Genetic susceptibility to periodontitis validation using next generation sequencing

Objectives: Periodontal disease is the most common chronic inflammatory disease controlled by bacteria, host and genetic factors. As a step toward identifying the genetic factors, we generated an A/J x BALB/cJ F2 mouse resource population. F2 mice (n=408) were co-infected with Porphyromonas gingivalis and Fusobacterium nucleatum bacteria. Six weeks following infection, alveolar bone loss was quantified by computerized tomography (microCT) to find out the most resistant and susceptible mice to experimental periodontitis. A genome-wide search for Quantitative Trait Loci (QTL) associated with periodontitis was performed and published.
The aim of this study is to explore the host response in these F2 mice by gene expression variation of the periodontal tissue through RNAseq approach using next generation sequencing technologies.
Methods: Periodontal tissues (bone and gingiva) were dissected from the mice and total RNA was extracted using TRIzol reagent (Invitrogen). RNA library was prepared and the samples were run using Trusek RNA kit and Hiseq sequencing machine. The bioinformatics analysis was done using both, Cufflinks and DESeq, systems for significant gene processing. IPA program was used for networking identification.
Results: Using the two systems we found nearly 250 significant genes that were expressed differentially comparing the resistant and susceptible mice. Taking together the results from QTL analysis and gene expression, several networks were suggested with high significance including cell morphology and leukocytes activity.
Conclusions: The bioinformatics analysis of the gene expression in combination with the proposed genes by the QTL analysis reveals unique networks connecting specific genes that are associated to periodontal disease susceptibility. Further study is required to validate the importance of these genes.