Rice prolamins are categorized into three groups by molecular size (10, 13, or 16 kDa), while the 13 kDa prolamins are assigned to four subgroups (Pro13a-I, Pro13a-II, Pro13b-I, and Pro13b-II) based on cysteine residue content. Since lowering prolamin content in rice is essential to minimize indigestion and allergy risks, we generated four knockout lines using CRISPR-Cas9, which selectively reduced the expression of a specific subgroup of the 13 kDa prolamins. These four mutant rice lines also showed the compensatory expression of glutelins and non-targeted prolamins and were accompanied by low grain weight, altered starch content, and atypically-shaped starch granules and protein bodies. Transcriptome analysis identified 746 differentially expressed genes associated with 13 kDa prolamins during development. Correlation analysis revealed negative associations between genes in Pro13a-I and those in Pro13a-II and Pro13b-I/II subgroups. Furthermore, alterations in the transcription levels of 9 ER stress and 17 transcription factor genes were also observed in mutant rice lines with suppressed expression of 13 kDa prolamin. Our results provide profound insight into the functional role of 13 kDa rice prolamins in the regulatory mechanisms underlying rice seed development, suggesting their promising potential application to improve nutritional and immunological value.

Seed storage proteins (SSPs) play a pivotal role in determining the development, quality, and nutritional value of rice seeds. In this study, we conducted a transcriptome-based correlation analysis to identify novel transcription factors (TFs) potentially involved in the biosynthesis and accumulation of SSPs. Our analysis revealed nine TFs—OsGATA8, OsMIF1, OsMIF2, OsGZF1, OsbZIP58, OsS1Fa1, OsS1Fa2, OsICE2, and OsMYB24—that exhibit strong co-expression with key SSP genes, including those encoding glutelin and prolamin. Gene expression profiling using quantitative RT-PCR and GUS reporter assays revealed that these TFs are predominantly expressed during seed development, with peak expression observed at 10 days after flowering (DAF). Promoter analysis further demonstrated an enrichment of seed-specific and hormone-responsive cis-regulatory elements, reinforcing the seed-preferential expression patterns of these TFs. Collectively, our findings identify a set of candidate TFs likely involved in SSP regulation and seed maturation, providing a foundation for the genetic enhancement of rice seed quality and nutritional content through targeted breeding and biotechnological approaches.

Wheat (Triticum aestivum L.) omega-5 gliadin, a major allergen responsible for wheat-dependent exercise-induced anaphylaxis in humans, is encoded by genes located at the Gli-B1 locus on chromosome 1B, which exhibits genetic polymorphism. Gli-B1 alleles have generally been identified based on the electrophoretic mobilities of the encoded gamma-, omega-1,2, and omega-5 gliadins in acid polyacrylamide gel electrophoresis. However, the similar mobilities of omega-5 gliadin variants make it difficult to distinguish them among different wheat varieties. In this study, we optimized reverse-phase–ultra-performance liquid chromatography (RP-UPLC) conditions to separate omega-5 gliadins in the reference wheat cultivar Chinese Spring and its nullisomic–tetrasomic lines for chromosome 1B. Five chromatographic peaks corresponded to omega-5 gliadin, and the average relative standard deviation to each peak retention time ranged from 0.31% to 0.93%, indicating that the method is accurate and reproducible for fractionating omega-5 gliadins in gliadin extracts from wheat flour. Using the optimized RP-UPLC method, we analyzed omega-5 gliadins in 24 wheat varieties with the Gli-B1f allele. The result showed that the wheat varieties were sorted into eight groups according to the composition of omega-5 gliadin, indicating that the classification of Gli-B1 alleles based on A-PAGE could not explain the composition of omega-5 gliadin in wheat. We reclassified 73 wheat varieties containing 16 unique Gli-B1 alleles into 31 groups based on the chromatographic patterns of their omega-5 gliadins. Our results provide information on the specific Gli-B1 alleles of wheat varieties belonging to each group and demonstrate the potential for RP-UPLC to facilitate genetic studies of wheat varieties.

Rice prolamins are categorized into three groups by molecular size (10, 13, or 16 kDa), while the 13 kDa prolamins are assigned to four subgroups (Pro13a-I, Pro13a-II, Pro13b-I, and Pro13b-II) based on cysteine residue content. Here, we generated four knockout strains of rice using CRISPR-Cas9, each of which demonstrated selectively reduced expression of specific subgroups of the 13 kDa prolamins. These four mutant rice lines also demonstrated compensatory expression of glutelins and non-targeted prolamins, which resulted in low grain weight, altered starch content and atypically-shaped starch granules and protein bodies. Transcriptome analysis identified 746 transcripts that were differentially expressed in the mutant rice lines during development. These transcripts played roles primarily in RNA processing, protein synthesis, stress response, and transport. After selective suppression/knockout of genes in the Pro13a-I subgroup, compensatory upregulation of genes in the Pro13a-II and Pro13b-I/II subgroups was observed. Compensatory expression of 9 ER stress and 17 transcription factor genes was also observed in mutant rice in which expression of 13 kDa prolamin genes was suppressed. Our results provide valuable insight into the regulatory mechanisms underlying rice seed development and the specific roles played by 13 kDa rice prolamins and their target genes.