Biological Databases

1. Biological Databases Lecture 9 2/16/2018 Instructor: Kritika Karri kkarri@bu.edu

2. Class Objectives • Why are databases the backbone of bioinformatics ? • The basic structure of a database • Data storage versus annotation- Refseq Database • Types of DBs: Genbank, PubMed, and NCBI • Query strategies • Quality of data issues

3. Biologists Collect Lots of Data • Hundreds of thousand of species • Million of articles in scientific literature • Genetic Information • Gene names (thousands) • Phenotype of mutants • Location of genes/mutations on chromosomes • Linkage (distances between genes)

4. What is a Database ? • A collection data that needs to be : • Structured • Searchable • Updated (periodically) • Cross referenced • Challenge: • To change “meaningless” data into useful information that can be accessed and analysed the best way possible. • For example: • How would you organise all biological sequences so that the biological information is optimally accessible?

5. A spreadsheet can be a Database • Columns are Fields • Rows are Records • Can search for a term within just one field • Or combine searched across several fields.

6. Database Organisation • Internal Organisation • Controls speed and flexibility. • A unit of programs that • Store • Extract • Modify • Flat file databases (flat DBMS) • Simple, restrictive, table • Hierarchical databases • Simple, restrictive, tables • Relational databases (RDBMS) • Complex, versatile, tables • Object-oriented databases (ODBMS) • Data warehouses and distributed databases

7. Where do the data come from ?

8. Types of Data • Sequence or Structure • Nucleic acid or protein • Important biological information such as about genes and their metabolic pathways, mutations, diseases, drugs, images etc.

9. Biological Database Architecture

10. Types of Database • Primary Databases: • Original submissions by experimentalists • Content controlled by the submitter • Examples: GenBank, Trace, SRA, SNP, GEO • Secondary databases: • Results of analysis of primary databases • Aggregate of many databases • Content controlled by third party (NCBI) • Examples: NCBI Protein, Refseq, TPA, RefSNP, GEO datasets, UniGene, Homologene, Structure, Conserved Domain

12. International Sequence Database Collaboration International Sequence Database Collaboration: http://www.insdc.org/ National Centre for Biotechnology Information (NCBI) : https://www.ncbi.nlm.nih.gov/ European Nucleotide Archive (ENA) :https://www.ebi.ac.uk/ena DNA Data Bank of Japan (DDBJ) : http://www.ddbj.nig.ac.jp/

13. Data sharing collaboration • Ensure data consistency • Avoid duplication • Open data sharing

14. Biological Databases I: Biomedical Literature

15. Biological Database I : Biomedical Literature Database • Medline:https://www.nlm.nih.gov/bsd/pmresources.html • NLM journal citation database. • Includes citations 5,600 scholarly journals published around the world. • PubMed https://www.ncbi.nlm.nih.gov/pubmed/ • ~28 million citations mainly from: • MEDLINE indexed journals • journals/manuscripts deposited in PMC • NCBI Bookshelf

16. Pubmed query builder using MeSH terms • MeSH (Medical Subject Headings) is the NLM controlled vocabulary thesaurus used for indexing articles for PubMed. • the U.S. National Library of Medicine's controlled vocabulary (thesaurus). • arranged in a hierarchical manner called the MeSH Tree Structures. • updated annually

17. PubMed search demo

18. Hands On Exercise I • Find all article related to PTEN gene on pubmed. • How many articles did you find ? • Modify your search to find entries in Pubmed for PTEN related work from authored by Hui Liang • How many articles did you find? • Restrict your search and find PTEN related articles by author Hui Liang in Cell Metabolism Journal. • What is the full title of the article? • Which year it was published in ? • Reflection question: What are some advantages of using MeSH term builder? More tutorials on building Pubmed queries for efficient search : https://www.nlm.nih.gov/bsd/disted/pubmedtutorial/cover.html

19. Biological Databases II: Genomics and Transcriptomics

20. Biological Database II- Genomics and Transcriptomics • GenBank: https://www.ncbi.nlm.nih.gov/genbank/ • Flat file • Nucleotide only sequence database • Archival in nature: Historical, Redundant • Data: Direct submissions (traditional records), Batch submissions, FTP accounts (genome data) • Sample GenBank record (accession number U49845) • NCBI: https://www.ncbi.nlm.nih.gov/genbank/samplerecord/#OtherFeaturesB • ENA: https://www.ebi.ac.uk/ena/data/view/U49845 • DDBJ: http://getentry.ddbj.nig.ac.jp/top-e.html

21. GenBank Flat File

22. Ensembl • Contains all the vertebrate genome DNA sequences currently available in the public domain. • Automated annotation: by using different software tools, features are identified in the DNA sequences: • Genes (known or predicted) • Single nucleotide polymorphisms (SNPs) • Repeats • Homologies • Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species. • www.ensembl.org

23. Nucleic Acid Structure Database • NDB Nucleic acid-containing structureshttp://ndbserver.rutgers.edu/ • NTDB Thermodynamic data for nucleic acidshttp://ntdb.chem.cuhk.edu.hk/ • RNABase RNA-containing structures from PDB and NDBhttp://www.rnabase.org/ • SCOR Structural classification of RNA: RNA motifs by structure, function and tertiary interactions http://scor.lbl.gov/

24. Biological Databases III: Proteomics

25. Biological Database III- Proteomics • Protein sequence database: https://www.ncbi.nlm.nih.gov/protein/

26. Genpept

27. Uniprot • The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. • UniProt is a collaboration between the European Bioinformatics Institute (EMBL-EBI), the SIB Swiss Institute of Bioinformatics and the Protein Information Resource (PIR). • the entry belongs to the Swiss-Prot section of UniProtKB (reviewed) or to the computer-annotated TrEMBL section (unreviewed). • http://www.uniprot.org/

28. Protein Structure database- PDB • Protein Data Bank (PDB) http://www.rcsb.org/ • Archive-information about the 3D shapes of proteins, nucleic acids, and complex assemblies that helps students and researchers understand all aspects of biomedicine and agriculture, from protein synthesis to health and disease.

29. Protein Family Database • http://pfam.xfam.org/family/piwi • Pfam is a database of protein families that includes their annotations and multiple sequence alignments generated using hidden Markov models

30. Protein-Protein Interaction Database • STRING:https://string-db.org/ (Search Tool for the Retrieval of Interacting Genes/Proteins) is a biological database and web resource of known and predicted protein–protein interactions. • Information from numerous sources, including experimental data, computational prediction methods and public text collections • Nodes: Network nodes represent proteins • Edges: Edges represent protein-protein associations

31. Hands-on Exercise II • Search Genbank or ensembl for human PTEN gene. • What chromosome is this gene located on? • Is it a protein coding gene ? • How many transcripts this gene have? • How many transcripts are functional ? • Does this gene has an alternative splicing events • What protein does PTEN gene code for? • How many of those protein entries are reviewed? • Number of protein-protein interactions for PTEN gene in humans? • Are there any records of Post Translational Modification (PTM) ?

32. Data vs Annotation Database • RefSeq provide a scientist-curated nonredundant set of biological sequences. (Derivative) https://www.ncbi.nlm.nih.gov/refseq/ • Source: Genbank (INSDC) • Annotated: Community collaboration, automated computer, NCBI staff curation • Advantages of using RefSeq • Non-redundancy • Updates to reflect current sequence data and biology • Data validation • Format consistency • Distinct accession series

33. Selected Refseq Accession

34. High-Throughput Sequencing Database • Gene Expression Omnibus (GEO) archives and freely distributes high throughput gene expression data submitted by the scientific community. • NCBI Sequence Read Archive (SRA) archives raw sequencing data and alignment information from high-throughput sequencing platforms. SRA experiment includes sequence data and metadata regarding how a biological sample was sequenced. Example dataset : https://www.ebi.ac.uk/ena/data/view/SRR494099 • database of Genotype and Phenotype(dbGAP): public repository for individual-level phenotype, exposure, genotype, and sequence data, and the associations between them. https://www.ncbi.nlm.nih.gov/gap • European Genome Phenome Archive: repository for a sequence and genotype experiments, case-control, population, and family studies. https://www.ebi.ac.uk/ega/about

35. Other Specialised Databases • UCSC Xena: https://xenabrowser.net/datapages/ • Genotype-Tissue Expression Gtex: https://www.gtexportal.org/home/Correlations between genotype and tissue-specific gene expression levels will help identify regions of the genome that influence whether and how much a gene is expressed. • mirBase:http://www.mirbase.org/ • Database of published miRNA sequences and annotation. • Each entry represents a predicted hairpin portion of a miRNA transcript (termed mir in the database), with information on the location and sequence of the mature miRNA sequence (termed miR). • Pubchem: https://pubchem.ncbi.nlm.nih.gov/chemical information with structures, information and links • DrugBank: https://www.drugbank.ca/combines detailed drug data with comprehensive drug target information. AND Many MORE !!!!!

36. Database Retrieval • Problem with Traditional link method • Rapidly growing databases with complex and changing relationships • Rapidly changing interfaces to match the above • Many people don’t know: • Where to begin • Where to click on a Web page • Why it might be useful to click there • Entrez GQuery is a retrieval system for searching several linked databases such as: Pubmed, GenBank etc. https://www.ncbi.nlm.nih.gov/gquery/

37. BLAST • BLAST stands for Basic Local Alignment Search Tool • Good balance of sensitivity and speed • Reliable • Flexible • Produce local alignments: short significant stretches of similarity, irrespective of where they are in the sequence • Blast applies heuristic approach, it does not necessarily find the best hit for your search.

38. BLAST Output • List of sequences with scores • Raw score • Higher is better • Depends on aligned length • Expect Value (E-value) • Smaller is better • Independent of length and database size • The Expect value (E) is a parameter that describes the number of hits one can "expect" to see by chance when searching a database of a particular size. It decreases exponentially as the Score (S) of the match increases. • Where can I BLAST ? • NCBI BLAST web service : https://blast.ncbi.nlm.nih.gov/Blast.cgi • EBI BLAST web service : https://www.ebi.ac.uk/Tools/sss/ncbiblast/ • FlyBase BLAST : http://flybase.org/blast/ • Drosophila and other insects

39. Hands on Exercise III This fragment of genomic DNA belong to a part of gene. >query 1 CTAAACTACCAAGGCCATCTCTACTTAAAAACAGTTGTCTTTTGTTTGTGATTTCAGGGGCCCTGGGTATAAGCGAAGTCCCTGTTTAGAGACCTTGTGATGGGTTCAAAATATCAAGAAAGATAGCAAAATATCACAAGCCTCCTGACCCGAGAAGATTAGCGTTGAAAGGGTCTGTCGTGTTTGTTTGGGCCTGGGGCTAAATTCCCAGCCCAAGTGCTGAGGCTGATAATAATCGGGGCGGCGATCAGACAGCCCCGGTGTGGGAAATCGTCCGCCCGGTCTCCCTAAGTCCCCGAAGTCGCCTCCCACTTTTGGTGACTGCTTGTTTATTTACATGCAGTCAATGATAGTAAATGGATGCGCGCCAGTATAGGCCGACCCTGAGGGTGGCGGGGTGCTCTTCGCAGCTTCTCTGTGGAGACCGGTCAGCGGGGCGGCGTGGCCGCTCGCGGCGTCTCCCTGGTGGCATCCGCACAGCCCGCCGCGGTCCGGTCCCGCTCCGGGTCAGAATTGGCGGCTGCGGGGACAGCCTTGCGGCTAGGCAGGGGGCGGGCCGCCGCGTGGGTCCGGCAGTCCCTCCTCCCGCCAAGGCGCCGCCCAGACCCGCTCTCCAGCCGGCCCGGCTCGCCACCCTAGACCGCCCCAGCCACCCCTTCCTCCGCCGGCCCGGCCCCCGCTCCTCCCCCGCCGGCCCGGCCCGGCCCCCTCCTTCTCCCCGCCGGCGCTCGCTGCCTCCCCCTCTTCCCTCTTCCCACACCGCCCTCAGCCGCTCCCTCTCGTACGCCCGTCTGAAGAAGAATCGAGCGCGGAACGCATCGATAGCTCTGCCCTCTGCGGCCGCCCGGCCCCGAACTCATCGGTGTGCTCGGAGCTCGATTTTCCTAGGCGGCGGCCGCGGCGGCGGAGGCAGCAGCGGCGGCGGCAGTGGCGGCGGCGAAGGTGGCGGCGGCTCGGCCAGTACTCCCGGCCCCCGCCATTTCGGACTGGGAGCGAGCGCGGCGCAGGCACTGAAGGCGGCGGCGGGGCCAGAGGCTCAGCGGCTCCCAG • Using BLAST search determine which gene/genes is this query fragment associated with?