Abstract

BackgroundThe Brassicaceae family includes the model plant Arabidopsis thaliana as well as a number of agronomically important species such as oilseed crops (in particular Brassica napus, B. juncea and B. rapa) and vegetables (eg. B. rapa and B. oleracea).Separated by only 10-20 million years, Brassica species and Arabidopsis thaliana are closely related, and it is expected that knowledge obtained relating to Arabidopsis growth and development can be translated into Brassicas for crop improvement. Moreover, certain aspects of plant development are sufficiently different between Brassica and Arabidopsis to warrant studies to be carried out directly in the crop species. However, mutating individual genes in the amphidiploid Brassicas such as B. napus and B. juncea may, on the other hand, not give rise to expected phenotypes as the genomes of these species can contain up to six orthologues per single-copy Arabidopsis gene. In order to elucidate and possibly exploit the function of redundant genes for oilseed rape crop improvement, it may therefore be more efficient to study the effects in one of the diploid Brassica species such as B. rapa. Moreover, the ongoing sequencing of the B. rapa genome makes this species a highly attractive model for Brassica research and genetic resource development.ResultsSeeds from the diploid Brassica A genome species, B. rapa were treated with ethyl methane sulfonate (EMS) to produce a TILLING (Targeting Induced Local Lesions In Genomes) population for reverse genetics studies. We used the B. rapa genotype, R-o-18, which has a similar developmental ontogeny to an oilseed rape crop. Hence this resource is expected to be well suited for studying traits with relevance to yield and quality of oilseed rape. DNA was isolated from a total of 9,216 M2 plants and pooled to form the basis of the TILLING platform. Analysis of six genes revealed a high level of mutations with a density of about one per 60 kb. This analysis also demonstrated that screening a 1 kb amplicon in just one third of the population (3072 M2 plants) will provide an average of 68 mutations and a 97% probability of obtaining a stop-codon mutation resulting in a truncated protein. We furthermore calculated that each plant contains on average ~10,000 mutations and due to the large number of plants, it is predicted that mutations in approximately half of the GC base pairs in the genome exist within this population.ConclusionsWe have developed the first EMS TILLING resource in the diploid Brassica species, B. rapa. The mutation density in this population is ~1 per 60 kb, which makes it the most densely mutated diploid organism for which a TILLING population has been published. This resource is publicly available through the RevGenUK reverse genetics platform http://revgenuk.jic.ac.uk.

Highlights

  • The Brassicaceae family includes the model plant Arabidopsis thaliana as well as a number of agronomically important species such as oilseed crops and vegetables

  • The advent of high-throughput sequencing technologies, vast genomic databases and increasingly powerful genetic tools has had a huge impact on the development of our understanding of the biochemical and developmental networks regulating the multitude of genetic and physiological processes in plants [1]

  • Large mutant populations are generated by the treatment of seed or pollen with a chemical mutagen - most commonly ethyl methane sulfonate (EMS) - that can induce point mutations at a very high density, sufficient to establish a series of allelic mutations in all genes

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Summary

Introduction

The Brassicaceae family includes the model plant Arabidopsis thaliana as well as a number of agronomically important species such as oilseed crops (in particular Brassica napus, B. juncea and B. rapa) and vegetables The last decade has seen the development of a number of large-scale ‘Reverse Genetics’ tools to study the effects of mutations in genes for which the sequence is known. These tools include T-DNA insertion [2], TILLING (Targeting Induced Local Lesions In Genomes) [3] and RNAi technologies [4,5,6]. Amplified sequences are screened using established high throughput SNP discovery methods

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