Natural Variation in Maize Aphid Resistance Is Associated with 2,4-Dihydroxy-7-Methoxy-1,4-Benzoxazin-3-One Glucoside Methyltransferase Activity

Plants differ greatly in their susceptibility to insect herbivory, suggesting both local adaptation and resistance tradeoffs. We used maize (Zea mays) recombinant inbred lines to map a quantitative trait locus (QTL) for the maize leaf aphid (Rhopalosiphum maidis) susceptibility to maize Chromosome 1. Phytochemical analysis revealed that the same locus was also associated with high levels of 2-hydroxy-4,7-dimethoxy-1,4-benzoxazin-3-one glucoside (HDMBOA-Glc) and low levels of 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one glucoside (DIMBOA-Glc). In vitro enzyme assays with candidate genes from the region of the QTL identified three O-methyltransferases (Bx10a-c) that convert DIMBOA-Glc to HDMBOA-Glc. Variation in HDMBOA-Glc production was attributed to a natural CACTA family transposon insertion that inactivates Bx10c in maize lines with low HDMBOA-Glc accumulation. When tested with a population of 26 diverse maize inbred lines, R. maidis produced more progeny on those with high HDMBOA-Glc and low DIMBOA-Glc. Although HDMBOA-Glc was more toxic to R. maidis than DIMBOA-Glc in vitro, BX10c activity and the resulting decline of DIMBOA-Glc upon methylation to HDMBOA-Glc were associated with reduced callose deposition as an aphid defense response in vivo. Thus, a natural transposon insertion appears to mediate an ecologically relevant trade-off between the direct toxicity and defense-inducing properties of maize benzoxazinoids.     

Genome-Wide Association of Carbon and Nitrogen Metabolism in the Maize Nested Association Mapping Population

Carbon (C) and nitrogen (N) metabolism are critical to plant growth and development and are at the basis of crop yield and adaptation. We performed high-throughput metabolite analyses on over 12,000 samples from the nested association mapping population to identify genetic variation in C and N metabolism in maize (Zea mays ssp. mays). All samples were grown in the same field and used to identify natural variation controlling the levels of 12 key C and N metabolites, namely chlorophyll a, chlorophyll b, fructose, fumarate, glucose, glutamate, malate, nitrate, starch, sucrose, total amino acids, and total protein, along with the first two principal components derived from them. Our genome-wide association results frequently identified hits with single-gene resolution. In addition to expected genes such as invertases, natural variation was identified in key C₄ metabolism genes, including carbonic anhydrases and a malate transporter. Unlike several prior maize studies, extensive pleiotropy was found for C and N metabolites. This integration of field-derived metabolite data with powerful mapping and genomics resources allows for the dissection of key metabolic pathways, providing avenues for future genetic improvement.Carbon (C) and nitrogen (N) metabolism are the basis for life on Earth. The production, balance, and tradeoffs of C and N metabolism are critical to all plant growth, yield, and local adaptation (Coruzzi and Bush, 2001; Coruzzi et al., 2007). In plants, there is a critical balance between the tissues that are producing energy (sources) and those using it (sinks), as the identities and locations of these vary through time and developmental stage (Smith et al., 2004). While a great deal of research has focused on the key genes and proteins involved in these processes (Wang et al., 1993; Kim et al., 2000; Takahashi et al., 2009), relatively little is known about the natural variation within a species that fine-tunes these processes in individual plants.In addition, a key aspect of core C metabolism involves the nature of plant photosynthesis. While the majority of plants use standard C₃ photosynthetic pathways, some, including maize (Zea mays) and many other grasses, use C₄ photosynthesis to concentrate CO₂ in bundle sheath cells to avoid wasteful photorespiration (Sage, 2004). Under some conditions (such as drought or high temperatures), C₄ photosynthesis is much more efficient than C₃ photosynthesis. Since these conditions are expected to become more prevalent in the near future due to climate change, various research groups are working to convert C₃ crop species to C₄ metabolism in order to boost crop production and food security (Sage and Zhu, 2011). Beyond this, better understanding of both C₃ and C₄ metabolic pathways will aid efforts to breed crops for superior yield, N-use efficiency, and other traits important for global food production.In the last two decades, quantitative trait locus (QTL) mapping, first with linkage analysis and later with association mapping, has been used to dissect C and N metabolism in several species, including Arabidopsis (Arabidopsis thaliana; Mitchell-Olds and Pedersen, 1998; Keurentjes et al., 2008; Lisec et al., 2008; Sulpice et al., 2009), tomato (Solanum lycopersicum; Schauer et al., 2006), and maize (Hirel et al., 2001; Limami et al., 2002; Zhang et al., 2006, 2010a, 2010b). These studies identified key genetic regions underlying variation in core C and N metabolism, many of which include candidate genes known to be involved in these processes.Previous studies of genetic variation for C and N metabolism are limited by the fact that they identified trait loci only through linkage mapping in artificial families or through association mapping across populations of unrelated individuals. Linkage mapping benefits from high statistical power due to many individuals sharing the same genotype at any given location, but it suffers from low resolution due to the limited number of generations (and hence recombination events) since the initial founders. Association mapping, in turn, enjoys high resolution due to the long recombination histories of natural populations but suffers from low power, since most genotypes occur in only a few individuals. In addition, many of these studies focused on C and N in artificial settings (e.g. greenhouses or growth chambers) instead of field conditions, running the risk that important genetic loci could be missed if the conditions do not include important (and potentially unknown) natural environmental variables.To address these issues and improve our understanding of C and N metabolism in maize, we used a massive and diverse germplasm resource, the maize nested association mapping (NAM) population (Buckler et al., 2009; McMullen et al., 2009), to evaluate genetic variation underlying the accumulation of 12 targeted metabolites in maize leaf tissue under field conditions. This population was formed by mating 25 diverse maize lines to the reference line, B73, and creating a 200-member biparental family from each of these crosses. The entire 5,000-member NAM population thus combines the strengths of both linkage and association mapping (McMullen et al., 2009), and it has been used to identify QTLs for important traits such as flowering time (Buckler et al., 2009), disease resistance (Kump et al., 2011; Poland et al., 2011), and plant architecture (Tian et al., 2011; Peiffer et al., 2013). Most importantly, this combination of power and resolution frequently resolves associations down to the single-gene level, even when using field-based data.The metabolites we profiled are key indicators of photosynthesis, respiration, glycolysis, and protein and sugar metabolism in the plant (Sulpice et al., 2009). By taking advantage of a robotized metabolic phenotyping platform (Gibon et al., 2004), we performed more than 100,000 assays across 12,000 samples, with two independent samples per experimental plot. Raw data and the best linear unbiased predictors (BLUPs) of these data were included as part of a study of general functional variation in maize (Wallace et al., 2014), but, to our knowledge, this is the first in-depth analysis of these metabolic data. We find strong correlations among several of the metabolites, and we also find extensive pleiotropy among the different traits. Many of the top QTLs are also near or within candidate genes relating to C and N metabolism, thus identifying targets for future breeding and selection. These results provide a powerful resource for those working with core C and N metabolism in plants and for improving maize performance in particular.     

Quantitative Trait Locus Mapping Reveals Regions of the Maize Genome Controlling Root System Architecture

The quest to determine the genetic basis of root system architecture (RSA) has been greatly facilitated by recent developments in root phenotyping techniques. Methods that are accurate, high throughput, and control for environmental factors are especially attractive for quantitative trait locus mapping. Here, we describe the adaptation of a nondestructive in vivo gel-based root imaging platform for use in maize (Zea mays). We identify a large number of contrasting RSA traits among 25 founder lines of the maize nested association mapping population and locate 102 quantitative trait loci using the B73 (compact RSA) × Ki3 (exploratory RSA) mapping population. Our results suggest that a phenotypic tradeoff exists between small, compact RSA and large, exploratory RSA.Maize (Zea mays) serves a key role in food, feedstock, and biofuel production throughout the world. To date, maize improvement through breeding has kept pace with the increasing demand for this crop (faostat3.fao.org). This feat has been accomplished through the utilization of the tremendous genetic diversity in maize (Flint-Garcia et al., 2005; Jiao et al., 2012), but increasing environmental pressures and a growing global population will require unprecedented gains in yield in the coming years. In the last decade, researchers have begun to explore the possibility of yield improvements through the manipulation of root systems, for example through breeding for roots better able to cope with drought (Uga et al., 2013) and flooding (Jackson and Armstrong, 1999), the use of plant growth-promoting rhizobacteria (Silby et al., 2009), or increasing nutrient use efficiency (Garnett et al., 2009). The potential of belowground solutions to enhanced plant productivity has driven the development of numerous methodologies for phenotyping root system architecture (RSA), which is the spatial organization of the plant’s root system.Several methods ranging from techniques adapted from medical imaging, such as x-ray tomography (Hargreaves et al., 2008) and combined positron emission tomography-magnetic resonance imaging (Jahnke et al., 2009), to refined versions of classical methods, such as field excavations (Trachsel et al., 2010) and pouch systems (Le Marié et al., 2014), have been used in attempts to understand the phenotypic consequences of genetic and environmental variation on root traits. Each root-phenotyping method has its advantages and disadvantages. Although the medical imaging-based techniques can produce highly detailed representations of roots, they are also very time consuming and require specialized equipment. Excavations, although more easily scaled to higher throughput and not requiring special equipment, are destructive and offer only coarse measurements of RSA. An alternative method for root phenotyping based on an optically clear gel substrate strikes an effective balance between throughput and detail, using a simple digital camera while maintaining precise control over environmental conditions. This platform has been used to quantify and classify distinctive root architectures from 12 rice (Oryza sativa) genotypes (Iyer-Pascuzzi et al., 2010), conduct a quantitative trait locus (QTL) mapping study of rice root traits in three dimensions (Topp et al., 2013), study interspecific and intraspecific rice root interactions (Fang et al., 2013), and quantify contributions of different root types to overall RSA (Clark et al., 2011).Here, we describe the adaptation of this gel imaging platform for use with the large maize root system. We used the platform to quantify the phenotypic diversity of RSA among 25 of the 26 nested association mapping (NAM) founder lines, which encompass a wide spectrum of maize genetic diversity (Yu et al., 2008; McMullen et al., 2009). We found that these lines exhibit diverse RSAs, ranging from small and compact to large and exploratory, suggesting tradeoffs between different types of architectures. In order to identify genetic loci that control maize RSA traits, we characterized a subpopulation that best represented the contrast between the compact and exploratory RSAs. We phenotyped the B73 (compact) × Ki3 (exploratory) recombinant inbred line (RIL) NAM subpopulation for 19 RSA traits at three time points (Topp et al., 2013). These data were used to map 102 QTLs that localized to nine genomic clusters. We found high heritability and large-effect QTLs for most traits, in contrast to maize flowering time QTLs (Buckler et al., 2009). Additionally, several of our QTL clusters overlapped with meta-QTLs for yield traits (Tuberosa et al., 2003; Semagn et al., 2013) as well as novel and previously unreported loci, suggesting that this system can provide a time- and cost-effective means to identify genes controlling root architecture in maize.     

Interactions of C4 Subtype Metabolic Activities and Transport in Maize Are Revealed through the Characterization of DCT2 Mutants

C₄ photosynthesis in grasses requires the coordinated movement of metabolites through two specialized leaf cell types, mesophyll (M) and bundle sheath (BS), to concentrate CO₂ around Rubisco. Despite the importance of transporters in this process, few have been identified or rigorously characterized. In maize (Zea mays), DCT2 has been proposed to function as a plastid-localized malate transporter and is preferentially expressed in BS cells. Here, we characterized the role of DCT2 in maize leaves using Activator-tagged mutant alleles. Our results indicate that DCT2 enables the transport of malate into the BS chloroplast. Isotopic labeling experiments show that the loss of DCT2 results in markedly different metabolic network operation and dramatically reduced biomass production. In the absence of a functioning malate shuttle, dct2 lines survive through the enhanced use of the phosphoenolpyruvate carboxykinase carbon shuttle pathway that in wild-type maize accounts for ∼25% of the photosynthetic activity. The results emphasize the importance of malate transport during C₄ photosynthesis, define the role of a primary malate transporter in BS cells, and support a model for carbon exchange between BS and M cells in maize.     

Focus Issue on Roots: Low Crown Root Number Enhances Nitrogen Acquisition from Low-Nitrogen Soils in Maize

In developing nations, low soil nitrogen (N) availability is a primary limitation to crop production and food security, while in rich nations, intensive N fertilization is a primary economic, energy, and environmental cost to crop production. It has been proposed that genetic variation for root architectural and anatomical traits enhancing the exploitation of deep soil strata could be deployed to develop crops with greater N acquisition. Here, we provide evidence that maize (Zea mays) genotypes with few crown roots (crown root number [CN]) have greater N acquisition from low-N soils. Maize genotypes differed in their CN response to N limitation in greenhouse mesocosms and in the field. Low-CN genotypes had 45% greater rooting depth in low-N soils than high-CN genotypes. Deep injection of ¹⁵N-labeled nitrate showed that low-CN genotypes under low-N conditions acquired more N from deep soil strata than high-CN genotypes, resulting in greater photosynthesis and plant N content. Under low N, low-CN genotypes had greater biomass than high-CN genotypes at flowering (85% in the field study in the United States and 25% in South Africa). In the field in the United States, 1.8× variation in CN was associated with 1.8× variation in yield reduction by N limitation. Our results indicate that CN deserves consideration as a potential trait for genetic improvement of N acquisition from low-N soils.Maize (Zea mays) is one of the world’s most important crops and is a staple food in Latin America and Africa. Maize production requires a large amount of fertilizer, especially nitrogen (N). In the United States, N fertilizers represent the greatest economic and energy costs for maize production (Ribaudo et al., 2011). However, on-farm studies across the northcentral United States revealed that more than half of applied N is not taken up by maize plants and is vulnerable to losses from volatilization, denitrification, and leaching, which pollute air and water resources (Cassman et al., 2002). Conversely, in developing countries, suboptimal N availability is a primary limitation to crop yields and, therefore, food security (Azeez et al., 2006). Increasing yield in these areas is an urgent concern, since chemical fertilizers are not affordable (Worku et al., 2007). Cultivars with greater N acquisition from low-N soils could help alleviate food insecurity in poor nations as well as reduce environmental degradation from excessive fertilizer use in developed countries.The two major soil N forms available to plants are ammonium and nitrate. Nitrate is the main N form in most maize production environments (Miller and Cramer, 2004). Nitrate is highly mobile in soil, and the spatiotemporal availability of soil N is rather complex. In the simplest case, N fertilizers applied to the soil and/or N released from the mineralization of soil organic matter are rapidly converted to nitrate by soil microbes. After irrigation and precipitation events, nitrate moves with water to deeper soil strata. Leaching of nitrate from the root zone has been shown to be a significant cause of low recovery of N fertilizer in commercial agricultural systems (Raun and Johnson, 1999; Cassman et al., 2002). Differences in root depth influence the ability of plants to acquire N. Studies using ¹⁵N-labeled nitrate placed at different soil depths showed that only plants with deep rooting can acquire N sources from deep soil strata, which would otherwise have been lost through leaching (Kristensen and Thorup-Kristensen, 2004a, 2004b). Therefore, selection for root traits enhancing rapid deep soil exploration could be used as a strategy to improve crop N efficiency.The maize root system consists of embryonic and postembryonic components. The embryonic root system consists of two distinct root classes: a primary root and a variable number of seminal roots formed at the scutellar node. The postembryonic root system consists of roots that are formed at consecutive shoot nodes and lateral roots, which are initiated in the pericycle of all root classes. Shoot-borne or nodal roots that are formed belowground are called crown roots, whereas those that are formed aboveground are designated brace roots (Hochholdinger, 2009). While the primary root and seminal roots are essential for the establishment of seedlings after germination, nodal roots and particularly crown roots make up most of the maize root system and are primarily responsible for soil resource acquisition later in development (Hoppe et al., 1986).Lynch (2013) proposed an ideotype for superior N and water acquisition in maize called Steep, Cheap, and Deep (SCD), which integrates root architectural, anatomical, and physiological traits to increase rooting depth and, therefore, the capture of N in leaching environments. One such trait is crown root number (CN). CN is an aggregate trait consisting of the number of belowground nodal whorls and the number of roots per whorl. The crown root system dominates resource acquisition during vegetative growth after the first few weeks and remains important during reproductive development (Hochholdinger et al., 2004). CN in maize ranges from five to 50 under fertile conditions (Trachsel et al., 2011). At the low end of this range, crown roots may be too spatially dispersed to sufficiently explore the soil. There is also a risk of root loss to herbivores and pathogens. If roots are lost in low-N plants, there may be too few crown roots left to support the nutrient, water, and anchorage needs of the plant. At the high end, a large number of crown roots may compete with each other for water and nutrients as well as incur considerable metabolic costs for the plant (Fig. 1). The SCD ideotype proposes that there is an optimal CN for N capture in maize (Lynch, 2013). Under low-N conditions, resources for root growth and maintenance are limiting, and nitrate is a mobile resource that can be captured by a dispersed root system. The optimal CN should tend toward the low end of the phenotypic variation to make resources available for the development of longer, deeper roots rather than more crown roots. According to the SCD ideotype, in low-N soils, maize genotypes with fewer crown roots could explore soils at greater depth, resulting in greater N acquisition, growth, and yield than genotypes with many crown roots.Open in a separate windowFigure 1.Visualization of the maize root system of low- and high-CN genotypes at 40 d after germination. Crown roots are colored in blue, and seminal roots are in red. The CN is eight in the low-CN genotype and 46 in the high-CN genotype. (Image courtesy of Larry M. York.)The objective of this study was to test the hypotheses that (1) low-CN genotypes have greater rooting depth than high-CN genotypes in low-N soils; (2) low-CN genotypes are better at acquiring deep soil N than high-CN genotypes; and (3) low-CN genotypes have greater biomass and yield than high-CN genotypes in low-N conditions.     

Ethanolamide Oxylipins of Linolenic Acid Can Negatively Regulate Arabidopsis Seedling Development

N-Acylethanolamines (NAEs) are fatty-acid derivatives with potent biological activities in a wide range of eukaryotic organisms. Polyunsaturated NAEs are among the most abundant NAE types in seeds of Arabidopsis thaliana, and they can be metabolized by either fatty acid amide hydrolase (FAAH) or by lipoxygenase (LOX) to low levels during seedling establishment. Here, we identify and quantify endogenous oxylipin metabolites of N-linolenoylethanolamine (NAE 18:3) in Arabidopsis seedlings and show that their levels were higher in faah knockout seedlings. Quantification of oxylipin metabolites in lox mutants demonstrated altered partitioning of NAE 18:3 into 9- or 13-LOX pathways, and this was especially exaggerated when exogenous NAE was added to seedlings. When maintained at micromolar concentrations, NAE 18:3 specifically induced cotyledon bleaching of light-grown seedlings within a restricted stage of development. Comprehensive oxylipin profiling together with genetic and pharmacological interference with LOX activity suggested that both 9-hydroxy and 13-hydroxy linolenoylethanolamides, but not corresponding free fatty-acid metabolites, contributed to the reversible disruption of thylakoid membranes in chloroplasts of seedling cotyledons. We suggest that NAE oxylipins of linolenic acid represent a newly identified, endogenous set of bioactive compounds that may act in opposition to progression of normal seedling development and must be depleted for successful establishment.     

Focus Issue on Roots: Root Cortical Aerenchyma Enhances Nitrogen Acquisition from Low-Nitrogen Soils in Maize

Suboptimal nitrogen (N) availability is a primary constraint for crop production in developing nations, while in rich nations, intensive N fertilization carries substantial environmental and economic costs. Therefore, understanding root phenes that enhance N acquisition is of considerable importance. Structural-functional modeling predicts that root cortical aerenchyma (RCA) could improve N acquisition in maize (Zea mays). We evaluated the utility of RCA for N acquisition by physiological comparison of maize recombinant inbred lines contrasting in RCA grown under suboptimal and adequate N availability in greenhouse mesocosms and in the field in the United States and South Africa. N stress increased RCA formation by 200% in mesocosms and by 90% to 100% in the field. RCA formation substantially reduced root respiration and root N content. Under low-N conditions, RCA formation increased rooting depth by 15% to 31%, increased leaf N content by 28% to 81%, increased leaf chlorophyll content by 22%, increased leaf CO₂ assimilation by 22%, increased vegetative biomass by 31% to 66%, and increased grain yield by 58%. Our results are consistent with the hypothesis that RCA improves plant growth under N-limiting conditions by decreasing root metabolic costs, thereby enhancing soil exploration and N acquisition in deep soil strata. Although potential fitness tradeoffs of RCA formation are poorly understood, increased RCA formation appears be a promising breeding target for enhancing crop N acquisition.Nitrogen (N) deficiency is one of the most limiting factors in maize (Zea mays) production worldwide (Ladha et al., 2005). In developing countries such as those in sub-Saharan Africa, less than 20 kg N ha⁻¹ is applied to fields of smallholder farmers due to high fertilizer cost (Azeez et al., 2006; Worku et al., 2007). In developed countries, intensive N fertilization is used to maintain satisfactory yield (Tilman et al., 2002). In the United States, N fertilizers are the greatest economic and energy cost for maize production (Ribaudo et al., 2011). However, less than half of the N applied to crops is actually acquired, and most of the remaining N becomes a source of environmental pollution (Raun and Johnson, 1999; Smil, 1999; Tilman et al., 2002). For example, N and phosphorus (P) effluents into marine systems from agriculture cause eutrophication and hypoxic zones (Diaz and Rosenberg, 2008; Robertson and Vitousek, 2009). Nitrate contamination in surface water and groundwater systems poses serious health risks, such as methemoglobinemia and N-nitroso-induced cancers (UNEP and WHRC, 2007). Emission of nitrous oxides from agricultural activities contributes to ozone damage and global warming (Kulkarni et al., 2008; Sutton et al., 2011). Furthermore, the production of N fertilizers requires considerable energy from fossil fuels, and since energy costs have risen in recent years, farmers face economic pressure from increasing N fertilizer costs, which are linked to higher food prices. It is estimated that a 1% increase in crop N efficiency could save more than $1 billion (U.S.) annually worldwide (Kant et al., 2011). Therefore, even a small improvement in N efficiency would have significant positive impacts on the environment and the economy.Soil N is heterogenous and dynamic. The bioavailability of soil N depends on the balance between the rates of mineralization, nitrification, and denitrification. These processes are determined by several factors, including soil composition, microbial activity, soil temperature, and soil water status (Miller and Cramer, 2004). The predominant form of soil N available to plants in most agricultural systems is nitrate, which is highly soluble in water and thus mobile in the soil (Barber, 1995; Marschner, 1995). Mineralization of organic matter and/or the application of N fertilizer at the beginning of the growing season followed by precipitation and irrigation create a pulse of nitrate that may exceed the N acquisition capacity of seedlings and leach below the root zone. Therefore, it has been proposed that increasing the speed of root exploration of deep soil strata could benefit N acquisition (Lynch, 2013). However, the structural investments and metabolic expenditures of root systems are substantial and can exceed half of daily photosynthesis (Lambers et al., 2002). Therefore, full consideration of the costs and benefits of root systems is crucial for identifying root traits to improve crop production, especially in water- and nutrient-deficient environments (Lynch, 2007). Taking rhizoeconomics and the spatiotemporal availability of soil N into account, Lynch (2013) proposed a root ideotype for enhanced N acquisition in maize called Steep, Cheap, and Deep, in which Steep refers to architectural phenes and Cheap refers to phenes that reduce the metabolic cost of soil exploration. One element of this ideotype is abundant root cortical aerenchyma (RCA).RCA consists of enlarged air spaces in the root cortex (Esau, 1977). RCA is known to form in response to hypoxia, and the role of RCA in improving oxygen transport to roots of many plant species under hypoxic conditions has been well researched (Vartapetian and Jackson, 1997; Jackson and Armstrong, 1999; Mano and Omori, 2007, 2013). Interestingly, RCA can also form in response to drought and edaphic stresses such as N, P, and sulfur deficiencies (Drew et al., 1989; Bouranis et al., 2003; Fan et al., 2003; Zhu et al., 2010a), which suggests that the benefit of RCA extends beyond facilitating oxygen transport. Several lines of evidence suggest that RCA enhances root metabolic efficiency under stress. Fan et al. (2003) found that RCA formation significantly reduced root segment respiration and P content of root tissue, which allowed greater shoot growth in soils with low P availability. Under drought, maize genotypes with high RCA formation had greater root length, deeper rooting, better leaf water status, and 8 times greater yield than closely related genotypes with low RCA (Zhu et al., 2010a). Effects of RCA on root respiration were more pronounced for large-diameter roots compared with small-diameter roots (Jaramillo et al., 2013). Results from the functional-structural plant model SimRoot showed that RCA formation could be an adaptive response to deficiency of N, P, and potassium by decreasing the metabolic cost of soil exploration. By reducing root respiration, RCA decreases the carbon cost of soil exploration, and by decreasing the N and P content of root tissue, RCA permits internal reallocation of nutrients to growing root tissue, which is particularly beneficial under conditions of low N and P availability (Postma and Lynch, 2011a). Under suboptimal P availability, RCA increased the growth of a simulated 40-d-old maize plant by 70% (Postma and Lynch, 2011b). In the case of N, RCA increased the growth of simulated maize plants up to 55% in low-N conditions, and plants benefit from RCA more in high-N-leaching environments than in low-N-leaching environments (Postma and Lynch, 2011a). In addition, the formation of RCA decreases critical soil nutrient levels, defined as the soil fertility below which growth is reduced, suggesting that cultivars with high RCA may require less fertilizer under nonstressed conditions. These in silico results suggest that RCA has potential utility for improving crop nutrient acquisition in both high- and low-input agroecosystems.The overall objective of this research was to assess the utility of RCA for N acquisition in maize under N-limiting conditions. Maize near-isophenic recombinant inbred lines (RILs) sharing a common genetic background (i.e. descending from the same parents) with common root phenotypes but contrasting in RCA formation were grown under N stress to test the hypothesis that RCA formation is associated with reduced root respiration, reduced tissue nutrient content, greater rooting depth, enhanced N acquisition, and therefore greater plant growth and yield under N limitation.     

One Divinyl Reductase Reduces the 8-Vinyl Groups in Various Intermediates of Chlorophyll Biosynthesis in a Given Higher Plant Species,But the Isozyme Differs between Species

Divinyl reductase (DVR) converts 8-vinyl groups on various chlorophyll intermediates to ethyl groups, which is indispensable for chlorophyll biosynthesis. To date, five DVR activities have been detected, but adequate evidence of enzymatic assays using purified or recombinant DVR proteins has not been demonstrated, and it is unclear whether one or multiple enzymes catalyze these activities. In this study, we systematically carried out enzymatic assays using four recombinant DVR proteins and five divinyl substrates and then investigated the in vivo accumulation of various chlorophyll intermediates in rice (Oryza sativa), maize (Zea mays), and cucumber (Cucumis sativus). The results demonstrated that both rice and maize DVR proteins can convert all of the five divinyl substrates to corresponding monovinyl compounds, while both cucumber and Arabidopsis (Arabidopsis thaliana) DVR proteins can convert three of them. Meanwhile, the OsDVR (Os03g22780)-inactivated 824ys mutant of rice exclusively accumulated divinyl chlorophylls in its various organs during different developmental stages. Collectively, we conclude that a single DVR with broad substrate specificity is responsible for reducing the 8-vinyl groups of various chlorophyll intermediates in higher plants, but DVR proteins from different species have diverse and differing substrate preferences, although they are homologous.Chlorophyll (Chl) molecules universally exist in photosynthetic organisms. As the main component of the photosynthetic pigments, Chl molecules perform essential processes of absorbing light and transferring the light energy in the reaction center of the photosystems (Fromme et al., 2003). Based on the number of vinyl side chains, Chls are classified into two groups, 3,8-divinyl (DV)-Chl and 3-monovinyl (MV)-Chl. The DV-Chl molecule contains two vinyl groups at positions 3 and 8 of the tetrapyrrole macrocycle, whereas the MV-Chl molecule contains a vinyl group at position 3 and an ethyl group at position 8 of the macrocycle. Almost all of the oxygenic photosynthetic organisms contain MV-Chls, with the exceptions of some marine picophytoplankton species that contain only DV-Chls as their primary photosynthetic pigments (Chisholm et al., 1992; Goericke and Repeta, 1992; Porra, 1997).The classical single-branched Chl biosynthetic pathway proposed by Granick (1950) and modified by Jones (1963) assumed the rapid reduction of the 8-vinyl group of DV-protochlorophyllide (Pchlide) catalyzed by a putative 8-vinyl reductase. Ellsworth and Aronoff (1969) found evidence for both MV and DV forms of several Chl biosynthetic intermediates between magnesium-protoporphyrin IX monomethyl ester (MPE) and Pchlide in Chlorella spp. mutants. Belanger and Rebeiz (1979, 1980) reported that the Pchlide pool of etiolated higher plants contains both MV- and DV-Pchlide. Afterward, following the further detection of MV- and DV-tetrapyrrole intermediates and their biosynthetic interconversion in tissues and extracts of different plants (Belanger and Rebeiz, 1982; Duggan and Rebeiz, 1982; Tripathy and Rebeiz, 1986, 1988; Parham and Rebeiz, 1992, 1995; Kim and Rebeiz, 1996), a multibranched Chl biosynthetic heterogeneity was proposed (Rebeiz et al., 1983, 1986, 1999; Whyte and Griffiths, 1993; Kolossov and Rebeiz, 2010).Biosynthetic heterogeneity refers to the biosynthesis of a particular metabolite by an organelle, tissue, or organism via multiple biosynthetic routes. Varieties of reports lead to the assumption that Chl biosynthetic heterogeneity originates mainly in parallel DV- and MV-Chl biosynthetic routes. These routes are interconnected by 8-vinyl reductases that convert DV-tetrapyrroles to MV-tetrapyrroles by conversion of the vinyl group at position 8 of ring B to the ethyl group (Parham and Rebeiz, 1995; Rebeiz et al., 2003). DV-MPE could be converted to MV-MPE in crude homogenates from etiolated wheat (Triticum aestivum) seedlings (Ellsworth and Hsing, 1974). Exogenous DV-Pchlide could be partially converted to MV-Pchlide in barley (Hordeum vulgare) plastids (Tripathy and Rebeiz, 1988). 8-Vinyl chlorophyllide (Chlide) a reductases in etioplast membranes isolated from etiolated cucumber (Cucumis sativus) cotyledons and barley and maize (Zea mays) leaves were found to be very active in the conversion of exogenous DV-Chlide a to MV-Chlide a (Parham and Rebeiz, 1992, 1995). Kim and Rebeiz (1996) suggested that Chl biosynthetic heterogeneity in higher plants may originate at the level of DV magnesium-protoporphyrin IX (Mg-Proto) and would be mediated by the activity of a putative 8-vinyl Mg-Proto reductase in barley etiochloroplasts and plastid membranes. However, since these reports did not use purified or recombinant enzyme, it is not clear whether the reductions of the 8-vinyl groups of various Chl intermediates are catalyzed by one enzyme of broad specificity or by multiple enzymes of narrow specificity, which actually has become one of the focus issues in Chl biosynthesis.Nagata et al. (2005) and Nakanishi et al. (2005) independently identified the AT5G18660 gene of Arabidopsis (Arabidopsis thaliana) as an 8-vinyl reductase, namely, divinyl reductase (DVR). Chew and Bryant (2007) identified the DVR BciA (CT1063) gene of the green sulfur bacterium Chlorobium tepidum, which is homologous to AT5G18660. An enzymatic assay using a recombinant Arabidopsis DVR (AtDVR) on five DV substrates revealed that the major substrate of AtDVR is DV-Chlide a, while the other four DV substrates could not be converted to corresponding MV compounds (Nagata et al., 2007). Nevertheless, a recombinant BciA is able to reduce the 8-vinyl group of DV-Pchlide to generate MV-Pchlide (Chew and Bryant, 2007). Recently, we identified the rice (Oryza sativa) DVR encoded by Os03g22780 that has sequence similarity with the Arabidopsis DVR gene AT5G18660. We also confirmed that the recombinant rice DVR (OsDVR) is able to not only convert DV-Chlide a to MV-Chlide a but also to convert DV-Chl a to MV-Chl a (Wang et al., 2010). Thus, it is possible that the reductions of the 8-vinyl groups of various Chl biosynthetic intermediates are catalyzed by one enzyme of broad specificity.In this report, we extended our studies to four DVR proteins and five DV substrates. First, ZmDVR and CsDVR genes were isolated from maize and cucumber genomes, respectively, using a homology-based cloning approach. Second, enzymatic assays were systematically carried out using recombinant OsDVR, ZmDVR, CsDVR, and AtDVR as representative DVR proteins and using DV-Chl a, DV-Chlide a, DV-Pchlide a, DV-MPE, and DV-Mg-Proto as DV substrates. Third, we examined the in vivo accumulations of various Chl intermediates in rice, maize, and cucumber. Finally, we systematically investigated the in vivo accumulations of Chl and its various intermediates in the OsDVR (Os03g22780)-inactivated 824ys mutant of rice (Wang et al., 2010). The results strongly suggested that a single DVR protein with broad substrate specificity is responsible for reducing the 8-vinyl groups of various intermediate molecules of Chl biosynthesis in higher plants, but DVR proteins from different species could have diverse and differing substrate preferences even though they are homologous.