General continuous-time Markov model of sequence evolution via insertions/deletions: local alignment probability...

Area of Science:

• Computational Biology
• Bioinformatics
• Evolutionary Genetics

Background:

• Insertions and deletions (indels) are major drivers of DNA sequence divergence.
• Accurate calculation of sequence alignment probabilities is essential for evolutionary studies.
• Previous work introduced a perturbative formulation for ab initio alignment probability calculation.

Purpose of the Study:

• To approximately calculate local alignment probabilities using a developed formulation.
• To assess the accuracy of approximate methods for pairwise and multiple sequence alignments.
• To provide a reference point for other indel probabilistic models.

Main Methods:

• Numerical computation of indel history contributions for pairwise and multiple sequence alignments.
• Derivation and numerical solution of integral equations for practically exact local PWA probabilities.
• Development of an algorithm for first-approximate MSA probability calculation.

Main Results:

• Total parsimonious contributions approximated multiplication factors well for moderate gap sizes and branch lengths.
• Approximate methods demonstrated good accuracy in calculating ab initio alignment probabilities.
• Comparison with a sequence evolution simulator (Dawg) validated the first-approximate MSA probability calculations.

Conclusions:

• Approximate methods offer accurate ab initio alignment probability calculations under biologically realistic models.
• The developed formulation serves as a sound reference for other indel probabilistic models.
• The study advances the computational analysis of evolutionary sequence changes.