Alignments Why do Alignments?

Detecting Selection Evolution of Drug Resistance in HIV

Selection on Amino Acid Properties TreeSAAP (2003) Wu Method (Sainudiin et al. 2005)

TreeSAAP Properties Alpha-helical tendencies Average number of surrounding residues Beta-structure tendencies Bulkiness Buriedness Chromatographic Index Coil tendencies Composition Compressibility Equilibrium constant (ionization of COOH) Helical contact area Hydropathy Isoelectric point Long-range non-bonded energy Mean r.m.s. fluctuation displacement Molecular volume Molecular weight Normalized consensus hydrophobicity Partial specific volume Polar requirement Polarity Power to be at the C-terminal Power to be at the middle of alpha- helix Power to be at the N-terminal Refractive index Short and medium range non-bonded energy Solvent accessible reduction ratio Surrounding hydrophobicity Thermodynamic transfer hydrophobicity Total non-bonded energy Turn tendencies

TreeSAAP

Rhinoviruses

Selected Sites

3D Mapping

PHENOTYPE GENOTYPE ENVIRONMENT OPSIN: Model System for Molecular Evolution Wavelength (nm) UVIR CRLAKIAMTTVALWFIAWT PYLLINWVGMFARSYLSPV YTIWGYVFAKANAVYNPIV YAISHPKYRAAMEKKLPCL SCKTESDDVSESASTTTSS

Is max Correlated with Ecological Differences? microscopic thin beam of spectral light INPUTOUTPUT INPUT – OUTPUT = pigment absorbance Detect light not absorbed by the photopigment 400 – 700 nm at 1nm intervals

Coil Tendencies, Compressibility, Alpha-Helix

Amino acid alignment number Coil Tendencies Compressibility Power to be at mid alpha Refractive Index Z-score TMI TMIITMIIITMIVTMVTMVI TreeSAAP

Homology

Homology definitions Homology is an evolutionary relationship that either exists or does not. It cannot be partial. An ortholog is a homolog that arose through a speciation event A paralog is a homolog that arose through a gene duplication event. Paralogs often have divergent function. Similarity is a measure of the quality of alignment between two sequences. High similarity is evidence for homology. Similar sequences may be orthologs or paralogs.

One More Homology type Xenology – similarity due to horizontal gene transfer (HGT) How do you discover this?

Alignment Problem (Optimal) pairwise alignment consists of considering all possible alignments of two sequences and choosing the optimal one. Sub-optimal (heuristic) alignment algorithms are also very important: eg BLAST

Key Issues Types of alignments (local vs. global) The scoring system The alignment algorithm Measuring alignment significance

Types of Alignment Global—sequences aligned from end- to-end. Local—alignments may start in the middle of either sequence Ungapped—no insertions or deletions are allowed Other types: overlap alignments, repeated match alignments

Local vs. Global Pairwise Alignments A global alignment includes all elements of the sequences and includes gaps. A global alignment may or may not include "end gap" penalties. Global alignments are better indicators of homology and take longer to compute. A local alignment includes only subsequences, and sometimes is computed without gaps. Local alignments can find shared domains in divergent proteins and are fast to compute

How do you compare alignments? Scoring scheme What events do we score? Matches Mismatches Gaps What scores will you give these events? What assumptions are you making? Score your alignment

Scoring Matrices How do you determine scores? What is out there already for your use? DNA versus Amino Acids? TTACGGAGCTTC CTGAGATCC

Multiple Sequence Alignment Global versus Local Alignments Progressive alignment Estimate guide tree Do pairwise alignment on subtrees ClustalX

Improvements Consistency-based Algorithms T-Coffee - consistency-based objective function to minimize potential errors Generates pair-wise global (Clustal) Local (Lalign) Then combine, reweight, progressive alignment

Iterative Algorithms Estimate draft progressive alignment (uncorrected distances) Improved progressive (reestimate guide tree using Kimura 2-parameter) Refinement - divide into 2 subtrees, estimate two profiles, then re-align 2 profiles Continue refinement until convergence

Software Clustal T-Coffee MUSCLE (limited models) MAFFT (wide variety of models)

Comparisons Speed Muscle>MAFFT>CLUSTALW>T-COFFEE Accuracy MAFFT>Muscle>T-COFFEE>CLUSTALW Lots more work to do here!