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Identifying structural variation in haploid microbial genomes from short-read resequencing data using breseq.

Barrick JE, Colburn G, Deatherage DE, Traverse CC, Strand MD, Borges JJ, Knoester DB, Reba A, Meyer AG - BMC Genomics (2014)

Bottom Line: They typically disregard information in reads mapping to repeat sequences, and significant post-processing and manual examination of their output is often required to rule out false-positive predictions and precisely describe mutational events.Finally, breseq combines predictions of new junctions and deleted chromosomal regions to output biologically relevant descriptions of mutations and their effects on genes.In these cases, breseq can discover mutations that may be responsible for important or unintended changes in genomes that might otherwise go undetected.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Biosciences, Institute for Cellular and Molecular Biology, Center for Systems and Synthetic Biology, Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, TX 78712, USA. jbarrick@cm.utexas.edu.

ABSTRACT

Background: Mutations that alter chromosomal structure play critical roles in evolution and disease, including in the origin of new lifestyles and pathogenic traits in microbes. Large-scale rearrangements in genomes are often mediated by recombination events involving new or existing copies of mobile genetic elements, recently duplicated genes, or other repetitive sequences. Most current software programs for predicting structural variation from short-read DNA resequencing data are intended primarily for use on human genomes. They typically disregard information in reads mapping to repeat sequences, and significant post-processing and manual examination of their output is often required to rule out false-positive predictions and precisely describe mutational events.

Results: We have implemented an algorithm for identifying structural variation from DNA resequencing data as part of the breseq computational pipeline for predicting mutations in haploid microbial genomes. Our method evaluates the support for new sequence junctions present in a clonal sample from split-read alignments to a reference genome, including matches to repeat sequences. Then, it uses a statistical model of read coverage evenness to accept or reject these predictions. Finally, breseq combines predictions of new junctions and deleted chromosomal regions to output biologically relevant descriptions of mutations and their effects on genes. We demonstrate the performance of breseq on simulated Escherichia coli genomes with deletions generating unique breakpoint sequences, new insertions of mobile genetic elements, and deletions mediated by mobile elements. Then, we reanalyze data from an E. coli K-12 mutation accumulation evolution experiment in which structural variation was not previously identified. Transposon insertions and large-scale chromosomal changes detected by breseq account for ~25% of spontaneous mutations in this strain. In all cases, we find that breseq is able to reliably predict structural variation with modest read-depth coverage of the reference genome (>40-fold).

Conclusions: Using breseq to predict structural variation should be useful for studies of microbial epidemiology, experimental evolution, synthetic biology, and genetics when a reference genome for a closely related strain is available. In these cases, breseq can discover mutations that may be responsible for important or unintended changes in genomes that might otherwise go undetected.

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Reanalysis of evolvedE. colisamples for structural variation. a) Summary of mutations predicted by breseq in 21 clones sequenced after 6,000 generations of growth in a mutation accumulation experiment [19]. These samples were previously analyzed for single-base substitutions and small indels. The line extending across the bars separates single-base substitutions and indels from mutations affecting more bases that were classified as structural variants. Full details for all mutations predicted in the ancestor of this experiment and each evolved lineage are provided in Additional file 2. b) Overall representation of the different types of structural variants predicted from combinations of new junction (JC) and missing coverage (MC) evidence across all 21 genomes. One structural variant was predicted from spurious read alignment (RA) evidence, as described in the text.
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Fig10: Reanalysis of evolvedE. colisamples for structural variation. a) Summary of mutations predicted by breseq in 21 clones sequenced after 6,000 generations of growth in a mutation accumulation experiment [19]. These samples were previously analyzed for single-base substitutions and small indels. The line extending across the bars separates single-base substitutions and indels from mutations affecting more bases that were classified as structural variants. Full details for all mutations predicted in the ancestor of this experiment and each evolved lineage are provided in Additional file 2. b) Overall representation of the different types of structural variants predicted from combinations of new junction (JC) and missing coverage (MC) evidence across all 21 genomes. One structural variant was predicted from spurious read alignment (RA) evidence, as described in the text.

Mentions: Overall, we found that 24% of the 225 mutations predicted in the mutation accumulation experiment led to structural variation in the E. coli chromosome (Figure 10, Additional file 2). Insertions of new copies of insertion sequence elements, particularly IS5, dominated among these events. This reanalysis enables us to estimate a spontaneous rate of SV mutations, which accounts for all mutations that are not single-base substitutions or short indels, in E. coli K-12 MG1655 of 0.00042 mutations per genome per generation (with a Poisson 95% confidence interval from 0.00032–0.00055). Of the SV predicted, 92% of the events were fully predicted by breseq without the need for any manual examination of “orphan” pieces of evidence to resolve them into precise molecular events. Thus, breseq is a useful tool for discovering mutations that cause structural variation in order to more comprehensively understand how microbial genomes evolve.Figure 10


Identifying structural variation in haploid microbial genomes from short-read resequencing data using breseq.

Barrick JE, Colburn G, Deatherage DE, Traverse CC, Strand MD, Borges JJ, Knoester DB, Reba A, Meyer AG - BMC Genomics (2014)

Reanalysis of evolvedE. colisamples for structural variation. a) Summary of mutations predicted by breseq in 21 clones sequenced after 6,000 generations of growth in a mutation accumulation experiment [19]. These samples were previously analyzed for single-base substitutions and small indels. The line extending across the bars separates single-base substitutions and indels from mutations affecting more bases that were classified as structural variants. Full details for all mutations predicted in the ancestor of this experiment and each evolved lineage are provided in Additional file 2. b) Overall representation of the different types of structural variants predicted from combinations of new junction (JC) and missing coverage (MC) evidence across all 21 genomes. One structural variant was predicted from spurious read alignment (RA) evidence, as described in the text.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4300727&req=5

Fig10: Reanalysis of evolvedE. colisamples for structural variation. a) Summary of mutations predicted by breseq in 21 clones sequenced after 6,000 generations of growth in a mutation accumulation experiment [19]. These samples were previously analyzed for single-base substitutions and small indels. The line extending across the bars separates single-base substitutions and indels from mutations affecting more bases that were classified as structural variants. Full details for all mutations predicted in the ancestor of this experiment and each evolved lineage are provided in Additional file 2. b) Overall representation of the different types of structural variants predicted from combinations of new junction (JC) and missing coverage (MC) evidence across all 21 genomes. One structural variant was predicted from spurious read alignment (RA) evidence, as described in the text.
Mentions: Overall, we found that 24% of the 225 mutations predicted in the mutation accumulation experiment led to structural variation in the E. coli chromosome (Figure 10, Additional file 2). Insertions of new copies of insertion sequence elements, particularly IS5, dominated among these events. This reanalysis enables us to estimate a spontaneous rate of SV mutations, which accounts for all mutations that are not single-base substitutions or short indels, in E. coli K-12 MG1655 of 0.00042 mutations per genome per generation (with a Poisson 95% confidence interval from 0.00032–0.00055). Of the SV predicted, 92% of the events were fully predicted by breseq without the need for any manual examination of “orphan” pieces of evidence to resolve them into precise molecular events. Thus, breseq is a useful tool for discovering mutations that cause structural variation in order to more comprehensively understand how microbial genomes evolve.Figure 10

Bottom Line: They typically disregard information in reads mapping to repeat sequences, and significant post-processing and manual examination of their output is often required to rule out false-positive predictions and precisely describe mutational events.Finally, breseq combines predictions of new junctions and deleted chromosomal regions to output biologically relevant descriptions of mutations and their effects on genes.In these cases, breseq can discover mutations that may be responsible for important or unintended changes in genomes that might otherwise go undetected.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Biosciences, Institute for Cellular and Molecular Biology, Center for Systems and Synthetic Biology, Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, TX 78712, USA. jbarrick@cm.utexas.edu.

ABSTRACT

Background: Mutations that alter chromosomal structure play critical roles in evolution and disease, including in the origin of new lifestyles and pathogenic traits in microbes. Large-scale rearrangements in genomes are often mediated by recombination events involving new or existing copies of mobile genetic elements, recently duplicated genes, or other repetitive sequences. Most current software programs for predicting structural variation from short-read DNA resequencing data are intended primarily for use on human genomes. They typically disregard information in reads mapping to repeat sequences, and significant post-processing and manual examination of their output is often required to rule out false-positive predictions and precisely describe mutational events.

Results: We have implemented an algorithm for identifying structural variation from DNA resequencing data as part of the breseq computational pipeline for predicting mutations in haploid microbial genomes. Our method evaluates the support for new sequence junctions present in a clonal sample from split-read alignments to a reference genome, including matches to repeat sequences. Then, it uses a statistical model of read coverage evenness to accept or reject these predictions. Finally, breseq combines predictions of new junctions and deleted chromosomal regions to output biologically relevant descriptions of mutations and their effects on genes. We demonstrate the performance of breseq on simulated Escherichia coli genomes with deletions generating unique breakpoint sequences, new insertions of mobile genetic elements, and deletions mediated by mobile elements. Then, we reanalyze data from an E. coli K-12 mutation accumulation evolution experiment in which structural variation was not previously identified. Transposon insertions and large-scale chromosomal changes detected by breseq account for ~25% of spontaneous mutations in this strain. In all cases, we find that breseq is able to reliably predict structural variation with modest read-depth coverage of the reference genome (>40-fold).

Conclusions: Using breseq to predict structural variation should be useful for studies of microbial epidemiology, experimental evolution, synthetic biology, and genetics when a reference genome for a closely related strain is available. In these cases, breseq can discover mutations that may be responsible for important or unintended changes in genomes that might otherwise go undetected.

Show MeSH
Related in: MedlinePlus