Abstract
We report genome-wide association study results for the levels of A1, A2 and fetal hemoglobins, analyzed for the first time concurrently. Integrating high-density array genotyping and whole-genome sequencing in a large general population cohort from Sardinia, we detected 23 associations at 10 loci. Five signals are due to variants at previously undetected loci: MPHOSPH9, PLTP-PCIF1, ZFPM1 (FOG1), NFIX and CCND3. Among the signals at known loci, ten are new lead variants and four are new independent signals. Half of all variants also showed pleiotropic associations with different hemoglobins, which further corroborated some of the detected associations and identified features of coordinated hemoglobin species production.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Accession codes
References
Sankaran, V.G., Xu, J. & Orkin, S.H. Advances in the understanding of haemoglobin switching. Br. J. Haematol. 149, 181–194 (2010).
Modell, B. & Darlison, M. Global epidemiology of haemoglobin disorders and derived service indicators. Bull. World Health Organ. 86, 480–487 (2008).
Malaria Genomic Epidemiology Network. Reappraisal of known malaria resistance loci in a large multicenter study. Nat. Genet. 46, 1197–1204 (2014).
Pilia, G. et al. Heritability of cardiovascular and personality traits in 6,148 Sardinians. PLoS Genet. 2, e132 (2006).
Menzel, S., Garner, C., Rooks, H., Spector, T.D. & Thein, S.L. HbA2 levels in normal adults are influenced by two distinct genetic mechanisms. Br. J. Haematol. 160, 101–105 (2013).
Bae, H.T. et al. Meta-analysis of 2040 sickle cell anemia patients: BCL11A and HBS1L-MYB are the major modifiers of HbF in African Americans. Blood 120, 1961–1962 (2012).
Uda, M. et al. Genome-wide association study shows BCL11A associated with persistent fetal hemoglobin and amelioration of the phenotype of β-thalassemia. Proc. Natl. Acad. Sci. USA 105, 1620–1625 (2008).
Lettre, G. et al. DNA polymorphisms at the BCL11A, HBS1L-MYB, and β-globin loci associate with fetal hemoglobin levels and pain crises in sickle cell disease. Proc. Natl. Acad. Sci. USA 105, 11869–11874 (2008).
Danjou, F. et al. Genetic modifiers of β-thalassemia and clinical severity as assessed by age at first transfusion. Haematologica 97, 989–993 (2012).
Danjou, F. et al. A genetic score for the prediction of β-thalassemia severity. Haematologica 100, 452–457 (2015).
van der Harst, P. et al. Seventy-five genetic loci influencing the human red blood cell. Nature 492, 369–375 (2012).
Trecartin, R.F. et al. Beta zero thalassemia in Sardinia is caused by a nonsense mutation. J. Clin. Invest. 68, 1012–1017 (1981).
Sidore, C. et al. Genome sequencing elucidates Sardinian genetic architecture and augments association analyses for lipid and blood inflammatory markers. Nat. Genet. doi: 10.1038/ng.3368 (14 September 2015).
Kircher, M. et al. A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. 46, 310–315 (2014).
Freson, K. et al. Molecular cloning and characterization of the GATA1 cofactor human FOG1 and assessment of its binding to GATA1 proteins carrying D218 substitutions. Hum. Genet. 112, 42–49 (2003).
Nichols, K.E. et al. Familial dyserythropoietic anaemia and thrombocytopenia due to an inherited mutation in GATA1. Nat. Genet. 24, 266–270 (2000).
Kozar, K. et al. Mouse development and cell proliferation in the absence of D-cyclins. Cell 118, 477–491 (2004).
Sankaran, V.G. et al. Cyclin D3 coordinates the cell cycle during differentiation to regulate erythrocyte size and number. Genes Dev. 26, 2075–2087 (2012).
Soranzo, N. et al. A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium. Nat. Genet. 41, 1182–1190 (2009).
Kamatani, Y. et al. Genome-wide association study of hematological and biochemical traits in a Japanese population. Nat. Genet. 42, 210–215 (2010).
Kathiresan, S. et al. Common variants at 30 loci contribute to polygenic dyslipidemia. Nat. Genet. 41, 56–65 (2009).
Jarvik, G.P. et al. Genetic and nongenetic sources of variation in phospholipid transfer protein activity. J. Lipid Res. 51, 983–990 (2010).
Lettre, G. et al. Genome-wide association study of coronary heart disease and its risk factors in 8,090 African Americans: the NHLBI CARe Project. PLoS Genet. 7, e1001300 (2011).
Kettunen, J. et al. Genome-wide association study identifies multiple loci influencing human serum metabolite levels. Nat. Genet. 44, 269–276 (2012).
Hirose, Y. et al. Human phosphorylated CTD–interacting protein, PCIF1, negatively modulates gene expression by RNA polymerase II. Biochem. Biophys. Res. Commun. 369, 449–455 (2008).
Lessard, S., Beaudoin, M., Benkirane, K. & Lettre, G. Comparison of DNA methylation profiles in human fetal and adult red blood cell progenitors. Genome Med. 7, 1 (2015).
Riddell, J. et al. Reprogramming committed murine blood cells to induced hematopoietic stem cells with defined factors. Cell 157, 549–564 (2014).
Holmfeldt, P. et al. Nfix is a novel regulator of murine hematopoietic stem and progenitor cell survival. Blood 122, 2987–2996 (2013).
Kawane, K. et al. Requirement of DNase II for definitive erythropoiesis in the mouse fetal liver. Science 292, 1546–1549 (2001).
Porcu, S. et al. Klf1 affects DNase IIα expression in the central macrophage of a fetal liver erythroblastic island: a non-cell-autonomous role in definitive erythropoiesis. Mol. Cell. Biol. 31, 4144–4154 (2011).
Zhou, D., Liu, K., Sun, C.-W., Pawlik, K.M. & Townes, T.M. KLF1 regulates BCL11A expression and γ- to β-globin gene switching. Nat. Genet. 42, 742–744 (2010).
Siatecka, M. & Bieker, J.J. The multifunctional role of EKLF/KLF1 during erythropoiesis. Blood 118, 2044–2054 (2011).
Satta, S. et al. Compound heterozygosity for KLF1 mutations associated with remarkable increase of fetal hemoglobin and red cell protoporphyrin. Haematologica 96, 767–770 (2011).
Borg, J. et al. Haploinsufficiency for the erythroid transcription factor KLF1 causes hereditary persistence of fetal hemoglobin. Nat. Genet. 42, 801–805 (2010).
Perseu, L. et al. KLF1 gene mutations cause borderline HbA2. Blood 118, 4454–4458 (2011).
1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65 (2012).
Su, A.I. et al. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc. Natl. Acad. Sci. USA 101, 6062–6067 (2004).
Ashburner, M. et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25–29 (2000).
Raychaudhuri, S. et al. Identifying relationships among genomic disease regions: predicting genes at pathogenic SNP associations and rare deletions. PLoS Genet. 5, e1000534 (2009).
Andrews, N.C. The NF-E2 transcription factor. Int. J. Biochem. Cell Biol. 30, 429–432 (1998).
Hoogewijs, D. et al. Androglobin: a chimeric globin in metazoans that is preferentially expressed in Mammalian testes. Mol. Biol. Evol. 29, 1105–1114 (2012).
Iolascon, A., Perrotta, S. & Stewart, G.W. Red blood cell membrane defects. Rev. Clin. Exp. Hematol. 7, 22–56 (2003).
Moayyeri, A., Hammond, C.J., Valdes, A.M. & Spector, T.D. Cohort profile: TwinsUK and Healthy Ageing Twin Study. Int. J. Epidemiol. 42, 76–85 (2013).
Sangerman, J. et al. Mechanism for fetal hemoglobin induction by histone deacetylase inhibitors involves γ-globin activation by CREB1 and ATF-2. Blood 108, 3590–3599 (2006).
Goh, S.-H. et al. A newly discovered human α-globin gene. Blood 106, 1466–1472 (2005).
Farrell, J.J. et al. A 3-bp deletion in the HBS1L-MYB intergenic region on chromosome 6q23 is associated with HbF expression. Blood 117, 4935–4945 (2011).
Stadhouders, R. et al. HBS1L-MYB intergenic variants modulate fetal hemoglobin via long-range MYB enhancers. J. Clin. Invest. 124, 1699–1710 (2014).
Zeller, T. et al. Genetics and beyond—the transcriptome of human monocytes and disease susceptibility. PLoS ONE 5, e10693 (2010).
Bhatnagar, P. et al. Genome-wide association study identifies genetic variants influencing F-cell levels in sickle-cell patients. J. Hum. Genet. 56, 316–323 (2011).
Bauer, D.E. & Orkin, S.H. Update on fetal hemoglobin gene regulation in hemoglobinopathies. Curr. Opin. Pediatr. 23, 1–8 (2011).
Bauer, D.E. et al. An erythroid enhancer of BCL11A subject to genetic variation determines fetal hemoglobin level. Science 342, 253–257 (2013).
Grundberg, E. et al. Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements. Am. J. Hum. Genet. 93, 876–890 (2013).
Karolchik, D. et al. The UCSC Genome Browser database: 2014 update. Nucleic Acids Res. 42, D764–D770 (2014).
Rosenbloom, K.R. et al. ENCODE data in the UCSC Genome Browser: year 5 update. Nucleic Acids Res. 41, D56–D63 (2013).
Steinberg, M.H. & Adams, J.G. Hemoglobin A2: origin, evolution, and aftermath. Blood 78, 2165–2177 (1991).
Pistis, G. et al. Rare variant genotype imputation with thousands of study-specific whole-genome sequences: implications for cost-effective study designs. Eur. J. Hum. Genet. 23, 975–983 (2015).
Goldstein, J.I. et al. zCall: a rare variant caller for array-based genotyping: genetics and population analysis. Bioinformatics 28, 2543–2545 (2012).
Li, Y., Willer, C.J., Ding, J., Scheet, P. & Abecasis, G.R. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet. Epidemiol. 34, 816–834 (2010).
Howie, B., Fuchsberger, C., Stephens, M., Marchini, J. & Abecasis, G.R. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat. Genet. 44, 955–959 (2012).
Kang, H.M. et al. Variance component model to account for sample structure in genome-wide association studies. Nat. Genet. 42, 348–354 (2010).
Abecasis, G.R., Cherny, S.S., Cookson, W.O. & Cardon, L.R. Merlin—rapid analysis of dense genetic maps using sparse gene flow trees. Nat. Genet. 30, 97–101 (2002).
R Core Development Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013).
Origa, R. et al. Complexity of the α-globin genotypes identified with thalassemia screening in Sardinia. Blood Cells Mol. Dis. 52, 46–49 (2014).
Naitza, S. et al. A genome-wide association scan on the levels of markers of inflammation in Sardinians reveals associations that underpin its complex regulation. PLoS Genet. 8, e1002480 (2012).
Howie, B.N., Donnelly, P. & Marchini, J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529 (2009).
Menzel, S. et al. A QTL influencing F cell production maps to a gene encoding a zinc-finger protein on chromosome 2p15. Nat. Genet. 39, 1197–1199 (2007).
Myers, A.J. et al. A survey of genetic human cortical gene expression. Nat. Genet. 39, 1494–1499 (2007).
Stranger, B.E. et al. Population genomics of human gene expression. Nat. Genet. 39, 1217–1224 (2007).
Veyrieras, J.-B. et al. High-resolution mapping of expression-QTLs yields insight into human gene regulation. PLoS Genet. 4, e1000214 (2008).
Dimas, A.S. et al. Common regulatory variation impacts gene expression in a cell type–dependent manner. Science 325, 1246–1250 (2009).
Pickrell, J.K. et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464, 768–772 (2010).
Fehrmann, R.S.N. Trans-eQTLs reveal that independent genetic variants associated with a complex phenotype converge on intermediate genes, with a major role for the HLA. PLoS Genet. 7, e1002197 (2011).
Innocenti, F. et al. Identification, replication, and functional fine-mapping of expression quantitative trait loci in primary human liver tissue. PLoS Genet. 7, e1002078 (2011).
Montgomery, S.B., Lappalainen, T., Gutierrez-Arcelus, M. & Dermitzakis, E.T. Rare and common regulatory variation in population-scale sequenced human genomes. PLoS Genet. 7, e1002144 (2011).
Degner, J.F. et al. DNaseI sensitivity QTLs are a major determinant of human expression variation. Nature 482, 390–394 (2012).
Gaffney, D.J. et al. Dissecting the regulatory architecture of gene expression QTLs. Genome Biol. 13, R7 (2012).
Wright, F.A., Shabalin, A.A. & Rusyn, I. Computational tools for discovery and interpretation of expression quantitative trait loci. Pharmacogenomics 13, 343–352 (2012).
Lappalainen, T. et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501, 506–511 (2013).
Westra, H.-J. et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 45, 1238–1243 (2013).
Battle, A. et al. Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals. Genome Res. 24, 14–24 (2014).
Fairfax, B.P. et al. Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science 343, 1246949 (2014).
Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
Acknowledgements
This work is dedicated to Antonio Cao, Renzo Galanello and Maurizio Longinotti, who devoted their scientific lives to understanding, preventing and treating hematological diseases in Sardinia. We are also grateful to M.S. Ristaldi and M.G. Marini for knowledge and insight that they freely shared with us. Finally, we thank all the volunteers who generously participated in this study and made this research possible. The SardiNIA study was funded in part by the US National Institutes of Health (National Institute on Aging, National Heart, Lung, and Blood Institute, and National Human Genome Research Institute). This research was supported by National Human Genome Research Institute grants HG005581, HG005552, HG006513 and HG007022; by National Heart, Lung, and Blood Institute grant HL117626; by the Intramural Research Program of the US National Institutes of Health, National Institute on Aging, contracts N01-AG-1-2109 and HHSN271201100005C; by Sardinian Autonomous Region (L.R. number 7/2009) grant cRP3-154; by grant FaReBio2011 “Farmaci e Reti Biotecnologiche di Qualità”; and by the PB05 InterOmics MIUR Flagship Project. The TwinsUK study was funded by the Wellcome Trust; the European Community's Seventh Framework Programme (FP7/2007-2013); and the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. Genotyping in the replication cohorts was performed by the Wellcome Trust Sanger Institute and National Eye Institute via the US National Institutes of Health/Center for Inherited Disease Research (CIDR). S.L.T. was supported by the Medical Research Council, UK (grant G0000111, ID51640), and S. Menzel received funding from the British Society for Haematology (start-up grant).
Author information
Authors and Affiliations
Contributions
G.R.A., D.S. and F.C. conceived the study. F.D., D.S., S.S. and F.C. drafted the manuscript. F.D., M.Z., M.U., P.M., S.L.T., G.R.A., D.S., S.S. and F.C. revised the manuscript. F.B., A. Maschio and A.A. performed sequencing experiments. M. Pitzalis, G.R.A. and S.S. selected samples for sequencing. F.D., C.S., M.S., E.P., G.P. and S.S. carried out genetic association analyses in the SardiNIA cohort. C.S. analyzed DNA sequence data. M.Z., F.B. and A. Mulas carried out SNP array genotyping. M.Z. designed the validation strategy, and M.Z., F.B. and A. Mulas verified genotypes by Sanger sequencing and TaqMan genotyping. L.P. performed genotyping of –α 3.7 deletion type I. M. Pala created an automatized pipeline to query the public eQTL repositories. P.M. and R.G. provided genotypes and phenotypic data for patients with β-thalassemia. S.B. and R.G. supervised the characterization of the hemoglobins in the SardiNIA cohort. F.D. analyzed the cohort of patients with β-thalassemia. S. Menzel, T.D.S. and S.L.T. provided replication samples. S. Metrustry analyzed replication samples. L.L. provided IT support for sequencing and genotype data processing and analyses. D.S. and F.C. supervised the study. All authors reviewed and approved the final manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–5, Supplementary Tables 1–11 and Supplementary Note. (PDF 4256 kb)
Rights and permissions
About this article
Cite this article
Danjou, F., Zoledziewska, M., Sidore, C. et al. Genome-wide association analyses based on whole-genome sequencing in Sardinia provide insights into regulation of hemoglobin levels. Nat Genet 47, 1264–1271 (2015). https://doi.org/10.1038/ng.3307
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/ng.3307
This article is cited by
-
Ancient DNA suggests anaemia and low bone mineral density as the cause for porotic hyperostosis in ancient individuals
Scientific Reports (2023)
-
Erythroid lineage chromatin accessibility maps facilitate identification and validation of NFIX as a fetal hemoglobin repressor
Communications Biology (2023)
-
Dual function NFI factors control fetal hemoglobin silencing in adult erythroid cells
Nature Genetics (2022)
-
Challenges and future directions for studying effects of host genetics on the gut microbiome
Nature Genetics (2022)
-
MTHFR, XRCC1 and OGG1 genetic polymorphisms in breast cancer: a case-control study in a population from North Sardinia
BMC Cancer (2020)