Carrots (Daucus carota) are a unique model for the accumulation of carotenoids. Beta-carotene accumulates in large amounts in the taproot if the proper alleles of the following three loci are present: OR, Y, and Y2. These three loci are not carotenoid biosynthetic genes but rather post-transcriptional regulation of carotenoid accumulation. The genes underlying the OR and Y loci have been characterized, but the gene underlying the Y2 locus is unknown. Through genomic and transcriptomic analyses, a single candidate that may interact with light signaling was found. To determine the function of this gene, the functional transcript from wild carrot was overexpressed in orange carrots and used in a transient infiltration assay with a GFP fusion tag in tobacco. The orange allele of this gene has a large transposon insertion that theoretically inactivates the gene. However, full length transcript can still be detected in orange carrots. This begs the question of whether the transposon is still active in certain accessions. In this study, the proportion properly assembled Y2 transcript was analyzed via qRT-PCR. A KASP marker was also developed to assist plant breeders in selection for the Y2 locus.
Anthocyanins, a group of secondary metabolites synthesized in the phenylpropanoid pathway, largely determine fruit peel color of fleshy fruits, but it is not known if its synthesis is linked to vacuolar malate accumulation that determines fruit acidity. Here, we show that when the coding sequence of Ma1, the major gene controlling apple fruit acidity, is overexpressed in ‘Royal Gala’ (RG), anthocyanin biosynthesis in the fruit peel is enhanced, corresponding to the downregulation of the expression of MYB73, an R2R3-MYB transcription factor. RNAi suppression of MYB73 expression via virus-induced gene silencing increases anthocyanin biosynthesis whereas its transient overexpression decreases anthocyanin biosynthesis in apple fruit peel. MYB73 binds to the promoter of the gene encoding UDP-glycose: flavonoid-3-O-glycosyltransferase (UFGT), the enzyme that catalyzes the last step in anthocyanin synthesis, to repress its expression. When MYB73 expression is suppressed by RNAi, UFGT expression is enhanced, leading to more anthocyanin synthesis, but this effect is blocked by RNAi suppression of UFGT expression. RNAi suppression of MYB73 enhances anthocyanin synthesis in wild-type RG apples whereas its overexpression decreases anthocyanin synthesis in Ma1-OE fruit. In the meantime, MYB73 competes with MYB1, one of the key activators of anthocyanin biosynthesis, binding to the promoter of UFGT and regulating its expression. These results indicate that MYB73 negatively regulates anthocyanin biosynthesis via repressing UFGT expression in apple peel. In Ma1-OE fruit, down-regulation of MYB73 releases UFGT from MYB73 repression and allows more MYB1 binding to UFGT promoter, leading to enhanced anthocyanin biosynthesis.
Aspergillus flavus is a widespread pathogen affecting crops like peanuts, contributing significantly to mycotoxin contamination and subsequent crop losses. Discriminating between toxigenic and non-toxigenic strains is crucial, yet conventional methods are often cumbersome and time-consuming. In this study, we developed rapid molecular tools to differentiate between these strains. Using morphological characteristics and species-specific PCR-sequencing, we identified isolates collected from peanut seeds in southern Georgia. Through primer optimization and qPCR targeting aflatoxin regulatory genes, we successfully distinguished aflatoxin-producing and non-producing isolates. Additional genes involved in aflatoxin biosynthesis were also analyzed, showing clear expression distinctions. Our findings demonstrate the specificity and efficiency of these primer sets, providing a valuable tool for managing A. flavus contamination in peanut seed lots. Additionally, research on the seed microbiome's impact on mycotoxin production remains limited. In this study, we assessed microbial communities in peanut seeds collected over various years using ITS gene sequencing. Our results revealed a diverse microbial population, including A. flavus and other fungal pathogens, highlighting the complexity of seed microbiota. This approach offers novel insights into peanut seed-associated microbiomes and aflatoxin contamination, shedding light on the correlation between microbial communities and aflatoxin pollution.
Lead (Pb) is a widespread toxic element in agricultural soils and Pb accumulation in plant roots represents a potential health risk for human beings. The sweetpotato (Ipomoea batatas L.) is a globally important root crop and one of the leading raw products for baby food processing. Limited information is available about the mechanism by which sweetpotato responds to Pb stress at the molecular level. Understanding the genetic mechanism of Pb uptake is essential for developing management approaches to mitigate Pb uptake in this crop. To address this knowledge gap, RNA-seq was used to characterize the transcriptome and identify differentially expressed genes from Pb-treated and untreated sweetpotato cv. Beauregard. Samples were taken from adventitious root tips at 5, 10, and 15 days after planting (DAP). Transcriptomic analysis revealed 4,077, 5,159, and 3,206 differentially expressed genes at 5, 10, and 15 DAP respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis shows that ABC transporters and sulfur metabolism pathways are upregulated at 5 DAP but are downregulated at 15 DAP, indicating that there may be a threshold in sweetpotato Pb tolerance. The results provide a deeper insight into the species-specific response of sweetpotato to Pb stress which can lead to the development of screening methods and evaluation of management strategies that reduce Pb uptake in this crop.
Nitrogen (N) is a key limiting macronutrient for crop growth and development and affects sweetpotato storage root formation and yield potential. In high-input production areas, excessive N application can suppress storage root formation and results in environmental pollution. The crop is also grown in low-input production systems with little or no N applications. In this study, sweetpotato cv Bayou Belle response to N deprivation during the establishment and storage root formation stages was investigated through a transcriptomic approach. RNA-seq data revealed a number of differentially expressed genes (DEGs) between N sufficient ( N) and N deficient (–N) conditions at 5, 10, and 15 days after planting (DAP). The number of significantly upregulated genes varied between timepoints. DEGs were further classified into functional categories and pathways to reveal putative functions. Gene Ontology annotation together with KEGG analysis revealed that majority of the DEGs are involved in sulfur compound metabolic process at 5 DAP and in ammonium transport for both 10 DAP and 15 DAP. These results provide valuable insights about the molecular mechanism of N regulation in sweetpotato adventitious roots undergoing storage root formation. These findings can lead to the development of tools and processes for improving N use efficiency and consistent storage root yields while reducing environmental impact in this globally important crop.
Climate change represents a significant challenge to global food security by altering environmental conditions critical to crop growth. Plant breeders can play a key role in mitigating these challenges by developing more resilient crop varieties; however, these efforts require significant investments in resources and time. In response, it is imperative to use current technologies that assimilate large biological and environmental datasets into predictive models to accelerate the research, development, and release of new improved varieties. Leveraging large and diverse data sets can improve the characterization of phenotypic responses due to environmental stimuli and genomic pulses. A better characterization of these signals holds the potential to enhance our ability to predict trait performance under changes in weather and/or soil conditions with high precision. This presentation introduces CHiDO, an easy-to-use, no-code platform designed to integrate diverse omics datasets and effectively model their interactions. With its flexibility to integrate and process data sets, CHiDO's intuitive interface allows users to explore historical data, formulate hypotheses, and optimize data collection strategies for future scenarios. The platform's mission emphasizes global accessibility, democratizing statistical solutions for situations where professional ability in data processing and data analysis is not available.
