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Item A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies(Springer Nature, 2022) Li, Zilin; Li, Xihao; Zhou, Hufeng; Gaynor, Sheila M.; Selvaraj, Margaret Sunitha; Arapoglou, Theodore; Quick, Corbin; Liu, Yaowu; Chen, Han; Sun, Ryan; Dey, Rounak; Arnett, Donna K.; Auer, Paul L.; Bielak, Lawrence F.; Bis, Joshua C.; Blackwell, Thomas W.; Blangero, John; Boerwinkle, Eric; Bowden, Donald W.; Brody, Jennifer A.; Cade, Brian E.; Conomos, Matthew P.; Correa, Adolfo; Cupples, L. Adrienne; Curran, Joanne E.; de Vries, Paul S.; Duggirala, Ravindranath; Franceschini, Nora; Freedman, Barry I.; Göring, Harald H. H.; Guo, Xiuqing; Kalyani, Rita R.; Kooperberg, Charles; Kral, Brian G.; Lange, Leslie A.; Lin, Bridget M.; Manichaikul, Ani; Manning, Alisa K.; Martin, Lisa W.; Mathias, Rasika A.; Meigs, James B.; Mitchell, Braxton D.; Montasser, May E.; Morrison, Alanna C.; Naseri, Take; O'Connell, Jeffrey R.; Palmer, Nicholette D.; Peyser, Patricia A.; Psaty, Bruce M.; Raffield, Laura M.; Redline, Susan; Reiner, Alexander P.; Reupena, Muagututi'a Sefuiva; Rice, Kenneth M.; Rich, Stephen S.; Smith, Jennifer A.; Taylor, Kent D.; Taub, Margaret A.; Vasan, Ramachandran S.; Weeks, Daniel E.; Wilson, James G.; Yanek, Lisa R.; Zhao, Wei; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; TOPMed Lipids Working Group; Rotter, Jerome I.; Willer, Cristen J.; Natarajan, Pradeep; Peloso, Gina M.; Lin, Xihong; Biostatistics and Health Data Science, School of MedicineLarge-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.Item Cancer Pharmacogenomics and Pharmacoepidemiology: Setting a Research Agenda to Accelerate Translation(Oxford University Press, 2010-10-13) Freedman, Andrew N.; Sansbury, Leah B.; Figg, William D.; Potosky, Arnold L.; Smith, Sheila R. Weiss; Khoury, Muin J.; Nelson, Stefanie A.; Weinshilboum, Richard M.; Ratain, Mark J.; McLeod, Howard L.; Epstein, Robert S.; Ginsburg, Geoffrey S.; Schilsky, Richard L.; Liu, Geoffrey; Flockhart, David A.; Ulrich, Cornelia M.; Davis, Robert L.; Lesko, Lawrence J.; Zineh, Issam; Randhawa, Gurvaneet; Ambrosone, Christine B.; Relling, Mary V.; Rothman, Nat; Xie, Heng; Spitz, Margaret R.; Ballard-Barbash, Rachel; Doroshow, James H.; Minasian, Lori M.; Medicine, School of MedicineRecent advances in genomic research have demonstrated a substantial role for genomic factors in predicting response to cancer therapies. Researchers in the fields of cancer pharmacogenomics and pharmacoepidemiology seek to understand why individuals respond differently to drug therapy, in terms of both adverse effects and treatment efficacy. To identify research priorities as well as the resources and infrastructure needed to advance these fields, the National Cancer Institute (NCI) sponsored a workshop titled “Cancer Pharmacogenomics: Setting a Research Agenda to Accelerate Translation” on July 21, 2009, in Bethesda, MD. In this commentary, we summarize and discuss five science-based recommendations and four infrastructure-based recommendations that were identified as a result of discussions held during this workshop. Key recommendations include 1) supporting the routine collection of germline and tumor biospecimens in NCI-sponsored clinical trials and in some observational and population-based studies; 2) incorporating pharmacogenomic markers into clinical trials; 3) addressing the ethical, legal, social, and biospecimen- and data-sharing implications of pharmacogenomic and pharmacoepidemiologic research; and 4) establishing partnerships across NCI, with other federal agencies, and with industry. Together, these recommendations will facilitate the discovery and validation of clinical, sociodemographic, lifestyle, and genomic markers related to cancer treatment response and adverse events, and they will improve both the speed and efficiency by which new pharmacogenomic and pharmacoepidemiologic information is translated into clinical practice.Item Genetic strategies to detect genes involved in alcoholism and alcohol-related traits(The National Institute on Alcohol Abuse and Alcoholism, 2002) Dick, Danielle M.; Foroud, Tatiana; Medical and Molecular Genetics, School of MedicineResearchers are using a variety of sophisticated approaches to identify genes that contribute to the development of alcoholism in humans or influence other alcohol-related traits. These strategies include linkage approaches, which can identify broad chromosomal regions that are likely to contain genes predisposing to the disorder, and association approaches, which test the association between a particular marker allele and a specific outcome. Animal studies using diverse strategies can also help identify genes or DNA regions that influence alcohol-related traits in humans. The results of these analyses are likely to have implications for fields such as genetic counseling, gene therapy, and pharmacogenetics.Item Genome sequence of Phormia regina Meigen (Diptera: Calliphoridae): implications for medical, veterinary and forensic research(Springer (Biomed Central Ltd.), 2016-10-28) Andere, Anne A.; Platt, Roy N.; Ray, David A.; Picard, Christine J.; Department of Biology, School of ScienceBACKGROUND: Blow flies (Diptera: Calliphoridae) are important medical, veterinary and forensic insects encompassing 8 % of the species diversity observed in the calyptrate insects. Few genomic resources exist to understand the diversity and evolution of this group. RESULTS: We present the hybrid (short and long reads) draft assemblies of the male and female genomes of the common North American blow fly, Phormia regina (Diptera: Calliphoridae). The 550 and 534 Mb draft assemblies contained 8312 and 9490 predicted genes in the female and male genomes, respectively; including > 93 % conserved eukaryotic genes. Putative X and Y chromosomes (21 and 14 Mb, respectively) were assembled and annotated. The P. regina genomes appear to contain few mobile genetic elements, an almost complete absence of SINEs, and most of the repetitive landscape consists of simple repetitive sequences. Candidate gene approaches were undertaken to annotate insecticide resistance, sex-determining, chemoreceptors, and antimicrobial peptides. CONCLUSIONS: This work yielded a robust, reliable reference calliphorid genome from a species located in the middle of a calliphorid phylogeny. By adding an additional blow fly genome, the ability to tease apart what might be true of general calliphorids vs. what is specific of two distinct lineages now exists. This resource will provide a strong foundation for future studies into the evolution, population structure, behavior, and physiology of all blow flies.Item HAPPI: A Bioinformatics Database Platform Enabling Network Biology Studies(2006-06-29T19:05:24Z) Mamidipalli, SudhaRani; Chen, Jake YueThe publication of the draft human genome consisting of 30,000 genes is merely the beginning of genome biology. A new way to understand the complexity and richness of molecular and cellular function of proteins in biological processes is through understanding of biological networks. These networks include protein-protein interaction networks, gene regulatory networks, and metabolic networks. In this thesis, we focus on human protein-protein interaction networks using informatics techniques. First, we performed a thorough literature survey to document different experimental methods to detect and collect protein interactions, current public databases that store these interactions, computational software to predict, validate and interpret protein networks. Then, we developed the Human Annotated Protein-Protein Interaction (HAPPI) database to manage a wealth of integrated information related to protein functions, protein-protein functional links, and protein-protein interactions. Approximately 12900 proteins from Swissprot, 57900 proteins from Trembl, 52186 protein-domains from Swisspfam, 4084 gene-pathways from KEGG, 2403190 interactions from STRING and 51207 interactions from OPHID public databases were integrated into a single relational database platform using Oracle 10g on an IU Supercomputing grid. We further assigned a confidence score to each protein interaction pair to help assess the quality and reliability of protein-protein interaction. We hosted the database on the Discovery Informatics and Computing web site, which is now publicly accessible. HAPPI database differs from other protein interaction databases in these following aspects: 1) It focuses on human protein interactions and contains approximately 860000 high-confidence protein interaction records—one of the most complete and reliable sources of human protein interaction today; 2) It includes thorough protein domain, gene and pathway information of interacting proteins, therefore providing a whole view of protein functional information; 3) It contains a consistent ranking score that can be used to gauge the confidence of protein interactions. To show the benefits of HAPPI database, we performed a case study using Insulin Signaling pathway in collaboration with a biology team on campus. We began by taking two sets of proteins that were previously well studied as separate processes, set A and set B. We queried these proteins against the HAPPI database, and derived high-confidence protein interaction data sets annotated with known KEGG pathways. We then organized these protein interactions on a network diagram. The end result shows many novel hub proteins that connect set A or B proteins. Some hub proteins are even novel members outside of any annotated pathway, making them interesting targets to validate for subsequent biological studies.Item High-throughput cis-regulatory element discovery in the vector mosquito Aedes aegypti(BioMed Central, 2016-05-10) Behura, Susanta K.; Sarro, Joseph; Li, Ping; Mysore, Keshava; Severson, David W.; Emrich, Scott J.; Duman-Scheel, Molly; Department of Medical & Molecular Genetics, IU School of MedicineBACKGROUND: Despite substantial progress in mosquito genomic and genetic research, few cis-regulatory elements (CREs), DNA sequences that control gene expression, have been identified in mosquitoes or other non-model insects. Formaldehyde-assisted isolation of regulatory elements paired with DNA sequencing, FAIRE-seq, is emerging as a powerful new high-throughput tool for global CRE discovery. FAIRE results in the preferential recovery of open chromatin DNA fragments that are not bound by nucleosomes, an evolutionarily conserved indicator of regulatory activity, which are then sequenced. Despite the power of the approach, FAIRE-seq has not yet been applied to the study of non-model insects. In this investigation, we utilized FAIRE-seq to profile open chromatin and identify likely regulatory elements throughout the genome of the human disease vector mosquito Aedes aegypti. We then assessed genetic variation in the regulatory elements of dengue virus susceptible (Moyo-S) and refractory (Moyo-R) mosquito strains. RESULTS: Analysis of sequence data obtained through next generation sequencing of FAIRE DNA isolated from A. aegypti embryos revealed >121,000 FAIRE peaks (FPs), many of which clustered in the 1 kb 5' upstream flanking regions of genes known to be expressed at this stage. As expected, known transcription factor consensus binding sites were enriched in the FPs, and of these FoxA1, Hunchback, Gfi, Klf4, MYB/ph3 and Sox9 are most predominant. All of the elements tested in vivo were confirmed to drive gene expression in transgenic Drosophila reporter assays. Of the >13,000 single nucleotide polymorphisms (SNPs) recently identified in dengue virus-susceptible and refractory mosquito strains, 3365 were found to map to FPs. CONCLUSION: FAIRE-seq analysis of open chromatin in A. aegypti permitted genome-wide discovery of CREs. The results of this investigation indicate that FAIRE-seq is a powerful tool for identification of regulatory DNA in the genomes of non-model organisms, including human disease vector mosquitoes.Item Increased epigenetic age in normal breast tissue from luminal breast cancer patients(Biomed Central, 2018-08-29) Hofstatter, Erin W.; Horvath, Steve; Dalela, Disha; Gupta, Piyush; Chagpar, Anees B.; Wali, Vikram B.; Bossuyt, Veerle; Storniolo, Anna Maria; Hatzis, Christos; Patwardhan, Gauri; Von Wahlde, Marie-Kristin; Butler, Meghan; Epstein, Lianne; Stavris, Karen; Sturrock, Tracy; Au, Alexander; Kwei, Stephanie; Pusztai, Lajos; Medicine, School of MedicineBACKGROUND: Age is one of the most important risk factors for developing breast cancer. However, age-related changes in normal breast tissue that potentially lead to breast cancer are incompletely understood. Quantifying tissue-level DNA methylation can contribute to understanding these processes. We hypothesized that occurrence of breast cancer should be associated with an acceleration of epigenetic aging in normal breast tissue. RESULTS: Ninety-six normal breast tissue samples were obtained from 88 subjects (breast cancer = 35 subjects/40 samples, unaffected = 53 subjects/53 samples). Normal tissue samples from breast cancer patients were obtained from distant non-tumor sites of primary mastectomy specimens, while samples from unaffected women were obtained from the Komen Tissue Bank (n = 25) and from non-cancer-related breast surgery specimens (n = 28). Patients were further stratified into four cohorts: age < 50 years with and without breast cancer and age ≥ 50 with and without breast cancer. The Illumina HumanMethylation450k BeadChip microarray was used to generate methylation profiles from extracted DNA samples. Data was analyzed using the "Epigenetic Clock," a published biomarker of aging based on a defined set of 353 CpGs in the human genome. The resulting age estimate, DNA methylation age, was related to chronological age and to breast cancer status. The DNAmAge of normal breast tissue was strongly correlated with chronological age (r = 0.712, p < 0.001). Compared to unaffected peers, breast cancer patients exhibited significant age acceleration in their normal breast tissue (p = 0.002). Multivariate analysis revealed that epigenetic age acceleration in the normal breast tissue of subjects with cancer remained significant after adjusting for clinical and demographic variables. Additionally, smoking was found to be positively correlated with epigenetic aging in normal breast tissue (p = 0.012). CONCLUSIONS: Women with luminal breast cancer exhibit significant epigenetic age acceleration in normal adjacent breast tissue, which is consistent with an analogous finding in malignant breast tissue. Smoking is also associated with epigenetic age acceleration in normal breast tissue. Further studies are needed to determine whether epigenetic age acceleration in normal breast tissue is predictive of incident breast cancer and whether this mediates the risk of chronological age on breast cancer risk.Item Mining the Plasma Proteome for Insights into the Molecular Pathology of Pulmonary Arterial Hypertension(American Thoracic Society, 2022) Harbaum, Lars; Rhodes, Christopher J.; Wharton, John; Lawrie, Allan; Karnes, Jason H.; Desai, Ankit A.; Nichols, William C.; Humbert, Marc; Montani, David; Girerd, Barbara; Sitbon, Olivier; Boehm, Mario; Novoyatleva, Tatyana; Schermuly, Ralph T.; Ghofrani, H. Ardeschir; Toshner, Mark; Kiely, David G.; Howard, Luke S.; Swietlik, Emilia M.; Gräf, Stefan; Pietzner, Maik; Morrell, Nicholas W.; Wilkins, Martin R.; U.K. National Institute for Health Research BioResource Rare Diseases Consortium; U.K. Pulmonary Arterial Hypertension Cohort Study Consortium; U.S. Pulmonary Arterial Hypertension Biobank Consortium; Medical and Molecular Genetics, School of MedicineRationale: Pulmonary arterial hypertension (PAH) is characterized by structural remodeling of pulmonary arteries and arterioles. Underlying biological processes are likely reflected in a perturbation of circulating proteins. Objectives: To quantify and analyze the plasma proteome of patients with PAH using inherited genetic variation to inform on underlying molecular drivers. Methods: An aptamer-based assay was used to measure plasma proteins in 357 patients with idiopathic or heritable PAH, 103 healthy volunteers, and 23 relatives of patients with PAH. In discovery and replication subgroups, the plasma proteomes of PAH and healthy individuals were compared, and the relationship to transplantation-free survival in PAH was determined. To examine causal relationships to PAH, protein quantitative trait loci (pQTL) that influenced protein levels in the patient population were used as instruments for Mendelian randomization (MR) analysis. Measurements and Main Results: From 4,152 annotated plasma proteins, levels of 208 differed between patients with PAH and healthy subjects, and 49 predicted long-term survival. MR based on cis-pQTL located in proximity to the encoding gene for proteins that were prognostic and distinguished PAH from health estimated an adverse effect for higher levels of netrin-4 (odds ratio [OR], 1.55; 95% confidence interval [CI], 1.16–2.08) and a protective effect for higher levels of thrombospondin-2 (OR, 0.83; 95% CI, 0.74–0.94) on PAH. Both proteins tracked the development of PAH in previously healthy relatives and changes in thrombospondin-2 associated with pulmonary arterial pressure at disease onset. Conclusions: Integrated analysis of the plasma proteome and genome implicates two secreted matrix-binding proteins, netrin-4 and thrombospondin-2, in the pathobiology of PAH.Item Neisseria meningitidis ST11 Complex Isolates Associated with Nongonococcal Urethritis, Indiana, USA, 2015-2016(CDC, 2017-02) Toh, Evelyn; Gangaiah, Dharanesh; Batteiger, Byron E.; Williams, James A.; Arno, Janet N.; Tai, Albert; Batteiger, Teresa A.; Nelson, David E.; Department of Microbiology & Immunology, IU School of MedicineAt a clinic in Indianapolis, Indiana, USA, we observed an increase in Neisseria gonorrhoeae-negative men with suspected gonococcal urethritis who had urethral cultures positive for N. meningitidis. We describe genomes of 2 of these N. meningitidis sequence type 11 complex urethritis isolates. Clinical evidence suggests these isolates may represent an emerging urethrotropic clade.Item Precise genome-editing in human diseases: mechanisms, strategies and applications(Springer Nature, 2024-02-26) Zheng, Yanjiang; Li, Yifei; Zhou, Kaiyu; Li, Tiange; VanDusen, Nathan J.; Hua, Yimin; Pediatrics, School of MedicinePrecise genome-editing platforms are versatile tools for generating specific, site-directed DNA insertions, deletions, and substitutions. The continuous enhancement of these tools has led to a revolution in the life sciences, which promises to deliver novel therapies for genetic disease. Precise genome-editing can be traced back to the 1950s with the discovery of DNA's double-helix and, after 70 years of development, has evolved from crude in vitro applications to a wide range of sophisticated capabilities, including in vivo applications. Nonetheless, precise genome-editing faces constraints such as modest efficiency, delivery challenges, and off-target effects. In this review, we explore precise genome-editing, with a focus on introduction of the landmark events in its history, various platforms, delivery systems, and applications. First, we discuss the landmark events in the history of precise genome-editing. Second, we describe the current state of precise genome-editing strategies and explain how these techniques offer unprecedented precision and versatility for modifying the human genome. Third, we introduce the current delivery systems used to deploy precise genome-editing components through DNA, RNA, and RNPs. Finally, we summarize the current applications of precise genome-editing in labeling endogenous genes, screening genetic variants, molecular recording, generating disease models, and gene therapy, including ex vivo therapy and in vivo therapy, and discuss potential future advances.