Download Cell Ontology – INCF Neuron Workshop

Cell Ontology – INCF Neuron
Workshop
April 12-14, 2011
Loudermilk Conference Center, Atlanta Georgia
Supported by NHGRI HG002273-09Z
and
The International Neuroinformatics Coordinating Facility
Co-sponsored by the Georgia State University Center for Neuromics
Thanks to
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Janis Breeze, INCF
Jyl Boline, INCF
Paul Katz, GSU
Alan Ruttenburg, SUNY Buffalo
Judith Blake, The Jackson Laboratory
Ashley Stanton, The Jackson Laboratory
Beth Partridge, Hurley Travel at Jax
Participants
Giorgio Ascoli, George Mason University
Judith Blake, The Jackson Laboratory
Mihail Bota, University of Southern California (via
teleconference)
Janis Breeze, INCF Program Officer
Robert Burgess, The Jackson Laboratory
Jyl Boline, INCF Project Coordinator (via
teleconference)
Alexander Diehl, SUNY Buffalo
Akshaye Dhawan, Ursinus College
Chad Frederick, Georgia State University
Daniel Gardner, Weil Medical College, Cornell
Melissa Haendel, Oregon Health & Science
University
David Hamilton, George Mason University
Sean Hill, INCF Excecutive Director
Kei Ito, The University of Tokyo
Saurav Karmakar, Georgia State University
Paul Katz, Georgia State University
Stephan Larson, University of California, San Diego
Ed Lein, Allen Brain Institute
Terrence Meehan, The Jackson Laboratory
Jose Leonardo Mejino, University of Washington
Chris Mungall, Lawrence Berkeley National
Laboratory
Sasha Nelson, Brandeis University
Sridevi Polavaram, George Mason University
David Osumi-Sutherland, Cambridge University (via
teleconference)
Abir Ashfakur Rahman, Georgia State University
Patrick Ray, SUNY Buffalo
Kathleen Rockland, Massachusetts Institute of
Technology
Alan Ruttenburg, SUNY Buffalo
Deboleena Roy, Emory University
Joseph Shea, SUNY Buffalo
Gordon Shepherd, Yale University
Raj Sunderraman, Georgia State University
Menno Witter, Norwegian University of Science and
Technology
Workshop Goals
• Introduction to the Cell Ontology
• Review of neuron ontology efforts
• Discussion of the ontological representation of
neurons
• Review of core set of high level neuron terms
• Set up Working Groups
• Working Groups develop neuron terms and
report back
Satellite Meeting
• For in depth discussion of ontology
development-related issues
• Discussion points to be collects during main
meeting
• For instance, “How do we present lines of
evidence for asserted neuron properties as
part of the ontology?”
The Cell Ontology
• An ontology of cell types built by biologists for the needs of
data annotation and analysis.
• The Cell Ontology covers in vivo cell types from all of biology.
• The Cell Ontology is not
– A list of specific cell lines, immortal or otherwise, although the Cell
Ontology may be used to describe such cells if they correspond to an
in vivo cell type.
– A list of in vitro methods for preparing cell cultures, although the Cell
Ontology may be used to describe the resulting cells if they
correspond to an in vivo cell type.
OBO Reference Ontologies
RELATION
TO TIME
CONTINUANT
INDEPENDENT
OCCURRENT
DEPENDENT
GRANULARITY
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy?)
CELL AND
CELLULAR
COMPONENT
Cell
(CL)
MOLECULE
Anatomical
Organ
Entity
Function
(FMA,
(FMP, CPRO) Phenotypic
CARO)
Quality
(PaTO)
Cellular
Cellular
Component Function
(FMA, GO)
(GO)
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
(GO)
Organism-Level
Process
(GO)
Cellular Process
(GO)
Molecular
Process
(GO)
Smith et al., Nature Biotechnology 25, 1251 - 1255 (2007)
Overview of Cell Ontology
• Developed by Jonathan Bard, David States,
Michael Ashburner, and Seung Rhee and first
described in 2005, Genome Biology, 6:R21.
• The Cell Ontology is sometimes called the Cell
Type Ontology, and often referred to as the “CL”,
based on its identifier space. For instance the
term “B cell” has the ID “CL:0000236”
• The CL currently has over 1500 cell type terms,
over 500 of which have logical definitions.
Textual Definitions
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name: CD4-positive, CD25-positive,
alpha-beta regulatory T cell
def: "A CD4-positive, CD25-positive,
alpha-beta T cell that regulates overall
immune responses as well as the
responses of other T cell subsets
through direct cell-cell contact and
cytokine release.”
name: induced T-regulatory cell
def: "CD4-positive alpha-beta T cell
with the phenotype CD25-positive,
CTLA-4-positive, and FoxP3-positive
with regulatory function."
Logical Definitions
Logical Definitions
Pre-reasoning
Post-reasoning
Logical Definitions of Neurons
• Retinal Ganglion Cell
– def: "A neuron located in the ganglion cell layer of the eye that receives
inputs via bipolar, horizontal and amacrine cells. The axons of these cells
make up the optic nerve." [GOC:add, GOC:dph]
CL Neuron Improvements so far
• We have added textual definitions for around 120
of the existing neuron types in CL, and logical
definitions for around 75 of these.
• With help from INCF, we have imported 130
neuron types from the BAMS (Brain Architecture
Management System) and created new genusdifferentia textual definitions for these. About 40
of these have been given logical definitions.
• These changes are still under review.
Neurons are complicated
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Most neurons are defined in part by their anatomical location.
– Brain and nervous system anatomy varies considerably between species.
– Many anatomical systems exist for brains of different species. These are often in conflict
with each other.
– Neurons often have their soma in one anatomical location, axon in another, and
dendrites in a third.
• We hope upper level neuron classes that can be defined reliably across
species.
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Morphology
Neurotransmitter secretion
Large scale anatomical structures
Function
What does it mean to “represent” a
Neuron in an Ontology?
• Capture basic properties of particular neurons in a
textual definition based on the literature. The
combination of properties should uniquely define
the neuron.
• Translate these properties to a logical definition
(cross-product), based on relations that link the
neuron to terms in other ontologies.
• Not a mathematical model.
Neuron Ontology and Database Efforts
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Neurolex and NIF-cell
INCF Neuron Registry Task Force
Petilla Interneuron Nomenclature Group
SenseLab
NeuronBank
Brain Architecture Management System (BAMS)
Foundational Model of Anatomy
Virtual FlyBrain