The Big Issues in Phylogenetic Reconstruction Randy Linder Integrative Biology, University of Texas

Overview for Talk Biological issues –Practical Time constraints Material constraints Monetary constraints Information constraints –Theoretical Models: Processes of evolution –How does information move through the system –How do nucleotides evolve –How do indels evolve –Rearrangements and duplications Alignment Reconstruction Comparative methodologies

Overview for Talk (cont.) Computational issues –Theoretical Graph theory Algorithmic Heuristics –Practical Performance –Running times –Accuracy of results –“Efficiency”: accuracy of results for a given amount of data Will not address these directly, but they will come up at various points

General Overview of a Systematist’s Work Determine the scope of the work –Anything from kingdoms to single genera Seek funding Plan and travel to get materials –Costs –Politics –Time

General Overview of a Systematist’s Work (cont.) Extract DNA (in most cases) –Sometimes easy (most animals, microbes) –Sometimes not (many plants, fungi) Determine which DNA regions to use –Ones previously determined by other studies –Develop new ones Amplify (and clone) regions –See if they have appropriate variation –Do so in all available specimens

General Overview of a Systematist’s Work (cont.) Align sequences –Use available algorithms (most often some flavor of Clustal) –Hand align where algorithms are too stupid If using model-based reconstruction method, determine model to use Reconstruct relationships –Choose method(s) of reconstruction Time Computational feasibility Quality of result Decide if datasets can be combined

General Overview of a Systematist’s Work (cont.) Assess quality of reconstruction –Bootstrap Non-parametric (any method, especially MP) Parametric (ML) –Posterior probabilities (Bayesian) Perform comparative analyses (often) –Examples: Assess character evolution Test for patterns consistent with –Types of speciation –Biogeographic hypotheses –Adaptive hypotheses

Biological Issues: Practical Time constraints –Gathering of material for study –Finding adequate regions for analysis –Cloning (sometimes) and sequencing of information Sometimes gathering of morphological information –Run time of phylogenetic analyses –Run time of assessments of support –Time to conduct comparative analyses

Biological Issues: Practical Material constraints –Getting all of the taxa desired Monetary constraints –Travel costs –Cloning and sequencing costs Information constraints –What regions will provide the right amount of variation for my group? –What is the best sampling strategy for my group? –Do my regions for analysis avoid gene tree/species tree problems? –Does my group have any reticulation in it and how will I know?

How Do Practical Issues Translate to Compuational Issues? Prior to lab work –Not much, really –Maybe with design of taxon sampling strategies b/c getting samples is often a major constraint During lab work –Help in locating new regions for analysis –Help in assessing/developing regions that are free of gene tree/species tree problems.

How Do Practical Issues Translate to Compuational Issues? Post lab work –Improved alignment methods Better methods, independent of reconstruction –Methods that handle indels better »Sequence length differences »Non-repeat indels »Repeat indels –Assessment of quality of alignment in different regions Alignment methods that simultaneously infer phylogeny –Need alignment methods that explicitly attempt to infer positional homology according to some optimality criterion

How Do Practical Issues Translate to Compuational Issues? Post lab work –Reconstruction methods Better models of sequence evolution –Relaxing of the rates-across-sites assumption –Models that make use of information in indels Methods that assess reasons for phylogenetic incongruence and support for different explanations –Reticulation above the species level –Reticulation below the species level –Lineage sorting: alleles, gene duplications

How Do Practical Issues Translate to Compuational Issues? Post lab work –Reconstruction methods Methods that statistically assess the tree-space of optimal and nearly optimal solutions to reconstructions Better supertree methods –Support methods Develop methods that assess support for alternative explanations: –Tree, network, gene tree/species tree, etc.