Life Sciences Commons^™

Alternative Use Of Dna Binding Domains By The Neurospora White Collar Complex Dictates Circadian Regulation And Light Responses, Bin Wang, Xiaoying Zhou, Jennifer J. Loros, Jay C. Dunlap

Dartmouth Scholarship

In the Neurospora circadian system, the White Collar complex (WCC) of WC-1 and WC-2 drives transcription of the circadian pacemaker gene frequency (frq), whose gene product, FRQ, as a part of the FRQ-FRH complex (FFC), inhibits its own expression. The WCC is also the principal Neurospora photoreceptor; WCC-mediated light induction of frq resets the clock, and all acute light induction is triggered by WCC binding to promoters of light-induced genes. However, not all acutely light-induced genes are also clock regulated, and conversely, not all clock-regulated direct targets of WCC are light induced; the structural determinants governing the shift …

Period-1 Encodes An Atp-Dependent Rna Helicase That Influences Nutritional Compensation Of The Neurospora Circadian Clock, Jillian M. Emerson, Bradley M. Bartholomai, Carol S. Ringelberg, Scott E. Baker, Jennifer Loros, Jay Dunlap

Dartmouth Scholarship

Mutants in the period-1 (prd-1) gene, characterized by a recessive allele, display a reduced growth rate and period lengthening of the developmental cycle controlled by the circadian clock. We refined the genetic location of prd-1 and used whole genome sequencing to find the mutation defining it, confirming the identity of prd-1 by rescuing the mutant circadian phenotype via transformation. PRD-1 is an RNA helicase whose orthologs, DDX5 [DEAD (Asp-Glu-Ala-Asp) Box Helicase 5] and DDX17 in humans and DBP2 (Dead Box Protein 2) in yeast, are implicated in various processes, including transcriptional regulation, elongation, and termination, ribosome biogenesis, and mRNA decay. …

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.

Identifying Gene-Gene Interactions That Are Highly Associated With Body Mass Index Using Quantitative Multifactor Dimensionality Reduction (Qmdr), Rishika De, Shefali S. Verma, Fotios Drenos, Emily R. Holzinger

Dartmouth Scholarship

Despite heritability estimates of 40–70% for obesity, less than 2% of its variation is explained by Body Mass Index (BMI) associated loci that have been identified so far. Epistasis, or gene-gene interactions are a plausible source to explain portions of the missing heritability of BMI. Using genotypic data from 18,686 individuals across five study cohorts – ARIC, CARDIA, FHS, CHS, MESA – we filtered SNPs (Single Nucleotide Polymorphisms) using two parallel approaches. SNPs were filtered either on the strength of their main effects of association with BMI, or on the number of knowledge sources supporting a specific SNP-SNP interaction in …

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 …

Yeast Integral Membrane Proteins Apq12, Brl1, And Brr6 Form A Complex Important For Regulation Of Membrane Homeostasis And Nuclear Pore Complex Biogenesis, Museer A. Lone, Aaron E. Atkinson, Christine A. Hodge, Stéphanie Cottier, Fernando Martínez-Montañés, Shelley Maithel, Laurent Mène-Saffrané, Cole Cole, Roger Schneiter

Dartmouth Scholarship

Proper functioning of intracellular membranes is critical for many cellular processes. A key feature of membranes is their ability to adapt to changes in environmental conditions by adjusting their composition so as to maintain constant biophysical proper- ties, including fluidity and flexibility. Similar changes in the biophysical properties of membranes likely occur when intracellular processes, such as vesicle formation and fusion, require dramatic changes in membrane curvature. Similar modifications must also be made when nuclear pore complexes (NPCs) are constructed within the existing nuclear membrane, as occurs during in- terphase in all eukaryotes. Here we report on the role of …

Development Of The Crispr/Cas9 System For Targeted Gene Disruption In Aspergillus Fumigatus, Kevin Fuller, Shan Chen, Jennifer J. Loros, Jay C. Dunlap

Dartmouth Scholarship

Low rates of homologous recombination have broadly encumbered genetic studies in the fungal pathogen Aspergillus fumigatus. The CRISPR/Cas9 system of bacteria has recently been developed for targeted mutagenesis of eukaryotic genomes with high effi- ciency and, importantly, through a mechanism independent of homologous repair machinery. As this new technology has not been developed for use in A. fumigatus, we sought to test its feasibility for targeted gene disruption in this organism. As a proof of principle, we first demonstrated that CRISPR/Cas9 can indeed be used for high-efficiency (25 to 53%) targeting of the A. fu- migatus polyketide synthase gene (pksP), …

The Role Of Visualization And 3-D Printing In Biological Data Mining, Talia L. Weiss, Amanda Zieselman, Douglas P. Hill, Solomon G. Diamond, Li Shen, Andrew J. Saykin, Jason H. Moore

Dartmouth Scholarship

Background:

Biological data mining is a powerful tool that can provide a wealth of information about patterns of genetic and genomic biomarkers of health and disease. A potential disadvantage of data mining is volume and complexity of the results that can often be overwhelming. It is our working hypothesis that visualization methods can greatly enhance our ability to make sense of data mining results. More specifically, we propose that 3-D printing has an important role to play as a visualization technology in biological data mining. We provide here a brief review of 3-D printing along with a case study to …

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 …

Polyq-Dependent Rna–Protein Assemblies Control Symmetry Breaking, Changhwan Lee, Patricia Occhipinti, Amy S. Gladfelter

Dartmouth Scholarship

Dendritic growth in fungi and neurons requires that multiple axes of polarity are established and maintained within the same cytoplasm. We have discovered that transcripts encoding key polarity factors including a formin, Bni1, and a polarisome scaffold, Spa2, are nonrandomly clustered in the cytosol to initiate and maintain sites of polarized growth in the fungus Ashbya gossypii. This asymmetric distribution requires the mRNAs to interact with a polyQ-containing protein, Whi3, and a Pumilio protein with a low-complexity sequence, Puf2. Cells lacking Whi3 or Puf2 had severe defects in establishing new sites of polarity and failed to localize Bni1 protein. Interaction …

Biological Significance Of Photoreceptor Photocycle Length: Vivid Photocycle Governs The Dynamic Vivid-White Collar Complex Pool Mediating Photo-Adaptation And Response To Changes In Light Intensity, Arko Dasgupta, Chen-Hui Chen, Changhwan Lee, Amy S. Gladfelter, Jay C. Dunlap, Jennifer J. Loros

Dartmouth Scholarship

Most organisms on earth sense light through the use of chromophore-bearing photoreceptive proteins with distinct and characteristic photocycle lengths, yet the biological significance of this adduct decay length is neither understood nor has been tested. In the filamentous fungus Neurospora crassa VIVID (VVD) is a critical player in the process of photoadaptation, the attenuation of light-induced responses and the ability to maintain photosensitivity in response to changing light intensities. Detailed in vitro analysis of the photochemistry of the blue light sensing, FAD binding, LOV domain of VVD has revealed residues around the site of photo-adduct formation that influence the stability …

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.

Allelic Polymorphism Of Gigantea Is Responsible For Naturally Occurring Variation In Circadian Period In Brassica Rapa, Qiguang Xie, Ping Lou, Victor Hermand, Rashid Aman

Dartmouth Scholarship

GIGANTEA (GI) was originally identified by a late-flowering mutant in Arabidopsis, but subsequently has been shown to act in circadian period determination, light inhibition of hypocotyl elongation, and responses to multiple abiotic stresses, including tolerance to high salt and cold (freezing) temperature. Genetic mapping and analysis of families of heterogeneous inbred lines showed that natural variation in GI is responsible for a major quantitative trait locus in circadian period in Brassica rapa. We confirmed this conclusion by transgenic rescue of an Arabidopsis gi-201 loss of function mutant. The two B. rapa GI alleles each fully rescued the …

Integrative Analysis Of Survival-Associated Gene Sets In Breast Cancer, Frederick S. Varn, Matthew H. Ung, Shao Ke Lou, Chao Cheng

Dartmouth Scholarship

Patient gene expression information has recently become a clinical feature used to evaluate breast cancer prognosis. The emergence of prognostic gene sets that take advantage of these data has led to a rich library of information that can be used to characterize the molecular nature of a patient’s cancer. Identifying robust gene sets that are consistently predictive of a patient’s clinical outcome has become one of the main challenges in the field. We inputted our previously established BASE algorithm with patient gene expression data and gene sets from MSigDB to develop the gene set activity score (GSAS), a metric that …

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 …

Highly Constrained Intergenic Drosophila Ultraconserved Elements Are Candidate Ncrnas, Andrew D. Kern, Daniel A. Barbash, Joshua Chang Mell, Daniel Hupalo, Amanda Jensen

Dartmouth Scholarship

Eukaryotes contain short (∼80–200 bp) regions that have few or no substitutions among species that represent hundreds of millions of years of evolutionary divergence. These ultraconserved elements (UCEs) are candidates for containing essential functions, but their biological roles remain largely unknown. Here, we report the discovery and characterization of UCEs from 12 sequenced Drosophilaspecies. We identified 98 elements ≥80 bp long with very high conservation across the Drosophila phylogeny. Population genetic analyses reveal that these UCEs are not present in mutational cold spots. Instead we infer that they experience a level of selective constraint almost 10-fold higher compared with …

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 …