Hematopoietic stem cells give rise to all blood cells in a differentiation process that involves widespread epigenome remodeling. Here we present genome-wide reference maps of the associated DNA ...methylation dynamics. We used a meta-epigenomic approach that combines DNA methylation profiles across many small pools of cells and performed single-cell methylome sequencing to assess cell-to-cell heterogeneity. The resulting dataset identified characteristic differences between HSCs derived from fetal liver, cord blood, bone marrow, and peripheral blood. We also observed lineage-specific DNA methylation between myeloid and lymphoid progenitors, characterized immature multi-lymphoid progenitors, and detected progressive DNA methylation differences in maturing megakaryocytes. We linked these patterns to gene expression, histone modifications, and chromatin accessibility, and we used machine learning to derive a model of human hematopoietic differentiation directly from DNA methylation data. Our results contribute to a better understanding of human hematopoietic stem cell differentiation and provide a framework for studying blood-linked diseases.
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•Sequencing provides DNA methylation maps of hematopoietic stem and progenitor cells•Methylation differs in HSCs from fetal liver, bone marrow, cord, and peripheral blood•Myeloid and lymphoid progenitors are distinguished by enhancer-linked DNA methylation•Machine learning enables data-driven reconstruction of the hematopoietic lineage
As part of the IHEC consortium, Bock and colleagues present genome-wide reference maps of DNA methylation dynamics during human blood development. The characteristic DNA methylation patterns they see in the different cell types allow data-driven inference of an epigenome-based model of hematopoietic differentiation. Explore the IHEC web portal at http://www.cell.com/consortium/IHEC.
Variations in platelet number, volume, and function are largely genetically controlled, and many loci associated with platelet traits have been identified by genome-wide association studies (GWASs).1 ...The genome also contains a large number of rare variants, of which a tiny fraction underlies the inherited diseases of humans. Research over the last 3 decades has led to the discovery of 51 genes harboring variants responsible for inherited platelet disorders (IPDs). However, the majority of patients with an IPD still do not receive a molecular diagnosis. Alongside the scientific interest, molecular or genetic diagnosis is important for patients. There is increasing recognition that a number of IPDs are associated with severe pathologies, including an increased risk of malignancy, and a definitive diagnosis can inform prognosis and care. In this review, we give an overview of these disorders grouped according to their effect on platelet biology and their clinical characteristics. We also discuss the challenge of identifying candidate genes and causal variants therein, how IPDs have been historically diagnosed, and how this is changing with the introduction of high-throughput sequencing. Finally, we describe how integration of large genomic, epigenomic, and phenotypic datasets, including whole genome sequencing data, GWASs, epigenomic profiling, protein–protein interaction networks, and standardized clinical phenotype coding, will drive the discovery of novel mechanisms of disease in the near future to improve patient diagnosis and management.
Small insertions and deletions (indels) are a common and functionally important type of sequence polymorphism. Most of the focus of studies of sequence variation is on single nucleotide variants ...(SNVs) and large structural variants. In principle, high-throughput sequencing studies should allow identification of indels just as SNVs. However, inference of indels from next-generation sequence data is challenging, and so far methods for identifying indels lag behind methods for calling SNVs in terms of sensitivity and specificity. We propose a Bayesian method to call indels from short-read sequence data in individuals and populations by realigning reads to candidate haplotypes that represent alternative sequence to the reference. The candidate haplotypes are formed by combining candidate indels and SNVs identified by the read mapper, while allowing for known sequence variants or candidates from other methods to be included. In our probabilistic realignment model we account for base-calling errors, mapping errors, and also, importantly, for increased sequencing error indel rates in long homopolymer runs. We show that our method is sensitive and achieves low false discovery rates on simulated and real data sets, although challenges remain. The algorithm is implemented in the program Dindel, which has been used in the 1000 Genomes Project call sets.
The production of megakaryocytes (MKs)--the precursors of blood platelets--from human pluripotent stem cells (hPSCs) offers exciting clinical opportunities for transfusion medicine. Here we describe ...an original approach for the large-scale generation of MKs in chemically defined conditions using a forward programming strategy relying on the concurrent exogenous expression of three transcription factors: GATA1, FLI1 and TAL1. The forward programmed MKs proliferate and differentiate in culture for several months with MK purity over 90% reaching up to 2 × 10(5) mature MKs per input hPSC. Functional platelets are generated throughout the culture allowing the prospective collection of several transfusion units from as few as 1 million starting hPSCs. The high cell purity and yield achieved by MK forward programming, combined with efficient cryopreservation and good manufacturing practice (GMP)-compatible culture, make this approach eminently suitable to both in vitro production of platelets for transfusion and basic research in MK and platelet biology.
Combinatorial transcription factor (TF) interactions control cellular phenotypes and, therefore, underpin stem cell formation, maintenance, and differentiation. Here, we report the genome-wide ...binding patterns and combinatorial interactions for ten key regulators of blood stem/progenitor cells (SCL/TAL1, LYL1, LMO2, GATA2, RUNX1, MEIS1, PU.1, ERG, FLI-1, and GFI1B), thus providing the most comprehensive TF data set for any adult stem/progenitor cell type to date. Genome-wide computational analysis of complex binding patterns, followed by functional validation, revealed the following: first, a previously unrecognized combinatorial interaction between a heptad of TFs (SCL, LYL1, LMO2, GATA2, RUNX1, ERG, and FLI-1). Second, we implicate direct protein-protein interactions between four key regulators (RUNX1, GATA2, SCL, and ERG) in stabilizing complex binding to DNA. Third,
Runx1
+/−
::
Gata2
+/−
compound heterozygous mice are not viable with severe hematopoietic defects at midgestation. Taken together, this study demonstrates the power of genome-wide analysis in generating novel functional insights into the transcriptional control of stem and progenitor cells.
► Genome-wide maps for 10 blood stem/progenitor transcriptional regulators ► New bioinformatic analysis pipeline to study combinatorial transcriptional control ► Identification of protein interactions between key blood stem cell regulators ► Genetic interaction between
Runx1 and
Gata2
In combination with microspotting, whole-blood microfluidics can provide high-throughput information on multiple platelet functions in thrombus formation. Based on assessment of the inter- and ...intra-subject variability in parameters of microspot-based thrombus formation, we aimed to determine the platelet factors contributing to this variation. Blood samples from 94 genotyped healthy subjects were analyzed for conventional platelet phenotyping: i.e. hematologic parameters, platelet glycoprotein (GP) expression levels and activation markers (24 parameters). Furthermore, platelets were activated by ADP, CRP-XL or TRAP. Parallel samples were investigated for whole-blood thrombus formation (6 microspots, providing 48 parameters of adhesion, aggregation and activation). Microspots triggered platelet activation through GP Ib-V-IX, GPVI, CLEC-2 and integrins. For most thrombus parameters, inter-subject variation was 2-4 times higher than the intra-subject variation. Principal component analyses indicated coherence between the majority of parameters for the GPVI-dependent microspots, partly linked to hematologic parameters, and glycoprotein expression levels. Prediction models identified parameters per microspot that were linked to variation in agonist-induced α
β
activation and secretion. Common sequence variation of
and
, associated with GPVI-induced α
β
activation and secretion, affected parameters of GPVI-and CLEC-2-dependent thrombus formation. Subsequent analysis of blood samples from patients with Glanzmann thrombasthenia or storage pool disease revealed thrombus signatures of aggregation-dependent parameters that were subject-dependent, but not linked to GPVI activity. Taken together, this high-throughput elucidation of thrombus formation revealed patterns of inter-subject differences in platelet function, which were partly related to GPVI-induced activation and common genetic variance linked to GPVI, but also included a distinct platelet aggregation component.
Genomic atlas of the human plasma proteome Sun, Benjamin B; Maranville, Joseph C; Peters, James E ...
Nature (London),
06/2018, Letnik:
558, Številka:
7708
Journal Article
Recenzirano
Odprti dostop
Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels ...are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.
Telomeres, the end fragments of chromosomes, play key roles in cellular proliferation and senescence. Here we characterize the genetic architecture of naturally occurring variation in leukocyte ...telomere length (LTL) and identify causal links between LTL and biomedical phenotypes in 472,174 well-characterized UK Biobank participants. We identified 197 independent sentinel variants associated with LTL at 138 genomic loci (108 new). Genetically determined differences in LTL were associated with multiple biological traits, ranging from height to bone marrow function, as well as several diseases spanning neoplastic, vascular and inflammatory pathologies. Finally, we estimated that, at the age of 40 years, people with an LTL >1 s.d. shorter than the population mean had a 2.5-year-lower life expectancy compared with the group with ≥1 s.d. longer LDL. Overall, we furnish new insights into the genetic regulation of LTL, reveal wide-ranging influences of LTL on physiological traits, diseases and longevity, and provide a powerful resource available to the global research community.
Stroke is the second leading cause of death with substantial unmet therapeutic needs. To identify potential stroke therapeutic targets, we estimate the causal effects of 308 plasma proteins on stroke ...outcomes in a two-sample Mendelian randomization framework and assess mediation effects by stroke risk factors. We find associations between genetically predicted plasma levels of six proteins and stroke (P ≤ 1.62 × 10
). The genetic associations with stroke colocalize (Posterior Probability >0.7) with the genetic associations of four proteins (TFPI, TMPRSS5, CD6, CD40). Mendelian randomization supports atrial fibrillation, body mass index, smoking, blood pressure, white matter hyperintensities and type 2 diabetes as stroke risk factors (P ≤ 0.0071). Body mass index, white matter hyperintensity and atrial fibrillation appear to mediate the TFPI, IL6RA, TMPRSS5 associations with stroke. Furthermore, thirty-six proteins are associated with one or more of these risk factors using Mendelian randomization. Our results highlight causal pathways and potential therapeutic targets for stroke.
Thrombosis and platelet activation play a central role in stroke pathogenesis, and antiplatelet and anticoagulant therapies are central to stroke prevention. However, whether haematological traits ...contribute equally to all ischaemic stroke subtypes is uncertain. Furthermore, identification of associations with new traits may offer novel treatment opportunities. The aim of this research was to ascertain causal relationships between a wide range of haematological traits and ischaemic stroke and its subtypes. We obtained summary statistics from 27 published genome-wide association studies of haematological traits involving over 375 000 individuals, and genetic associations with stroke from the MEGASTROKE Consortium (n = 67 000 stroke cases). Using two-sample Mendelian randomization we analysed the association of genetically elevated levels of 36 blood cell traits (platelets, mature/immature red cells, and myeloid/lymphoid/compound white cells) and 49 haemostasis traits (including clotting cascade factors and markers of platelet function) with risk of developing ischaemic (AIS), cardioembolic (CES), large artery (LAS), and small vessel stroke (SVS). Several factors on the intrinsic clotting pathway were significantly associated (P < 3.85 × 10-4) with CES and LAS, but not with SVS (e.g. reduced factor VIII activity with AIS/CES/LAS; raised factor VIII antigen with AIS/CES; and increased factor XI activity with AIS/CES). On the common pathway, increased gamma (γ') fibrinogen was significantly associated with AIS/CES. Furthermore, elevated plateletcrit was significantly associated with AIS/CES, eosinophil percentage of white cells with LAS, and thrombin-activatable fibrinolysis inhibitor activation peptide antigen with AIS. We also conducted a follow-up analysis in UK Biobank, which showed that amongst individuals with atrial fibrillation, those with genetically lower levels of factor XI are at reduced risk of AIS compared to those with normal levels of factor XI. These results implicate components of the intrinsic and common pathways of the clotting cascade, as well as several other haematological traits, in the pathogenesis of CES and possibly LAS, but not SVS. The lack of associations with SVS suggests thrombosis may be less important for this stroke subtype. Plateletcrit and factor XI are potentially tractable new targets for secondary prevention of ischaemic stroke, while factor VIII and γ' fibrinogen require further population-based studies to ascertain their possible aetiological roles.
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