RAP: RNA-Seq Analysis Pipeline, a new cloud-based NGS web application

HiOmics: A cloud-based one-stop platform for the comprehensive analysis of large-scale omics data

Analyzing the vast amount of omics data generated comprehensively by high-throughput sequencing technology is of utmost importance for scientists. In this context, we propose HiOmics, a cloud-based platform equipped with nearly 300 plugins designed for the comprehensive analysis and visualization of omics data. HiOmics utilizes the Element Plus framework to craft a user-friendly interface and harnesses Docker container technology to ensure the reliability and reproducibility of data analysis results. Furthermore, HiOmics employs the Workflow Description Language and Cromwell engine to construct workflows, ensuring the portability of data analysis and simplifying the examination of intricate data. Additionally, HiOmics has developed DataCheck, a tool based on Golang, which verifies and converts data formats. Finally, by leveraging the object storage technology and batch computing capabilities of public cloud platforms, HiOmics enables the storage and processing of large-scale data while maintaining resource independence among users.

Tumoral and stromal hMENA isoforms impact tertiary lymphoid structure localization in lung cancer and predict immune checkpoint blockade response in patients with cancer

BACKGROUND

Tertiary Lymphoid Structures (TLS) correlate with positive outcomes in patients with NSCLC and the efficacy of immune checkpoint blockade (ICB) in cancer. The actin regulatory protein hMENA undergoes tissue-specific splicing, producing the epithelial hMENA11a linked to favorable prognosis in early NSCLC, and the mesenchymal hMENAΔv6 found in invasive cancer cells and pro-tumoral cancer-associated fibroblasts (CAFs). This study investigates how hMENA isoforms in tumor cells and CAFs relate to TLS presence, localization and impact on patient outcomes and ICB response.

METHODS

Methods involved RNA-SEQ on NSCLC cells with depleted hMENA isoforms. A retrospective observational study assessed tissues from surgically treated N0 patients with NSCLC, using immunohistochemistry for tumoral and stromal hMENA isoforms, fibronectin, and TLS presence. ICB-treated patient tumors were analyzed using Nanostring nCounter and GeoMx spatial transcriptomics. Multiparametric flow cytometry characterized B cells and tissue-resident memory T cells (TRM). Survival and ICB response were estimated in the cohort and validated using bioinformatics pipelines in different datasets.

FINDINGS

Findings indicate that hMENA11a in NSCLC cells upregulates the TLS regulator LTβR, decreases fibronectin, and favors CXCL13 production by TRM. Conversely, hMENAΔv6 in CAFs inhibits LTβR-related NF-kB pathway, reduces CXCL13 secretion, and promotes fibronectin production. These patterns are validated in N0 NSCLC tumors, where hMENA11ahigh expression, CAF hMENAΔv6low, and stromal fibronectinlow are associated with intratumoral TLS, linked to memory B cells and predictive of longer survival. The hMENA isoform pattern, fibronectin, and LTβR expression broadly predict ICB response in tumors where TLS indicates an anti-tumor immune response.

INTERPRETATION

This study uncovers hMENA alternative splicing as an unexplored contributor to TLS-related Tumor Immune Microenvironment (TIME) and a promising biomarker for clinical outcomes and likely ICB responsiveness in N0 patients with NSCLC.

FUNDING

This work is supported by AIRC (IG 19822), ACC (RCR-2019-23669120), CAL.HUB.RIA Ministero Salute PNRR-POS T4, "Ricerca Corrente" granted by the Italian Ministry of Health.

RNA N6-Methyladenosine Affects Copper-Induced Oxidative Stress Response in Arabidopsis thaliana

Recently, post-transcriptional regulation of mRNA mediated by N6-methyladenosine (m6A) has been found to have profound effects on transcriptome regulation during plant responses to various abiotic stresses. However, whether this RNA modification can affect an oxidative stress response in plants has not been studied. To assess the role of m6A modifications during copper-induced oxidative stress responses, m6A-IP-seq was performed in Arabidopsis seedlings exposed to high levels of copper sulfate. This analysis revealed large-scale shifts in this modification on the transcripts most relevant for oxidative stress. This altered epitranscriptomic mark is known to influence transcript abundance and translation; therefore we scrutinized these possibilities. We found an increased abundance of copper-enriched m6A-containing transcripts. Similarly, we also found increased ribosome occupancy of copper-enriched m6A-containing transcripts, specifically those encoding proteins involved with stress responses relevant to oxidative stressors. Furthermore, the significance of the m6A epitranscriptome on plant oxidative stress tolerance was uncovered by assessing germination and seedling development of the mta (N6-methyladenosine RNA methyltransferase A mutant complemented with ABI3:MTA) mutant exposed to high copper treatment. These analyses suggested hypersensitivity of the mta mutant compared to the wild-type plants in response to copper-induced oxidative stress. Overall, our findings suggest an important role for m6A in the oxidative stress response of Arabidopsis.

DARPP-32 and t-DARPP in the development of resistance to anti-HER2 agents. Pre-clinical evidence from the STEP study

The therapeutic scenario of Human Epidermal Growth Factor Receptor 2 positive advanced breast cancer (ABC) has been recently enriched by a number of innovative agents, which are reshaping treatment sequence. While randomized trials have documented an advantage in terms of efficacy, for the newly available agents we lack effectiveness and tolerability evidence from the real-world setting. Similarly, the identification of predictive biomarkers might improve clinical decision. We herein describe the outline of a prospective/retrospective study which aims to explore the optimal sequence of treatment in HER2+, pertuzumab pre-treated ABC patients treated in II line with anti-HER2 agents in clinical practice. As part of the pre-clinical tasks envisioned by the STEP study, in vitro cell models of resistance were exploited to investigate molecular features associated with reduced efficacy of HER2 targeting agents at the transcript level. The aggressive behavior of resistant cell populations was measured by growth assessment in mouse models. This approach led to the identification of DARPP-32 and t-DARPP proteins as possible predictive biomarkers of efficacy of anti-HER2 agents. Biomarkers validation and the clinical goals will be reached through patients' inclusion into two independent cohorts, i.e., the prospective and retrospective cohorts, whose setup is currently ongoing.

ZFP750 affects the cutaneous barrier through regulating lipid metabolism

An essential function of the epidermis is to provide a physical barrier that prevents the loss of water. Essential mediators of this barrier function include ceramides, cholesterol, and very long chain fatty acids, and their alteration causes human pathologies, including psoriasis and atopic dermatitis. A frameshift mutation in the human ZNF750 gene, which encodes a zinc finger transcription factor, has been shown to cause a seborrhea-like dermatitis. Here, we show that genetic deletion of the mouse homolog ZFP750 results in loss of epidermal barrier function, which is associated with a substantial reduction of ceramides, nonpolar lipids. The alteration of epidermal lipid homeostasis is directly linked to the transcriptional activity of ZFP750. ZFP750 directly and/or indirectly regulates the expression of crucial enzymes primarily involved in the biosynthesis of ceramides. Overall, our study identifies the transcription factor ZFP750 as a master regulator epidermal homeostasis through lipid biosynthesis and thus contributing to our understanding of the pathogenesis of several human skin diseases.

PARP1 Regulates Circular RNA Biogenesis though Control of Transcriptional Dynamics

Circular RNAs (circRNAs) are a recently discovered class of RNAs derived from protein-coding genes that have important biological and pathological roles. They are formed through backsplicing during co-transcriptional alternative splicing; however, the unified mechanism that accounts for backsplicing decisions remains unclear. Factors that regulate the transcriptional timing and spatial organization of pre-mRNA, including RNAPII kinetics, the availability of splicing factors, and features of gene architecture, have been shown to influence backsplicing decisions. Poly (ADP-ribose) polymerase I (PARP1) regulates alternative splicing through both its presence on chromatin as well as its PARylation activity. However, no studies have investigated PARP1's possible role in regulating circRNA biogenesis. Here, we hypothesized that PARP1's role in splicing extends to circRNA biogenesis. Our results identify many unique circRNAs in PARP1 depletion and PARylation-inhibited conditions compared to the wild type. We found that while all genes producing circRNAs share gene architecture features common to circRNA host genes, genes producing circRNAs in PARP1 knockdown conditions had longer upstream introns than downstream introns, whereas flanking introns in wild type host genes were symmetrical. Interestingly, we found that the behavior of PARP1 in regulating RNAPII pausing is distinct between these two classes of host genes. We conclude that the PARP1 pausing of RNAPII works within the context of gene architecture to regulate transcriptional kinetics, and therefore circRNA biogenesis. Furthermore, this regulation of PARP1 within host genes acts to fine tune their transcriptional output with implications in gene function.

Design of the Building Research in CRC prevention (BRIDGE-CRC) trial: a 6-month, parallel group Mediterranean diet and weight loss randomized controlled lifestyle intervention targeting the bile acid-gut microbiome axis to reduce colorectal cancer risk among African American/Black adults with obesity

BACKGROUND

Among all racial/ethnic groups, people who identify as African American/Blacks have the second highest colorectal cancer (CRC) incidence in the USA. This disparity may exist because African American/Blacks, compared to other racial/ethnic groups, have a higher prevalence of risk factors for CRC, including obesity, low fiber consumption, and higher intakes of fat and animal protein. One unexplored, underlying mechanism of this relationship is the bile acid-gut microbiome axis. High saturated fat, low fiber diets, and obesity lead to increases in tumor promoting secondary bile acids. Diets high in fiber, such as a Mediterranean diet, and intentional weight loss may reduce CRC risk by modulating the bile acid-gut microbiome axis. The purpose of this study is to test the impact of a Mediterranean diet alone, weight loss alone, or both, compared to typical diet controls on the bile acid-gut microbiome axis and CRC risk factors among African American/Blacks with obesity. Because weight loss or a Mediterranean diet alone can reduce CRC risk, we hypothesize that weight loss plus a Mediterranean diet will reduce CRC risk the most.

METHODS

This randomized controlled lifestyle intervention will randomize 192 African American/Blacks with obesity, aged 45-75 years to one of four arms: Mediterranean diet, weight loss, weight loss plus Mediterranean diet, or typical diet controls, for 6 months (48 per arm). Data will be collected at baseline, mid-study, and study end. Primary outcomes include total circulating and fecal bile acids, taurine-conjugated bile acids, and deoxycholic acid. Secondary outcomes include body weight, body composition, dietary change, physical activity, metabolic risk, circulating cytokines, gut microbial community structure and composition, fecal short-chain fatty acids, and expression levels of genes from exfoliated intestinal cells linked to carcinogenesis.

DISCUSSION

This study will be the first randomized controlled trial to examine the effects of a Mediterranean diet, weight loss, or both on bile acid metabolism, the gut microbiome, and intestinal epithelial genes associated with carcinogenesis. This approach to CRC risk reduction may be especially important among African American/Blacks given their higher risk factor profile and increased CRC incidence.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04753359 . Registered on 15 February 2021.

Caspase-8 as a novel mediator linking Src kinase signaling to enhanced glioblastoma malignancy

Caspase-8 is a cysteine protease that plays an essential role in apoptosis. Consistently with its canonical proapoptotic function, cancer cells may genetically or epigenetically downregulate its expression. Unexpectedly, Caspase-8 is often retained in cancer, suggesting the presence of alternative mechanisms that may be exploited by cancer cells to their own benefit. In this regard, we reported that Src tyrosine kinase, which is aberrantly activated in many tumors, promotes Caspase-8 phosphorylation on Tyrosine 380 (Y380) preventing its full activation. Here, we investigated the significance of Caspase-8 expression and of its phosphorylation on Y380 in glioblastoma, a brain tumor where both Caspase-8 expression and Src activity are often aberrantly upregulated. Transcriptomic analyses identified inflammatory response as a major target of Caspase-8, and in particular, NFκB signaling as one of the most affected pathways. More importantly, we could show that Src-dependent phosphorylation of Caspase-8 on Y380 drives the assembly of a multiprotein complex that triggers NFκB activation, thereby inducing the expression of inflammatory and pro-angiogenic factors. Remarkably, phosphorylation on Y380 sustains neoangiogenesis and resistance to radiotherapy. In summary, our work identifies a novel interplay between Src kinase and Caspase-8 that allows cancer cells to hijack Caspase-8 to sustain tumor growth.

aTAP: automated transcriptome analysis platform for processing RNA-seq data by de novo assembly

RNA-seq is a sequencing technique that uses next-generation sequencing (NGS) to explore and study the entire transcriptome of a biological sample. NGS-based analyses are mostly performed via command-line interfaces, which is an obstacle for molecular biologists and researchers. Therefore, the higher throughputs from NGS can only be accessed with the help of bioinformatics and computer science expertise. As the cost of sequencing is continuously falling, the use of RNA-seq seems certain to increase. To minimize the problems encountered by biologists and researchers in RNA-seq data analysis, we propose an automated platform with a web application that integrates various bioinformatics pipelines. The platform is intended to enable academic users to more easily analyze transcriptome datasets. Our automated Transcriptome Analysis Platform (aTAP) offers comprehensive bioinformatics workflows, including quality control of raw reads, trimming of low-quality reads, de novo transcriptome assembly, transcript expression quantification, differential expression analysis, and transcript annotation. aTAP has a user-friendly graphical interface, allowing researchers to interact with and visualize results in the web browser. This project offers an alternative way to analyze transcriptome data, by integrating efficient and well-known tools, that is simpler and more accessible to research communities. aTAP is freely available to academic users at https://atap.psu.ac.th/.

SEAseq: a portable and cloud-based chromatin occupancy analysis suite

Background

Genome-wide protein-DNA binding is popularly assessed using specific antibody pulldown in Chromatin Immunoprecipitation Sequencing (ChIP-Seq) or Cleavage Under Targets and Release Using Nuclease (CUT&RUN) sequencing experiments. These technologies generate high-throughput sequencing data that necessitate the use of multiple sophisticated, computationally intensive genomic tools to make discoveries, but these genomic tools often have a high barrier to use because of computational resource constraints.

Results

We present a comprehensive, infrastructure-independent, computational pipeline called SEAseq, which leverages field-standard, open-source tools for processing and analyzing ChIP-Seq/CUT&RUN data. SEAseq performs extensive analyses from the raw output of the experiment, including alignment, peak calling, motif analysis, promoters and metagene coverage profiling, peak annotation distribution, clustered/stitched peaks (e.g. super-enhancer) identification, and multiple relevant quality assessment metrics, as well as automatic interfacing with data in GEO/SRA. SEAseq enables rapid and cost-effective resource for analysis of both new and publicly available datasets as demonstrated in our comparative case studies.

Conclusions

The easy-to-use and versatile design of SEAseq makes it a reliable and efficient resource for ensuring high quality analysis. Its cloud implementation enables a broad suite of analyses in environments with constrained computational resources. SEAseq is platform-independent and is aimed to be usable by everyone with or without programming skills. It is available on the cloud at https://platform.stjude.cloud/workflows/seaseq and can be locally installed from the repository at https://github.com/stjude/seaseq.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04588-z.

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."

Transcriptional regulation and functional analysis of Nicotiana tabacum under salt and ABA stress

Soil salinization is an important factor that restricts crop quality and yield and causes an enormous toll to human beings. Salt stress and abscisic acid (ABA) stress will occur in the process of soil salinization. In this study, transcriptome sequencing of tobacco leaves under salt and ABA stress in order to further study the resistance mechanism of tobacco. Compared with controlled groups, 1654 and 3306 DEGs were obtained in salt and ABA stress, respectively. The genes function enrichment analysis showed that the up-regulated genes in salt stress were mainly concentrated in transcription factor WRKY family and PAR1 resistance gene family, while the up-regulated genes were mainly concentrated on bHLH transcription factor, Kunitz-type protease inhibitor, dehydrin (Xero1) gene and CAT (Catalase) family protein genes in ABA stress. Tobacco MAPK cascade triggered stress response through up-regulation of gene expression in signal transduction. The expression products of these up-regulated genes can improve the abiotic stress resistance of plants. These results have an important implication for further understanding the mechanism of salinity tolerance in plants.

Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine

The cancer genome is characterized by extensive variability, in the form of Single Nucleotide Polymorphisms (SNPs) or structural variations such as Copy Number Alterations (CNAs) across wider genomic areas. At the molecular level, most SNPs and/or CNAs reside in non-coding sequences, ultimately affecting the regulation of oncogenes and/or tumor-suppressors in a cancer-specific manner. Notably, inherited non-coding variants can predispose for cancer decades prior to disease onset. Furthermore, accumulation of additional non-coding driver mutations during progression of the disease, gives rise to genomic instability, acting as the driving force of neoplastic development and malignant evolution. Therefore, detection and characterization of such mutations can improve risk assessment for healthy carriers and expand the diagnostic and therapeutic toolbox for the patient. This review focuses on functional variants that reside in transcribed or not transcribed non-coding regions of the cancer genome and presents a collection of appropriate state-of-the-art methodologies to study them.

Cloud Computing Enabled Big Multi-Omics Data Analytics

High-throughput experiments enable researchers to explore complex multifactorial diseases through large-scale analysis of omics data. Challenges for such high-dimensional data sets include storage, analyses, and sharing. Recent innovations in computational technologies and approaches, especially in cloud computing, offer a promising, low-cost, and highly flexible solution in the bioinformatics domain. Cloud computing is rapidly proving increasingly useful in molecular modeling, omics data analytics (eg, RNA sequencing, metabolomics, or proteomics data sets), and for the integration, analysis, and interpretation of phenotypic data. We review the adoption of advanced cloud-based and big data technologies for processing and analyzing omics data and provide insights into state-of-the-art cloud bioinformatics applications.

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.

RAP: A Web Tool for RNA-Seq Data Analysis

Since 1950 main studies of RNA regarded its role in the protein synthesis. Later insights showed that only a small portion of RNA codes for proteins where the rest could have different functional roles. With the advent of Next Generation Sequencing (NGS) and in particular with RNA-seq technology the cost of sequencing production dropped down. Among the NGS application areas, the transcriptome analysis, that is, the analysis of transcripts in a cell, their quantification for a specific developmental stage or treatment condition, became more and more adopted in the laboratories. As a consequence in the last decade new insights were gained in the understanding of both transcriptome complexity and involvement of RNA molecules in cellular processes. For what concerns computational advances, bioinformatics research developed new methods for analyzing RNA-seq data. The comparison among transcriptome profiles from several samples is often a difficult task for nonexpert programmers. Here, in this chapter, we introduce RAP (RNA-Seq Analysis Pipeline), a completely automated web tool for transcriptome analysis. It is a user-friendly web tool implementing a detailed transcriptome workflow to detect differential expressed genes and transcript, identify spliced junctions and constitutive or alternative polyadenylation sites and predict gene fusion events. Through the web interface the researchers can get all this information without any knowledge of the underlying High Performance Computing infrastructure.

Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists

Recent advances in next-generation sequencing technologies have paved the path for a considerable amount of sequencing data at a relatively low cost. This has revolutionized the genomics and transcriptomics studies. However, different challenges are now created in handling such data with available bioinformatics platforms both in assembly and downstream analysis performed in order to infer correct biological meaning. Though there are a handful of commercial software and tools for some of the procedures, cost of such tools has made them prohibitive for most research laboratories. While individual open-source or free software tools are available for most of the bioinformatics applications, those components usually operate standalone and are not combined for a user-friendly workflow. Therefore, beginners in bioinformatics might find analysis procedures starting from raw sequence data too complicated and time-consuming with the associated learning-curve. Here, we outline a procedure for de novo transcriptome assembly and Simple Sequence Repeats (SSR) primer design solely based on tools that are available online for free use. For validation of the developed workflow, we used Illumina HiSeq reads of different tissue samples of Santalum album (sandalwood), generated from a previous transcriptomics project. A portion of the designed primers were tested in the lab with relevant samples and all of them successfully amplified the targeted regions. The presented bioinformatics workflow can accurately assemble quality transcriptomes and develop gene specific SSRs. Beginner biologists and researchers in bioinformatics can easily utilize this workflow for research purposes.

Differential gene expression in skin RNA of horses affected with degenerative suspensory ligament desmitis

BACKGROUND

Equine degenerative suspensory ligament desmitis (DSLD) is a systemic connective tissue disorder first identified in Peruvian Paso horses but afflicting other horse breeds as well. Inappropriate accumulation of proteoglycans in connective tissues, most prominently in tendons and ligaments, leads to progressive and debilitating lameness and pain. It is largely unknown what drives the overproduction of proteoglycans, but our previous studies suggest involvement of bone morphogenetic protein 2 (BMP2), a member of the transforming growth factor-β (TGFβ) family, impacting synthesis of proteoglycans. To identify potential players in pathogenesis of DSLD a new approach utilizing next generation sequencing was undertaken.

METHODS

Next generation sequencing was performed using RNA extracted from skin biopsies of six control Peruvian Pasos and six horses with DSLD (4 Peruvian Pasos and 2 warmbloods). The CuffDiff result sets were validated with algorithms used to run them. This was based on the determined false discovery rates derived from the P values adjusted for multiple testing for any given result.

RESULTS

Bioinformatics analysis of transcriptomes revealed differential expression of over 1500 genes, including increased expression of genes for several growth factors (most prominently BMP2, FGF5, CTGF, many members of the EGF family), and mediators of signaling (Fos, Myc, MAPK system), and keratins. Two genes encoding for enzymes involved in synthesis of hyaluronan were also overexpressed. Gene expression was decreased for protein cores of many proteoglycans, several growth factors, most collagens, and many peptides with immune function.

CONCLUSIONS

The overexpression of BMP2 correlates well with our previous data. However, the decrease in expression of numerous proteoglycans was unexpected. A mutation in a gene of a less characterized proteoglycan and/or glycosyltransferase with subsequent increased production of hyaluronan and/or a proteoglycan(s) undetected in our study could account for the systemic proteoglycan deposition. Decreased collagen gene expression indicates abnormal connective tissue metabolism. The increased expression of keratin genes and FGF5 supports reports of skin abnormalities in DSLD. Underexpression of immune function genes corresponds with lack of inflammation in DSLD tissues. Finally, though the proteoglycan and/or glycosaminoglycan abundant in DSLD has not been identified, we validated our previous data, including overexpression of BMP2, and systemic nature of DSLD due to disturbed metabolism of the extracellular matrix.

ELIXIR-IT HPC@CINECA: high performance computing resources for the bioinformatics community

BACKGROUND

The advent of Next Generation Sequencing (NGS) technologies and the concomitant reduction in sequencing costs allows unprecedented high throughput profiling of biological systems in a cost-efficient manner. Modern biological experiments are increasingly becoming both data and computationally intensive and the wealth of publicly available biological data is introducing bioinformatics into the "Big Data" era. For these reasons, the effective application of High Performance Computing (HPC) architectures is becoming progressively more recognized also by bioinformaticians. Here we describe HPC resources provisioning pilot programs dedicated to bioinformaticians, run by the Italian Node of ELIXIR (ELIXIR-IT) in collaboration with CINECA, the main Italian supercomputing center.

RESULTS

Starting from April 2016, CINECA and ELIXIR-IT launched the pilot Call "ELIXIR-IT HPC@CINECA", offering streamlined access to HPC resources for bioinformatics. Resources are made available either through web front-ends to dedicated workflows developed at CINECA or by providing direct access to the High Performance Computing systems through a standard command-line interface tailored for bioinformatics data analysis. This allows to offer to the biomedical research community a production scale environment, continuously updated with the latest available versions of publicly available reference datasets and bioinformatic tools. Currently, 63 research projects have gained access to the HPC@CINECA program, for a total handout of ~ 8 Millions of CPU/hours and, for data storage, ~ 100 TB of permanent and ~ 300 TB of temporary space.

CONCLUSIONS

Three years after the beginning of the ELIXIR-IT HPC@CINECA program, we can appreciate its impact over the Italian bioinformatics community and draw some considerations. Several Italian researchers who applied to the program have gained access to one of the top-ranking public scientific supercomputing facilities in Europe. Those investigators had the opportunity to sensibly reduce computational turnaround times in their research projects and to process massive amounts of data, pursuing research approaches that would have been otherwise difficult or impossible to undertake. Moreover, by taking advantage of the wealth of documentation and training material provided by CINECA, participants had the opportunity to improve their skills in the usage of HPC systems and be better positioned to apply to similar EU programs of greater scale, such as PRACE. To illustrate the effective usage and impact of the resources awarded by the program - in different research applications - we report five successful use cases, which have already published their findings in peer-reviewed journals.

CSI NGS Portal: An Online Platform for Automated NGS Data Analysis and Sharing

Next-generation sequencing (NGS) has been a widely-used technology in biomedical research for understanding the role of molecular genetics of cells in health and disease. A variety of computational tools have been developed to analyse the vastly growing NGS data, which often require bioinformatics skills, tedious work and a significant amount of time. To facilitate data processing steps minding the gap between biologists and bioinformaticians, we developed CSI NGS Portal, an online platform which gathers established bioinformatics pipelines to provide fully automated NGS data analysis and sharing in a user-friendly website. The portal currently provides 16 standard pipelines for analysing data from DNA, RNA, smallRNA, ChIP, RIP, 4C, SHAPE, circRNA, eCLIP, Bisulfite and scRNA sequencing, and is flexible to expand with new pipelines. The users can upload raw data in FASTQ format and submit jobs in a few clicks, and the results will be self-accessible via the portal to view/download/share in real-time. The output can be readily used as the final report or as input for other tools depending on the pipeline. Overall, CSI NGS Portal helps researchers rapidly analyse their NGS data and share results with colleagues without the aid of a bioinformatician. The portal is freely available at: https://csibioinfo.nus.edu.sg/csingsportal.

Developing a Reproducible Microbiome Data Analysis Pipeline Using the Amazon Web Services Cloud for a Cancer Research Group: Proof-of-Concept Study

BACKGROUND

Cloud computing for microbiome data sets can significantly increase working efficiencies and expedite the translation of research findings into clinical practice. The Amazon Web Services (AWS) cloud provides an invaluable option for microbiome data storage, computation, and analysis.

OBJECTIVE

The goals of this study were to develop a microbiome data analysis pipeline by using AWS cloud and to conduct a proof-of-concept test for microbiome data storage, processing, and analysis.

METHODS

A multidisciplinary team was formed to develop and test a reproducible microbiome data analysis pipeline with multiple AWS cloud services that could be used for storage, computation, and data analysis. The microbiome data analysis pipeline developed in AWS was tested by using two data sets: 19 vaginal microbiome samples and 50 gut microbiome samples.

RESULTS

Using AWS features, we developed a microbiome data analysis pipeline that included Amazon Simple Storage Service for microbiome sequence storage, Linux Elastic Compute Cloud (EC2) instances (ie, servers) for data computation and analysis, and security keys to create and manage the use of encryption for the pipeline. Bioinformatics and statistical tools (ie, Quantitative Insights Into Microbial Ecology 2 and RStudio) were installed within the Linux EC2 instances to run microbiome statistical analysis. The microbiome data analysis pipeline was performed through command-line interfaces within the Linux operating system or in the Mac operating system. Using this new pipeline, we were able to successfully process and analyze 50 gut microbiome samples within 4 hours at a very low cost (a c4.4xlarge EC2 instance costs $0.80 per hour). Gut microbiome findings regarding diversity, taxonomy, and abundance analyses were easily shared within our research team.

CONCLUSIONS

Building a microbiome data analysis pipeline with AWS cloud is feasible. This pipeline is highly reliable, computationally powerful, and cost effective. Our AWS-based microbiome analysis pipeline provides an efficient tool to conduct microbiome data analysis.

Genome-wide mapping of 8-oxo-7,8-dihydro-2'-deoxyguanosine reveals accumulation of oxidatively-generated damage at DNA replication origins within transcribed long genes of mammalian cells

8-Oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG) is one of the major DNA modifications and a potent pre-mutagenic lesion prone to mispair with 2′-deoxyadenosine (dA). Several thousand residues of 8-oxodG are constitutively generated in the genome of mammalian cells, but their genomic distribution has not yet been fully characterized. Here, by using OxiDIP-Seq, a highly sensitive methodology that uses immuno-precipitation with efficient anti–8-oxodG antibodies combined with high-throughput sequencing, we report the genome-wide distribution of 8-oxodG in human non-tumorigenic epithelial breast cells (MCF10A), and mouse embryonic fibroblasts (MEFs). OxiDIP-Seq revealed sites of 8-oxodG accumulation overlapping with γH2AX ChIP-Seq signals within the gene body of transcribed long genes, particularly at the DNA replication origins contained therein. We propose that the presence of persistent single-stranded DNA, as a consequence of transcription-replication clashes at these sites, determines local vulnerability to DNA oxidation and/or its slow repair. This oxidatively-generated damage, likely in combination with other kinds of lesion, might contribute to the formation of DNA double strand breaks and activation of DNA damage response.

Colonic mucosal and exfoliome transcriptomic profiling and fecal microbiome response to a flaxseed lignan extract intervention in humans

BACKGROUND

Microbial metabolism of lignans from high-fiber plant foods produces bioactive enterolignans, such as enterolactone (ENL) and enterodiol (END). Enterolignan exposure influences cellular pathways important to cancer risk and is associated with reduced colon tumorigenesis in animal models and lower colorectal cancer risk in humans.

OBJECTIVES

The aim of this study was to test the effects of a flaxseed lignan supplement (50 mg secoisolariciresinol diglucoside/d) compared with placebo on host gene expression in colon biopsies and exfoliated colonocyte RNA in feces and fecal microbial community composition, and to compare responses in relation to ENL excretion.

METHODS

We conducted a 2-period randomized, crossover intervention in 42 healthy men and women (20-45 y). We used RNA-seq to measure differentially expressed (DE) genes in colonic mucosa and fecal exfoliated cells through the use of edgeR and functional analysis with Ingenuity Pathway Analysis. We used 16S ribosomal RNA gene (V1-V3) analysis to characterize the fecal microbiome, and measured END and ENL in 24-h urine samples by gas chromatography-mass spectrometry.

RESULTS

We detected 32 DE genes (false discovery rate <0.05) in the exfoliome, but none in the mucosal biopsies, in response to 60 d of lignan supplement compared with placebo. Statistically significant associations were detected between ENL excretion and fecal microbiome measured at baseline and at the end of the intervention periods. Further, we detected DE genes in colonic mucosa and exfoliome between low- and high-ENL excreters. Analysis of biopsy samples indicated that several anti-inflammatory upstream regulators, including transforming growth factor β and interleukin 10 receptor, were suppressed in low-ENL excreters. Complementary analyses in exfoliated cells also suggested that low-ENL excreters may be predisposed to proinflammatory cellular events due to upregulation of nuclear transcription factor κB and NOS2, and an inhibition of the peroxisome proliferator-activated receptor γ network.

CONCLUSIONS

These results suggest that ENL or other activities of the associated gut microbial consortia may modulate response to a dietary lignan intervention. This has important implications for dietary recommendations and chemoprevention strategies. This study was registered at clinicaltrials.gov as NCT01619020.

Genetic association and functional characterization of MCPH1 gene variation in bipolar disorder and schizophrenia

A rare microcephalin 1 gene (MCPH1) variant rs61749465A>G (p.Asp61Gly) with prior evidence for association with schizophrenia (p = 3.78 × 10-7 ) was tested for association in 2,300 bipolar disorder (BPD) participants, 1,930 SCZ participants and 1,820 normal comparison subjects. We report evidence for association of rs61749465A>G with BPD (p = 0.0009). rs61749465 is located in the N-terminal of the BRCT1 domain of MCPH1. Bioinformatic analysis predicted the Asp61Gly substitution to be damaging to MCPH1 function. A second MCPH1 BRCT1 domain variant (rs199422124C>G; p.Thr27Arg), reported to cause autosomal recessive microcephaly, was not detected in the participants tested here. We sought to characterize the functional effects of these variants on MCPH1 function. Cell count assays indicated that rs199422124 allele G had a greater impact on cell survival compared to the G allele of rs61749465. Gene expression analysis combined with gene network and pathway analysis indicated that rs61749465 allele G may impact protein translation and cell cycle control. The evidence for association between rs61749465A>G and psychosis in both BPD and SCZ warrants further replication. Likewise, the data from the functional analyses point to molecular mechanisms that may underlie the proposed MCPH1 mediated risk of psychosis and pathogenesis in autosomal recessive microcephaly require additional experimental validation.

Multiomics Assessment of Gene Expression in a Clinical Strain of CTX-M-15-Producing ST131 Escherichia coli

Extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli strain C999 was isolated of a Spanish patient with urinary tract infection. Previous genotyping indicated that this strain presented a multidrug-resistance phenotype and carried beta-lactamase genes encoding CTX-M-15, TEM-1, and OXA-1 enzymes. The whole-cell proteome, and the membrane, cytoplasmic, periplasmic and extracellular sub-proteomes of C999 were obtained in this work by two-dimensional gel electrophoresis (2DE) followed by fingerprint sequencing through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS). A total of 602 proteins were identified in the different cell fractions, several of which are related to stress response systems, cellular responses, and antibiotic and drug responses, consistent with the multidrug-resistance phenotype. In parallel, whole genome sequencing (WGS) and RNA sequencing (RNA-Seq) was done to identify and quantify the genes present and expressing. The in silico prediction following WGS confirmed our strain as being serotype O25:H4 and sequence type ST131. The presence of proteins related to antibiotic resistance and virulence in an O25:H4-ST131 E. coli clone are serious indicators of the continued threat of antibiotic resistance spread amongst healthcare institutions. On a positive note, a multiomics approach can facilitate surveillance and more detailed characterization of virulent bacterial clones from hospital environments.

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/.

iSeq: Web-Based RNA-seq Data Analysis and Visualization

Transcriptome sequencing (RNA-seq) is becoming a standard experimental methodology for genome-wide characterization and quantification of transcripts at single base-pair resolution. However, downstream analysis of massive amount of sequencing data can be prohibitively technical for wet-lab researchers. A functionally integrated and user-friendly platform is required to meet this demand. Here, we present iSeq, an R-based Web server, for RNA-seq data analysis and visualization. iSeq is a streamlined Web-based R application under the Shiny framework, featuring a simple user interface and multiple data analysis modules. Users without programming and statistical skills can analyze their RNA-seq data and construct publication-level graphs through a standardized yet customizable analytical pipeline. iSeq is accessible via Web browsers on any operating system at http://iseq.cbi.pku.edu.cn .

MGL_3741 gene contributes to pathogenicity of Malassezia globosa in pityriasis versicolor

Dihydroxyacid dehydratase (DHAD) is a key enzyme in biosynthetic pathway of isoleucine and valine. This pathway is absent in human but exists in various organisms such as fungi. Using RNA-seq analysis in this study, we identified MGL_3741gene which encodes DHAD protein in Malassezia globosa (M. globosa). Furthermore, we found that mentioned gene is homologous to the Ustilago maydis, Saccharomyces cerevisiae, Aspergillus flavus, and Aspergillus fumigatus ILV3P. For understanding the probable role of this gene in pathogenicity of M. globosa, we applied Real-time PCR to investigate the differentially expressed of the MGL_3741 gene in healthy and pathogenic states. Our results indicate a significant difference between two mentioned stats. These results revealed that ILV3-like gene in M. globosa can be related to the pathogenicity of this yeast.

Deficiency in the nuclear long noncoding RNA Charme causes myogenic defects and heart remodeling in mice

Myogenesis is a highly regulated process that involves the conversion of progenitor cells into multinucleated myofibers. Besides proteins and miRNAs, long noncoding RNAs (lncRNAs) have been shown to participate in myogenic regulatory circuitries. Here, we characterize a murine chromatin‐associated muscle‐specific lncRNA, Charme, which contributes to the robustness of the myogenic program in vitro and in vivo. In myocytes, Charme depletion triggers the disassembly of a specific chromosomal domain and the downregulation of myogenic genes contained therein. Notably, several Charme‐sensitive genes are associated with human cardiomyopathies and Charme depletion in mice results in a peculiar cardiac remodeling phenotype with changes in size, structure, and shape of the heart. Moreover, the existence of an orthologous transcript in human, regulating the same subset of target genes, suggests an important and evolutionarily conserved function for Charme. Altogether, these data describe a new example of a chromatin‐associated lncRNA regulating the robustness of skeletal and cardiac myogenesis.

Definition of the R-superfamily of conotoxins: Structural convergence of helix-loop-helix peptidic scaffolds

The F14 conotoxins define a four-cysteine, three-loop conotoxin scaffold that produce tightly folded structures held together by two disulfide bonds with a CCCC arrangement (conotoxin framework 14). Here we describe the precursors of the F14 conotoxins from the venom of Conus anabathrum and Conus villepinii. Using transcriptomic and cDNA cloning analysis, the full-length of the precursors of flf14a and flf14b from the transcriptome of C. anabathrum revealed a unique signal sequence that defines the new conotoxin R-superfamily. Using the signal sequence as a primer, we cloned seven additional previously undescribed toxins of the R-superfamily from C. villepinii. The propeptide regions of the R-conotoxins are unusually long and with prevalent proline residues in repeating pentads which qualifies them as Pro-rich motifs (PRMs), which can be critical for protein-protein interactions or they can be cleaved to release short linear peptides that may be part of the envenomation mélange. Additionally, we determined the three-dimensional structure of vil14a by solution ¹H-NMR and found that the structure of this conotoxin displays a cysteine-stabilized α-helix-loop-helix (C_s α/α) fold. The structure is well-defined over the helical regions (backbone RMSD for residues 2-13 and 17-26 is 0.63 ± 0.14 Å), with conformational flexibility in the triple Gly region of the second loop as well as the N- and C- termini. Structurally, the F14 conotoxins overlap with the C_s α/α scorpion toxins and other peptidic natural products, and in spite of their different exogenomic origins, there is convergence into this scaffold from several classes of living organisms that express these peptides.

Computational systems biology approaches for Parkinson's disease

Parkinson's disease (PD) is a prime example of a complex and heterogeneous disorder, characterized by multifaceted and varied motor- and non-motor symptoms and different possible interplays of genetic and environmental risk factors. While investigations of individual PD-causing mutations and risk factors in isolation are providing important insights to improve our understanding of the molecular mechanisms behind PD, there is a growing consensus that a more complete understanding of these mechanisms will require an integrative modeling of multifactorial disease-associated perturbations in molecular networks. Identifying and interpreting the combinatorial effects of multiple PD-associated molecular changes may pave the way towards an earlier and reliable diagnosis and more effective therapeutic interventions. This review provides an overview of computational systems biology approaches developed in recent years to study multifactorial molecular alterations in complex disorders, with a focus on PD research applications. Strengths and weaknesses of different cellular pathway and network analyses, and multivariate machine learning techniques for investigating PD-related omics data are discussed, and strategies proposed to exploit the synergies of multiple biological knowledge and data sources. A final outlook provides an overview of specific challenges and possible next steps for translating systems biology findings in PD to new omics-based diagnostic tools and targeted, drug-based therapeutic approaches.

Deptor transcriptionally regulates endoplasmic reticulum homeostasis in multiple myeloma cells

Multiple myeloma (MM) is a malignant disorder of plasma cells characterized by active production and secretion of monoclonal immunoglobulins (IgG), thus rendering cells prone to endoplasmic reticulum (ER) stress. For this reason, MM cell survival requires to maintain ER homeostasis at basal levels. Deptor is an mTOR binding protein, belonging to the mTORC1 and mTORC2 complexes. It was reported that Deptor is overexpressed in MM cells where it inhibits mTOR kinase activity and promotes cell survival by activating Akt signaling. Here we identify Deptor as a nuclear protein, able to bind DNA and regulate transcription in MM cells. In particular, we found that Deptor plays an important role in the maintenance of the ER network, sustaining the expression of several genes involved in this pathway. In agreement with this, Deptor depletion induces ER stress and synergizes the effect of the proteasome inhibitor bortezomib (Bz) in MM cells. These findings provide important new insights in the ER stress control in MM cells.

Structural plasticity of mini-M conotoxins - expression of all mini-M subtypes by Conus regius

The mini-M conotoxins are peptidic scaffolds found in the venom of cones snails. These scaffolds are tightly folded structures held together by three disulfide bonds with a CC-C-C-CC arrangement (conotoxin framework III) and belong to the M Superfamily of conotoxins. Here, we describe mini-M conotoxins from the venom of Conus regius, a Western Atlantic worm-hunting cone snail species using transcriptomic and peptidomic analyses. These C. regius conotoxins belong to three different subtypes: M1, M2, and M3. The subtypes show little sequence homology, and their loop sizes (intercysteine amino acid chains) vary significantly. The mini-Ms isolated from dissected venom contains preferentially hydroxylated proline residues, thus augmenting the structural reach of this conotoxin class. Using 2D-NMR methods, we have determined the 3D structure of reg3b, an M2 subtype conotoxin, which shows a constrained multi-turn scaffold. The structural diversity found within mini-M conotoxin scaffolds of C. regius is indicative of structural hypervariability of the conotoxin M superfamily that is not seen in other superfamilies. These stable minimalistic scaffolds may be investigated for the development of engineered peptides for therapeutic applications.

DATABASES

Sequences are available in GenBank under accession numbers MF588935-MF588952. Structural data are available in the RCSB protein database under the accession code 6BX9.

Che-1 is targeted by c-Myc to sustain proliferation in pre-B-cell acute lymphoblastic leukemia

Despite progress in treating B-cell precursor acute lymphoblastic leukemia (BCP-ALL), disease recurrence remains the main cause of treatment failure. New strategies to improve therapeutic outcomes are needed, particularly in high-risk relapsed patients. Che-1/AATF (Che-1) is an RNA polymerase II-binding protein involved in proliferation and tumor survival, but its role in hematological malignancies has not been clarified. Here, we show that Che-1 is overexpressed in pediatric BCP-ALL during disease onset and at relapse, and that its depletion inhibits the proliferation of BCP-ALL cells. Furthermore, we report that c-Myc regulates Che-1 expression by direct binding to its promoter and describe a strict correlation between Che-1 expression and c-Myc expression. RNA-seq analyses upon Che-1 or c-Myc depletion reveal a strong overlap of the respective controlled pathways. Genomewide ChIP-seq experiments suggest that Che-1 acts as a downstream effector of c-Myc. These results identify the pivotal role of Che-1 in the control of BCP-ALL proliferation and present the protein as a possible therapeutic target in children with relapsed BCP-ALL.

Multitargeting activity of miR-24 inhibits long-term melatonin anticancer effects

We have previously shown that melatonin exerts tumor suppressor activities by inducing the p38-p53 axis. This occurred within a few hours while no data are available on how melatonin pathway can be sustained on the long term. Here we show that miR-24, which has been demonstrated to target genes involved in the DNA repair process, targets p38, p53, PML and H2AX simultaneously. We show that long-term treatment with melatonin can decrease miR-24 levels post-transcriptionally, which pairs with a long-wave regulation of genes involved in cell proliferation, DNA damage, RNA metabolism and cell shape and transformation. Moreover, we show that melatonin can inhibit cell proliferation and migration, at least in part, by downregulating miR-24. Furthermore, we propose the involvement of hnRNP A1, which is downregulated by melatonin and involved in miRNA processing, in the regulation of miR-24 levels by melatonin. We conclude showing that miR-24 is upregulated in colon, breast and head and neck datasets and its levels negatively correlate with overall survival.

Candidate genes and pathways downstream of PAX8 involved in ovarian high-grade serous carcinoma

Understanding the biology and molecular pathogenesis of ovarian epithelial cancer (EOC) is key to developing improved diagnostic and prognostic indicators and effective therapies. Although research has traditionally focused on the hypothesis that high-grade serous carcinoma (HGSC) arises from the ovarian surface epithelium (OSE), recent studies suggest that additional sites of origin exist and a substantial proportion of cases may arise from precursor lesions located in the Fallopian tubal epithelium (FTE). In FTE cells, the transcription factor PAX8 is a marker of the secretory cell lineage and its expression is retained in 96% of EOC. We have recently reported that PAX8 is involved in the tumorigenic phenotype of ovarian cancer cells. In this study, to uncover genes and pathways downstream of PAX8 involved in ovarian carcinoma we have determined the molecular profiles of ovarian cancer cells and in parallel of Fallopian tube epithelial cells by means of a silencing approach followed by an RNA-seq analysis. Interestingly, we highlighted the involvement of pathways like WNT signaling, epithelial-mesenchymal transition, p53 and apoptosis. We believe that our analysis has led to the identification of candidate genes and pathways regulated by PAX8 that could be additional targets for the therapy of ovarian carcinoma.

Novel SEC61G-EGFR Fusion Gene in Pediatric Ependymomas Discovered by Clonal Expansion of Stem Cells in Absence of Exogenous Mitogens

The basis for molecular and cellular heterogeneity in ependymomas of the central nervous system is not understood. This study suggests a basis for this phenomenon in the selection for mitogen-independent (MI) stem-like cells with impaired proliferation but increased intracranial tumorigenicity. MI ependymoma cell lines created by selection for EGF/FGF2-independent proliferation exhibited constitutive activation of EGFR, AKT, and STAT3 and sensitization to the antiproliferative effects of EGFR tyrosine kinase inhibitors (TKI). One highly tumorigenic MI line harbored membrane-bound, constitutively active, truncated EGFR. Two EGFR mutants (ΔN566 and ΔN599) were identified as products of intrachromosomal rearrangements fusing the 3' coding portion of the EGFR gene to the 5'-UTR of the SEC61G, yielding products lacking the entire extracellular ligand-binding domain of the receptor while retaining the transmembrane and tyrosine kinase domains. EGFR TKI efficiently targeted ΔN566/ΔN599-mutant-mediated signaling and prolonged the survival of mice bearing intracranial xenografts of MI cells harboring these mutations. RT-PCR sequencing of 16 childhood ependymoma samples identified SEC61G-EGFR chimeric mRNAs in one infratentorial ependymoma WHO III, arguing that this fusion occurs in a small proportion of these tumors. Our findings demonstrate how in vitro culture selections applied to genetically heterogeneous tumors can help identify focal mutations that are potentially pharmaceutically actionable in rare cancers. Cancer Res; 77(21); 5860-72. ©2017 AACR.

ExpressionDB: An open source platform for distributing genome-scale datasets

RNA-sequencing (RNA-seq) and microarrays are methods for measuring gene expression across the entire transcriptome. Recent advances have made these techniques practical and affordable for essentially any laboratory with experience in molecular biology. A variety of computational methods have been developed to decrease the amount of bioinformatics expertise necessary to analyze these data. Nevertheless, many barriers persist which discourage new labs from using functional genomics approaches. Since high-quality gene expression studies have enduring value as resources to the entire research community, it is of particular importance that small labs have the capacity to share their analyzed datasets with the research community. Here we introduce ExpressionDB, an open source platform for visualizing RNA-seq and microarray data accommodating virtually any number of different samples. ExpressionDB is based on Shiny, a customizable web application which allows data sharing locally and online with customizable code written in R. ExpressionDB allows intuitive searches based on gene symbols, descriptions, or gene ontology terms, and it includes tools for dynamically filtering results based on expression level, fold change, and false-discovery rates. Built-in visualization tools include heatmaps, volcano plots, and principal component analysis, ensuring streamlined and consistent visualization to all users. All of the scripts for building an ExpressionDB with user-supplied data are freely available on GitHub, and the Creative Commons license allows fully open customization by end-users. We estimate that a demo database can be created in under one hour with minimal programming experience, and that a new database with user-supplied expression data can be completed and online in less than one day.

Human iPSC Glial Mouse Chimeras Reveal Glial Contributions to Schizophrenia

In this study, we investigated whether intrinsic glial dysfunction contributes to the pathogenesis of schizophrenia (SCZ). Our approach was to establish humanized glial chimeric mice using glial progenitor cells (GPCs) produced from induced pluripotent stem cells derived from patients with childhood-onset SCZ. After neonatal implantation into myelin-deficient shiverer mice, SCZ GPCs showed premature migration into the cortex, leading to reduced white matter expansion and hypomyelination relative to controls. The SCZ glial chimeras also showed delayed astrocytic differentiation and abnormal astrocytic morphologies. When established in myelin wild-type hosts, SCZ glial mice showed reduced prepulse inhibition and abnormal behavior, including excessive anxiety, antisocial traits, and disturbed sleep. RNA-seq of cultured SCZ human glial progenitor cells (hGPCs) revealed disrupted glial differentiation-associated and synaptic gene expression, indicating that glial pathology was cell autonomous. Our data therefore suggest a causal role for impaired glial maturation in the development of schizophrenia and provide a humanized model for its in vivo assessment.

The RNA workbench: best practices for RNA and high-throughput sequencing bioinformatics in Galaxy

RNA-based regulation has become a major research topic in molecular biology. The analysis of epigenetic and expression data is therefore incomplete if RNA-based regulation is not taken into account. Thus, it is increasingly important but not yet standard to combine RNA-centric data and analysis tools with other types of experimental data such as RNA-seq or ChIP-seq. Here, we present the RNA workbench, a comprehensive set of analysis tools and consolidated workflows that enable the researcher to combine these two worlds. Based on the Galaxy framework the workbench guarantees simple access, easy extension, flexible adaption to personal and security needs, and sophisticated analyses that are independent of command-line knowledge. Currently, it includes more than 50 bioinformatics tools that are dedicated to different research areas of RNA biology including RNA structure analysis, RNA alignment, RNA annotation, RNA-protein interaction, ribosome profiling, RNA-seq analysis and RNA target prediction. The workbench is developed and maintained by experts in RNA bioinformatics and the Galaxy framework. Together with the growing community evolving around this workbench, we are committed to keep the workbench up-to-date for future standards and needs, providing researchers with a reliable and robust framework for RNA data analysis.

AVAILABILITY

The RNA workbench is available at https://github.com/bgruening/galaxy-rna-workbench.

RNA editing signature during myeloid leukemia cell differentiation

Adenosine deaminases acting on RNA (ADARs) are key proteins for hematopoietic stem cell self-renewal and for survival of differentiating progenitor cells. However, their specific role in myeloid cell maturation has been poorly investigated. Here we show that ADAR1 is present at basal level in the primary myeloid leukemia cells obtained from patients at diagnosis as well as in myeloid U-937 and THP1 cell lines and its expression correlates with the editing levels. Upon phorbol-myristate acetate or Vitamin D3/granulocyte macrophage colony-stimulating factor (GM-CSF)-driven differentiation, both ADAR1 and ADAR2 enzymes are upregulated, with a concomitant global increase of A-to-I RNA editing. ADAR1 silencing caused an editing decrease at specific ADAR1 target genes, without, however, interfering with cell differentiation or with ADAR2 activity. Remarkably, ADAR2 is absent in the undifferentiated cell stage, due to its elimination through the ubiquitin-proteasome pathway, being strongly upregulated at the end of the differentiation process. Of note, peripheral blood monocytes display editing events at the selected targets similar to those found in differentiated cell lines. Taken together, the data indicate that ADAR enzymes play important and distinct roles in myeloid cells.

Che-1 sustains hypoxic response of colorectal cancer cells by affecting Hif-1α stabilization

Background

Solid tumours are less oxygenated than normal tissues. Consequently, cancer cells acquire to be adapted to a hypoxic environment. The poor oxygenation of solid tumours is also a major indicator of an adverse cancer prognosis and leads to resistance to conventional anticancer treatments. We previously showed the involvement of Che-1/AATF (Che-1) in cancer cell survival under stress conditions. Herein we hypothesized that Che-1 plays a role in the response of cancer cells to hypoxia.

Methods

The human colon adenocarcinoma HCT116 and HT29 cell lines undepleted or depleted for Che-1 expression by siRNA, were treated under normoxic and hypoxic conditions to perform studies regarding the role of this protein in metabolic adaptation and cell proliferation. Che-1 expression was detected using western blot assays; cell metabolism was assessed by NMR spectroscopy and functional assays. Additional molecular studies were performed by RNA seq, qRT-PCR and ChIP analyses.

Results

Here we report that Che-1 expression is required for the adaptation of cells to hypoxia, playing an important role in metabolic modulation. Indeed, Che-1 depletion impacted on HIF-1α stabilization, thus downregulating the expression of several genes involved in the response to hypoxia and affecting glucose metabolism.

Conclusions

We show that Che-1 a novel player in the regulation of HIF-1α in response to hypoxia. Notably, we found that Che-1 is required for SIAH-2 expression, a member of E3 ubiquitin ligase family that is involved in the degradation of the hydroxylase PHD3, the master regulator of HIF-1α stability.

Electronic supplementary material

The online version of this article (doi:10.1186/s13046-017-0497-1) contains supplementary material, which is available to authorized users.

LocExpress: a web server for efficiently estimating expression of novel transcripts

Background

The temporal and spatial-specific expression pattern of a transcript in multiple tissues and cell types can indicate key clues about its function. While several gene atlas available online as pre-computed databases for known gene models, it’s still challenging to get expression profile for previously uncharacterized (i.e. novel) transcripts efficiently.

Results

Here we developed LocExpress, a web server for efficiently estimating expression of novel transcripts across multiple tissues and cell types in human (20 normal tissues/cells types and 14 cell lines) as well as in mouse (24 normal tissues/cell types and nine cell lines). As a wrapper to RNA-Seq quantification algorithm, LocExpress efficiently reduces the time cost by making abundance estimation calls increasingly within the minimum spanning bundle region of input transcripts. For a given novel gene model, such local context-oriented strategy allows LocExpress to estimate its FPKMs in hundreds of samples within minutes on a standard Linux box, making an online web server possible.

Conclusions

To the best of our knowledge, LocExpress is the only web server to provide nearly real-time expression estimation for novel transcripts in common tissues and cell types. The server is publicly available at http://loc-express.cbi.pku.edu.cn.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3329-3) contains supplementary material, which is available to authorized users.

Resetting cancer stem cell regulatory nodes upon MYC inhibition

MYC deregulation is common in human cancer and has a role in sustaining the aggressive cancer stem cell populations. MYC mediates a broad transcriptional response controlling normal biological programmes, but its activity is not clearly understood. We address MYC function in cancer stem cells through the inducible expression of Omomyc-a MYC-derived polypeptide interfering with MYC activity-taking as model the most lethal brain tumour, glioblastoma. Omomyc bridles the key cancer stemlike cell features and affects the tumour microenvironment, inhibiting angiogenesis. This occurs because Omomyc interferes with proper MYC localization and itself associates with the genome, with a preference for sites occupied by MYC This is accompanied by selective repression of master transcription factors for glioblastoma stemlike cell identity such as OLIG2, POU3F2, SOX2, upregulation of effectors of tumour suppression and differentiation such as ID4, MIAT, PTEN, and modulation of the expression of microRNAs that target molecules implicated in glioblastoma growth and invasion such as EGFR and ZEB1. Data support a novel view of MYC as a network stabilizer that strengthens the regulatory nodes of gene expression networks controlling cell phenotype and highlight Omomyc as model molecule for targeting cancer stem cells.

systemPipeR: NGS workflow and report generation environment

Background

Next-generation sequencing (NGS) has revolutionized how research is carried out in many areas of biology and medicine. However, the analysis of NGS data remains a major obstacle to the efficient utilization of the technology, as it requires complex multi-step processing of big data demanding considerable computational expertise from users. While substantial effort has been invested on the development of software dedicated to the individual analysis steps of NGS experiments, insufficient resources are currently available for integrating the individual software components within the widely used R/Bioconductor environment into automated workflows capable of running the analysis of most types of NGS applications from start-to-finish in a time-efficient and reproducible manner.

Results

To address this need, we have developed the R/Bioconductor package systemPipeR. It is an extensible environment for both building and running end-to-end analysis workflows with automated report generation for a wide range of NGS applications. Its unique features include a uniform workflow interface across different NGS applications, automated report generation, and support for running both R and command-line software on local computers and computer clusters. A flexible sample annotation infrastructure efficiently handles complex sample sets and experimental designs. To simplify the analysis of widely used NGS applications, the package provides pre-configured workflows and reporting templates for RNA-Seq, ChIP-Seq, VAR-Seq and Ribo-Seq. Additional workflow templates will be provided in the future.

Conclusions

systemPipeR accelerates the extraction of reproducible analysis results from NGS experiments. By combining the capabilities of many R/Bioconductor and command-line tools, it makes efficient use of existing software resources without limiting the user to a set of predefined methods or environments. systemPipeR is freely available for all common operating systems from Bioconductor (http://bioconductor.org/packages/devel/systemPipeR).

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1241-0) contains supplementary material, which is available to authorized users.

Comprehensive site-specific whole genome profiling of stromal and epithelial colonic gene signatures in human sigmoid colon and rectal tissue

The strength of associations between various exposures (e.g., diet, tobacco, chemopreventive agents) and colorectal cancer risk may partially depend on the complex interaction between epithelium and stroma across anatomic subsites. Currently, baseline data describing genome-wide coding and long noncoding gene expression profiles in the healthy colon specific to tissue type and location are lacking. Therefore, colonic mucosal biopsies from 10 healthy participants who were enrolled in a clinical study to evaluate effects of lignan supplementation on gut resiliency were used to characterize the site-specific global gene expression signatures associated with stromal vs. epithelial cells in the sigmoid colon and rectum. Using RNA-seq, we demonstrate that tissue type and location patterns of gene expression and upstream regulatory pathways are distinct. For example, consistent with a key role of stroma in the crypt niche, mRNAs associated with immunoregulatory and inflammatory processes (i.e., CXCL14, ANTXR1), smooth muscle contraction (CALD1), proliferation and apoptosis (GLP2R, IGFBP3), and modulation of extracellular matrix (MMP2, COL3A1, MFAP4) were all highly expressed in the stroma. In comparison, HOX genes (HOXA3, HOXD9, HOXD10, HOXD11, and HOXD-AS2, a HOXD cluster antisense RNA 2), and WNT5B expression were also significantly higher in sigmoid colon compared with the rectum. These findings provide strong impetus for considering colorectal tissue subtypes and location in future observational studies and clinical trials designed to evaluate the effects of exposures on colonic health.

miARma-Seq: a comprehensive tool for miRNA, mRNA and circRNA analysis

Large-scale RNAseq has substantially changed the transcriptomics field, as it enables an unprecedented amount of high resolution data to be acquired. However, the analysis of these data still poses a challenge to the research community. Many tools have been developed to overcome this problem, and to facilitate the study of miRNA expression profiles and those of their target genes. While a few of these enable both kinds of analysis to be performed, they also present certain limitations in terms of their requirements and/or the restrictions on data uploading. To avoid these restraints, we have developed a suite that offers the identification of miRNA, mRNA and circRNAs that can be applied to any sequenced organism. Additionally, it enables differential expression, miRNA-mRNA target prediction and/or functional analysis. The miARma-Seq pipeline is presented as a stand-alone tool that is both easy to install and flexible in terms of its use, and that brings together well-established software in a single bundle. Our suite can analyze a large number of samples due to its multithread design. By testing miARma-Seq in validated datasets, we demonstrate here the benefits that can be gained from this tool by making it readily accessible to the research community.

Advancements in RNASeqGUI towards a Reproducible Analysis of RNA-Seq Experiments

We present the advancements and novelties recently introduced in RNASeqGUI, a graphical user interface that helps biologists to handle and analyse large data collected in RNA-Seq experiments. This work focuses on the concept of reproducible research and shows how it has been incorporated in RNASeqGUI to provide reproducible (computational) results. The novel version of RNASeqGUI combines graphical interfaces with tools for reproducible research, such as literate statistical programming, human readable report, parallel executions, caching, and interactive and web-explorable tables of results. These features allow the user to analyse big datasets in a fast, efficient, and reproducible way. Moreover, this paper represents a proof of concept, showing a simple way to develop computational tools for Life Science in the spirit of reproducible research.