Genetics and Genomics Commons^™

Geometric Framework For Evaluating Rare Variant Tests Of Association, Keli Liu, Shannon Fast, Matthew Zawistowski, Nathan L. Tintle

Faculty Work Comprehensive List

The wave of next-generation sequencing data has arrived. However, many questions still remain about how to best analyze sequence data, particularly the contribution of rare genetic variants to human disease. Numerous statistical methods have been proposed to aggregate association signals across multiple rare variant sites in an effort to increase statistical power; however, the precise relation between the tests is often not well understood. We present a geometric representation for rare variant data in which rare allele counts in case and control samples are treated as vectors in Euclidean space. The geometric framework facilitates a rigorous classification of existing rare …

Optimal Methods For Using Posterior Probabilities In Association Testing, Keli Liu, Alexander Luedtke, Nathan L. Tintle

Faculty Work Comprehensive List

Objective: The use of haplotypes to impute the genotypes of unmeasured single nucleotide variants continues to rise in popularity. Simulation results suggest that the use of the dosage as a one-dimensional summary statistic of imputation posterior probabilities may be optimal both in terms of statistical power and computational efficiency; however, little theoretical understanding is available to explain and unify these simulation results. In our analysis, we provide a theoretical foundation for the use of the dosage as a one-dimensional summary statistic of genotype posterior probabilities from any technology. Methods: We analytically evaluate the dosage, mode and the more general set …

The Natural And Orthogonal Interaction (Noia) Models For Quantitative Traits (Qts) And Complex Diseases, Feifei Xiao

Dissertations and Theses (Open Access)

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting.

In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and …

A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer

Computer Science: Faculty Publications and Other Works

RNA-interference has potential therapeutic use against HIV-1 by targeting highly-functional mRNA sequences that contribute to the virulence of the virus. Empirical work has shown that within cell lines, all of the HIV-1 genes are affected by RNAi-induced gene silencing. While promising, inherent in this treatment is the fact that RNAi sequences must be highly specific. HIV, however, mutates rapidly, leading to the evolution of viral escape mutants. In fact, such strains are under strong selection to include mutations within the targeted region, evading the RNAi therapy and thus increasing the virus’ fitness in the host. Taking a phylogenetic approach, we …

Assessing The Impact Of Differential Genotyping Errors On Rare Variant Tests Of Association, Morgan Mayer-Jochimsen, Shannon Fast, Nathan L. Tintle

Faculty Work Comprehensive List

Genotyping errors are well-known to impact the power and type I error rate in single marker tests of association. Genotyping errors that happen according to the same process in cases and controls are known as non-differential genotyping errors, whereas genotyping errors that occur with different processes in the cases and controls are known as differential genotype errors. For single marker tests, non-differential genotyping errors reduce power, while differential genotyping errors increase the type I error rate. However, little is known about the behavior of the new generation of rare variant tests of association in the presence of genotyping errors. In …

Landscape Genetics Of Leaf-Toed Geckos In The Tropical Dry Forest Of Northern Mexico, Christopher Blair, Victor H. Jimenez-Arcos, Fausto R. Mendez De La Cruz, Robert W. Murphy

Publications and Research

Habitat fragmentation due to both natural and anthropogenic forces continues to threaten the evolution and maintenance of biological diversity. This is of particular concern in tropical regions that are experiencing elevated rates of habitat loss. Although less well-studied than tropical rain forests, tropical dry forests (TDF) contain an enormous diversity of species and continue to be threatened by anthropogenic activities including grazing and agriculture. However, little is known about the processes that shape genetic connectivity in species inhabiting TDF ecosystems. We adopt a landscape genetic approach to understanding functional connectivity for leaf-toed geckos (Phyllodactylus tuberculosus) at multiple sites …

How Long Is A Piece Of Loop?, Yoonjoo Choi, Sumeet Agarwal, Charlotte M. Deane

Dartmouth Scholarship

Loops are irregular structures which connect two secondary structure elements in proteins. They often play important roles in function, including enzyme reactions and ligand binding. Despite their importance, their structure remains difficult to predict. Most protein loop structure prediction methods sample local loop segments and score them. In particular protein loop classifications and database search methods depend heavily on local properties of loops. Here we examine the distance between a loop's end points (span). We find that the distribution of loop span appears to be independent of the number of residues in the loop, in other words the separation between …

The Drosophila Interactions Database: Integrating The Interactome And Transcriptome, Thilakam Murali

Wayne State University Dissertations

In this thesis I describe the integration of heterogeneous interaction data for Drosophila into DroID, the Drosophilainteractions database, making it a one-stop public resource for interaction data. I have also made it possible to filter the interaction data using gene expression data to generate context-relevant networks making DroID a one-of-a kind resource for biologists. In the two years since the upgraded DroID has been available, several studies have used the heterogeneous interaction data in DroID to advance our understanding of Drosophila biology thus validating the need for such a resource for biologists. In addition to this, I have identified …

Dissection Of Stress Response Networks Regulating Multiple Stresses In Rice, Rafi Shaik

Dissertations, Master's Theses and Master's Reports - Open

Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes …

A Novel Computational Framework For Transcriptome Analysis With Rna-Seq Data, Yin Hu

Theses and Dissertations--Computer Science

The advance of high-throughput sequencing technologies and their application on mRNA transcriptome sequencing (RNA-seq) have enabled comprehensive and unbiased profiling of the landscape of transcription in a cell. In order to address the current limitation of analyzing accuracy and scalability in transcriptome analysis, a novel computational framework has been developed on large-scale RNA-seq datasets with no dependence on transcript annotations. Directly from raw reads, a probabilistic approach is first applied to infer the best transcript fragment alignments from paired-end reads. Empowered by the identification of alternative splicing modules, this framework then performs precise and efficient differential analysis at automatically detected …

Detection Of Genomic Inversion From Single End Read, Pankaj Ghimire

Master's Theses

Structural Variations (SVs) are genomic rearrangements that include both copy-number variants,such as insertion,deletions, duplications and balanced variants like inversion and translocations. These SVs are getting more attentions for research and investigation because of their role on human phenotype, genetic diseases and genomic rearrangements. Evolution of Next-generation Sequencing has provided golden opportunities to investigate these variants and make their wider and clear spectrum in human genome. This investigation includes identification of type of SVs and their breakpoints at base pair level. For their effective identification and breakpoint resolution, many techniques are devised mainly based on paired end read. With relatively low …

Reconstructability Analysis Of Genetic Loci Associated With Alzheimer Disease, Martin Zwick, Shawn K. Westaway, Stephen Shervais, Patricia L. Kramer

Complex Systems Faculty Publications and Presentations

Reconstructability Analysis (RA) is an information- and graph-theory-based method which has been successfully used in previous genomic studies. Here we apply it to genetic (14 SNPs) and non-genetic (Education, Age, Gender) data on Alzheimer disease in a well-characterized Case/Control sample of 424 individuals. We confirm the importance of APOE as a predictor of the disease, and identify one non-genetic factor, Education, and two SNPs, one in BINI and the other in SORCS1, as likely disease predictors. SORCS1 appears to be a common risk factor for people with or without APOE. We also identify a possible interaction effect between Education and …

Freq-Seq: A Rapid, Cost-Effective, Sequencing-Based Method To Determine Allele Frequencies Directly From Mixed Populations, Lon Chubiz, Ming-Chun Lee, Nigel Delaney, Christopher Marx

Biology Department Faculty Works

No abstract provided.

Evolution Of Nuclear Integrations Of The Mitochondrial Genome In Great Apes And Their Potential As Molecular Markers, Ivan D. Soto-Calderon

LSU New Orleans Theses and Dissertations

The mitochondrial control region (MCR) has played an important role as a population genetic marker in many taxa but sequencing of complete eukaryotic genomes has revealed that nuclear integrations of mitochondrial DNA (numts) are abundant and widespread across many taxa. If left undetected, numts can inflate mitochondrial diversity and mislead interpretation of phylogenetic relationships. Comparative analyses of complete genomes in humans, orangutans and chimpanzees, and preliminary studies in gorillas have revealed high numt prevalence in great apes, but rigorous comparative analyses across taxa have been lacking.

The present study aimed to systematically compare the evolutionary dynamics of MCR numts in …

Classification Of Genomic Sequences By Latent Semantic Analysis, Samuel F. Way

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Evolutionary distance measures provide a means of identifying and organizing related organisms by comparing their genomic sequences. As such, techniques that quantify the level of similarity between DNA sequences are essential in our efforts to decipher the genetic code in which they are written.

Traditional methods for estimating the evolutionary distance separating two genomic sequences often require that the sequences first be aligned before they are compared. Unfortunately, this preliminary step imposes great computational burden, making this class of techniques impractical for applications involving a large number of sequences. Instead, we desire new methods for differentiating genomic sequences that eliminate …

Systems Biology Approaches To Probe Gene Regulation In Bacteria, Diogo F. Troggian Veiga

Dissertations and Theses (Open Access)

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb).

First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses …

Gene Ontology Analysis Of Pairwise Genetic Associations In Two Genome-Wide Studies Of Sporadic Als, Nora Chung Kim, Peter C. Andrews, Folkert W. Asselbergs, H Robert Frost, Scott M. Williams, Brent T. Harris, Cynthia Read, Kathleen D. Askland, Jason H. Moore

Dartmouth Scholarship

It is increasingly clear that common human diseases have a complex genetic architecture characterized by both additive and nonadditive genetic effects. The goal of the present study was to determine whether patterns of both additive and nonadditive genetic associations aggregate in specific functional groups as defined by the Gene Ontology (GO).

Automated Identification Of Binding Sites Forphosphorylated Ligands In Protein Structures, Dario Ghersi, Roberto Sanchez

Interdisciplinary Informatics Faculty Publications

Phosphorylation is a crucial step in many cellular processes, ranging from metabolic reactions involved in energy transformation to signaling cascades. In many instances, protein domains specifically recognize the phosphogroup. Knowledge of the binding site provides insights into the interaction, and it can also be exploited for therapeutic purposes. Previous studies have shown that proteins interacting with phosphogroups are highly heterogeneous, and no single property can be used to reliably identify the binding site. Here we present an energy-based computational procedure that exploits the protein three-dimensional structure to identify binding sites involved in the recognition of phosphogroups. The procedure is validated …

Dna Methylation Arrays As Surrogate Measures Of Cell Mixture Distribution, Eugene Houseman, William P. Accomando, Devin C. Koestler, Brock C. Christensen, Carmen J. Marsit

Dartmouth Scholarship

There has been a long-standing need in biomedical research for a method that quantifies the normally mixed composition of leukocytes beyond what is possible by simple histological or flow cytometric assessments. The latter is restricted by the labile nature of protein epitopes, requirements for cell processing, and timely cell analysis. In a diverse array of diseases and following numerous immune-toxic exposures, leukocyte composition will critically inform the underlying immuno-biology to most chronic medical conditions. Emerging research demonstrates that DNA methylation is responsible for cellular differentiation, and when measured in whole peripheral blood, serves to distinguish cancer cases from controls.

An Integrated Bioinformatics And Computational Biology Approach Identifies New Bh3-Only Protein Candidates, Robert G. Hawley, Yuzhong Chen, Irene Riz, Chen Zeng

Anatomy and Regenerative Biology Faculty Publications

FoxD4L1 is a forkhead transcription factor that expands the neural ectoderm by down-regulating genes that promote the onset of neural differentiation and up-regulating genes that maintain proliferative neural precursors in an immature state. We previously demonstrated that binding of Grg4 to an Eh-1 motif enhances the ability of FoxD4L1 to down-regulate target neural genes but does not account for all of its repressive activity. Herein we analyzed the protein sequence for additional interaction motifs and secondary structure. Eight conserved motifs were identified in the C-terminal region of fish and frog proteins. Extending the analysis to mammals identified a high scoring …

Sparse Integrative Clustering Of Multiple Omics Data Sets, Ronglai Shen, Sijian Wang, Qianxing Mo

Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series

High resolution microarrays and second-generation sequencing platforms are powerful tools to investigate genome-wide alterations in DNA copy number, methylation, and gene expression associated with a disease. An integrated genomic profiling approach measuring multiple omics data types simultaneously in the same set of biological samples would render an integrated data resolution that would not be available with any single data type. In a previous publication (Shen et al., 2009), we proposed a latent variable regression with a lasso constraint (Tibshirani, 1996) for joint modeling of multiple omics data types to identify common latent variables that can be used to cluster patient …

Mtbindingsim: Simulate Protein Binding To Microtubules, Julia T. Philip, Charles H. Pence, Holly V. Goodson

Faculty Publications

Summary: Many protein–protein interactions are more complex than can be accounted for by 1:1 binding models. However, biochemists have few tools available to help them recognize and predict the behaviors of these more complicated systems, making it difficult to design experiments that distinguish between possible binding models. MTBindingSim provides researchers with an environment in which they can rapidly compare different models of binding for a given scenario. It is written specifically with microtubule polymers in mind, but many of its models apply equally well to any polymer or any protein–protein interaction. MTBindingSim can thus both help in training intuition about …

Mechanistic Studies Of A Novel Ppar-Gamma Mutant That Causes Lipodystrophy And Diabetes, Olga Astapova

Wayne State University Dissertations

PPAR-gamma is a nuclear receptor that plays a central role in metabolic regulation by regulating extensive gene expression networks in adipose, liver, skeletal muscle and many other tissues. Human PPAR-gamma mutations are rare and cause a monogenetic form of severe type II diabetes with metabolic syndrome, known as familiar partial lypodystrophy. The E157D PPAR-gamma mutant causes atypical lipodystrophy in a large Canadian kindred, presenting with multiple musculoskeletal, neurological and hematological abnormalities in addition to the classic lipodystrophy features of insulin-resistant diabetes, hypertension and dyslipidemia. This mutation is localized to the p-box of PPAR-gamma, a small region that interacts directly with …

Efficient And Robust Rna-Seq Process For Cultured Bacteria And Complex Community Transcriptomes, Georgia Giannoukos, Dawn M. Ciulla, Katherine Huang, Brian J. Haas, Jacques Izard, Joshua Z. Levin, Jonathan Livny, Ashlee M. Earl, Dirk Gevers, Doyle V. Ward, Chad Nusbaum, Bruce W. Birren, Andreas Gnirke

Department of Food Science and Technology: Faculty Publications

We have developed a process for transcriptome analysis of bacterial communities that accommodates both intact and fragmented starting RNA and combines efficient rRNA removal with strand-specific RNA-seq. We applied this approach to an RNA mixture derived from three diverse cultured bacterial species and to RNA isolated from clinical stool samples. The resulting expression profiles were highly reproducible, enriched up to 40-fold for non-rRNA transcripts, and correlated well with profiles representing undepleted total RNA.

Modeling Protein Expression And Protein Signaling Pathways, Donatello Telesca, Peter Muller, Steven Kornblau, Marc Suchard, Yuan Ji

COBRA Preprint Series

High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The …

A Study Of Correlations Between The Definition And Application Of The Gene Ontology, Yuji Mo

Department of Computer Electronics and Engineering: Dissertations, Theses, and Student Research

When using the Gene Ontology (GO), nucleotide and amino acid sequences are annotated by terms in a structured and controlled vocabulary organized into relational graphs. The usage of the vocabulary (GO terms) in the annotation of these sequences may diverge from the relations defined in the ontology. We measure the consistency of the use of GO terms by comparing GO's defined structure to the terms' application. To do this, we first use synthetic data with different characteristics to understand how these characteristics influence the correlation values determined by various similarity measures. Using these results as a baseline, we found that …

Planning Combinatorial Disulfide Cross-Links For Protein Fold Determination, Fei Xiong, Alan M Friedman, Chris Bailey-Kellogg

Dartmouth Scholarship

Fold recognition techniques take advantage of the limited number of overall structural organizations, and have become increasingly effective at identifying the fold of a given target sequence. However, in the absence of sufficient sequence identity, it remains difficult for fold recognition methods to always select the correct model. While a native-like model is often among a pool of highly ranked models, it is not necessarily the highest-ranked one, and the model rankings depend sensitively on the scoring function used. Structure elucidation methods can then be employed to decide among the models based on relatively rapid biochemical/biophysical experiments.

Assessing The Impact Of Non-Differential Genotyping Errors On Rare Variant Tests Of Association, Scott Powers, Shyam Gopalakrishnan, Nathan L. Tintle

Faculty Work Comprehensive List

Background/Aims: We aim to quantify the effect of non-differential genotyping errors on the power of rare variant tests and identify those situations when genotyping errors are most harmful. Methods: We simulated genotype and phenotype data for a range of sample sizes, minor allele frequencies, disease relative risks and numbers of rare variants. Genotype errors were then simulated using five different error models covering a wide range of error rates. Results: Even at very low error rates, misclassifying a common homozygote as a heterozygote translates into a substantial loss of power, a result that is exacerbated even further as the minor …

Gc-Content Normalization For Rna-Seq Data, Davide Risso, Katja Schwartz, Gavin Sherlock, Sandrine Dudoit

U.C. Berkeley Division of Biostatistics Working Paper Series

Background: Transcriptome sequencing (RNA-Seq) has become the assay of choice for high-throughput studies of gene expression. However, as is the case with microarrays, major technology-related artifacts and biases affect the resulting expression measures. Normalization is therefore essential to ensure accurate inference of expression levels and subsequent analyses thereof.

Results: We focus on biases related to GC-content and demonstrate the existence of strong sample-specific GC-content effects on RNA-Seq read counts, which can substantially bias differential expression analysis. We propose three simple within-lane gene-level GC-content normalization approaches and assess their performance on two different RNA-Seq datasets, involving different species and experimental designs. …

Multiple Testing Of Local Maxima For Detection Of Peaks In Chip-Seq Data, Armin Schwartzman, Andrew Jaffe, Yulia Gavrilov, Clifford A. Meyer

Harvard University Biostatistics Working Paper Series

No abstract provided.