Life Sciences Commons^™

A Longitudinal Cline Characterizes The Genetic Structure Of Human Populations In The Tibetan Plateau, Choongwon Jeong, Benjamin M. Peter, Buddha Basnyat, Maniraj Neupane, Geoff Childs, Sienna Craig, John Novembre, Anna Di Rienzo

Dartmouth Scholarship

Indigenous populations of the Tibetan plateau have attracted much attention for their good performance at extreme high altitude. Most genetic studies of Tibetan adaptations have used genetic variation data at the genome scale, while genetic inferences about their de- mography and population structure are largely based on uniparental markers. To provide genome-wide information on population structure, we analyzed new and published data of 338 individuals from indigenous populations across the plateau in conjunction with world- wide genetic variation data. We found a clear signal of genetic stratification across the east- west axis within Tibetan samples. Samples from more eastern locations …

Inferring Condition-Specific Targets Of Human Tf-Tf Complexes Using Chip-Seq Data, Chia-Chun Yang, Min-Hsuan Chen, Sheng-Yi Lin, Erik H. Andrews, Chao Cheng, Jeremy J.W Chen

Dartmouth Scholarship

Background:

Transcription factors (TFs) often interact with one another to form TF complexes that bind DNA and regulate gene expression. Many databases are created to describe known TF complexes identified by either mammalian two-hybrid experiments or data mining. Lately, a wealth of ChIP-seq data on human TFs under different experiment conditions are available, making it possible to investigate condition-specific (cell type and/or physiologic state) TF complexes and their target genes.

Results:

Here, we developed a systematic pipeline to infer Condition-Specific Targets of human TF-TF complexes (called the CST pipeline) by integrating ChIP-seq data and TF motifs. In total, we predicted …

Circnet: A Database Of Circular Rnas Derived From Transcriptome Sequencing Data, Yu-Chen Liu, Jian-Rong Li, Chuan-Hu Sun, Erik Andrews, Rou-Fang Chao, Feng-Mao Lin, Shun-Long Weng, Sheng-Da Hsu, Chieh-Chen Huang, Chao Cheng, Chun-Chi Liu, Hsien-Da Huang

Dartmouth Scholarship

Circular RNAs (circRNAs) represent a new type of regulatory noncoding RNA that only recently has been identified and cataloged. Emerging evidence indicates that circRNAs exert a new layer of post-transcriptional regulation of gene expression. In this study, we utilized transcriptome sequencing datasets to systematically identify the expression of circRNAs (including known and newly identified ones by our pipeline) in 464 RNA-seq samples, and then constructed the CircNet database (http://circnet.mbc.nctu.edu.tw/) that provides the following resources: (i) novel circRNAs, (ii) integrated miRNA-target networks, (iii) expression profiles of circRNA isoforms, (iv) genomic annotations of circRNA isoforms (e.g. 282 948 exon positions), …

Comprehensive Genetic Testing Identifies Targetable Genomic Alterations In Most Patients With Non-Small Cell Lung Cancer, Specifically Adenocarcinoma, Single Institute Investigation, Janani Vigneswaran, Yi-Hung Carol Tan, Septimiu D. Murgu, Brian M. Won, Kathryn Alexa Patton, Victoria M. Villaflor, Philip C. Hoffman, Thomas Hensing, D. Kyle Hogarth, Renuka Malik

Dartmouth Scholarship

This study reviews extensive genetic analysis in advanced non-small cell lung cancer (NSCLC) patients in order to: describe how targetable mutation genes interrelate with the genes identified as variants of unknown significance; assess the percentage of patients with a potentially targetable genetic alterations; evaluate the percentage of patients who had concurrent alterations, previously considered to be mutually exclusive; and characterize the molecular subset of KRAS. Thoracic Oncology Research Program Databases at the University of Chicago provided patient demographics, pathology, and results of genetic testing. 364 patients including 289 adenocarcinoma underwent genotype testing by various platforms such as FoundationOne, Caris Molecular …

Genomic Characterization Of Patient-Derived Xenograft Models Established From Fine Needle Aspirate Biopsies Of A Primary Pancreatic Ductal Adenocarcinoma And From Patient-Matched Metastatic Sites, Robert J. Allaway, Dawn A. Fischer, Francine B. De Abreu, Timothy B. Gardner, Stuart R. Gordon, Richard J. Barth, Thomas A. Colacchio, Matthew Wood, Balint Z. Kacsoh, Stephanie J. Bouley

Dartmouth Scholarship

N-of-1 trials target actionable mutations, yet such approaches do not test genomically-informed therapies in patient tumor models prior to patient treatment. To address this, we developed patient-derived xenograft (PDX) models from fine needle aspiration (FNA) biopsies (FNA-PDX) obtained from primary pancreatic ductal adenocarcinoma (PDAC) at the time of diagnosis. Here, we characterize PDX models established from one primary and two metastatic sites of one patient. We identified an activating KRAS G12R mutation among other mutations in these models. In explant cells derived from these PDX tumor models with a KRAS G12R mutation, treatment with inhibitors of CDKs (including CDK9) reduced …

A Targeted Genetic Association Study Of Epithelial Ovarian Cancer Susceptibility, Madalene Earp, Stacey J. Winham, Nicholas Larson, Jennifer B. Permuth, Hugues Sicotte, Jeremy Chien, Hoda Anton-Culver, Elisa V. Bandera, Andrew Berchuck, Linda S. Cook, Daniel Cramer, Jennifer A. Doherty

Dartmouth Scholarship

BACKGROUND:

Genome-wide association studies have identified several common susceptibility alleles for epithelial ovarian cancer (EOC). To further understand EOC susceptibility, we examined previously ungenotyped candidate variants, including uncommon variants and those residing within known susceptibility loci.

RESULTS:

At nine of eleven previously published EOC susceptibility regions (2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13), novel variants were identified that were more strongly associated with risk than previously reported variants. Beyond known susceptibility regions, no variants were found to be associated with EOC risk at genome-wide statistical significance (p <5x10(-8)), nor were any significant after Bonferroni correction for 17,000 variants (p< 3x10-6).

METHODS:

A customized genotyping array was used to assess over …

Leveraging Global Gene Expression Patterns To Predict Expression Of Unmeasured Genes, James Rudd, René A. Zelaya, Eugene Demidenko, Ellen L. Goode, Casey S. Greene S. Greene, Jennifer A. Doherty

Dartmouth Scholarship

BackgroundLarge collections of paraffin-embedded tissue represent a rich resource to test hypotheses based on gene expression patterns; however, measurement of genome-wide expression is cost-prohibitive on a large scale. Using the known expression correlation structure within a given disease type (in this case, high grade serous ovarian cancer; HGSC), we sought to identify reduced sets of directly measured (DM) genes which could accurately predict the expression of a maximized number of unmeasured genes.

A Forward Genetic Screen Reveals Novel Independent Regulators Of Ulbp1, An Activating Ligand For Natural Killer Cells, Benjamin G Gowen, Bryan Chim, Caleb D. Marceau, Trever T Greene, Patrick Burr, Jeanmarie R. Gonzalez, Charles Hesser, Peter A. Dietzen, Teal Russell, Alexandre Iannello, Laurent Coscoy, Charles L. Sentman

Dartmouth Scholarship

Recognition and elimination of tumor cells by the immune system is crucial for limiting tumor growth. Natural killer (NK) cells become activated when the receptor NKG2D is engaged by ligands that are frequently upregulated in primary tumors and on cancer cell lines. However, the molecular mechanisms driving NKG2D ligand expression on tumor cells are not well defined. Using a forward genetic screen in a tumor-derived human cell line, we identified several novel factors supporting expression of the NKG2D ligand ULBP1. Our results show stepwise contributions of independent pathways working at multiple stages of ULBP1 biogenesis. Deeper investigation of selected hits …

Genome-Wide Meta-Analysis In Alopecia Areata Resolves Hla Associations And Reveals Two New Susceptibility Loci, Regina C. Betz, Lynn Petukhova, Stephan Ripke, Hailiang Huang, Androniki Menelaou, Silke Redeler, Tim Becker, Stefanie Heilmann, Tarek Yamany, Madeleine Duvic, Maria Hordinsky, David Norris, Vera H. Price, Julian Mackay-Wiggan, Annemieke De Jong, Gina M. Destefano, Susanne Moebus, Markus Böhm, Ulrike Blume-Peytavi, Hans Wolff, Gerhard Lutz, Roland Kruse, Li Bian, Christopher I. Amos

Dartmouth Scholarship

Alopecia areata (AA) is a prevalent autoimmune disease with ten known susceptibility loci. Here we perform the first meta-analysis in AA by combining data from two genome-wide association studies (GWAS), and replication with supplemented ImmunoChip data for a total of 3,253 cases and 7,543 controls. The strongest region of association is the MHC, where we fine-map 4 independent effects, all implicating HLA-DR as a key etiologic driver. Outside the MHC, we identify two novel loci that exceed statistical significance, containing ACOXL/BCL2L11(BIM) (2q13); GARP (LRRC32) (11q13.5), as well as a third nominally significant region SH2B3(LNK)/ ATXN2 (12q24.12). Candidate susceptibility gene expression …

Loregic: A Method To Characterize The Cooperative Logic Of Regulatory Factors, Daifeng Wang, Koon-Kiu Yan, Cristina Sisu, Chao Cheng, Joel Rozowsky, William Meyerson, Mark B. Gerstein

Dartmouth Scholarship

The topology of the gene-regulatory network has been extensively analyzed. Now, given the large amount of available functional genomic data, it is possible to go beyond this and systematically study regulatory circuits in terms of logic elements. To this end, we present Loregic, a computational method integrating gene expression and regulatory network data, to characterize the cooperativity of regulatory factors. Loregic uses all 16 possible two-input-one-output logic gates (e.g. AND or XOR) to describe triplets of two factors regulating a common target. We attempt to find the gate that best matches each triplet’s observed gene expression pattern across many conditions. …

Machine Learning Methods Enable Predictive Modeling Of Antibody Feature:Function Relationships In Rv144 Vaccinees, Ickwon Choi, Amy W. Chung, Todd J. Suscovich, Supachai Rerks-Ngarm, Punnee Pitisuttithum, Sorachai Nitayapha, Jaranit Kaewkungwal, Robert J. O'Connell, Donald Francis, Merlin L. Robb, Nelson L. Michael, Jerome H. Kim, Galit Alter, Margaret E. Ackerman, Chris Bailey-Kellogg

Dartmouth Scholarship

The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine …

An Approach For Determining And Measuring Network Hierarchy Applied To Comparing The Phosphorylome And The Regulome, Chao Cheng, Erik Andrews, Koon-Kiu Yan, Matthew Ung, Daifeng Wang, Mark Gerstein

Dartmouth Scholarship

Many biological networks naturally form a hierarchy with a preponderance of downward information flow. In this study, we define a score to quantify the degree of hierarchy in a network and develop a simulated-annealing algorithm to maximize the hierarchical score globally over a network. We apply our algorithm to determine the hierarchical structure of the phosphorylome in detail and investigate the correlation between its hierarchy and kinase properties. We also compare it to the regulatory network, finding that the phosphorylome is more hierarchical than the regulome.

Spectral Gene Set Enrichment (Sgse), H Robert Frost, Zhigang Li, Jason H. Moore

Dartmouth Scholarship

Gene set testing is typically performed in a supervised context to quantify the association between groups of genes and a clinical phenotype. In many cases, however, a gene set-based interpretation of genomic data is desired in the absence of a phenotype variable. Although methods exist for unsupervised gene set testing, they predominantly compute enrichment relative to clusters of the genomic variables with performance strongly dependent on the clustering algorithm and number of clusters. We propose a novel method, spectral gene set enrichment (SGSE), for unsupervised competitive testing of the association between gene sets and empirical data sources. SGSE first computes …

Modeling Neurovascular Coupling From Clustered Parameter Sets For Multimodal Eeg-Nirs, M. Tanveer Talukdar, H. Robert Frost, Solomon G. G. Diamond

Dartmouth Scholarship

Despite significant improvements in neuroimaging technologies and analysis methods, the fundamental relationship between local changes in cerebral hemodynamics and the underlying neural activity remains largely unknown. In this study, a data driven approach is proposed for modeling this neurovascular coupling relationship from simultaneously acquired electroencephalographic (EEG) and near-infrared spectroscopic (NIRS) data. The approach uses gamma transfer functions to map EEG spectral envelopes that reflect time-varying power variations in neural rhythms to hemodynamics measured with NIRS during median nerve stimulation. The approach is evaluated first with simulated EEG-NIRS data and then by applying the method to experimental EEG-NIRS data measured from …

Mapping The Pareto Optimal Design Space For A Functionally Deimmunized Biotherapeutic Candidate, Regina S. Salvat, Andrew S. Parker, Yoonjoo Choi, Chris Bailey-Kellogg, Karl E. Griswold

Dartmouth Scholarship

The immunogenicity of biotherapeutics can bottleneck development pipelines and poses a barrier to widespread clinical application. As a result, there is a growing need for improved deimmunization technologies. We have recently described algorithms that simultaneously optimize proteins for both reduced T cell epitope content and high-level function. In silico analysis of this dual objective design space reveals that there is no single global optimum with respect to protein deimmunization. Instead, mutagenic epitope deletion yields a spectrum of designs that exhibit tradeoffs between immunogenic potential and molecular function. The leading edge of this design space is the Pareto frontier, i.e. the …

Systems Level Analysis Of Systemic Sclerosis Shows A Network Of Immune And Profibrotic Pathways Connected With Genetic Polymorphisms, J. Matthew Mahoney, Jaclyn Taroni, Viktor Martyanov, Tammara A. A. Wood, Casey S. Greene, Patricia A. Pioli, Monique E. Hinchcliff, Michael L. Whitfield

Dartmouth Scholarship

Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6-12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes …

Dprp: A Database Of Phenotype-Specific Regulatory Programs Derived From Transcription Factor Binding Data, David T. W. Tzeng, Yu-Ting Tseng, Matthew Ung, I-En Liao, Chun-Chi Liu, Chao Cheng

Dartmouth Scholarship

Gene expression profiling has been extensively used in the past decades, resulting in an enormous amount of expression data available in public databases. These data sets are informative in elucidating transcriptional regulation of genes underlying various biological and clinical conditions. However, it is usually difficult to identify transcription factors (TFs) responsible for gene expression changes directly from their own expression, as TF activity is often regulated at the posttranscriptional level. In recent years, technical advances have made it possible to systematically determine the target genes of TFs by ChIP-seq experiments. To identify the regulatory programs underlying gene expression profiles, we …

Myeloid Derived Hypoxia Inducible Factor 1-Alpha Is Required For Protection Against Pulmonary Aspergillus Fumigatus Infection, Kelly M. Shepardson, Anupam Jhingran, Alayna Caffrey, Joshua J. Obar, Benjamin T. Suratt, Brent L. Berwin, Tobias M. Hohl, Robert A. Cramer

Dartmouth Scholarship

Hypoxia inducible factor 1α (HIF1α) is the mammalian transcriptional factor that controls metabolism, survival, and innate immunity in response to inflammation and low oxygen. Previous work established that generation of hypoxic microenvironments occurs within the lung during infection with the human fungal pathogen Aspergillus fumigatus. Here we demonstrate that A. fumigatus stabilizes HIF1α protein early after pulmonary challenge that is inhibited by treatment of mice with the steroid triamcinolone. Utilizing myeloid deficient HIF1α mice, we observed that HIF1α is required for survival and fungal clearance early following pulmonary challenge with A. fumigatus. Unlike previously reported research with bacterial …

Methylation Of Leukocyte Dna And Ovarian Cancer: Relationships With Disease Status And Outcome, Brooke L. Fridley, Sebastian M. Armasu, Mine S. Cicek, Melissa C. Larson, Chen Wang, Stacey J. Winham, Kimberly R. Kalli, Devin C. Koestler

Dartmouth Scholarship

Genome-wide interrogation of DNA methylation (DNAm) in blood-derived leukocytes has become feasible with the advent of CpG genotyping arrays. In epithelial ovarian cancer (EOC), one report found substantial DNAm differences between cases and controls; however, many of these disease-associated CpGs were attributed to differences in white blood cell type distributions. We examined blood-based DNAm in 336 EOC cases and 398 controls; we included only high-quality CpG loci that did not show evidence of association with white blood cell type distributions to evaluate association with case status and overall survival.

How To Get The Most From Microarray Data: Advice From Reverse Genomics, Ivan P. Gorlov, Ji-Yeon Yang, Jinyoung Byun, Christopher Logothetis, Olga Y. Gorlova, Kim-Anh Do, Christopher Amos

Dartmouth Scholarship

Whole-genome profiling of gene expression is a powerful tool for identifying cancer-associated genes. Genes differentially expressed between normal and tumorous tissues are usually considered to be cancer associated. We recently demonstrated that the analysis of interindividual variation in gene expression can be useful for identifying cancer associated genes. The goal of this study was to identify the best microarray data–derived predictor of known cancer associated genes. We found that the traditional approach of identifying cancer genes—identifying differentially expressed genes—is not very efficient. The analysis of interindividual variation of gene expression in tumor samples identifies cancer-associated genes more effectively. The results …

Integrated Assessment Of Predicted Mhc Binding And Cross-Conservation With Self Reveals Patterns Of Viral Camouflage, Lu He, Anne S. De Groot, Andres H. Gutierrez, William D. Martin, Lenny Moise, Chris Bailey-Kellogg

Dartmouth Scholarship

Immune recognition of foreign proteins by T cells hinges on the formation of a ternary complex sandwiching a constituent peptide of the protein between a major histocompatibility complex (MHC) molecule and a T cell receptor (TCR). Viruses have evolved means of "camouflaging" themselves, avoiding immune recognition by reducing the MHC and/or TCR binding of their constituent peptides. Computer-driven T cell epitope mapping tools have been used to evaluate the degree to which articular viruses have used this means of avoiding immune response, but most such analyses focus on MHC-facing ‘agretopes'. Here we set out a new means of evaluating the …

Interaction Between Allelic Variations In Vitamin D Receptor And Retinoid X Receptor Genes On Metabolic Traits, Karani S. Vimaleswaran, Alana Cavadino, Diane J. Berry, Massimo Mangino, Peter Andrews, Jason H. Moore

Dartmouth Scholarship

Low vitamin D status has been shown to be a risk factor for several metabolic traits such as obesity, diabetes and cardiovascular disease. The biological actions of 1, 25-dihydroxyvitamin D, are mediated through the vitamin D receptor (VDR), which heterodimerizes with retinoid X receptor, gamma (RXRG). Hence, we examined the potential interactions between the tagging polymorphisms in the VDR (22 tag SNPs) and RXRG (23 tag SNPs) genes on metabolic outcomes such as body mass index, waist circumference, waist-hip ratio (WHR), high- and low-density lipoprotein (LDL) cholesterols, serum triglycerides, systolic and diastolic blood pressures and glycated haemoglobin in the 1958 …

Gene And Protein Sequence Optimization For High-Level Production Of Fully Active And Aglycosylated Lysostaphin In Pichia Pastoris, Hongliang Zhao, Kristina Blazanovic, Yoonjoo Choi, Chris Bailey-Kellogg, Karl E. Griswold

Dartmouth Scholarship

Lysostaphin represents a promising therapeutic agent for the treatment of staphylococcal infections, in particular those of methicillin-resistant Staphylococcus aureus (MRSA). However, conventional expression systems for the enzyme suffer from various limitations, and there remains a need for an efficient and cost-effective production process to facilitate clinical translation and the development of nonmedical applications. While Pichia pastoris is widely used for high-level production of recombinant proteins, there are two major barriers to the production of lysostaphin in this industrially relevant host: lack of expression from the wild-type lysostaphin gene and aberrant glycosylation of the wild-type protein sequence. The first barrier can …

Trip/Nopo E3 Ubiquitin Ligase Promotes Ubiquitylation Of Dna Polymerase Η, Heather A. Wallace, Julie A. Merkle, Michael C. Yu, Taloa G. Berg, Ethan Lee, Giovanni Bosco, Laura A. Lee

Dartmouth Scholarship

We previously identified a Drosophila maternal effect-lethal mutant named ‘no poles’ (nopo). Embryos from nopo females undergo mitotic arrest with barrel-shaped, acentrosomal spindles during the rapid cycles of syncytial embryogenesis because of activation of a Chk2-mediated DNA checkpoint. NOPO is the Drosophila homolog of human TNF receptor associated factor (TRAF)-interacting protein (TRIP), which has been implicated in TNF signaling. NOPO and TRIP contain RING domains closely resembling those of known E3 ubiquitin ligases. We herein sought to elucidate the mechanism by which TRIP/NOPO promotes genomic stability by performing a yeast two-hybrid screen to identify potential substrates/interactors. We identified members of …

Recurrent Tissue-Specific Mtdna Mutations Are Common In Humans, David C. Samuels, Chun Li, Bingshan Li, Zhuo Song, Eric Torstenson, Hayley Boyd Clay, Antonis Rokas, Tricia A. Thornton-Wells, Jason H. Moore, Tia M. Hughes, Robert D. Hoffman, Jonathan L. Haines, Deborah G. Murdock, Douglas P. Mortlock, Scott M. Williams

Dartmouth Scholarship

Mitochondrial DNA (mtDNA) variation can affect phenotypic variation; therefore, knowing its distribution within and among individuals is of importance to understanding many human diseases. Intra-individual mtDNA variation (heteroplasmy) has been generally assumed to be random. We used massively parallel sequencing to assess heteroplasmy across ten tissues and demonstrate that in unrelated individuals there are tissue-specific, recurrent mutations. Certain tissues, notably kidney, liver and skeletal muscle, displayed the identical recurrent mutations that were undetectable in other tissues in the same individuals. Using RFLP analyses we validated one of the tissue-specific mutations in the two sequenced individuals and replicated the patterns in …

A Unified Framework Integrating Parent-Of-Origin Effects For Association Study, Feifei Xiao, Jianzhong Ma, Christopher I. I. Amos

Dartmouth Scholarship

Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting is related to several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we generalize the natural and orthogonal interactions (NOIA) framework to allow for estimation of both main allelic effects and POEs. We develop a statistical (Stat-POE) model that has the orthogonal estimates of parameters including …

Discovering Chromatin Motifs Using Faire Sequencing And The Human Diploid Genome, Chia-Chun Yang, Michael J. Buck, Min-Hsuan Chen, Yun-Fan Chen, Hsin-Chi Lan, Jeremy J.W Chen, Chao Cheng, Chun-Chi Liu

Dartmouth Scholarship

Background: Specific chromatin structures are associated with active or inactive gene transcription. The gene regulatory elements are intrinsically dynamic and alternate between inactive and active states through the recruitment of DNA binding proteins, such as chromatin-remodeling proteins. Results: We developed a unique genome-wide method to discover DNA motifs associated with chromatin accessibility using formaldehyde-assisted isolation of regulatory elements with high-throughput sequencing (FAIRE-seq). We aligned the FAIRE-seq reads to the GM12878 diploid genome and subsequently identified differential chromatin-state regions (DCSRs) using heterozygous SNPs. The DCSR pairs represent the locations of imbalances of chromatin accessibility between alleles and are ideal to reveal …

Key Genes For Modulating Information Flow Play A Temporal Role As Breast Tumor Coexpression Networks Are Dynamically Rewired By Letrozole, Nadia M. Penrod, Jason H. Moore

Dartmouth Scholarship

Genes do not act in isolation but instead as part of complex regulatory networks. To understand how breast tumors adapt to the presence of the drug letrozole, at the molecular level, it is necessary to consider how the expression levels of genes in these networks change relative to one another. Using transcriptomic data generated from sequential tumor biopsy samples, taken at diagnosis, following 10-14 days and following 90 days of letrozole treatment, and a pairwise partial orrelation statistic, we build temporal gene coexpression networks. We characterize the structure of each network and identify genes that hold prominent positions for maintaining …

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.

The Tlo Proteins Are Stoichiometric Components Of Candida Albicans Mediator Anchored Via The Med3 Subunit, Anda Zhang, Kostadin O. Petrov, Emily R. Hyun, Zhongle Liu, Scott A. Gerber, Lawrence C. Myers

Dartmouth Scholarship

The amplification of the TLO (for telomere-associated) genes in Candida albicans, compared to its less pathogenic, close relative Candida dubliniensis, suggests a role in virulence. Little, however, is known about the function of the Tlo proteins. We have purified the Mediator coactivator complex from C. albicans (caMediator) and found that Tlo proteins are a stoichiometric component of caMediator. Many members of the Tlo family are expressed, and each is a unique member of caMediator. Protein expression analysis of individual Tlo proteins, as well as the purification of tagged Tlo proteins, demonstrate that there is a large free population of Tlo …