Timing and Biosynthetic Potential for Carotenoid Accumulation in Genetically Diverse Germplasm of Maize      

Abstract

Enhancement of the carotenoid biosynthetic pathway in food crops benefits human health and adds commercial value of natural food colorants. However, predictable metabolic engineering or breeding is limited by the incomplete understanding of endogenous pathway regulation, including rate-controlling steps and timing of expression in carotenogenic tissues. The grass family (Poaceae) contains major crop staples, including maize (Zea mays), wheat (Triticum aestivum), rice (Oryza sativa), sorghum (Sorghum bicolor), and millet (Pennisetum glaucum). Maize carotenogenesis was investigated using a novel approach to discover genes encoding limiting biosynthetic steps in the nutritionally targeted seed endosperm. A combination of bioinformatics and cloning were first used to identify and map gene families encoding enzymes in maize and other grasses. These enzymes represented upstream pathways for isopentenyl diphosphate and geranylgeranyl diphosphate synthesis and the downstream carotenoid biosynthetic pathway, including conversion to abscisic acid. A maize germplasm collection was used for statistical testing of the correlation between carotenoid content and candidate gene transcript levels. Multiple pathway bottlenecks for isoprenoid biosynthesis and carotenoid biosynthesis were discovered in specific temporal windows of endosperm development. Transcript levels of paralogs encoding isoprenoid isopentenyl diphosphate and geranylgeranyl diphosphate-producing enzymes, DXS3, DXR, HDR, and GGPPS1, were found to positively correlate with endosperm carotenoid content. For carotenoid pathway enzymes, transcript levels for CrtISO inversely correlated with seed carotenoid content, as compared with positive correlation of PSY1 transcripts. Since zeaxanthin epoxidase (ZEP) depletes the carotenoid pool in subsequent conversion to abscisic acid, ZEP transcripts were examined. Carotenoid accumulation was found to be inversely associated with ZEP1 and ZEP2 transcript levels. Extension of the maize results using phylogenetic analysis identified orthologs in other grass species that may serve as potential metabolic engineering targets.

Genetic Enhancement of Grain Quality-Related Traits in Maize

“…In particular transcript profiling led to discovery of the Hydroxylase3 locus that coincidently mapped to a carotene QTL, thereby prompting investigation of allelic variation in a broader collection. Vallabhaneni & Wurtzel (2009) …”

“…Genetic variation at crtRB1 also affects hydroxylation efficiency among encoded allozymes, as observed by resultant carotenoid profiles in recombinant expression assays. Similarly, studies on natural maize genetic diversity carried out by Vallabhaneni et al (2009), have provided the identification of hydroxylation genes associated with reduced endosperm provitamin A content. In particular transcript profiling led to discovery of the Hydroxylase3 locus that coincidently mapped to a carotene QTL, thereby prompting investigation of allelic variation in a broader collection.…”

Influence of the moisture at harvest and drying process of the grains on the level of carotenoids in maize (Zea mays)

“…Maize is considered a source of carotenoids, substances that are important for human health, given the capability as antioxidant and the activity as vitamin A precursor of some of these compounds (Rodriguez-Amaya, 2001;Vallabhaneni & Wurtzel, 2009). The variability in the concentration of carotenoids in grains have been observed in maize cultivars and inbred lines, making the increase of concentration these compounds in the edible part of the plant possible by genetic improvement, especially of those of biological significance, provitamin A carotenoids (pVAC), precursors of vitamin A (Janick-Buckner et al, 1999;Kurilich & Juvik, 1999;Cardoso et al, 2009).…”

Network-Guided GWAS Improves Identification of Genes Affecting Free Amino Acids

“…These traits include, for example, the sum of related metabolites or the ratio of two related metabolites, such as precursors or products (Sauer et al, 1999;Weckwerth et al, 2004;Wentzell et al, 2007). With both linkage analysis and GWAS, derived traits that represent ratios based on metabolic pathways or known interactions have generated more significant associations compared with associations from absolute levels of metabolites (Wentzell et al, 2007;Vallabhaneni and Wurtzel, 2009;Wurtzel et al, 2012;Angelovici et al, 2013; GonzalezJorge et al, 2013;Lipka et al, 2013;Owens et al, 2014). One explanation for this phenomenon could be the higher heritability of metabolic ratios compared with content traits (Wentzell et al, 2007).…”

“…In addition, Gu et al (2010) found that knocking out mitochondrial isovaleryl-CoA dehydrogenase, an enzyme in the Leu degradation pathway, results in a significant increase in 12 FAAs in a seed-specific manner (Gu et al, 2010). Taken together, these findings suggest that the inherent coordination of seed FAAs could be used as a tool to further unravel the genetic basis of quantitative traits, such as amino acids.Forward genetic approaches, such as linkage analysis, have proven to be powerful for identifying quantitative trait loci (QTLs) that control phenotypic variation for phenological and metabolic traits, such as flowering time and levels of carotenoids, tocochromanols, and amino acids in seed (Kowalski et al, 1994; Alonso-Blanco et al, 1998;Yan et al, 2000;Wong et al, 2004;Wentzell et al, 2007;Chander et al, 2008; Balasubramanian et al, 2009;Vallabhaneni and Wurtzel, 2009;Gutiérrez-Rojas et al, 2010;Maloney et al, 2010;Kochevenko and Fernie, 2011). Nevertheless, traditional linkage analysis to identify QTLs in biparental recombinant inbred line (RIL) populations has two major weaknesses: it captures narrow levels of allelic diversity as a result of only two parental lines, and it provides low mapping resolution due to the overall limited number of recombination events that occur while constructing the RIL population (Yu and Buckler, 2006;Korte and Farlow, 2013).…”