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Plant Methods  2011 

Rapid analysis of seed size in Arabidopsis for mutant and QTL discovery

DOI: 10.1186/1746-4811-7-3

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Abstract:

By using the transmitted light from the slide scanning function of a flatbed scanner and particle analysis of the resulting images, we have developed a method for the rapid and high throughput analysis of seed size and seed size distribution. The technical variation due to the approach was negligible enabling us to identify aspects of maternal plant growth that contribute to biological variation in seed size. By controlling for these factors, differences in seed size caused by altered parental genome dosage and mutation were easily detected. The method has high reproducibility and sensitivity, such that a mutant with a 10% reduction in seed size was identified in a screen of endosperm-expressed genes. Our study also generated average seed size data for 91 Arabidopsis accessions and identified a number of quantitative trait loci from two recombinant inbred line populations, generated from Cape Verde Islands and Burren accessions crossed with Columbia.This study describes a sensitive, high-throughput approach for measuring seed size and seed size distribution. The method provides a low cost and robust solution that can be easily implemented into the workflow of studies relating to various aspects of seed development.More food will need to be produced during the next 50 years than in the entire history of humankind. Therefore, increasing crop yields is a major challenge for the 21st century. Since most of the world's food calories come from seed, one way to meet this challenge is to create plants with more and larger seeds. Arabidopsis thaliana is a useful model organism for studying seed development due to its ease of cultivation and extensive genetic and community resources available. Thus far, only a handful of genes are known to be directly involved in determining Arabidopsis seed size [1-8].Genes that regulate seed size can be discovered by screening for mutants or by quantitative trait loci (QTL) analysis to identify the genes that underlie the natural variation

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