Sequence Alignment Overview

Sequence Alignment

• Sequence alignment is the process of arranging two or more sequences of nucleotides (DNA or RNA) or amino acids (proteins) to identify regions of similarity and difference.
• This process helps to infer structural, functional, and evolutionary relationships between the sequences.
• The procedure involves searching for series of identical or similar characters or patterns in the same order between the sequences.
• Alignments are typically generated using computer programs and algorithms that assess the quality of the alignment based on a scoring system that rewards matches and penalizes mismatches and gaps.

Uses of Sequence Alignment

• Predicting the function of a gene or protein
• Predicting molecular structure
• Discovering evolutionary or phylogenetic relationships
• Annotation (to characterize features) of new sequences
• Fragment or genome assembly (reassemble fragments in their correct order to reconstitute the genome or RNA sequence)
• Detect gene mutations

Why Sequence Alignment?

• Sequences that are very similar likely share the same function, similar secondary and 3D structure (for proteins), and a shared ancestral sequence, though not always.

Evolutionary Basis of Sequence Alignment

• One goal of sequence alignment is to infer homology (origin from a common ancestor) through observed shared sequence similarity.
• Changes that occur during sequence divergence from a common ancestor include substitutions (point mutations), deletions, and insertions.

Causes for Sequence Dissimilarity in Sequence Alignment

• Point mutations (substitutions): a nucleotide at a specific location is replaced by another nucleotide (e.g., ATA → AGA). This leads to mismatches in sequence alignment.
• Indels (insertions and/or deletions): nucleotides are inserted and/or deleted into genomic DNA. This leads to gaps in sequence alignment.
• Insertion: at a specific location, one new nucleotide is inserted between two existing nucleotides (e.g., AA → AGA).
• Deletion: at a certain location, one existing nucleotide is deleted (e.g., ACTG → AC-G).

Sequence Identity and Similarity

• Sequence Identity means the same residues are present at corresponding positions in two sequences.
• Sequence Similarity means similar residues are present at corresponding positions in two sequences. This can involve amino acids with similar physicochemical and functional properties.
• When comparing nucleic acids, sequence similarity and sequence identity are the same.

Types of Sequence Homology

• Orthologous sequences: very similar sequences found in different species, which are likely due to a speciation event, that carry out a similar biological function.
• Paralogous sequences: sequences related through gene duplication events, which can have variable biological functions within the same species.
• Analogous sequences: related through convergency. These are similar genetic changes in independent species (unrelated species) due to parallel evolution.

Types of Sequence Alignment

• Global alignment: Aligns and compares two sequences along their entire length, providing the best alignment that displays the maximum number of nucleotides or amino acids aligned.
• Local alignment: Finds the most similar regions in two sequences being aligned. This is useful for sequences that are not similar in character and length, but may contain small regions of similarity.
• Pairwise alignment: Maps and compares residues between two sequences.
• Multiple sequence alignment: Determines the best alignment between multiple (more than two) DNA sequences.

Sequence Alignment Algorithms

• Dynamic programming: These are rigorous algorithms that provide optimal alignments:
  • Needlman-Wunsch algorithm: Used for global alignments.
  • Smith-Waterman algorithm: Used for local alignments; provides one or more alignments of the sequences.
• Heuristic algorithms: These are faster algorithms that provide approximate alignments:
  • BLAST
  • FASTA