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C. elegans Models of ASD-Associated Missense Variants

Citation

Wong, Wan-Rong (2021) C. elegans Models of ASD-Associated Missense Variants. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/y9gj-y034. https://resolver.caltech.edu/CaltechTHESIS:03112021-005902753

Abstract

The evolving next-generation sequencing technology accelerates the identification of disease-associated genetic variants. However, interpretation of these variants remains challenging, especially variants with subtle effects such as missense variants. Missense variants account for a large proportion of genetic variants in human diseases, including autism spectrum disorder (ASD). The causal relationship of most missense variants in the pathogenesis of ASD has not yet been demonstrated, and an experimental method systematically prioritizing missense alleles can gain crucial insight into the molecular basis for disease pathology. Therefore, I developed an in vivo multi-cellular system using Caenorhabditis elegans to systematically evaluate the functional consequences of disease-associated missense variants. I identified highly conserved human ASD-associated missense variants in their C. elegans orthologs, used a CRISPR/Cas9-mediated homology-directed knock-in strategy to generate missense mutants, and analyzed their impact on behaviors and development via several broad-spectrum assays. Overall, I generated 60 ASD-associated missense variants and characterized these missense mutant strains using a fecundity assay, an automated locomotor tracking system, and a chemotaxis assay. I found that 19% of the human disease-associated alleles have conserved loci in their C. elegans orthologs. Among the genes I tested, 64-70% of the missense variants predicted to perturb protein function showed detectable phenotypic changes in morphology, locomotion, or fecundity. Our results also revealed that missense mutants in different gene networks displayed distinct phenotypic profiles. Moreover, I focused on studying the genetic properties of missense variants on two ASD risk genes. I discovered the developmental defects in the ALDH1A3 C174Y missense mutation involved in the retinoic acid signaling pathway. I also identified a conserved missense residue lin-45(K565N), orthologous to human BRAF(K499N), which displayed a hypersensitive non-dominant phenotype in the diacetyl chemotaxis assay that was capable of being inhibited by RNAi. The finding suggests a potential gain-of-function allele in BRAF, especially in the sensory function. To sum up, I established a working pipeline to systematically identify and generate evolutionarily conserved ASD-associated missense mutants in C. elegans. This approach will help assess the impact of a single missense mutation in the whole organism and prioritize consequential missense variants for further intensive analysis in vertebrate models and human cells.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Autism spectrum disorder; missense variants; C. elegans
Degree Grantor:California Institute of Technology
Division:Biology and Biological Engineering
Major Option:Neurobiology
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Sternberg, Paul W.
Thesis Committee:
  • Prober, David A. (chair)
  • Zinn, Kai George
  • Hong, Elizabeth J.
  • Sternberg, Paul W.
Defense Date:4 February 2021
Funders:
Funding AgencyGrant Number
Simons Foundation367560
NIHT32GM007616
Record Number:CaltechTHESIS:03112021-005902753
Persistent URL:https://resolver.caltech.edu/CaltechTHESIS:03112021-005902753
DOI:10.7907/y9gj-y034
Related URLs:
URLURL TypeDescription
https://doi.org/10.1093/hmg/ddz051DOIArticle adapted for Chapter 2.
https://doi.org/10.17912/micropub.biology.000357DOIArticle adapted for Chapter 4.
ORCID:
AuthorORCID
Wong, Wan-Rong0000-0002-9757-8145
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:14103
Collection:CaltechTHESIS
Deposited By: Wan Rong Wong
Deposited On:23 Mar 2021 15:40
Last Modified:26 Oct 2021 20:53

Thesis Files

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