CIPHER: a flexible and extensive workflow platform for integrative next-generation sequencing data analysis and genomic regulatory element prediction

Analysis and Interpretation of metagenomics data: an approach

Advances in next-generation sequencing technologies have accelerated the momentum of metagenomic studies, which is increasing yearly. The metagenomics field is one of the versatile applications in microbiology, where any interaction in the environment involving microorganisms can be the topic of study. Due to this versatility, the number of applications of this omics technology reached its horizons. Agriculture is a crucial sector involving crop plants and microorganisms interacting together. Hence, studying these interactions through the lenses of metagenomics would completely disclose a new meaning to crop health and development. The rhizosphere is an essential reservoir of the microbial community for agricultural soil. Hence, we focus on the R&D of metagenomic studies on the rhizosphere of crops such as rice, wheat, legumes, chickpea, and sorghum. These recent developments are impossible without the continuous advancement seen in the next-generation sequencing platforms; thus, a brief introduction and analysis of the available sequencing platforms are presented here to have a clear picture of the workflow. Concluding the topic is the discussion about different pipelines applied to analyze data produced by sequencing techniques and have a significant role in interpreting the outcome of a particular experiment. A plethora of different software and tools are incorporated in the automated pipelines or individually available to perform manual metagenomic analysis. Here we describe 8-10 advanced, efficient pipelines used for analysis that explain their respective workflows to simplify the whole analysis process.

Bibliometric review of ATAC-Seq and its application in gene expression

With recent advances in high-throughput next-generation sequencing, it is possible to describe the regulation and expression of genes at multiple levels. An assay for transposase-accessible chromatin using sequencing (ATAC-seq), which uses Tn5 transposase to sequence protein-free binding regions of the genome, can be combined with chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) and ribonucleic acid sequencing (RNA-seq) to provide a detailed description of gene expression. Here, we reviewed the literature on ATAC-seq and described the characteristics of ATAC-seq publications. We then briefly introduced the principles of RNA-seq, ChIP-seq and ATAC-seq, focusing on the main features of the techniques. We built a phylogenetic tree from species that had been previously studied by using ATAC-seq. Studies of Mus musculus and Homo sapiens account for approximately 90% of the total ATAC-seq data, while other species are still in the process of accumulating data. We summarized the findings from human diseases and other species, illustrating the cutting-edge discoveries and the role of multi-omics data analysis in current research. Moreover, we collected and compared ATAC-seq analysis pipelines, which allowed biological researchers who lack programming skills to better analyze and explore ATAC-seq data. Through this review, it is clear that multi-omics analysis and single-cell sequencing technology will become the mainstream approach in future research.

Bacterial keratitis: identifying the areas of clinical uncertainty

Bacterial keratitis is a common corneal infection that is treated with topical antimicrobials. By the time of presentation there may already be severe visual loss from corneal ulceration and opacity, which may persist despite treatment. There are significant differences in the associated risk factors and the bacterial isolates between high income and low- or middle-income countries, so that general management guidelines may not be appropriate. Although the diagnosis of bacterial keratitis may seem intuitive there are multiple uncertainties about the criteria that are used, which impacts the interpretation of investigations and recruitment to clinical studies. Importantly, the concept that bacterial keratitis can only be confirmed by culture ignores the approximately 50% of cases clinically consistent with bacterial keratitis in which investigations are negative. The aetiology of these culture-negative cases is unknown. Currently, the estimation of bacterial susceptibility to antimicrobials is based on data from systemic administration and achievable serum or tissue concentrations, rather than relevant corneal concentrations and biological activity in the cornea. The provision to the clinician of minimum inhibitory concentrations of the antimicrobials for the isolated bacteria would be an important step forward. An increase in the prevalence of antimicrobial resistance is a concern, but the effect this has on disease outcomes is yet unclear. Virulence factors are not routinely assessed although they may affect the pathogenicity of bacteria within species and affect outcomes. New technologies have been developed to detect and kill bacteria, and their application to bacterial keratitis is discussed. In this review we present the multiple areas of clinical uncertainty that hamper research and the clinical management of bacterial keratitis, and we address some of the assumptions and dogma that have become established in the literature.

PEPATAC: an optimized pipeline for ATAC-seq data analysis with serial alignments

As chromatin accessibility data from ATAC-seq experiments continues to expand, there is continuing need for standardized analysis pipelines. Here, we present PEPATAC, an ATAC-seq pipeline that is easily applied to ATAC-seq projects of any size, from one-off experiments to large-scale sequencing projects. PEPATAC leverages unique features of ATAC-seq data to optimize for speed and accuracy, and it provides several unique analytical approaches. Output includes convenient quality control plots, summary statistics, and a variety of generally useful data formats to set the groundwork for subsequent project-specific data analysis. Downstream analysis is simplified by a standard definition format, modularity of components, and metadata APIs in R and Python. It is restartable, fault-tolerant, and can be run on local hardware, using any cluster resource manager, or in provided Linux containers. We also demonstrate the advantage of aligning to the mitochondrial genome serially, which improves the accuracy of alignment statistics and quality control metrics. PEPATAC is a robust and portable first step for any ATAC-seq project. BSD2-licensed code and documentation are available at https://pepatac.databio.org.

Testing assembly strategies of Francisella tularensis genomes to infer an evolutionary conservation analysis of genomic structures

Background

We benchmarked sequencing technology and assembly strategies for short-read, long-read, and hybrid assemblers in respect to correctness, contiguity, and completeness of assemblies in genomes of Francisella tularensis. Benchmarking allowed in-depth analyses of genomic structures of the Francisella pathogenicity islands and insertion sequences. Five major high-throughput sequencing technologies were applied, including next-generation “short-read” and third-generation “long-read” sequencing methods.

Results

We focused on short-read assemblers, hybrid assemblers, and analysis of the genomic structure with particular emphasis on insertion sequences and the Francisella pathogenicity island. The A5-miseq pipeline performed best for MiSeq data, Mira for Ion Torrent data, and ABySS for HiSeq data from eight short-read assembly methods. Two approaches were applied to benchmark long-read and hybrid assembly strategies: long-read-first assembly followed by correction with short reads (Canu/Pilon, Flye/Pilon) and short-read-first assembly along with scaffolding based on long reads (Unicyler, SPAdes). Hybrid assembly can resolve large repetitive regions best with a “long-read first” approach.

Conclusions

Genomic structures of the Francisella pathogenicity islands frequently showed misassembly. Insertion sequences (IS) could be used to perform an evolutionary conservation analysis. A phylogenetic structure of insertion sequences and the evolution within the clades elucidated the clade structure of the highly conservative F. tularensis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08115-x.

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).

AnnoMiner is a new web-tool to integrate epigenetics, transcription factor occupancy and transcriptomics data to predict transcriptional regulators

Gene expression regulation requires precise transcriptional programs, led by transcription factors in combination with epigenetic events. Recent advances in epigenomic and transcriptomic techniques provided insight into different gene regulation mechanisms. However, to date it remains challenging to understand how combinations of transcription factors together with epigenetic events control cell-type specific gene expression. We have developed the AnnoMiner web-server, an innovative and flexible tool to annotate and integrate epigenetic, and transcription factor occupancy data. First, AnnoMiner annotates user-provided peaks with gene features. Second, AnnoMiner can integrate genome binding data from two different transcriptional regulators together with gene features. Third, AnnoMiner offers to explore the transcriptional deregulation of genes nearby, or within a specified genomic region surrounding a user-provided peak. AnnoMiner’s fourth function performs transcription factor or histone modification enrichment analysis for user-provided gene lists by utilizing hundreds of public, high-quality datasets from ENCODE for the model organisms human, mouse, Drosophila and C. elegans. Thus, AnnoMiner can predict transcriptional regulators for a studied process without the strict need for chromatin data from the same process. We compared AnnoMiner to existing tools and experimentally validated several transcriptional regulators predicted by AnnoMiner to indeed contribute to muscle morphogenesis in Drosophila. AnnoMiner is freely available at http://chimborazo.ibdm.univ-mrs.fr/AnnoMiner/.

Evaluation of serverless computing for scalable execution of a joint variant calling workflow

Advances in whole-genome sequencing have greatly reduced the cost and time of obtaining raw genetic information, but the computational requirements of analysis remain a challenge. Serverless computing has emerged as an alternative to using dedicated compute resources, but its utility has not been widely evaluated for standardized genomic workflows. In this study, we define and execute a best-practice joint variant calling workflow using the SWEEP workflow management system. We present an analysis of performance and scalability, and discuss the utility of the serverless paradigm for executing workflows in the field of genomics research. The GATK best-practice short germline joint variant calling pipeline was implemented as a SWEEP workflow comprising 18 tasks. The workflow was executed on Illumina paired-end read samples from the European and African super populations of the 1000 Genomes project phase III. Cost and runtime increased linearly with increasing sample size, although runtime was driven primarily by a single task for larger problem sizes. Execution took a minimum of around 3 hours for 2 samples, up to nearly 13 hours for 62 samples, with costs ranging from $2 to $70.

Binding of the Treslin-MTBP Complex to Specific Regions of the Human Genome Promotes the Initiation of DNA Replication

The processes that control where higher eukaryotic cells initiate DNA replication throughout the genome are not understood clearly. In metazoans, the Treslin-MTBP complex mediates critical final steps in formation of the activated replicative helicase prior to initiation of replication. Here, we map the genome-wide distribution of the MTBP subunit of this complex in human cells. Our results indicate that MTBP binds to at least 30,000 sites in the genome. A majority of these sites reside in regions of open chromatin that contain transcriptional-regulatory elements (e.g., promoters, enhancers, and super-enhancers), which are known to be preferred areas for initiation of replication. Furthermore, many binding sites encompass two genomic features: a nucleosome-free DNA sequence (e.g., G-quadruplex DNA or AP-1 motif) and a nucleosome bearing histone marks characteristic of open chromatin, such as H3K4me2. Taken together, these findings indicate that Treslin-MTBP associates coordinately with multiple genomic signals to promote initiation of replication.

Kumagai and Dunphy show that Treslin-MTBP, activator of the replicative helicase, binds to at least 30,000 sites in the human genome. Many sites contain a nucleosome with active chromatin marks and nucleosome-free DNA (G-quadruplex or AP-1 site). Thus, Treslin-MTBP associates with multiple genomic elements to promote initiation of DNA replication.

Global Analyses to Identify Direct Transcriptional Targets of p53

The transcription factor p53 controls a gene expression program with pleiotropic effects on cell biology including cell cycle arrest and apoptosis. Identifying direct p53 target genes within this network and determining how they influence cell fate decisions downstream of p53 activation is a prerequisite for designing therapeutic approaches that target p53 to effectively kill cancer cells. Here we describe a comprehensive multi-omics approach for identifying genes that are direct transcriptional targets of p53. We provide detailed procedures for measuring global RNA polymerase activity, defining p53 binding sites across the genome, and quantifying changes in steady-state mRNA in response to p53 activation.

Analytical Approaches for ATAC-seq Data Analysis

ATAC-seq, the assay for transposase-accessible chromatin using sequencing, is a quick and efficient approach to investigating the chromatin accessibility landscape. Investigating chromatin accessibility has broad utility for answering many biological questions, such as mapping nucleosomes, identifying transcription factor binding sites, and measuring differential activity of DNA regulatory elements. Because the ATAC-seq protocol is both simple and relatively inexpensive, there has been a rapid increase in the availability of chromatin accessibility data. Furthermore, advances in ATAC-seq protocols are rapidly extending its breadth to additional experimental conditions, cell types, and species. Accompanying the increase in data, there has also been an explosion of new tools and analytical approaches for analyzing it. Here, we explain the fundamentals of ATAC-seq data processing, summarize common analysis approaches, and review computational tools to provide recommendations for different research questions. This primer provides a starting point and a reference for analysis of ATAC-seq data. © 2020 Wiley Periodicals LLC.

DolphinNext: a distributed data processing platform for high throughput genomics

BACKGROUND

The emergence of high throughput technologies that produce vast amounts of genomic data, such as next-generation sequencing (NGS) is transforming biological research. The dramatic increase in the volume of data, the variety and continuous change of data processing tools, algorithms and databases make analysis the main bottleneck for scientific discovery. The processing of high throughput datasets typically involves many different computational programs, each of which performs a specific step in a pipeline. Given the wide range of applications and organizational infrastructures, there is a great need for highly parallel, flexible, portable, and reproducible data processing frameworks. Several platforms currently exist for the design and execution of complex pipelines. Unfortunately, current platforms lack the necessary combination of parallelism, portability, flexibility and/or reproducibility that are required by the current research environment. To address these shortcomings, workflow frameworks that provide a platform to develop and share portable pipelines have recently arisen. We complement these new platforms by providing a graphical user interface to create, maintain, and execute complex pipelines. Such a platform will simplify robust and reproducible workflow creation for non-technical users as well as provide a robust platform to maintain pipelines for large organizations.

RESULTS

To simplify development, maintenance, and execution of complex pipelines we created DolphinNext. DolphinNext facilitates building and deployment of complex pipelines using a modular approach implemented in a graphical interface that relies on the powerful Nextflow workflow framework by providing 1. A drag and drop user interface that visualizes pipelines and allows users to create pipelines without familiarity in underlying programming languages. 2. Modules to execute and monitor pipelines in distributed computing environments such as high-performance clusters and/or cloud 3. Reproducible pipelines with version tracking and stand-alone versions that can be run independently. 4. Modular process design with process revisioning support to increase reusability and pipeline development efficiency. 5. Pipeline sharing with GitHub and automated testing 6. Extensive reports with R-markdown and shiny support for interactive data visualization and analysis.

CONCLUSION

DolphinNext is a flexible, intuitive, web-based data processing and analysis platform that enables creating, deploying, sharing, and executing complex Nextflow pipelines with extensive revisioning and interactive reporting to enhance reproducible results.

From reads to insight: a hitchhiker's guide to ATAC-seq data analysis

Assay of Transposase Accessible Chromatin sequencing (ATAC-seq) is widely used in studying chromatin biology, but a comprehensive review of the analysis tools has not been completed yet. Here, we discuss the major steps in ATAC-seq data analysis, including pre-analysis (quality check and alignment), core analysis (peak calling), and advanced analysis (peak differential analysis and annotation, motif enrichment, footprinting, and nucleosome position analysis). We also review the reconstruction of transcriptional regulatory networks with multiomics data and highlight the current challenges of each step. Finally, we describe the potential of single-cell ATAC-seq and highlight the necessity of developing ATAC-seq specific analysis tools to obtain biologically meaningful insights.

A neural network based model effectively predicts enhancers from clinical ATAC-seq samples

Enhancers are cis-acting sequences that regulate transcription rates of their target genes in a cell-specific manner and harbor disease-associated sequence variants in cognate cell types. Many complex diseases are associated with enhancer malfunction, necessitating the discovery and study of enhancers from clinical samples. Assay for Transposase Accessible Chromatin (ATAC-seq) technology can interrogate chromatin accessibility from small cell numbers and facilitate studying enhancers in pathologies. However, on average, ~35% of open chromatin regions (OCRs) from ATAC-seq samples map to enhancers. We developed a neural network-based model, Predicting Enhancers from ATAC-Seq data (PEAS), to effectively infer enhancers from clinical ATAC-seq samples by extracting ATAC-seq data features and integrating these with sequence-related features (e.g., GC ratio). PEAS recapitulated ChromHMM-defined enhancers in CD14+ monocytes, CD4+ T cells, GM12878, peripheral blood mononuclear cells, and pancreatic islets. PEAS models trained on these 5 cell types effectively predicted enhancers in four cell types that are not used in model training (EndoC-βH1, naïve CD8+ T, MCF7, and K562 cells). Finally, PEAS inferred individual-specific enhancers from 19 islet ATAC-seq samples and revealed variability in enhancer activity across individuals, including those driven by genetic differences. PEAS is an easy-to-use tool developed to study enhancers in pathologies by taking advantage of the increasing number of clinical epigenomes.

Systems and Synthetic Biology Approaches to Engineer Fungi for Fine Chemical Production

Since the advent of systems and synthetic biology, many studies have sought to harness microbes as cell factories through genetic and metabolic engineering approaches. Yeast and filamentous fungi have been successfully harnessed to produce fine and high value-added chemical products. In this review, we present some of the most promising advances from recent years in the use of fungi for this purpose, focusing on the manipulation of fungal strains using systems and synthetic biology tools to improve metabolic flow and the flow of secondary metabolites by pathway redesign. We also review the roles of bioinformatics analysis and predictions in synthetic circuits, highlighting in silico systemic approaches to improve the efficiency of synthetic modules.

Dual Roles of Poly(dA:dT) Tracts in Replication Initiation and Fork Collapse

Replication origins, fragile sites, and rDNA have been implicated as sources of chromosomal instability. However, the defining genomic features of replication origins and fragile sites are among the least understood elements of eukaryote genomes. Here, we map sites of replication initiation and breakage in primary cells at high resolution. We find that replication initiates between transcribed genes within nucleosome-depleted structures established by long asymmetrical poly(dA:dT) tracts flanking the initiation site. Paradoxically, long (>20 bp) (dA:dT) tracts are also preferential sites of polar replication fork stalling and collapse within early-replicating fragile sites (ERFSs) and late-replicating common fragile sites (CFSs) and at the rDNA replication fork barrier. Poly(dA:dT) sequences are fragile because long single-strand poly(dA) stretches at the replication fork are unprotected by the replication protein A (RPA). We propose that the evolutionary expansion of poly(dA:dT) tracts in eukaryotic genomes promotes replication initiation, but at the cost of chromosome fragility.

YAMP: a containerized workflow enabling reproducibility in metagenomics research

YAMP ("Yet Another Metagenomics Pipeline") is a user-friendly workflow that enables the analysis of whole shotgun metagenomic data while using containerization to ensure computational reproducibility and facilitate collaborative research. YAMP can be executed on any UNIX-like system and offers seamless support for multiple job schedulers as well as for the Amazon AWS cloud. Although YAMP was developed to be ready to use by nonexperts, bioinformaticians will appreciate its flexibility, modularization, and simple customization.