What I hope you ll learn. Introduction to NCBI & Ensembl tools including BLAST and database searching!

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1 What I hope you ll learn Introduction to NCBI & Ensembl tools including BLAST and database searching What do we learn from database searching and sequence alignments What tools are available at NCBI What tools are available through Ensembl Incorporating Bioinformatics into the High School Biology Curriculum Fran Lewitter, Ph.D. Director, Bioinformatics & Research Computing Whitehead Institute for Biomedical Research Lewitter AT wi.mit.edu Lewitter-Whitehead Institute August 15, Lewitter-Whitehead Institute August 15, First some background info Lewitter-Whitehead Institute August 15,

2 Simian sarcoma virus onc gene, v-sis, is derived from the gene (or genes) encoding a platelet-derived growth factor. Doolittle RF, Hunkapiller MW, Hood LE, Devare SG, Robbins KC, Aaronson SA, Antoniades HN. Science 221: , Why do alignments Use sequence similarity to infer homology and/or structural similarity between 2 or more genes/ proteins Identify more conserved regions of a protein, potentially identifying regions of most functional importance Compare and contrast homologs (perhaps into groups) based on shared positions or regions Infer evolutionary distance from sequence dissimilarity Lewitter-Whitehead Institute August 15, Lewitter-Whitehead Institute August 15, Evolutionary Basis of Sequence Alignment Similarity - observable quantity, such as percent identity Homology - conclusion drawn from data that two genes share a common evolutionary history; no metric is associated with this Paralog genes related by duplication Ortholog genes related by speciation Lewitter-Whitehead Institute August 15, 2012 Local vs Global Alignment LOCAL GLOBAL 7 Lewitter-Whitehead Institute August 15, 2012 From Mount, Bioinformatics, 2004, pg 71 8

3 Nucleotide vs Protein If comparing protein coding genes, use protein sequences because of less noise If protein sequences are very similar, it might be more instructive to use DNA sequences Example of simple scoring system for nucleic acids Match = +1 (ex. A-A, T-T, C-C, G-G) Mismatch = -1 (ex. A-T, A-C, etc) Gap opening = - 5 Gap extension = -2 T C A G A C G A G T G T C G G A - - G C T G = -4 Lewitter-Whitehead Institute August 15, Lewitter-Whitehead Institute August 15, Possible Alignments A:T C A G A C G A G T G B:T C G G A G C T G I. T C A G A C G A G T G -4 T C G G A - - G C T G II. T C A G A C G A G T G -5 T C G G A - G C - T G III.T C A G A C G A G T G -5 T C G G A - G - C T G Scoring for Protein Alignments - Amino Acid Substitution Matrices PAM - point accepted mutation based on global alignment [evolutionary model] BLOSUM - block substitutions based on local alignments [similarity among conserved sequences] Lewitter-Whitehead Institute August 15, Lewitter-Whitehead Institute August 15,

4 AA Scoring Matrices Substitution Matrices PAM - point accepted mutation based on global alignment [evolutionary model] Log-odds= pair in homologous proteins pair in unrelated proteins by chance BLOSUM - block substitutions based on local alignments [similarity among conserved sequences] Log-odds= obs freq of aa substitutions freq expected by chance BLOSUM 30 BLOSUM 62 BLOSUM 80 % identity Increasing similarity PAM 250 (80) PAM 120 (66) PAM 90 (50) % change Lewitter-Whitehead Institute August 15, Lewitter-Whitehead Institute August 15, Scoring for BLAST Alignments Score = 94.0 bits (230), Expect = 6e-19 Identities = 45/101 (44%), Positives = 54/101 (52%), Gaps = 7/101 (6%) Query: 204 YTGPFCDV----DTKASCYDGRGLSYRGLARTTLSGAPCQPWASEATYRNVTAEQ---AR 256 Y+ FC + + CY G G +YRG T SGA C PW S V Q A+ Sbjct: 198 YSSEFCSTPACSEGNSDCYFGNGSAYRGTHSLTESGASCLPWNSMILIGKVYTAQNPSAQ 257 Query: 257 NWGLGGHAFCRNPDNDIRPWCFVLNRDRLSWEYCDLAQCQT 297 GLG H +CRNPD D +PWC VL RL+WEYCD+ C T Sbjct: 258 ALGLGKHNYCRNPDGDAKPWCHVLKNRRLTWEYCDVPSCST 298 Based on BLOSUM62 Position 1: Y - Y = 7 Position 2: T - S = 1 Position 3: G - S = 0 Position 4: P - E = Position 9: - - P = -11 Position 10: - - A = Sum 230 Statistical Significance Raw Scores - score of an alignment equal to the sum of substitution and gap scores. Bit scores - scaled version of an alignment s raw score that accounts for the statistical properties of the scoring system used. E-value - expected number of distinct alignments that would achieve a given score by chance. Lower E-value => more significant. Lewitter-Whitehead Institute August 15, Lewitter-Whitehead Institute August 15,

5 A formula E = Kmn e -λs This is the Expected number of high-scoring segment pairs (HSPs) with score at least S for sequences of length m and n. This is the E value for the score S. The parameters K and λ can be thought of simply as natural scales for the search space size and the scoring system respectively. What s significant? High confidence - >40% identity for long alignments (Rost, 1999 found that sequence alignments unambiguously distinguish between protein pairs of similar and non-similar structure when the pairwise sequence identity >40%) Twilight zone blurry % identity Midnight zone - <20% identity Lewitter-Whitehead Institute August 15, Lewitter-Whitehead Institute August 15, Tools of Interest NCBI Home Page NCBI (US) - BLAST Entrez EBI/EMBL/WTSI (Europe) Ensembl ( Lewitter-Whitehead Institute August 15, Lewitter-Whitehead Institute August 15,

6 Ensembl Home Page Hands-On Entrez finding sequences BLAST look for similar sequences Ensembl finding sequences Lewitter-Whitehead Institute August 15, Lewitter-Whitehead Institute August 15, How is BLAST WIBR? Looking for homologs Identifying domains in proteins Peptide identification Genome annotation Remember 1. Don t be afraid to look at help pages for each website Click, click, click 2. Any analysis tool will give you results 3. Interpret results you find Lewitter-Whitehead Institute August 15, Lewitter-Whitehead Institute August 15,