1 of 47

The Reactome Knowledgebase

Eliot Ragueneau - Software Engineer�Krishna Tiwari - Curator & Biologist

2 of 47

Background

3 of 47

Motivation for Pathway Databases and Analysis

Nature 407(6805):770-6.The Biochemistry of Apoptosis.

Caspase-8 is the key initiator caspase in the death-receptor pathway. Upon ligand binding, death receptors such as CD95 (Apo-1/Fas) aggregate and form membrane-bound signalling complexes (Box 3). These complexes then recruit, through adapter proteins, several molecules of procaspase-8, resulting in a high local concentration of zymogen. The induced proximity model posits that under these crowded conditions, the low intrinsic protease activity of procaspase-8 (ref. 20) is sufficient to allow the various proenzyme molecules to mutually cleave and activate each other (Box 2). A similar mechanism of action has been proposed to mediate the activation of several other caspases, including caspase-2 and the nematode caspase CED-3 (ref. 21).”

 

4 of 47

Motivation for Pathway Databases and Analysis

  • Intuitive to Scientists:
    • Intuitive display for biological data.
    • Visualize multiple data types.
    • Computational methods available to automate analysis.

  • Pathway Analysis satisfy common “use cases” in biological research:
    • Identifying hidden patterns in gene lists.
    • Predicting the function of unannotated genes.
    • Establishing the framework for quantitative modeling.
    • Assisting in the development of molecular signatures.

5 of 47

What is Reactome?

  • Open source and open access pathway knowledgebase
    • Dates to 2002 @ CSHL & EBI
    • Human pathways encompassing metabolism, signaling, gene regulation, and other biological processes
    • Every pathway is traceable to primary literature
  • Extensively cross-referenced to external bioinformatics databases
  • Provides software tools for browsing and visualizing pathway data and analyzing user data

6 of 47

Data Model

  • Reactome is a reaction-based database
  • Explicitly describe biological processes as a series of biochemical reactions and events

Literature

(PubMed PMID)

location

(GO cell component)

protein (UniProt)

molecule (ChEBI)

complex (GO/PRO)

ncRNA (miRBase)

disease variant (ClinGen, COSMIC)

drug (ChEBI, IUPHAR)

CatalystActivity

(GO mol function)

Output 1

Reaction

Input 1

Input 2

Output 2

Regulation

(GO biol process)

7 of 47

Reactome supports multiple types of reaction

Phosphorylation

Binding

Dimerization

8 of 47

Reactions connect to one another

OUTPUT

INPUT

CATALYST

INPUT OUTPUT

CATALYST

INPUT

OUTPUT

CATALYST

9 of 47

Where does the data comes from?

10 of 47

Reactome Coverage

20K human protein coding genes

11K Reactome

to do

  1. Oprea TI, et al. Unexplored therapeutic opportunities in the human genome. Nat Rev Drug Discov. 2018 May;17(5):377.
  2. 10,092 human high confidence interactors from IntAct

7K no functional data [1]

10K interactors [2]

11 of 47

PANTHER is used to identify model organism orthologs

12 of 47

Reactome Website

13 of 47

Searching with keyword

14 of 47

Searching with keyword

15 of 47

Pathway Browser

16 of 47

Pathway Browser

Hierarchy

Graphics

Details

17 of 47

Pathway Browser

18 of 47

Pathway Browser - Graphics Panel

19 of 47

Pathway Browser - Graphics Panel

20 of 47

Pathway Browser - Graphics Panel

21 of 47

Pathway Browser - Graphics Panel

22 of 47

Pathway Browser - Graphics Panel

23 of 47

Pathway Browser - Graphics Panel

24 of 47

Pathway Browser - Graphics Panel

25 of 47

Pathway Browser - Graphics Panel

26 of 47

Pathway Browser - Hierarchy Panel

27 of 47

Pathway Browser - Details Panel

28 of 47

Analyze Data

29 of 47

Analyze Data

Pathway Enrichment Analysis

Gene set Enrichment Analysis

Human to Other species

Generic cell to specific tissue

30 of 47

Analyze Data - Pathway Enrichment

Pathway Enrichment Analysis

31 of 47

Analyze Data - Pathway Enrichment

32 of 47

Analyze Data - Pathway Enrichment

33 of 47

Analyze Data - Expression Overlay

Pathway Enrichment Analysis

34 of 47

Analyze Data - Expression Overlay

35 of 47

Analyze Data - Gene Set Enrichment

Gene set Enrichment Analysis

36 of 47

Analyze Data - Gene Set Enrichment

Gene set Enrichment Analysis

  1. Algorithm Selection

  1. Adding Data

  1. Adding Metadata

  1. Define Experimental Design

  1. Launch Analysis

37 of 47

Analyze Data - Gene Set Enrichment

38 of 47

Analyze Data - Species Comparison

Human to Other species

39 of 47

Analyze Data - Tissue Distribution

Generic cell to specific tissue

40 of 47

Analyze Data - DisGeNet Overlay

41 of 47

How to export data?

Pathways as

  • png
  • svg
  • pptx

42 of 47

How to export data?

Icons as

  • png
  • svg

43 of 47

How to export data?

44 of 47

Programmatic Access

45 of 47

Reactome licence

46 of 47

I want to know more!

From Reactome Homepage

help@reactome.org

Train Online - https://www.ebi.ac.uk/training/online/

47 of 47

Acknowledgements

  • EMBL-EBI
    • Henning Hermjakob
    • Chuqiao Gong
    • Cristoffer Sevilla
    • Eliot Ragueneau
    • Krishna Tiwari

  • OHSU
    • Guanming Wu
    • Liam Beckman
    • Tim Brunson
    • Nasim Sanati
  • Funding
    • US NIH NHGRI P41 HG003751
    • US NIH NCI IDG 1U01CA239069
    • EMBL

  • Websites
    • reactome.org
    • idg.reactome.org
    • spp.reactome.org
    • reactome.ncpsb.org

  • Contact
    • email:help@reactome.org
    • Twitter: @reactome
  • OICR
    • Lincoln Stein
    • Justin Cook
    • Marc Gillespie
    • Robin Haw
    • Bijay Jassal
    • Bruce May
    • Marija Orlic-Milacic
    • Karen Rothfels
    • Joel Weiser
    • Adam Wright

  • NYU
    • Peter D’Eustachio
    • Lisa Matthews
    • Veronica Shamovsky