There are many methods used in phylogeny viz. Maximum Likelihood Tree; Neighbor-Joining Tree; Minimum evolution Tree; UPGMA TREE & Maximum Parsimony Tree.
I have simply two questions
Whats a criteria for new species and how molecular studies will support?
Which will be best method for species relationship or identification of new species/genus?
Parsimony is outdated. Go for both Maximum Likelihood (ML) and Bayesian analyses.
For ML analysis can use Garli, RaxML or IQTree. For Bayesian try MrBayes or BEAST.
Parsimony is outdated. Go for both Maximum Likelihood (ML) and Bayesian analyses.
For ML analysis can use Garli, RaxML or IQTree. For Bayesian try MrBayes or BEAST.
Thanks Thilina Nethmin De Silva for kind suggestions.
with best regards
Kamalesh S. Mahar
Thanks Lixia Shi and msr Krishna for your concern and kind suggestions.
Here I am talking about method not software. MEGA is a software which we are using for phylogenetic analyses.
Thanking you
with best regards
Kamalesh S. Mahar
Hi
You can use matK and rbcL markers can be used for plant relation studies
Basically, these methods of getting phylogenetic relationships will get highly similar topology. There is no right or wrong answer. I would rather apply multiple analyses and then combine the results for a better resolution.
As for supports in species or higher taxonomic rank delimitation, it would vary depending on which plant family are you studying. Try to find the widely used markers so that when you construct your phylogenetic trees, you will have more OTUs to compare from. Combining multiple markers most of the time provides a stronger resolution.
You need to decide which markers are best used in a particular group, e.g. agreed barcoding markers for plants. Then, in my experience the best approach is either single marker or multi-marker analysis under Maximum Likelihood (e.g. RAxML) and then do a species recognition test, e.g. GMYC or PTP. You can do this eg here: http://species.h-its.org/ptp. For GMYC you need an ultrametric tree, which can be easily done in Mesquite (a molecular clock tree is not really needed). For PTP you use the best-scoring ML tree. In my experience GMYC is more reliable, as PTP is very sensitive to data structure and aberrant sequences, e.g. sequences with reading errors, etc. PTP will then likely overestimate species. In contrast to species, a genus is an abstract construct and whether two sister clades are one or two genera is up to a subjective decision. However, you can highjack the species recognition test for this purpose, if you want to delimit genera using branch length distribution patterns. You simply use a single OTU for each species of interest and assume that you test for species, then the obtained clusters will actually suggest genera.
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