Sequence alignment is a way of arranging DNA, RNA, or protein sequences to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships.
There are two main types of pairwise sequence alignment:
1.
Global Alignment:
- Assumes that the two sequences are generally similar over their entire length.
- Attempts to align every residue in one sequence with a residue or a gap in the other sequence.
- Useful for comparing closely related sequences of similar length.
- Example algorithm: Needleman-Wunsch algorithm.
2.
Local Alignment:
- Does not assume that the two sequences are similar over their entire length.
- Instead, it finds the regions of highest similarity between subsequences of the two sequences. It looks for conserved domains or motifs.
- Useful for comparing more distantly related sequences, sequences of different lengths, or finding conserved domains within larger sequences.
- Example algorithm: Smith-Waterman algorithm. BLAST is a heuristic method that performs local alignments.
Let's analyze the options:
(a)
Local alignment: This type specifically does not assume similarity over the entire length and seeks out the best matching sub-regions. This is the correct answer.
(b) Global alignment: Assumes similarity over the entire length.
(c) Heuristic: This refers to an approach or algorithm that finds an approximate solution, often faster than optimal algorithms (e.g., BLAST and FASTA are heuristic local alignment tools). It's a method type, not an alignment type (local vs. global) itself, though heuristic methods are often used for local alignments.
(d) Clustal (e.g., ClustalW, Clustal Omega): This is a program for performing multiple sequence alignment (aligning three or more sequences), not pairwise alignment. Multiple sequence alignment often aims for a global-like alignment of the set of sequences.
Therefore, local alignment does not assume similarity over the entire length.
\[ \boxed{\text{Local}} \]