What is Multiple alignment and profiles? — Biology

Definition 5.11 University Biology — Year 3 · Chapter 5 — Bioinformatics and Sequence Analysis

A multiple sequence alignment arranges a family of sequences in columns of homologous residues. Exact dynamic programming over $k$ sequences costs $n^{k}$ and is impossible beyond three; practical programs align progressively, first the closest pair by a guide tree, then sequences and groups to the growing alignment, with rounds of refinement. A finished alignment is summarised as a profile: for each column, the frequency of each residue and of gaps. A profile hidden Markov model formalises this as a chain of match states, one per conserved column, each emitting residues with its own probabilities, with insert and delete states allowing extra or missing residues at each position; the model of a family (a Pfam entry) scores a new sequence by the probability of the best path through the states, and finds homologues far below the twilight zone of pairwise comparison, because a column that tolerates only hydrophobic residues says so, while a single sequence cannot.

A profile hidden Markov model of a four-column family. Each match state M emits a residue with the column’s own frequencies; insert states I (with self-loops) admit extra residues, delete states D skip a column. Scoring a sequence is finding its most probable path.

Examples

Example 5.7 (Identity, similarity and the twilight zone)

Two random protein sequences aligned optimally with gaps reach about $15\text{ to }20\,\%$ identity by chance. Above $35\,\%$ identity over a hundred residues two proteins are almost surely homologous; between $20\,\%$ and $35\,\%$ is the twilight zone, where identity alone cannot decide and the statistics below must. Homologues can fall far below the zone: haemoglobin and myoglobin subunits share $25\,\%$ identity, lysozyme and $\alpha$ -lactalbumin $40\,\%$ , and many pairs of proteins with the same fold share less than $15\,\%$ , detectable only by comparing profiles or structures.

Example 5.10 (Reading an E-value)

A query of $250$ residues against a database of $5\times 10^{10}$ residues has $mn = 1.25\times 10^{13} \approx 2^{43.5}$ . A hit with a bit score of $60$ has $E = 2^{43.5 - 60} = 2^{-16.5} \approx 10^{-5}$ : essentially certainly a homologue. A hit with $S' = 40$ has $E = 2^{3.5} \approx 11$ : eleven such scores are expected by chance, and the hit means nothing. The same alignment, with the same bit score, searched against a database ten times larger, has an $E$ ten times larger — significance is a property of the search, not of the pair. The threshold in common use is $E < 10^{-3}$ for a confident homologue; $E \approx 0.01$ – $1$ deserves a second look with a profile method.

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Examples

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