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Structural variation across 138,134 samples in the TOPMed consortium

Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision....

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Detalles Bibliográficos
Autores principales: Jun, Goo, English, Adam C, Metcalf, Ginger A, Yang, Jianzhi, Chaisson, Mark JP, Pankratz, Nathan, Menon, Vipin K, Salerno, William J, Krasheninina, Olga, Smith, Albert V, Lane, John A, Blackwell, Tom, Kang, Hyun Min, Salvi, Sejal, Meng, Qingchang, Shen, Hua, Pasham, Divya, Bhamidipati, Sravya, Kottapalli, Kavya, Arnett, Donna K., Ashley-Koch, Allison, Auer, Paul L., Beutel, Kathleen M, Bis, Joshua C., Blangero, John, Bowden, Donald W., Brody, Jennifer A., Cade, Brian E., Chen, Yii-Der Ida, Cho, Michael H., Curran, Joanne E., Fornage, Myriam, Freedman, Barry I., Fingerlin, Tasha, Gelb, Bruce D., Hou, Lifang, Hung, Yi-Jen, Kane, John P, Kaplan, Robert, Kim, Wonji, Loos, Ruth J.F., Marcus, Gregory M, Mathias, Rasika A., McGarvey, Stephen T., Montgomery, Courtney, Naseri, Take, Nouraie, S. Mehdi, Preuss, Michael H., Palmer, Nicholette D., Peyser, Patricia A., Raffield, Laura M., Ratan, Aakrosh, Redline, Susan, Reupena, Sefuiva, Rotter, Jerome I., Rich, Stephen S., Rienstra, Michiel, Ruczinski, Ingo, Sankaran, Vijay G., Schwartz, David A., Seidman, Christine E., Seidman, Jonathan G., Silverman, Edwin K., Smith, Jennifer A., Stilp, Adrienne, Taylor, Kent D., Telen, Marilyn J., Weiss, Scott T., Williams, L. Keoki, Wu, Baojun, Yanek, Lisa R., Zhang, Yingze, Lasky-Su, Jessica, Gingras, Marie Claude, Dutcher, Susan K., Eichler, Evan E., Gabriel, Stacey, Germer, Soren, Kim, Ryan, Viaud-Martinez, Karine A., Nickerson, Deborah A., Luo, James, Reiner, Alex, Gibbs, Richard A, Boerwinkle, Eric, Abecasis, Goncalo, Sedlazeck, Fritz J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900832/
https://www.ncbi.nlm.nih.gov/pubmed/36747810
http://dx.doi.org/10.1101/2023.01.25.525428
Descripción
Sumario:Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hemotologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.