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Fundamentals in Sequence Analysis 1.(part 1)

Fundamentals in Sequence Analysis 1.(part 1)

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Fundamentals in Sequence Analysis 1.(part 1)

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  1. Fundamentals in Sequence Analysis 1.(part 1) Review of Basic biology + database searching in Biology. Hugues Sicotte NCBI


  3. Prequisites to Sequence Analysis • Basic Biology so you can understand the language of the databases: Central Dogma (transcription; Translation, Prokaryotes, Eukaryotes,CDS, 3´UTR, 5´UTR, introns, exons, promoters, operons, codons, start codons, stop codons,snRNA,hnRNA,tRNA, secondary structure, tertiary structure). • Before you can analyze sequences.. You have to understand their structure.. And know about Basic Biological Database Searching

  4.   Central Dogmas of Molecular Biology 1) The concept of genes is historically defined on the basic of genetic inheritance of a phenotype. (Mendellian Inheritance) 2) The DNA an organism encodes the genetic information. It is made up of a double stranded helix composed of ribose sugars. Adenine(A), Citosine (C), Guanine (G) and Thymine (T). [note that only 4 values nees be encode ACGT.. Which can be done using 2 bits.. But to allow redundant letter combinations (like N means any 4 nucleotides), one usually resorts to a 4 bit alphabet.]

  5.   Central Dogmas of Molecular Biology 3) Each side of the double helix faces it´s complementary base. A T, and G  C. 4) Biochemical process that read off the DNA always read it from the 5´´side towards the 3´ side. (replication and transcription). 5) A gene can be located on either the ´plus strand´ or the minus strand. But rule 4) imposes the orientation of reading .. And rule 3 (complementarity) tells us to complement each base E.g. If the sequence on the + strand is ACGTGATCGATGCTA, the – strand must be read off by reading the complement of this sequence going ´backwards´ e.g. TAGCATCGATCACGT

  6.   Central Dogmas of Molecular Biology 6) DNA information is copied over to mRNA that acts as a template to produce proteins. We often concentrate on protein coding genes, because proteins are the building blocks of cells and the majority of bio-active molecules. (but let´s not forget the various RNA genes)

  7. Prokaryotic genes Prokaryotes (intronless protein coding genes) Upstream (5’) Gene region promoter Downstream (3’) TAC DNA Transcription (gene is encoded on minus strand .. And the reverse complement is read into mRNA) ATG mRNA 5´ UTR 3´ UTR CoDing Sequence (CDS) ATG Translation: tRNA read off each codons, 3 bases at a time, starting at start codon until it reaches a STOP codon. protein

  8. Why does Nature bothers with the mRNA? • Why would the cell want to have an intermediate between DNA and the proteins it encodes? • Gene information can be amplified by having many copies of an RNA made from one copy of DNA. • Regulation of gene expression can be effected by having specific controls at each element of the pathway between DNA and proteins. The more elements there are in the pathway, the more opportunities there are to control it in different circumstances. • In Eukaryotes, the DNA can then stay pristine and protected, away from the caustic chemistry of the cytoplasm.

  9. Prokaryotic genes (operons) Prokaryotes (operon structure) upstream promoter downstream Gene 1 Gene 2 Gene 3 In prokaryotes, sometimes genes that are part of the same operational pathway are grouped together under a single promoter. They then produce a pre-mRNA which eventually produces 3 separates mRNA´s.

  10. Bacterial Gene Structure of signals • Bacterial genomes have simple gene structure. • - Transcription factor binding site. • - Promoters • -35 sequence (T82T84G78A65C54A45) 15-20 bases • -10 sequence (T80A95T45A60A50T96) 5-9 bases • - Start of transcription : initiation start: Purine90 (sometimes it’s the “A” in CAT) • - translation binding site (shine-dalgarno) 10 bp upstream of AUG (AGGAGG) • - One or more Open Reading Frame • start-codon (unless sequence is partial) • until next in-frame stop codon on that strand .. • Separated by intercistronic sequences. • - Termination

  11. Genetic Code • How does an mRNA specify amino acid sequence? The answer lies in the genetic code. It would be impossible for each amino acid to be specified by one nucleotide, because there are only 4 nucleotides and 20 amino acids. Similarly, two nucleotide combinations could only specify 16 amino acids. The final conclusion is that each amino acid is specified by a particular combination of three nucleotides, called a codon: • Each 3 nucleotide code for one amino acid. • The first codon is the start codon, and usually coincides with the Amino Acid Methionine. (M which has codon code ‘ATG’) • The last codon is the stop codon and does NOT code for an amino acid. It is sometimes represented by ‘*’ to indicate the ‘STOP’ codon. • A coding region (abbreviation CDS) starts at the START codon and ends at the STOP codon.

  12. Note the degeneracy of the genetic code. Each amino acid might have up to six codons that specify it. • Different organisms have different frequencies of codon usage. • A handful of species vary from the codon association described above, and use different codons fo different amino acids. • How do tRNAs recognize to which codon to bring an amino acid? The tRNA has an anticodon on its mRNA-binding end that is complementary to the codon on the mRNA. Each tRNA only binds the appropriate amino acid for its anticodon. Codon table

  13. RNA • RNA has the same primary structure as DNA. It consists of a sugar-phosphatebackbone, with nucleotides attached to the 1' carbon of the sugar. The differences between DNA and RNA are that: • RNA has a hydroxyl group on the 2' carbon of the sugar (thus, the difference between deoxyribonucleic acid and ribonucleic acid. • Instead of using the nucleotide thymine, RNA uses another nucleotide called uracil:  • Because of the extra hydroxyl group on the sugar, RNA is too bulky to form a stable double helix. RNA exists as a single-stranded molecule. However, regions of double helix can form where there is some base pair complementation (U and A , G and C), resulting in hairpin loops. The RNA molecule with its hairpin loops is said to have a secondary structure.          • Because the RNA molecule is not restricted to a rigid double helix, it can form many different stable three-dimensional tertiary structures.

  14. tRNA ( transfer RNA) is a small RNA that has a very specific secondary and tertiary structure such that it can bind an amino acid at one end, and mRNA at the other end. It acts as an adaptor to carry the amino acid elements of a protein to the appropriate place as coded for by the mRNA. T Three-dimensional Tertiary structure Secondary structure of tRNA

  15. Bacterial Gene Prediction Most of the consensus sequences are known from ecoli studies. So for each bacteria the exact distribution of consensus will change. Most modern gene prediction programs need to be “trained”. E.g. they find their own consensus and assembly rules given a few examples genes. A few programs find their own rules from a completely unannotated bacterial genome by trying to find conserved patterns. This is feasible because ORF’s restrict the search space of possible gene candidates. E.g. selfid program(

  16. Open Reading Frames • The simplest bacterial gene prediction techniques simply • identify all open reading frames(ORFs), • and blastx them against known proteins. • The ORFs with the best homology are retained first. • This usually densely covers the bacterial genomes with genes. rRNA and tRNA are detected separately using tRNAScan or blastn.

  17. Open Reading Frames (ORF) On a given piece of DNA, there can be 6 possible frames. The ORF can be either on the + or minus strand and on any of 3 possible frames Frame 1: 1st base of start codon can either start at base 1,4,7,10,... Frame 2: 1st base of start codon can either start at base 2,5,8,11,... Frame 3: 1st base of start codon can either start at base 3,6,9,12,... (frame –1,-2,-3 are on minus strand) Some programs have other conventions for naming frames.. (0..5, 1-6, etc) Gene finding in eukaryotic cDNA uses ORF finding +blastx as well. try with gi=41 ( or your own piece of DNA)

  18. Eukaryotic Central Dogma In Eukaryotes ( cells where the DNA is sequestered in a separate nucleus) The DNA does not contain a duplicate of the coding gene, rather exons must be spliced. ( many eukaryotes genes contain no introns! .. Particularly true in ´lower´ organisms) mRNA – (messenger RNA) Contains the assembled copy of the gene. The mRNA acts as a messenger to carry the information stored in the DNA in the nucleus to the cytoplasm where the ribosomes can make it into protein.

  19. Eukaryotic Nuclear Gene Structure • Gene prediction for Pol II transcribed genes. • Upstream Enhancer elements. • Upstream Promoter elements. • GC box(-90nt) (20bp), CAAT box(-75 nt)(22bp) • TATA promoter (-30 nt) (70%, 15 nt consensus (Bucher et al (1990)) • 14-20 nt spacer DNA • CAP site (8 bp) • Transcription Initiation. • Transcript region, interrupted by introns. Translation Initiation (Kozak signal 12 bp consensus) 6 bp prior to initiation codon. • polyA signal (AATAAA 99%,other)

  20. introns • Transcript region, interrupted by introns. Each introns • starts with a donor site consensus (G100T100A62A68G84T63..) • Has a branch site near 3’ end of intron (one not very conserved consensus UACUAAC) • ends with an acceptor site consensus. (12Py..NC65A100G100) UG UACUAAC AG

  21. Exons • The exons of the transcript region are composed of: • 5’UTR (mean length of 769 bp) with a specific base composition, that depends on local G+C content of genome) • AUG (or other start codon) • Remainder of coding region • Stop Codon • 3’ UTR (mean length of 457, with a specific base composition that depends on local G+C content of genome)

  22. Structure of the Eukaryotic Genome ~6-12% of human DNA encodes proteins(higher fraction in nematode) ~10% of human DNA codes for UTR ~90% of human DNA is non-coding.

  23. Non-Coding Eukaryotic DNA • Untranslated regions (UTR’s) • introns (can be genes within introns of another gene!) • intergenic regions. • - repetitive elements • - pseudogenes (dead • genes that may(or not) have been retroposed back in the genome as a single-exon “gene”

  24. Pseudogenes Pseudogenes: Dna sequence that might code for a gene, but that is unable to result in a protein. This deficiency might be in transcription (lack of promoter, for example) or in translation or both. Processed pseudogenes: Gene retroposed back in the genome after being processed by the splicing apperatus. Thus it is fully spliced and has polyA tail. Insertion process flanks mRNA sequence with short direct repeats. Thus no promoters.. Unless is accidentally retroposed downstream of the promoter sequence. Do not confuse with single-exon genes.

  25. Repeats • Each repeat family has many subfamilies. • - ALU: ~ 300nt long; 600,000 elements in human genome. can cause false homology with mRNA. Many have an Alu1 restriction site. • - Retroposons. ( can get copied back into genome) • - Telltale sign: Direct or inverted repeat flank the repeated element. That repeat was the priming site for the RNA that was inserted. • LINEs (Long INtersped Elements) • L1 1-7kb long, 50000 copies • Have two ORFs!!!!! Will cause problems for gene prediction programs. • SINEs (Short Intersped Elements)

  26. Low-Complexity Elements • When analyzing sequences, one often rely on the fact that two stretches are similar to infer that they are homologous (and therefore related).. But sequences with repeated patterns will match without there being any philogenetic relation! • Sequences like ATATATACTTATATA which are mostly two letters are called low-complexity. • Triplet repeats (particularly CAG) have a tendency to make the replication machinery stutter.. So they are amplified. • The low-complexity sequence can also be hidden at the translated protein level.

  27. Masking • To avoid finding spurious matches in alignment programs, you should always mask out the query sequence. • Before predicting genes it is a good idea to mask out repeats (at least those containing ORFs). • Before running blastn against a genomic record, you must mask out the repeats. • Most used Programs: • CENSOR: • Repeat Masker: •

  28. More Non-Protein genes • rRNA - ribosomal RNA • is one of the structural components of the ribosome. It has sequence complementarity to regions of the mRNA so that the ribosome knows where to bind to an mRNA it needs to make protein from. • snRNA - small nuclear RNA • is involved in the machinery that processes RNA's as they travel between the nucleus and the cytoplasm. • hnRNA – hetero-nuclear RNA. • small RNA involved in transcription.

  29. Protein Processing & localization. • The protein as read off from the mRNA may not be in the final form that will be used in the cell. Some proteins contains • Signal Peptide (located at N-terminus (beginning)), this signal peptide is used to guide the protein out of the nucleus towards it´s final cellular localization. This signal peptide is cleaved-out at the cleavage site once the protein has reach (or is near) it´s final destination. • Various Post-Translational modifications (phosphorylation) • The final protein is called the “mature peptide”

  30. Convention for nucleotides in database Because the mRNA is actually read off the minus strand of the DNA, the nucleotide sequence are always quoted on the minus strand. In bioinformatics the sequence format does NOT make a difference between Uracil and Thymine. There is no symbol for Uracil.. It is always represented by a ´T´ Even genomic sequence follows that convention. A gene on the ´plus´ strand is quoted so that it is in the same strand as it´s product mRNA.

  31. Biology Information on the Internet

  32. Biology Information on the Internet • Introduction to Databases • Searching the Internet for Biology Information. • General Search methods • Biology Web sites • Introduction to Genbank file format. • Introduction to Entrez and Pubmed • Ref: Chapters 1,2,5,6 of “Bioinformatics”

  33. Spread-sheet Flat-file version of a database. • Databases: • A collection of Records. • Each record has many fields. • Each field contain specific information. • Each field has a data type. • E.g. money, currency,Text Field, Integer, date,address(text field) ,citation (text field) • Each record has a primary key. A UNIQUE identifier that unambiguously defines this record.

  34. Gi = Genbank Identifier: Unique Key : Primary Key GI Changes with each update of the sequencerecord. Accession Number: Secondary key: Points to same locus and sequence despite sequence updates. Accession + Version Number equivalent to Gi

  35. Relational Database (Normalizing a database for repeated sub-elements of a database.. Splitting it into smaller databases, relating the sub-databases to the first one using the primary key.)

  36. Types of Relational databases. • The Internet can be though of as one enormous relational database. • The “links”/URL are the primary keys. • SQL (Standard Query Language) • Sybase; Oracle ; Access; (Databases systems) • Sybase used at NCBI. • SRS(One type of database querying system of use in Biology)

  37. Indexed searches. • To allow easy searching of a database, make an index. • An index is a list of primary keys corresponding to a key in a given field (or to a collection of fields)

  38. Indexed searches. • Boolean Query: Merging and Intersecting lists: • AND (in both lists) (e.g. human AND genome) • +human +genome • human && genome • OR (in either lists) (e.g. human OR genome) • human || genome

  39. Search strategies • Search engines use complex strategies that go beyond Boolean queries. • Phrases matching: • human genome -> “human genome” • togetherness: documents with human close to genome are scored higher. • Term expansion & synomyms: • human -> homo sapiens • neigbours: • human genome-> genome projects, chromosomes,genetics • Frequency of links ( • To avoid these term mapping, enclose your queries in quotes: “human” AND “genome”

  40. Search strategies • Search engines use complex strategies that go beyond Boolean queries. • To avoid these term mapping, enclose your queries in quotes: “human” AND “genome” • To require that ALL the terms in your query be important, precede them with a “+” . This also prevents term mapping. • To force the order of the words to be important, group sentences within strings. “biology of mammals”.

  41. Indexed searches. Example • find the advanced query page at • type human (and hit the Search button) • Type genome: • type human AND genome • type “human genome” (finds the least matches) • type human OR genome (finds the most matches)

  42. Search Engines: • Web Spiders: Collection of All web pages, but since Web pages change all the time and new ones appear, they must constantly roam the web and re-index.. Or depend on people submitting their own pages. • (BEST!) • • • • • • (country specific)

  43. Search Engines: • (BEST!) • Google ranks pages according to how many pages with those terms refer to the pages you are asking for. Not only must one document contain ALL the search terms, but other documents which refer to this one must also contain all the terms. • Great when you know what you are looking for! You can also use “” to require immediate proximity and order of terms. • E.g. type • Web server for the blast program. But google only indexes about 40% of the web.. So you may have to use other web spiders. (disclaimer.. I don’t own stock in that company.. But I’d like to)

  44. Search Engines: • Curated Collections: Not comprehensive: Contains list of best sites for commonly requested topics, but is missing important sites for more specialized topics (like biology) • (Has travel maps too!) • Answer-based curated collections: Easy to use english-like queries. First looks at list of predefined answers, then refines answers based on user interaction. Also answer new questions. • • • translation TOOLS) •

  45. Search Engines: • Meta-Search Engines: Polls several search engines, and returns the consensus of all results. Is likely to miss sites, but the sites it returns are very relevant to the query. • Other operating mode is to return the sum of all the results.. Then becomes very sensitive to a very detailled query. • • • (fast) • •

  46. Virtual Libraries: Curated collections of links for Biologists.(by Biologists) • Pedro’s BioMolecular Research Tools:(1996) • • Virtual Library: Bio Sciences • • Publications and abstract search. • • Expasy server • • EBI Biocatalog (software & databases list) •

  47. Biological Databases • Nucleotide databases: • Genbank: International Collaboration • NCBI(USA), EMBL(Europe), DDBJ (Japan and Asia) • A “bank” No curation.. Submission to these database is required for publication in a journal. • Organism specific databases (Exercize: Find URLs using search engines) • FlyBase • ChickGBASE • pigbase • wormpep • YPD (Yeast Protein Database) • SGD(Saccharomyces Genome Database)

  48. Protein Databases: • NCBI: • Swiss Prot:(Free for academic use, otherwise commercial. Licensing restrictions on discoveries made using the DB. 1998 version free of any licensing) • pay version) • NCBI has the latest free version. • Translated Proteins from Genbank Submissions • EMBL • TrEMBL is a computer-annotated supplement of SWISS-PROT that contains all the translations of EMBL nucleotide sequence entries not yet integrated in SWISS-PROT • PIR

  49. Structure databases: • PDB: Protein structure database. • Http:// • MMDB: NCBI’s version of PDB with entrez links. • Http:// • Genome Mapping Information: • • NCBI(Human) • Genome Centers: • Stanford, Washington University, Stanford • Research Centers and Universities

  50. Litterature databases: • NCBI: Pubmed: All biomedical litterature. • • Abstracts and links to publisher sites for • full text retrieval/ordering • journal browsing. • Publisher web sites. • Biomednet: Commercial site for litterature search. • Pathways Database: • KEGG: Kyoto Encyclopedia of Genes and Genomes: