4.7 Article

Detecting variation in starch granule size and morphology by high-throughput microscopy and flow cytometry

Journal

CARBOHYDRATE POLYMERS
Volume 299, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.carbpol.2022.120169

Keywords

High -throughput genetic screen; Arabidopsis thaliana; Hordeum vulgare; Induced genetic variation; Automated image analysis

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Starch forms water-insoluble granules with semi-crystalline structures, and their size and morphology vary depending on the biological source. However, there is a lack of screening methods to identify differences in starch granule size and shape. This study presents two high-throughput approaches using flow cytometry and automated light microscopy for starch granule extraction and size determination. The effectiveness of these methods was demonstrated by screening over 10,000 barley lines and identifying heritable changes in granule ratios. The findings suggest that these approaches can be used to identify genes controlling starch traits and improve starch processing.
Starch forms semi-crystalline, water-insoluble granules, the size and morphology of which vary according to biological origin. These traits, together with polymer composition and structure, determine the physicochemical properties of starch. However, screening methods to identify differences in starch granule size and shape are lacking. Here, we present two approaches for high-throughput starch granule extraction and size determination using flow cytometry and automated, high-throughput light microscopy. We evaluated the practicality of both methods using starch from different species and tissues and demonstrated their effectiveness by screening for induced variation in starch extracted from over 10,000 barley lines, yielding four with heritable changes in the ratio of large A-granules to small B-granules. Analysis of Arabidopsis lines altered in starch biosynthesis further demonstrates the applicability of these approaches. Identifying variation in starch granule size and shape will enable identification of trait-controlling genes for developing crops with desired properties, and could help optimise starch processing.

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