Article

Molecular Breeding

, Volume 29, Issue 2, pp 349-360

First online:

A survey of natural and ethyl methane sulfonate-induced variations of eIF4E using high-resolution melting analysis in Capsicum

  • Hee-Jin JeongAffiliated withDepartment of Plant Science, Plant Genomics and Breeding Institute, and Research Institute for Agriculture and Life Sciences, Seoul National University
  • , Jin-Kyung KwonAffiliated withDepartment of Plant Science, Plant Genomics and Breeding Institute, and Research Institute for Agriculture and Life Sciences, Seoul National University
  • , Devendra PandeyaAffiliated withDepartment of Plant Science, Plant Genomics and Breeding Institute, and Research Institute for Agriculture and Life Sciences, Seoul National University
  • , JeeNa HwangAffiliated withDepartment of Plant Science, Plant Genomics and Breeding Institute, and Research Institute for Agriculture and Life Sciences, Seoul National University
  • , Ngoc Huy HoangAffiliated withDepartment of Plant Science, Plant Genomics and Breeding Institute, and Research Institute for Agriculture and Life Sciences, Seoul National University
  • , Joong-Hwan BaeAffiliated withDepartment of Plant Science, Plant Genomics and Breeding Institute, and Research Institute for Agriculture and Life Sciences, Seoul National University
  • , Byoung-Cheorl KangAffiliated withDepartment of Plant Science, Plant Genomics and Breeding Institute, and Research Institute for Agriculture and Life Sciences, Seoul National University Email author 

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Abstract

Allele mining is a method used to find undiscovered natural variations or induced mutations in a plant, and has become increasingly important as more genomic information is available in plants. A high-throughput method is required to facilitate the identification of novel alleles in a large number of samples. In this paper we describe the application of a high-resolution melting (HRM) method to detect natural variations and ethyl methane sulfonate (EMS)-induced mutations in Capsicum. We have scanned single polymorphic mutations in the first exon of the eIF4E gene, wherein the mutations confer resistance to potyviruses. Sixteen allelic variations out of 248 germplasm collections were identified using HRM analysis, and one accession carrying an allelic variation (pvrHRM1 13 ) was confirmed to be resistant to the TEV-HAT strain. In addition, five single polymorphic mutations in the eIF4E gene were identified in an EMS-induced mutant population. These results demonstrate that HRM allows for the rapid identification of new allelic variants in both natural and artificial mutant populations.

Keywords

Allele mining EMS HRM Mutant screening Capsicum