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Transcript
Online BIOS QTL atlases
Jan Bert van Klinken
Introduction
In BBMRI-NL a unique collection of omics datasets have been generated,
reflecting different layers of biological processes
metabolome (NMR)
transcriptome (RNA-seq)
epigenome (CpG methylation)
genome (whole-genome seq)
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Introduction
The BIOS consortium aims at integrating these layers of data, in order to
uncover molecular pathways involved in health and disease.
Genome-wide association analyses between omics layers:
genome -> methylome
genome -> transcriptome
(meQTLs)
(eQTLs: gene, exon,
exon ratio, polyA ratio)
genome -> metabolome
(metabolite QTLs)
methylome -> transcriptome (eQTMs)
methylome -> metabolome
transcriptome -> metabolome
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BIOS QTL browser
An important task of BIOS is to make the association results available
to the public. To this end, a QTL web browser has been developed by
the BIOS team: http://genenetwork.nl/biosqtlbrowser
Data can be downloaded all at once
or the database can be queried
for specific SNPs, CpG sites, genes.
Currently, query results are presented
in tabular format separately for each
association study.
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BIOS QTL browser
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BIOS QTL browser
bulk download
query database
query results
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BIOS QTL browser
The current BIOS QTL browser will be improved
Goal
Make BIOS QTL results accessible for and interpretable by a wide range
of users* through a user-friendly** and sustainable*** web application.
*
**
***
7
users with different expertises and backgrounds
present results in a visually more appealing way
easy to maintain and to add new association results or data layers
Online BIOS QTL atlases
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Prototype development
Make QTL browser more user-friendly and flexible:
better represent omics data layers and associations between layers
variants
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CpG sites
genes
phenotypes
21-09-2016
Prototype development
Alpha version of new QTL browser
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Online BIOS QTL atlases
(query: OPLAH)
21-09-2016
Prototype development
Alpha version of new QTL browser
10
Online BIOS QTL atlases
(query: OPLAH)
21-09-2016
Prototype development
Alpha version of new QTL browser
11
Online BIOS QTL atlases
(query: OPLAH)
21-09-2016
Prototype development
Alpha version of new QTL browser
12
Online BIOS QTL atlases
(query: OPLAH)
21-09-2016
Prototype development
Alpha version of new QTL browser
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Online BIOS QTL atlases
(query: SORT1)
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Prototype development
SNP query -> list of SNPs in LD ->
->
->
->
->
find meQTLs
-> list CpG sites
find eQTLs
-> list of genes
find QTLs
-> list of phenotypes
CpG chr pos overlap
-> list of CpG sites
5' UTR/exon chr pos overlap -> list of genes
list of CpG sites
-> find eQTMs
-> list of genes
-> find associated phenotypes -> list of phenotypes
list of genes
-> find related diseases -> list of phenotypes
For each SNP, CpG site, gene and phenotype, gather functional information from
external databases and hyperlinks to database entries.
Show resulting SNPs, CpG sites, genes, phenotypes and intermediate associations in a
layered graph.
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Prototype development
linkage
disequilibrium
Exploit database integration pipeline developed for QTL annotation
NCBI-GTEx
60651 eQTLs
ConsensusPathDB
4827 genesets
eqtl.uchicago
152947 eQTLs
GeneRIF
517870 references
seeQTL
127148 eQTLs
gEUVADIS
3603289 eQTLs
NCBI gene
36687 genes
TCDB
8556 trans. prot.
GSMM reactions
7440 (Recon2)
8181 (HMR2)
2539 (HepatoNet1)
GSMM compounds
5063 (Recon2)
6006 (HMR2)
1420 (HepatoNet1)
UniProtKB
20207 proteins
ExPASy
6469 enzymes
KEGG Reaction
9174 reactions
KEGG Compound
27893 compounds
KEGG Orthology
17813 identifiers
Reactome
9314 reactions
Reactome
29987 compounds
HMDB
42040 compounds
ChEBI
82827 compounds
linkage
disequilibrium
dbSNP
52026147 SNPs
Gene Ontology
41222 terms
GWAS catalog
17341 SNPs
OMIM
23576 diseases
Orphanet
6930 diseases
KEGG Disease
1396 diseases
MeSH
27149 diseases
Case study
Reanalysis of metabolite GWAS results of Suhre et al (Nature, 2011)
HPS5 ???
3-methyl-2-oxobutyrate
a-hydroxyisovalerate
Creating SNP reports for all QTLs, we found that LDHA is the most logical
candidate gene that could explain the the effect on the metabolite levels
(Heemskerk et al, EJHG, 2015)
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Case study
We showed that LDH can catalyze this conversion in vitro, suggesting that
lactate dehydrogenase plays a role in branched-chain amino acid metabolism.
3-methyl-2-oxobutyrate
Integration with ENCODE
data showed chromatin
interaction between
rs2403254 and the LDHA TSS.
Heemskerk et al., 2015
a-hydroxyisovalerate
Case study
We showed that LDH can catalyze this conversion in vitro, suggesting that
lactate dehydrogenase plays a role in branched-chain amino acid metabolism.
3-methyl-2-oxobutyrate
a-hydroxyisovalerate
Recent data from GTEx V6p confirmed that rs2403254 is an eQTL for LDHA in
the muscle.
Heemskerk et al., 2015
Current and future work
1. Finish prototype (implement LD computation, enable different types of queries)
2. Front end: develop dynamic web application to display query results
as a layered network.
3. Back end: convert existing MATLAB scripts into server-side scripts
(JavaScript+Node.js, Perl, Python) and store database content in a
format that can be efficiently queried (CSV, JSON, RDF, MySQL,
levelDB).
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Conclusion
• Task of BIOS to develop a user-friendly and sustainable
web application to browse QTL results.
• First version online: http://genenetwork.nl/biosqtlbrowser .
• Prototype of new browser has been developed that emphasizes
layered structure in the data.
• Which additional features will/should be added is open for discussion.
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BIOS QTL browser
Features
• Report variants in strong Linkage Disequilibrium with top SNPs
• Functional annotation of genetic variants and methylation sites
(histone marks, DNAse activity, TF binding)
• Gather gene-specific knowledge from external databases
(gene function, role in pathways, implication in disease)
•
•
•
•
Complex / composite queries (e.g. variant list and gene combinations)
Download query results
Develop API to facilitate data access
FAIR-ification of QTL results (Findable Accessible Interoperable Reusable)
Open for discussion - all input is welcome!
[email protected]
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