背景:尽管全基因组关联研究(GWAS)已经确定了多个区域赋予青少年特发性关节炎(JIA)的遗传风险,我们仍然面临着鉴定疾病单倍型的单核苷酸多态性(SNPs)的任务,这些单倍型发挥了赋予风险的生物学效应.在我们确定风险驱动变体之前,识别受这些变异影响的基因,因此,将遗传信息转化为更好的临床护理,将仍然是一项不可逾越的任务。我们使用基于功能的方法来识别JIA风险单倍型上的因果变异候选和靶基因。
方法:我们在髓样K562细胞中使用了大规模平行报告子测定法(MPRA),以查询非编码区中的5,226个SNP对JIA风险单倍型的影响,与普通等位基因相比,它们改变基因表达的能力。该测定依赖于180bp寡核苷酸报告基因(“寡核苷酸”),其中感兴趣的等位基因侧翼有其同源基因组序列。通过PCR向每个寡核苷酸随机添加条形码以实现每个寡核苷酸>20个条形码以提供每个等位基因的基因表达的定量读出。在未刺激的K562细胞和用干扰素γ(IFNg)刺激过夜的细胞中进行测定。作为概念的证明,然后,我们使用CRISPRi来证明鉴定由包含表达改变SNP的增强子调控的基因的可行性.
结果:我们在未刺激的K562细胞中鉴定了553种改变表达的SNP,在用IFNg刺激的细胞中鉴定了另外的490种。我们进一步过滤了SNP,以鉴定那些似乎位于功能性染色质内的SNP,在未刺激的细胞中使用开放染色质和H3K27acChIPseq峰,在刺激的细胞中使用开放染色质加H3K4me1。这些程序对于每组产生42个独特的SNP(总计=84)。使用CRISPRi,我们证明了在TRAF1和LNPEP/ERAP2基因座中带有MPRA筛选变体的增强子调节多个基因,提示疾病驱动变异的复杂影响。
结论:使用MPRA和CRISPRi,可以查询JIA风险单倍型,以确定疾病驱动变异的合理候选者。一旦识别出这些候选变体,靶基因可以使用由包含风险单倍型的3D染色质结构告知的CRISPRi来鉴定。
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: 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: 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.
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.