A systematic strategy for identifying causal single nucleotide polymorphisms and their target genes on Juvenile arthritis risk haplotypes.
CRISPRi
Causal variant
Enhancers
Genetics
Haplotype
Juvenile arthritis
Journal
BMC medical genomics
ISSN: 1755-8794
Titre abrégé: BMC Med Genomics
Pays: England
ID NLM: 101319628
Informations de publication
Date de publication:
12 Jul 2024
12 Jul 2024
Historique:
received:
15
04
2024
accepted:
27
06
2024
medline:
13
7
2024
pubmed:
13
7
2024
entrez:
12
7
2024
Statut:
epublish
Résumé
Although genome-wide association studies (GWAS) have identified multiple regions conferring genetic risk for juvenile idiopathic arthritis (JIA), we are still faced with the task of identifying the single nucleotide polymorphisms (SNPs) on the disease haplotypes that exert the biological effects that confer risk. Until we identify the risk-driving variants, identifying the genes influenced by these variants, and therefore translating genetic information to improved clinical care, will remain an insurmountable task. We used a function-based approach for identifying causal variant candidates and the target genes on JIA risk haplotypes. We used a massively parallel reporter assay (MPRA) in myeloid K562 cells to query the effects of 5,226 SNPs in non-coding regions on JIA risk haplotypes for their ability to alter gene expression when compared to the common allele. The assay relies on 180 bp oligonucleotide reporters ("oligos") in which the allele of interest is flanked by its cognate genomic sequence. Barcodes were added randomly by PCR to each oligo to achieve > 20 barcodes per oligo to provide a quantitative read-out of gene expression for each allele. Assays were performed in both unstimulated K562 cells and cells stimulated overnight with interferon gamma (IFNg). As proof of concept, we then used CRISPRi to demonstrate the feasibility of identifying the genes regulated by enhancers harboring expression-altering SNPs. We identified 553 expression-altering SNPs in unstimulated K562 cells and an additional 490 in cells stimulated with IFNg. We further filtered the SNPs to identify those plausibly situated within functional chromatin, using open chromatin and H3K27ac ChIPseq peaks in unstimulated cells and open chromatin plus H3K4me1 in stimulated cells. These procedures yielded 42 unique SNPs (total = 84) for each set. Using CRISPRi, we demonstrated that enhancers harboring MPRA-screened variants in the TRAF1 and LNPEP/ERAP2 loci regulated multiple genes, suggesting complex influences of disease-driving variants. Using MPRA and CRISPRi, JIA risk haplotypes can be queried to identify plausible candidates for disease-driving variants. Once these candidate variants are identified, target genes can be identified using CRISPRi informed by the 3D chromatin structures that encompass the risk haplotypes.
Sections du résumé
BACKGROUND
BACKGROUND
Although genome-wide association studies (GWAS) have identified multiple regions conferring genetic risk for juvenile idiopathic arthritis (JIA), we are still faced with the task of identifying the single nucleotide polymorphisms (SNPs) on the disease haplotypes that exert the biological effects that confer risk. Until we identify the risk-driving variants, identifying the genes influenced by these variants, and therefore translating genetic information to improved clinical care, will remain an insurmountable task. We used a function-based approach for identifying causal variant candidates and the target genes on JIA risk haplotypes.
METHODS
METHODS
We used a massively parallel reporter assay (MPRA) in myeloid K562 cells to query the effects of 5,226 SNPs in non-coding regions on JIA risk haplotypes for their ability to alter gene expression when compared to the common allele. The assay relies on 180 bp oligonucleotide reporters ("oligos") in which the allele of interest is flanked by its cognate genomic sequence. Barcodes were added randomly by PCR to each oligo to achieve > 20 barcodes per oligo to provide a quantitative read-out of gene expression for each allele. Assays were performed in both unstimulated K562 cells and cells stimulated overnight with interferon gamma (IFNg). As proof of concept, we then used CRISPRi to demonstrate the feasibility of identifying the genes regulated by enhancers harboring expression-altering SNPs.
RESULTS
RESULTS
We identified 553 expression-altering SNPs in unstimulated K562 cells and an additional 490 in cells stimulated with IFNg. We further filtered the SNPs to identify those plausibly situated within functional chromatin, using open chromatin and H3K27ac ChIPseq peaks in unstimulated cells and open chromatin plus H3K4me1 in stimulated cells. These procedures yielded 42 unique SNPs (total = 84) for each set. Using CRISPRi, we demonstrated that enhancers harboring MPRA-screened variants in the TRAF1 and LNPEP/ERAP2 loci regulated multiple genes, suggesting complex influences of disease-driving variants.
CONCLUSION
CONCLUSIONS
Using MPRA and CRISPRi, JIA risk haplotypes can be queried to identify plausible candidates for disease-driving variants. Once these candidate variants are identified, target genes can be identified using CRISPRi informed by the 3D chromatin structures that encompass the risk haplotypes.
Identifiants
pubmed: 38997781
doi: 10.1186/s12920-024-01954-z
pii: 10.1186/s12920-024-01954-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
185Subventions
Organisme : National Institutes of Health (USA)
ID : R21-AR071878
Organisme : NIH HHS
ID : R21 AR076948
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1TR001412
Pays : United States
Informations de copyright
© 2024. The Author(s).
Références
Gortmaker SL, Sappenfield W. Chronic childhood disorders: prevalence and impact. Pediatr Clin North Am. 1984;31(1):3–18.
pubmed: 6366717
doi: 10.1016/S0031-3955(16)34532-1
Singsen BH. Rheumatic diseases of childhood. Rheum Dis Clin North Am. 1990;16(3):581–99.
pubmed: 2217959
doi: 10.1016/S0889-857X(21)00889-9
Glass DN, Giannini EH. Juvenile rheumatoid arthritis as a complex genetic trait. Arthritis Rheum. 1999;42(11):2261–8.
pubmed: 10555018
doi: 10.1002/1529-0131(199911)42:11<2261::AID-ANR1>3.0.CO;2-P
Prahalad S, Zeft AS, Pimentel R, Clifford B, McNally B, Mineau GP, et al. Quantification of the familial contribution to juvenile idiopathic arthritis. Arthritis Rheum. 2010;62(8):2525–9.
pubmed: 20506132
pmcid: 2921017
doi: 10.1002/art.27516
Hersh AO, Prahalad S. Immunogenetics of juvenile idiopathic arthritis: a comprehensive review. J Autoimmun. 2015;64:113–24.
pubmed: 26305060
pmcid: 4838197
doi: 10.1016/j.jaut.2015.08.002
Hinks A, Cobb J, Marion MC, Prahalad S, Sudman M, Bowes J, et al. Dense genotyping of immune-related disease regions identifies 14 new susceptibility loci for juvenile idiopathic arthritis. Nat Genet. 2013;45(6):664–9.
pubmed: 23603761
pmcid: 3673707
doi: 10.1038/ng.2614
McIntosh LA, Marion MC, Sudman M, Comeau ME, Becker ML, Bohnsack JF, et al. Genome-Wide Association Meta-Analysis reveals Novel Juvenile Idiopathic Arthritis susceptibility loci. Arthritis Rheumatol. 2017;69(11):2222–32.
pubmed: 28719732
pmcid: 5874801
doi: 10.1002/art.40216
Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H, et al. Systematic localization of common disease-associated variation in regulatory DNA. Science. 2012;337(6099):1190–5.
pubmed: 22955828
pmcid: 3771521
doi: 10.1126/science.1222794
Farh KK, Marson A, Zhu J, Kleinewietfeld M, Housley WJ, Beik S, et al. Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature. 2015;518(7539):337–43.
pubmed: 25363779
doi: 10.1038/nature13835
Jiang K, Zhu L, Buck MJ, Chen Y, Carrier B, Liu T, et al. Disease-Associated single-nucleotide polymorphisms from noncoding regions in Juvenile Idiopathic Arthritis are located within or adjacent to functional genomic elements of human neutrophils and CD4 + T cells. Arthritis Rheumatol. 2015;67(7):1966–77.
pubmed: 25833190
pmcid: 4485537
doi: 10.1002/art.39135
Zhu L, Jiang K, Webber K, Wong L, Liu T, Chen Y, et al. Chromatin landscapes and genetic risk for juvenile idiopathic arthritis. Arthritis Res Ther. 2017;19(1):57.
pubmed: 28288683
pmcid: 5348874
doi: 10.1186/s13075-017-1260-x
Jiang K, Kessler H, Park Y, Sudman M, Thompson SD, Jarvis JN. Broadening our understanding of the genetics of Juvenile Idiopathic Arthritis (JIA): interrogation of three dimensional chromatin structures and genetic regulatory elements within JIA-associated risk loci. PLoS ONE. 2020;15(7):e0235857.
pubmed: 32730263
pmcid: 7392255
doi: 10.1371/journal.pone.0235857
Tewhey R, Kotliar D, Park DS, Liu B, Winnicki S, Reilly SK, et al. Direct identification of hundreds of expression-modulating variants using a multiplexed reporter assay. Cell. 2016;165(6):1519–29.
pubmed: 27259153
pmcid: 4957403
doi: 10.1016/j.cell.2016.04.027
Wong L, Jiang K, Chen Y, Jarvis JN. Genetic insights into juvenile idiopathic arthritis derived from deep whole genome sequencing. Sci Rep. 2017;7(1):2657.
pubmed: 28572608
pmcid: 5453970
doi: 10.1038/s41598-017-02966-9
Throm AA, Moncrieffe H, Orandi AB, Pingel JT, Geurs TL, Miller HL et al. Identification of enhanced IFN-gamma signaling in polyarticular juvenile idiopathic arthritis with mass cytometry. JCI Insight. 2018;3(15).
Jarvis JN, Dozmorov I, Jiang K, Frank MB, Szodoray P, Alex P, et al. Novel approaches to gene expression analysis of active polyarticular juvenile rheumatoid arthritis. Arthritis Res Ther. 2004;6(1):R15–32.
pubmed: 14979934
doi: 10.1186/ar1018
Love MI, Huber W, Anders S. Moderated estimation of Fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.
pubmed: 25516281
pmcid: 4302049
doi: 10.1186/s13059-014-0550-8
Kim D, Park Y. Molecular mechanism for the multiple sclerosis risk variant rs17594362. Hum Mol Genet. 2019;28(21):3600–9.
pubmed: 31509193
pmcid: 6927461
doi: 10.1093/hmg/ddz216
Kim D, An H, Shearer RS, Sharif M, Fan C, Choi JO, et al. A principled strategy for mapping enhancers to genes. Sci Rep. 2019;9(1):11043.
pubmed: 31363138
pmcid: 6667464
doi: 10.1038/s41598-019-47521-w
Kim D, An H, Fan C, Park Y. Identifying oligodendrocyte enhancers governing Plp1 expression. Hum Mol Genet. 2021;30(23):2225–39.
pubmed: 34230963
pmcid: 8600034
doi: 10.1093/hmg/ddab184
Huang X, Wilber AC, Bao L, Tuong D, Tolar J, Orchard PJ, et al. Stable gene transfer and expression in human primary T cells by the sleeping Beauty transposon system. Blood. 2006;107(2):483–91.
pubmed: 16189271
pmcid: 1895607
doi: 10.1182/blood-2005-05-2133
Gasperini M, Hill AJ, McFaline-Figueroa JL, Martin B, Kim S, Zhang MD et al. A genome-wide Framework for Mapping Gene Regulation via Cellular Genetic screens. Cell. 2019;176(1–2):377 – 90 e19.
Albers HM, Kurreeman FA, Houwing-Duistermaat JJ, Brinkman DM, Kamphuis SS, Girschick HJ, et al. The TRAF1/C5 region is a risk factor for polyarthritis in juvenile idiopathic arthritis. Ann Rheum Dis. 2008;67(11):1578–80.
pubmed: 18593758
doi: 10.1136/ard.2008.089060
Paladini F, Fiorillo MT, Tedeschi V, Mattorre B, Sorrentino R. The multifaceted nature of Aminopeptidases ERAP1, ERAP2, and LNPEP: from evolution to Disease. Front Immunol. 2020;11:1576.
pubmed: 32793222
pmcid: 7390905
doi: 10.3389/fimmu.2020.01576
Thakore PI, D’Ippolito AM, Song L, Safi A, Shivakumar NK, Kabadi AM, et al. Highly specific epigenome editing by CRISPR-Cas9 repressors for silencing of distal regulatory elements. Nat Methods. 2015;12(12):1143–9.
pubmed: 26501517
pmcid: 4666778
doi: 10.1038/nmeth.3630
Breunig JJ, Levy R, Antonuk CD, Molina J, Dutra-Clarke M, Park H, et al. Ets factors regulate neural stem cell depletion and gliogenesis in Ras Pathway Glioma. Cell Rep. 2015;12(2):258–71.
pubmed: 26146073
doi: 10.1016/j.celrep.2015.06.012
Herlin MKPM, Herlin T. Update on genetic susceptibility and pathogenesis in juvenile idiopathic arthritis. EMJ Rheumatol. 2014;1:73–83.
doi: 10.33590/emjrheumatol/10313716
Gate RE, Cheng CS, Aiden AP, Siba A, Tabaka M, Lituiev D, et al. Genetic determinants of co-accessible chromatin regions in activated T cells across humans. Nat Genet. 2018;50(8):1140–50.
pubmed: 29988122
pmcid: 6097927
doi: 10.1038/s41588-018-0156-2
Birnbaum RY, Clowney EJ, Agamy O, Kim MJ, Zhao J, Yamanaka T, et al. Coding exons function as tissue-specific enhancers of nearby genes. Genome Res. 2012;22(6):1059–68.
pubmed: 22442009
pmcid: 3371700
doi: 10.1101/gr.133546.111
Ahituv N. Exonic enhancers: proceed with caution in exome and genome sequencing studies. Genome Med. 2016;8(1):14.
pubmed: 26856702
pmcid: 4745165
doi: 10.1186/s13073-016-0277-0
Wang Y, Song F, Zhang B, Zhang L, Xu J, Kuang D, et al. The 3D genome browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions. Genome Biol. 2018;19(1):151.
pubmed: 30286773
pmcid: 6172833
doi: 10.1186/s13059-018-1519-9
Rao SS, Huntley MH, Durand NC, Stamenova EK, Bochkov ID, Robinson JT, et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell. 2014;159(7):1665–80.
pubmed: 25497547
pmcid: 5635824
doi: 10.1016/j.cell.2014.11.021
Kim-Hellmuth S, Aguet F, Oliva M, Munoz-Aguirre M, Kasela S, Wucher V et al. Cell type-specific genetic regulation of gene expression across human tissues. Science. 2020;369(6509).
Gallagher MD, Chen-Plotkin AS. The Post-GWAS era: from association to function. Am J Hum Genet. 2018;102(5):717–30.
pubmed: 29727686
pmcid: 5986732
doi: 10.1016/j.ajhg.2018.04.002
Rao S, Yao Y, Bauer DE. Editing GWAS: experimental approaches to dissect and exploit disease-associated genetic variation. Genome Med. 2021;13(1):41.
pubmed: 33691767
pmcid: 7948363
doi: 10.1186/s13073-021-00857-3
Lu X, Chen X, Forney C, Donmez O, Miller D, Parameswaran S, et al. Global discovery of lupus genetic risk variant allelic enhancer activity. Nat Commun. 2021;12(1):1611.
pubmed: 33712590
pmcid: 7955039
doi: 10.1038/s41467-021-21854-5
Hui-Yuen JS, Zhu L, Wong LP, Jiang K, Chen Y, Liu T, et al. Chromatin landscapes and genetic risk in systemic lupus. Arthritis Res Ther. 2016;18(1):281.
pubmed: 27906046
pmcid: 5134118
doi: 10.1186/s13075-016-1169-9
Ray JP, de Boer CG, Fulco CP, Lareau CA, Kanai M, Ulirsch JC, et al. Prioritizing disease and trait causal variants at the TNFAIP3 locus using functional and genomic features. Nat Commun. 2020;11(1):1237.
pubmed: 32144282
pmcid: 7060350
doi: 10.1038/s41467-020-15022-4
Bourges C, Groff AF, Burren OS, Gerhardinger C, Mattioli K, Hutchinson A, et al. Resolving mechanisms of immune-mediated disease in primary CD4 T cells. EMBO Mol Med. 2020;12(5):e12112.
pubmed: 32239644
pmcid: 7207160
doi: 10.15252/emmm.202012112
Inoue F, Kircher M, Martin B, Cooper GM, Witten DM, McManus MT, et al. A systematic comparison reveals substantial differences in chromosomal versus episomal encoding of enhancer activity. Genome Res. 2017;27(1):38–52.
pubmed: 27831498
pmcid: 5204343
doi: 10.1101/gr.212092.116
Ainsworth HC, Howard TD, Langefeld CD. Intrinsic DNA topology as a prioritization metric in genomic fine-mapping studies. Nucleic Acids Res. 2020;48(20):11304–21.
pubmed: 33084892
pmcid: 7672465
doi: 10.1093/nar/gkaa877
Wong L, Jiang K, Chen Y, Hennon T, Holmes L, Wallace CA, et al. Limits of Peripheral Blood mononuclear cells for gene expression-based biomarkers in Juvenile Idiopathic Arthritis. Sci Rep. 2016;6:29477.
pubmed: 27385437
pmcid: 4935846
doi: 10.1038/srep29477
Wu CY, Yang HY, Huang JL, Lai JH. Signals and mechanisms regulating monocyte and macrophage activation in the pathogenesis of Juvenile Idiopathic Arthritis. Int J Mol Sci. 2021;22(15).
Zhou Z, Xu MJ, Gao B. Hepatocytes: a key cell type for innate immunity. Cell Mol Immunol. 2016;13(3):301–15.
pubmed: 26685902
doi: 10.1038/cmi.2015.97
Jiang K, Wong L, Sawle AD, Frank MB, Chen Y, Wallace CA, et al. Whole blood expression profiling from the TREAT trial: insights for the pathogenesis of polyarticular juvenile idiopathic arthritis. Arthritis Res Ther. 2016;18(1):157.
pubmed: 27388672
pmcid: 4936089
doi: 10.1186/s13075-016-1059-1
Jiang K, Sawle AD, Frank MB, Chen Y, Wallace CA, Jarvis JN. Whole blood gene expression profiling predicts therapeutic response at six months in patients with polyarticular juvenile idiopathic arthritis. Arthritis Rheumatol. 2014;66(5):1363–71.
pubmed: 24782192
pmcid: 4077198
doi: 10.1002/art.38341