Direct dissection of genomic features determining transcription factor binding, and systematic characterization of long noncoding RNAs, which are associated with an increased risk of aggressive periodontitis

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Periodontitis (PD) is among the most common inflammatory diseases worldwide with a heritability of 50%. It affects human populations at prevalence rates of 11% for the severe forms. The oral inflammation can affect large areas of the periodontal tissues and can thus pose a substantial stress for the immune system. Detailed knowledge of the precise genetic molecular biological mechanisms that drive the individual steps in the pathogenesis of PD is currently missing. To identify major susceptibility genes of PD, we performed a large genome-wide association study (GWAS) with aggressive periodontitis (AgP), the most severe and early-onset disease phenotype of PD. By integrating our imputed GWAS data together with variants in strong linkage disequilibrium to the most suggestive GWAS lead-polymorphisms with data of the ENCODE (Encyclopedia of DNA Elements) consortium on cell type specific genomic features, we identified putative causative variants (PCVs) that are highly suggestive to have a regulatory role in gene expression. To establish their causality and function, we formulated the following aims of research. (1) Dissection of the functional impacts of the effect alleles of the nominated PCVs on protein-DNA binding by EMSA (electrophoretic mobility shift assays). (2) To provide evidence for the direct effects of the PCVs on gene expression, we will design chromosomally integrated reporter assays in immortalized gingival and lymphoblast cell lines. (3) Following overexpression of the identified transcription factors, we will validate the predicted target genes of the PCVs by quantitative expression profiling and protein blotting. In addition, we will characterize the three most suggestive AgP-associated long noncoding RNAs (lncRNAs) by CRISPR-dCas9 activation and RACE-PCR (rapid amplification of cDNA-ends) in primary cells of blood and the gingiva, followed by whole transcriptome mRNA sequencing. The genes that are regulated by the lncRNA will be validated by protein blotting. The generated data will aggregate the AgP-associated lncRNA into etiological relevant gene networks and will substantially contribute to identify and characterize key PCVs and their effects on signaling pathways that drive the disease risk of AgP.