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Abstract 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 .

ABSTRACT Are two adjacent genes in the same operon? What are the order and spacing between several transcription factor binding sites? Genome browsers are software data visualization and exploration tools that enable biologists to answer questions such as these. In this paper, we report on a major update to our browser, Genome Explorer, that provides nearly instantaneous scaling and traversing of a genome, enabling users to quickly and easily zoom into an area of interest. The user can rapidly move between scales that depict the entire genome, individual genes, and the sequence; Genome Explorer presents the most relevant detail and context for each scale. By downloading the data for the entire genome to the user’s web browser and dynamically generating visualizations locally, we enable fine control of zoom and pan functions and real-time redrawing of the visualization, resulting in smoother and more intuitive exploration of a genome than is possible with other browsers. Further, genome features are presented together, in-line, using familiar graphical depictions. In contrast, many other browsers depict genome features using data tracks, which have low information density and can visually obscure the relative positions of features. Genome Explorer diagrams have a high information density that provides larger amounts of genome context and sequence information to be presented in a given-sized monitor than for tracks-based browsers. Genome Explorer provides optional data tracks for the analysis of large-scale data sets and a unique comparative mode that aligns genomes at orthologous genes with synchronized zooming.IMPORTANCEGenome browsers provide graphical depictions of genome information to speed the uptake of complex genome data by scientists. They provide search operations to help scientists find information and zoom operations to enable scientists to view genome features at different resolutions. We introduce the Genome Explorer browser, which provides extremely fast zooming and panning of genome visualizations and displays with high information density.

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.

GrainGenes is the USDA-ARS database and Web resource for wheat, barley, oat, rye, and their relatives. As a community Web hub and database for small grains, GrainGenes strives to provide resources for researchers, students, and plant breeders to improve traits such as quality, yield, and disease resistance. Quantitative trait loci (QTL), genes, and genetic maps for quality attributes in GrainGenes represent the historical approach to mapping genes for groat percentage, test weight, protein, fat, and β-glucan content in oat (Avena spp.). Genetic maps are viewable in CMap, the comparative mapping tool that enables researchers to take advantage of highly populated consensus maps to increase the marker density around their genes-of-interest. GrainGenes hosts over 50 genome browsers and is launching an effort for community curation, including the manually curated tracks with beta-glucan QTL and significant markers found via GWAS and cloned cellulose synthase-like AsClF6 alleles.

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.

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. [ABSTRACT FROM AUTHOR]

Abstract 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.

Common wheat (Triticum aestivum) is a hexaploid plant (AABBDD) derived from genetically related tetraploid wheat T. turgidum (AABB) and a diploid goatgrass Aegilops tauschii (DD). Recent advances in sequencing technology and genome assembly strategies allow the acquisition of multiple wheat genomes, calling for a centralized database to store, manage and query the genomics information in a manner to reflect their evolutionary relationship and to perform effective comparative genome analysis. Here, we built WheatGene, a database that contains five wheat genomes of 318,102 genes and 945,900 transcripts and their expression information in 998 RNA-seq samples that can be searched and compared in an interactive manner. WheatGene was developed with Drupal, a popular content management system and the toolkit Tripal managed the biological information. The database was accessible through a web browser with species, search, gene expression, tools, and literature entries. Tools available were BLAST, synteny viewer, map viewer, JBrowse, data downloads, gene expression heatmap and bar chart, and homologs viewer. Moreover, the map viewer connected genomics data with genetic maps and QTL that can be searched for markers for molecular breeding. WheatGene was developed with open-source modules and libraries. WheatGene is available at http://wheatgene.agrinome.org.

Abstract 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.

JBrowse 2 is a modular genome browser that can visualize many common genomic file formats. While JBrowse 2 supports a variety of different usages, it is particularly suited for deployment on websites, such as model organism databases or other web-based genomic data resources. This protocol provides detailed instructions for setting up JBrowse 2 on an Ubuntu Linux web server, loading a reference genome from a FASTA format file, and adding a gene annotation track from a GFF3 format file. By the end of the protocol, users will have a working JBrowse 2 instance that is accessible via the web. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Setting up JBrowse 2 on your web server., (© 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC.)

Are two adjacent genes in the same operon? What are the order and spacing between several transcription factor binding sites? Genome browsers are software data visualization and exploration tools that enable biologists to answer questions such as these. In this paper, we report on a major update to our browser, Genome Explorer, that provides nearly instantaneous scaling and traversing of a genome, enabling users to quickly and easily zoom into an area of interest. The user can rapidly move between scales that depict the entire genome, individual genes, and the sequence; Genome Explorer presents the most relevant detail and context for each scale. By downloading the data for the entire genome to the user's web browser and dynamically generating visualizations locally, we enable fine control of zoom and pan functions and real-time redrawing of the visualization, resulting in smoother and more intuitive exploration of a genome than is possible with other browsers. Further, genome features are presented together, in-line, using familiar graphical depictions. In contrast, many other browsers depict genome features using data tracks, which have low information density and can visually obscure the relative positions of features. Genome Explorer diagrams have a high information density that provides larger amounts of genome context and sequence information to be presented in a given-sized monitor than for tracks-based browsers. Genome Explorer provides optional data tracks for the analysis of large-scale data sets and a unique comparative mode that aligns genomes at orthologous genes with synchronized zooming., Importance: Genome browsers provide graphical depictions of genome information to speed the uptake of complex genome data by scientists. They provide search operations to help scientists find information and zoom operations to enable scientists to view genome features at different resolutions. We introduce the Genome Explorer browser, which provides extremely fast zooming and panning of genome visualizations and displays with high information density., Competing Interests: The authors declare no conflict of interest.

Tree House Explorer (THEx) is a genome browser that integrates phylogenomic data and genomic annotations into a single interactive platform for combined analysis. THEx allows users to visualize genome-wide variation in evolutionary histories and genetic divergence on a chromosome-by-chromosome basis, with continuous sliding window comparisons to gene annotations, recombination rates, and other user-specified, highly customizable feature annotations. THEx provides a new platform for interactive phylogenomic data visualization to analyze and interpret the diverse evolutionary histories woven throughout genomes. Hosted on Conda, THEx integrates seamlessly into new or pre-existing workflows. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 has spread worldwide and caused social, economic, and health turmoil. The first genome assembly of SARS-CoV-2 was produced in Wuhan, and it is widely used as a reference. Subsequently, more than a hundred additional SARS-CoV-2 genomes have been sequenced. While the genomes appear to be mostly identical, there are variations. Therefore, an alignment of all available genomes and the derived consensus sequence could be used as a reference, better serving the science community. Variations are significant, but representing them in a genome browser can become, especially if their sequences are largely identical. Here we summarize the variation in one track. Other information not currently found in genome browsers for SARS-CoV-2, such as predicted miRNAs and predicted TRS as well as secondary structure information, were also added as tracks to the consensus genome. We believe that a genome browser based on the consensus sequence is better suited when considering worldwide effects and can become a valuable resource in the combating of COVID-19. The genome browser is available at http://cov.iaba.online.

Drosophila pseudoobscura is a classic model system for the study of evolutionary genetics and genomics. Given this long-standing interest, many genome sequences have accumulated for D. pseudoobscura and closely related species D. persimilis, D. miranda, and D. lowei. To facilitate the exploration of genetic variation within species and comparative genomics across species, we present PseudoBase, a database that couples extensive publicly available genomic data with simple visualization and query tools via an intuitive graphical interface, amenable for use in both research and educational settings. All genetic variation (SNPs and indels) within the database is derived from the same workflow, so variants are easily comparable across data sets. Features include an embedded JBrowse interface, ability to pull out alignments of individual genes/regions, and batch access for gene lists. Here, we introduce PseudoBase, and we demonstrate how this resource facilitates use of extensive genomic data from flies of the Drosophila pseudoobscura subgroup.

Abstract 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/ .

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract Cytosine methylome data is commonly generated through next-generation sequencing, with analyses averaging methylation states of individual reads. We propose an alternative method of analysing single-read methylome data. Using this method, we identify patterns relating to the mechanism of two plant non-CG-methylating enzymes, CMT2 and DRM2. CMT2-methylated regions show higher stochasticity, while DRM2-methylated regions have higher variation among cells. Based on these patterns, we develop a classifier that predicts enzyme activity in different species and tissues. To facilitate further single-read analyses, we develop a genome browser, SRBrowse, optimised for visualising and analysing sequencing data at single-read resolution.

Abstract The REPIC (RNA E PItranscriptome Collection) database records about 10 million peaks called from publicly available m6A-seq and MeRIP-seq data using our unified pipeline. These data were collected from 672 samples of 49 studies, covering 61 cell lines or tissues in 11 organisms. REPIC allows users to query N 6-methyladenosine (m6A) modification sites by specific cell lines or tissue types. In addition, it integrates m6A/MeRIP-seq data with 1418 histone ChIP-seq and 118 DNase-seq data tracks from the ENCODE project in a modern genome browser to present a comprehensive atlas of m6A methylation sites, histone modification sites, and chromatin accessibility regions. REPIC is accessible at https://repicmod.uchicago.edu/repic .

Abstract 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.

The combination of genomic, physiological, and population genetic research has accelerated the understanding and improvement of numerous crops. For nonmodel crops, the lack of interdisciplinary research hinders their improvement. Grain amaranth is an ancient nutritious pseudocereal that has been domesticated three times in different regions of the Americas. We present and employ PopAmaranth, a population genetic genome browser, which provides an accessible representation of the genetic variation of the threegrain amaranth species (Amaranthus hypochondriacus, Amaranthus cruentus, and Amaranthus caudatus) and two wild relatives (Amaranthus hybridus and Amaranthus quitensis) along the A. hypochondriacus reference sequence. We performed population-scale diversity and selection analysis from whole-genome sequencing data of 88 curated genetically and taxonomically unambiguously classified accessions. We employ the platform to show that genetic diversity in the water stress-related MIF1 gene declined during amaranth domestication and provide evidence for convergent saponin reduction between amaranth and quinoa. PopAmaranth is available through amaranthGDB at amaranthgdb.org/popamaranth.html. [ABSTRACT FROM AUTHOR]

Among the livestock species, buffalo remained as an integral part of the Indian rural economy. With the advent of genome sequencing technologies, it became possible to sequence the whole genome of Murrah buffalo. Also, significant amount of information on different genomic elements of buffalo is available at National Centre for Biotechnology Information (NCBI). However, the positions of these elements on the genome are not fully known. In addition, the 3D structures of buffalo proteins are not available and also there exist no browser to visualize important genic elements on buffalo genome. Hence, a study was taken up to develop a web-based information system having information on genomic elements, protein 3-D structures and genome browser. Initially, information on nucleotide and protein sequences were retrieved from NCBI and parsed suitably. Later, the protein structures were predicted, validated, refined and stabilized in silico. An Information System on Buffalo Genome (ISBG) with 3-tier architecture was developed containing the sequence and structural information. ISBG contains complete coding sequences (CDS), Mitochondrial DNAs, 1k upstream regions and Untranslated Regions (UTRs) of buffalo genome. The buffalo genes were also mapped onto the genome. The results revealed that maximum number of genes were found distributed on chromosome 4 followed by chromosome 18, which can also be visualized from the developed genome browser. ISBG can be accessed at http://cabgrid.res.in:8080/bgis. The proposed information system helps animal breeders and biotechnologist in animal improvement.

Genome assembly is cheaper, more accurate and more automated than it has ever been. This is due to a combination of more cost-efficient chemistries, new sequencing technologies and better algorithms. The livestock community has been at the forefront of this new wave of genome assembly, generating some of the highest quality vertebrate genome sequences. Ensembl’s goal is to add functional and comparative annotation to these genomes, through our gene annotation, genomic alignments, gene trees, regulatory, and variation data. We run computationally complex analyses in a high throughput and consistent manner to help accelerate downstream science. Our livestock resources are continuously growing in both breadth and depth. We annotate reference genome assemblies for newly sequenced species and regularly update annotation for existing genomes. We are the only major resource to support the annotation of breeds and other non-reference assemblies. We currently provide resources for 13 pig breeds, maternal and paternal haplotypes for hybrid cattle and various other non-reference or wild type assemblies for livestock species. Here, we describe the livestock data present in Ensembl and provide protocols for how to view data in our genome browser, download via it our FTP site, manipulate it via our tools and interact with it programmatically via our REST API.

Genome assembly is cheaper, more accurate and more automated than it has ever been. This is due to a combination of more cost-efficient chemistries, new sequencing technologies and better algorithms. The livestock community has been at the forefront of this new wave of genome assembly, generating some of the highest quality vertebrate genome sequences. Ensembl's goal is to add functional and comparative annotation to these genomes, through our gene annotation, genomic alignments, gene trees, regulatory, and variation data. We run computationally complex analyses in a high throughput and consistent manner to help accelerate downstream science. Our livestock resources are continuously growing in both breadth and depth. We annotate reference genome assemblies for newly sequenced species and regularly update annotation for existing genomes. We are the only major resource to support the annotation of breeds and other non-reference assemblies. We currently provide resources for 13 pig breeds, maternal and paternal haplotypes for hybrid cattle and various other non-reference or wild type assemblies for livestock species. Here, we describe the livestock data present in Ensembl and provide protocols for how to view data in our genome browser, download via it our FTP site, manipulate it via our tools and interact with it programmatically via our REST API. [ABSTRACT FROM AUTHOR]

Malaria remains a major healthcare risk to growing economies like India, and a chromosome-level reference genome of Anopheles stephensi is critical for successful vector management and understanding of vector evolution using comparative genomics. We report chromosome-level assemblies of an Indian strain, STE2, and a Pakistani strain SDA-500 by combining draft genomes of the two strains using a homology-based iterative approach. The resulting assembly IndV3/PakV3 with L50 of 9/12 and N50 6.3/6.9 Mb had scaffolds long enough for building 90% of the euchromatic regions of the three chromosomes, IndV3s/PakV3s, using low-resolution physical markers and enabled the generation of the next version of genome assemblies, IndV4/PakV4, using HiC data. We have validated these assemblies using contact maps against publicly available HiC raw data from two strains including STE2 and another lab strain of An. stephensi from UCI and compare the quality of the assemblies with other assemblies made available as preprints since the submission of the manuscript. We show that the IndV3s and IndV4 assemblies are sensitive in identifying a homozygous 2Rb inversion in the UCI strain and a 2Rb polymorphism in the STE2 strain. Multiple tandem copies of CYP6a14, 4c1, and 4c21 genes, implicated in insecticide resistance, lie within this inversion locus. Comparison of assembled genomes suggests a variation of 1 in 81 positions between the UCI and STE2 lab strains, 1 in 82 between SDA-500 and UCI strain, and 1 in 113 between SDA-500 and STE2 strains of An. stephensi, which are closer than 1 in 68 variations among individuals from two other lab strains sequenced and reported here. Based on the developmental transcriptome and orthology of all the 54 olfactory receptors (ORs) to those of other Anopheles species, we identify an OR with the potential for host recognition in the genus Anopheles. A comparative analysis of An. stephensi genomes with the completed genomes of a few other Anopheles species suggests limited inter-chromosomal gene flow and loss of synteny within chromosomal arms even among the closely related species.

Malaria remains a major healthcare risk to growing economies like India, and a chromosome-level reference genome of Anopheles stephensi is critical for successful vector management and understanding of vector evolution using comparative genomics. We report chromosome-level assemblies of an Indian strain, STE2, and a Pakistani strain SDA-500 by combining draft genomes of the two strains using a homology-based iterative approach. The resulting assembly IndV3/PakV3 with L50 of 9/12 and N50 6.3/6.9 Mb had scaffolds long enough for building 90% of the euchromatic regions of the three chromosomes, IndV3s/PakV3s, using low-resolution physical markers and enabled the generation of the next version of genome assemblies, IndV4/PakV4, using HiC data. We have validated these assemblies using contact maps against publicly available HiC raw data from two strains including STE2 and another lab strain of An. stephensi from UCI and compare the quality of the assemblies with other assemblies made available as preprints since the submission of the manuscript. We show that the IndV3s and IndV4 assemblies are sensitive in identifying a homozygous 2Rb inversion in the UCI strain and a 2Rb polymorphism in the STE2 strain. Multiple tandem copies of CYP6a14, 4c1, and 4c21 genes, implicated in insecticide resistance, lie within this inversion locus. Comparison of assembled genomes suggests a variation of 1 in 81 positions between the UCI and STE2 lab strains, 1 in 82 between SDA-500 and UCI strain, and 1 in 113 between SDA-500 and STE2 strains of An. stephensi , which are closer than 1 in 68 variations among individuals from two other lab strains sequenced and reported here. Based on the developmental transcriptome and orthology of all the 54 olfactory receptors (ORs) to those of other Anopheles species, we identify an OR with the potential for host recognition in the genus Anopheles. A comparative analysis of An. stephensi genomes with the completed genomes of a few other Anopheles species suggests limited inter-chromosomal gene flow and loss of synteny within chromosomal arms even among the closely related species. [ABSTRACT FROM AUTHOR]

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/. [ABSTRACT FROM AUTHOR]

Researchers seldom look at naked genome assemblies: instead the attributes of DNA sequences are mediated through statistics, annotations and high level summaries. Here we present software that visualizes the bare sequences of whole genome assemblies in a zoomable interface. This can assist in detection of chromosome architecture and contamination by the naked eye through changes in color patterns, in the absence of any other annotation. When available, annotations can be visualized alongside or on top of the naked sequence. Genome alignments can also be visualized, laying two genomes side by side in an alignment and highlighting their differences at nucleotide resolution. FluentDNA gives researchers direct visualization of whole genome assemblies, annotations and alignments, for quality control, hypothesis generation, and communicating results.

Abstract 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.

Researchers seldom look at naked genome assemblies: instead the attributes of DNA sequences are mediated through statistics, annotations and high level summaries. Here we present software that visualizes the bare sequences of whole genome assemblies in a zoomable interface. This can assist in detection of chromosome architecture and contamination by the naked eye through changes in color patterns, in the absence of any other annotation. When available, annotations can be visualized alongside or on top of the naked sequence. Genome alignments can also be visualized, laying two genomes side by side in an alignment and highlighting their differences at nucleotide resolution. FluentDNA gives researchers direct visualization of whole genome assemblies, annotations and alignments, for quality control, hypothesis generation, and communicating results. [ABSTRACT FROM AUTHOR]

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/. • This is a Docker based portable package for genome data analysis and visualization. • Input genome data with different levels of annotations are automatically analyzed. • The schema underneath fetches common data and stores parsed data ready to be queried. • Comparative genomics is performed automatically within the same taxonomic class. [ABSTRACT FROM AUTHOR]

Next-generation sequencing (NGS) technology has become a trend in the genomics research area. There are many software programs and automated pipelines to analyze NGS data, which can ease the pain for traditional scientists who are not familiar with computer programming. However, downstream analyses, such as finding differentially expressed genes or visualizing linkage disequilibrium maps and genome-wide association study (GWAS) data, still remain a challenge. Here, we introduce a dockerized web application written in R using the Shiny platform to visualize pre-analyzed RNA sequencing and GWAS data. In addition, we have integrated a genome browser based on the JBrowse platform and an automated intermediate parsing process required for custom track construction, so that users can easily build and navigate their personal genome tracks with in-house datasets. This application will help scientists perform series of downstream analyses and obtain a more integrative understanding about various types of genomic data by interactively visualizing them with customizable options.

Recent revolutionary advancements in sequencing technologies have made it possible to obtain mass quantities of genome-scale sequence data in a cost-effective manner and have drastically altered molecular biological studies. To utilize these sequence data, genome-wide association studies (GWASs) have become increasingly important. Hence, there is an urgent need to develop a visualization tool that enables efficient data retrieval, integration of GWAS results with diverse information and rapid public release of such large-scale genotypic and phenotypic data. We developed a web-based genome browser TASUKE+ (https://tasuke.dna.affrc.go.jp/), which is equipped with the following functions: (i) interactive GWAS results visualization with genome resequencing data and annotation information, (ii) PCR primer design, (iii) phylogenetic tree reconstruction and (iv) data sharing via the web. GWAS results can be displayed in parallel with polymorphism data, read depths and annotation information in an interactive and scalable manner. Users can design PCR primers for polymorphic sites of interest. In addition, a molecular phylogenetic tree of any region can be reconstructed so that the overall relationship among the examined genomes can be understood intuitively at a glance. All functions are implemented through user-friendly web-based interfaces so that researchers can easily share data with collaborators in remote places without extensive bioinformatics knowledge. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 Listi Wiki (http://listiwiki.uni-goettingen.de/) which stores comprehensive information on the widely used L. monocytogenes reference strain EDG-e. Listi Wiki 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, Listi Wiki combines the most recent annotation of the EDG-e genome with published data on gene essentiality, gene expression and subcellular protein localization. Listi Wiki 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 Subti Wiki. Furthermore, crystallographic information of proteins is made accessible through integration of Protein Structure Database codes and AlphaFold structure predictions. Listi Wiki is an easy-to-use web interface that has been developed with a focus on an intuitive access to all information. Use of Listi Wiki is free of charge and its content can be edited by all members of the scientific community after registration. In our labs, Listi Wiki 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. [ABSTRACT FROM AUTHOR]

Abstract 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.

Abstract 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.

Abstract GIVE is a framework and library for creating portable and personalized genome browsers. It makes visualizing genomic data as easy as building a laboratory homepage.

Prokaryotes are actively studied objects in the scope of genomic regulation. Microbiologists need special tools for complex analysis of data to study and identification of regulatory mechanism in bacteria and archaea.We developed a tool BAC-BROWSER, specifically for visualization and analysis of small prokaryotic genomes. BAC-BROWSER provides tools for different types of analysis to study a wide set of regulatory mechanisms of prokaryotes: -transcriptional regulation by transcription factors (TFs), analysis of TFs, their targets, and binding sites.-other regulatory motifs, promoters, terminators and ribosome binding sites-transcriptional regulation by variation of operon structure, alternative starts or ends of transcription.-non-coding RNAs, antisense RNAs-RNA secondary structure, riboswitches-GC content, GC skew, codon usageBAC-browser incorporated free programs accelerating the verification of obtained results: primer design and oligocalculator, vector visualization, the tool for synthetic gene construction. The program is designed for Windows operating system and freely available for download in http://smdb.rcpcm.org/tools/index.html.

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/ [ABSTRACT FROM AUTHOR]

Prokaryotes are actively studied objects in the scope of genomic regulation. Microbiologists need special tools for complex analysis of data to study and identification of regulatory mechanism in bacteria and archaea. We developed a tool BAC-BROWSER, specifically for visualization and analysis of small prokaryotic genomes. BAC-BROWSER provides tools for different types of analysis to study a wide set of regulatory mechanisms of prokaryotes: - transcriptional regulation by transcription factors (TFs), analysis of TFs, their targets, and binding sites. - other regulatory motifs, promoters, terminators and ribosome binding sites - transcriptional regulation by variation of operon structure, alternative starts or ends of transcription. - non-coding RNAs, antisense RNAs - RNA secondary structure, riboswitches - GC content, GC skew, codon usage BAC-browser incorporated free programs accelerating the verification of obtained results: primer design and oligocalculator, vector visualization, the tool for synthetic gene construction. The program is designed for Windows operating system and freely available for download in http://smdb.rcpcm.org/tools/index.html. [ABSTRACT FROM AUTHOR]