Lab 3'2: Database Similarity Searching

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Lab 3.2 Database Similarity Searching

• The BLAST Buffet
• Stephanie Minnema
• University of Calgary

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Our Goal

• Take a tour of NCBI BLAST
• Review practicalities of submitting BLAST queries
• Understand BLAST output
• Do sequence comparisons using basic and advanced
  BLAST methods

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BLAST is Good For You
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Database Similarity Searching

• The method youll use most!
• Scans a database for alignments to a query
  sequence
• Can get tons of information
• functionality
• evolutionary history
• important residues
• Basis for many forms of bioinformatic analysis

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Most Common Tool

• BLAST basic local alignment search tool
• NCBI and others
• Based on fast local alignment methods
• Global alignment computationally intensive
• Global alignment not always biologically
  significant
• Breaks query down into words (K-tuples)
• Finds regions of similarity
• NCBI uses BLAST 2.0 (gapped BLAST)
• Balances speed and sensitivity

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www.ncbi.nlm.nih.gov/BLAST/
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Basic BLAST Flavors

• blastp protein query vs. protein sequence
  database.
• blastn nucleotide query vs. nucleotide sequence
  database.
• blastx translated nucleotide query vs. protein
  sequence database
• tblastn protein query vs. translated nucleotide
  sequence database
• tblastx translated nucleotide query vs.
  translated nucleotide sequence database.

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Whats Your Favorite Flavor?

• What program will best suit your query, and
  desired output?
• Protein comparisons give most meaningful results
• Sequence complexity 20 aa vs. 4 nt.
• Moderately similar nucleotide sequences could
  encode a highly similar protein sequence!

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Takeout Message 1

• Compare sequences on the protein level unless you
  know your query does not encode a protein product

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Using Basic BLAST Methods

• Example MASH-1 protein sequence from mouse
• Can I find similar proteins in Human?

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Submitting Your Query

• Input query sequence
• FASTA
• Raw
• Accession/ ID
• Choose Database
• Many available varies with program
• For complete list follow the link to

http//www.ncbi.nlm.nih.gov/blast/html/blastcgihel
p.htmlprotein_databases
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Finds Conserved Domains
Limit results with entrez query
E-Value cut off
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Submitting Your Query

• CD Search
• Finds conserved domains in query sequence
• Compares to patterns and profiles of CDs
• Limit by entrez query
• Restricts results to single organism etc.
• E-value cut off
• Restricts results to ones falling below defined
  e-value
• Default 10
• Will revisit concept of e-value

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Filtering
Matrix
Gap Penalties
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Submitting Your Query

• Low complexity filtering
• Low complexity sequence can lead to spurious
  alignments
• Filtering hides these regions
• On by default
• SEG (proteins) or DUST (nucleic acids)
• Should turn it off in some cases what if your
  entire sequence gets filtered?

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Submitting Your Query

• Choice of scoring matrix
• Different ones available
• BLOSUM matrices based on observed frequencies of
  a.a. substitutions
• Each tailored to different levels of sequence
  divergence and length
• BLOSUM 62 default
• Shown to be best at detecting most protein
  similarities dont usually need to change
• Follow link for detailed information

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Submitting Your Query

• Gap Penalties
• Accounts for insertions and deletions in
  different sequences
• Scores are penalized for gaps to prevent aberrant
  alignments
• Opening penalty is high extension penalty is
  lower
• Defaults may change depending on matrix choice
• Rarely need to change default value

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Click for more info
Take note
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Formatting Options
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Understanding Your Results

• Graphic representation of results
• Top of graph represents query sequence
• Underlying bars show where hits occur
• Colors represent alignment scores
• Grey areas represent non similar regions
  surrounded by similar regions
• Scrolling over bar shows accession and
  description of hit
• Clicking on a bar takes you to its alignment with
  the query

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Understanding Your Results

• Bit scores
• Normalized raw score
• Raw score sum of substitution scores and gap
  penalties
• Normalized on basis of scoring method
• Can compare searches scored using different
  matrices
• Higher is better, but dont adequately represent
  significance of alignment

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Understanding Your Results

• E-values
• Indicator of alignment significance
• Number of times an alignment with the same score
  could have arose by chance
• Lower is better
• E-values decrease exponentially as scores for an
  alignment increase

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Examine Results
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Understanding Your Results

• Alignments
• Important to inspect them
• Take note of percent identity and similarity
  between query and aligned sequence
• Examine regions of similarity and gaps
• What if a sub-optimal alignment is the most
  functionally significant one?

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Takeout Message 2

• Dont trust your computer blindly Examine and
  think about your results

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Homology Some Rules to Consider

• Similarity can be indicative of homology
• Generally, if two sequences are significantly
  similar over entire length they are likely
  homologous
• 50 similarity over a short sequence often occurs
  by chance
• Low complexity regions can be highly similar
  without being homologous
• Homologous sequences not always highly similar

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Takeout Message 3

• Homology is like pregnancy

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Basic BLAST Flavors for Special Occasions

• BLAST 2 Sequences (bl2seq)
• Aligns two sequences of your choice
• Can do different types of comparison ex. Blastx
• Gives dot-plot like output
• VecScreen
• Compares query with sequences of known cloning
  vectors
• Both very handy for sequencing!

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Basic BLAST Flavors for Special Occasions

• BLAST against genomes
• Many available
• BLAST parameters pre-optimized
• Handy for mapping query to genome
• Search for short exact matches
• BLAST parameters pre-optimized
• Great for checking probes and primers

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Basic BLAST Flavors for Special Occasions

• megaBLAST
• For aligning sequences which differ slightly due
  to sequencing errors etc.
• Very efficient for long query sequences
• Uses big word (k-tuple) sizes to start search
• Very fast
• Accepts batch submissions of ESTs
• Can upload files of sequences as queries
• More detailed info see megaBLAST pages

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Time to Sample the Buffet

• Try questions 1 4, found at the end of the lab
  notes accompanying this lecture.
• Well discuss them in 15 - 20 minutes

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Advanced BLAST Methods

• The NCBI BLAST pages have several advanced BLAST
  methods available
• PSI-BLAST
• PHI-BLAST
• RPS-BLAST
• All are powerful methods based on protein
  similarities

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More Complex Flavor PSI-BLAST

• Position Specific Iterated BLAST
• A cycling/iterative method
• Gives increased sensitivity for detecting
  distantly related proteins
• Can give insight into functional relationships
• Very refined statistical methods
• Fast still based on BLAST methods
• Simple to use

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PSI-BLAST Principle

• First, a standard blastp is performed
• The highest scoring hits are used to generate a
  multiple alignment
• A PSSM is generated from the multiple alignment.
  
• Highly conserved residues get high scores
• Less conserved residues get lower scores
• Another similarity search is performed, this time
  using the new PSSM
• Steps 2-4 can be repeated until convergence
• No new sequences appear after iteration

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Example Aminoacyl tRNA Synthetases

• 20 enzymes for 20 amino acids
• Each is very different
• Big, small, monomers, tetramers, strange globs
• All bind to their appropriate tRNAs, with high
  specificity
• Bind all for their amino acid, but none of the
  others
• TrpRS and TyrRS share only 13 sequence identity
• BUT, overall structures of TrpRS and TyrRS are
  similar
• Structure ? Function relationship

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Same SCOP family based on catalytic domain
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TyrRS and TrpRS are Similar

• Sequence similarity expected right?
• BUT blastp of E.coli TyrRS against bacterial
  sequences in SwissProt does not show similarity
  with TrpRS
• e-value cutoff of 10

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No TrpRS!?
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Try Using PSI-BLAST

• PSI-BLAST available from BLAST main page
• Query form just like for blastp
• BUT one extra formatting option must be used
• Format for PSI-BLAST check it off!
• Second e-value cutoff used to determine which
  alignments will be used for PSSM build
  Threshold for inclusion
• First search using TyrRS as query
• Db SwissProt limit Bacteria ORGN
• Threshold for inclusion 0.005

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After A Few Iterations
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TyrRS Similarity to TrpRS!
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Power of PSI-BLAST

• We knew TyrRS and TrpRS were similarly
• Functionally and structurally
• Blastp gave no indication
• PSI-BLAST was able to detect their weak sequence
  similarity
• A word of caution be sure to inspect and think
  about the results included in the PSSM build.
• Include/exclude sequences on basis of biological
  knowldge

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Query
Does the query really have a relationship with
the results?
Results
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Takeout Message 4

• Use you biological knowledge when doing PSI-Blast
  to yield the most significant results

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Another Complex Flavour PHI-BLAST

• Pattern Hit Initiated BLAST
• PHI-BLAST principle
• Same method as PSI-BLAST
• Starts first search with query sequence pattern
  for a motif in the query
• PHI-BLAST finds sequences containing the motif
  and having significant sequence similarity in the
  vicinity of the motif occurrence
• Highly specific

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Example TyrRS

• TyrRS contains the aaRS class-I signature
• Want to find sequences containing that motif, and
  regional similarity to TyrRS
• First get the Prosite pattern for the class-I
  signature
• Prosite db of protein families and domains

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http//ca.expasy.org/prosite
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P-x(0,2)-GSTAN-DENQGAPK-x-LIVMFP-HT-LIVMY
AC-G- HNTG-LIVMFYSTAGPC
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Insert Query Sequence
Insert PHI Pattern
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PHI-BLAST Results

• After first search, PHI-BLAST functions same as
  PSI-BLAST
• Result page is the same
• Can iterate in same way.
• Try it later if you like

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The Key to PHI- and PSI-BLAST

• Generating the multiple alignments to create
  PSSMs
• Refines scoring in searches
• Annotated collections of multiple alignments
  defining domains exist
• Conserved domain database (CDD)
• Contains 18039 alignments (10013 last year)
• Can search the CDD using CD search
• Uses RPS-BLAST

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RPS-BLAST

• Reverse Position Specific BLAST
• Opposite of PSI-BLAST
• CDD multiple alignments converted to PSSMs
• PSSMs are processed and turned into a searchable
  database
• Queries are searched against PSSMs using
  RPS-BLAST
• Output indicates conserved domains within the
  query sequence

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Example CRADD protein
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Click on picture to see CDD multiple alignment
Click to see alignment with query
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Summary of Advanced BLAST Methods

• PSI-BLAST
• Input SEQUENCE
• Database SEQUENCES
• Algorithm Constructs a PSSM from an initial pass
  and uses this in the next pass
• Output Distantly related sequences
• sensitive, -specific
• PHI-BLAST
• Input PROFILE SEQUENCE
• Database SEQUENCES
• Algorithm Same as PSI-BLAST except start with a
  profile
• Output Sequences containing the domain and that
  are similar in the domain region
• sensitive, -gt -specific
• RPS-BLAST
• Input SEQUENCE
• Database DOMAINS
• Output Domains found in the sequence
• sensitive, specific

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Back for Another Helping

• Try the remaining questions in the notes!

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Enlightenment begins with a BLAST
Special Thanks to Sohrab Shah for the aaRS
example and further BLAST enlightenment