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Accurate detection of recombinant breakpoints in whole-genome alignments.

Westesson O, Holmes I - PLoS Comput. Biol. (2009)

Bottom Line: Using a combined algorithm for estimating tree structure and hidden Markov model parameters, our program detects changes in phylogenetic tree topology over a multiple sequence alignment.We show that we are not only able to detect recombinant regions of vastly different sizes but also the location of breakpoints with great accuracy.In all cases, we confirm the breakpoint predictions of previous studies, and in many cases we offer novel predictions.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioengineering, University of California Berkeley, Berkeley, California, United States of America.

ABSTRACT
We propose a novel method for detecting sites of molecular recombination in multiple alignments. Our approach is a compromise between previous extremes of computationally prohibitive but mathematically rigorous methods and imprecise heuristic methods. Using a combined algorithm for estimating tree structure and hidden Markov model parameters, our program detects changes in phylogenetic tree topology over a multiple sequence alignment. We evaluate our method on benchmark datasets from previous studies on two recombinant pathogens, Neisseria and HIV-1, as well as simulated data. We show that we are not only able to detect recombinant regions of vastly different sizes but also the location of breakpoints with great accuracy. We show that our method does well inferring recombination breakpoints while at the same time maintaining practicality for larger datasets. In all cases, we confirm the breakpoint predictions of previous studies, and in many cases we offer novel predictions.

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Brazilian strain BREPM16704.We confirm breakpoints near 1322, 2571, and 5462 (red) and predict recombinations in 9281–9405 and 1017–1085 (green). Trees trained in hidden states are shown below the plot.
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pcbi-1000318-g007: Brazilian strain BREPM16704.We confirm breakpoints near 1322, 2571, and 5462 (red) and predict recombinations in 9281–9405 and 1017–1085 (green). Trees trained in hidden states are shown below the plot.

Mentions: Strain BREPM16704 was previously predicted to have four breakpoints, which we recovered with remarkably high posterior probabilities for the tree-states. Figure 7 shows our results with previous predictions in red. A new region, at 9281–9405, shows high posterior probability and is common to BREPM11871 and CRF12BF [20], making a strong case for a recombination hotspot.


Accurate detection of recombinant breakpoints in whole-genome alignments.

Westesson O, Holmes I - PLoS Comput. Biol. (2009)

Brazilian strain BREPM16704.We confirm breakpoints near 1322, 2571, and 5462 (red) and predict recombinations in 9281–9405 and 1017–1085 (green). Trees trained in hidden states are shown below the plot.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2651022&req=5

pcbi-1000318-g007: Brazilian strain BREPM16704.We confirm breakpoints near 1322, 2571, and 5462 (red) and predict recombinations in 9281–9405 and 1017–1085 (green). Trees trained in hidden states are shown below the plot.
Mentions: Strain BREPM16704 was previously predicted to have four breakpoints, which we recovered with remarkably high posterior probabilities for the tree-states. Figure 7 shows our results with previous predictions in red. A new region, at 9281–9405, shows high posterior probability and is common to BREPM11871 and CRF12BF [20], making a strong case for a recombination hotspot.

Bottom Line: Using a combined algorithm for estimating tree structure and hidden Markov model parameters, our program detects changes in phylogenetic tree topology over a multiple sequence alignment.We show that we are not only able to detect recombinant regions of vastly different sizes but also the location of breakpoints with great accuracy.In all cases, we confirm the breakpoint predictions of previous studies, and in many cases we offer novel predictions.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioengineering, University of California Berkeley, Berkeley, California, United States of America.

ABSTRACT
We propose a novel method for detecting sites of molecular recombination in multiple alignments. Our approach is a compromise between previous extremes of computationally prohibitive but mathematically rigorous methods and imprecise heuristic methods. Using a combined algorithm for estimating tree structure and hidden Markov model parameters, our program detects changes in phylogenetic tree topology over a multiple sequence alignment. We evaluate our method on benchmark datasets from previous studies on two recombinant pathogens, Neisseria and HIV-1, as well as simulated data. We show that we are not only able to detect recombinant regions of vastly different sizes but also the location of breakpoints with great accuracy. We show that our method does well inferring recombination breakpoints while at the same time maintaining practicality for larger datasets. In all cases, we confirm the breakpoint predictions of previous studies, and in many cases we offer novel predictions.

Show MeSH
Related in: MedlinePlus