Genetic variation in gene regulation Prof. Jonathan K. Pritchard 1 The screen versions of these slides have full details of copyright and acknowledgements 1 Genetic Variation in Gene Regulation Prof. Jonathan K. Pritchard Departments of Genetics & Biology Howard Hughes Medical Institute Stanford University Web: pritchardlab.stanford.edu 2 It is now clear that much of the genetic basis of complex traits is noncoding – presumably due to regulatory variants Genes Figure from WTCCC study (2007) A noncoding GWAS hit for Crohn’s disease 3 Figure from Pickrell, 2014 (AJHG) Only a minority of GWAS hits are due to non-synonymous variants
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Genetic variation in gene regulation · Genetic Variation in Gene Regulation Prof. Jonathan K. Pritchard Departments of Genetics & Biology Howard Hughes Medical Institute Stanford
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Genetic variation in gene regulation
Prof. Jonathan K. Pritchard
1The screen versions of these slides have full details of copyright and acknowledgements
1
Genetic Variation in Gene Regulation
Prof. Jonathan K. Pritchard
Departments of Genetics & Biology
Howard Hughes Medical Institute
Stanford University
Web: pritchardlab.stanford.edu
2
It is now clear that much of the genetic basis of complex traits is noncoding –
presumably due to regulatory variants
Genes
Figure from WTCCC study (2007)
A noncoding GWAS hit for Crohn’s disease
3 Figure from Pickrell, 2014 (AJHG)
Only a minority of GWAS hits are due to non-synonymous variants
Genetic variation in gene regulation
Prof. Jonathan K. Pritchard
2The screen versions of these slides have full details of copyright and acknowledgements
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eQTLs: expression Quantitative Trait Loci -linking genetic variation to changes
in gene regulation
(Early key work on eQTLs by Leonid Kruglyak, Vivian Cheung,Manolis Dermitzakis and others)
Expre
ssion: +
/-S
Ds fro
m m
ean
Expression levels at HLA-C
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DNA sequence encodes cis-acting regulatory
information
(Output is cell-type or context specific)
Steady state mRNA levels
Trans-acting factors in the cell
How do genetic variants influence expression?
Cis-eQTLs presumably disrupt this encoded
information
Affect expression of other genesTrans-eQTLs
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Question: how do SNPs impact
gene regulation?
Ultimately we want to get much better
at interpreting noncoding variants
that affect phenotypes
Genetic variation in gene regulation
Prof. Jonathan K. Pritchard
3The screen versions of these slides have full details of copyright and acknowledgements
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One major source of eQTL data is from GTEx
GTEx is collecting expression data from dozens
of tissue sites in hundreds of individuals
http://www.gtexportal.org/home/
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• Immortalized B cells: There are now >1000 cell lines genotyped
and sequenced by HapMap and the 1000 Genomes Project
• Numerous studies have shown strong overlap
between HapMap eQTLs and GWAS signals for a variety of traits
Ima
ge:
ha
pm
ap
.org
HapMap cell lines as a model system for studying expression variation
See work by Cheung, Dermitzakis, Snyder and Gilad/Pritchard groups
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RNA-seq studies in HapMap samples have so far identified several thousand
cis-eQTLs
[Montgomery et al., 2010, Pickrell et al., 2010, Lappalainen et al., 2013]
Genetic variation in gene regulation
Prof. Jonathan K. Pritchard
4The screen versions of these slides have full details of copyright and acknowledgements
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Example cis-eQTL from HapMap samplesRNA-seq read depth at TSP50, stratified by genotype
at associated SNP
Pickrell et al, Nature (2010)
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Some eQTLs affect individual exons only
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What is the molecular basis for cis-eQTLs?
Genetic variation in gene regulation
Prof. Jonathan K. Pritchard
5The screen versions of these slides have full details of copyright and acknowledgements
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eQTLs are detected because genotype correlates with steady state expression
Figure: Athma Pai
DNaseI, Pol II,
DNA methylation,
H3K4me1, H3K4me3, H3K27me3,
H3K27ac, MNase
mRNA transcription
rates (4SU metabolic
labeling)
Alternative splicing
from RNA-seq
Steady state expression
from RNA-seq
mRNA decay experiments
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Most analyses of eQTLs are complicated by the fact that there is uncertainty
about which site is causal
Gaffney et al. (Genome Biology 2012)
15Pickrell et al (2010)
Model: Veyrieras, PLOS Gen (2008)
Most eQTLs lie inside, or very near target genes (long-range eQTLs >100kb do exist,
but these are unusual)
Distribution of top signals
with respect to affected genes
Using a model to correct for LD
Genetic variation in gene regulation
Prof. Jonathan K. Pritchard
6The screen versions of these slides have full details of copyright and acknowledgements
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Most eQTLs affect regulators of chromatin function including
promoters and enhancers
Much of this is by altering transcription factor binding sites
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DNaseI footprinting was first used by Galas & Schmitz (1979); genome-wide
assays developed by Crawford and Stamatoyannopoulos labs
Average DNaseI profile at NRSF binding sites
(Pique-Regi et al, 2011, Genome Research)
DNaseI sequencing
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Degner et al. (2012) performed DNase-seq in 70 HapMap cell lines
They identified ~9000 DNase-QTLs
Genetic variation in gene regulation
Prof. Jonathan K. Pritchard
7The screen versions of these slides have full details of copyright and acknowledgements
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Example dsQTL: C haplotype has DNaseIhypersensitive site; only weak cutting
of T haplotypeAssociated SNP
(rs4953223)
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This dsQTL appears to be due to disruption of an NF-KB binding site
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NF-kB ChIP-seq data show that binding is virtually eliminated from the T haplotype
Degner, Nature (2012)
Data from Kasowski, Science (2010)
Genetic variation in gene regulation
Prof. Jonathan K. Pritchard
8The screen versions of these slides have full details of copyright and acknowledgements
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dsQTL SNPs typically drive coordinated changes in multiple aspects of chromatin
architecture as well as TF occupancy
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Example: a promoter SNP at SNX7 drives coordinated changes in chromatin
and transcription
McVicker et al. Science (2013)
rs12723363
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Increased DNaseI sensitivity at dsQTLscorrelates with higher TF occupancy…
Degner et al, 2012
DNase1: fraction of reads in heterozygote carrying major allele
Transcription
factor data:
fraction
of reads
in heterozygote
carrying major
allele
Genetic variation in gene regulation
Prof. Jonathan K. Pritchard
9The screen versions of these slides have full details of copyright and acknowledgements
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Nucleosome midpoint density around dsQTLs
(MNase data)Gaffney et al, PLOS Gen (2012)
…And increased DNaseI sensitivity at dsQTLscorrelates with lower nucleosome occupancy
and stronger positioning
dsQTL center
High DNase genotypes
Low DNase genotypes
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What types of regulatory information encoded in the DNA sequence are disrupted
by chromatin QTL SNPs?
eQTLs can potentially help us to determine causal links from DNA sequence to chromatin function