidates for putative medicinal products emerge. However, most published preclinical data are not conducted according to the standard Good Laboratory Practice (GLP). GLP is mandatory for preclinical analysis of Advanced Therapy Medicinal Products (ATMP) and thereby a prerequisite for planning and conduction of clinical trials. Not inconsiderable numbers of clinical trials are terminated earlier or fail - do inadequate testing strategies or missing specialized assays during the preclinical development contribute to this severe complex of problems? Unfortunately, there is also a lack of access to GLP testing results and OECD (Organisation for Economic Co-operation and Development) GLP guidelines are not yet adjusted to ATMP specialties. Ultimately, GLP offers possibilities to generate reliable and reproducible data. Therefore, this review elucidates different GLP aspects in drug development, speculates on reasons of putative low GLP acceptance in the scientific community and mentions solution proposals.

Translating 'big data': better understanding of host-pathogen interactions to control bacterial foodborne pathogens in poultry

Recent technological advances has led to the generation, storage, and sharing of colossal sets of information ('big data'), and the expansion of 'omics' in science. To date, genomics/metagenomics, transcriptomics, proteomics, and metabolomics are arguably the most ground breaking approaches in food and public safety. Here we review some of the recent studies of foodborne pathogens (Campylobacter spp., Salmonella spp., and Escherichia coli) in poultry using big data. Genomic/metagenomic approaches have reveal the importance of the gut microbiota in health and disease. They have also been used to identify, monitor, and understand the epidemiology of antibiotic-resistance mechanisms and provide concrete evidence about the role of poultry in human infections. Transcriptomics studies have increased our understanding of the pathophysiology and immunopathology of foodborne pathogens in poultry and have led to the identification of host-resistance mechanisms. Proteomic/metabolomic approaches have aided in identifying biomarkers and the rapid detection of low levels of foodborne pathogens. Overall, 'omics' approaches complement each other and may provide, at least in part, a solution to our current food-safety issues by facilitating the development of new rapid diagnostics, therapeutic drugs, and vaccines to control foodborne pathogens in poultry. However, at this time most 'omics' approaches still remain underutilized due to their high cost and the high level of technical skills required.

hppRNA-a Snakemake-based handy parameter-free pipeline for RNA-Seq analysis of numerous samples

RNA-Seq technology has been gradually becoming a routine approach for characterizing the properties of transcriptome in terms of organisms, cell types and conditions and consequently a big burden has been put on the facet of data analysis, which calls for an easy-to-learn workflow to cope with the increased demands from a large number of laboratories across the world. We report a one-in-all solution called hppRNA, composed of four scenarios such as pre-mapping, core-workflow, post-mapping and sequence variation detection, written by a series of individual Perl and R scripts, counting on well-established and preinstalled software, irrespective of single-end or paired-end, unstranded or stranded sequencing method. It features six independent core-workflows comprising the state-of-the-art technology with dozens of popular cutting-edge tools such as Tophat-Cufflink-Cuffdiff, Subread-featureCounts-DESeq2, STAR-RSEM-EBSeq, Bowtie-eXpress-edgeR, kallisto-sleuth, HISAT-StringTie-Ballgown, and embeds itself in Snakemake, which is a modern pipeline management system. The core function of this pipeline is turning the raw fastq files into gene/isoform expression matrix and differentially expressed genes or isoforms as well as the identification of fusion genes, single nucleotide polymorphisms, long noncoding RNAs and circular RNAs. Last but not least, this pipeline is specifically designed for performing the systematic analysis on a huge set of samples in one go, ideally for the researchers who intend to deploy the pipeline on their local servers. The scripts as well as the user manual are freely available at https://sourceforge.net/projects/hpprna/.

Workflow Development for the Functional Characterization of ncRNAs

During the last decade, ncRNAs have been investigated intensively and revealed their regulatory role in various biological processes. Worldwide research efforts have identified numerous ncRNAs and multiple RNA subtypes, which are attributed to diverse functionalities known to interact with different functional layers, from DNA and RNA to proteins. This makes the prediction of functions for newly identified ncRNAs challenging. Current bioinformatics and systems biology approaches show promising results to facilitate an identification of these diverse ncRNA functionalities. Here, we review (a) current experimental protocols, i.e., for Next Generation Sequencing, for a successful identification of ncRNAs; (b) sequencing data analysis workflows as well as available computational environments; and (c) state-of-the-art approaches to functionally characterize ncRNAs, e.g., by means of transcriptome-wide association studies, molecular network analyses, or artificial intelligence guided prediction. In addition, we present a strategy to cover the identification and functional characterization of unknown transcripts by using connective workflows.

Specific Cell (Re-)Programming: Approaches and Perspectives

Many disorders are manifested by dysfunction of key cell types or their disturbed integration in complex organs. Thereby, adult organ systems often bear restricted self-renewal potential and are incapable of achieving functional regeneration. This underlies the need for novel strategies in the field of cell (re-)programming-based regenerative medicine as well as for drug development in vitro. The regenerative field has been hampered by restricted availability of adult stem cells and the potentially hazardous features of pluripotent embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs). Moreover, ethical concerns and legal restrictions regarding the generation and use of ESCs still exist. The establishment of direct reprogramming protocols for various therapeutically valuable somatic cell types has overcome some of these limitations. Meanwhile, new perspectives for safe and efficient generation of different specified somatic cell types have emerged from numerous approaches relying on exogenous expression of lineage-specific transcription factors, coding and noncoding RNAs, and chemical compounds.It should be of highest priority to develop protocols for the production of mature and physiologically functional cells with properties ideally matching those of their endogenous counterparts. Their availability can bring together basic research, drug screening, safety testing, and ultimately clinical trials. Here, we highlight the remarkable successes in cellular (re-)programming, which have greatly advanced the field of regenerative medicine in recent years. In particular, we review recent progress on the generation of cardiomyocyte subtypes, with a focus on cardiac pacemaker cells. Graphical Abstract.

Gene expression in adverse reaction to metal debris around metal-on-metal arthroplasty: An RNA-Seq-based study

Joint replacement surgery is a standard treatment of advanced osteoarthritis (OA). Since 2000, cobalt-chromium (CoCr) metal-on-metal (MoM) implants were widely used in hip arthroplasties. Some patients developed "adverse reaction to metal debris" (ARMD) around the prosthesis, resulting in a need for revision surgery. In the present study, we addressed the pathogenesis of ARMD by genome-wide expression analysis. Pseudosynovial ARMD tissue was obtained from revision surgery of Articular Surface Replacement (ASR, DePuy, Warsaw, IN, USA) hip arthroplasties. Control tissue was 1) OA synovium from primary hip arthroplasties and 2) inflammatory pseudosynovial tissue from metal-on-plastic (MoP) implant revisions. In ARMD tissue, the expression of 1446 genes was significantly increased and that of 1881 decreased as compared to OA synovium. Genes associated with immune response, tissue development and certain leukocyte signaling pathways were enriched in the differently (FC > 2) expressed genes. The network analysis proposed PRKACB, CD2, CD52 and CD53 as the central regulators of the greatest (FC > 10) differences. When ARMD tissue was compared to MoP tissue, the expression of 16 genes was significantly higher and that of 21 lower. Many of these genes were associated with redox homeostasis, metal ion binding and transport, macrophage activation and apoptosis. Interestingly, genes central to myofibroblast (AEBP1 and DES) and osteoclast (CCL21, TREM2 and CKB) development were upregulated in the MoP tissue. In network analysis, IL8, NQO1, GSTT1 and HMOX1 were identified as potential central regulators of the changes. In conclusion, excessive amounts of CoCr debris produced by MoM hip implants induces in a group of patients a unique adverse reaction characterized with enhanced expression of genes associated with inflammation, redox homeostasis, metal ion binding and transport, macrophage activation and apoptosis.

VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis

Background

RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts.

Results

Using the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses.

Conclusions

VIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2139-9) contains supplementary material, which is available to authorized users.

Explorative visual analytics on interval-based genomic data and their metadata

Background

With the wide-spreading of public repositories of NGS processed data, the availability of user-friendly and effective tools for data exploration, analysis and visualization is becoming very relevant. These tools enable interactive analytics, an exploratory approach for the seamless “sense-making” of data through on-the-fly integration of analysis and visualization phases, suggested not only for evaluating processing results, but also for designing and adapting NGS data analysis pipelines.

Results

This paper presents abstractions for supporting the early analysis of NGS processed data and their implementation in an associated tool, named GenoMetric Space Explorer (GeMSE). This tool serves the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can also be used starting from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions; metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis and visualization that help biologists and bioinformaticians in making sense of heterogeneous genomic datasets. By means of an explorative interaction support, users can trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps.

Conclusions

GeMSE effective application and practical usefulness is demonstrated through significant use cases of biological interest. GeMSE is available at http://www.bioinformatics.deib.polimi.it/GeMSE/, and its source code is available at https://github.com/Genometric/GeMSE under GPLv3 open-source license.

Mammalian γ2 AMPK regulates intrinsic heart rate

AMPK is a conserved serine/threonine kinase whose activity maintains cellular energy homeostasis. Eukaryotic AMPK exists as αβγ complexes, whose regulatory γ subunit confers energy sensor function by binding adenine nucleotides. Humans bearing activating mutations in the γ2 subunit exhibit a phenotype including unexplained slowing of heart rate (bradycardia). Here, we show that γ2 AMPK activation downregulates fundamental sinoatrial cell pacemaker mechanisms to lower heart rate, including sarcolemmal hyperpolarization-activated current (I f) and ryanodine receptor-derived diastolic local subsarcolemmal Ca2+ release. In contrast, loss of γ2 AMPK induces a reciprocal phenotype of increased heart rate, and prevents the adaptive intrinsic bradycardia of endurance training. Our results reveal that in mammals, for which heart rate is a key determinant of cardiac energy demand, AMPK functions in an organ-specific manner to maintain cardiac energy homeostasis and determines cardiac physiological adaptation to exercise by modulating intrinsic sinoatrial cell behavior.

Stem cells and heart disease - Brake or accelerator?

After two decades of intensive research and attempts of clinical translation, stem cell based therapies for cardiac diseases are not getting closer to clinical success. This review tries to unravel the obstacles and focuses on underlying mechanisms as the target for regenerative therapies. At present, the principal outcome in clinical therapy does not reflect experimental evidence. It seems that the scientific obstacle is a lack of integration of knowledge from tissue repair and disease mechanisms. Recent insights from clinical trials delineate mechanisms of stem cell dysfunction and gene defects in repair mechanisms as cause of atherosclerosis and heart disease. These findings require a redirection of current practice of stem cell therapy and a reset using more detailed analysis of stem cell function interfering with disease mechanisms. To accelerate scientific development the authors suggest intensifying unified computational data analysis and shared data knowledge by using open-access data platforms.

(Re-)programming of subtype specific cardiomyocytes

Adult cardiomyocytes (CMs) possess a highly restricted intrinsic regenerative potential - a major barrier to the effective treatment of a range of chronic degenerative cardiac disorders characterized by cellular loss and/or irreversible dysfunction and which underlies the majority of deaths in developed countries. Both stem cell programming and direct cell reprogramming hold promise as novel, potentially curative approaches to address this therapeutic challenge. The advent of induced pluripotent stem cells (iPSCs) has introduced a second pluripotent stem cell source besides embryonic stem cells (ESCs), enabling even autologous cardiomyocyte production. In addition, the recent achievement of directly reprogramming somatic cells into cardiomyocytes is likely to become of great importance. In either case, different clinical scenarios will require the generation of highly pure, specific cardiac cellular-subtypes. In this review, we discuss these themes as related to the cardiovascular stem cell and programming field, including a focus on the emergent topic of pacemaker cell generation for the development of biological pacemakers and in vitro drug testing.

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

This workflow allows novice researchers to leverage advanced computational resources such as cloud computing to carry out pairwise comparative transcriptomics. It also serves as a primer for biologists to develop data scientist computational skills, e.g. executing bash commands, visualization and management of large data sets. All command line code and further explanations of each command or step can be found on the wiki (https://wiki.cyverse.org/wiki/x/dgGtAQ). The Discovery Environment and Atmosphere platforms are connected together through the CyVerse Data Store. As such, once the initial raw sequencing data has been uploaded there is no more need to transfer large data files over an Internet connection, minimizing the amount of time needed to conduct analyses. This protocol is designed to analyze only two experimental treatments or conditions. Differential gene expression analysis is conducted through pairwise comparisons, and will not be suitable to test multiple factors. This workflow is also designed to be manual rather than automated. Each step must be executed and investigated by the user, yielding a better understanding of data and analytical outputs, and therefore better results for the user. Once complete, this protocol will yield de novo assembled transcriptome(s) for underserved (non-model) organisms without the need to map to previously assembled reference genomes (which are usually not available in underserved organism). These de novo transcriptomes are further used in pairwise differential gene expression analysis to investigate genes differing between two experimental conditions. Differentially expressed genes are then functionally annotated to understand the genetic response organisms have to experimental conditions. In total, the data derived from this protocol is used to test hypotheses about biological responses of underserved organisms.

Human Nup98 regulates the localization and activity of DExH/D-box helicase DHX9

Beyond their role at nuclear pore complexes, some nucleoporins function in the nucleoplasm. One such nucleoporin, Nup98, binds chromatin and regulates gene expression. To gain insight into how Nup98 contributes to this process, we focused on identifying novel binding partners and understanding the significance of these interactions. Here we report on the identification of the DExH/D-box helicase DHX9 as an intranuclear Nup98 binding partner. Various results, including in vitro assays, show that the FG/GLFG region of Nup98 binds to N- and C-terminal regions of DHX9 in an RNA facilitated manner. Importantly, binding of Nup98 stimulates the ATPase activity of DHX9, and a transcriptional reporter assay suggests Nup98 supports DHX9-stimulated transcription. Consistent with these observations, our analysis revealed that Nup98 and DHX9 bind interdependently to similar gene loci and their transcripts. Based on our results, we propose that Nup98 functions as a co-factor that regulates DHX9 and, potentially, other RNA helicases.