Rapid cloning of disease-resistance genes in plants using mutagenesis and sequence capture

Burkhard Steuernagel, Sambasivam K. Periyannan, Inmaculada Hernández-Pinzón, Kamil Witek, Matthew N. Rouse, Guotai Yu, Asyraf Hatta, Mick Ayliffe, Harbans Bariana, Jonathan D.G. Jones, Evans S. Lagudah, Brande B.H. Wulff

Research output: Contribution to journalArticlepeer-review

155 Scopus citations

Abstract

Wild relatives of domesticated crop species harbor multiple, diverse, disease resistance (R) genes that could be used to engineer sustainable disease control. However, breeding R genes into crop lines often requires long breeding timelines of 5-15 years to break linkage between R genes and deleterious alleles (linkage drag). Further, when R genes are bred one at a time into crop lines, the protection that they confer is often overcome within a few seasons by pathogen evolution. If several cloned R genes were available, it would be possible to pyramid R genes in a crop, which might provide more durable resistance. We describe a three-step method (MutRenSeq)-that combines chemical mutagenesis with exome capture and sequencing for rapid R gene cloning. We applied MutRenSeq to clone stem rust resistance genes Sr22 and Sr45 from hexaploid bread wheat. MutRenSeq can be applied to other commercially relevant crops and their relatives, including, for example, pea, bean, barley, oat, rye, rice and maize.

Original languageEnglish (US)
Pages (from-to)652-655
Number of pages4
JournalNature biotechnology
Volume34
Issue number6
DOIs
StatePublished - Jun 1 2016

Bibliographical note

Funding Information:
This research was supported by funds from the Gatsby Charitable Foundation, UK; Two Blades Foundation, USA; Biotechnology and Biological Sciences Research Council, UK; Borlaug Global Rust Initiative (BGRI) Durable Rust Resistance in Wheat (DRRW) Project (administered by Cornell University with a grant from the Bill & Melinda Gates Foundation and the UK Department for International Development); USDA-ARS National Plant Disease Recovery System; Grains Research and Development Corporation, Australia; and a fellowship to A.H. from Universiti Putra Malaysia (UPM), Malaysia. We are grateful to colleagues in The Sainsbury Laboratory and the Two Blades Foundation for helpful discussions. This research was supported in part by the NBI Computing infrastructure for Science (CiS) group and Dan MacLean's group by providing computational infrastructure.

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