Dynamic Resistant Starch Accumulation in Contrasting Wheat Genotypes Highlights the Lipid Metabolic Pathway Related to Resistant Starch Synthesis

Abstract

Resistant starch (RS) shows several health benefits. Enhancing the RS content of wheat is of major commercial importance. However, knowledge regarding the RS synthesis mechanism in wheat remains limited. In this study, the dynamic accumulation of RS during the filling process in two wheat (Triticum aestivum L.) genotypes with contrasting RS contents (H242, high RS content; H189, low RS content) were investigated. The results demonstrate that beyond 25 days after pollination (DAP), the RS content of H189 was relatively stable, but that of H242 continued to increase. Secondary accumulation was observed in the high-RS-content wheat genotype. A comparative transcriptome analysis between H242 and H189 at 20 DAP and 35 DAP showed that the differentially expressed genes were mainly involved in glycerolipid metabolism, glycerophospholipid metabolism and glucuronate interconversions. Furthermore, weighted gene coexpression network analysis suggested that lipid metabolic pathways such as the glycerophospholipid metabolism pathway might be involved in RS synthesis, and lipid-related genes upregulated beyond 25 DAP resulted in RS secondary accumulation. This work provides insight into the characteristics and mechanisms of RS synthesis.

Characterization of Starch Physicochemical Properties and Grain Transcriptome Reveal the Mechanism for Resistant Starch Accumulation

“…Of course, the changes in the starch physiochemical properties could not be excluded. Wang et al [24] also found that the RS content of a cultivar with a high RS content increased gradually with the development of grain filling but that of H189 (a low RS content cultivar) was relatively stable beyond 25 DAA. The comparison of different cultivars showed that RS639 had the highest total starch content, and RS683 had the lowest total starch content during kernel development.…”

Time-Series Transcriptomic Analysis of Contrasting Rice Materials under Heat Stress Reveals a Faster Response in the Tolerant Cultivar

“…Pearson's correlation coefficient was used to calculate the correlation coefficients of FPKM of all transcripts among three replications for each sample. DESeq2 was used for differential expression analysis based on count value, and clustered profiles of genes with a p value ≤ 0.05 and |log 2 (fold-change)| ≥ 1 were considered differentially expressed [70]. STEM was conducted to classify the identified DEG expression patterns.…”

“…Primers (Table S3) were designed using Primer v5 software (Premier Biosoft International, San Francisco, CA, USA), and ubiquitin (UBQ5) was used as an internal control. The experimental operating system used for RT-qPCR was described in our previous studies [70,72]. The data were processed according to the Ct (2 −∆∆Ct ) method.…”