Presentations

Abstract

Introduction:

The molecular clock concept serves to monitor the evolution of genes and genetic sequences by measuring their divergence from a shared ancestor over time. A novel model, rooted in CpG methylation and employing smnCAT-seq data, is introduced to effectively discern swift mutations and distinguish between neurons. This model underscores the substantial impact of embryonic neural tissue on methylation patterns, with excitatory neurons originating from the cerebral cortex and inhibitory neurons tracing back to CGE or MGE sources. Our objective is to determine if excitatory and inhibitory neurons have a common ancestor lineage and gain a better understanding of how methylation influences normal brain development.

Methods:

The data encompasses RNAseq and WGBS data derived from individual neurons in the frontal cortex, specifically focusing on single-cell phenotype and epigenome analysis of a 25-year-old individual post- mortem. This dataset, accessible via the GEO database and contributed by the Salk Institute, comprises binary barcodes representing CpG methylation on the X-chromosome in a male patient. Through a Python-based sorting algorithm, the raw methylome data is transformed into an N-by-N barcode matrix. This algorithm facilitates the comparison of methylation barcodes between neurons, each consisting of a minimum of 30 CpG sites. The metric employed for this analysis is the pairwise distance, where identical barcodes exhibit a distance value of "0," while random barcodes yield distances approximately 0.5.

Results:

The preliminary data demonstrates that the neurons that have the most similar methylation patterns originate from the same embryological region, such as excitatory vs excitatory neurons and the neurons that are the most dissimilar are from different regions. Additionally, we found that there were significant differences even between subgroups of inhibitory or exhibitory neurons.

Conclusion:

Statistically significant disparities in pairwise distances are observed between inhibitory and excitatory neurons. These findings highlight the influence of embryological brain tissue location on neuronal methylation patterns. Furthermore, our study underscores the need to investigate various tissue types to assess the viability of CpG methylation as a molecular clock mechanism. In the future, we hope to expand upon our current model by adding additional patients as well as adapting our model for different types of tissues.