Using chain-length distributions to diagnose genetic diversity in starch biosynthesis

Amylopectin synthesis is controlled by the coordinated action of several types of enzymes, including starch synthases, branching and debranching enzymes. The contributions of some of these enzymes to the building of starch molecules have been previously established. Changes to the activity of an enzyme can affect amylopectin structure, which is associated with diversity in functional properties. One such property, gelatinisation temperature, has been studied at the genetic, biochemical and phenotypic level. A technique, the ‘log(number distribution) approach’, offers a means of collecting normalisation-free representations of the chain-length distributions of starch, with the potential to reveal new information about kinetics and processes of starch synthesis; this method of plotting the data can potentially reveal much more than that usually employed, viz., the simple number chain-length distribution. In this study, samples from genotypes with defined mutations in starch biosynthetic genes that specifically and differently alter the chain-length distribution of single-cluster chains, with a resultant effect on gelatinisation temperature, are used to show that log(number distribution) plots have sufficient discriminative capacity to diagnose the gene affected by mutations, provide new information, and determine those features of the plot which associate with genotype and phenotype.