Familiarization with bioinformatics terms:

• Query Sequences: Sequence obtained by experiments or desired sequence retrieve from database.
• Database sequence: Sequences deposited in database
• Identity is a measure made on an alignment

Sequence A can be “32 % identical to” Sequence B

• Similarity is a measure of how close two amino acids are.
• For instance, isoleucine and leucine are similar

Homology is a property that exists or does not exist and reflects the evolutionary association between two sequences.

• Sequence A IS or IS NOT homologous to Sequence B
• Sequence A cannot be “40% homologous to” B
• Homology is established on the basis of measured similarity or identity

Some Uses for BLAST

• Identify an unknown sequence (protein/nucleotide) by comparing a sequence against the sequence database
• To identify sequences homologous to query
  • Similarity may extent to entire length
  • Similarity may be restricted to local regions (domains)
• Build a homology tree for a protein/nucleotide sequence
• Get clues about protein structure by finding similar proteins with known structures
• Map a sequence in a genome

Steps in sequence-based database searching

• Identify the query sequence
  • Protein/nucleic acid
• Select an algorithm/tool
  • BLAST (BLASTp or BLASTn)
• Select the database
  • Protein or nucleic acid sequence database
  • One or all databases
• Fire the query
  • On-line / Off-line
• Analyse the results
  • Statistically significant vs chance findings

The most widely used BLAST in world!

Free, online service from National Center for Biotechnology Information (NCBI)

http://blast.ncbi.nlm.nih.gov/Blast.cgi

BLAST family of programs

• Blastp: compares an amino acid query sequence against a protein sequence database
• Blastn: compares a nucleotide query sequence against a nucleotide sequence database
• Blastx: compares a nucleotide query sequence translated in all reading frames against a protein sequence database
• 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.

 Asking the Right Question with BLAST

 Pairwise alignment: key points

• Pairwise alignments allow us to describe the percent identity two sequences share, as well as the percent similarity
• The score of a pairwise alignment includes positive values for exact matches, and negative scores for mismatches and gaps
• PAM and BLOSUM matrices (Specialized pair wise alignment matrics ) are used for protein alignment. PAM250 and BLOSUM30 are examples of matrices used to score distantly related proteins.

Pair-wise alignment is the key for BLAST search:

Pair-wise alignment  score relies on 3 factors:

1. Positive hits/matches
2. Mismatches scores
3. Gap penalties

Identity score = Number of positive hits × score of each positive hit- {(Number of mismatches × Score of each mismatches) + (Number of gaps × score for each gap penalty)}

Here:

* = Positive match

–  = Mismatch

Gap= gap between the sequences

Score for each positive hit = 1, total no of positive hits=18

Score for each mismatch = 2, total number of mismatches= 5

Penalty score for each gap= 2 (you can set the penalty score of gap), total numbers of gaps =3

Score= ?

Two major types of pair-wise alignment:

1. Local alignment: Compares segments of sequences :

• The alignment may contain just a portion of either sequence, and is appropriate for finding matched domains between sequences.
• Finds cases when one sequence is a part of another sequence, or they only     in parts.

2. Global alignment: Compares total length of two sequences

• Global alignment using dynamic programming to find optimal alignments between two sequences.
• Gaps are permitted in the alignments, and the total lengths of both sequences are aligned (hence “global”).

Typical BLAST output

 

Interpreting Results

• Score: Normalized score of alignment Considering positive matches, mismatches gap penalty and substitution matrix (SM for proteins only).
• Max score: Score of single best aligned sequence
• Total score: Sum of scores of all aligned sequences
• Query coverage: What percent of query sequence is aligned

Interpreting Statistical results

• E Value: Number of matches with same score expected by chance. Lower the E-value higher is the significance of score, and lower the possibility of random matches. Typically, E < .05 is required to be considered significant

• P-value indicates level of significance of the random alignment or alignment from a chance alone. Lower P score indicates lower chance of random alignment and higher significance of observed homology.

Algorithm Parameters: Fine-tune the algorithm

• Expect threshold: The lower it is, the fewer false positives (but you might miss real hits)
• Scoring Matrix: For protein alignment:
• PAM: Accepted Point Mutation
• Empirically derived chance a substitution will be accepted, based on closely related proteins (BLASTp)
• Higher PAM numbers correspond to greater evolutionary distance
• BLOSUM: Blacks Substitution Matrix
• Another empirically derived matrix, based on more distantly related proteins (PSI-BLAST)
• Lower BLOSUM numbers correspond to greater evolutionary distance

Specialized BLAST:

• PSI-BLAST
• PHI-BLAST
• MegaBLAST
• Discontigous Megablast

PSI-BLAST

PSI-BLAST is Position-Specific Iterated BLAST

• More sensitive than BLAST: finds matches BLAST would not find
• More specific than BLAST: reports fewer false matches
• A bit slower than BLAST
• PSI-BLAST finds remote homologues
• Will let you identify very distant members of your protein family
• PSI-BLAST uses the results of each iteration to increase its specificity

PSI-BLAST Iterations

• PSI-BLAST uses the best results of the first iteration to build a profile (PSSM)
• PSI-BLAST uses the profile to re-scan the database
• PSI-BLAST keeps re-scanning until it stops finding new matches

Some Tips for Using PSI-BLAST

• If your protein is multi-domain, search one domain at a time
• PSI-BLAST is slower than normal BLAST because of the iterations
• You can feed PSI-BLAST with your own PSSM – Use the NCBI server for this purpose

PHI-BLAST

• Protein-protein BLAST
• Pattern Hit Initiated BLAST
• Modified version of PSI-BLAST
• Specify a pattern that hits must match
• Use when you know protein family has a signature pattern: active site, structural domain, etc.
• Better chance of eliminating false positives

Megablast

• For large Nucleotide BLAST
• Finds highly similar sequences
• Very fast
• Use to identify a nucleotide sequence

Discontiguous Megablast

• Nucleotide BLAST
• Highly dissimilar sequences
• Use to find diverged sequences (possible homologies) from different organisms