Presentation on how to support cancer genomics at tissue and single cell level with Expression Atlas at the Industry workshop: from genomics and bioinformatics to personalised medicine at University of Buenos Aires

1. Laura Huerta, PhD
Senior Scientific Curator
lauhuema@ebi.ac.uk
17th October 2018
FCEN-UBA, Argentina
Supporting cancer genomics at tissue and
single cell level with Expression Atlas
Industry Workshop: From Genomics and
Bioinformatics to Personalized Medicine

2. www.ebi.ac.uk/gxa/
What is Expression Atlas?
Open science resource that selects, curates,
re-analyses and displays gene/protein expression data

3. OUR MISSION
To provide to the scientific
community freely available
information on the abundance
and localisation of RNA (and
proteins) across different
species and biological
conditions
§ Where is my favourite gene
expressed?
§ How its expression changes
in a disease?

4. research community
lab1 lab2 lab3 lab n...
Gene expression
across species
and biological
conditions
Data curation & ontology Data integration & visualizationData analysis
• Baseline expression
• Differential expression
• Gene co-expression
• Transcript quantification
• Enrichment analysis
• Genome tracksraw data + metadata
Ontology
annotation
Access re-analysed
RNA-seq data
Curation research community
lab1 lab2 lab3 lab n...
derived
resultsraw data
curated
metadata
Data journey at Expression Atlas

5. 150 baseline expression
> 3,200 differential expression
> 3,300 datasets
Expression Atlas contains thousands of
selected and curated datasets

6. … across more than 45 species ...
Mus musculus
963
Homo sapiens
1,189
Arabidopsis thaliana
528
Ratus
norvegius
138
Drosophila
melanogaster
128
Oryza sativa
Japonica Group
72
Zea mays
35
Vitis vinifera
20
Gallus gallus
25
Saccharomyces
cerevisiae
39
Danio rerio
14
Caenorhabditis elegans
24
Triticum aestivum
14
Sus scrofa
17
Glycine max
20

7. … across more than 45 species ...

8. Large-scale RNA-seq experiments
Access gene expression results of large-scale datasets
Basic research
Cancer research
Key cell line
models
Proteomics
Zebrafish development
Prenatal human brain
Mouse models

9. PCAWG data visualization
High expression of KLK3, ACPP,
PCA3, FOLH1, HPN and GALNT3
genes in prostate adenocarcinoma

10. In which conditions
is a particular gene
expressed?
Discover and interpret gene/
protein expression analysis
results quickly and easy
www.ebi.ac.uk/gxa/
Let’s try Expression Atlas

11. Baseline expression results
KLK3 gene/protein expression across human
tissues from different experiments is
integrated and visualised in one heatmap
Protein
expression
Expressed in prostate gland

12. Differential Expression results
Curated comparisons in which KLK3
gene is differentially expressed

13. Baseline experiment page
Search for a particular gene, e.g. TSPAN6
and find genes with similar expression

14. Baseline experiment page
Search for a particular gene, e.g. TSPAN6
and find genes with similar expression

15. Baseline experiment page
Search for a particular gene, e.g. TSPAN6
and find genes with similar expression

16. Baseline experiment page
Visualise variation among biological replicates
and transcript expression quantification

17. Baseline experiment page
Visualise variation among biological replicates
and transcript expression quantification

18. Expression Atlas data in other resources
www.opentargets.org

19. Expression Atlas data in other resources

20. Expression Atlas data in other resources

21. Expression Atlas data in other resources

22. Expression Atlas data in other resources
Evidence of KLK3 in prostate carcinoma based
on RNA expression from Expression Atlas

23. Single Cell Expression Atlas
ü To provide information on where and under what conditions
different genes are expressed at single cell level
ü Analysis results for ~53,000 cells
ü 43 single cell experiments
ü 9 species: human, mouse, rat,
zebrafish, common fruit fly

24. research community
lab1 lab2 lab3 lab n...
Single cell gene
expression across
species
Data curation & ontology Data integration & visualizationData analysis
• Baseline expression
• Clustering results
• Marker genesraw data + metadata
Ontology
annotation
Curation research community
lab1 lab2 lab3 lab n...
derived
resultsraw data
curated
metadata
Single cell data journey at Expression Atlas
https://github.com/nunofonseca/irap/

25. Expression Atlas - Single Cell Component
www.ebi.ac.uk/gxa/sc/
Discover and interpret gene
expression analysis results
at single cell level

26. GPR17 gene expression across
human cells from different
single cell experiments
Expression Atlas - Single Cell Component

27. GPR17 gene expression across
human cells from different
single cell experiments
Expression Atlas - Single Cell Component
Single cell human experiments in
which GPR17 is a marker gene

28. Expression Atlas - Single Cell Component
High GPR17 expression in
oligodendrocyte precursor cells

29. Expression Atlas - Single Cell Component
High EGFR expression in
“neoplastic” cells

30. Expression Atlas - Single Cell Component
High SOX9 expression in
“neoplastic” cells

31. FUTURE
ü Display bulk RNA-seq and
single cell RNA-seq data in one
place. We will try to design a
unique interface that will help
users navigate and “zoom in”
through the data.
ü Meta-analysis. We will continue
testing methods for batch
correction to derive gene
expression signatures on baseline
and differential views of the data.

32. Expression Atlas: Who we are?
gene-expression@ebi.ac.uk @ExpressionAtlas
Irene
Papatheodorou
Team Leader
Alfonso FuentesLaura Huerta
Silvie Flexova
Data curation Data analysis User Interface
Suhaib MohammedNancy George Haider IqbalJon Manning
Pablo Moreno Monica JianuAnja Fullgrabe
Lingyun Zhao

33. Acknowledgements
ü Gramene collaborators
ü EBI teams:
o SPOT
o Reactome
o ENA
o Ensembl
o Ensembl Genomes
o PRIDE
ü Chan Zuckerberg Initiative
ü Human Cell Atlas
ü Wellcome Trust

34. Laura Huerta, PhD
Senior Scientific Curator
lauhuema@ebi.ac.uk
17th October 2018
FCEN-UBA, Argentina
Supporting cancer genomics at tissue and
single cell level with Expression Atlas
Industry Workshop: From Genomics and
Bioinformatics to Personalized Medicine