Cell Specific eQTL Analysis without Sorting Cells

The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn’s disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus.

Jingyuan Fu | Thomas Meitinger | Uwe Völker | Andres Metspalu | Luigi Ferrucci | Ritsert C. Jansen | Markus Perola | Silva Kasela | Harald Grallert | Cisca Wijmenga | Lude Franke | Fernando Rivadeneira | Michael Poidinger | Hanieh Yaghootkar | Konstantin Strauch | Tõnu Esko | Andrew R. Wood | Samuli Ripatti | Albert Hofman | Yang Li | Veikko Salomaa | Harm-Jan Westra | Holger Prokisch | Benjamin P. Fairfax | Rinse K. Weersma | André G. Uitterlinden | David Melzer | Julian C. Knight | Francesca Zolezzi | Jan H. Veldink | Anis Larbi | Johannes Kettunen | Astrid Petersmann | De Yun Wang | Christian Herder | Rossella Melchiotti | Andrew B. Singleton | Lili Milani | Michael Roden | Pärt Peterson | Juha Karjalainen | Marjolein J. Peters | Katharina Schramm | Georg Homuth | Danny Arends | M. Peters | D. Hernandez | D. Melzer | A. Singleton | A. Hofman | A. Uitterlinden | J. V. van Meurs | L. Ferrucci | E. Reinmaa | V. Salomaa | M. Perola | Jingyuan Fu | C. Wijmenga | K. Strauch | F. Rivadeneira | J. Knight | T. Meitinger | R. Jansen | S. Ripatti | A. Metspalu | T. Esko | L. Milani | H. Prokisch | L. H. van den Berg | J. Veldink | J. Kettunen | J. Karjalainen | H. Westra | H. Grallert | L. Franke | K. Schramm | C. Schurmann | G. Homuth | A. Petersmann | M. Roden | U. Völker | C. Herder | A. Wood | A. Andiappan | O. Rotzschke | S. Kasela | R. Weersma | B. Fairfax | M. Platteel | R. Lorbeer | H. Yaghootkar | D. Arends | Yang Li | M. Visschedijk | L. Tserel | P. Peterson | R. Melchiotti | Bernett Lee | M. Poidinger | F. Zolezzi | A. Larbi | D. Wang | Seiko Makino | Tim M. Frayling | Dena G. Hernandez | Claudia Schurmann | Seiko Makino | Roberto Lorbeer | Mathieu Platteel | Leonard H. van den Berg | Eva Reinmaa | Liina Tserel | Joyce B. J. van Meurs | Bernett Lee | Olaf Rotzschke | Anand Kumar Andiappan | Marijn Visschedijk | A. Uitterlinden | A. Hofman | Tim Frayling

[1]  Pedro G. Ferreira,et al.  Transcriptome and genome sequencing uncovers functional variation in humans , 2013, Nature.

[2]  Monique M. B. Breteler,et al.  The Rotterdam Study: 2016 objectives and design update , 2015, European Journal of Epidemiology.

[3]  E. Rissman,et al.  Loss of estrogen-mediated immunoprotection underlies female gender bias in experimental Crohn’s-like ileitis , 2014, Mucosal Immunology.

[4]  E. Andres Houseman,et al.  Reference-free cell mixture adjustments in analysis of DNA methylation data , 2014, Bioinform..

[5]  R. Irizarry,et al.  Accounting for cellular heterogeneity is critical in epigenome-wide association studies , 2014, Genome Biology.

[6]  Devin C. Koestler,et al.  DNA methylation arrays as surrogate measures of cell mixture distribution , 2012, BMC Bioinformatics.

[7]  John K Wiencke,et al.  Quantitative reconstruction of leukocyte subsets using DNA methylation , 2013, Genome Biology.

[8]  Subrata Ghosh,et al.  Natalizumab for active Crohn's disease. , 2003, The New England journal of medicine.

[9]  C. Gieger,et al.  Genome-Wide Association Study Identifies Two Novel Regions at 11p15.5-p13 and 1p31 with Major Impact on Acute-Phase Serum Amyloid A , 2010, PLoS genetics.

[10]  Christopher D. Brown,et al.  Integrative Modeling of eQTLs and Cis-Regulatory Elements Suggests Mechanisms Underlying Cell Type Specificity of eQTLs , 2012, PLoS genetics.

[11]  P. Donnelly,et al.  A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies , 2009, PLoS genetics.

[12]  Meike W. Vernooij,et al.  The Rotterdam Study: 2014 objectives and design update , 2013, European Journal of Epidemiology.

[13]  R. Ophoff,et al.  Unraveling the Regulatory Mechanisms Underlying Tissue-Dependent Genetic Variation of Gene Expression , 2012, PLoS genetics.

[14]  H. Uhlig.  Monogenic diseases associated with intestinal inflammation: implications for the understanding of inflammatory bowel disease , 2013, Gut.

[15]  P. Deloukas,et al.  Multiple common variants for celiac disease influencing immune gene expression , 2010, Nature Genetics.

[16]  Ritsert C. Jansen,et al.  MixupMapper: correcting sample mix-ups in genome-wide datasets increases power to detect small genetic effects , 2011, Bioinform..

[17]  Luigi Ferrucci,et al.  Genome-Wide Association Study of Plasma Polyunsaturated Fatty Acids in the InCHIANTI Study , 2009, PLoS genetics.

[18]  Jingyuan Fu,et al.  Trans-eQTLs Reveal That Independent Genetic Variants Associated with a Complex Phenotype Converge on Intermediate Genes, with a Major Role for the HLA , 2011, PLoS genetics.

[19]  Mark M. Davis,et al.  Cell type–specific gene expression differences in complex tissues , 2010, Nature Methods.

[20]  Christian Gieger,et al.  Impact of common regulatory single-nucleotide variants on gene expression profiles in whole blood , 2012, European Journal of Human Genetics.

[21]  F. Vannberg,et al.  GENETICS OF GENE EXPRESSION IN PRIMARY IMMUNE CELLS IDENTIFIES CELL-SPECIFIC MASTER REGULATORS AND ROLES OF HLA ALLELES , 2012, Nature Genetics.

[22]  Greg Gibson,et al.  Blood-Informative Transcripts Define Nine Common Axes of Peripheral Blood Gene Expression , 2013, PLoS genetics.

[23]  Markus Perola,et al.  An Immune Response Network Associated with Blood Lipid Levels , 2010, PLoS genetics.

[24]  C. Wijmenga,et al.  Gene expression analysis identifies global gene dosage sensitivity in cancer , 2015, Nature Genetics.

[25]  R. Holle,et al.  Incidence of Type 2 diabetes in the elderly German population and the effect of clinical and lifestyle risk factors: KORA S4/F4 cohort study , 2009, Diabetic medicine : a journal of the British Diabetic Association.

[26]  John D. Storey,et al.  Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis , 2007, PLoS genetics.

[27]  B. Browning,et al.  A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. , 2009, American journal of human genetics.

[28]  J. McCord,et al.  A comparative study of neutrophil purification and function. , 1985, Journal of immunological methods.

[29]  Christian Gieger,et al.  Multiple Loci Are Associated with White Blood Cell Phenotypes , 2011, PLoS genetics.

[30]  Andres Metspalu.  The Estonian Genome Project , 2004 .

[31]  M. W. Foster,et al.  Integrating ethics and science in the International HapMap Project , 2004, Nature Reviews Genetics.

[32]  C. Gieger,et al.  Analyzing Illumina Gene Expression Microarray Data from Different Tissues: Methodological Aspects of Data Analysis in the MetaXpress Consortium , 2012, PloS one.

[33]  C. Carlson,et al.  Genetic variants associated with the white blood cell count in 13,923 subjects in the eMERGE Network , 2011, Human Genetics.

[34]  Luigi Ferrucci,et al.  Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain , 2010, PLoS genetics.

[35]  B. K. Suri,et al.  Genome-Wide Association Study for Atopy and Allergic Rhinitis in a Singapore Chinese Population , 2011, PloS one.

[36]  A. Ekbom,et al.  Sex-specific risks for pediatric onset among patients with Crohn's disease. , 2003, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.

[37]  G. Abecasis,et al.  MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes , 2010, Genetic epidemiology.

[38]  M. Whitlock.  Combining probability from independent tests: the weighted Z‐method is superior to Fisher's approach , 2005, Journal of evolutionary biology.

[39]  J. Korzenik,et al.  Sargramostim for active Crohn's disease. , 2005, The New England journal of medicine.

[40]  P. Deloukas,et al.  Patterns of Cis Regulatory Variation in Diverse Human Populations , 2012, PLoS genetics.

[41]  W. Rathmann,et al.  Cohort profile: the study of health in Pomerania. , 2011, International journal of epidemiology.

[42]  Dorret I. Boomsma,et al.  DeepSAGE Reveals Genetic Variants Associated with Alternative Polyadenylation and Expression of Coding and Non-coding Transcripts , 2013, PLoS genetics.

[43]  Toshihiro Tanaka.  The International HapMap Project , 2003, Nature.

[44]  M. Peters,et al.  Systematic identification of trans eQTLs as putative drivers of known disease associations , 2013, Nature Genetics.

[45]  F. Collins,et al.  Potential etiologic and functional implications of genome-wide association loci for human diseases and traits , 2009, Proceedings of the National Academy of Sciences.