Research square · 2023

Structural variation across 138,134 samples in the TOPMed consortium.

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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, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Luo James, Reiner Alex, Gibbs Richard A, Boerwinkle Eric, Abecasis Goncalo, Sedlazeck Fritz J

Аннотация

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 hematologic 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.

Structural variation across 138,134 samples in the TOPMed consortium.

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Аннотация