Genetics at superresolution : mapping natural genetic variation to single nucoleotides and hacking a genome sequencer
Abstract/Contents
- Abstract
- Uri Alon often asks his audiences if they consider themselves to be theorists or experimentalists. However, these narrow tribal affiliations create artificial boundaries. Since Salvador Luria and Max Delbruck and the early days of the phage group, the foundational discoveries in molecular biology have frequently arisen from a combination of theory and experiment. This thesis aspires to continue this long and storied history, with a new twist. We are living in an era where exponential growth in sequencing output is unlocking powerful new genomic assays. Our ability to observe the molecular constituents of a cell is becoming ever more comprehensive and precise. However, the new possibilities enabled by this technology require special care. More data does not beget greater understanding. One should not simply "sequence everything." New technology is best used in service of answering a fundamental biological question, rather than as an end in itself. The chapters of this thesis touch on many disparate biological domains, including RNA biology, quantitative genetics, and experimental evolution. My humble hope is that perhaps the one thread that ties these topics together is the mix of classical sensibilities and cutting edge technology. In the first chapter, a new technology drives biological insight into an exhaustively studied model RNA-binding protein (RBP), Vts1. Though Vts1 has been assayed with numerous existing methods for interrogating RBPs and their substrates, we developed a new comprehensive genomic assay that possesses unique advantages. First, our assay provided direct transcriptome-wide measurements of a biophysical parameter iv (binding affinity) that is lost in traditional sequencing based assays. We linked binding affinity to RNA sequence, structure, and phenotypic outcomes, providing a detailed portrait of structure and function. Our assay also revealed hundreds of low-abundance Vts1 substrates missed by other methods and implicated Vts1 in the 'birth' of new genes. Lastly, our unpublished data links the prionogenic properties of full-length Vts1 to diverse biophysical consequences. The second chapter provides an example of theory guiding experiment. Through extensive modeling, we conceived of an inbred yeast cross that could enable accurate identification of causal variants within an extensive background of passenger mutations. We put our theory into practice by mapping hundreds of causal variants across dozens of heritable traits. This systematic super-resolution fine-mapping revealed a mix of missense, synonymous, and cis-regulatory mutations that collectively gave rise to phenotypic diversity. Our data also systematically unmasked complex genetic architectures, revealing that multiple closely linked driver mutations frequently act on the same quantitative trait. The ability to systematically identify the individual polymorphisms that give rise to quantitative traits provides new possibilities for understanding the relationship between genetic variation and phenotypic diversity on a genome-wide scale. The third chapter describes the strategies by which highly mutated cells evolve and proliferate. We conducted an experimental evolution experiment in S. cerevisiae in a parental genotype engineered to mutate at ~1000x the rate of wild type cells. Richard Lenski's famous long-term evolution experiment has taken decades to accumulate several hundred mutations in E. coli. In contrast, by intentionally designing a hypermutator phenotype that cannot be reverted, our lines accumulated thousands of mutations over several months -- the equivalent of over a million generations of evolution for wild-type yeast. By bottlenecking the cells every 25 generations, we promoted evolution by drift, and observed a monotonic fitness decline in all parallel lineages. However, despite acquiring completely distinct mutations, we characterized a shared transcriptional response to mutation burden. The highly mutated cells also exhibited shared chemical sensitivities, suggested new routes towards treating highly robust and mutagenic pathogens and tumors. Lastly, by employing accelerated evolution in laboratory settings, we observed nascent sterility and speciation phenotypes arising. Most quantitative evolution focuses on the fate of single mutations, while phylogenetic trees give us a portrait of evolution between distant species. Our hypermutator lineages provide a unique opportunity to study evolution at the meso-scale, with all the benefits of parallel passages from the same starting point and a living fossil record of all intermediate stages of evolution. The final chapter pays homage to my scientific grandmother Susan Lindquist, whose influential work on Hsp90 provides the intellectual inspiration for the manuscript. In this chapter, we show that the striking parallelism between the biochemical functions of protein chaperone Hsp90 and RNA chaperone Lhp1 extends to their effects on naturally arising mutations. Like Hsp90, Lhp1 buffers and potentiates numerous mutations in wild strains of S. cerevisiae. In so doing, it transforms the folding landscape of its substrate RNAs and prevents misfolded species from permanently residing in unresolvable kinetic traps. Our findings underscore the ability for non-coding mutations to act as drivers of phenotypic change by tuning gene expression. Lastly, the capacity for RNA chaperones to resolve the intrinsic kinetic defects of RNA folding provides a link between the origin of macromolecules and eukaryotic life.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | She, Richard | |
|---|---|---|
| Associated with | Stanford University, Department of Chemical and Systems Biology. | |
| Primary advisor | Jarosz, Daniel | |
| Thesis advisor | Jarosz, Daniel | |
| Thesis advisor | Das, Rhiju | |
| Thesis advisor | Feldman, Marcus W | |
| Thesis advisor | Ferrell, James Ellsworth | |
| Advisor | Das, Rhiju | |
| Advisor | Feldman, Marcus W | |
| Advisor | Ferrell, James Ellsworth |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Richard She. |
|---|---|
| Note | Submitted to the Department of Chemical and Systems Biology. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Richard She
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...