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Assessing the evolutionary rate of positional orthologous genes in prokaryotes using synteny data.

Lemoine F, Lespinet O, Labedan B - BMC Evol. Biol. (2007)

Bottom Line: Once all these synteny blocks have been detected, we showed that POGs are subject to more evolutionary constraints than orthologs outside synteny groups, whichever the taxonomic distance separating the compared organisms.The suite of programs described in this paper allows a reliable detection of orthologs and is useful for evaluating gene order conservation in prokaryotes whichever their taxonomic distance.Thus, our approach will make easy the rapid identification of POGS in the next few years as we are expecting to be inundated with thousands of completely sequenced microbial genomes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institut de Génétique et Microbiologie, CNRS UMR 8621, Bâtiment 400, Université Paris Sud XI, 91405 Orsay Cedex, France. frederic.lemoine@igmors.u-psud.fr

ABSTRACT

Background: Comparison of completely sequenced microbial genomes has revealed how fluid these genomes are. Detecting synteny blocks requires reliable methods to determining the orthologs among the whole set of homologs detected by exhaustive comparisons between each pair of completely sequenced genomes. This is a complex and difficult problem in the field of comparative genomics but will help to better understand the way prokaryotic genomes are evolving.

Results: We have developed a suite of programs that automate three essential steps to study conservation of gene order, and validated them with a set of 107 bacteria and archaea that cover the majority of the prokaryotic taxonomic space. We identified the whole set of shared homologs between two or more species and computed the evolutionary distance separating each pair of homologs. We applied two strategies to extract from the set of homologs a collection of valid orthologs shared by at least two genomes. The first computes the Reciprocal Smallest Distance (RSD) using the PAM distances separating pairs of homologs. The second method groups homologs in families and reconstructs each family's evolutionary tree, distinguishing bona fide orthologs as well as paralogs created after the last speciation event. Although the phylogenetic tree method often succeeds where RSD fails, the reverse could occasionally be true. Accordingly, we used the data obtained with either methods or their intersection to number the orthologs that are adjacent in for each pair of genomes, the Positional Orthologous Genes (POGs), and to further study their properties. Once all these synteny blocks have been detected, we showed that POGs are subject to more evolutionary constraints than orthologs outside synteny groups, whichever the taxonomic distance separating the compared organisms.

Conclusion: The suite of programs described in this paper allows a reliable detection of orthologs and is useful for evaluating gene order conservation in prokaryotes whichever their taxonomic distance. Thus, our approach will make easy the rapid identification of POGS in the next few years as we are expecting to be inundated with thousands of completely sequenced microbial genomes.

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Bootstrap analysis of the distribution of PAM distances separating pairs of orthologs located inside and outside synteny blocks. The number of cases rejecting and not rejecting hypothesis H0, and those corresponding to cases too small to be included in this statistical test are shown for each method (RSD and phylogeny) and their intersection. The inset table details the data for trees of complexity 0 (orthologs only) or 1 (orthologs and in-paralogs).
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Figure 5: Bootstrap analysis of the distribution of PAM distances separating pairs of orthologs located inside and outside synteny blocks. The number of cases rejecting and not rejecting hypothesis H0, and those corresponding to cases too small to be included in this statistical test are shown for each method (RSD and phylogeny) and their intersection. The inset table details the data for trees of complexity 0 (orthologs only) or 1 (orthologs and in-paralogs).

Mentions: To validate this study, we first used the phylogenetic approach, taking into account orthologs contained in trees of various complexities defined as follows. We analyzed trees made up uniquely of orthologs (complexity 0), and trees containing only orthologs and in-paralogs (complexity 1). We then did similar computations for the 107 genomes with the entire dataset obtained using the RSD ortholog detection method. Fig. 5 shows that in both RSD and phylogeny approaches, the overwhelming majority of the statistical tests reject the hypothesis H0 in favour of H1. We found that the remaining, untested cases (NT) correspond to a few comparisons that are too small to be safely used in this bootstrap test. This is the case, for example, of all comparisons (1% of the total) involving Nanoarchaea equitans, an archaeon with a very small genome that is also very distant from all other species, including the other archaea.


Assessing the evolutionary rate of positional orthologous genes in prokaryotes using synteny data.

Lemoine F, Lespinet O, Labedan B - BMC Evol. Biol. (2007)

Bootstrap analysis of the distribution of PAM distances separating pairs of orthologs located inside and outside synteny blocks. The number of cases rejecting and not rejecting hypothesis H0, and those corresponding to cases too small to be included in this statistical test are shown for each method (RSD and phylogeny) and their intersection. The inset table details the data for trees of complexity 0 (orthologs only) or 1 (orthologs and in-paralogs).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2238764&req=5

Figure 5: Bootstrap analysis of the distribution of PAM distances separating pairs of orthologs located inside and outside synteny blocks. The number of cases rejecting and not rejecting hypothesis H0, and those corresponding to cases too small to be included in this statistical test are shown for each method (RSD and phylogeny) and their intersection. The inset table details the data for trees of complexity 0 (orthologs only) or 1 (orthologs and in-paralogs).
Mentions: To validate this study, we first used the phylogenetic approach, taking into account orthologs contained in trees of various complexities defined as follows. We analyzed trees made up uniquely of orthologs (complexity 0), and trees containing only orthologs and in-paralogs (complexity 1). We then did similar computations for the 107 genomes with the entire dataset obtained using the RSD ortholog detection method. Fig. 5 shows that in both RSD and phylogeny approaches, the overwhelming majority of the statistical tests reject the hypothesis H0 in favour of H1. We found that the remaining, untested cases (NT) correspond to a few comparisons that are too small to be safely used in this bootstrap test. This is the case, for example, of all comparisons (1% of the total) involving Nanoarchaea equitans, an archaeon with a very small genome that is also very distant from all other species, including the other archaea.

Bottom Line: Once all these synteny blocks have been detected, we showed that POGs are subject to more evolutionary constraints than orthologs outside synteny groups, whichever the taxonomic distance separating the compared organisms.The suite of programs described in this paper allows a reliable detection of orthologs and is useful for evaluating gene order conservation in prokaryotes whichever their taxonomic distance.Thus, our approach will make easy the rapid identification of POGS in the next few years as we are expecting to be inundated with thousands of completely sequenced microbial genomes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institut de Génétique et Microbiologie, CNRS UMR 8621, Bâtiment 400, Université Paris Sud XI, 91405 Orsay Cedex, France. frederic.lemoine@igmors.u-psud.fr

ABSTRACT

Background: Comparison of completely sequenced microbial genomes has revealed how fluid these genomes are. Detecting synteny blocks requires reliable methods to determining the orthologs among the whole set of homologs detected by exhaustive comparisons between each pair of completely sequenced genomes. This is a complex and difficult problem in the field of comparative genomics but will help to better understand the way prokaryotic genomes are evolving.

Results: We have developed a suite of programs that automate three essential steps to study conservation of gene order, and validated them with a set of 107 bacteria and archaea that cover the majority of the prokaryotic taxonomic space. We identified the whole set of shared homologs between two or more species and computed the evolutionary distance separating each pair of homologs. We applied two strategies to extract from the set of homologs a collection of valid orthologs shared by at least two genomes. The first computes the Reciprocal Smallest Distance (RSD) using the PAM distances separating pairs of homologs. The second method groups homologs in families and reconstructs each family's evolutionary tree, distinguishing bona fide orthologs as well as paralogs created after the last speciation event. Although the phylogenetic tree method often succeeds where RSD fails, the reverse could occasionally be true. Accordingly, we used the data obtained with either methods or their intersection to number the orthologs that are adjacent in for each pair of genomes, the Positional Orthologous Genes (POGs), and to further study their properties. Once all these synteny blocks have been detected, we showed that POGs are subject to more evolutionary constraints than orthologs outside synteny groups, whichever the taxonomic distance separating the compared organisms.

Conclusion: The suite of programs described in this paper allows a reliable detection of orthologs and is useful for evaluating gene order conservation in prokaryotes whichever their taxonomic distance. Thus, our approach will make easy the rapid identification of POGS in the next few years as we are expecting to be inundated with thousands of completely sequenced microbial genomes.

Show MeSH