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The problem. How to integrate the massive amounts of data on Drosophila neurobiology to explore anatomy, formulate hypotheses and find reagents?. Behavior/neural process ontology on FlyBase. Gene ontology annotations of genes neurological system process

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Presentation Transcript
the problem
The problem

How to integrate the massive amounts of data on Drosophila neurobiology to explore anatomy, formulate hypotheses and find reagents?

behavior neural process ontology on flybase
Behavior/neural process ontology on FlyBase
  • Gene ontology annotations of genes
    • neurological system process

7,904 annotations coverring 3,099 proteins and 121 terms

    • behavior
      • 1,964 annotations coverring 932 proteins and 89 terms
  • Phenotypes
    • Number of annotations: 4961
    • Number of terms used in annotation: 24 – all defined using GO.
  • Gene ontology annotations of anatomical structures
    • neurological system process: 1479
      • detection of stimulus involved in sensory perception: 1467
    • GO behavior: 17
genetic dissection of neural circuit function
Genetic dissection of neural circuit function

behavior

neural activity

repress

activate

modulate

UAS - < some activity

modulator >

transgenic driver(s) target expression to specific neuron classes

direct assays of neural activity

Mutant

slide4
Anatomical

phenotypes

DA1 vPN

Phenotype

Expresses

Scer\GAL4[fru-NP0021]

Function

GO: response to pheromone

GO: sensory perception of smell

GO: male courtship behavior

Expresses

Fru

Phenotype

neuron based bioinformatics tracking 3d data
Neuron based bioinformatics: tracking 3D data

segmentation

registration

(warping)

3D co-ordinates for neuron

3D co-ordinates

for Brain regions

computation of overlap

Standard brain => standard

3D coordinate space

QUERIES

e.g.- neurons with some part in AMMC

analysis of cross registered 3 d image data
Analysis of cross-registered 3 D image data
  • Predicted innervation patterns
  • NeuronBlast => predictions of neuron classes
  • Predicted connectivity from Arbor proximity
slide7
3D overlap defines potential connectivity

Output

300 µm / 40,000 neurons

queries
Queries
  • Neurons by function (inferred from phenotype or electrophysiology)
  • Phenotypes due to modulation of neurons in expression domain of driver X
  • Potential circuit partners – direct or indirect, with X function
what we need
What we need
  • Clear definitions and safe inference
    • infer classification
  • Avoid vertebrate specificity
    • references to anatomical structures
    • references to species specific movement types
    • Bundling together of functions in species specific ways (vestibulo-auditory)
  • Cross ontology integration
    • GO; Uberon; CHEBI, PATO
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