| Literature DB >> 32553272 |
Michael Alonge1, Xingang Wang2, Matthias Benoit3, Sebastian Soyk2, Lara Pereira4, Lei Zhang4, Hamsini Suresh2, Srividya Ramakrishnan1, Florian Maumus5, Danielle Ciren2, Yuval Levy6, Tom Hai Harel6, Gili Shalev-Schlosser6, Ziva Amsellem6, Hamid Razifard7, Ana L Caicedo7, Denise M Tieman8, Harry Klee8, Melanie Kirsche1, Sergey Aganezov1, T Rhyker Ranallo-Benavidez9, Zachary H Lemmon2, Jennifer Kim3, Gina Robitaille3, Melissa Kramer2, Sara Goodwin2, W Richard McCombie10, Samuel Hutton11, Joyce Van Eck12, Jesse Gillis2, Yuval Eshed6, Fritz J Sedlazeck13, Esther van der Knaap14, Michael C Schatz15, Zachary B Lippman16.
Abstract
Structural variants (SVs) underlie important crop improvement and domestication traits. However, resolving the extent, diversity, and quantitative impact of SVs has been challenging. We used long-read nanopore sequencing to capture 238,490 SVs in 100 diverse tomato lines. This panSV genome, along with 14 new reference assemblies, revealed large-scale intermixing of diverse genotypes, as well as thousands of SVs intersecting genes and cis-regulatory regions. Hundreds of SV-gene pairs exhibit subtle and significant expression changes, which could broadly influence quantitative trait variation. By combining quantitative genetics with genome editing, we show how multiple SVs that changed gene dosage and expression levels modified fruit flavor, size, and production. In the last example, higher order epistasis among four SVs affecting three related transcription factors allowed introduction of an important harvesting trait in modern tomato. Our findings highlight the underexplored role of SVs in genotype-to-phenotype relationships and their widespread importance and utility in crop improvement.Entities:
Keywords: breeding; cis-regulatory; copy number variation; cryptic variation; domestication; dosage; epistasis; long-read sequencing; structural variation; tomato
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Year: 2020 PMID: 32553272 PMCID: PMC7354227 DOI: 10.1016/j.cell.2020.05.021
Source DB: PubMed Journal: Cell ISSN: 0092-8674 Impact factor: 66.850