Sequence%20Alignment

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Sequence Alignment
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Two general methods for sequence alignment

• Global alignment considers similarity across the
  full extent of the sequences, e.g. MegAlign
• Local alignment focuses on regions of similarity
  in parts of the sequences only, e.g. BLAST
  programs.

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• Questions
• How similar are two sequences?
• What is the best alignment between the two
  sequences?
• How should alignments be scored?
• And, if gaps are allowed, how should they be
  scored?
• Three things are required
• a means of scoring matches and mismatches,
• a means of scoring gaps, and
• a method of using the two to evaluate numerous
  possible alignments.

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Sequence 1 ALCPQCDIE ALC CDE Sequence
2 ALCAKCDVE
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Grouping of amino acids based on
physico-chemical properties important in protein
structures.
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• Commonly used substitution matrices are
• Point Accepted Mutation matrix (PAM)
• PAM250
• BLOcks SUBstitution Matrix (BLOSUM)
• BLOSUM62

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Gap penalties

• Mutational events include not only substitutions
  but also insertions and deletions.
• Affined gap penalties impose an 'opening' penalty
  for a gap and an 'extension' penalty that
  decreases the relative penalty for each
  additional position in an already opened gap.

Sequence 1 ALCPQCDIE ALC CDE Sequence
2 ALCA--DVE
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Sequence Search
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Sensitivity versus Speed

• FASTA looks for exactly matching 'words.
• BLAST uses a scoring matrix.

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• BLAST (Basic Local Alignment Search Tools)
• The BLAST programs have been designed for speed,
  with a minimal sacrifice of sensitivity.
• Include a set of similarity search programs
  designed to explore all of the available sequence
  databases regardless of whether the query is
  protein or DNA.
• The scores assigned in a BLAST search have a
  well-defined statistical interpretation, making
  real matches easier to distinguish from random
  background hits.
• Local alignment may produce more biologically
  meaningful and sensitive results.

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Dynamic programming

• First described in the 1950s.
• First applied in this context by Needleman and
  Wunsch in 1970.
• Breaking the original problem into smaller and
  smaller subproblems until the subproblems have a
  trivial solution, and then using those solutions
  to construct solutions for larger and larger
  portions of the original problem.

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All BLAST programs take the following steps

• The query is divided to overlapping, short word
  sizes, (e.g. 3 for amino acid sequence, 11 for
  nucleotide sequence).
• Words with simple compositions are filtered out.
• The remaining words are searched for in the
  databases.
• After finding the best matching sequence with
  each word, the matching is extended in both
  direction until the highest scoring pairs (HSP)
  are found.
• HSPs are reported to the client.

MNPLSSSGQPHTLM MNP SGQ NPL GQP PLS QPH
LSS PHT SSS HTL SSG TLM
MNGPLSSSGQTSTSPH LSS
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BLAST Programs

• BLASTN
• Compares a nucleotide query sequence against a
  nucleotide sequence database.

• BLASTP
• Compares an amino acid query sequence against a
  protein sequence database.

• BLASTX
• Compares a nucleotide query sequence translated
  in all reading frames against a protein sequence
  database.

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• tblastn
• Compares a protein query sequence against a
  nucleotide sequence database dynamically
  translated in all reading frames.

• tblastx
• Compares the six-frame translations of a
  nucleotide query sequence against the six-frame
  translations of a nucleotide sequence database.

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If your sequence is NUCLEOTIDE

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BLAST search examples