So far molecular studies of subfossil material have served only to confirm the placement of extinct taxa and not influenced the relationships of extant species. This is a section where morphological analysis has the advantage, as it is able to provide a much denser taxon sampling than sequence analysis and so provide much more information about the past. This is especially useful where the group has undergone a reduction of the number of species that are extant.
There are certain advantages to the processing of the data that DNA sequence analysis provides over that of morphology. In order to draw any phylogenetic tree the relationships between the different subjects must be assessed. Morphological characters have to be transformed from description into numerical values to be processed on a computer if any complex analysis is to be undertook. Scotland [1] stated that there were currently 9 different coding strategies for translating observations into discrete numerical codes for morphological cladistic analysis. This is fraught with error and even if the most accurate method is chosen the conversion from a subjective continuous variable to a discrete one cannot be entirely accurate. DNA sequencing provides a direct numerical code for analysis of the characters based on the nucleotides (A,C,G,T = 0,1,2,3). There is no error possible in the conversion, except for human and even then the current levels of automation remove that.
Once the data has been converted into a format ready for analysis the algorithms themselves used for the construction of the trees are subject to scrutiny. Similar methods for analysing and creating the trees are used for both morphological characters and DNA sequencing, such as bootstrapping, Maximum Likelihood Maximum Parsimony and the only advantage that DNA sequence data has here is that the algorithms can be smaller as the characters have the same numeric basis, leading to faster construction of trees and the data is much more reliable. This does not mean that the process is perfect though for DNA, due to the massive amount of data generated current analytical methods are inadequate, and new algorithms are need for interpreting and analysing changes in characters are needed [5].
Studies by Pryer [3] show that discrepancies can arise through the use of different algorithms. When Maximum likelihood was used Gymnosperms were resolved as monophyletic and Gnetum was a sister to pinus. However when maximum Parsimony (preferring the scheme that has the fewest state changes) resolved Gnetum as basal among seed plants and all other Gymnosperms as monophyletic and sister to Angiosperms. This may appear pedantic but knowledge of the relationships to this detail is vital for the accurate construction of a phylogenetic tree. Output also depends on the weighting each individual character is given during analysis, opening an area for subjectiveness in sequence analysis. Without the downweighting of the 3rd codon position of rbcL (due to apparent saturation), analysis of bryophyte phylogeny would of been inconclusive [6].
DNA sequence data is very good at providing the information regarding the composition of a phylogenetic tree, but where it falls down is how all this information is arranged on the tree, on a rooting and temporal basis. The disadvantage regarding rooting is best describe thought he use of an example [1]: The DNA sequence data places the conifers, angiosperms and the Gnetales certain distances from each other based on the divergence of their genes. However the DNA sequence data does not provide the information regarding the root (location of divergence), leading to the possible construction of two different phylogenies.
In order to accurately assess the rooting position an outgroup is needed, a subject that is related to all three but diverged from all of them a long time ago in order to provide a “template” in order to refer the changes in sequence to, the one with the least parsimony is the oldest. Hanseh, from whom this diagram is taken, used the Liverwort Marchantia, a distant relative with 450 MYA divergence. The problem with using outgroups is that they are all subject to long branch attrition artefacts, reducing reliability, and the choice of outgroup, being subjective.
Because DNA sequencing can only be reliably used on extant species the construction of the tree runs into another obstacle. Accurate assessment of times of divergence and rooting is nearly impossible. The use of the molecular clock does provide some guidelines, but it assumes a constant rate of nucleotide substitution and evolution, something that is very rarely checked for and often assumed [5], negating the effects of rapid evolution and extinction. This is a major source of inaccuracy in the phylogeny of land plants based on DNA sequence data.
Fossil data based on morphological analysis provides the answer to many of these problems. Fossils provide direct evidence for the rapid divergence and mass extinction processes, allowing absolute temporal calibration of the molecular clock. They also provide information that can be used to “fill in the gaps” where DNA sequence data fails to concerning the branching of the tree if outgrouping is unsuccessful, resolving conflicts at the nodes. This allows for the correct rooting of groups, removing long branch attrition artefacts that have to be based on extant species. The ability to analyse extinct species provides key information regarding the topology of the tree constructed and larger data sets across more taxa leading to a more detailed tree.
Conclusions
DNA sequence data has not removed the need for morphological assessment of the relationships between land plants, but it has provided a new route of analysis which provides much higher resolution and statistically robust data from which new hypothesis can be drawn from. It is reassuring to know that molecular analysis has not upset the overall topology of the tree, in fact it has re-affirmed conclusions regarding groups and families drawn up on morphological characters. Although morphology is limited in its robustness it does provide the key framework to which all DNA sequence analysis is hung from and the data obtained serves to augment and refine the work already provided by 300 years of study.
Bibliography
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2. Scotland, Olmstead & Bennett (unpublished) Role of Morphology
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