Inferring Transcriptional and Post-Transcriptional Network Structure by Exploiting Natural Sequence Variation
type: CreativeWork
description: Understanding how cellular processes of an organism translate its genome into its phenotype is one of the grand challenges in biology. Linkage studies seek to identify allelic variants that manifest themselves as phenotypic variation between individuals in a population. The advent of high-throughput genotyping and gene expression profiling technologies has made it possible to use messenger RNA levels as quantitative traits in linkage studies. This has created new opportunities to study genetic variation at the level of gene regulatory networks rather than individual genes. This thesis consists of four parts, each of which outlines a different strategy for integrating genome-wide expression data and genotype data in order to identify transcriptional and post-transcriptional regulatory mechanisms. The data for these analyses comes from segregating populations of Saccharomyces cerevisiae (baker’s yeast) as well as Caenorhabditis elegans (roundworm). The first study focused on inferring the in vitro binding specificity of RNA-binding proteins (RBPs). We first analyzed a recent compendium of in vivo mRNA binding data to model the sequence specificity of 45 yeast RBPs in the form of a position- specific affinity matrix (PSAM). We were able to recover known consensus nucleotide sequences for 12 RBPs and discovered novel binding preferences for 3 of the RBPs namely, Scp160p, Sik1p and Tdh3p. The second study aimed to identify transacting chromosomal loci that regulate expression of a large number of genes. Traditionally, such loci are discovered by first mapping expression quantitative loci (eQTLs) for individual genes, and then looking for so-called “eQTLs hotspots”. Our method avoids the first step by integrating information across all genes, leading to a more elegant method that has increased statistical power. For yeast, we recovered 70% of the reported eQTL hotspots from two independent studies, and discovered a new transacting locus on chromosome V. For worm, we detec…
abstract: Understanding how cellular processes of an organism translate its genome into its phenotype is one of the grand challenges in biology. Linkage studies seek to identify allelic variants that manifest themselves as phenotypic variation between individuals in a population. The advent of high-throughput genotyping and gene expression profiling technologies has made it possible to use messenger RNA levels as quantitative traits in linkage studies. This has created new opportunities to study genetic variation at the level of gene regulatory networks rather than individual genes. This thesis consists of four parts, each of which outlines a different strategy for integrating genome-wide expression data and genotype data in order to identify transcriptional and post-transcriptional regulatory mechanisms. The data for these analyses comes from segregating populations of Saccharomyces cerevisiae (baker’s yeast) as well as Caenorhabditis elegans (roundworm). The first study focused on inferring the in vitro binding specificity of RNA-binding proteins (RBPs). We first analyzed a recent compendium of in vivo mRNA binding data to model the sequence specificity of 45 yeast RBPs in the form of a position- specific affinity matrix (PSAM). We were able to recover known consensus nucleotide sequences for 12 RBPs and discovered novel binding preferences for 3 of the RBPs namely, Scp160p, Sik1p and Tdh3p. The second study aimed to identify transacting chromosomal loci that regulate expression of a large number of genes. Traditionally, such loci are discovered by first mapping expression quantitative loci (eQTLs) for individual genes, and then looking for so-called “eQTLs hotspots”. Our method avoids the first step by integrating information across all genes, leading to a more elegant method that has increased statistical power. For yeast, we recovered 70% of the reported eQTL hotspots from two independent studies, and discovered a new transacting locus on chromosome V. For worm, we detec…
author: Fazlollahi, Mina
language: English
keywords: Biomechanics, Physics, Saccharomyces cerevisiae--Genetics, Caenorhabditis elegans--Genetics, Messenger RNA, RNA-protein interactions, Allelomorphism, Genomes
date published: 2013
date modified: 2026-07-24T01:44:29Z
provider: Columbia University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Columbia University

PropertyValue
property ID: DOI
value: 10.7916/D8XK8DXC