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Single Cell Phylogenetic Fate Mapping: Combining Microsatellite and Methylation Sequencing for Retrospective Lineage Tracing

  • Author(s): Wei, Christopher Jen-Yue;
  • Advisor(s): Zhang, Kun;
  • Bafna, Vineet
  • et al.
Abstract

Retrospective lineage tracing has the potential to answer many outstanding questions in the fields of developmental and cancer biology. The first implementation of lineage tracing, also known as phylogenetic fate mapping, was through the meticulous visual tracking of C elegans development using light microscopy. Throughout the decades, newer methods have been developed to harness emerging next generation sequencing technologies to determine lineage of cells. This was usually done by analyzing naturally occurring mutations in the genome that acted as historical markers for cell division. One group of such highly targeted markers was microsatellites, short tandem repeats in known locations found throughout the human genome. However, the study of microsatellites, particularly at the single cell level has proven especially difficult. This was due to the fact that microsatellites could mutate in vitro in similar ways as in vivo, thus introducing immense amounts of noise. In addition, once lineage was determined using microsatellite loci, there was no way to determine the corresponding cell type analyzed.

In order to tackle these challenges and current limitations, we have developed a novel method for highly accurate microsatellite calling and simultaneous cell type determination: RETrace. In this thesis, I will discuss the current issues of in vitro polymerase slippage, which we have quantified to introduce orders of magnitude more mutations per replication than natural cell division. To overcome the challenge of amplifying single cell genomes that current microsatellite methods have encountered, we developed a novel method of linear whole genome amplification. At the same time, the original methylation signal and thus cell type epigenetic information was preserved. We demonstrate that RETrace achieved higher accuracy and higher cell division resolution than any previous retrospective lineage tracing method. All of this, with the added information of cell type. Finally, we discuss future efforts to utilize RETrace for further investigation of human development, particularly in the brain.

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