Comprehensive population-based genome sequencing provides insight into hematopoietic regulatory mechanisms

Proceedings of the National Academy of Sciences of the United States of America

Volumn 114, Issue 3, 2017, Pages E327-E336

  Guoa, Michael H ^a,b,c   Nandakumar, Satish K ^a,b   Ulirsch, Jacob C ^a,b   Zekavat, Seyedeh M ^a,d   Buenrostro, Jason D ^a   Natarajan, Pradeep ^a,d   Salem, Rany M ^a,b,c   Chiarle, Roberto ^b,e   Mitt, Mario ^f   Kals, Mart ^f   Pärn, Kalle ^f   Fischer, Krista ^f   Milani, Lili ^f   Mägi, Reedik ^f   Palta, Priit ^f,g   Gabriel, Stacey B ^a   Metspalu, Andres ^f   Lander, Eric S ^a,c,h   Kathiresan, Sekar ^a,d   Hirschhorn, Joel N ^a,b,c   Esko, Tõnu ^a,b,f   Sankaran, Vijay G ^a,b   more..

^a BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^b BOSTON CHILDREN S HOSPITAL   (United States)

^c HARVARD MEDICAL SCHOOL   (United States)

^d MASSACHUSETTS GENERAL HOSPITAL   (United States)

^e UNIVERSITY OF TURIN   (Italy)

^f UNIVERSITY OF TARTU   (Estonia)

^g UNIVERSITY OF HELSINKI   (Finland)

^h MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Basophils; CEBPA; Genome sequencing; GWAS; Hematopoiesis

Indexed keywords

TRANSCRIPTION FACTOR GATA 2; CCAAT ENHANCER BINDING PROTEIN; CEBPA PROTEIN, HUMAN; GATA2 PROTEIN, HUMAN;

BASOPHIL; BIOBANK; BLOOD CELL; CELL DIFFERENTIATION; CLUSTERED REGULARLY INTERSPACED SHORT PALINDROMIC REPEAT; COHORT ANALYSIS; CONFERENCE PAPER; CONTROLLED STUDY; ENHANCER REGION; EPIGENETICS; FEMALE; GENE SEQUENCE; GENETIC ASSOCIATION STUDY; GENETIC REGULATION; GENETIC TRAIT; GENOME; GENOTYPE; HEMATOPOIESIS; HUMAN; MALE; MUTAGENESIS; MYELOID PROGENITOR CELL; PLEIOTROPY; POPULATION GENETICS; PRIORITY JOURNAL; WHOLE GENOME SEQUENCING; CELL LINEAGE; CHROMOSOMAL MAPPING; CYTOLOGY; ESTONIA; GENE EXPRESSION REGULATION; GENETIC EPIGENESIS; GENETICS; GENOME-WIDE ASSOCIATION STUDY; LEUKOCYTE COUNT; NUCLEIC ACID DATABASE; NUCLEOTIDE SEQUENCE; SINGLE NUCLEOTIDE POLYMORPHISM;

BASE SEQUENCE; BASOPHILS; CCAAT-ENHANCER-BINDING PROTEINS; CELL DIFFERENTIATION; CELL LINEAGE; CHROMOSOME MAPPING; DATABASES, NUCLEIC ACID; ENHANCER ELEMENTS, GENETIC; EPIGENESIS, GENETIC; ESTONIA; FEMALE; GATA2 TRANSCRIPTION FACTOR; GENE EXPRESSION REGULATION, DEVELOPMENTAL; GENOME-WIDE ASSOCIATION STUDY; HEMATOPOIESIS; HUMANS; LEUKOCYTE COUNT; MALE; POLYMORPHISM, SINGLE NUCLEOTIDE; WHOLE GENOME SEQUENCING;

EID: 85009756476     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1619052114     Document Type: Article

References (105)

1. Sankaran VG, Orkin SH (2013) Genome-wide association studies of hematologic phenotypes: A window into human hematopoiesis. Curr Opin Genet Dev 23(3): 339-344.
2. Sankaran VG, Weiss MJ (2015) Anemia: Progress in molecular mechanisms and therapies. Nat Med 21(3):221-230.
3. van der Harst P, et al. (2012) Seventy-five genetic loci influencing the human red blood cell. Nature 492(7429):369-375.
4. Ulirsch JC, et al. (2016) Systematic functional dissection of common genetic variation affecting red blood cell traits. Cell 165(6):1530-1545.
5. Orrù V, et al. (2013) Genetic variants regulating immune cell levels in health and disease. Cell 155(1):242-256.
6. Leitsalu L, Alavere H, Tammesoo ML, Leego E, Metspalu A (2015) Linking a population biobank with national health registries-the Estonian experience. J Pers Med 5(2):96-106.
7. Lee S, et al.; NHLBI GO Exome Sequencing Project-ESP Lung Project Team (2012) Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies. Am J Hum Genet 91(2): 224-237.
8. Sankaran VG, et al. (2013) Rare complete loss of function provides insight into a pleiotropic genome-wide association study locus. Blood 122(23):3845-3847.
9. Galarneau G, et al. (2010) Fine-mapping at three loci known to affect fetal hemoglobin levels explains additional genetic variation. Nat Genet 42(12):1049-1051.
10. Nuinoon M, et al. (2010) A genome-wide association identified the common genetic variants influence disease severity in beta0-thalassemia/hemoglobin E. Hum Genet 127(3):303-314.
11. Lettre G, et al. (2008) DNA polymorphisms at the BCL11A, HBS1L-MYB, and betaglobin loci associate with fetal hemoglobin levels and pain crises in sickle cell disease. Proc Natl Acad Sci USA 105(33):11869-11874.
12. Khwaja A (2006) The role of Janus kinases in haemopoiesis and haematological malignancy. Br J Haematol 134(4):366-384.
13. Auer PL, et al. (2014) Rare and low-frequency coding variants in CXCR2 and other genes are associated with hematological traits. Nat Genet 46(6):629-634.
14. Kahn ML, et al. (1998) A dual thrombin receptor system for platelet activation. Nature 394(6694):690-694.
15. Polfus LM, et al. (2016) Whole-exome sequencing identifies loci associated with blood cell traits and reveals a role for alternative GFI1B splice variants in human hematopoiesis. Am J Hum Genet 99(2):481-488.
16. Zuk O, et al. (2014) Searching for missing heritability: Designing rare variant association studies. Proc Natl Acad Sci USA 111(4):E455-E464.
17. Keller MF, et al.; CHARGE Hematology; COGENT; BioBank Japan Project (RIKEN) Working Groups (2014) Trans-ethnic meta-analysis of white blood cell phenotypes. Hum Mol Genet 23(25):6944-6960.
18. Okada Y, et al. (2011) Identification of nine novel loci associated with white blood cell subtypes in a Japanese population. PLoS Genet 7(6):e1002067.
19. Nalls MA, et al. (2011) Multiple loci are associated with white blood cell phenotypes. PLoS Genet 7(6):e1002113.
20. Abecasis GR, et al.; 1000 Genomes Project Consortium (2012) An integrated map of genetic variation from 1, 092 human genomes. Nature 491(7422):56-65.
21. Auton A, et al.; 1000 Genomes Project Consortium (2015) A global reference for human genetic variation. Nature 526(7571):68-74.
22. Maller JB, et al.; Wellcome Trust Case Control Consortium (2012) Bayesian refinement of association signals for 14 loci in 3 common diseases. Nat Genet 44(12): 1294-1301.
23. Chen W, et al. (2015) Fine mapping causal variants with an approximate Bayesian method using marginal test statistics. Genetics 200(3):719-736.
24. Farh KK-H, et al. (2015) Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature 518(7539):337-343.
25. Gusev A, et al.; Schizophrenia Working Group of the Psychiatric Genomics Consortium; SWE-SCZ Consortium; Schizophrenia Working Group of the Psychiatric Genomics Consortium; SWE-SCZ Consortium (2014) Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. Am J Hum Genet 95(5): 535-552.
26. Finucane HK, et al.; ReproGen Consortium; Schizophrenia Working Group of the Psychiatric Genomics Consortium; RACI Consortium (2015) Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat Genet 47(11):1228-1235.
27. Corces MR, et al. (2016) Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution. Nat Genet 48(10):1193-1203.
28. Trynka G, et al. (2015) Disentangling the effects of colocalizing genomic annotations to functionally prioritize non-coding variants within complex-trait loci. Am J Hum Genet 97(1):139-152.
29. Nai A, et al. (2011) TMPRSS6 rs855791 modulates hepcidin transcription in vitro and serum hepcidin levels in normal individuals. Blood 118(16):4459-4462.
30. Finberg KE, et al. (2008) Mutations in TMPRSS6 cause iron-refractory iron deficiency anemia (IRIDA). Nat Genet 40(5):569-571.
31. Stadhouders R, et al. (2014) HBS1L-MYB intergenic variants modulate fetal hemoglobin via long-range MYB enhancers. J Clin Invest 124(4):1699-1710.
32. Serbanovic-Canic J, et al. (2011) Silencing of RhoA nucleotide exchange factor, ARHGEF3, reveals its unexpected role in iron uptake. Blood 118(18):4967-4976.
33. Battle A, et al. (2014) Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals. Genome Res 24(1):14-24.
34. Zhang X, et al. (2014) Genetic associations with expression for genes implicated in GWAS studies for atherosclerotic cardiovascular disease and blood phenotypes. Hum Mol Genet 23(3):782-795.
35. Zhou J, Troyanskaya OG (2015) Predicting effects of noncoding variants with deep learning-based sequence model. Nat Methods 12(10):931-934.
36. Avellino R, et al. (2016) An autonomous CEBPA enhancer specific for myeloid-lineage priming and neutrophilic differentiation. Blood 127(24):2991-3003.
37. Guo H, Cooper S, Friedman AD (2016) In vivo deletion of the Cebpa +37 kb enhancer markedly reduces Cebpa mRNA in myeloid progenitors but not in non-hematopoietic tissues to impair granulopoiesis. PLoS One 11(3):e0150809.
38. Wilson NK, et al. (2016) Integrated genome-scale analysis of the transcriptional regulatory landscape in a blood stem/progenitor cell model. Blood 127(13):e12-e23.
39. Chen C-C, Grimbaldeston MA, Tsai M, Weissman IL, Galli SJ (2005) Identification of mast cell progenitors in adult mice. Proc Natl Acad Sci USA 102(32):11408-11413.
40. Franco CB, Chen CC, Drukker M, Weissman IL, Galli SJ (2010) Distinguishing mast cell and granulocyte differentiation at the single-cell level. Cell Stem Cell 6(4):361-368.
41. Görgens A, et al. (2013) Revision of the human hematopoietic tree: Granulocyte subtypes derive from distinct hematopoietic lineages. Cell Rep 3(5):1539-1552.
42. Drissen R, et al. (2016) Distinct myeloid progenitor-differentiation pathways identified through single-cell RNA sequencing. Nat Immunol 17(6):666-676.
43. Wakabayashi A, et al. (2016) Insight into GATA1 transcriptional activity through interrogation of cis elements disrupted in human erythroid disorders. Proc Natl Acad Sci USA 113(16):4434-4439.
44. Voehringer D (2013) Protective and pathological roles of mast cells and basophils. Nat Rev Immunol 13(5):362-375.
45. Huang H, Li Y (2014) Mechanisms controlling mast cell and basophil lineage decisions. Curr Allergy Asthma Rep 14(9):457.
46. Dwyer DF, Barrett NA, Austen KF; Immunological Genome Project Consortium (2016) Expression profiling of constitutive mast cells reveals a unique identity within the immune system. Nat Immunol 17(7):878-887.
47. Friedman AD (2015) C/EBPα in normal and malignant myelopoiesis. Int J Hematol 101(4):330-341.
48. Paul F, et al. (2015) Transcriptional heterogeneity and lineage commitment in myeloid progenitors. Cell 163(7):1663-1677.
49. Iwasaki H, et al. (2006) The order of expression of transcription factors directs hierarchical specification of hematopoietic lineages. Genes Dev 20(21):3010-3021.
50. Ishmael SS, MacGlashan DW, Jr (2010) Syk expression in peripheral blood leukocytes, CD34+ progenitors, and CD34-derived basophils. J Leukoc Biol 87(2):291-300.
51. Choi KD, Vodyanik MA, Slukvin II (2009) Generation of mature human myelomonocytic cells through expansion and differentiation of pluripotent stem cell-derived lin-CD34+CD43+CD45+ progenitors. J Clin Invest 119(9):2818-2829.
52. Kepley CL, Pfeiffer JR, Schwartz LB, Wilson BS, Oliver JM (1998) The identification and characterization of umbilical cord blood-derived human basophils. J Leukoc Biol 64(4):474-483.
53. Bühring HJ, et al. (1999) The monoclonal antibody 97A6 defines a novel surface antigen expressed on human basophils and their multipotent and unipotent progenitors. Blood 94(7):2343-2356.
54. Langdon JM, et al. (2008) Histamine-releasing factor/translationally controlled tumor protein (HRF/TCTP)-induced histamine release is enhanced with SHIP-1 knockdown in cultured human mast cell and basophil models. J Leukoc Biol 84(4): 1151-1158.
55. Arinobu Y, et al. (2005) Developmental checkpoints of the basophil/mast cell lineages in adult murine hematopoiesis. Proc Natl Acad Sci USA 102(50):18105-18110.
56. Rao KN, Smuda C, Gregory GD, Min B, Brown MA (2013) Ikaros limits basophil development by suppressing C/EBP-α expression. Blood 122(15):2572-2581.
57. Westra H-J, et al. (2013) Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat Genet 45(10):1238-1243.
58. Gudbjartsson DF, et al. (2009) Sequence variants affecting eosinophil numbers associate with asthma and myocardial infarction. Nat Genet 41(3):342-347.
59. Nandakumar SK, et al. (2015) Low-level GATA2 overexpression promotes myeloid progenitor self-renewal and blocks lymphoid differentiation in mice. Exp Hematol 43(7):565-577.e1-10.
60. Li Y, Qi X, Liu B, Huang H (2015) The STAT5-GATA2 pathway is critical in basophil and mast cell differentiation and maintenance. J Immunol 194(9):4328-4338.
61. Nadif R, Zerimech F, Bouzigon E, Matran R (2013) The role of eosinophils and basophils in allergic diseases considering genetic findings. Curr Opin Allergy Clin Immunol 13(5):507-513.
62. Min B (2008) Basophils: What they "can do" versus what they "actually do." Nat Immunol 9(12):1333-1339.
63. Sullivan BM, Locksley RM (2009) Basophils: A nonredundant contributor to host immunity. Immunity 30(1):12-20.
64. Sudlow C, et al. (2015) UK Biobank: An open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med 12(3):e1001779.
65. Jostins L, et al.; International IBD Genetics Consortium (IIBDGC) (2012) Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491(7422):119-124.
66. Franke A, et al. (2010) Genome-wide meta-analysis increases to 71 the number of confirmed Crohn's disease susceptibility loci. Nat Genet 42(12):1118-1125.
67. Imielinski M, et al.; Western Regional Alliance for Pediatric IBD; International IBD Genetics Consortium; NIDDK IBD Genetics Consortium; Belgian-French IBD Consortium; Wellcome Trust Case Control Consortium (2009) Common variants at five new loci associated with early-onset inflammatory bowel disease. Nat Genet 41(12): 1335-1340.
68. Bush WS, Oetjens MT, Crawford DC (2016) Unravelling the human genome-phenome relationship using phenome-wide association studies. Nat Rev Genet 17(3):129-145.
69. Nandakumar SK, Ulirsch JC, Sankaran VG (2016) Advances in understanding erythropoiesis: Evolving perspectives. Br J Haematol 173(2):206-218.
70. Graf T, Enver T (2009) Forcing cells to change lineages. Nature 462(7273):587-594.
71. Mukai K, et al. (2012) Critical role of P1-Runx1 in mouse basophil development. Blood 120(1):76-85.
72. Qi X, et al. (2013) Antagonistic regulation by the transcription factors C/EBPα and MITF specifies basophil and mast cell fates. Immunity 39(1):97-110.
73. Collins FS, Varmus H (2015) A new initiative on precision medicine. N Engl J Med 372(9):793-795.
74. Sanjana NE, Shalem O, Zhang F (2014) Improved vectors and genome-wide libraries for CRISPR screening. Nat Methods 11(8):783-784.
75. Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25(14):1754-1760.
76. Van der Auwera GA, et al. (2013) From FastQ data to high confidence variant calls: The Genome Analysis Toolkit best practices pipeline. Curr Protoc Bioinformatics 43(SUPL.43):1-33.
77. DePristo MA, et al. (2011) A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 43(5):491-498.
78. McKenna A, et al. (2010) The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20(9):1297-1303.
79. Li H (2014) Toward better understanding of artifacts in variant calling from highcoverage samples. Bioinformatics 30(20):2843-2851.
80. Delaneau O, Marchini J, Zagury J-F (2011) A linear complexity phasing method for thousands of genomes. Nat Methods 9(2):179-181.
81. Joshi PK, et al. (2016) Variants near CHRNA3/5 and APOE have age- and sex-related effects on human lifespan. Nat Commun 7:11174.
82. Männik K, et al. (2015) Copy number variations and cognitive phenotypes in unselected populations. JAMA 313(20):2044-2054.
83. Lall K, Magi R, Morris A, Metspalu A, Fischer K (2016) Personalized risk prediction for type 2 diabetes: The potential of genetic risk scores. Genet Med, in press.
84. Howie BN, Donnelly P, Marchini J (2009) A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 5(6):e1000529.
85. Marchini J, Howie B, Myers S, McVean G, Donnelly P (2007) A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 39(7):906-913.
86. Willer CJ, et al. (2008) Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet 40(2):161-169.
87. Kumar P, Henikoff S, Ng PC (2009) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 4(7):1073-1081.
88. Adzhubei IA, et al. (2010) A method and server for predicting damaging missense mutations. Nat Methods 7(4):248-249.
89. Browning BL, Browning SR (2016) Genotype imputation with millions of reference samples. Am J Hum Genet 98(1):116-126.
90. Handsaker RE, et al. (2015) Large multiallelic copy number variations in humans. Nat Genet 47(3):296-303.
91. Chan Y, et al.; GIANT Consortium (2015) Genome-wide analysis of body proportion classifies height-associated variants by mechanism of action and implicates genes important for skeletal development. Am J Hum Genet 96(5):695-708.
92. Altshuler DM, et al.; International HapMap 3 Consortium (2010) Integrating common and rare genetic variation in diverse human populations. Nature 467(7311):52-58.
93. Purcell S, Chang C (2015) PLINK 1.9. Available at https://www.cog-genomics.org/ plink2. Accessed November 1, 2015.
94. Chang CC, et al. (2015) Second-generation PLINK: Rising to the challenge of larger and richer datasets. Gigascience 4(1):7.
95. UK Biobank (2015) Genotyping and Quality Control of UK Biobank, a Large-Scale, Extensively Phenotyped Prospective Resource. Available at biobank.ctsu.ox.ac.uk/ crystal/docs/genotyping-qc.pdf. Accessed April 1, 2016.
96. Purcell S, Cherny SS, Sham PC (2003) Genetic power calculator: Design of linkage and association genetic mapping studies of complex traits. Bioinformatics 19(1):149-150.
97. Wakefield J (2009) Bayes factors for genome-wide association studies: Comparison with P-values. Genet Epidemiol 33(1):79-86.
98. Yue F, et al.; Mouse ENCODE Consortium (2014) A comparative encyclopedia of DNA elements in the mouse genome. Nature 515(7527):355-364.
99. Pollard KS, Hubisz MJ, Rosenbloom KR, Siepel A (2010) Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res 20(1):110-121.
100. Davydov EV, et al. (2010) Identifying a high fraction of the human genome to be under selective constraint using GERP++. PLOS Comput Biol 6(12):e1001025.
101. Rosenbloom KR, et al. (2015) The UCSC Genome Browser database: 2015 update. Nucleic Acids Res 43(Database issue, D1):D670-D681.
102. Kulakovskiy IV, et al. (2016) HOCOMOCO: Expansion and enhancement of the collection of transcription factor binding sites models. Nucleic Acids Res 44(D1):D116-D125.
103. Mathelier A, et al. (2016) JASPAR 2016: A major expansion and update of the openaccess database of transcription factor binding profiles. Nucleic Acids Res 44(D1): D110-D115.
104. Grant CE, Bailey TL, Noble WS (2011) FIMO: Scanning for occurrences of a given motif. Bioinformatics 27(7):1017-1018.
105. Rao SSP, et al. (2014) A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159(7):1665-1680.