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Light Intro to the Gene Ontology
 

Light Intro to the Gene Ontology

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A set of slides for a seminar I led introducing the Gene Ontology.

A set of slides for a seminar I led introducing the Gene Ontology.

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    Light Intro to the Gene Ontology Light Intro to the Gene Ontology Presentation Transcript

    • Introduction to the Gene Ontology
      Nic Weber
      LIS 590 Ontology Development in Natural Sciences
      9/24/2010
      All works referenced at first use,
      all images are CC except where notes
    • Gene Ontology
      Why : “The main opportunity lies in the possibility of automated transfer of biological annotations from the experimentally tractable model organisms to the less tractable organisms based on gene and protein sequence similarity.” Ashburner et al. p 25
      *Breakthroughs in sequencing show large fraction of genes specifying core bio functions are shared by all eukaryotes (commonalities at cellular level)
      *Knowledge of role of shared protein in one organism can often transferred (less duplication of work / saved money)
      *Sequencing takes place at large scale, new discoveries constant (need for documenting change in controlled way)
      *Traditional Indexing efforts proved “unwieldy” in fruit fly and mouse sequencing
      Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., et al. (2000). Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nature genetics, 25(1), 25-9. doi: 10.1038/75556.
    • Gene Ontology
      Goals
      Produce a dynamic, controlled vocabulary of that can be applied to eukaryotes. Provide formal structure to document and adopt change.
      Facilitate the annotation of and dissemination of annotations for genes and gene products
      For problematic reasons with hierarchal models (EC), indexing, and biological terminology like “functions”, three ontologies were developed
      1.Biological Process
      2. Molecular Function
      3. Cellular Component
    • Biological Process
      The biolgical objective to which the gene or gene product contributes. A process is accomplished via one or more ordered assemblies of molecular functions.
      *(This is an ordered process in that something goes in, something different comes out)
    • Molecular Function
      The biochemical activity (incuding binding ) of a gene product. Also applies to the capability that a gene product carries as a potential. Describes only what is done, not when or where.
    • Cellular Component
      The place in all cells where a gene product is active. These terms reflect our understanding of eukaryotic cell structure. (i.e. ‘ribosome’ or ‘nuclear membrane’)
    • Dependent vs. Independent Entities
      Biological Process: Dependent (“occurrents that require support from some substance in order to allow them to occur.” Smith et al. p4)
      2. Molecular Function: Dependent (“which means entities which have a necessary reference to the sub- stances in which they inhere.” ibid)
      3. Cellular Component: Independent
    • GO “Terms”
      Each “Ontology” defines terms representing gene product properties.
      Each GO term within the ontology contains the following:
      unique alphanumeric identifier
      term name (which may be a word or string of words)
      3. definitionwith cited sources
      4. namespace indicating the domain to which it belongs.
      *Terms may also have synonyms, which are classed as being exactly equivalent to the term name, broader, narrower, or related
      4. references to equivalent concepts in other databases
      5. commentson term meaning or usage.
    • Example GO Term
      [Term] id: GO:0000010
      name: trans-hexaprenyltranstransferase
      activity namespace: molecular_function
      def: "Catalysis of the reaction: all-trans-hexaprenyldiphosphate + isopentenyldiphosphate = diphosphate + all-trans-heptaprenyldiphosphate." [EC:2.5.1.30]
      subset: gosubset_prok
      synonym: "all-trans-heptaprenyl-diphosphatesynthase activity" EXACT [EC:2.5.1.30]
      synonym: "all-trans-hexaprenyl-diphosphate:isopentenyl-diphosphatehexaprenyltranstransferase activity" EXACT [EC:2.5.1.30]
      synonym: "heptaprenyldiphosphatesynthase activity" EXACT [EC:2.5.1.30]
      synonym: "heptaprenyl pyrophosphate synthase activity" EXACT [EC:2.5.1.30]
      synonym: "heptaprenyl pyrophosphate synthetase activity" EXACT [EC:2.5.1.30]
      xref: EC:2.5.1.30
      xref: MetaCyc:TRANS-HEXAPRENYLTRANSTRANSFERASE-RXN
      is_a: GO:0016765 ! transferase activity, transferring alkyl or aryl (other than methyl) groups
    • How Do GO Terms Work
      GO terms are connected into nodes of a network, thus the connections between its parents and children are known and form what are technically described as directed acyclic graphs.
      In a GO DAG- Terms are nodes and Relationships among them are edges.
    • What the F*@% is a Directed Acyclic Graph?
      directed graph- a set A whose elements are called nodes or verticies and a set E with connecting arcs or edges.
      So that G = (V,E)
      Directed Acyclic Graph- a directed graph with no directed cycles.
      *Formed by a collection of vertices and directed edges
      *Each edge connecting one vertex to another, so that there is no way to start at some vertex A and follow a sequence of edges that eventually loops back to A again.
      *Important note : DAGs are distinct from hierarchies, in that each term in a DAG may have more than one parent term; these terms are generally connected by ‘is-a’ and ‘part-of’ relations.
      Images via: commons.wikimedia.org
    • GO Directed Acyclic Graph
      Image via: commons.wikimedia.org
    • “Relationships”
      Each term has a defined “relationship” to another term in the same ontology or a related ontology (in GO.)
      is_a: GO:0016765 ! transferase activity, transferring alkyl or aryl (other than methyl) groups
    • Relationship types
      is_a …part_of
      Originally only two relationship types.
      is_a = subsumption ; part_of = patromonic inclusion
      New Types
      In last year regulates, positively-regulates, and negatively regulates have been added to distinguish gene products that play a regulatory vs. direct role in a biological process
    • Problems… is_a
      Meant to facilitate “instance of ”
      In practice often used to model as “is a kind of” relationships between universals.
      The is_a relation in its intended meaning indicates a necessary relationship. That is, when we say “euka- ryotic cell is_a cell”, we mean that every eukaryotic cell is a cell.
      In practice, cases of non-necessary subsumption
      (i.e. transport, or cell growth)
    • Problems…part_of
      Explained usage = “can be a part of, not is always a part of”
      In GO, part_of is used transitively
      (e.g. where A = B; and B = C; then also A = C)
      Can’t significantly represent an occurrent , meaning the notion of time is not accurately represented in these relations.
    • Part – Whole …. has_part
      Also introducedhas_part “…In GO, the relationship A has_part B means that A necessarily (always) has B as a part; i.e., if A exists then B also exists as a part of A. If A does not exist, B may or may not exist.
      Example ‘cell envelope’ has_part ‘plasma membrane’”
      From: Consortium, G. O. (2010). The Gene Ontology in 2010: extensions and refinements. Nucleic acids research, 38(Database issue), D331-5. doi: 10.1093/nar/gkp1018.
    • has_part modeled
    • Annotations (applied terms)
      Capture data about a gene or gene product, GO provides terms to do so. These annotations allow for genomic information to be uploaded and shared.
      When a gene is annotated to a term, associations between the gene and terms’ parents are implicitly inferred.
      Annotations are either generated by a curator or automatically through predictive methods (Rhee et al. p 509)
    • Annotation Structure
      Gene product identifier
      Relevant GO term
      GO annotations have the following data:
      Reference of the annotation (e.g. a journal article)
      Evidence code denoting the type of evidence upon which the annotation is based
      Date of annotation
      Creator of annotation
    • Evidence Codes
      Evidence codes are of four types:
      Experimental
      Computational
      Indirectly derived from exp or comp
      unknown
      95% of annotations are computational, this is problematic in that computational annotations increase coverage but also likely to be false positives
    • Annotation Qualifiers
      Colocallizes_with
      Contributes_to
      Not (most vital) – indicates a lack of properties.
    • Annotation in EMBL-EBI
      http://www.ebi.ac.uk/QuickGO/GTerm?id=GO:0006915#term=info
      (In case link fails, this is a quick view from GO)
      Gene product: Actin, alpha cardiac muscle 1, UniProtKB:P68032
      GO term: heart contraction ; GO:0060047 (biological process)
      Evidence code: Inferred from Mutant Phenotype (IMP)
      Reference: PMID:17611253
      Assigned by: UniProtKB, June 06, 2008
    • Universals and Particulars
      Universal: species E-coli; function: boost insulin
      Particulars: E-coli in this petri dish; function: boost insulin in subject X pancreas
      “GO terms correspond, in philosophical terminology, to universals…and each universal corresponding to the term Cell is instantiated by every actual cell.” Smith et al. p 3
    • Continuants vs. Occurrents
      Continuants: entities that continue to exist throughout time (cells, organisms, chromosomes) Preserve their identity, while undergoing variety of changes.
      Occurrents (events, processes): Unfold through time.
    • But…
      “Biological process, molecular function and cellular components are all attributes of genes, gene products or gene-product groups.” p. 27
      ..do we usually model attributes as ontologies? Are genes, gene products or gene product groups, “backbone” ontologies, OR Super Classes? If these aren’t Top Level Ontologies, what are they?
    • Smith et al. ; Yu’s “other” example
      *Recall Yu’s Fourth Definition of Ontologies
      “The Gene Ontology, in spite of its name, is not an ontology as the latter term is commonly used either by information scientists or by philosophers.It is, as the GO Consortium puts it, a ‘controlled vocabulary’…. their efforts have been directed toward providing a practically useful framework for keeping track of the biological annotations that are applied to gene products.” Smith et al. p 1
    • Problems and Potential Solutions
      Each new term requires understanding of the whole. Therefore curators must be subject experts in order to perform meaningful enhancement.
      Solution: make explicit the criteria used for discriminating subclassifications by introducing a decision-tree methodology into the construction of each hierarchy. ( Is this a good solution?)
    • Drawbacks to GO
      It is unclear what kinds of reasoning are permissible on the basis of GO’s hierarchies.
      The rationale of GO’ssubclassificationsis un- clear. The reasoning that went into current choices has not been preserved and thus cannot be explained to or re-examined by a third party.
      No procedures are offered by which GO can be validated.
      There are insufficient rules for determining how to recognize whether a given concept is or is not present in GO. The use of a mere string search pre- supposes that all concepts already have a single standardized representation, which is not the case.
      Smith et al. p6