Dr. Scott Ochsner and Dr. Neil McKenna from Baylor College of Medicine, Houston, TX, introduced dkNET Hypothesis Center - Signaling Pathways Project (SPP). Abstract: Mining of integrated public transcriptomic and ChIP-Seq (cistromic) datasets can illuminate functions of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates community classifications of signaling pathway nodes (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules. We then mapped over 10,000 public transcriptomic or cistromic experiments to their pathway node or biosample of study. To enable prediction of pathway node-gene target transcriptional regulatory relationships through SPP, we generated consensus ‘omics signatures, or consensomes, which ranked genes based on measures of their significant differential expression or promoter occupancy across transcriptomic or cistromic experiments mapped to a specific node family. Consensomes were validated using alignment with canonical literature knowledge, gene target-level integration of transcriptomic and cistromic data points, and in bench experiments confirming previously uncharacterized node-gene target regulatory relationships. To expose the SPP knowledgebase to researchers, a web browser interface was designed that accommodates numerous routine data mining strategies. SPP is freely accessible at https://www.signalingpathways.org. In this webinar, the presenters will demonstrate several SPP use cases, as well as take questions from the audience about specific aspects of SPP.

1. The Signaling Pathways Project:
The Signaling Pathways Project, An Integrated ‘Omics Knowledgebase
For Mammalian Cellular Signaling Pathways
Scott Ochsner, PhD & Neil McKenna, PhD
Department of Molecular and Cellular Biology
Baylor College of Medicine, Houston TX

2. What are signaling pathways?

3. Most of our knowledge of cellular signaling pathways is
derived from the research literature

4. Archived ‘omics datasets are alternative
sources of information on cellular signaling pathways
Expression array & RNA-Seq ChIP-Seq
Transcriptomics Cistromics

5. Transcriptomic and cistromic experiments report on
distinct events in a signaling pathway

6. Transcriptomic and cistromic experiments report on
distinct events in a signaling pathway

7. Expression array experiment
Small number of
the genes with
highest fold changes
are selected for
detailed
mechanistic analysis
Most of the data points in archived ‘omics datasets are not
followed up on for further study

8. Unlike research articles, archived ‘omics datasets are not easily
accessible or re-usable

9. Research literature ‘Omics data archives
Archived ‘omics datasets are not easily accessible or re-usable

10. The Nuclear Receptor Signaling Atlas: enhancing access
to archived ‘omics datasets in the field of NR signaling

11. The Nuclear Receptor Signaling Atlas: enhancing access
to archived ‘omics datasets in the field of NR signaling

12. Nuclear receptors are only a small part of the cell signaling story!

13. Transcriptomic
Expression array & RNA-Seq
Cistromic
ChIP-Seq
Receptors
Enzymes
Transcription
Factors
Co-nodes
Signaling Pathways Project (SPP): two universes of biocurated
transcriptional data points mapped to cell signaling pathway nodes
SPP node types
Hs
Mm
Rn
Hs
Mm Mm

14. The SPP user interface enables mining of SPP data points:
single gene queries
Regulation Report

15. Single Gene use case: association between reduced STARD10
expression and defective insulin secretion

16. Estrogen
receptor
STARD10
X
No evidence in the research literature of
estrogen receptor regulation of STARD10

17. Estrogen receptor is known to increase
pancreatic insulin content

18. Estrogen
receptor
Insulin
status
STARD10
X
SPP generates a hypothesis linking
ER, STARD10 and pancreatic insulin

19. Estrogen
receptor
Insulin
status
STARD10
SPP generates a hypothesis linking
ER, STARD10 and pancreatic insulin

20. GO term use case: mechanisms underlying regulation of
brown fat formation by EGF receptor signaling

21. PPARG is an established target of EGF receptor signaling

22. Hypothesis: EGF receptor signaling promotes
brown adipose tissue formation through regulation of LAMA4
EGF
receptor
family
LAMA4
Brown fat
metabolism

23. Custom gene list use case: mechanisms underlying the role
of HGF receptor signaling in Crohn’s disease

24. CXCR4 is an established target of HGF receptor signaling

25. HGF
receptor
family
CXCL11
Crohn’s
Disease
Hypothesis: HGF receptor signaling drives
Crohn’s disease through induction of CXCL11

26. Signaling Pathways Project consensomes

27. Consensomes rank genomic targets according to the strength of their
transcriptional relationship with cellular signaling nodes

28. Kim et al. (2016) Nat Rev Mol Cell Biol 16, 461-472
Insulin, a signal of the fed state, represses starvation-induced autophagy

29. Kim et al. (2016) Nat Cell Biol 13, 132-141
Insulin repression of autophagy is well characterized at the protein level

30. Kaur & Debnath (2016) Nat Rev Mol Cell Biol 16, 461-472
Multiple components of the autophagy pathway have elevated rankings
in the insulin receptor consensome and are repressed by insulin

31. Kaur & Debnath (2016) Nat Rev Mol Cell Biol 16, 461-472
Multiple components of the autophagy pathway have elevated rankings
in the insulin receptor consensome and are repressed by insulin

32. Symbol Name Percentile CPV
ATG14 autophagy related 14 99.83 4.152E-34
ULK1 unc-51 like autophagy activating kinase 1 98.86 2.896E-22
ATG2A autophagy related 2A 98.45 8.834E-21
MAP1LC3B microtubule associated protein 1 light chain 3 beta 96.71 1.332E-16
ATG101 autophagy related 101 95.81 2.677E-15
RB1CC1 RB1 inducible coiled-coil 1 95.81 2.677E-15
WIPI2 WD repeat domain, phosphoinositide interacting 2 95.81 2.677E-15
ATG2B autophagy related 2B 94.57 4.86E-14
SNX30 sorting nexin family member 30 93.86 1.451E-13
ATG16L2 autophagy related 16 like 2 93.86 1.451E-13
ATG9A autophagy related 9A 93.07 7.964E-13
GABARAPL2 GABA type A receptor associated protein like 2 91.56 1.178E-11
ATG13 autophagy related 13 91.56 1.178E-11
GABARAP GABA type A receptor-associated protein 91.56 1.178E-11
Of the 33 autophagy pathway genes in the human genome, nearly 50%
are in the 90th percentile of the human insulin receptor consensome

33. The Hypothesis Center: a dkNET-hosted, SPP-driven hypothesis
generation environment for dkNET users

34. Other ongoing SPP collaborations
Enhancing connections between articles and their associated ‘omics datasets
Intersecting literature annotations (Reactome) and ‘omics dataset biocuration (SPP)
to fill gaps in pathway discovery (via SPP API)
Helping the American Thyroid Association encourage re-use datasets of
relevance to its member academic researchers and clinicians
Exposing SPP Regulation Reports as networks in the NDEX biological network
data exchange (via SPP API)

35. Symbiosis between the literature and ‘omics datasets
can drive discovery in cellular signaling

36. Symbiosis between the literature and ‘omics datasets
can drive discovery in cellular signaling

37. Thank you
National Institute of Diabetes, Digestive & Kidney Diseases (NIDDK)
NIDDK Information Network (dkNET)
American Thyroid Association
www.signalingpathways.org
@sigpathproject