Dataset Information

Colocalization analyses of genomic elements: approaches, recommendations and challenges.

ABSTRACT:

Motivation

Many high-throughput methods produce sets of genomic regions as one of their main outputs. Scientists often use genomic colocalization analysis to interpret such region sets, for example to identify interesting enrichments and to understand the interplay between the underlying biological processes. Although widely used, there is little standardization in how these analyses are performed. Different practices can substantially affect the conclusions of colocalization analyses.

Results

Here, we describe the different approaches and provide recommendations for performing genomic colocalization analysis, while also discussing common methodological challenges that may influence the conclusions. As illustrated by concrete example cases, careful attention to analysis details is needed in order to meet these challenges and to obtain a robust and biologically meaningful interpretation of genomic region set data.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Kanduri C

PROVIDER: S-EPMC6499241 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Colocalization analyses of genomic elements: approaches, recommendations and challenges.

Kanduri Chakravarthi C Bock Christoph C Gundersen Sveinung S Hovig Eivind E Sandve Geir Kjetil GK

Bioinformatics (Oxford, England) 20190501 9

<h4>Motivation</h4>Many high-throughput methods produce sets of genomic regions as one of their main outputs. Scientists often use genomic colocalization analysis to interpret such region sets, for example to identify interesting enrichments and to understand the interplay between the underlying biological processes. Although widely used, there is little standardization in how these analyses are performed. Different practices can substantially affect the conclusions of colocalization analyses.<h ...[more]

PMID: 30307532

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Project description:Next-generation sequencing techniques such as ChIP-seq allow researchers to investigate the genomic position of nuclear components and events. These experiments provide researchers with thousands of regions of interest to probe in order to identify biological relevance. As the cost of sequencing decreases and its robustness increases, more and more researchers turn to genome-wide studies to better understand the genomic elements they are studying. One way to interpret the output of sequencing studies is to investigate how the element of interest localizes in relationship to genome annotations and the binding of other nuclear components. Colocalization of genomic features could indicate cooperation and provide evidence for more detailed investigations. Although there are several existing tools for visualizing and analyzing colocalization, either they are difficult to use for experimental researchers, not well maintained, or without measurements for colocalization strength. Here we describe an online tool, ColoWeb, designed to allow experimentalists to compare their datasets to existing genomic features in order to generate hypotheses about biological interactions easily and quickly.ColoWeb is a web-based service for evaluating the colocation of genomic features. Users submit genomic regions of interest, for example, a set of locations from a ChIP-seq analysis. ColoWeb compares the submitted regions of interest to the location of other genomic features such as transcription factors and chromatin modifiers. To facilitate comparisons among various genomic features, the output consists of both graphical representations and quantitative measures of the degree of colocalization between user's genomic regions and selected features. Frequent colocation may indicate a biological relationship.ColoWeb is a biologist-friendly web service that can quickly provide an assessment of thousands of genomic regions to identify colocated genomic features. ColoWeb is freely available at: http://projects.insilico.us.com/ColoWeb .

Project description:BACKGROUND:We benchmarked the hybrid assembly approaches of MaSuRCA, SPAdes, and Unicycler for bacterial pathogens using Illumina and Oxford Nanopore sequencing by determining genome completeness and accuracy, antimicrobial resistance (AMR), virulence potential, multilocus sequence typing (MLST), phylogeny, and pan genome. Ten bacterial species (10 strains) were tested for simulated reads of both mediocre- and low-quality, whereas 11 bacterial species (12 strains) were tested for real reads. RESULTS:Unicycler performed the best for achieving contiguous genomes, closely followed by MaSuRCA, while all SPAdes assemblies were incomplete. MaSuRCA was less tolerant of low-quality long reads than SPAdes and Unicycler. The hybrid assemblies of five antimicrobial-resistant strains with simulated reads provided consistent AMR genotypes with the reference genomes. The MaSuRCA assembly of Staphylococcus aureus with real reads contained msr(A) and tet(K), while the reference genome and SPAdes and Unicycler assemblies harbored blaZ. The AMR genotypes of the reference genomes and hybrid assemblies were consistent for the other five antimicrobial-resistant strains with real reads. The numbers of virulence genes in all hybrid assemblies were similar to those of the reference genomes, irrespective of simulated or real reads. Only one exception existed that the reference genome and hybrid assemblies of Pseudomonas aeruginosa with mediocre-quality long reads carried 241 virulence genes, whereas 184 virulence genes were identified in the hybrid assemblies of low-quality long reads. The MaSuRCA assemblies of Escherichia coli O157:H7 and Salmonella Typhimurium with mediocre-quality long reads contained 126 and 118 virulence genes, respectively, while 110 and 107 virulence genes were detected in their MaSuRCA assemblies of low-quality long reads, respectively. All approaches performed well in our MLST and phylogenetic analyses. The pan genomes of the hybrid assemblies of S. Typhimurium with mediocre-quality long reads were similar to that of the reference genome, while SPAdes and Unicycler were more tolerant of low-quality long reads than MaSuRCA for the pan-genome analysis. All approaches functioned well in the pan-genome analysis of Campylobacter jejuni with real reads. CONCLUSIONS:Our research demonstrates the hybrid assembly pipeline of Unicycler as a superior approach for genomic analyses of bacterial pathogens using Illumina and Oxford Nanopore sequencing.

Dataset Information

Colocalization analyses of genomic elements: approaches, recommendations and challenges.

Motivation

Results

Supplementary information

Publications

Colocalization analyses of genomic elements: approaches, recommendations and challenges.

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