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Reconstructible phylogenetic networks: do not distinguish the indistinguishable.

Pardi F, Scornavacca C - PLoS Comput. Biol. (2015)

Bottom Line: This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem.For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set.While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM, UMR 5506) CNRS, Université de Montpellier, France; Institut de Biologie Computationnelle, Montpellier, France.

ABSTRACT
Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are "indistinguishable". This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.

No MeSH data available.


Edge lengths are informative to distinguish among different network topologies.The only network topology, among N1, N2 and N3 that can display simultaneously T1 and T2 with the indicated edge lengths is N2: see for example the edge lengths assignment in the bottom right corner.
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pcbi.1004135.g002: Edge lengths are informative to distinguish among different network topologies.The only network topology, among N1, N2 and N3 that can display simultaneously T1 and T2 with the indicated edge lengths is N2: see for example the edge lengths assignment in the bottom right corner.

Mentions: However, there is another motivation for our choice: accounting for edge lengths solves some of the identifiability problems outlined above, as in some cases it allows to distinguish between networks with different topologies, which would be otherwise impossible to tell apart. For example, consider the three network topologies in Fig. 2 (top), where taxon o is an outgroup used to identify the root of the phylogeny for a, b and c. These networks show three very different evolutionary histories: in N1 taxon b is the only one issued of a reticulation event—in other words the genome of b is recombinant—whereas in N2 and N3, it is a and c, respectively, that are recombinant. However, N1, N2 and N3 display the same tree topologies—those of T1 and T2—and thus would be indistinguishable to any approach that does not model edge lengths.


Reconstructible phylogenetic networks: do not distinguish the indistinguishable.

Pardi F, Scornavacca C - PLoS Comput. Biol. (2015)

Edge lengths are informative to distinguish among different network topologies.The only network topology, among N1, N2 and N3 that can display simultaneously T1 and T2 with the indicated edge lengths is N2: see for example the edge lengths assignment in the bottom right corner.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4388854&req=5

pcbi.1004135.g002: Edge lengths are informative to distinguish among different network topologies.The only network topology, among N1, N2 and N3 that can display simultaneously T1 and T2 with the indicated edge lengths is N2: see for example the edge lengths assignment in the bottom right corner.
Mentions: However, there is another motivation for our choice: accounting for edge lengths solves some of the identifiability problems outlined above, as in some cases it allows to distinguish between networks with different topologies, which would be otherwise impossible to tell apart. For example, consider the three network topologies in Fig. 2 (top), where taxon o is an outgroup used to identify the root of the phylogeny for a, b and c. These networks show three very different evolutionary histories: in N1 taxon b is the only one issued of a reticulation event—in other words the genome of b is recombinant—whereas in N2 and N3, it is a and c, respectively, that are recombinant. However, N1, N2 and N3 display the same tree topologies—those of T1 and T2—and thus would be indistinguishable to any approach that does not model edge lengths.

Bottom Line: This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem.For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set.While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM, UMR 5506) CNRS, Université de Montpellier, France; Institut de Biologie Computationnelle, Montpellier, France.

ABSTRACT
Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are "indistinguishable". This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.

No MeSH data available.