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A comprehensive and user-friendly framework for 3D-data visualisation in invertebrates and other organisms.

ABSTRACT: Methods for 3D-imaging of biological samples are experiencing unprecedented development, with tools such as X-ray micro-computed tomography (?CT) becoming more accessible to biologists. These techniques are inherently suited to small subjects and can simultaneously image both external and internal morphology, thus offering considerable benefits for invertebrate research. However, methods for visualising 3D-data are trailing behind the development of tools for generating such data. Our aim in this article is to make the processing, visualisation and presentation of 3D-data easier, thereby encouraging more researchers to utilise 3D-imaging. Here, we present a comprehensive workflow for manipulating and visualising 3D-data, including basic and advanced options for producing images, videos and interactive 3D-PDFs, from both volume and surface-mesh renderings. We discuss the importance of visualisation for quantitative analysis of invertebrate morphology from 3D-data, and provide example figures illustrating the different options for generating 3D-figures for publication. As more biology journals adopt 3D-PDFs as a standard option, research on microscopic invertebrates and other organisms can be presented in high-resolution 3D-figures, enhancing the way we communicate science.

SUBMITTER: Semple TL

PROVIDER: S-EPMC6590182 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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A comprehensive and user-friendly framework for 3D-data visualisation in invertebrates and other organisms.

Semple Thomas L TL Peakall Rod R Tatarnic Nikolai J NJ

Journal of morphology 20190201 2

Methods for 3D-imaging of biological samples are experiencing unprecedented development, with tools such as X-ray micro-computed tomography (μCT) becoming more accessible to biologists. These techniques are inherently suited to small subjects and can simultaneously image both external and internal morphology, thus offering considerable benefits for invertebrate research. However, methods for visualising 3D-data are trailing behind the development of tools for generating such data. Our aim in thi ...[more]

PMID: 30653713

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Project description:Genotyping by re-sequencing has become a standard approach to estimate single nucleotide polymorphism (SNP) diversity, haplotype structure and the biodiversity and has been defined as an efficient approach to address geographical population genomics of several model species. To access core SNPs and insertion/deletion polymorphisms (indels), and to infer the phyletic patterns of speciation, most such approaches map short reads to the reference genome. Variant calling is important to establish patterns of genome-wide association studies (GWAS) for quantitative trait loci (QTLs), and to determine the population and haplotype structure based on SNPs, thus allowing content-dependent trait and evolutionary analysis. Several tools have been developed to investigate such polymorphisms as well as more complex genomic rearrangements such as copy number variations, presence/absence variations and large deletions. The programs available for this purpose have different strengths (e.g. accuracy, sensitivity and specificity) and weaknesses (e.g. low computation speed, complex installation procedure and absence of a user-friendly interface). Here we introduce Altools, a software package that is easy to install and use, which allows the precise detection of polymorphisms and structural variations.Altools uses the BWA/SAMtools/VarScan pipeline to call SNPs and indels, and the dnaCopy algorithm to achieve genome segmentation according to local coverage differences in order to identify copy number variations. It also uses insert size information from the alignment of paired-end reads and detects potential large deletions. A double mapping approach (BWA/BLASTn) identifies precise breakpoints while ensuring rapid elaboration. Finally, Altools implements several processes that yield deeper insight into the genes affected by the detected polymorphisms. Altools was used to analyse both simulated and real next-generation sequencing (NGS) data and performed satisfactorily in terms of positive predictive values, sensitivity, the identification of large deletion breakpoints and copy number detection.Altools is fast, reliable and easy to use for the mining of NGS data. The software package also attempts to link identified polymorphisms and structural variants to their biological functions thus providing more valuable information than similar tools.

Project description:BackgroundHigh-throughput sequencing has increased the number of available microbial genomes recovered from isolates, single cells, and metagenomes. Accordingly, fast and comprehensive functional gene annotation pipelines are needed to analyze and compare these genomes. Although several approaches exist for genome annotation, these are typically not designed for easy incorporation into analysis pipelines, do not combine results from different annotation databases or offer easy-to-use summaries of metabolic reconstructions, and typically require large amounts of computing power for high-throughput analysis not available to the average user.ResultsHere, we introduce MicrobeAnnotator, a fully automated, easy-to-use pipeline for the comprehensive functional annotation of microbial genomes that combines results from several reference protein databases and returns the matching annotations together with key metadata such as the interlinked identifiers of matching reference proteins from multiple databases [KEGG Orthology (KO), Enzyme Commission (E.C.), Gene Ontology (GO), Pfam, and InterPro]. Further, the functional annotations are summarized into Kyoto Encyclopedia of Genes and Genomes (KEGG) modules as part of a graphical output (heatmap) that allows the user to quickly detect differences among (multiple) query genomes and cluster the genomes based on their metabolic similarity. MicrobeAnnotator is implemented in Python 3 and is freely available under an open-source Artistic License 2.0 from https://github.com/cruizperez/MicrobeAnnotator .ConclusionsWe demonstrated the capabilities of MicrobeAnnotator by annotating 100 Escherichia coli and 78 environmental Candidate Phyla Radiation (CPR) bacterial genomes and comparing the results to those of other popular tools. We showed that the use of multiple annotation databases allows MicrobeAnnotator to recover more annotations per genome compared to faster tools that use reduced databases and is computationally efficient for use in personal computers. The output of MicrobeAnnotator can be easily incorporated into other analysis pipelines while the results of other annotation tools can be seemingly incorporated into MicrobeAnnotator to generate summary plots.

Dataset Information

A comprehensive and user-friendly framework for 3D-data visualisation in invertebrates and other organisms.

Publications

A comprehensive and user-friendly framework for 3D-data visualisation in invertebrates and other organisms.

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