Identifying Variants in Neuroligin Pathway Genes Using Next Generation Sequencing Technologies Open Access

Steinberg, Karyn Meltz (2009)

Permanent URL: https://etd.library.emory.edu/concern/etds/mg74qm33r?locale=en
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Abstract

The fields of population genomics and evolutionary quantitative genetics provide a
framework in which one can best pursue the heritable component of complex human
phenotypes. A central challenge lies in the comprehensive ascertainment of all the
relevant genomic variation, irrespective of their population frequency, in a large
collection of human samples. Autism Spectrum Disorder (ASD) is a complex human
neurodevelopmental disorder, characterized by a high heritability and a nearly 4:1 male
excess. Applying this comprehensive genomic variation detection paradigm poses two
main challenges. The first lies in developing and applying technologies that can
efficiently detect the relevant genomic variation. The second lies in applying these
methods in the context of a testable genetic hypothesis that might elucidate the etiology
of ASD. Here I report on a series of studies that have pursued both of these challenges.
While sequencing technologies have advanced rapidly in the past decade, the ability to
rapidly isolated target DNA for sequencing has lagged. I first describe a novel technique
for isolating target DNA for downstream resequencing applications. This protocol, named
Microarray-based Genomic Selection, is able to efficiently select user-defined sequence
that is then hybridized to resequencing arrays. Two experiments that used Microarray-
based Genomic Selection for resequencing are described. In the first experiment the
technology was used to isolate all of the exons on the X chromosome, while the second
experiment used it to isolate specific genes in the neuroligin pathway that are
hypothesized to contribute to ASD. Advantages and limitations of MGS are discussed. To
address the genetic basis of ASD, I first selected X-linked neuroligin pathway genes
thought to harbor ASD susceptibility alleles that may help explain the male excess in
ASD. Using samples of male individuals with ASD obtained from the Autism Genetic
Resource Exchange (AGRE), I performed paired-end multiplexed sequencing on the
Illumina Genome Analyzer to comprehensively sequence the genomic regions containing
the neuroligin pathway genes. This study identified a series of candidate variants that
may contribute to ASD susceptibility. Finally, I will highlight the importance of using
quantitative evolutionary genetics when analyzing and interpreting sequence data.

Table of Contents


DISTRIBUTION AGREEMENT
APPROVAL SHEET
ABSTRACT COVER PAGE
ABSTRACT
COVER PAGE
ACKNOWLEDGEMENTS
TABLE OF CONTENTS
TABLES
FIGURES

I. Introduction
I.I. Quantitative genetics and complex disease
I.I.1. Evolutionary quantitative genetics
I.I.2. Common Disease Common Variant hypothesis
I.I.3. Common Disease Rare Variant hypothesis
I.II. Autism as a complex trait
I.II.1. Patterns of inheritance
I.II.2. The X chromosome and Cognitive Disorders
I.III. Development of sequencing technologies
I.III.1. First generation technology
I.III.2. Second generation technology
I.III.3. Third generation technology
I.IV. Scope of thesis
I.V. Figure Legends
I.VI. Figures

1. Chapter 1
1.1. Abstract
1.2. Text
1.3. Figure Legends
1.4. Supplementary Methods
1.5. Tables
1.6. Figures

2. Chapter 2
2.1. Introduction
2.2. Results
2.2.1. Statistical analysis of MGS probes
2.2.2. Chip redesign
2.3. Discussion
2.4. Methods
2.5. Figure Legends
2.6. Figures


3. Chapter 3

3.1. Introduction
3.1.1. Association of autism with neuroligin genes
3.1.2. Evolutionary history of neuroligins
3.1.3. Mouse models
3.1.4. Further evidence of Xp22.3 involvement in cognitive disorders
3.2. Results
3.3. Discussion
3.4. Methods
3.4.1. Sample selection
3.4.2. Array design
3.4.3. Target DNA selection and resequencing
3.4.4. Analysis
3.5. Tables
3.6. Figure Legends
3.7. Figures

4. Chapter 4
4.1. Introduction
4.2. Results
4.2.1. Evaluation of Alignment and Assembly Algorithms
4.2.2. Annotation of Variants
4.2.3. Indel Analysis
4.3. Discussion
4.4. Conclusion
4.5. Methods
4.5.1. Sample Selection
4.5.2. Primer Design
4.5.3. Long PCR
4.5.4. Fragmentation
4.5.5. End Repair
4.5.6. Add "A" Bases to 3' End of Fragments
4.5.7. Ligation of Adapters
4.5.8. Size Selection and Enrichment
4.5.9. Cluster Generation and Paired End Multiplexed Sequencing
4.5.10. Data Analysis
4.6. Tables
4.7. Figure Legends
4.8. Figures

5. Conclusion
6. References

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