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Efficient Genome-Wide Detection and Cataloging of EMS-Induced Mutations Using Exome Capture and Next-Generation Sequencing
Author(s) -
Isabelle Henry,
Ugrappa Nagalakshmi,
Meric Lieberman,
Kathie J. Ngo,
Ksenia V. Krasileva,
Hans Vasquez-Gross,
Alina Akhunova,
Eduard Akhunov,
Jorge Dubcovsky,
Thomas H. Tai,
Luca Comai
Publication year - 2014
Publication title -
the plant cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.324
H-Index - 341
eISSN - 1532-298X
pISSN - 1040-4651
DOI - 10.1105/tpc.113.121590
Subject(s) - biology , ethyl methanesulfonate , genetics , mutagenesis , forward genetics , context (archaeology) , gene , mutation , oryza sativa , mutant , computational biology , genome , exome sequencing , dna sequencing , paleontology
Chemical mutagenesis efficiently generates phenotypic variation in otherwise homogeneous genetic backgrounds, enabling functional analysis of genes. Advances in mutation detection have brought the utility of induced mutant populations on par with those produced by insertional mutagenesis, but systematic cataloguing of mutations would further increase their utility. We examined the suitability of multiplexed global exome capture and sequencing coupled with custom-developed bioinformatics tools to identify mutations in well-characterized mutant populations of rice (Oryza sativa) and wheat (Triticum aestivum). In rice, we identified ∼18,000 induced mutations from 72 independent M2 individuals. Functional evaluation indicated the recovery of potentially deleterious mutations for >2600 genes. We further observed that specific sequence and cytosine methylation patterns surrounding the targeted guanine residues strongly affect their probability to be alkylated by ethyl methanesulfonate. Application of these methods to six independent M2 lines of tetraploid wheat demonstrated that our bioinformatics pipeline is applicable to polyploids. In conclusion, we provide a method for developing large-scale induced mutation resources with relatively small investments that is applicable to resource-poor organisms. Furthermore, our results demonstrate that large libraries of sequenced mutations can be readily generated, providing enhanced opportunities to study gene function and assess the effect of sequence and chromatin context on mutations.

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