Limits...
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.

Show MeSH

Related in: MedlinePlus

Predicting structural variation from new junction and missing coverage evidence. a) Types of structural variation for which breseq can predict precise mutational events from new junction sequences (JC) and missing read coverage (MC) evidence are shown in the context of the reference and mutant genomes. For JC evidence, the matched sequence on each side is shown as a solid arrow with a dashed line connecting the two sides. Orange JC arrows indicate that this side of a new sequence junction maps equally well to multiple locations in the reference genome (i.e., the location is ambiguous). Details for the procedure used in each case are described in the text. b) Mobile element insertions may require additional fields to describe the precise sequence change caused by insertion of a new copy. These may include a target site duplication and deleted or inserted bases on the margins of the new element copy, as shown.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig7: Predicting structural variation from new junction and missing coverage evidence. a) Types of structural variation for which breseq can predict precise mutational events from new junction sequences (JC) and missing read coverage (MC) evidence are shown in the context of the reference and mutant genomes. For JC evidence, the matched sequence on each side is shown as a solid arrow with a dashed line connecting the two sides. Orange JC arrows indicate that this side of a new sequence junction maps equally well to multiple locations in the reference genome (i.e., the location is ambiguous). Details for the procedure used in each case are described in the text. b) Mobile element insertions may require additional fields to describe the precise sequence change caused by insertion of a new copy. These may include a target site duplication and deleted or inserted bases on the margins of the new element copy, as shown.

Mentions: breseq predicts and annotates several types of mutations that produce structural variation by considering new junction (JC) and missing coverage (MC) evidence together with reference sequence annotations of the locations of mobile elements (FigureĀ 7a). This automated integration of information results in precise (i.e., down to the exact nucleotide) and biologically meaningful (e.g., insertion of a new copy of the transposable element IS150 with duplication of three target site base pairs) predictions of how a sequence is altered in the sample relative to the reference that would be laborious to reconstruct from the output of other programs that could potentially be used to predict SV in microbial genomes. The predictions by breseq include:Figure 7


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)

Predicting structural variation from new junction and missing coverage evidence. a) Types of structural variation for which breseq can predict precise mutational events from new junction sequences (JC) and missing read coverage (MC) evidence are shown in the context of the reference and mutant genomes. For JC evidence, the matched sequence on each side is shown as a solid arrow with a dashed line connecting the two sides. Orange JC arrows indicate that this side of a new sequence junction maps equally well to multiple locations in the reference genome (i.e., the location is ambiguous). Details for the procedure used in each case are described in the text. b) Mobile element insertions may require additional fields to describe the precise sequence change caused by insertion of a new copy. These may include a target site duplication and deleted or inserted bases on the margins of the new element copy, as shown.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig7: Predicting structural variation from new junction and missing coverage evidence. a) Types of structural variation for which breseq can predict precise mutational events from new junction sequences (JC) and missing read coverage (MC) evidence are shown in the context of the reference and mutant genomes. For JC evidence, the matched sequence on each side is shown as a solid arrow with a dashed line connecting the two sides. Orange JC arrows indicate that this side of a new sequence junction maps equally well to multiple locations in the reference genome (i.e., the location is ambiguous). Details for the procedure used in each case are described in the text. b) Mobile element insertions may require additional fields to describe the precise sequence change caused by insertion of a new copy. These may include a target site duplication and deleted or inserted bases on the margins of the new element copy, as shown.
Mentions: breseq predicts and annotates several types of mutations that produce structural variation by considering new junction (JC) and missing coverage (MC) evidence together with reference sequence annotations of the locations of mobile elements (FigureĀ 7a). This automated integration of information results in precise (i.e., down to the exact nucleotide) and biologically meaningful (e.g., insertion of a new copy of the transposable element IS150 with duplication of three target site base pairs) predictions of how a sequence is altered in the sample relative to the reference that would be laborious to reconstruct from the output of other programs that could potentially be used to predict SV in microbial genomes. The predictions by breseq include:Figure 7

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