HiBrowser: an interactive and dynamic browser for synchronous Hi-C data visualization.

With the development of chromosome conformation capture technology, the genome-wide investigation of higher-order chromatin structure by using high-throughput chromatin conformation capture (Hi-C) technology is emerging as an important component for understanding the mechanism of gene regulation. Considering genetic and epigenetic differences are typically used to explore the pathological reasons on the chromosome and gene level, visualizing multi-omics data and performing an intuitive analysis by using an interactive browser become a powerful and welcomed way. In this paper, we develop an effective sequence and chromatin interaction data display browser called HiBrowser for visualizing and analyzing Hi-C data and their associated genetic and epigenetic annotations. The advantages of HiBrowser are flexible multi-omics navigation, novel multidimensional synchronization comparisons and dynamic interaction system. In particular, HiBrowser first provides an out of the box web service and allows flexible and dynamic reconstruction of custom annotation tracks on demand during running. In order to conveniently and intuitively analyze the similarities and differences among multiple samples, such as visual comparisons of normal and tumor tissue samples, and pan genomes of multiple (consanguineous) species, HiBrowser develops a clone mode to synchronously display the genome coordinate positions or the same regions of multiple samples on the same page of visualization. HiBrowser also supports a pluralistic and precise search on correlation data of distal cis-regulatory elements and navigation to any region on Hi-C heatmap of interest according to the searching results. HiBrowser is a no-build tool, and could be easily deployed in local server. The source code is available at https://github.com/lyotvincent/HiBrowser.

ARGV: 3D genome structure exploration using augmented reality.

Over the past two decades, scientists have increasingly realized the importance of the three-dimensional (3D) genome organization in regulating cellular activity. Hi-C and related experiments yield 2D contact matrices that can be used to infer 3D models of chromosome structure. Visualizing and analyzing genomes in 3D space remains challenging. Here, we present ARGV, an augmented reality 3D Genome Viewer. ARGV contains more than 350 pre-computed and annotated genome structures inferred from Hi-C and imaging data. It offers interactive and collaborative visualization of genomes in 3D space, using standard mobile phones or tablets. A user study comparing ARGV to existing tools demonstrates its benefits.

PPanG: a precision pangenome browser enabling nucleotide-level analysis of genomic variations in individual genomes and their graph-based pangenome.

Graph-based pangenome is gaining more popularity than linear pangenome because it stores more comprehensive information of variations. However, traditional linear genome browser has its own advantages, especially the tremendous resources accumulated historically. With the fast-growing number of individual genomes and their annotations available, the demand for a genome browser to visualize genome annotation for many individuals together with a graph-based pangenome is getting higher and higher. Here we report a new pangenome browser PPanG, a precise pangenome browser enabling nucleotide-level comparison of individual genome annotations together with a graph-based pangenome. Nine rice genomes with annotations were provided by default as potential references, and any individual genome can be selected as the reference. Our pangenome browser provides unprecedented insights on genome variations at different levels from base to gene, and reveals how the structures of a gene could differ for individuals. PPanG can be applied to any species with multiple individual genomes available and it is available at https://cgm.sjtu.edu.cn/PPanG .

ListiWiki: A database for the foodborne pathogen Listeria monocytogenes.

Listeria monocytogenes is a Gram positive foodborne pathogen that regularly causes outbreaks of systemic infectious diseases. The bacterium maintains a facultative intracellular lifestyle; it thrives under a variety of environmental conditions and is able to infect human host cells. L. monocytogenes is genetically tractable and therefore has become an attractive model system to study the mechanisms employed by facultative intracellular bacteria to invade eukaryotic cells and to replicate in their cytoplasm. Besides its importance for basic research, L. monocytogenes also serves as a paradigmatic pathogen in genomic epidemiology, where the relative stability of its genome facilitates successful outbreak detection and elucidation of transmission chains in genomic pathogen surveillance systems. In both terms, it is necessary to keep the annotation of the L. monocytogenes genome up to date. Therefore, we have created the database ListiWiki (http://listiwiki.uni-goettingen.de/) which stores comprehensive information on the widely used L. monocytogenes reference strain EDG-e. ListiWiki is designed to collect information on genes, proteins and RNAs and their relevant functional characteristics, but also further information such as mutant phenotypes, available biological material, and publications. In its present form, ListiWiki combines the most recent annotation of the EDG-e genome with published data on gene essentiality, gene expression and subcellular protein localization. ListiWiki also predicts protein-protein interactions networks based on protein homology to Bacillus subtilis proteins, for which detailed interaction maps have been compiled in the sibling database SubtiWiki. Furthermore, crystallographic information of proteins is made accessible through integration of Protein Structure Database codes and AlphaFold structure predictions. ListiWiki is an easy-to-use web interface that has been developed with a focus on an intuitive access to all information. Use of ListiWiki is free of charge and its content can be edited by all members of the scientific community after registration. In our labs, ListiWiki has already become an important and easy to use tool to quickly access genome annotation details that we can keep updated with advancing knowledge. It also might be useful to promote the comprehensive understanding of the physiology and virulence of an important human pathogen.

Variant interpretation: UCSC Genome Browser Recommended Track Sets.

The UCSC Genome Browser has been an important tool for genomics and clinical genetics since the sequence of the human genome was first released in 2000. As it has grown in scope to display more types of data it has also grown more complicated. The data, which are dispersed at many locations worldwide, are collected into one view on the Browser, where the graphical interface presents the data in one location. This supports the expertise of the researcher to interpret variants in the genome. Because the analysis of single nucleotide variants and copy number variants require interpretation of data at very different genomic scales, different data resources are required. We present here several Recommended Track Sets designed to facilitate the interpretation of variants in the clinic, offering quick access to datasets relevant to the appropriate scale.

OpenGenomeBrowser: a versatile, dataset-independent and scalable web platform for genome data management and comparative genomics.

BACKGROUND: As the amount of genomic data continues to grow, there is an increasing need for systematic ways to organize, explore, compare, analyze and share this data. Despite this, there is a lack of suitable platforms to meet this need. RESULTS: OpenGenomeBrowser is a self-hostable, open-source platform to manage access to genomic data and drastically simplifying comparative genomics analyses. It enables users to interactively generate phylogenetic trees, compare gene loci, browse biochemical pathways, perform gene trait matching, create dot plots, execute BLAST searches, and access the data. It features a flexible user management system, and its modular folder structure enables the organization of genomic data and metadata, and to automate analyses. We tested OpenGenomeBrowser with bacterial, archaeal and yeast genomes. We provide a docker container to make installation and hosting simple. The source code, documentation, tutorials for OpenGenomeBrowser are available at opengenomebrowser.github.io and a demo server is freely accessible at opengenomebrowser.bioinformatics.unibe.ch . CONCLUSIONS: To our knowledge, OpenGenomeBrowser is the first self-hostable, database-independent comparative genome browser. It drastically simplifies commonly used bioinformatics workflows and enables convenient as well as fast data exploration.

CoolBox: a flexible toolkit for visual analysis of genomics data.

BACKGROUND: Data visualization, especially the genome track plots, is crucial for genomics researchers to discover patterns in large-scale sequencing dataset. Although existing tools works well for producing a normal view of the input data, they are not convenient when users want to create customized data representations. Such gap between the visualization and data processing, prevents the users to uncover more hidden structure of the dataset. RESULTS: We developed CoolBox-an open-source toolkit for visual analysis of genomics data. This user-friendly toolkit is highly compatible with the Python ecosystem and customizable with a well-designed user interface. It can be used in various visualization situations like a Swiss army knife. For example, to produce high-quality genome track plots or fetch commonly used genomic data files with a Python script or command line, to explore genomic data interactively within Jupyter environment or web browser. Moreover, owing to the highly extensible Application Programming Interface design, users can customize their own tracks without difficulty, which greatly facilitate analytical, comparative genomic data visualization tasks. CONCLUSIONS: CoolBox allows users to produce high-quality visualization plots and explore their data in a flexible, programmable and user-friendly way.

qtlXplorer: an online systems genetics browser in the Eucalyptus Genome Integrative Explorer (EucGenIE).

BACKGROUND: Affordable high-throughput DNA and RNA sequencing technologies are allowing genomic analysis of plant and animal populations and as a result empowering new systems genetics approaches to study complex traits. The availability of intuitive tools to browse and analyze the resulting large-scale genetic and genomic datasets remain a significant challenge. Furthermore, these integrative genomics approaches require innovative methods to dissect the flow and interconnectedness of biological information underlying complex trait variation. The Plant Genome Integrative Explorer (PlantGenIE.org) is a multi-species database and domain that houses online tools for model and woody plant species including Eucalyptus. Since the Eucalyptus Genome Integrative Explorer (EucGenIE) is integrated within PlantGenIE, it shares genome and expression analysis tools previously implemented within the various subdomains (ConGenIE, PopGenIE and AtGenIE). Despite the success in setting up integrative genomics databases, online tools for systems genetics modelling and high-resolution dissection of complex trait variation in plant populations have been lacking. RESULTS: We have developed qtlXplorer ( https://eucgenie.org/QTLXplorer ) for visualizing and exploring systems genetics data from genome-wide association studies including quantitative trait loci (QTLs) and expression-based QTL (eQTL) associations. This module allows users to, for example, find co-located QTLs and eQTLs using an interactive version of Circos, or explore underlying genes using JBrowse. It provides users with a means to build systems genetics models and generate hypotheses from large-scale population genomics data. We also substantially upgraded the EucGenIE resource and show how it enables users to combine genomics and systems genetics approaches to discover candidate genes involved in biotic stress responses and wood formation by focusing on two multigene families, laccases and peroxidases. CONCLUSIONS: qtlXplorer adds a new dimension, population genomics, to the EucGenIE and PlantGenIE environment. The resource will be of interest to researchers and molecular breeders working in Eucalyptus and other woody plant species. It provides an example of how systems genetics data can be integrated with functional genetics data to provide biological insight and formulate hypotheses. Importantly, integration within PlantGenIE enables novel comparative genomics analyses to be performed from population-scale data.

Genome Annotator Light (GAL): A Docker-based package for genome analysis and visualization.

Next generation sequencing techniques produce enormous data but its analysis and visualization remains a big challenge. To address this, we have developed Genome Annotator Light(GAL), a Docker based package for genome analysis and data visualization. GAL integrated several existing tools and in-house programs inside a Docker Container for systematic analysis and visualization of genomes through web browser. GAL takes varieties of input types ranging from raw Fasta files to fully annotated files, processes them through a standard annotation pipeline and visualizes on a web browser. Comparative genomic analysis is performed automatically within a given taxonomic class. GAL creates interactive genome browser with clickable genomic feature tracks; local BLAST-able database; query page, on-fly downstream data analysis using EMBOSS etc. Overall, GAL is an extremely convenient, portable and platform independent. Fully integrated web-resources can be easily created and deployed, e.g. www.eumicrobedb.org/cglab, for our in-house genomes. GAL is freely available at https://hub.docker.com/u/cglabiicb/.

Search and comparison of (epi)genomic feature patterns in multiple genome browser tracks.

BACKGROUND: Genome browsers are widely used for locating interesting genomic regions, but their interactive use is obviously limited to inspecting short genomic portions. An ideal interaction is to provide patterns of regions on the browser, and then extract other genomic regions over the whole genome where such patterns occur, ranked by similarity. RESULTS: We developed SimSearch, an optimized pattern-search method and an open source plugin for the Integrated Genome Browser (IGB), to find genomic region sets that are similar to a given region pattern. It provides efficient visual genome-wide analytics computation in large datasets; the plugin supports intuitive user interactions for selecting an interesting pattern on IGB tracks and visualizing the computed occurrences of similar patterns along the entire genome. SimSearch also includes functions for the annotation and enrichment of results, and is enhanced with a Quickload repository including numerous epigenomic feature datasets from ENCODE and Roadmap Epigenomics. The paper also includes some use cases to show multiple genome-wide analyses of biological interest, which can be easily performed by taking advantage of the presented approach. CONCLUSIONS: The novel SimSearch method provides innovative support for effective genome-wide pattern search and visualization; its relevance and practical usefulness is demonstrated through a number of significant use cases of biological interest. The SimSearch IGB plugin, documentation, and code are freely available at https://deib-geco.github.io/simsearch-app/ and https://github.com/DEIB-GECO/simsearch-app/ .

MoMI-G: modular multi-scale integrated genome graph browser.

BACKGROUND: Genome graph is an emerging approach for representing structural variants on genomes with branches. For example, representing structural variants of cancer genomes as a genome graph is more natural than representing such genomes as differences from the linear reference genome. While more and more structural variants are being identified by long-read sequencing, many of them are difficult to visualize using existing structural variants visualization tools. To this end, visualization method for large genome graphs such as human cancer genome graphs is demanded. RESULTS: We developed MOdular Multi-scale Integrated Genome graph browser, MoMI-G, a web-based genome graph browser that can visualize genome graphs with structural variants and supporting evidences such as read alignments, read depth, and annotations. This browser allows more intuitive recognition of large, nested, and potentially more complex structural variations. MoMI-G has view modules for different scales, which allow users to view the whole genome down to nucleotide-level alignments of long reads. Alignments spanning reference alleles and those spanning alternative alleles are shown in the same view. Users can customize the view, if they are not satisfied with the preset views. In addition, MoMI-G has Interval Card Deck, a feature for rapid manual inspection of hundreds of structural variants. Herein, we describe the utility of MoMI-G by using representative examples of large and nested structural variations found in two cell lines, LC-2/ad and CHM1. CONCLUSIONS: Users can inspect complex and large structural variations found by long-read analysis in large genomes such as human genomes more smoothly and more intuitively. In addition, users can easily filter out false positives by manually inspecting hundreds of identified structural variants with supporting long-read alignments and annotations in a short time. SOFTWARE AVAILABILITY: MoMI-G is freely available at https://github.com/MoMI-G/MoMI-G under the MIT license.

svist4get: a simple visualization tool for genomic tracks from sequencing experiments.

BACKGROUND: High-throughput sequencing often provides a foundation for experimental analyses in the life sciences. For many such methods, an intermediate layer of bioinformatics data analysis is the genomic signal track constructed by short read mapping to a particular genome assembly. There are many software tools to visualize genomic tracks in a web browser or with a stand-alone graphical user interface. However, there are only few command-line applications suitable for automated usage or production of publication-ready visualizations. RESULTS: Here we present svist4get, a command-line tool for customizable generation of publication-quality figures based on data from genomic signal tracks. Similarly to generic genome browser software, svist4get visualizes signal tracks at a given genomic location and is able to aggregate data from several tracks on a single plot along with the transcriptome annotation. The resulting plots can be saved as the vector or high-resolution bitmap images. We demonstrate practical use cases of svist4get for Ribo-Seq and RNA-Seq data. CONCLUSIONS: svist4get is implemented in Python 3 and runs on Linux. The command-line interface of svist4get allows for easy integration into bioinformatics pipelines in a console environment. Extra customization is possible through configuration files and Python API. For convenience, svist4get is provided as pypi package. The source code is available at https://bitbucket.org/artegorov/svist4get/.

MuSERA: Multiple Sample Enriched Region Assessment.

Enriched region (ER) identification is a fundamental step in several next-generation sequencing (NGS) experiment types. Yet, although NGS experimental protocols recommend producing replicate samples for each evaluated condition and their consistency is usually assessed, typically pipelines for ER identification do not consider available NGS replicates. This may alter genome-wide descriptions of ERs, hinder significance of subsequent analyses on detected ERs and eventually preclude biological discoveries that evidence in replicate could support. MuSERA is a broadly useful stand-alone tool for both interactive and batch analysis of combined evidence from ERs in multiple ChIP-seq or DNase-seq replicates. Besides rigorously combining sample replicates to increase statistical significance of detected ERs, it also provides quantitative evaluations and graphical features to assess the biological relevance of each determined ER set within its genomic context; they include genomic annotation of determined ERs, nearest ER distance distribution, global correlation assessment of ERs and an integrated genome browser. We review MuSERA rationale and implementation, and illustrate how sets of significant ERs are expanded by applying MuSERA on replicates for several types of NGS data, including ChIP-seq of transcription factors or histone marks and DNase-seq hypersensitive sites. We show that MuSERA can determine a new, enhanced set of ERs for each sample by locally combining evidence on replicates, and prove how the easy-to-use interactive graphical displays and quantitative evaluations that MuSERA provides effectively support thorough inspection of obtained results and evaluation of their biological content, facilitating their understanding and biological interpretations. MuSERA is freely available at http://www.bioinformatics.deib.polimi.it/MuSERA/.

A tool for integrating genetic and mass spectrometry-based peptide data: Proteogenomics Viewer: PV: A genome browser-like tool, which includes MS data visualization and peptide identification parameters.

In this manuscript we describe Proteogenomics Viewer, a web-based tool that collects MS peptide identification, indexes to genomic sequence and structure, assigns exon usage, reports the identified protein isoforms with genomic alignments and, most importantly, allows the inspection of MS2 information for proper peptide identification. It also provides all performed indexing to facilitate global analysis of the data. The relevance of such tool is that there has been an increase in the number of proteogenomic efforts to improve the annotation of both genomics and proteomics data, culminating with the release of the two human proteome drafts. It is now clear that mass spectrometry-based peptide identification of uncharacterized sequences, such as those resulting from unpredicted exon joints or non-coding regions, is still prone to a higher than expected false discovery rate. Therefore, proper visualization of the raw data and the corresponding genome alignments are fundamental for further data validation and interpretation. Also see the video abstract here: http://youtu.be/5NzyRvuk4Ac.

Enhanced JBrowse plugins for epigenomics data visualization.

BACKGROUND: New sequencing techniques require new visualization strategies, as is the case for epigenomics data such as DNA base modifications, small non-coding RNAs, and histone modifications. RESULTS: We present a set of plugins for the genome browser JBrowse that are targeted for epigenomics visualizations. Specifically, we have focused on visualizing DNA base modifications, small non-coding RNAs, stranded read coverage, and sequence motif density. Additionally, we present several plugins for improved user experience such as configurable, high-quality screenshots. CONCLUSIONS: In visualizing epigenomics with traditional genomics data, we see these plugins improving scientific communication and leading to discoveries within the field of epigenomics.

Ginseng Genome Database: an open-access platform for genomics of Panax ginseng.

BACKGROUND: The ginseng (Panax ginseng C.A. Meyer) is a perennial herbaceous plant that has been used in traditional oriental medicine for thousands of years. Ginsenosides, which have significant pharmacological effects on human health, are the foremost bioactive constituents in this plant. Having realized the importance of this plant to humans, an integrated omics resource becomes indispensable to facilitate genomic research, molecular breeding and pharmacological study of this herb. DESCRIPTION: The first draft genome sequences of P. ginseng cultivar "Chunpoong" were reported recently. Here, using the draft genome, transcriptome, and functional annotation datasets of P. ginseng, we have constructed the Ginseng Genome Database http://ginsengdb.snu.ac.kr /, the first open-access platform to provide comprehensive genomic resources of P. ginseng. The current version of this database provides the most up-to-date draft genome sequence (of approximately 3000 Mbp of scaffold sequences) along with the structural and functional annotations for 59,352 genes and digital expression of genes based on transcriptome data from different tissues, growth stages and treatments. In addition, tools for visualization and the genomic data from various analyses are provided. All data in the database were manually curated and integrated within a user-friendly query page. CONCLUSION: This database provides valuable resources for a range of research fields related to P. ginseng and other species belonging to the Apiales order as well as for plant research communities in general. Ginseng genome database can be accessed at http://ginsengdb.snu.ac.kr /.

GTB - an online genome tolerance browser.

BACKGROUND: Accurate methods capable of predicting the impact of single nucleotide variants (SNVs) are assuming ever increasing importance. There exists a plethora of in silico algorithms designed to help identify and prioritize SNVs across the human genome for further investigation. However, no tool exists to visualize the predicted tolerance of the genome to mutation, or the similarities between these methods. RESULTS: We present the Genome Tolerance Browser (GTB, http://gtb.biocompute.org.uk ): an online genome browser for visualizing the predicted tolerance of the genome to mutation. The server summarizes several in silico prediction algorithms and conservation scores: including 13 genome-wide prediction algorithms and conservation scores, 12 non-synonymous prediction algorithms and four cancer-specific algorithms. CONCLUSION: The GTB enables users to visualize the similarities and differences between several prediction algorithms and to upload their own data as additional tracks; thereby facilitating the rapid identification of potential regions of interest.

C-State: an interactive web app for simultaneous multi-gene visualization and comparative epigenetic pattern search.

BACKGROUND: Comparative epigenomic analysis across multiple genes presents a bottleneck for bench biologists working with NGS data. Despite the development of standardized peak analysis algorithms, the identification of novel epigenetic patterns and their visualization across gene subsets remains a challenge. RESULTS: We developed a fast and interactive web app, C-State (Chromatin-State), to query and plot chromatin landscapes across multiple loci and cell types. C-State has an interactive, JavaScript-based graphical user interface and runs locally in modern web browsers that are pre-installed on all computers, thus eliminating the need for cumbersome data transfer, pre-processing and prior programming knowledge. CONCLUSIONS: C-State is unique in its ability to extract and analyze multi-gene epigenetic information. It allows for powerful GUI-based pattern searching and visualization. We include a case study to demonstrate its potential for identifying user-defined epigenetic trends in context of gene expression profiles.

SalmoBase: an integrated molecular data resource for Salmonid species.

BACKGROUND: Salmonids are ray-finned fishes which constitute 11 genera and at least 70 species including Atlantic salmon, whitefishes, graylings, rainbow trout, and char. The common ancestor of all Salmonidae experienced a whole genome duplication (WGD) ~80 million years ago, resulting in an autotetraploid genome. Genomic rediplodization is still going on in salmonid species, providing an unique system for studying evolutionary consequences of whole genome duplication. In recent years, high quality genome sequences of Atlantic salmon and Rainbow trout has been established, due to their scientific and commercial values. In this paper we introduce SalmoBase ( http://www.salmobase.org/ ), a tool for making molecular resources for salmonids public available in a framework of visualizations and analytic tools. RESULTS: SalmoBase has been developed as a part of the ELIXIR.NO project. Currently, SalmoBase contains molecular resources for Atlantic salmon and Rainbow trout. Data can be accessed through BLAST, Genome Browser (GBrowse), Genetic Variation Browser (GVBrowse) and Gene Expression Browser (GEBrowse). CONCLUSIONS: To the best of our knowledge, SalmoBase is the first database which integrates salmonids data and allow users to study salmonids in an integrated framework. The database and its tools (e.g., comparative genomics tools, synteny browsers) will be expanded as additional public resources describing other Salmonidae genomes become available.

CRISPR/Cas9-mediated deletion of lncRNA Gm26878 in the distant Foxf1 enhancer region.

Recent genome editing techniques, including CRISPR mutagenesis screens, offer unparalleled opportunities to study the regulatory non-coding genomic regions, enhancers, promoters, and functional non-coding RNAs. Heterozygous point mutations in FOXF1 and genomic deletion copy-number variants at chromosomal region 16q24.1 involving FOXF1 or its regulatory region mapping ~300 kb upstream of FOXF1 and leaving it intact have been identified in the vast majority of patients with a lethal neonatal lung disease, alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV). Homozygous Foxf1 -/- mice have been shown to die by embryonic day 8.5 because of defects in the development of extraembryonic and lateral mesoderm-derived tissues, whereas heterozygous Foxf1 +/- mice exhibit features resembling ACDMPV. We have previously defined a human lung-specific enhancer region encoding two long non-coding RNAs, LINC01081 and LINC01082, expressed in the lungs. To investigate the biological significance of lncRNAs in the Foxf1 enhancer region, we have generated a CRISPR/Cas9-mediated ~2.4 kb deletion involving the entire lncRNA-encoding gene Gm26878, located in the mouse region syntenic with the human Foxf1 upstream enhancer. Very recently, this mouse genomic region has been shown to function as a Foxf1 enhancer. Our results indicate that homozygous loss of Gm26878 is neonatal lethal with low penetrance. No changes in Foxf1 expression were observed, suggesting that the regulation of Foxf1 expression differs between mouse and human.