Measuring Transcription Directly From Our Chromosomes

Loading...
Thumbnail Image
Degree type
Doctor of Philosophy (PhD)
Graduate group
Bioengineering
Discipline
Subject
Chromosomes
fluorescence microscopy
RNA FISH
Single nucleotide variants
Translocations
Biomedical
Cell Biology
Funder
Grant number
License
Copyright date
2014-08-21T20:13:00-07:00
Distributor
Related resources
Contributor
Abstract

Our genome is organized into DNA segments called chromosomes. Alterations to the typically invariant number and composition of chromosomes are hallmarks of serious disease like cancer. Understanding how rearranging chromosomes affects chromosomal behavior and ultimately leads to disease requires chromosome-specific gene expression measurements, but current tools are insufficient. This thesis describes tools for measuring transcription while discriminating which copy of a gene the RNA comes from. The ability to take these measurements in single cells enabled us to measure changes in transcription on translocated chromosomes or from the maternal vs. paternal chromosomes. Firstly, we introduce intron chromosomal expression FISH (iceFISH), a multiplex imaging method for measuring transcription and chromosome structure simultaneously on single chromosomes. We find substantial differences in transcriptional frequency between genes on a translocated chromosome and the same genes in their normal chromosomal context in the same cell. Correlations between genes on a single chromosome pointed toward a cis chromosome-level transcriptional interaction spanning 14.3 megabases. Chromosomes also come in nearly identical pairs and gene expression is a mixture of RNA transcribed from the maternal or paternal copies. The infrequent sequence differences between parental copies can have serious implications for the viability of cell or organism but detecting single nucleotide differences is difficult, making these behaviors nearly impossible to study in detail. We present a high efficiency fluorescence in situ hybridization method for detecting single nucleotide variants (SNVs) on individual RNA transcripts, both exonic and intronic. We used this method to quantify allelic expression at the population and single cell level, and also to distinguish maternal from paternal chromosomes in single cells. The findings we present in this thesis have far-reaching implications for understanding the transcriptional effects of translocations, and the tools described in this thesis are widely applicable to studying gene regulation and developing in vitro diagnostics.

Advisor
Arjun Raj
Andrew Tsourkas
Date of degree
2013-01-01
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Recommended citation