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

Department of Biochemistry, University of Otago, PO Box 56, Dunedin 9054, New Zealand. .
Plant Methods (Impact Factor: 3.1). 02/2011; 7(1):3. DOI: 10.1186/1746-4811-7-3
Source: PubMed

ABSTRACT Arabidopsis thaliana is a useful model organism for deciphering the genetic determinants of seed size; however the small size of its seeds makes measurements difficult. Bulk seed weights are often used as an indicator of average seed size, but details of individual seed is obscured. Analysis of seed images is possible but issues arise from variations in seed pigmentation and shadowing making analysis laborious. We therefore investigated the use of a consumer level scanner to facilitate seed size measurements in conjunction with open source image-processing software.
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.

Download full-text


Available from: Robert C Day, Sep 27, 2015
22 Reads
  • Source
    • "concerning breeding purposes, linking to germination rate or plant growth. For this, 2D scanning is a popular, affordable technique [17] [30] [42] [48]. Several commercial software packages are available for seed investigations using flat-bed scanners, e.g. "
    [Show abstract] [Hide abstract]
    ABSTRACT: We describe a method for 3D reconstruction of plant seed surfaces, focusing on small seeds with diameters as small as 200 µm. The method considers robotized systems allowing single seed handling in order to rotate a single seed in front of a camera. Even though such systems feature high position repeatability, at sub-millimeter object scales, camera pose variations have to be compensated. We do this by robustly estimating the tool center point from each acquired image. 3D reconstruction can then be performed by a simple shape-from-silhouette approach. In experiments we investigate runtimes, the achieved accuracy, and show as a proof of principle that the proposed method is well sufficient for 3D seed phenotyping purposes.
    Computer Vision Problems in Plant Phenotyping 2015, Swansea, UK; 09/2015
  • Source
    • "Developments in the availability of image analysis for plant measurement applications have made low cost alternatives available, including: RootScan, which analyses root cross sections [21]; Tomato Analyzer, which measures a range of features including shape and disease state in tomatoes and other fruits [22]; and the web application PhenoPhyte, which allows users to quantify leaf area and herbivory from above ground plant images [23]. ImageJ is general purpose image analysis software that is freely available [24], and has been used to analyse seed shape and size parameters in a range of plant species including wheat, rice and Arabidopsis[25-28]. SmartGrain [29] is another image analysis system that is free to use, and is also based on images captured by consumer level flatbed scanners to extract seed characteristics. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Background Measuring grain characteristics is an integral component of cereal breeding and research into genetic control of seed development. Measures such as thousand grain weight are fast, but do not give an indication of variation within a sample. Other methods exist for detailed analysis of grain size, but are generally costly and very low throughput. Grain colour analysis is generally difficult to perform with accuracy, and existing methods are expensive and involved. Results We have developed a software method to measure grain size and colour from images captured with consumer level flatbed scanners, in a robust, standardised way. The accuracy and precision of the method have been demonstrated through screening wheat and Brachypodium distachyon populations for variation in size and colour. Conclusion By using GrainScan, cheap and fast measurement of grain colour and size will enable plant research programs to gain deeper understanding of material, where limited or no information is currently available.
    Plant Methods 07/2014; 10(1):23. DOI:10.1186/1746-4811-10-23 · 3.10 Impact Factor
  • Source
    • "The benefits of accuracy and objectivity attending this approach increase the quality of the resulting phenotype data. Accordingly, automated or semiautomated image analysis is beginning to impact the mapping of quantitative trait loci in plants (Herridge et al. 2011; Moore et al. 2013; Tisné et al. 2013; Topp et al. 2013). The project presented here combines an ability to capture the time course of gravitropism in high resolution with the throughput needed to make mapping populations feasible subjects. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Automated image acquisition, a custom analysis algorithm, and a distributed computing resource were used to add time as a third dimension to a quantitative trait locus (QTL) map for plant root gravitropism, a model growth response to an environmental cue. Digital images of Arabidopsis thaliana seedling roots from two independently reared sets of 162 recombinant inbred lines (RILs) and one set of 92 near isogenic lines (NILs) derived from a Cape Verde Islands (Cvi) x Landsberg erecta (Ler) cross were collected automatically every two minutes for eight hours following induction of gravitropism by 90 degree reorientation of the sample. High Throughput Computing (HTC) was used to measure root tip angle in each of the 1.1 million images acquired and to perform statistical regression of tip angle against the genotype at each of the 234 (RIL) or 102 (NIL) DNA markers independently at each time point using a standard stepwise procedure. Time-dependent QTL were detected on chromosomes 1, 3, and 4 by this mapping method and by an approach developed to treat the phenotype time course as a function-valued trait. The QTL on chromosome 4 was earliest, appearing at 0.5 h and remaining significant for 5 h, while the QTL on chromosome 1 appeared at 3 h and thereafter remained significant. The Cvi allele generally had a negative effect of 2.6-4.0%. Heritability due to the QTL approached 25%. This study shows how computer vision and statistical genetic analysis by HTC can characterize the developmental timing of genetic architectures.
    Genetics 08/2013; 195(3). DOI:10.1534/genetics.113.153346 · 5.96 Impact Factor
Show more