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Title: Maps of Open Chromatin Guide the Functional Follow-Up of Genome-Wide Association Signals: Application to Hematological Traits}
Article:
Abstract:
Turning genetic discoveries identified in genome-wide association( GWA) studies into biological mechanisms is an important challenge in human genetics. Many GWA signals map outside exons, suggesting that the associated variants may lie within regulatory regions. We applied the formaldehyde-assisted isolation of regulatory elements( FAIRE) method in a megakaryocytic and an erythroblastoid cell line to map active regulatory elements at known loci associated with hematological quantitative traits, coronary artery disease, and myocardial infarction. We showed that the two cell types exhibit distinct patterns of open chromatin and that cell-specific open chromatin can guide the finding of functional variants. We identified an open chromatin region at chromosome 7q22. 3 in megakaryocytes but not erythroblasts, which harbors the common non-coding sequence variant rs342293 known to be associated with platelet volume and function. Resequencing of this open chromatin region in 643 individuals provided strong evidence that rs342293 is the only putative causative variant in this region. We demonstrated that the C- and G-alleles differentially bind the transcription factor EVI1 affecting PIK3CG gene expression in platelets and macrophages. A protein–protein interaction network including up- and down-regulated genes in Pik3cg knockout mice indicated that PIK3CG is associated with gene pathways with an established role in platelet membrane biogenesis and thrombus formation. Thus, rs342293 is the functional common variant at this locus; to the best of our knowledge this is the first such variant to be elucidated among the known platelet quantitative trait loci( QTLs). Our data suggested a molecular mechanism by which a non-coding GWA index SNP modulates platelet phenotype.
Introduction:
In recent years, genome-wide association( GWA) studies have driven the discovery of genetic loci associated with a multitude of complex traits and diseases. However, due to linkage disequilibrium( LD), the single-nucleotide polymorphisms( SNPs) assayed in large-scale GWA studies typically yield a proxy for the actual causative variant( s) and often fail to even pinpoint the underlying gene[1]–[3]. Therefore, despite great success in biological discovery, GWA studies have shed little light on which are the functional variants, common and/or low-frequency, and how they relate to biological mechanisms. Several strategies have been proposed to identify causative sequence variants underlying GWA signals, including fine-mapping( i. e. targeted resequencing followed by additional genotyping of large cohorts) and functional annotation using biochemical assays( e. g. gene expression studies)[1],[3]. Since many initial association signals are localized at intronic and intergenic regions, it has been postulated that they may correspond to gene regulatory variants[4]. Therefore, functional variants may exert their effects through regulation of gene expression, which can vary substantially among tissues and cell types[5],[6]. Integrated studies have illustrated how particular trait-associated alleles are mechanistically relevant to cellular functions and pathways[7]–[12]. In a recent study, Gaulton et al. used the formaldehyde-assisted isolation of regulatory elements( FAIRE) technique to identify pancreatic islet-specific open chromatin regions, some of which embed known diabetes risk variants[13]. FAIRE is an elegant approach to isolating nucleosome-depleted regions( NDRs) that encompass active regulatory elements, and thus, to accessing regulatory variants[14],[15]. Heritable hematological traits are of particular interest in studying the architecture of complex traits, since relevant cell types for functional assays are easily accessible. In addition, genetic loci associated with platelet counts, SH2B3–ATXN2 and PTPN11, have been reported to be associated with coronary artery disease( CAD) and myocardial infarction( MI) suggesting a possible role for platelets as an intermediate phenotype[16]. Here we describe maps of open chromatin generated by FAIRE in a megakaryocytic and an erythroblastoid cell line at known GWA loci associated with hematological quantitative traits, CAD and MI. We report substantial differences in chromatin architecture among the two cell types and assess the phenotypic causality of variants that fall into NDRs specific to either cell type. We demonstrate the procedure with the locus at chromosome 7q22. 3, which is associated with mean platelet volume and function, where we identify a site of open chromatin in megakaryocytes but not erythroblasts and elucidate the molecular mechanism that contributes to the platelet phenotype.
Discussion:
The intersection of maps of open chromatin with variants identified through GWA studies can facilitate the search for underlying functional variant( s). We applied the FAIRE assay to generate a catalog of NDRs in a megakaryocytic and an erythroblastoid cell line at 62 selected genetic loci associated with hematological and cardiovascular traits. We provided evidence that open chromatin profiles exhibit distinct patterns among different cell types and that cell-specific NDRs can be useful in prioritizing regions for further functional analysis. As proof, we elucidated the molecular basis of the association with mean platelet volume and function at chromosome 7q22. 3. We identified a NDR in MK but not EB cells containing the index SNP rs342293 for this association and demonstrated that the alleles of rs342293 differentially bind the transcription factor EVI1. Thus, to the best of our knowledge this is the first functional variant to be elucidated among the known platelet QTLs. Expression QTL data in platelets and macrophages provided statistical support that rs342293 affects PIK3CG gene expression levels. PIK3CG is transcribed in megakaryocytes but only weakly expressed in erythroblasts[18], which is in agreement with the MK-specific properties of the identified NDR. However, additional work is required to scrutinize all possible targets of this regulatory module. The closest gene FLJ36031, which spans only 2 kb, has no reported protein product and function and requires further characterization. PIK3CG is located 134 kb downstream of rs342293 and encodes the phosphoinositide-3-kinase γ-catalytic subunit. The lipid kinase PIK3CG( PI3Kγ) is a member of the class I PI3Ks and catalyzes the conversion of phosphatidylinositol-4, 5-bisphosphate( PtdIns( 4, 5) P2; PIP2) to phosphatidylinositol-3, 4, 5-trisphosphate( PtdIns( 3, 4, 5) P3; PIP3) downstream of cell surface receptor activation[25]–[27]. In megakaryocytes and platelets, PIP3 is crucial in the collagen-induced regulation of phospholipase C and initiation of megakaryopoiesis and proplatelet formation[28]. Functional studies with Pik3cg knockout mice have indicated a role in wound healing[29], ADP-induced platelet aggregation and thrombosis[30],[31]. It is noteworthy that PIK3CG has also a prominent role in macrophage activation[27]. Whole-genome gene expression profiling in Pik3cg−/− mice showed differential expression of genes involved in important platelet-related pathways compared to wild type mice, most notably Vwf and its platelet membrane receptor components. Our recent meta-analysis of GWA studies in 68, 000 Northern Europeans showed that common sequence variation at the VWF and GP1BA loci exert an effect on platelet volume and counts, respectively( NS, unpublished data). This recent finding together with the established knowledge that Mendelian mutations in the genes encoding the platelet VWF( Von Willebrand disease, type 2; OMIM: 613554) and its receptor( Bernard-Soulier syndrome; OMIM: 231200) are causative of giant platelets, give biological credence to the observed effects of Pik3cg knockout on the transcription of these platelet genes. The protein-protein interaction network centered on PIK3CG highlighted additional proteins implicated in severe platelet disorders, including TUBB1( macrothrombocytopenia, autosomal dominant, TUBB1-related; OMIM: 613112), F5( factor V deficiency; OMIM: 612309) and P2RY12( bleeding disorder due to P2RY12 defect; OMIM: 609821). Therefore, it is plausible to assume that differences in the PIK3CG transcript levels in humans, based on the different alleles of rs342293, may lead to changes in the abundance of platelet membrane proteins that are key regulators of platelet formation. We previously showed an association of rs342293-G with decreased platelet reactivity in humans, assessed as the proportion of binding to annexin V and fibrinogen, as well as P-selectin expression, after activation of platelets with collagen-related peptide( CRP-XL)[20]. We also observed that rs342293 is likely to modify events downstream of signaling via the collagen signaling receptor glycoprotein VI, which is encoded by GP6[32]. A recent GWA study showed the same locus at chromosome 7q22. 3 to be associated also with epinephrine-induced platelet aggregation[33]. The index SNP in that study, rs342286, and rs342293 are in high LD( r2=0. 87, Phase II HapMap, CEU) making rs342293 the putative causative variant underlying both functional associations. The observation that platelet functional events triggered via an immunoreceptor tyrosine-based activation motif on the Fc receptor γ-chain( ITAM-FcR-γ) or G-protein-coupled receptor, for collagen and epinephrine, respectively, are both modified by differences in the PIK3CG transcript level is compatible with the notion that both signaling cascades require PIP3 and that silencing of Pik3cg in mice reduces the expression of the Gp6 gene. Based on the above data, we propose a model( Figure 5) in which the DNA sequence containing the C- but not the G-allele of rs342293 binds the transcription factor EVI1, which acts as transcriptional repressor of PIK3CG in megakaryocytes and ultimately affects platelet phenotype. EVI1( ecotropic viral integration site-1) encodes a protein with two zinc-finger domains( ZF1 and ZF2), which feature distinct DNA-binding specificities[34]. EVI1 mainly promotes hematopoietic differentiation into the megakaryocytic lineage. EVI1 was frequently reported to be a repressor of transcription that has the potential to recruit diverse regulatory proteins. For example, EVI1 antagonizes the growth-inhibitory effect of transforming growth factor-β( TGF-β), a potent regulator of megakaryopoiesis[35], by interacting with SMAD3 via ZF1, and inhibiting SMAD3 from binding to DNA[36],[37]. EVI1 contains domains that interact with RUNX1( Runt-related transcription factor 1), which is the α-subunit of the transcription factor CBF( core binding factor). The interaction of EVI1 with the DNA-binding domain Runt of RUNX1 leads to the destabilization of the DNA-RUNX1 complex and subsequent loss of RUNX1 function[38]. By converting the read-out system from microarrays to high-throughput next-generation sequencing, genome-wide open chromatin profiles can be interrogated. This would scale up analysis to the whole genome generating a catalog of open chromatin profiles to annotate association loci identified in past and future GWA studies. Furthermore, resources such as the completed 1000 Genomes Project will make the requirement for resequencing any identified NDR redundant. However, access to cell types relevant to the studied trait is not always feasible and can be a limitation for functional studies. For instance, we did not observe any intersection of FAIRE peaks with variants associated with CAD/MI or hypertension indicating that cell types other than the megakaryocytic and erythroblastoid cell lines analyzed here may be more suitable. In addition to rs342293, we identified six putative functional variants associated with hematological and cardiovascular traits that fall into open chromatin( Table 2). Follow-up functional studies of these variants will further test the applicability of the approach we have proposed here. For example, the MK-specific NDR containing rs2038479 was found to mark an alternative promoter of a dynamin 3( DNM3) transcript with expression restricted to the megakaryocytic lineage( WHO, unpublished data). Correlation of signatures of open chromatin with experimentally determined transcription factor binding sites studied in different cell types can systematically and rapidly translate GWA signals into functional components and biological mechanisms, thus paving the way to clinical benefit.
Genome-wide scans have revealed multiple genetic regions underlying complex traits . However , the transition from an initial association signal to identifying the functional DNA change ( s ) has proved challenging . Many of the DNA changes discovered are located outside protein-coding regions and may exert their effects through gene regulation . We screened genetic regions associated with hematological traits in erythroblasts ( red blood cells ) and megakaryocytes ( platelet-producing cells ) and mapped sites of open chromatin , which harbor active gene regulatory elements . We investigated a DNA sequence change located within a site of open chromatin at chromosome 7 in megakaryocytes , but not erythroblasts , known to be associated with platelet volume . We showed that this DNA change is functional due to alteration of the binding site of a transcription factor , which regulates the expression of a gene that affects platelet characteristics . Mice lacking this gene revealed significant differences in expression of several important platelet genes compared to wild-type mice . The approach described here can be applied in different cell types to functionally follow-up association signals with many other biological traits by identification of the causative base change and how it affects gene function , thus paving the way to clinical benefit .