6 Difference Between Pairwise And Multiple Sequence Alignment

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What Is Pairwise Sequence Alignment?

Pairwise alignment is one of the most fundamental tools of bioinformatics and underpins a variety of other, more sophisticated methods of annotation. The goal of Pairwise sequence alignment is to establish a correspondence between the elements in a pair of sequence that share a common property, such as common ancestry or a common structural or functional role. In computational biology, the sequences under consideration are typically nucleic acid or amino acid polymers.

What You Need To Know About Pairwise Sequence Alignment

  • An alignment procedure comparing two biological sequences of either protein, DNA or RNA.
  • Pairwise alignments can be generally categorized as global or local alignment methods.
  • Comparatively simple algorithm is used.
  • A general global alignment technique is the Needleman–Wunsch algorithm. A general local alignment method is Smith–Waterman algorithm.
  • Applications: a) Primarily to find out conserved regions between the two sequences. b)Similarity searches in a database.
  • Examples of pairwise alignment tools: LALIGN, BLAST, EMBOSS Needle; EMBOSS Water

What Is Multiple Sequence Alignment?

Multiple Sequence Alignment is a tool used to study closely related genes or proteins in order to find the evolutionary relationship between genes and to identify shared patterns among functionally or structurally related genes. From the resulting MSA, sequence homology can be inferred and Phylogenetic analysis can be conducted to assess the sequences’ shared evolutionary origins.

Multiple sequence alignment is often used to assess sequence conservation of protein domains, tertiary and secondary structures and even individual amino acids or nucleotides.

MSAs require more sophisticated methodologies than Pairwise  alignment because they are more computationally complex. Most multiple sequence alignment programs use heuristic methods rather than global optimization because identifying the optimal alignment between more than a few sequences of moderate length is prohibitively computationally expensive.  

What You Need To Know About Multiple Sequence Alignment

  • An alignment procedure comparing three or more biological sequences of either protein, DNA or RNA.
  • MSA is generally a global multiple sequence alignment.
  • Complex sophisticated algorithm is used.
  • A technique called progressive alignment method is employed. In this approach, a pairwise alignment algorithm is used iteratively, first to align the most closely related pair of sequences, then the next most similar one to that pair, and so on.
  • Applications: a) To detect regions of variability or conservation in a family of proteins; b) Phylogenetic analysis (inferring a tree, estimating rates of substitution, etc.) ; c) Detection of homology between a newly sequenced gene and an existing gene family prediction of protein structure; d) Demonstration of homology in multigene families.
  • Examples of Multiple Sequence Alignment tools: MUSCLE; T-Coffee; MAFFT; CLUSTALW.

Also Read: Difference Between Global And Local Sequence Alignment

Difference Between Pairwise And Multiple Sequence Alignment In Tabular Form

BASIS OF COMPARISON PAIRWISE SEQUENCE ALIGNMENT MULTIPLE SEQUENCE ALIGNMENT
Description An alignment procedure comparing two biological sequences of either protein, DNA or RNA.   An alignment procedure comparing three or more biological sequences of either protein, DNA or RNA.  
Category Pairwise alignments can be generally categorized as global or local alignment methods.   MSA is generally a global multiple sequence alignment.  
Algorithm Comparatively simple algorithm is used.   Complex sophisticated algorithm is used.  
Techniques A general global alignment technique is the Needleman–Wunsch algorithm. A general local alignment method is Smith–Waterman algorithm.   A technique called progressive alignment method is employed. In this approach, a pairwise alignment algorithm is used iteratively, first to align the most closely related pair of sequences, then the next most similar one to that pair, and so on.  
Application – Primarily to find out conserved regions between the two sequences.     -Similarity searches in a database.   -To detect regions of variability or conservation in a family of proteins;   -Phylogenetic analysis (inferring a tree, estimating rates of substitution, etc.) ;   -Detection of homology between a newly sequenced gene and an existing gene family prediction of protein structure;   -Demonstration of homology in multigene families.
Example Of Tools -LALIGN

  -BLAST
 
 -EMBOSS Needle

 -EMBOSS Water  
-MUSCLE
 
-T-Coffee
 
-MAFFT
 
-CLUSTALW.

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