Improved Structural Variation Detection Facilitates the Discovery of Somatic Mutations in Single Post-Mitotic Neurons 699 views

The extent and origin of somatic cell genome diversity is a question of central importance to human biology and disease, and one about which surprisingly little is known. Somatic mutations are involved in tumor formation, are implicated in many developmental and neurological diseases, and have been suggested as a mechanism driving the vast diversity of morphology and stochastic interconnections exhibited by neurons. Conventional genome-wide methods applied to bulk tissue samples are ill suited for somatic variant detection. Such samples contain diverse cell types and intermixed lineages, making it difficult to distinguish somatic mutational patterns in a specific cell type, or the clonal prevalence of those mutations. Examination of single cell genomes avoids these problems, but current methods lack sensitivity. We make two important methodological improvements to somatic mutation discovery, and use them to study somatic mutations in single post-mitotic neurons. First, we utilize a novel experimental design that allows deep sequencing of single cell genomes by forming clonal cell populations derived by somatic cell nuclear transfer and enculturation. The resultant sequencing data allows investigation of single cell somatic mutations with unprecedented resolution. Second, we improve bioinformatic methods for the detection of structural variation. Due to the complexity of structural variants, methods for their discovery have lagged behind those used to identify single nucleotide polymorphisms and small insertions and deletions. Improvements in these methods are useful in general. But they are particularly important for the study of post-mitotic neurons, as we wish to investigate the long proposed hypotheses that the diversity in neuronal morphology and connectivity patterns may be due to structural variations akin to V(D)J recombination in the immune system and/or high levels of mobile element transposition. By applying these two new methods, we find that each neuronal genome harbors hundreds of private somatic mutations that likely arose during late development or post-mitotic aging, and that many somatic structural variants are complex events defined by multiple clustered breakpoints. We also demonstrate that neither programmed or recurrent mutations, nor mobile element insertions, are likely to be a major mutational force shaping neuronal genome diversity.

PHD (Doctor of Philosophy)

Bioinformatics; Genomics; Computational Biology

English

All rights reserved (no additional license for public reuse)

2015-04-29