Maps of open chromatin guide the functional follow-up of genome-wide association signals: application to hematological traits

Advances in understanding the pathogenesis of hereditary macrothrombocytopenia

Low platelet count, or thrombocytopenia, is a common haematological abnormality, with a wide differential diagnosis, which may represent a clinically significant underlying pathology. Macrothrombocytopenia, the presence of large platelets in combination with thrombocytopenia, can be acquired or hereditary and indicative of a complex disorder. In this review, we discuss the interpretation of platelet count and volume measured by automated haematology analysers and highlight some important technical considerations relevant to the analysis of blood samples with macrothrombocytopenia. We review how large cohorts, such as the UK Biobank and INTERVAL studies, have enabled an accurate description of the distribution and co-variation of platelet parameters in adult populations. We discuss how genome-wide association studies have identified hundreds of genetic associations with platelet count and mean platelet volume, which in aggregate can explain large fractions of phenotypic variance, consistent with a complex genetic architecture and polygenic inheritance. Finally, we describe the large genetic diagnostic and discovery programmes, which, simultaneously to genome-wide association studies, have expanded the repertoire of genes and variants associated with extreme platelet phenotypes. These have advanced our understanding of the pathogenesis of hereditary macrothrombocytopenia and support a future clinical diagnostic strategy that utilises genotype alongside clinical and laboratory phenotype data.

Common variants in signaling transcription-factor-binding sites drive phenotypic variability in red blood cell traits

Genome-wide association studies identify genomic variants associated with human traits and diseases. Most trait-associated variants are located within cell-type-specific enhancers, but the molecular mechanisms governing phenotypic variation are less well understood. Here, we show that many enhancer variants associated with red blood cell (RBC) traits map to enhancers that are co-bound by lineage-specific master transcription factors (MTFs) and signaling transcription factors (STFs) responsive to extracellular signals. The majority of enhancer variants reside on STF and not MTF motifs, perturbing DNA binding by various STFs (BMP/TGF-β-directed SMADs or WNT-induced TCFs) and affecting target gene expression. Analyses of engineered human blood cells and expression quantitative trait loci verify that disrupted STF binding leads to altered gene expression. Our results propose that the majority of the RBC-trait-associated variants that reside on transcription-factor-binding sequences fall in STF target sequences, suggesting that the phenotypic variation of RBC traits could stem from altered responsiveness to extracellular stimuli.

In The Blood: Connecting Variant to Function In Human Hematopoiesis

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with a range of human diseases and traits. However, understanding the mechanisms by which these genetic variants have an impact on associated diseases and traits, often referred to as the variant-to-function (V2F) problem, remains a significant hurdle. Solving the V2F challenge requires us to identify causative genetic variants, relevant cell types/states, target genes, and mechanisms by which variants can cause diseases or alter phenotypic traits. We discuss emerging functional approaches that are being applied to tackle the V2F problem for blood cell traits, illuminating how human genetic variation can impact on key mechanisms in hematopoiesis, as well as highlighting future prospects for this nascent field.

GWAS and PheWAS of red blood cell components in a Northern Nevadan cohort

In this study, we perform a full genome-wide association study (GWAS) to identify statistically significantly associated single nucleotide polymorphisms (SNPs) with three red blood cell (RBC) components and follow it with two independent PheWASs to examine associations between phenotypic data (case-control status of diagnoses or disease), significant SNPs, and RBC component levels. We first identified associations between the three RBC components: mean platelet volume (MPV), mean corpuscular volume (MCV), and platelet counts (PC), and the genotypes of approximately 500,000 SNPs on the Illumina Infimum DNA Human OmniExpress-24 BeadChip using a single cohort of 4,673 Northern Nevadans. Twenty-one SNPs in five major genomic regions were found to be statistically significantly associated with MPV, two regions with MCV, and one region with PC, with p<5x10^-8. Twenty-nine SNPs and nine chromosomal regions were identified in 30 previous GWASs, with effect sizes of similar magnitude and direction as found in our cohort. The two strongest associations were SNP rs1354034 with MPV (p = 2.4x10^-13) and rs855791 with MCV (p = 5.2x10^-12). We then examined possible associations between these significant SNPs and incidence of 1,488 phenotype groups mapped from International Classification of Disease version 9 and 10 (ICD9 and ICD10) codes collected in the extensive electronic health record (EHR) database associated with Healthy Nevada Project consented participants. Further leveraging data collected in the EHR, we performed an additional PheWAS to identify associations between continuous red blood cell (RBC) component measures and incidence of specific diagnoses. The first PheWAS illuminated whether SNPs associated with RBC components in our cohort were linked with other hematologic phenotypic diagnoses or diagnoses of other nature. Although no SNPs from our GWAS were identified as strongly associated to other phenotypic components, a number of associations were identified with p-values ranging between 1x10^-3 and 1x10^-4 with traits such as respiratory failure, sleep disorders, hypoglycemia, hyperglyceridemia, GERD and IBS. The second PheWAS examined possible phenotypic predictors of abnormal RBC component measures: a number of hematologic phenotypes such as thrombocytopenia, anemias, hemoglobinopathies and pancytopenia were found to be strongly associated to RBC component measures; additional phenotypes such as (morbid) obesity, malaise and fatigue, alcoholism, and cirrhosis were also identified to be possible predictors of RBC component measures.

Dynamic modelling of an ACADS genotype in fatty acid oxidation - Application of cellular models for the analysis of common genetic variants

Background

Genome-wide association studies of common diseases or metabolite quantitative traits often identify common variants of small effect size, which may contribute to phenotypes by modulation of gene expression. Thus, there is growing demand for cellular models enabling to assess the impact of gene regulatory variants with moderate effects on gene expression. Mitochondrial fatty acid oxidation is an important energy metabolism pathway. Common noncoding acyl-CoA dehydrogenase short chain (ACADS) gene variants are associated with plasma C4-acylcarnitine levels and allele-specific modulation of ACADS expression may contribute to the observed phenotype.

Methods and findings

We assessed ACADS expression and intracellular acylcarnitine levels in human lymphoblastoid cell lines (LCL) genotyped for a common ACADS variant associated with plasma C4-acylcarnitine and found a significant genotype-dependent decrease of ACADS mRNA and protein. Next, we modelled gradual decrease of ACADS expression using a tetracycline-regulated shRNA-knockdown of ACADS in Huh7 hepatocytes, a cell line with high fatty acid oxidation-(FAO)-capacity. Assessing acylcarnitine flux in both models, we found increased C4-acylcarnitine levels with decreased ACADS expression levels. Moreover, assessing time-dependent changes of acylcarnitine levels in shRNA-hepatocytes with altered ACADS expression levels revealed an unexpected effect on long- and medium-chain fatty acid intermediates.

Conclusions

Both, genotyped LCL and regulated shRNA-knockdown are valuable tools to model moderate, gradual gene-regulatory effects of common variants on cellular phenotypes. Decreasing ACADS expression levels modulate short and surprisingly also long/medium chain acylcarnitines, and may contribute to increased plasma acylcarnitine levels.

A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis

Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. Here, we conduct a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS), which had analyzed a total of 47,351 cases and 68,284 healthy controls and found more than 200 non-MHC genome-wide associations. Our analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intra-individual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available.

Genetics of platelet traits in ischaemic stroke: focus on mean platelet volume and platelet count

Purpose/Aim of the study: The aim of this review is to summarize the role of genetic variants affecting mean platelet volume (MPV) and platelet count (PLT) leading to higher platelet reactivity and in turn to thrombotic events like stroke and cardiovascular diseases.

MATERIALS AND METHODS

A search was conducted in PUBMED, MEDLINE, EMBASE, PROQUEST, Science Direct, Cochrane Library, and Google Scholar related to the studies focussing on genome-wide association studies (GWAS), whole exome sequencing (WES), whole genome sequencing (WGS), phenome-wide association studies (PheWAS) and multi-omic analysis that have been employed to identify the genetic variants influencing MPV and PLT.

RESULTS

Antiplatelet agents underscore the crucial role of platelets in the pathogenesis of stroke. Higher platelet reactivity in terms of mean platelet volume (MPV) and platelet count (PLT) contributes significantly to the interindividual variation in platelet reaction at the site of vessel wall injury. Some individuals encounter thrombotic events as platelets get occluded at the site of vessel wall injury whereas others heal the injury without occluding the circulation. Evidence suggests that MPV and PLT have a strong genetic component. High throughput techniques including genome-wide association studies (GWAS), whole exome sequencing (WES), whole genome sequencing (WGS), phenome-wide association studies (PheWAS) and multi-omic analysis have identified different genetic variants influencing MPV and PLT.

CONCLUSIONS

Identification of complex genetic cross talks affecting PLT and MPV might help to develop novel treatment strategies in treating neurovascular diseases like stroke.

Platelet function is modified by common sequence variation in megakaryocyte super enhancers

Linking non-coding genetic variants associated with the risk of diseases or disease-relevant traits to target genes is a crucial step to realize GWAS potential in the introduction of precision medicine. Here we set out to determine the mechanisms underpinning variant association with platelet quantitative traits using cell type-matched epigenomic data and promoter long-range interactions. We identify potential regulatory functions for 423 of 565 (75%) non-coding variants associated with platelet traits and we demonstrate, through ex vivo and proof of principle genome editing validation, that variants in super enhancers play an important role in controlling archetypical platelet functions.

Numerous genetic variants, including those located in the non-coding regions of the genome, are known to be associated with blood cells traits. Here, Frontini and colleagues investigate their potential regulatory functions using epigenomic data and promoter long-range interactions.

The genetics of platelet count and volume in humans

The last decade has witnessed an explosion in the depth, variety, and amount of human genetic data that can be generated. This revolution in technical and analytical capacities has enabled the genetic investigation of human traits and disease in thousands to now millions of participants. Investigators have taken advantage of these advancements to gain insight into platelet biology and the platelet's role in human disease. To do so, large human genetics studies have examined the association of genetic variation with two quantitative traits measured in many population and patient based cohorts: platelet count (PLT) and mean platelet volume (MPV). This article will review the many human genetic strategies-ranging from genome-wide association study (GWAS), Exomechip, whole exome sequencing (WES), to whole genome sequencing (WGS)-employed to identify genes and variants that contribute to platelet traits. Additionally, we will discuss how these investigations have examined and interpreted the functional implications of these newly identified genetic factors and whether they also impart risk to human disease. The depth and size of genetic, phenotypic, and other -omic data are primed to continue their growth in the coming years and provide unprecedented opportunities to gain critical insights into platelet biology and how platelets contribute to disease.

From GWAS to function: lessons from blood cells

Haematopoiesis, or the process of formation of mature blood cells from committed progenitors, represents an accessible and well-studied paradigm of cell differentiation and lineage specification. Genetic association studies provide a powerful approach to discover new genes, biological pathways and mechanisms underlying haematopoietic development. Here, we highlight recent findings of genomewide association studies (GWAS) linking 145 genomic loci to traits affecting the formation of red and white cells and platelets in European and other ancestries. We present strategies to address the main challenges in GWAS discoveries, particularly to find functional and regulatory effects of genetic variants, and to identify genes through which these genetic variants affect haematological phenotypes. We argue that studies of haematological trait variation provide an ideal paradigm for understanding the function of GWAS-associated variants owing to the accessible nature of cells, simple cellular phenotype and focused efforts to characterize the genetic and epigenetic factors influencing the regulatory landscape in highly pure mature cell populations.

BCL11A enhancer dissection by Cas9-mediated in situ saturating mutagenesis

Enhancers, critical determinants of cellular identity, are commonly recognized by correlative chromatin marks and gain-of-function potential, although only loss-of-function studies can demonstrate their requirement in the native genomic context. Previously, we identified an erythroid enhancer of human BCL11A, subject to common genetic variation associated with the fetal haemoglobin level, the mouse orthologue of which is necessary for erythroid BCL11A expression. Here we develop pooled clustered regularly interspaced palindromic repeat (CRISPR)-Cas9 guide RNA libraries to perform in situ saturating mutagenesis of the human and mouse enhancers. This approach reveals critical minimal features and discrete vulnerabilities of these enhancers. Despite conserved function of the composite enhancers, their architecture diverges. The crucial human sequences appear to be primate-specific. Through editing of primary human progenitors and mouse transgenesis, we validate the BCL11A erythroid enhancer as a target for fetal haemoglobin reinduction. The detailed enhancer map will inform therapeutic genome editing, and the screening approach described here is generally applicable to functional interrogation of non-coding genomic elements.

Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment

Accurate assessment of genetic variation in human DNA sequencing studies remains a nontrivial challenge in clinical genomics and genome informatics. Ascribing functional roles and/or clinical significances to single nucleotide variants identified from a next-generation sequencing study is an important step in genome interpretation. Experimental characterization of all the observed functional variants is yet impractical; thus, the prediction of functional and/or regulatory impacts of the various mutations using in silico approaches is an important step toward the identification of functionally significant or clinically actionable variants. The relationships between genotypes and the expressed phenotypes are multilayered and biologically complex; such relationships present numerous challenges and at the same time offer various opportunities for the design of in silico variant assessment strategies. Over the past decade, many bioinformatics algorithms have been developed to predict functional consequences of single nucleotide variants in the protein coding regions. In this review, we provide an overview of the bioinformatics resources for the prediction, annotation and visualization of coding single nucleotide variants. We discuss the currently available approaches and major challenges from the perspective of protein sequence, structure, function and interactions that require consideration when interpreting the impact of putatively functional variants. We also discuss the relevance of incorporating integrated workflows for predicting the biomedical impact of the functionally important variations encoded in a genome, exome or transcriptome. Finally, we propose a framework to classify variant assessment approaches and strategies for incorporation of variant assessment within electronic health records.

Multiple functional variants in long-range enhancer elements contribute to the risk of SNP rs965513 in thyroid cancer

The [A] allele of SNP rs965513 in 9q22 has been consistently shown to be highly associated with increased papillary thyroid cancer (PTC) risk with an odds ratio of ∼1.8 as determined by genome-wide association studies, yet the molecular mechanisms remain poorly understood. Previously, we noted that the expression of two genes in the region, forkhead box E1 (FOXE1) and PTC susceptibility candidate 2 (PTCSC2), is regulated by rs965513 in unaffected thyroid tissue, but the underlying mechanisms were not elucidated. Here, we fine-mapped the 9q22 region in PTC and controls and detected an ∼33-kb linkage disequilibrium block (containing the lead SNP rs965513) that significantly associates with PTC risk. Chromatin characteristics and regulatory element signatures in this block disclosed at least three regulatory elements functioning as enhancers. These enhancers harbor at least four SNPs (rs7864322, rs12352658, rs7847449, and rs10759944) that serve as functional variants. The variant genotypes are associated with differential enhancer activities and/or transcription factor binding activities. Using the chromosome conformation capture methodology, long-range looping interactions of these elements with the promoter region shared by FOXE1 and PTCSC2 in a human papillary thyroid carcinoma cell line (KTC-1) and unaffected thyroid tissue were found. Our results suggest that multiple variants coinherited with the lead SNP and located in long-range enhancers are involved in the transcriptional regulation of FOXE1 and PTCSC2 expression. These results explain the mechanism by which the risk allele of rs965513 predisposes to thyroid cancer.

Genetic variation at MECOM, TERT, JAK2 and HBS1L-MYB predisposes to myeloproliferative neoplasms

Clonal proliferation in myeloproliferative neoplasms (MPN) is driven by somatic mutations in JAK2, CALR or MPL, but the contribution of inherited factors is poorly characterized. Using a three-stage genome-wide association study of 3,437 MPN cases and 10,083 controls, we identify two SNPs with genome-wide significance in JAK2(V617F)-negative MPN: rs12339666 (JAK2; meta-analysis P=1.27 × 10(-10)) and rs2201862 (MECOM; meta-analysis P=1.96 × 10(-9)). Two additional SNPs, rs2736100 (TERT) and rs9376092 (HBS1L/MYB), achieve genome-wide significance when including JAK2(V617F)-positive cases. rs9376092 has a stronger effect in JAK2(V617F)-negative cases with CALR and/or MPL mutations (Breslow-Day P=4.5 × 10(-7)), whereas in JAK2(V617F)-positive cases rs9376092 associates with essential thrombocythemia (ET) rather than polycythemia vera (allelic χ(2) P=7.3 × 10(-7)). Reduced MYB expression, previously linked to development of an ET-like disease in model systems, associates with rs9376092 in normal myeloid cells. These findings demonstrate that multiple germline variants predispose to MPN and link constitutional differences in MYB expression to disease phenotype.

Identification of a regulatory variant that binds FOXA1 and FOXA2 at the CDC123/CAMK1D type 2 diabetes GWAS locus

Many of the type 2 diabetes loci identified through genome-wide association studies localize to non-protein-coding intronic and intergenic regions and likely contain variants that regulate gene transcription. The CDC123/CAMK1D type 2 diabetes association signal on chromosome 10 spans an intergenic region between CDC123 and CAMK1D and also overlaps the CDC123 3′UTR. To gain insight into the molecular mechanisms underlying the association signal, we used open chromatin, histone modifications and transcription factor ChIP-seq data sets from type 2 diabetes-relevant cell types to identify SNPs overlapping predicted regulatory regions. Two regions containing type 2 diabetes-associated variants were tested for enhancer activity using luciferase reporter assays. One SNP, rs11257655, displayed allelic differences in transcriptional enhancer activity in 832/13 and MIN6 insulinoma cells as well as in human HepG2 hepatocellular carcinoma cells. The rs11257655 risk allele T showed greater transcriptional activity than the non-risk allele C in all cell types tested. Using electromobility shift and supershift assays we demonstrated that the rs11257655 risk allele showed allele-specific binding to FOXA1 and FOXA2. We validated FOXA1 and FOXA2 enrichment at the rs11257655 risk allele using allele-specific ChIP in human islets. These results suggest that rs11257655 affects transcriptional activity through altered binding of a protein complex that includes FOXA1 and FOXA2, providing a potential molecular mechanism at this GWAS locus.

GWAS have identified more than 1200 loci contributing to risk of disease, including more than 70 loci associated with type 2 diabetes. With a majority of associated variants localized to non-coding regions of the genome, focus has moved to identifying the functional variants explaining the association signals. One mechanism by which variants may act is to affect activity of enhancer elements regulating target gene expression. In this study, we take advantage of recent advances in genome-wide annotation of human regulatory elements to prioritize candidate functional variants at the CDC123/CAMK1D locus. We identify two T2D-associated variants that overlap predicted regulatory enhancer elements. We demonstrate that one variant, rs11257655, shows allele-specific transcriptional enhancer activity in mammalian cell lines relevant to type 2 diabetes. We also show differential protein-DNA binding suggesting that the rs11257655 type 2 diabetes- risk allele increased transcriptional activity through binding a protein complex that includes FOXA1 and FOXA2. This study demonstrates that genome-wide maps of regulatory elements are a useful resource to guide identification of variants differentially affecting transcriptional activity and provides insight into molecular mechanisms underlying a T2D susceptibility locus.

From genome-wide association study hits to new insights into experimental hematology

Despite significant improvements in our knowledge of the mechanisms of normal and pathological hematopoiesis, our current understanding is most likely an oversimplification of the complexity of regulatory networks at play. Thus, considerable efforts have been made to catalogue the total sum of germline alterations in individual genomes affecting human hematopoiesis. These efforts ultimately led to the discovery of a large number of new genes not previously implicated in blood formation. Although identification of novel genes is important in revealing the profiles of genetic variations associated with normal hematopoiesis, further functional studies are necessary to improve our understanding of the mechanism(s) involved in these processes. In this review, we summarize the knowledge gained from genome-wide association studies to elucidate the relationship between genetics and blood cell traits. We discuss the most important recent advances, with an emphasis on functional follow-up studies that have been particularly useful in providing an insight into novel regulatory processes that influence blood cell formation and function. We also discuss potential future directions and challenges in the field.

A loss of function screen of identified genome-wide association study Loci reveals new genes controlling hematopoiesis

The formation of mature cells by blood stem cells is very well understood at the cellular level and we know many of the key transcription factors that control fate decisions. However, many upstream signalling and downstream effector processes are only partially understood. Genome wide association studies (GWAS) have been particularly useful in providing new directions to dissect these pathways. A GWAS meta-analysis identified 68 genetic loci controlling platelet size and number. Only a quarter of those genes, however, are known regulators of hematopoiesis. To determine function of the remaining genes we performed a medium-throughput genetic screen in zebrafish using antisense morpholino oligonucleotides (MOs) to knock down protein expression, followed by histological analysis of selected genes using a wide panel of different hematopoietic markers. The information generated by the initial knockdown was used to profile phenotypes and to position candidate genes hierarchically in hematopoiesis. Further analysis of brd3a revealed its essential role in differentiation but not maintenance and survival of thrombocytes. Using the from-GWAS-to-function strategy we have not only identified a series of genes that represent novel regulators of thrombopoiesis and hematopoiesis, but this work also represents, to our knowledge, the first example of a functional genetic screening strategy that is a critical step toward obtaining biologically relevant functional data from GWA study for blood cell traits.

Genomics meets proteomics: identifying the culprits in disease

Genome-wide association studies (GWAS) revealed genomic risk loci that potentially have an impact on disease and phenotypic traits. This extensive resource holds great promise in providing novel directions for personalized medicine, including disease risk prediction, prevention and targeted medication. One of the major challenges that researchers face on the path between the initial identification of an association and precision treatment of patients is the comprehension of the biological mechanisms that underlie these associations. Currently, the focus to solve these questions lies on the integrative analysis of system-wide data on global genome variation, gene expression, transcription factor binding, epigenetic profiles and chromatin conformation. The generation of this data mainly relies on next-generation sequencing. However, due to multiple recent developments, mass spectrometry-based proteomics now offers additional, by the GWAS field so far hardly recognized possibilities for the identification of functional genome variants and, in particular, for the identification and characterization of (differentially) bound protein complexes as well as physiological target genes. In this review, we introduce these proteomics advances and suggest how they might be integrated in post-GWAS workflows. We argue that the combination of highly complementary techniques is powerful and can provide an unbiased, detailed picture of GWAS loci and their mechanistic involvement in disease.

Joint analysis of functional genomic data and genome-wide association studies of 18 human traits

Annotations of gene structures and regulatory elements can inform genome-wide association studies (GWASs). However, choosing the relevant annotations for interpreting an association study of a given trait remains challenging. I describe a statistical model that uses association statistics computed across the genome to identify classes of genomic elements that are enriched with or depleted of loci influencing a trait. The model naturally incorporates multiple types of annotations. I applied the model to GWASs of 18 human traits, including red blood cell traits, platelet traits, glucose levels, lipid levels, height, body mass index, and Crohn disease. For each trait, I used the model to evaluate the relevance of 450 different genomic annotations, including protein-coding genes, enhancers, and DNase-I hypersensitive sites in over 100 tissues and cell lines. The fraction of phenotype-associated SNPs influencing protein sequence ranged from around 2% (for platelet volume) up to around 20% (for low-density lipoprotein cholesterol), repressed chromatin was significantly depleted for SNPs associated with several traits, and cell-type-specific DNase-I hypersensitive sites were enriched with SNPs associated with several traits (for example, the spleen in platelet volume). Finally, reweighting each GWAS by using information from functional genomics increased the number of loci with high-confidence associations by around 5%.

Functional interpretation of non-coding sequence variation: concepts and challenges

Understanding the functional mechanisms underlying genetic signals associated with complex traits and common diseases, such as cancer, diabetes and Alzheimer's disease, is a formidable challenge. Many genetic signals discovered through genome-wide association studies map to non-protein coding sequences, where their molecular consequences are difficult to evaluate. This article summarizes concepts for the systematic interpretation of non-coding genetic signals using genome annotation data sets in different cellular systems. We outline strategies for the global analysis of multiple association intervals and the in-depth molecular investigation of individual intervals. We highlight experimental techniques to validate candidate (potential causal) regulatory variants, with a focus on novel genome-editing techniques including CRISPR/Cas9. These approaches are also applicable to low-frequency and rare variants, which have become increasingly important in genomic studies of complex traits and diseases. There is a pressing need to translate genetic signals into biological mechanisms, leading to prognostic, diagnostic and therapeutic advances.

Systems biology of megakaryocytes

The molecular pathways that regulate megakaryocyte production have historically been identified through multiple candidate gene approaches. Several transcription factors critical for generating megakaryocytes were identified by promoter analysis of megakaryocyte-specific genes, and their biological roles then verified by gene knockout studies; for example, GATA-1, NF-E2, and RUNX1 were identified in this way. In contrast, other transcription factors important for megakaryopoiesis were discovered through a systems approach; for example, c-Myb was found to be critical for the erythroid versus megakaryocyte lineage decision by genome-wide loss-of-function studies. The regulation of the levels of these transcription factors is, for the most part, cell intrinsic, although that assumption has recently been challenged. Epigenetics also impacts megakaryocyte gene expression, mediated by histone acetylation and methylation. Several cytokines have been identified to regulate megakaryocyte survival, proliferation, and differentiation, most prominent of which is thrombopoietin. Upon binding to its receptor, the product of the c-Mpl proto-oncogene, thrombopoietin induces a conformational change that activates a number of secondary messengers that promote cell survival, proliferation, and differentiation, and down-modulate receptor signaling. Among the best studied are the signal transducers and activators of transcription (STAT) proteins; phosphoinositol-3-kinase; mitogen-activated protein kinases; the phosphatases PTEN, SHP1, SHP2, and SHIP1; and the suppressors of cytokine signaling (SOCS) proteins. Additional signals activated by these secondary mediators include mammalian target of rapamycin; β(beta)-catenin; the G proteins Rac1, Rho, and CDC42; several transcription factors, including hypoxia-inducible factor 1α(alpha), the homeobox-containing proteins HOXB4 and HOXA9, and a number of signaling mediators that are reduced, including glycogen synthase kinase 3α(alpha) and the FOXO3 family of forkhead proteins. More recently, systematic interrogation of several aspects of megakaryocyte formation have been conducted, employing genomics, proteomics, and chromatin immunoprecipitation (ChIP) analyses, among others, and have yielded many previously unappreciated signaling mechanisms that regulate megakaryocyte lineage determination, proliferation, and differentiation. This chapter focuses on these pathways in normal and neoplastic megakaryopoiesis, and suggests areas that are ripe for further study.

A genome- and phenome-wide association study to identify genetic variants influencing platelet count and volume and their pleiotropic effects

Platelets are enucleated cell fragments derived from megakaryocytes that play key roles in hemostasis and in the pathogenesis of atherothrombosis and cancer. Platelet traits are highly heritable and identification of genetic variants associated with platelet traits and assessing their pleiotropic effects may help to understand the role of underlying biological pathways. We conducted an electronic medical record (EMR)-based study to identify common variants that influence inter-individual variation in the number of circulating platelets (PLT) and mean platelet volume (MPV), by performing a genome-wide association study (GWAS). We characterized genetic variants associated with MPV and PLT using functional, pathway and disease enrichment analyses; we assessed pleiotropic effects of such variants by performing a phenome-wide association study (PheWAS) with a wide range of EMR-derived phenotypes. A total of 13,582 participants in the electronic MEdical Records and GEnomic network had data for PLT and 6,291 participants had data for MPV. We identified five chromosomal regions associated with PLT and eight associated with MPV at genome-wide significance (P < 5E-8). In addition, we replicated 20 SNPs [out of 56 SNPs (α: 0.05/56 = 9E-4)] influencing PLT and 22 SNPs [out of 29 SNPs (α: 0.05/29 = 2E-3)] influencing MPV in a published meta-analysis of GWAS of PLT and MPV. While our GWAS did not find any new associations, our functional analyses revealed that genes in these regions influence thrombopoiesis and encode kinases, membrane proteins, proteins involved in cellular trafficking, transcription factors, proteasome complex subunits, proteins of signal transduction pathways, proteins involved in megakaryocyte development, and platelet production and hemostasis. PheWAS using a single-SNP Bonferroni correction for 1,368 diagnoses (0.05/1368 = 3.6E-5) revealed that several variants in these genes have pleiotropic associations with myocardial infarction, autoimmune, and hematologic disorders. We conclude that multiple genetic loci influence interindividual variation in platelet traits and also have significant pleiotropic effects; the related genes are in multiple functional pathways including those relevant to thrombopoiesis.

Detection of regulatory SNPs in human genome using ChIP-seq ENCODE data

A vast amount of SNPs derived from genome-wide association studies are represented by non-coding ones, therefore exacerbating the need for effective identification of regulatory SNPs (rSNPs) among them. However, this task remains challenging since the regulatory part of the human genome is annotated much poorly as opposed to coding regions. Here we describe an approach aggregating the whole set of ENCODE ChIP-seq data in order to search for rSNPs, and provide the experimental evidence of its efficiency. Its algorithm is based on the assumption that the enrichment of a genomic region with transcription factor binding loci (ChIP-seq peaks) indicates its regulatory function, and thereby SNPs located in this region are more likely to influence transcription regulation. To ensure that the approach preferably selects functionally meaningful SNPs, we performed enrichment analysis of several human SNP datasets associated with phenotypic manifestations. It was shown that all samples are significantly enriched with SNPs falling into the regions of multiple ChIP-seq peaks as compared with the randomly selected SNPs. For experimental verification, 40 SNPs falling into overlapping regions of at least 7 TF binding loci were selected from OMIM. The effect of SNPs on the binding of the DNA fragments containing them to the nuclear proteins from four human cell lines (HepG2, HeLaS3, HCT-116, and K562) has been tested by EMSA. A radical change in the binding pattern has been observed for 29 SNPs, besides, 6 more SNPs also demonstrated less pronounced changes. Taken together, the results demonstrate the effective way to search for potential rSNPs with the aid of ChIP-seq data provided by ENCODE project.

An erythroid enhancer of BCL11A subject to genetic variation determines fetal hemoglobin level

Genome-wide association studies (GWASs) have ascertained numerous trait-associated common genetic variants, frequently localized to regulatory DNA. We found that common genetic variation at BCL11A associated with fetal hemoglobin (HbF) level lies in noncoding sequences decorated by an erythroid enhancer chromatin signature. Fine-mapping uncovers a motif-disrupting common variant associated with reduced transcription factor (TF) binding, modestly diminished BCL11A expression, and elevated HbF. The surrounding sequences function in vivo as a developmental stage-specific, lineage-restricted enhancer. Genome engineering reveals the enhancer is required in erythroid but not B-lymphoid cells for BCL11A expression. These findings illustrate how GWASs may expose functional variants of modest impact within causal elements essential for appropriate gene expression. We propose the GWAS-marked BCL11A enhancer represents an attractive target for therapeutic genome engineering for the β-hemoglobinopathies.

Allele-specific transcriptional activity at type 2 diabetes-associated single nucleotide polymorphisms in regions of pancreatic islet open chromatin at the JAZF1 locus

Translation of noncoding common variant association signals into meaningful molecular and biological mechanisms explaining disease susceptibility remains challenging. For the type 2 diabetes association signal in JAZF1 intron 1, we hypothesized that the underlying risk variants have cis-regulatory effects in islets or other type 2 diabetes-relevant cell types. We used maps of experimentally predicted open chromatin regions to prioritize variants for functional follow-up studies of transcriptional activity. Twelve regions containing type 2 diabetes-associated variants were tested for enhancer activity in 832/13 and MIN6 insulinoma cells. Three regions exhibited enhancer activity and only rs1635852 displayed allelic differences in enhancer activity; the type 2 diabetes risk allele T showed lower transcriptional activity than the nonrisk allele C. This risk allele showed increased binding to protein complexes, suggesting that it functions as part of a transcriptional repressor complex. We applied DNA affinity capture to identify factors in the complex and determined that the risk allele preferentially binds the pancreatic master regulator PDX1. These data suggest that the rs1635852 region in JAZF1 intron 1 is part of a cis-regulatory complex and that maps of open chromatin are useful to guide identification of variants with allelic differences in regulatory activity at type 2 diabetes loci.

Maps of open chromatin highlight cell type-restricted patterns of regulatory sequence variation at hematological trait loci

Nearly three-quarters of the 143 genetic signals associated with platelet and erythrocyte phenotypes identified by meta-analyses of genome-wide association (GWA) studies are located at non-protein-coding regions. Here, we assessed the role of candidate regulatory variants associated with cell type–restricted, closely related hematological quantitative traits in biologically relevant hematopoietic cell types. We used formaldehyde-assisted isolation of regulatory elements followed by next-generation sequencing (FAIRE-seq) to map regions of open chromatin in three primary human blood cells of the myeloid lineage. In the precursors of platelets and erythrocytes, as well as in monocytes, we found that open chromatin signatures reflect the corresponding hematopoietic lineages of the studied cell types and associate with the cell type–specific gene expression patterns. Dependent on their signal strength, open chromatin regions showed correlation with promoter and enhancer histone marks, distance to the transcription start site, and ontology classes of nearby genes. Cell type–restricted regions of open chromatin were enriched in sequence variants associated with hematological indices. The majority (63.6%) of such candidate functional variants at platelet quantitative trait loci (QTLs) coincided with binding sites of five transcription factors key in regulating megakaryopoiesis. We experimentally tested 13 candidate regulatory variants at 10 platelet QTLs and found that 10 (76.9%) affected protein binding, suggesting that this is a frequent mechanism by which regulatory variants influence quantitative trait levels. Our findings demonstrate that combining large-scale GWA data with open chromatin profiles of relevant cell types can be a powerful means of dissecting the genetic architecture of closely related quantitative traits.

Genome-wide association studies of hematologic phenotypes: a window into human hematopoiesis

The study of human hematopoiesis is often limited by the inability to manipulate this process in vivo and differences that exist between humans and commonly employed model organisms. However, human genetics provides a way to gain insight into natural variation in a variety of hematologic phenotypes and creates an opportunity to better understand hematopoiesis. In this review, we discuss how genome-wide association studies are revealing common genetic variation that is associated with hematologic traits and diseases. We discuss how the resulting insight from these studies promises to increase our understanding of human hematopoiesis and outline the challenges that lay ahead in this field.

Linking disease associations with regulatory information in the human genome

Genome-wide association studies have been successful in identifying single nucleotide polymorphisms (SNPs) associated with a large number of phenotypes. However, an associated SNP is likely part of a larger region of linkage disequilibrium. This makes it difficult to precisely identify the SNPs that have a biological link with the phenotype. We have systematically investigated the association of multiple types of ENCODE data with disease-associated SNPs and show that there is significant enrichment for functional SNPs among the currently identified associations. This enrichment is strongest when integrating multiple sources of functional information and when highest confidence disease-associated SNPs are used. We propose an approach that integrates multiple types of functional data generated by the ENCODE Consortium to help identify “functional SNPs” that may be associated with the disease phenotype. Our approach generates putative functional annotations for up to 80% of all previously reported associations. We show that for most associations, the functional SNP most strongly supported by experimental evidence is a SNP in linkage disequilibrium with the reported association rather than the reported SNP itself. Our results show that the experimental data sets generated by the ENCODE Consortium can be successfully used to suggest functional hypotheses for variants associated with diseases and other phenotypes.

Seventy-five genetic loci influencing the human red blood cell

Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

A GWAS sequence variant for platelet volume marks an alternative DNM3 promoter in megakaryocytes near a MEIS1 binding site

We recently identified 68 genomic loci where common sequence variants are associated with platelet count and volume. Platelets are formed in the bone marrow by megakaryocytes, which are derived from hematopoietic stem cells by a process mainly controlled by transcription factors. The homeobox transcription factor MEIS1 is uniquely transcribed in megakaryocytes and not in the other lineage-committed blood cells. By ChIP-seq, we show that 5 of the 68 loci pinpoint a MEIS1 binding event within a group of 252 MK-overexpressed genes. In one such locus in DNM3, regulating platelet volume, the MEIS1 binding site falls within a region acting as an alternative promoter that is solely used in megakaryocytes, where allelic variation dictates different levels of a shorter transcript. The importance of dynamin activity to the latter stages of thrombopoiesis was confirmed by the observation that the inhibitor Dynasore reduced murine proplatelet for-mation in vitro.

Compound inheritance of a low-frequency regulatory SNP and a rare null mutation in exon-junction complex subunit RBM8A causes TAR syndrome

The exon-junction complex (EJC) performs essential RNA processing tasks. Here, we describe the first human disorder, thrombocytopenia with absent radii (TAR), caused by deficiency in one of the four EJC subunits. Compound inheritance of a rare null allele and one of two low-frequency SNPs in the regulatory regions of RBM8A, encoding the Y14 subunit of EJC, causes TAR. We found that this inheritance mechanism explained 53 of 55 cases (P < 5 × 10(-228)) of the rare congenital malformation syndrome. Of the 53 cases with this inheritance pattern, 51 carried a submicroscopic deletion of 1q21.1 that has previously been associated with TAR, and two carried a truncation or frameshift null mutation in RBM8A. We show that the two regulatory SNPs result in diminished RBM8A transcription in vitro and that Y14 expression is reduced in platelets from individuals with TAR. Our data implicate Y14 insufficiency and, presumably, an EJC defect as the cause of TAR syndrome.

New gene functions in megakaryopoiesis and platelet formation

Platelets are the second most abundant cell type in blood and are essential for maintaining haemostasis. Their count and volume are tightly controlled within narrow physiological ranges, but there is only limited understanding of the molecular processes controlling both traits. Here we carried out a high-powered meta-analysis of genome-wide association studies (GWAS) in up to 66,867 individuals of European ancestry, followed by extensive biological and functional assessment. We identified 68 genomic loci reliably associated with platelet count and volume mapping to established and putative novel regulators of megakaryopoiesis and platelet formation. These genes show megakaryocyte-specific gene expression patterns and extensive network connectivity. Using gene silencing in Danio rerio and Drosophila melanogaster, we identified 11 of the genes as novel regulators of blood cell formation. Taken together, our findings advance understanding of novel gene functions controlling fate-determining events during megakaryopoiesis and platelet formation, providing a new example of successful translation of GWAS to function.