Bioinformatic approaches for investigating the impact of 16p11.2 deletion in the developing neocortex
Abstract/Contents
- Abstract
- An estimated 1 in 59 children is diagnosed with autism spectrum disorder (ASD), a neurodevel- opmental condition associated with behavioral alterations and atypical neural connectivity. Research suggests that ASD risk factors acting at mid-gestation may bias the brain towards an abnormal developmental trajectory. Of the genetic risks for autism, 16p11.2 deletion is among the most common, accounting for up to 1% of genetic ASD cases. I hypothesized that loss of 16p11.2 region genes alters the transcriptome of cell types in the developing brain. In addition to genetic risks for ASD, immune events during pregnancy are increasingly impli- cated in ASD etiology. For example, children who are born to mothers who were diagnosed with an infection during pregnancy are at higher risk of developing ASD. Our lab has modeled the effects of midgestational immune events in mice at a time window that coincides with the development of cortical structures implicated in ASD, and finds a selective loss of Satb2-ex- pressing callosal projection neurons. Existing epidemiological studies demonstrate that the neurodevelopmental outcome of infants affected by both a collection of ASD risk CNVs and MIA are worse than either insult alone. Given the overlap in cell types affected by MIA and 16p11.2 CNV, I hypothesized that the effects of 16p11.2 deletion on the developing brain may be modulated by the addition of another common ASD risk factor in a manner that may be unique to that combination of risks. I will present work demonstrating in both human and mouse models that heterozygous loss of 16p11.2 region gene transcripts alters the transcriptome of the developing brain and creates vulnerability to MIA. In Chapter 1, I will use mRNA-Seq to describe the transcriptional impact of 16p11.2 deletion in a model of early human neuroepithelium derived from a novel resource of human induced pluripotent stem cells (iPSC). In Chapter 2, I will use single cell mRNA- Seq (scRNA-Seq) to observe the impact to transcription and fate choice in a mouse model of 16p11.2 deletion. Finally, in Chapter 3, I will leverage this scRNA-Seq model to examine how these effects are modulated by MIA. In addition to this work, I will present two novel tools. First, I describe a method to leverage sequencing data to assist quality control in the generation of iPSC lines. Next, I demonstrate that it is possible to demultiplex pooled scRNA-Seq samples on the basis of sex gene expression. I conclude by proposing new research directions for the study of 16p11.2 biology that emerge from my research that will assist the field in efficiently determining the relationship between 16p11.2 deletion and the development of ASD.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2019; ©2019 |
| Publication date | 2019; 2019 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Muench, Kristin Lynn | |
|---|---|---|
| Degree supervisor | Palmer, Theo | |
| Thesis advisor | Palmer, Theo | |
| Thesis advisor | Kundaje, Anshul, 1980- | |
| Thesis advisor | Wysocka, Joanna, Ph. D | |
| Thesis advisor | Wyss-Coray, Anton | |
| Degree committee member | Kundaje, Anshul, 1980- | |
| Degree committee member | Wysocka, Joanna, Ph. D | |
| Degree committee member | Wyss-Coray, Anton | |
| Associated with | Stanford University, Neurosciences Program. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Kristin Lynn Muench. |
|---|---|
| Note | Submitted to the Neurosciences Program. |
| Thesis | Thesis Ph.D. Stanford University 2019. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2019 by Kristin Lynn Muench
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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