IU Indianapolis ScholarWorks :: Browsing by Subject "Genomics"

Browsing by Subject "Genomics"

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3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies
(Public Library of Science, 2021-05-13) Hoskens, Hanne; Liu, Dongjing; Naqvi, Sahin; Lee, Myoung Keun; Eller, Ryan J.; Indencleef, Karlijne; White, Julie D.; Li, Jiarui; Larmuseau, Maarten H. D.; Hens, Greet; Wysocka, Joanna; Walsh, Susan; Richmond, Stephen; Shriver, Mark D.; Shaffer, John R.; Peeters, Hilde; Weinberg, Seth M.; Claes, Peter; Biology, School of Science
The analysis of contemporary genomic data typically operates on one-dimensional phenotypic measurements (e.g. standing height). Here we report on a data-driven, family-informed strategy to facial phenotyping that searches for biologically relevant traits and reduces multivariate 3D facial shape variability into amendable univariate measurements, while preserving its structurally complex nature. We performed a biometric identification of siblings in a sample of 424 children, defining 1,048 sib-shared facial traits. Subsequent quantification and analyses in an independent European cohort (n = 8,246) demonstrated significant heritability for a subset of traits (0.17-0.53) and highlighted 218 genome-wide significant loci (38 also study-wide) associated with facial variation shared by siblings. These loci showed preferential enrichment for active chromatin marks in cranial neural crest cells and embryonic craniofacial tissues and several regions harbor putative craniofacial genes, thereby enhancing our knowledge on the genetic architecture of normal-range facial variation.
5. Collaborative Study on the Genetics of Alcoholism: Functional genomics
(Wiley, 2023) Gameiro-Ros, Isabel; Popova, Dina; Prytkova, Iya; Pang, Zhiping P.; Liu, Yunlong; Dick, Danielle; Bucholz, Kathleen K.; Agrawal, Arpana; Porjesz, Bernice; Goate, Alison M.; Xuei, Xiaoling; Kamarajan, Chella; COGA Collaborators; Tischfield, Jay A.; Edenberg, Howard J.; Slesinger, Paul A.; Hart, Ronald P.; Medical and Molecular Genetics, School of Medicine
Alcohol Use Disorder is a complex genetic disorder, involving genetic, neural, and environmental factors, and their interactions. The Collaborative Study on the Genetics of Alcoholism (COGA) has been investigating these factors and identified putative alcohol use disorder risk genes through genome-wide association studies. In this review, we describe advances made by COGA in elucidating the functional changes induced by alcohol use disorder risk genes using multimodal approaches with human cell lines and brain tissue. These studies involve investigating gene regulation in lymphoblastoid cells from COGA participants and in post-mortem brain tissues. High throughput reporter assays are being used to identify single nucleotide polymorphisms in which alternate alleles differ in driving gene expression. Specific single nucleotide polymorphisms (both coding or noncoding) have been modeled using induced pluripotent stem cells derived from COGA participants to evaluate the effects of genetic variants on transcriptomics, neuronal excitability, synaptic physiology, and the response to ethanol in human neurons from individuals with and without alcohol use disorder. We provide a perspective on future studies, such as using polygenic risk scores and populations of induced pluripotent stem cell-derived neurons to identify signaling pathways related with responses to alcohol. Starting with genes or loci associated with alcohol use disorder, COGA has demonstrated that integration of multimodal data within COGA participants and functional studies can reveal mechanisms linking genomic variants with alcohol use disorder, and potential targets for future treatments.
A Between-Sex Comparison of the Genomic Architecture of Asthma
(American Thoracic Society, 2023) Zein, Joe G.; Bazeley, Peter; Meyers, Deborah; Bleecker, Eugene; Gaston, Benjamin; Hu, Bo; Attaway, Amy; Ortega, Victor; Pediatrics, School of Medicine
A cross-disorder dosage sensitivity map of the human genome
(Elsevier, 2022) Collins, Ryan L.; Glessner, Joseph T.; Porcu, Eleonora; Lepamets, Maarja; Brandon, Rhonda; Lauricella, Christopher; Han, Lide; Morley, Theodore; Niestroj, Lisa-Marie; Ulirsch, Jacob; Everett, Selin; Howrigan, Daniel P.; Boone, Philip M.; Fu, Jack; Karczewski, Konrad J.; Kellaris, Georgios; Lowther, Chelsea; Lucente, Diane; Mohajeri, Kiana; Nõukas, Margit; Nuttle, Xander; Samocha, Kaitlin E.; Trinh, Mi; Ullah, Farid; Võsa, Urmo; Epi25 Consortium; Estonian Biobank Research Team; Hurles, Matthew E.; Aradhya, Swaroop; Davis, Erica E.; Finucane, Hilary; Gusella, James F.; Janze, Aura; Katsanis, Nicholas; Matyakhina, Ludmila; Neale, Benjamin M.; Sanders, David; Warren, Stephanie; Hodge, Jennelle C.; Lal, Dennis; Ruderfer, Douglas M.; Meck, Jeanne; Mägi, Reedik; Esko, Tõnu; Reymond, Alexandre; Kutalik, Zoltán; Hakonarson, Hakon; Sunyaev, Shamil; Brand, Harrison; Talkowski, Michael E.; Medical and Molecular Genetics, School of Medicine
Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.
A Multicenter Analysis of Abnormal Chromosomal Microarray Findings in Congenital Heart Disease
(American Heart Association, 2023) Landis, Benjamin J.; Helvaty, Lindsey R.; Geddes, Gabrielle C.; Lin, Jiuann-Huey Ivy; Yatsenko, Svetlana A.; Lo, Cecilia W.; Border, William L.; Burns Wechsler, Stephanie; Murali, Chaya N.; Azamian, Mahshid S.; Lalani, Seema R.; Hinton, Robert B.; Garg, Vidu; McBride, Kim L.; Hodge, Jennelle C.; Ware, Stephanie M.; Pediatrics, School of Medicine
Background: Chromosomal microarray analysis (CMA) provides an opportunity to understand genetic causes of congenital heart disease (CHD). The methods for describing cardiac phenotypes in patients with CMA abnormalities have been inconsistent, which may complicate clinical interpretation of abnormal testing results and hinder a more complete understanding of genotype–phenotype relationships. Methods and Results: Patients with CHD and abnormal clinical CMA were accrued from 9 pediatric cardiac centers. Highly detailed cardiac phenotypes were systematically classified and analyzed for their association with CMA abnormality. Hierarchical classification of each patient into 1 CHD category facilitated broad analyses. Inclusive classification allowing multiple CHD types per patient provided sensitive descriptions. In 1363 registry patients, 28% had genomic disorders with well‐recognized CHD association, 67% had clinically reported copy number variants (CNVs) with rare or no prior CHD association, and 5% had regions of homozygosity without CNV. Hierarchical classification identified expected CHD categories in genomic disorders, as well as uncharacteristic CHDs. Inclusive phenotyping provided sensitive descriptions of patients with multiple CHD types, which occurred commonly. Among CNVs with rare or no prior CHD association, submicroscopic CNVs were enriched for more complex types of CHD compared with large CNVs. The submicroscopic CNVs that contained a curated CHD gene were enriched for left ventricular obstruction or septal defects, whereas CNVs containing a single gene were enriched for conotruncal defects. Neuronal‐related pathways were over‐represented in single‐gene CNVs, including top candidate causative genes NRXN3, ADCY2, and HCN1. Conclusions: Intensive cardiac phenotyping in multisite registry data identifies genotype–phenotype associations in CHD patients with abnormal CMA.
A research agenda to support the development and implementation of genomics-based clinical informatics tools and resources
(Oxford University Press, 2022) Wiley, Ken; Findley, Laura; Goldrich, Madison; Rakhra-Burris, Tejinder K.; Stevens, Ana; Williams, Pamela; Bult, Carol J.; Chisholm, Rex; Deverka, Patricia; Ginsburg, Geoffrey S.; Green, Eric D.; Jarvik, Gail; Mensah, George A.; Ramos, Erin; Relling, Mary V.; Roden, Dan M.; Rowley, Robb; Alterovitz, Gil; Aronson, Samuel; Bastarache, Lisa; Cimino, James J.; Crowgey, Erin L.; Del Fiol, Guilherme; Freimuth, Robert R.; Hoffman, Mark A.; Jeff, Janina; Johnson, Kevin; Kawamoto, Kensaku; Madhavan, Subha; Mendonca, Eneida A.; Ohno-Machado, Lucila; Pratap, Siddharth; Overby Taylor, Casey; Ritchie, Marylyn D.; Walton, Nephi; Weng, Chunhua; Zayas-Cabán, Teresa; Manolio, Teri A.; Williams, Marc S.; Pediatrics, School of Medicine
Objective: The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled "Developing a Clinical Genomic Informatics Research Agenda". The meeting's goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. Materials and methods: Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. Results: Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. Discussion: Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.
Acquisition, processing, and single-cell analysis of normal human breast tissues from a biobank
(Cell Press, 2021-12-16) Bhat-Nakshatri, Poornima; Marino, Natascia; Gao, Hongyu; Liu, Yunlong; Storniolo, Anna Maria; Nakshatri, Harikrishna; Surgery, School of Medicine
The Komen Tissue Bank is the only biorepository in the world for normal breast tissues from women. Below we report the acquisition and processing of breast tissue from volunteer donors and describe an experimental and analysis pipeline to generate a single-cell atlas. This atlas is based on single-cell RNA-seq and is useful to derive breast epithelial cell subcluster-specific gene expression signatures, which can be applied to breast cancer gene expression data to identify putative cell-of-origin. For complete details on the use and execution of this protocol, please refer to Bhat-Nakshatri et al. (2021).
Advances and Obstacles in the Genetic Dissection of Chlamydial Virulence
(Springer, 2018) Brothwell, Julie A.; Muramatsu, Matthew K.; Zhong, Guangming; Nelson, David E.; Microbiology and Immunology, School of Medicine
Obligate intracellular pathogens in the family Chlamydiaceae infect taxonomically diverse eukaryotes ranging from amoebae to mammals. However, many fundamental aspects of chlamydial cell biology and pathogenesis remain poorly understood. Genetic dissection of chlamydial biology has historically been hampered by a lack of genetic tools. Exploitation of the ability of chlamydia to recombine genomic material by lateral gene transfer (LGT) ushered in a new era in chlamydia research. With methods to map mutations in place, genetic screens were able to assign functions and phenotypes to specific chlamydial genes. Development of an approach for stable transformation of chlamydia also provided a mechanism for gene delivery and platforms for disrupting chromosomal genes. Here, we explore how these and other tools have been used to test hypotheses concerning the functions of known chlamydial virulence factors and discover the functions of completely uncharacterized genes. Refinement and extension of the existing genetic tools to additional Chlamydia spp. will substantially advance understanding of the biology and pathogenesis of this important group of pathogens.
The association of polygenic risk for schizophrenia, bipolar disorder, and depression with neural connectivity in adolescents and young adults: examining developmental and sex differences
(Springer Nature, 2021-01-14) Meyers, J.L.; Chorlian, D.B.; Bigdeli, T.B.; Johnson, E.C.; Aliev, F.; Agrawal, A.; Almasy, L.; Anokhin, A.; Edenberg, H.J.; Foroud, T.; Goate, A.; Kamarajan, C.; Kinreich, S.; Nurnberger, J.; Pandey, A.K.; Pandey, G.; Plawecki, M.H.; Salvatore, J.E.; Zhang, J.; Fanous, A.; Porjesz, B.; Medical and Molecular Genetics, School of Medicine
Neurodevelopmental abnormalities in neural connectivity have been long implicated in the etiology of schizophrenia (SCZ); however, it remains unclear whether these neural connectivity patterns are associated with genetic risk for SCZ in unaffected individuals (i.e., an absence of clinical features of SCZ or a family history of SCZ). We examine whether polygenic risk scores (PRS) for SCZ are associated with functional neural connectivity in adolescents and young adults without SCZ, whether this association is moderated by sex and age, and if similar associations are observed for genetically related neuropsychiatric PRS. One-thousand four-hundred twenty-six offspring from 913 families, unaffected with SCZ, were drawn from the Collaborative Study of the Genetics of Alcoholism (COGA) prospective cohort (median age at first interview = 15.6 (12-26), 51.6% female, 98.1% European American, 41% with a family history of alcohol dependence). Participants were followed longitudinally with resting-state EEG connectivity (i.e., coherence) assessed every two years. Higher SCZ PRS were associated with elevated theta (3-7 Hz) and alpha (7-12 Hz) EEG coherence. Associations differed by sex and age; the most robust associations were observed between PRS and parietal-occipital, central-parietal, and frontal-parietal alpha coherence among males between ages 15-19 (B: 0.15-0.21, p < 10-4). Significant associations among EEG coherence and Bipolar and Depression PRS were observed, but differed from SCZ PRS in terms of sex, age, and topography. Findings reveal that polygenic risk for SCZ is robustly associated with increased functional neural connectivity among young adults without a SCZ diagnosis. Striking differences were observed between men and women throughout development, mapping onto key periods of risk for the onset of psychotic illness and underlining the critical importance of examining sex differences in associations with neuropsychiatric PRS across development.
Bidirectional Regulatory Cross-Talk between Cell Context and Genomic Aberrations Shapes Breast Tumorigenesis
(American Association for Cancer Research, 2021) Kumar, Brijesh; Bhat-Nakshatri, Poornima; Maguire, Calli; Jacobsen, Max; Temm, Constance J.; Sandusky, George; Nakshatri, Harikrishna; Surgery, School of Medicine
Breast cancers are classified into five intrinsic subtypes and 10 integrative clusters based on gene expression patterns and genomic aberrations, respectively. Although the cell-of-origin, adaptive plasticity, and genomic aberrations shape dynamic transcriptomic landscape during cancer progression, how interplay between these three core elements governs obligatory steps for a productive cancer progression is unknown. Here, we used genetic ancestry-mapped immortalized breast epithelial cell lines generated from breast biopsies of healthy women that share gene expression profiles of luminal A, normal-like, and basal-like intrinsic subtypes of breast cancers and breast cancer relevant oncogenes to develop breast cancer progression model. Using flow cytometry, mammosphere growth, signaling pathway, DNA damage response, and in vivo tumorigenicity assays, we provide evidence that establishes cell context-dependent effects of oncogenes in conferring plasticity, self-renewal/differentiation, intratumor heterogeneity, and metastatic properties. In contrast, oncogenic aberrations, independent of cell context, shaped response to DNA damage-inducing agents. Collectively, this study reveals how the same set of genomic aberration can have distinct effects on tumor characteristics based on cell-of-origin of tumor and highlights the need to utilize multiple "normal" epithelial cell types to decipher oncogenic properties of a gene of interest. In addition, by creating multiple isogenic cell lines ranging from primary cells to metastatic variants, we provide resources to elucidate cell-intrinsic properties and cell-oncogene interactions at various stages of cancer progression. IMPLICATIONS: Our findings demonstrate that how an interplay between the normal cell type that encountered genomic aberrations and type of genomic aberration influences heterogeneity, self-renewal/differentiation, and tumor properties including propensity for metastasis.

Browsing by Subject "Genomics"

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