Novel Peptide Identification using ESTs and Genomic Sequence

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Novel Peptide Identification using ESTs and
Genomic Sequence

• Nathan Edwards
• Center for Bioinformatics and Computational
  Biology
• University of Maryland, College Park

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Sample Preparation for Peptide Identification
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Mass Spectrometer

• ElectronMultiplier(EM)

• Time-Of-Flight (TOF)
• Quadrapole
• Ion-Trap

• MALDI
• Electro-SprayIonization (ESI)

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Single Stage MS
MS
m/z
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Tandem Mass Spectrometry(MS/MS)
m/z
Precursor selection
m/z
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Tandem Mass Spectrometry(MS/MS)
Precursor selection collision induced
dissociation (CID)
m/z
MS/MS
m/z
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Peptide Identification

• For each (likely) peptide sequence
• 1. Compute fragment masses
• 2. Compare with spectrum
• 3. Retain those that match well
• Peptide sequences from protein sequence databases
• Swiss-Prot, IPI, NCBIs nr, ...
• Automated, high-throughput peptide identification
  in complex mixtures

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What goes missing?

• Known coding SNPs
• Novel coding mutations
• Alternative splicing isoforms
• Alternative translation start-sites
• Microexons
• Alternative translation frames

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Why should we care?

• Alternative splicing is the norm!
• Only 20-25K human genes
• Each gene makes many proteins
• Proteins have clinical implications
• Biomarker discovery
• Evidence for SNPs and alternative splicing stops
  with transcription
• Genomic assays, ESTs, mRNA sequence.
• Little hard evidence for translation start site

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Novel Splice Isoform
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Novel Splice Isoform
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Novel Frame
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Novel Frame
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Novel Mutation
Ala2?Pro associated with familial amyloid
polyneuropathy
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Novel Mutation
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Genomic Peptide Sequences

• Genomic DNA
• Exons introns, 6 frames, large (3Gb ? 6Gb)
• ESTs
• No introns, 6 frames, large (4Gb ? 8Gb)
• Used by gene, protein, and alternative splicing
  annotation pipelines
• Highly redundant, nucleotide error rate 1

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Compressed EST Database

• Six-frame translation of all ESTs
• Optionally, ESTs that map to a gene
• Eliminate ORFs lt 30 amino-acids
• Amino-acid 30-mers
• Observed in at least two ESTs
• Represent AA 30-mers in C3 FASTA database
• Complete, Correct, Compact

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SBH-graph
ACDEFGI, ACDEFACG, DEFGEFGI
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Compressed SBH-graph
ACDEFGI, ACDEFACG, DEFGEFGI
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Sequence Databases CSBH-graphs

• Original sequences correspond to paths

ACDEFGI, ACDEFACG, DEFGEFGI
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Sequence Databases CSBH-graphs

• All k-mers represented by an edge have the same
  count

1
2
2
1
2
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cSBH-graphs

• Quickly determine those that occur twice

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2
1
2
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Compressed-SBH-graph
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2
1
2
ACDEFGI
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Compressed EST Database

• Gene centric compressed EST peptide sequence
  database
• 20,774 sequence entries
• 8Gb vs 223 Mb
• 35 fold compression
• 22 hours becomes 15 minutes
• E-values improve by similar factor!
• Makes routine EST searching feasible
• Search ESTs instead of IPI?

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Conclusions

• Peptides identify more than just proteins
• Compressed peptide sequence databases make
  routine EST searching feasible
• cSBH-graph edge counts C2/C3 enumeration
  algorithms
• Minimal FASTA representation of k-mer sets

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Collaborators

• Chau-Wen Tseng, Xue Wu
• Computer Science
• Catherine Fenselau, Crystal Harvey
• Biochemistry
• Calibrant Biosystems
• Thanks to PeptideAtlas, X!Tandem