Bioinformatics, Sequences and Genomes

Transcription

1 Bioinformatics, Sequences and Genomes BL4273 Bioinformatics for Biologists Week 1 Daniel Barker, School of Biology, University of St Andrews db60@st-andrews.ac.uk

2 BL4273 and 4273π 4273π is a custom Linux operating system for the Raspberry Pi, including an Open Access course in bioinformatics. The Open Access course is based on BL4273 and is similar, but not identical. See: Barker, D., Ferrier, D.E.K., Holland, P.W.H., Mitchell, J.B.O., Plaisier, H., Ritchie, M.D. and Smart, S.D. (2013) 4273π: bioinformatics education on low cost ARM hardware. BMC Bioinformatics 14: 243. Further discussion in BMC s Biome magazine:

3 What is bioinformatics? Use of computers in biology DNA, RNA, proteins sequences, structure, function, expression Amount of data is large Release 123 of the European Nucleotide Archive database (March 2015) contains 1,154,095,724,206 nucleotides Degree of automation should be as high as possible

4 Some research examples Alderson, R.G., Barker, D. and Mitchell, J.B.O. (2014) One origin for metallo-β-lactamase activity, or two? An investigation assessing a diverse set of reconstructed ancestral sequences based on a sample of phylogenetic trees. Journal of Molecular Evolution 79: It is unclear whether metallo-β-lactamse activity evolved once or twice. Latysheva, N., Junker, V.L., Palmer, W.J., Codd, G.A. and Barker, D. (2012) The evolution of nitrogen fixation in cyanobacteria. Bioinformatics 28: The last common ancestor of cyanobacteria may have fixed nitrogen. Lim, J.-H., Iggo, R.D. and Barker, D. (2013) Nucleic Acids Research 41: Chromatin modification data help us identify functional p53 transcription factor binding sites. Mendivil Ramos, O., Barker, D. and Ferrier, D.E.K. (2012) Ghost loci imply Hox and ParaHox existence in the last common ancestor of animals. Current Biology 22:

5 Nucleotide database growth Source:

6 The major nucleotide sequence databases GenBank (USA), EMBL (EU), DDBJ (Japan) These three databases share their data. To access the data, we can use GQuery at the National Center for Biotechnology Information (NCBI), USA

7 A typical DNA record at the NCBI accession.version Source: NCBI GQuery,

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11 Same sequence in Fasta format Source: NCBI GQuery,

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13 What is a genome? Sum total of heritable nucleic acids in an individual (or organelle, or virus particle) DNA for some viruses and all (other) life RNA for most viruses

14 Raw genome data Genome sequence Transcriptome sequence Gene expression data Variation data (polymorphisms, repeats, allele frequencies) Subsequent bioinformatic analysis Genome annotation Functional annotation

15 Growth of genome sequence databases In June 2015: In 2012: Source: GOLD database,

16 Genome sequencing Decent job sequencing a eukaryotic genome: 20,000 to 1,000,000. Decent job sequencing a eukaryotic transcriptome: 1,000 to 2,000. Technology is moving fast. Sequencing a eukaryotic genome to draft standard will soon cost < 1,000. (Doing a proper job of sequencing a genome to finished standard remains extremely expensive.)

17 Genome analysis Stage: Methods: Genome sequencing (laboratory) Genome assembly computers Genome annotation computers Computational genome analysis single-genome analyses computers comparative analyses computers (Validate computational predictions laboratory)

18 DNA sequencing Reads Source: NCBI Traces Archive,

19 Genome assembly Genomes Reads Contigs fragment assembly software whole-genome assembly software Contigs Assembly

20 Genome annotation Genes Genomic DNA (contigs / assembly) Known mrnas and proteins + ab initio methods Genome annotation procedure Putative genes location in the genome, DNA, mrna and protein sequences

21 Genes Biology How do genes vary? Correlate with environmental, phenotypic and genomic features How are gene products affected? Secondary and tertiary structure Active sites Protein-protein and protein-dna interaction surfaces What are the consequences? Disease Virulence Drug susceptibility and resistance Fitness and adaptation Speciation

22 Protein sequences Most protein sequences are obtained by conceptual translation of coding DNA. It is usually DNA which is sequenced in the laboratory, rather than protein. The protein database available via Gquery includes translations of all annotated coding sequences in the DNA database. Additionally it includes SwissProt, a highquality (but smaller) protein sequence database.

23 Protein sequence databases GenPept (via GQuery) Translation of all coding sequences in Genbank Automatically generated without review High volume, unpredictable quality Swissprot (via GQuery and various sites) Whole-genome data: genomic DNA Manually curated Low volume, high quality

24 Protein sequence in Fasta format Single-letter amino acid codes G P A V L I M C F Y glycine proline alanine valine leucine isoleucine methionine cysteine phenylalanine tyrosine W H K R Q N E D S T tryptophan histidine lysine arginine glutamine asparagine glutamic Acid aspartic Acid serine threonine

25 Genome databases Contain sequence and annotation Often better than general databases, for the genome in question There are many for example Ensembl NCBI Genome

26 Gene expression database GEO Further protein databases RefSeq, genome-oriented PDB: structures

27 General aims of BL4273 To see what research-grade bioinformatics is like. To reach the point where, in a biology or biochemistry research project, you can begin to do the necessary bioinformatics for that project. Underlying principles, data, software, computers, scripting. Linux operating system, command-line software. Have fun.

28 Module contents Five lectures Seven practical classes, 2 hours each One tutorial, up to 2 hours One seminar, 2 hours One practical-project to complete and write up in your own time (50% of final grade) One exam (50% of final grade)

29 Recommended reading: main journals Bioinformatics PLoS Computational Biology BMC Bioinformatics Nucleic Acids Research Genome Research All papers more than a year old in Bioinformatics, and more than six months old in Genome Research, are available free online. PLoS Computational Biology, BMC Bioinformatics and Nucleic Acids Research are Open Access journals, with all published content available free online.

30 Recommended reading: main books Bradnam, K. and Korf, I. (2012) UNIX and Perl to the Rescue! A field guide for the life sciences (and other data-rich pursuits). (Cambridge: Cambridge University Press) Baxevanis, A.D. and Ouellette, B.F.F., editors (2005) Bioinformatics: A practical Guide to the Analysis of Genes and Proteins, 3rd edition (Hoboken, New Jersey: John Wiley). Dear, P.H., editor (2007) Bioinformatics (Bloxham, Oxfordshire: Scion). Schwartz, R.L., Phoenix, T. and foy, b d (2008) Learning Perl, 5th edition (Sebastopol, California: O'Reilly). Zvelebil, M. and Baum, J.O. (2007) Understanding Bioinformatics (New York: Garland Science).

31 Recommended reading: other books Robbins, A. (2006). UNIX in a Nutshell, 4th edition (Sebastopol, California: O Reilly). Christiansen, T., foy, b d and Orwant, J. (2012) Programming Perl, 4th edition (Sebastopol, California: O Reilly). [3rd ed. is also OK.] Brown, T.A. (2007) Genomes, 3rd edition (New York: Garland Science). Cristianini, N. and Hahn, M.W. (2007) Introduction to Computational Genomics: A Case Studies Approach (Cambridge: Cambridge University Press). Kernighan, B.W. and Pike, R. (1984) The UNIX Programming Environment (Englewood Cliffs: Prentice-Hall). Orengo, C.A., Jones, D.T. and Thornton, J.M. (2003) Bioinformatics: Genes, Proteins and Computers (Oxford: BIOS Scientific). Sunnerhagen, P. and Piškur, J., editors (2006) Comparative Genomics: Using Fungi as Models (Heidelberg: Springer).

32 Further reading for the keen: genre-defining classics Durbin, R., Eddy, S., Krogh, A. and Mitchison, G. (1998) Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids (Cambridge: Cambridge University Press). Baldi, P. and Brunak, S. (2001) Bioinformatics: The Machine Learning Approach, 2nd edition (Cambridge, Massachusetts: MIT Press). Deonier, R.C., Tavaré, S. and Waterman, M. (2005) Computational Genome Analysis: An Introduction (New York: Springer). These three books are beyond the scope of this course. But you may wish to take a look.