7 Difference Between Local And Global Sequence Alignment

Local And Global Sequence Alignment

A sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. Aligned sequences of nucleotide or amino acid residues are typically represented as rows within a matrix. Gaps are inserted between the residues so that identical or similar characters are aligned in successive columns. Sequence alignments are also used for non-biological sequences, such as calculating the distance cost between strings in a natural language or in financial data.

Sequence alignments can be further divided into global alignments that align the complete sequences and local alignments that identify only the most similar segments or sequence patterns (motifs). While global alignment algorithms produce more accurate alignments for proteins of similar length, local alignment algorithms are better at identifying similar regions within sequences when the sequences are not related over their entire length.

Alignments are produced by a wide variety of programs, known as “aligners”, sometimes as a side product of the main function of the program. In local alignments, produced by aligners such as Dialign, the conserved motifs are identified and the rest of the sequences are included for information only. Thus, only a subset of the residues is actually aligned. In global alignments, typically produced by aligners such as Clustal W, all the residues in both sequences participate in the alignment. By placing the sequence in the context of the overall family, the global alignment permits not only a horizontal analysis of the sequence over its entire length, but also a vertical view of the evolution of the protein. The global alignment thus represents a powerful integrative tool that addresses a variety of biological problems, ranging from key functional residue detection to the evolution of a protein family.

Facts About Global Sequence Alignment

1. In global alignment, an attempt is made to align the entire sequence (end to end alignment).
2. A global alignment contains all letters from both the query and target sequences.
3. If two sequences have approximately the same length and are quite similar, they are suitable for global alignment.
4. Suitable for aligning two closely related sequences.
5. Global alignments are usually done for comparing homologous genes like comparing two genes with same function (in human vs. mouse) or comparing two proteins with similar function.
6. A general global alignment technique is the Needleman–Wunsch algorithm.

Facts About Local  Sequence Alignment

1. Finds local regions with the highest level of similarity between the two sequences.
2. A local alignment aligns a substring of the query sequence to a substring of the target sequence.
3. Any two sequences can be locally aligned as local alignment finds stretches of sequences with high level of matches without considering the alignment of rest of the sequence regions.
4. Suitable for aligning more divergent sequences or distantly related sequences.
5. Used for finding out conserved patterns in DNA sequences or conserved domains or motifs in two proteins.
6. A general local alignment method is Smith–Waterman algorithm.

Difference Between Global And Local Sequence Alignment In Tabular Form