Tetranucleotide usage highlights genomic heterogeneity among mycobacteriophages
Identifieur interne : 000C68 ( Pmc/Curation ); précédent : 000C67; suivant : 000C69Tetranucleotide usage highlights genomic heterogeneity among mycobacteriophages
Auteurs : Benjamin Siranosian [États-Unis] ; Sudheesha Perera [États-Unis] ; Edward Williams [États-Unis] ; Chen Ye [États-Unis] ; Christopher De Graffenried [États-Unis] ; Peter Shank [États-Unis]Source :
- F1000Research [ 2046-1402 ] ; 2015.
Abstract
The genomic sequences of mycobacteriophages, phages infecting mycobacterial hosts, are diverse and mosaic. Mycobacteriophages often share little nucleotide similarity, but most of them have been grouped into lettered clusters and further into subclusters. Traditionally, mycobacteriophage genomes are analyzed based on sequence alignment or knowledge of gene content. However, these approaches are computationally expensive and can be ineffective for significantly diverged sequences. As an alternative to alignment-based genome analysis, we evaluated tetranucleotide usage in mycobacteriophage genomes. These methods make it easier to characterize features of the mycobacteriophage population at many scales.
We computed tetranucleotide usage deviation (TUD), the ratio of observed counts of 4-mers in a genome to the expected count under a null model. TUD values are comparable between members of a phage subcluster and distinct between subclusters. With few exceptions, neighbor joining phylogenetic trees and hierarchical clustering dendrograms constructed using TUD values place phages in a monophyletic clade with members of the same subcluster. Regions in a genome with exceptional TUD values can point to interesting features of genomic architecture. Finally, we found that subcluster B3 mycobacteriophages contain significantly overrepresented 4-mers and 6-mers that are atypical of phage genomes.
Statistics based on tetranucleotide usage support established clustering of mycobacteriophages and can uncover interesting relationships within and between sequenced phage genomes. These methods are efficient to compute and do not require sequence alignment or knowledge of gene content. The code to download mycobacteriophage genome sequences and reproduce our analysis is freely available at
Url:
DOI: 10.12688/f1000research.6077.2
PubMed: 27134721
PubMed Central: 4841201
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<front><div type="abstract" xml:lang="en"><p><bold>Background</bold>
</p>
<p>The genomic sequences of mycobacteriophages, phages infecting mycobacterial hosts, are diverse and mosaic. Mycobacteriophages often share little nucleotide similarity, but most of them have been grouped into lettered clusters and further into subclusters. Traditionally, mycobacteriophage genomes are analyzed based on sequence alignment or knowledge of gene content. However, these approaches are computationally expensive and can be ineffective for significantly diverged sequences. As an alternative to alignment-based genome analysis, we evaluated tetranucleotide usage in mycobacteriophage genomes. These methods make it easier to characterize features of the mycobacteriophage population at many scales.</p>
<p><bold>Description</bold>
</p>
<p>We computed tetranucleotide usage deviation (TUD), the ratio of observed counts of 4-mers in a genome to the expected count under a null model. TUD values are comparable between members of a phage subcluster and distinct between subclusters. With few exceptions, neighbor joining phylogenetic trees and hierarchical clustering dendrograms constructed using TUD values place phages in a monophyletic clade with members of the same subcluster. Regions in a genome with exceptional TUD values can point to interesting features of genomic architecture. Finally, we found that subcluster B3 mycobacteriophages contain significantly overrepresented 4-mers and 6-mers that are atypical of phage genomes.</p>
<p><bold>Conclusions</bold>
</p>
<p>Statistics based on tetranucleotide usage support established clustering of mycobacteriophages and can uncover interesting relationships within and between sequenced phage genomes. These methods are efficient to compute and do not require sequence alignment or knowledge of gene content. The code to download mycobacteriophage genome sequences and reproduce our analysis is freely available at
<ext-link ext-link-type="uri" xlink:href="https://github.com/bsiranosian/tango_final">https://github.com/bsiranosian/tango_final</ext-link>
.</p>
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<article-id pub-id-type="doi">10.12688/f1000research.6077.2</article-id>
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<title-group><article-title>Tetranucleotide usage highlights genomic heterogeneity among mycobacteriophages</article-title>
<fn-group content-type="pub-status"><fn><p>[version 2; referees: 2 approved]</p>
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<given-names>Benjamin</given-names>
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<given-names>Sudheesha</given-names>
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<contrib contrib-type="author"><name><surname>Shank</surname>
<given-names>Peter</given-names>
</name>
<xref ref-type="aff" rid="a3">3</xref>
</contrib>
<aff id="a1"><label>1</label>
Center for Computational Molecular Biology, Brown University, Providence, RI, 02912, USA</aff>
<aff id="a2"><label>2</label>
Division of Biology and Medicine, Brown University, Providence, RI, 02912, USA</aff>
<aff id="a3"><label>3</label>
Department of Molecular Microbiology and Immunology, Brown University, Providence, RI, 02912, USA</aff>
</contrib-group>
<author-notes><corresp id="c1"><label>a</label>
<email xlink:href="mailto:benjamin_siranosian@alumni.brown.edu">benjamin_siranosian@alumni.brown.edu</email>
</corresp>
<fn fn-type="con"><p>BS designed the study. BS, SP, EW and CY performed the analysis. BS and CY prepared the figures. BS, SP, EW, CDG and PS wrote the manuscript.</p>
</fn>
<fn fn-type="COI-statement"><p><bold>Competing interests: </bold>
No competing interests were disclosed.</p>
</fn>
</author-notes>
<pub-date pub-type="epub"><day>30</day>
<month>10</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="collection"><year>2015</year>
</pub-date>
<volume>4</volume>
<elocation-id>36</elocation-id>
<history><date date-type="accepted"><day>28</day>
<month>10</month>
<year>2015</year>
</date>
</history>
<permissions><copyright-statement>Copyright: © 2015 Siranosian B et al.</copyright-statement>
<copyright-year>2015</copyright-year>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<self-uri content-type="pdf" xlink:type="simple" xlink:href="f1000research-4-7828.pdf"></self-uri>
<abstract><p><bold>Background</bold>
</p>
<p>The genomic sequences of mycobacteriophages, phages infecting mycobacterial hosts, are diverse and mosaic. Mycobacteriophages often share little nucleotide similarity, but most of them have been grouped into lettered clusters and further into subclusters. Traditionally, mycobacteriophage genomes are analyzed based on sequence alignment or knowledge of gene content. However, these approaches are computationally expensive and can be ineffective for significantly diverged sequences. As an alternative to alignment-based genome analysis, we evaluated tetranucleotide usage in mycobacteriophage genomes. These methods make it easier to characterize features of the mycobacteriophage population at many scales.</p>
<p><bold>Description</bold>
</p>
<p>We computed tetranucleotide usage deviation (TUD), the ratio of observed counts of 4-mers in a genome to the expected count under a null model. TUD values are comparable between members of a phage subcluster and distinct between subclusters. With few exceptions, neighbor joining phylogenetic trees and hierarchical clustering dendrograms constructed using TUD values place phages in a monophyletic clade with members of the same subcluster. Regions in a genome with exceptional TUD values can point to interesting features of genomic architecture. Finally, we found that subcluster B3 mycobacteriophages contain significantly overrepresented 4-mers and 6-mers that are atypical of phage genomes.</p>
<p><bold>Conclusions</bold>
</p>
<p>Statistics based on tetranucleotide usage support established clustering of mycobacteriophages and can uncover interesting relationships within and between sequenced phage genomes. These methods are efficient to compute and do not require sequence alignment or knowledge of gene content. The code to download mycobacteriophage genome sequences and reproduce our analysis is freely available at
<ext-link ext-link-type="uri" xlink:href="https://github.com/bsiranosian/tango_final">https://github.com/bsiranosian/tango_final</ext-link>
.</p>
</abstract>
<kwd-group kwd-group-type="author"><kwd>mycobacteriophages, computed</kwd>
<kwd>tetranucleotide</kwd>
<kwd>usage</kwd>
<kwd>deviation, genome</kwd>
<kwd>sequences</kwd>
</kwd-group>
<funding-group><award-group id="fund-1"><funding-source>Brown University</funding-source>
</award-group>
<award-group id="fund-2"><funding-source>HHMI SEA-PHAGES program</funding-source>
</award-group>
<funding-statement>This work was funded by Brown University Biology Undergraduate Education and the HHMI SEA-PHAGES program.</funding-statement>
</funding-group>
</article-meta>
<notes notes-type="version-changes"><sec sec-type="version-changes"><label>Revised</label>
<title>Amendments from Version 1</title>
<p>This version addresses the review by Dr. Bonham-Carter. Changes have been made to make the methods section more clear, and I have included an example figure to show the calculation of TUD on a small sequence. The results from the paper remain unchanged.</p>
</sec>
</notes>
</front>
<sub-article id="report13337" article-type="peer-review"><front-stub><article-id pub-id-type="doi">10.5256/f1000research.7828.r13337</article-id>
<title-group><article-title>Referee response for version 2</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Martin</surname>
<given-names>David</given-names>
</name>
<xref ref-type="aff" rid="r13337a1">1</xref>
<role>Referee</role>
</contrib>
<aff id="r13337a1"><label>1</label>
Life and Biomedical Sciences Education, School of Life Sciences, University of Dundee, Dundee, UK</aff>
</contrib-group>
<author-notes><fn fn-type="COI-statement"><p><bold>Competing interests: </bold>
No competing interests were disclosed.</p>
</fn>
</author-notes>
<pub-date pub-type="epub"><day>20</day>
<month>4</month>
<year>2016</year>
</pub-date>
<related-article id="d35e2771" related-article-type="peer-reviewed-article" ext-link-type="doi" xlink:href="10.12688/f1000research.6077.2">Version 2</related-article>
<custom-meta-group><custom-meta><meta-name>recommendation</meta-name>
<meta-value>approve</meta-value>
</custom-meta>
</custom-meta-group>
</front-stub>
<body><p>The study provides an interesting approach to the evaluation of divergence between the phage genomes. I'm not an expert in this area so come into it with a more general view. I found the revised paper clear and well explained in terms of approach. I agree with the first reviewer that the authors have perhaps been selective in just showing data from a select choice of
<italic>k-</italic>
mer values. Expanding the results to show the deviation across the full range of
<italic>k</italic>
tested, even if just in summary, would be interesting, though there would be a disparity between odd and even values of
<italic>k </italic>
as there are no palindormes with odd
<italic>k</italic>
. </p>
<p>A minor issue with regard to the present publication, but which might be worth consideration for future work, is over the TUD metric where the authors compare the observed frequencies to the expected. It is not clear from the study as to the variation one might see in a null model. If TUD is the test statistic of choice, a significance value for the deviation from expected should be deteminable empirically by modelling TUD, e.g.where there is a randomly assigned sequence of nucleotides corresponding to the genome of the organism. This could be done by shuffling the whole genome, taking a large sliding window and aggregating these scores (with or without shuffling etc.) A discussion of the significance of the deviation from expected (or the lack of appreciation of it) is worth including into the paper.</p>
<p>It is nice to see the distance measures, but without an estimate of the significance of the deviation from expected values, it becomes difficult to assess the significance of the deviation between genomes. It may be the case that using a significance measure as the distance (a Z-score or equivalent) may produce a different clustering.</p>
<p>I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
</body>
</sub-article>
<sub-article id="report11005" article-type="peer-review"><front-stub><article-id pub-id-type="doi">10.5256/f1000research.7828.r11005</article-id>
<title-group><article-title>Referee response for version 2</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Bonham-Carter</surname>
<given-names>Oliver</given-names>
</name>
<xref ref-type="aff" rid="r11005a1">1</xref>
<role>Referee</role>
</contrib>
<aff id="r11005a1"><label>1</label>
College of Information Science & Technology, School of Interdisciplinary Informatics, University of Nebraska, Omaha, NE, USA</aff>
</contrib-group>
<author-notes><fn fn-type="COI-statement"><p><bold>Competing interests: </bold>
No competing interests were disclosed.</p>
</fn>
</author-notes>
<pub-date pub-type="epub"><day>17</day>
<month>11</month>
<year>2015</year>
</pub-date>
<related-article id="d35e2836" related-article-type="peer-reviewed-article" ext-link-type="doi" xlink:href="10.12688/f1000research.6077.2">Version 2</related-article>
<custom-meta-group><custom-meta><meta-name>recommendation</meta-name>
<meta-value>approve</meta-value>
</custom-meta>
</custom-meta-group>
</front-stub>
<body><p>My initial concerns have been addressed.</p>
<p>I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
</body>
<back><ref-list><title>References</title>
<ref id="rep-ref-11005-1"><label>1</label>
<mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Bonham-Carter</surname>
<given-names>O</given-names>
</name>
<name><surname>Steele</surname>
<given-names>J</given-names>
</name>
<name><surname>Bastola</surname>
<given-names>D</given-names>
</name>
</person-group>
:
<article-title>Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis.</article-title>
<source><italic>Brief Bioinform</italic>
</source>
.<year>2014</year>
;<volume>15</volume>
(<issue>6</issue>
) :
<elocation-id>10.1093/bib/bbt052</elocation-id>
<fpage>890</fpage>
-<lpage>905</lpage>
<pub-id pub-id-type="doi">10.1093/bib/bbt052</pub-id>
<pub-id pub-id-type="pmid">23904502</pub-id>
</mixed-citation>
</ref>
</ref-list>
</back>
</sub-article>
<sub-article id="report7811" article-type="peer-review"><front-stub><article-id pub-id-type="doi">10.5256/f1000research.6506.r7811</article-id>
<title-group><article-title>Referee response for version 1</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Bonham-Carter</surname>
<given-names>Oliver</given-names>
</name>
<xref ref-type="aff" rid="r7811a1">1</xref>
<role>Referee</role>
</contrib>
<aff id="r7811a1"><label>1</label>
College of Information Science & Technology, School of Interdisciplinary Informatics, University of Nebraska, Omaha, NE, USA</aff>
</contrib-group>
<author-notes><fn fn-type="COI-statement"><p><bold>Competing interests: </bold>
No competing interests were disclosed.</p>
</fn>
</author-notes>
<pub-date pub-type="epub"><day>10</day>
<month>3</month>
<year>2015</year>
</pub-date>
<related-article id="d35e2943" related-article-type="peer-reviewed-article" ext-link-type="doi" xlink:href="10.12688/f1000research.6077.1">Version 1</related-article>
<custom-meta-group><custom-meta><meta-name>recommendation</meta-name>
<meta-value>reject</meta-value>
</custom-meta>
</custom-meta-group>
</front-stub>
<body><p>The article is nicely written but sadly, there are elements of discussion which are absent from the paper. If added, the paper's research on mycobacteriophages using alignment-free analysis would have much more support.
<list list-type="bullet"><list-item><p>The choice of TUD's as statistics for the alignment-free analysis is not fully explained /justified, nor is there much discussion about what algorithm or method is being employed by the analysis tools of the paper. Are TUD's frequencies? How do these software tools work?</p>
</list-item>
<list-item><p>An simple example of how to calculate a TUD and apply it to a method is necessary to completely understand what they are and to see how they are different from any other motif frequency calculation applied to some other method.</p>
</list-item>
<list-item><p>The assumptions of the methods are not discussed. Many methods from information theory, statistics and other kinds of mathematics require that the input data meets specific requirements (is normal, has a certain distribution, is a frequency, etc.). From the discussion in this paper, the function of analysis tool (the exact algorithm or method) is never clear and so we cannot be sure that the calculations from this work, as applied to these tools, is appropriate. For instance, many tools in information theory require that frequencies be used for their analysis. These frequencies must pass basic rules to be called as such (i.e., found on the scale of 0 to 1, all frequencies must sum to 1, 0 = false, 1 = true). This discussion is not mentioned and if it were, then the choice to used TUDs could be easily integrated into this discussion.</p>
</list-item>
<list-item><p>The manuscript mentioned that k-mers in the range of two to seven were calculated (Methods Section). Where are the results for all these other values of k={2, 3, 5 and 7} which were not the k={4 and 6} results of the article?</p>
</list-item>
<list-item><p>Although other sizes of motifs where apparently used in the analysis, the manuscript focuses on the length-4 motifs. The choice of k=4 for the size of motifs to study is not a very interesting statistic since the probability of a particular length-4 motif showing up randomly in a sequence not very high (1/(4^4) = 1/256). Given that the frequency of mutations, and all the evolutionary time during which to make changes to a sequence, these length=4 similar motifs are likely to randomly turn-up.</p>
</list-item>
<list-item><p>The authors should consider using the occurrence of motifs which are at least seven since these frequencies begin to become less randomly placed. Length-4 words are already common in many many bacteria as restriction sites for restriction enzymes. The authors will also find that there are restriction sites of length-6 for the same purpose and so they will have to remove all restriction enzyme palindromes from their sets of k=4 or 6 sized motifs if they cannot continue with a longer motif length. However, if they are determining the level of conservation between organisms, then having longer motifs should not hurt their results.</p>
</list-item>
</list>
Once these issues are addressed, the manuscript will be much stronger.</p>
<p>I have read this submission. I believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.</p>
</body>
<sub-article id="comment1668" article-type="response"><front-stub><contrib-group><contrib contrib-type="author"><name><surname>Siranosian</surname>
<given-names>Benjamin</given-names>
</name>
<aff></aff>
</contrib>
</contrib-group>
<author-notes><fn fn-type="COI-statement"><p><bold>Competing interests: </bold>
No competing interests were disclosed.</p>
</fn>
</author-notes>
<pub-date pub-type="epub"><day>23</day>
<month>10</month>
<year>2015</year>
</pub-date>
</front-stub>
<body><p>Thank you for reviewing the manuscript. I have considered the points you raised, and responded in order below. Changes to the manuscript are noted.
<list list-type="order"><list-item><p>The usage deviation-based statistics chosen for this paper are similar to those based on the composition vector of a sequence (
<ext-link ext-link-type="uri" xlink:href="http://www.ncbi.nlm.nih.gov/pubmed/23904502">Bonham-Carter
<italic>et al</italic>
., 2013</ext-link>
). Usage deviation (tetranucleotide usage deviation, TUD, in the case of k=4) is a vector of the counts of the possible k-mers, normalized to the expected counts in a randomized genome with the same nucleotide composition. I have made additions to the methods section and included a new figure that makes the calculation of usage deviation more clear. The software tools used to perform these calculations have a description at the github page linked in the paper.</p>
</list-item>
<list-item><p>I have added an example in the methods section that shows how to calculate TUD for a small sequence. Although this example outlines the method, the results are not very informative. The expected number of any 4-mer is very small in a short sequence, resulting in high TUD values for any 4-mers that do occur.</p>
</list-item>
<list-item><p>We do not make any assumptions about the input data when calculating usage deviation or performing statistics in the paper.</p>
</list-item>
<list-item><p>I showed trees constructed from other values of k in Figure 2. The relationships between phage genomes were consistent regardless of the value chosen for k. Other analyses mirrored this result, so we proceed exclusively with k={4, 6}.</p>
</list-item>
<list-item><p>I agree that length-4 motifs are not interesting to study in isolation. Usage deviation, where values represent deviations from expected frequencies, overcome this point. Single occurrences or counts of any 4-mer are uninteresting. Only when counts are normalized and compared in aggregate do the trends that observed in the paper become meaningful.</p>
</list-item>
<list-item><p>7-mers would be less randomly placed in the phage genomes analyzed. Similar to the point above, however, the occurrences of singular k-mers are not considered. As k increases, the resulting usage deviation vectors become sparse. Up to 43% of the (4^7=16384) 7-mers are absent from individual genome sequences, and no 7-mer occurs at least once in every genome analyzed. The sparse nature of the data for 7-mers would not be well-suited to some of the analyses presented in this paper (PCA, searching for horizontally transferred segments).</p>
</list-item>
<list-item><p>I acknowledge that many 4-mers and 6-mers are restriction sites. In fact, this makes the substrings more interesting. B3 mycobacteriophages have 4 times the expected usage of GATC, a restriction site in some bacteria. Biological sense dictates restriction sites would occur infrequently, but the results say the opposite. I do not feel it is necessary to remove restriction sites before the analysis, and doing so would be somewhat arbitrary. The set of restriction sites in mycobacteria species is not entirely characterized, and the host range for each mycobacteriophage has not been studied.</p>
</list-item>
</list>
We hope you find the answers to the points you raised and the revisions to the paper acceptable.</p>
<p><bold>References:</bold>
</p>
<p>Bonham-Carter, O., Steele, J. & Bastola, D. Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis.
<italic>Brief Bioinform</italic>
<bold>15,</bold>
890–905 (2014).</p>
</body>
</sub-article>
</sub-article>
</pmc>
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