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Introduction to NCBI & Ensembl tools including BLAST and database searching

Introduction to NCBI & Ensembl tools including BLAST and database searching. Incorporating Bioinformatics into the High School Biology Curriculum. Fran Lewitter, Ph.D. Founding Director, Bioinformatics & Research Computing Whitehead Institute for Biomedical Research

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Introduction to NCBI & Ensembl tools including BLAST and database searching

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  1. Introduction to NCBI & Ensembltools including BLAST and database searching Incorporating Bioinformatics into the High School Biology Curriculum Fran Lewitter, Ph.D. Founding Director, Bioinformatics & Research Computing Whitehead Institute for Biomedical Research Lewitter (-AT--) iscb.org http://www.iscb.org/iscb-education-home

  2. What I hope you’ll learn • What do we learn from database searching and sequence alignments • What tools are available at NCBI • What tools are available through Ensembl Lewitter-ISCB High School Teachers Workshop – 7/11/14

  3. First some background info It’s all about alignments. Lewitter-ISCB High School Teachers Workshop – 7/11/14

  4. Lewitter-ISCB High School Teachers Workshop – 7/11/14

  5. 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 221:275-277, 1983. Lewitter-ISCB High School Teachers Workshop – 7/11/14

  6. 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-ISCB High School Teachers Workshop – 7/11/14

  7. 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-ISCB High School Teachers Workshop – 7/11/14

  8. Local vs Global Alignment LOCAL GLOBAL From Mount, Bioinformatics, 2004, pg 71 Lewitter-ISCB High School Teachers Workshop – 7/11/14

  9. 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 Lewitter-ISCB High School Teachers Workshop – 7/11/14

  10. 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 TCAG AC G A GT G TCGG A- - G CT G +1 +1 -1 +1 +1 -5 -2 -1 -1 +1 +1 = -4 Lewitter-ISCB High School Teachers Workshop – 7/11/14

  11. 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. TCAG AC G A GT G TCGG A- - G CT G score=-4 score=-5 score=-5 II. TCAG AC G A GT G TCGG A- G C -T G III. TCAG AC G A GT G TCGG A- G - CT G Lewitter-ISCB High School Teachers Workshop – 7/11/14

  12. 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-ISCB High School Teachers Workshop – 7/11/14

  13. AA Scoring Matrices • PAM - point accepted mutation based on global alignment[evolutionary model] • BLOSUM - block substitutions based on local alignments [similarity among conserved sequences] Log-odds= pair in homologous proteins pair in unrelated proteins bychance Log-odds= obs freq of aa substitutions freq expected by chance Lewitter-ISCB High School Teachers Workshop – 7/11/14

  14. BLOSUM 30 BLOSUM 62 BLOSUM 80 % identity PAM 250 (80) PAM 120 (66) PAM 90 (50) % change Substitution Matrices Increasing similarity Lewitter-ISCB High School Teachers Workshop – 7/11/14

  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 Position 1: Y - Y = 7 Position 2: T - S = 1 Position 3: G - S = 0 Position 4: P - E = -1 . . . Position 9: - - P = -11 Position 10: - - A = -1 . . . Sum 230 Based on BLOSUM62 Lewitter-ISCB High School Teachers Workshop – 7/11/14

  16. 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-ISCB High School Teachers Workshop – 7/11/14

  17. A formula E = Kmn e-lS 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 lcan be thought of simply as natural scales for the search space size and the scoring system respectively. Lewitter-ISCB High School Teachers Workshop – 7/11/14

  18. 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 - 20-35% identity • “Midnight zone” - <20% identity Lewitter-ISCB High School Teachers Workshop – 7/11/14

  19. Tools of Interest • NCBI (US) - http://www.ncbi.nlm.nih.gov/ • BLAST • Entrez • EBI/EMBL/WTSI (Europe) • Ensembl (http://www.ensembl.org/) Lewitter-ISCB High School Teachers Workshop – 7/11/14

  20. NCBI Home Page http://www.ncbi.nlm.nih.gov Lewitter-ISCB High School Teachers Workshop – 7/11/14

  21. Ensembl Home Page http://ensembl.org Lewitter-ISCB High School Teachers Workshop – 7/11/14

  22. Hands-On • Entrez – finding sequences • BLAST – look for similar sequences • Ensembl – finding sequences Lewitter-ISCB High School Teachers Workshop – 7/11/14

  23. How is BLAST used? • Looking for homologs • Identifying domains in proteins • Peptide identification • Genome annotation Lewitter-ISCB High School Teachers Workshop – 7/11/14

  24. Remember • Don’t be afraid to look at help pages for each website • Click, click, click • Any analysis tool will give you results • Interpret results you find Lewitter-ISCB High School Teachers Workshop – 7/11/14

  25. Sequence of Note Biotechniques, 1992 1 GCGTTGCTGG CGTTTTTCCA TAGGCTCCGC 31CCCCCTGACG AGCATCACAA AAATCGACGC 61 GGTGGCGAAA CCCGACAGGA CTATAAAGAT ………….. 1371 GTAAAGTCTG GAAACGCGGA AGTCAGCGCC “Here you see the actual structure of a small fragment of dinosaur DNA,” Wu said. “Notice the sequence is made up of four compounds - adenine, guanine, thymine and cytosine. This amount of DNA probably contains instructions to make a single protein - say, a hormone or an enzyme. The full DNA molecule contains three billion of these bases. If we looked at a screen like this once a second, for eight hours a day, it’d still take more than two years to look at the entire DNA strand. It’s that big.” (page 103) (Published in 1990) Lewitter-ISCB High School Teachers Workshop – 7/11/14

  26. DinoDNA "Dinosaur DNA" from Crichton's THE LOST WORLD p. 135 GAATTCCGGAAGCGAGCAAGAGATAAGTCCTGGCATCAGATACAGTTGGAGATAAGGACGACGTGTGGCAGCTCCCGCAGAGGATTCACTGGAAGTGCATTACCTATCCCATGGGAGCCATGGAGTTCGTGGCGCTGGGGGGGCCGGATGCGGGCTCCCCCACTCCGTTCCCTGATGAAGCCGGAGCCTTCCTGGGGCTGGGGGGGGGCGAGAGGACGGAGGCGGGGGGGCTGCTGGCCTCCTACCCCCCCTCAGGCCGCGTGTCCCTGGTGCCGTGGCAGACACGGGTACTTTGGGGACCCCCCAGTGGGTGCCGCCCGCCACCCAAATGGAGCCCCCCCACTACCTGGAGCTGCTGCAACCCCCCCGGGGCAGCCCCCCCCATCCCTCCTCCGGGCCCCTACTGCCACTCAGCAGCGCCTGCGGCCTCTACTACAAAC…… Published in 1995 Lewitter-ISCB High School Teachers Workshop – 7/11/14

  27. >Erythroid transcription factor (NF-E1 DNA-binding protein) Query: 121 MEFVALGGPDAGSPTPFPDEAGAFLGLGGGERTEAGGLLASYPPSGRVSLVPWADTGTLG 300 MEFVALGGPDAGSPTPFPDEAGAFLGLGGGERTEAGGLLASYPPSGRVSLVPWADTGTLG Sbjct: 1 MEFVALGGPDAGSPTPFPDEAGAFLGLGGGERTEAGGLLASYPPSGRVSLVPWADTGTLG 60 Query: 301 TPQWVPPATQMEPPHYLELLQPPRGSPPHPSSGPLLPLSSGPPPCEARECVMARKNCGAT 480 TPQWVPPATQMEPPHYLELLQPPRGSPPHPSSGPLLPLSSGPPPCEARECV NCGAT Sbjct: 61 TPQWVPPATQMEPPHYLELLQPPRGSPPHPSSGPLLPLSSGPPPCEARECV----NCGAT 116 Query: 481 ATPLWRRDGTGHYLCNWASACGLYHRLNGQNRPLIRPKKRLLVSKRAGTVCSHERENCQT 660 ATPLWRRDGTGHYLCN ACGLYHRLNGQNRPLIRPKKRLLVSKRAGTVCS NCQT Sbjct: 117 ATPLWRRDGTGHYLCN---ACGLYHRLNGQNRPLIRPKKRLLVSKRAGTVCS----NCQT 169 Query: 661 STTTLWRRSPMGDPVCNNIHACGLYYKLHQVNRPLTMRKDGIQTRNRKVSSKGKKRRPPG 840 STTTLWRRSPMGDPVCN ACGLYYKLHQVNRPLTMRKDGIQTRNRKVSSKGKKRRPPG Sbjct: 170 STTTLWRRSPMGDPVCN---ACGLYYKLHQVNRPLTMRKDGIQTRNRKVSSKGKKRRPPG 226 Query: 841 GGNPSATAGGGAPMGGGGDPSMPPPPPPPAAAPPQSDALYALGPVVLSGHFLPFGNSGGF 1020 GGNPSATAGGGAPMGGGGDPSMPPPPPPPAAAPPQSDALYALGPVVLSGHFLPFGNSGGF Sbjct: 227 GGNPSATAGGGAPMGGGGDPSMPPPPPPPAAAPPQSDALYALGPVVLSGHFLPFGNSGGF 286 Query: 1021 FGGGAGGYTAPPGLSPQI 1074 FGGGAGGYTAPPGLSPQI Sbjct: 287 FGGGAGGYTAPPGLSPQI 304 Lewitter-ISCB High School Teachers Workshop – 7/11/14

  28. >Erythroid transcription factor (NF-E1 DNA-binding protein) Query: 121 MEFVALGGPDAGSPTPFPDEAGAFLGLGGGERTEAGGLLASYPPSGRVSLVPWADTGTLG 300 MEFVALGGPDAGSPTPFPDEAGAFLGLGGGERTEAGGLLASYPPSGRVSLVPWADTGTLG Sbjct: 1 MEFVALGGPDAGSPTPFPDEAGAFLGLGGGERTEAGGLLASYPPSGRVSLVPWADTGTLG 60 Query: 301 TPQWVPPATQMEPPHYLELLQPPRGSPPHPSSGPLLPLSSGPPPCEARECVMARKNCGAT 480 TPQWVPPATQMEPPHYLELLQPPRGSPPHPSSGPLLPLSSGPPPCEARECV NCGAT Sbjct: 61 TPQWVPPATQMEPPHYLELLQPPRGSPPHPSSGPLLPLSSGPPPCEARECV----NCGAT 116 Query: 481 ATPLWRRDGTGHYLCNWASACGLYHRLNGQNRPLIRPKKRLLVSKRAGTVCSHERENCQT 660 ATPLWRRDGTGHYLCN ACGLYHRLNGQNRPLIRPKKRLLVSKRAGTVCS NCQT Sbjct: 117 ATPLWRRDGTGHYLCN---ACGLYHRLNGQNRPLIRPKKRLLVSKRAGTVCS----NCQT 169 Query: 661 STTTLWRRSPMGDPVCNNIHACGLYYKLHQVNRPLTMRKDGIQTRNRKVSSKGKKRRPPG 840 STTTLWRRSPMGDPVCN ACGLYYKLHQVNRPLTMRKDGIQTRNRKVSSKGKKRRPPG Sbjct: 170 STTTLWRRSPMGDPVCN---ACGLYYKLHQVNRPLTMRKDGIQTRNRKVSSKGKKRRPPG 226 Query: 841 GGNPSATAGGGAPMGGGGDPSMPPPPPPPAAAPPQSDALYALGPVVLSGHFLPFGNSGGF 1020 GGNPSATAGGGAPMGGGGDPSMPPPPPPPAAAPPQSDALYALGPVVLSGHFLPFGNSGGF Sbjct: 227 GGNPSATAGGGAPMGGGGDPSMPPPPPPPAAAPPQSDALYALGPVVLSGHFLPFGNSGGF 286 Query: 1021 FGGGAGGYTAPPGLSPQI 1074 FGGGAGGYTAPPGLSPQI Sbjct: 287 FGGGAGGYTAPPGLSPQI 304 Lewitter-ISCB High School Teachers Workshop – 7/11/14

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