The K-Segment of Maize DHN1 Mediates Binding to Anionic Phospholipid Vesicles and Concomitant Structural Changes

Dehydrins (DHNs; late embryogenesis abundant D11 family) are a family of intrinsically unstructured plant proteins that accumulate in the late stages of seed development and in vegetative tissues subjected to water deficit, salinity, low temperature, or abscisic acid treatment. We demonstrated previously that maize (Zea mays) DHNs bind preferentially to anionic phospholipid vesicles; this binding is accompanied by an increase in α-helicity of the protein, and adoption of α-helicity can be induced by sodium dodecyl sulfate. All DHNs contain at least one “K-segment,” a lysine-rich 15-amino acid consensus sequence. The K-segment is predicted to form a class A2 amphipathic α-helix, a structural element known to interact with membranes and proteins. Here, three K-segment deletion proteins of maize DHN1 were produced. Lipid vesicle-binding assays revealed that the K-segment is required for binding to anionic phospholipid vesicles, and adoption of α-helicity of the K-segment accounts for most of the conformational change of DHNs upon binding to anionic phospholipid vesicles or sodium dodecyl sulfate. The adoption of structure may help stabilize cellular components, including membranes, under stress conditions.When plants encounter environmental stresses such as drought or low temperature, various responses take place to adapt to these conditions. Typical responses include increased expression of chaperones, signal transduction pathway and late embryogenesis abundant (LEA) proteins, osmotic adjustment, and induction of degradation and repair systems (Ingram and Bartels, 1996).Dehydrins (DHNs; LEA D11 family) are a subfamily of group 2 LEA proteins that accumulate to high levels during late stages of seed development and in vegetative tissues subjected to water deficit, salinity, low temperature, or abscisic acid (ABA) treatment (Svensson et al., 2002). Some DHNs are expressed constitutively during normal growth (Nylander et al., 2001; Rorat et al., 2004, 2006; Rodriguez et al., 2005). DHNs exist in a wide range of photosynthetic organisms, including angiosperms, gymnosperms, algae, and mosses (Svensson et al., 2002). DHNs are encoded by a dispersed multigene family and are differentially regulated, at least in higher plants. For example, 13 Dhn genes have been identified in barley (Hordeum vulgare), dispersed over seven genetic map locations (Choi et al., 1999; Svensson et al., 2002) and regulated variably by drought, low temperature, and embryo development (Tommasini et al., 2008). DHNs are localized in various subcellular compartments, including cytosol (Roberts et al., 1993), nucleus (Houde et al., 1995), chloroplast (Artus et al., 1996), vacuole (Heyen et al., 2002), and proximal to the plasma membrane and protein bodies (Asghar et al., 1994; Egerton-Warburton et al., 1997; Puhakainen et al., 2004). Elevated expression of Dhn genes generally has been correlated with the acquisition of tolerance to abiotic stresses such as drought (Whitsitt et al., 1997), salt (Godoy et al., 1994; Jayaprakash et al., 1998), chilling (Ismail et al., 1999a), or freezing (Houde et al., 1995; Danyluk et al., 1998; Fowler et al., 2001). The differences in expression and tissue location suggest that individual members of the Dhn multigene family have somewhat distinct biological functions (Close, 1997; Zhu et al., 2000; Nylander et al., 2001). Many studies have observed a positive correlation between the accumulation of DHNs and tolerance to abiotic stresses (Svensson et al., 2002). However, overexpression of a single DHN protein has not, in general, been sufficient to confer stress tolerance (Puhakainen et al., 2004).DHNs are subclassified by sequence motifs referred to as the K-segment (Lys-rich consensus sequence), the Y-segment (N-terminal conserved sequence), the S-segment (a tract of Ser residues), and the φ-segment (Close, 1996). Because of high hydrophilicity, high content of Gly (>20%), and the lack of a defined three-dimensional structure in the pure form (Lisse et al., 1996), DHNs have been categorized as “intrinsically disordered/unstructured proteins” or “hydrophilins” (Wright and Dyson, 1999; Garay-Arroyo et al., 2000; Tompa, 2005; Kovacs et al., 2008). On the basis of compositional and biophysical properties and their link to abiotic stresses, several functions of DHNs have been proposed, including ion sequestration (Roberts et al., 1993), water retention (McCubbin et al., 1985), and stabilization of membranes or proteins (Close, 1996, 1997). Observations from in vitro experiments include DHN binding to lipid vesicles (Koag et al., 2003; Kovacs et al., 2008) or metals (Svensson et al., 2000; Heyen et al., 2002; Kruger et al., 2002; Alsheikh et al., 2003; Hara et al., 2005), protection of membrane lipid against peroxidation (Hara et al., 2003), retention of hydration or ion sequestration (Bokor et al., 2005; Tompa et al., 2006), and chaperone activity against the heat-induced inactivation and aggregation of various proteins (Kovacs et al., 2008).Intrinsically disordered/unstructured proteins that lack a well-defined three-dimensional structure have recently been recognized to be prevalent in prokaryotes and eukaryotes (Oldfield et al., 2005). They fulfill important functions in signal transduction, gene expression, and binding to targets such as protein, RNA, ions, and membranes (Wright and Dyson, 1999; Tompa, 2002; Dyson and Wright, 2005). The disorder confers structural flexibility and malleability to adapt to changes in the protein environment, including water potential, pH, ionic strength, and temperature, and to undergo structural transition when complexed with ligands such as other proteins, DNA, RNA, or membranes (Prestrelski et al., 1993; Uversky, 2002). Structural changes from disorder to ordered functional structure also can be induced by the folding of a partner protein (Wright and Dyson, 1999; Tompa, 2002; Mouillon et al., 2008).The idea that DHNs interact with membranes is consistent with many immunolocalization studies, which have shown that DHNs accumulate near the plasma membrane or membrane-rich areas surrounding lipid and protein bodies (Asghar et al., 1994; Egerton-Warburton et al., 1997; Danyluk et al., 1998; Puhakainen et al., 2004). The K-segment is predicted to form a class A2 amphipathic α-helix, in which hydrophilic and hydrophobic residues are arranged on opposite faces (Close, 1996). The amphipathic α-helix is a structural element known to interact with membranes and proteins (Epand et al., 1995). Also, in the presence of helical inducers such as SDS and trifluoroethanol (Dalal and Pio, 2006), DHNs take on α-helicity (Lisse et al., 1996; Ismail et al., 1999b). We previously examined the binding of DHN1 to liposomes and found that DHNs bind preferentially to anionic phospholipids and that this binding is accompanied by an increase in α-helicity of the protein (Koag et al., 2003). Similarly, a mitochondrial LEA protein, one of the group III LEA proteins, recently has been shown to interact with and protect membranes subjected to desiccation, coupled with the adoption of amphipathic α-helices (Tolleter et al., 2007).Here, we explore the basis of DHN-vesicle interaction using K-segment deletion proteins. This study reveals that the K-segment is necessary and sufficient for binding to anionic phospholipid vesicles and that the adoption of α-helicity of DHN proteins can be attributed mainly to the K-segment.     

Wettability,Polarity, and Water Absorption of Holm Oak Leaves: Effect of Leaf Side and Age

Plant trichomes play important protective functions and may have a major influence on leaf surface wettability. With the aim of gaining insight into trichome structure, composition, and function in relation to water-plant surface interactions, we analyzed the adaxial and abaxial leaf surface of holm oak (Quercus ilex) as a model. By measuring the leaf water potential 24 h after the deposition of water drops onto abaxial and adaxial surfaces, evidence for water penetration through the upper leaf side was gained in young and mature leaves. The structure and chemical composition of the abaxial (always present) and adaxial (occurring only in young leaves) trichomes were analyzed by various microscopic and analytical procedures. The adaxial surfaces were wettable and had a high degree of water drop adhesion in contrast to the highly unwettable and water-repellent abaxial holm oak leaf sides. The surface free energy and solubility parameter decreased with leaf age, with higher values determined for the adaxial sides. All holm oak leaf trichomes were covered with a cuticle. The abaxial trichomes were composed of 8% soluble waxes, 49% cutin, and 43% polysaccharides. For the adaxial side, it is concluded that trichomes and the scars after trichome shedding contribute to water uptake, while the abaxial leaf side is highly hydrophobic due to its high degree of pubescence and different trichome structure, composition, and density. Results are interpreted in terms of water-plant surface interactions, plant surface physical chemistry, and plant ecophysiology.Plant surfaces have an important protecting function against multiple biotic and abiotic stress factors (Riederer, 2006). They may, for example, limit the attack of insects (Eigenbrode and Jetter, 2002) or pathogenic fungi (Gniwotta et al., 2005; Łaźniewska et al., 2012), avoid damage caused by high intensities of UV and visible radiation (Reicosky and Hanover, 1978; Karabourniotis and Bormann, 1999), help to regulate leaf temperature (Ehleringer and Björkman, 1978; Ripley et al., 1999), and chiefly prevent plant organs from dehydration (Riederer and Schreiber, 2001).The epidermis of plants has been found to have a major degree of physical and chemical variability and may often contain specialized cells such as trichomes or stomata (Roth-Nebelsick et al., 2009; Javelle et al., 2011). Most aerial organs are covered with an extracellular and generally lipid-rich layer named the cuticle, which is typically composed of waxes embedded in (intracuticular waxes) or deposited on (epicuticular waxes) a biopolymer matrix of cutin, forming a network of cross-esterified hydroxy C₁₆ and/or C₁₈ fatty acids, and/or cutan, with variable amounts of polysaccharides and phenolics (Domínguez et al., 2011; Yeats and Rose, 2013). Different nano- and/or microscale levels of plant surface sculpturing have been observed by scanning electron microscopy (SEM), generally in relation to the topography of epicuticular waxes, cuticular folds, and epidermal cells (Koch and Barthlott, 2009). Such surface features together with their chemical composition (Khayet and Fernández, 2012) may lead to a high degree of roughness and hydrophobicity (Koch and Barthlott, 2009; Konrad et al., 2012). The interactions of plant surfaces with water have been addressed in some investigations (Brewer et al., 1991; Brewer and Smith, 1997; Pandey and Nagar, 2003; Hanba et al., 2004; Dietz et al., 2007; Holder, 2007a, 2007b; Fernández et al., 2011, 2014; Roth-Nebelsick et al., 2012; Wen et al., 2012; Urrego-Pereira et al., 2013) and are a topic of growing interest for plant ecophysiology (Helliker and Griffiths, 2007; Aryal and Neuner, 2010; Limm and Dawson, 2010; Kim and Lee, 2011; Berry and Smith, 2012; Berry et al., 2013; Rosado and Holder, 2013; Helliker, 2014). On the other hand, the mechanisms of foliar uptake of water and solutes by plant surfaces are still not fully understood (Fernández and Eichert, 2009; Burkhardt and Hunsche, 2013), but they may play an important ecophysiological role (Limm et al., 2009; Johnstone and Dawson, 2010; Adamec, 2013; Berry et al., 2014).The importance of trichomes and pubescent layers on water drop-plant surface interactions and on the subsequent potential water uptake into the organs has been analyzed in some investigations (Fahn, 1986; Brewer et al., 1991; Grammatikopoulos and Manetas, 1994; Brewer and Smith, 1997; Pierce et al., 2001; Kenzo et al., 2008; Fernández et al., 2011, 2014; Burrows et al., 2013). Trichomes are unicellular or multicellular and glandular or nonglandular appendages, which originate from epidermal cells only and develop outwards on the surface of plant organs (Werker, 2000). Nonglandular trichomes are categorized according to their morphology and exhibit a major variability in size, morphology, and function. On the other hand, glandular trichomes are classified by the secretory materials they excrete, accumulate, or absorb (Johnson, 1975; Werker, 2000; Wagner et al., 2004). Trichomes can be often found in xeromorphic leaves and in young organs (Fahn, 1986; Karabourniotis et al., 1995). The occurrence of protecting leaf trichomes has been also reported for Mediterranean species such as holm oak (Quercus ilex; Karabourniotis et al., 1995, 1998; Morales et al., 2002; Karioti et al., 2011; Camarero et al., 2012). There is limited information about the nature of the surface of trichomes, but they are also covered with a cuticle similarly to other epidermal cell types (Fernández et al., 2011, 2014).In this study and using holm oak as a model, we assessed, for the first time, the leaf surface-water relations of the abaxial (always pubescent) versus the adaxial (only pubescent in developing leaves and for a few months) surface, including their capacity to absorb surface-deposited water drops. Based on membrane science methodologies (Fernández et al., 2011; Khayet and Fernández, 2012) and following a new integrative approach, the chemical, physical, and anatomical properties of holm oak leaf surfaces and trichomes were analyzed, with the aim of addressing the following questions. Are young and mature adaxial and abaxial leaf surfaces capable of absorbing water deposited as drops on to the surfaces? Are young and mature abaxial and adaxial leaf surfaces similar in relation to their wettability, hydrophobicity, polarity, work of adhesion (W_a) for water, solubility parameter (δ), and surface free energy (γ)? What is the physical and chemical nature of the adaxial versus the abaxial trichomes, chiefly in relation to young leaves?     

Calcineurin B-Like Protein-Interacting Protein Kinase CIPK21 Regulates Osmotic and Salt Stress Responses in Arabidopsis

The role of calcium-mediated signaling has been extensively studied in plant responses to abiotic stress signals. Calcineurin B-like proteins (CBLs) and CBL-interacting protein kinases (CIPKs) constitute a complex signaling network acting in diverse plant stress responses. Osmotic stress imposed by soil salinity and drought is a major abiotic stress that impedes plant growth and development and involves calcium-signaling processes. In this study, we report the functional analysis of CIPK21, an Arabidopsis (Arabidopsis thaliana) CBL-interacting protein kinase, ubiquitously expressed in plant tissues and up-regulated under multiple abiotic stress conditions. The growth of a loss-of-function mutant of CIPK21, cipk21, was hypersensitive to high salt and osmotic stress conditions. The calcium sensors CBL2 and CBL3 were found to physically interact with CIPK21 and target this kinase to the tonoplast. Moreover, preferential localization of CIPK21 to the tonoplast was detected under salt stress condition when coexpressed with CBL2 or CBL3. These findings suggest that CIPK21 mediates responses to salt stress condition in Arabidopsis, at least in part, by regulating ion and water homeostasis across the vacuolar membranes.Drought and salinity cause osmotic stress in plants and severely affect crop productivity throughout the world. Plants respond to osmotic stress by changing a number of cellular processes (Xiong et al., 1999; Xiong and Zhu, 2002; Bartels and Sunkar, 2005; Boudsocq and Lauriére, 2005). Some of these changes include activation of stress-responsive genes, regulation of membrane transport at both plasma membrane (PM) and vacuolar membrane (tonoplast) to maintain water and ionic homeostasis, and metabolic changes to produce compatible osmolytes such as Pro (Stewart and Lee, 1974; Krasensky and Jonak, 2012). It has been well established that a specific calcium (Ca²⁺) signature is generated in response to a particular environmental stimulus (Trewavas and Malhó, 1998; Scrase-Field and Knight, 2003; Luan, 2009; Kudla et al., 2010). The Ca²⁺ changes are primarily perceived by several Ca²⁺ sensors such as calmodulin (Reddy, 2001; Luan et al., 2002), Ca²⁺-dependent protein kinases (Harper and Harmon, 2005), calcineurin B-like proteins (CBLs; Luan et al., 2002; Batistič and Kudla, 2004; Pandey, 2008; Luan, 2009; Sanyal et al., 2015), and other Ca²⁺-binding proteins (Reddy, 2001; Shao et al., 2008) to initiate various cellular responses.Plant CBL-type Ca²⁺ sensors interact with and activate CBL-interacting protein kinases (CIPKs) that phosphorylate downstream components to transduce Ca²⁺ signals (Liu et al., 2000; Luan et al., 2002; Batistič and Kudla, 2004; Luan, 2009). In several plant species, multiple members have been identified in the CBL and CIPK family (Luan et al., 2002; Kolukisaoglu et al., 2004; Pandey, 2008; Batistič and Kudla, 2009; Weinl and Kudla, 2009; Pandey et al., 2014). Involvement of specific CBL-CIPK pair to decode a particular type of signal entails the alternative and selective complex formation leading to stimulus-response coupling (D’Angelo et al., 2006; Batistič et al., 2010).Several CBL and CIPK family members have been implicated in plant responses to drought, salinity, and osmotic stress based on genetic analysis of Arabidopsis (Arabidopsis thaliana) mutants (Zhu, 2002; Cheong et al., 2003, 2007; Kim et al., 2003; Pandey et al., 2004, 2008; D’Angelo et al., 2006; Qin et al., 2008; Tripathi et al., 2009; Held et al., 2011; Tang et al., 2012; Drerup et al., 2013; Eckert et al., 2014). A few CIPKs have also been functionally characterized by gain-of-function approach in crop plants such as rice (Oryza sativa), pea (Pisum sativum), and maize (Zea mays) and were found to be involved in osmotic stress responses (Mahajan et al., 2006; Xiang et al., 2007; Yang et al., 2008; Tripathi et al., 2009; Zhao et al., 2009; Cuéllar et al., 2010).In this report, we examined the role of the Arabidopsis CIPK21 gene in osmotic stress response by reverse genetic analysis. The loss-of-function mutant plants became hypersensitive to salt and mannitol stress conditions, suggesting that CIPK21 is involved in the regulation of osmotic stress response in Arabidopsis. These findings are further supported by an enhanced tonoplast targeting of the cytoplasmic CIPK21 through interaction with the vacuolar Ca²⁺ sensors CBL2 and CBL3 under salt stress condition.     

Relationships between Growth,Growth Response to Nutrient Supply,and Ion Content Using a Recombinant Inbred Line Population in Arabidopsis

Growth is an integrative trait that responds to environmental factors and is crucial for plant fitness. A major environmental factor influencing plant growth is nutrient supply. In order to explore this relationship further, we quantified growth-related traits, ion content, and other biochemical traits (protein, hexose, and chlorophyll contents) of a recombinant inbred line population of Arabidopsis (Arabidopsis thaliana) grown on different levels of potassium and phosphate. Performing an all subsets multiple regression analyses revealed a link between growth-related traits and mineral nutrient content. Based on our results, up to 85% of growth variation can be explained by variation in ion content, highlighting the importance of ionomics for a broader understanding of plant growth. In addition, quantitative trait loci (QTLs) were detected for growth-related traits, ion content, further biochemical traits, and their responses to reduced supplies of potassium or phosphate. Colocalization of these QTLs is explored, and candidate genes are discussed. A QTL for rosette weight response to reduced potassium supply was identified on the bottom of chromosome 5, and its effects were validated using selected near isogenic lines. These lines retained over 20% more rosette weight in reduced potassium supply, accompanied by an increase in potassium content in their leaves.Plants in natural environments face abiotic constraints limiting growth and ultimately affecting their fitness. In response to such constraints, flowering time (Korves et al., 2007) and seed dormancy (Donohue et al., 2005) as well as vegetative growth (Barto and Cipollini, 2005; Milla et al., 2009) are the main traits controlling fitness (for review, see Alonso-Blanco et al., 2009). These traits are under the control of complex networks integrating genetic (G) and environmental (E) factors as well as their interaction (G × E). Due to the implications for food and renewable energy sources, dissecting the genetic architecture that underlies plant growth is becoming a priority for plant science (Rengel and Damon, 2008; Carroll and Somerville, 2009; Gilbert, 2009).Plant growth is highly dependent on mineral nutrient uptake (Clarkson, 1980; Sinclair, 1992). Minerals can be distinguished into two categories based on the amount required by plants: micronutrients, which are found in relatively small amounts in the plant (such as copper and iron), and macronutrients, which constitute between 1,000 and 15,000 μg g⁻¹ plant dry weight (such as potassium and phosphate; Marschner, 1995, Buchanan et al., 2002). Phosphate is an important structural and signaling molecule with an essential role in photosynthesis, energy conservation, and carbon metabolism. Its deficiency leads to a reduction of growth and an increase of pathogen susceptibility (Marschner, 1995; Williamson et al., 2001; Abel et al., 2002; López-Bucio et al., 2005; Poirier and Bucher, 2008; Vijayraghavan and Soole, 2010). Potassium is not incorporated into any organic substances but acts as the major osmoticum of the cell, controlling cell expansion, plasma membrane potential and transport, pH value, and many other catalytic processes (Maathuis and Sanders, 1996; Armengaud et al., 2004; Christian et al., 2006; Di Cera, 2006). Potassium deficiency leads to reduced plant growth, a loss of turgor, increased susceptibility to cold stress and pathogens, and the development of chlorosis and necrosis (Marschner, 1995; Véry and Sentenac, 2003; Ashley et al., 2006; Amtmann et al., 2008). To cope with changes in nutrient availability, plants have evolved different mechanisms of adaptation, such as changes in ion transporter expression and activity (Ashley et al., 2006; Jung et al., 2009), morphological changes, such as an increase in root growth to explore more soil volume (Marschner, 1995; Shirvani et al., 2001; Jiang et al., 2007; Jordan-Meille and Pellerin, 2008), or acidification of the surrounding soil in order to mobilize more mineral nutrients (for review, see Ryan et al., 2001). Although these adaptations are well known, the mechanisms involved in sensing and signaling low mineral nutrient status are less well understood, despite significant progress in this area being made (Doerner, 2008; Jung et al., 2009; Luan et al., 2009; Wang and Wu, 2010).One approach to identify genes that are involved in plant responses to environmental factors is to perform a quantitative trait locus (QTL) analysis on a mapping population grown in contrasting environments, allowing the identification of QTL-environment (QTL × E) interactions. Some QTLs for growth-related traits in response to environmental changes were cloned already. For example, the differential response of root growth of some Arabidopsis (Arabidopsis thaliana) accessions to phosphate starvation led to the identification of allelic differences responsible for this phenotype (Reymond et al., 2006; Svistoonoff et al., 2007). Other studies have identified QTLs for shoot dry matter under changing nitrogen supply (Rauh et al., 2002; Loudet et al., 2003). In parallel to natural variation for growth, natural variation for ion content has also been reported. In Arabidopsis, considerable variation in the content of mineral nutrients exists both in seeds (Vreugdenhil et al., 2004; Waters and Grusak, 2008) and in leaves (Harada and Leigh, 2006; Rus et al., 2006; Baxter et al., 2008a; Morrissey et al., 2009). Furthermore, changes in mineral nutrient homeostasis have also been reported to be associated with characteristic multivariate changes in the leaf ionome, the mineral nutrient and trace element composition of an organism or an organ (Baxter et al., 2008b). Due to higher throughput and lower costs, such “omics” analyses examining alterations of large numbers of certain molecules at once have recently become available for mapping purposes. Some QTL studies have linked the variations of these omics data to variation of growth or other physiological traits. For instance, Meyer et al. (2007) and Schauer et al. (2008) linked plant growth or morphological traits to a synergistic network of metabolomic compounds in Arabidopsis and tomato (Solanum lycopersicum), respectively. In addition, Sulpice et al. (2009) associated differences in growth with starch content using a set of Arabidopsis accessions. Compiling the importance of ions in the process of cell division (Lai et al., 2007; Sano et al., 2007) or cell expansion (Philippar et al., 1999; Elumalai et al., 2002), ionomics appears to be a major unexplored field for understanding growth.In this study, we focus on variation in plant growth, the root and leaf ionomes, and their response to varying supplies of potassium and phosphate. Studying variations for these traits among recombinant inbred lines (RILs) in Arabidopsis enabled us to detect QTL and QTL × E interactions for all of these traits. To understand the observed variation in plant growth, predictors that explained a high percentage of variation of growth-related traits have been selected especially among the root and leaf ionomes. The colocalization between growth-related trait QTLs and QTLs for their predictors allowed us to point out genetic regions of possible causality. In addition, the effect of a growth-response QTL on reduced potassium supply was validated with selected near isogenic lines (NILs) that maintained a higher rosette weight when grown in reduced potassium supply. This growth advantage went along with significant changes in ion contents that further emphasize the impact of the ionome in plant growth variations.     

Metabolite Profiles of Maize Leaves in Drought,Heat, and Combined Stress Field Trials Reveal the Relationship between Metabolism and Grain Yield

The development of abiotic stress-resistant cultivars is of premium importance for the agriculture of developing countries. Further progress in maize (Zea mays) performance under stresses is expected by combining marker-assisted breeding with metabolite markers. In order to dissect metabolic responses and to identify promising metabolite marker candidates, metabolite profiles of maize leaves were analyzed and compared with grain yield in field trials. Plants were grown under well-watered conditions (control) or exposed to drought, heat, and both stresses simultaneously. Trials were conducted in 2010 and 2011 using 10 tropical hybrids selected to exhibit diverse abiotic stress tolerance. Drought stress evoked the accumulation of many amino acids, including isoleucine, valine, threonine, and 4-aminobutanoate, which has been commonly reported in both field and greenhouse experiments in many plant species. Two photorespiratory amino acids, glycine and serine, and myoinositol also accumulated under drought. The combination of drought and heat evoked relatively few specific responses, and most of the metabolic changes were predictable from the sum of the responses to individual stresses. Statistical analysis revealed significant correlation between levels of glycine and myoinositol and grain yield under drought. Levels of myoinositol in control conditions were also related to grain yield under drought. Furthermore, multiple linear regression models very well explained the variation of grain yield via the combination of several metabolites. These results indicate the importance of photorespiration and raffinose family oligosaccharide metabolism in grain yield under drought and suggest single or multiple metabolites as potential metabolic markers for the breeding of abiotic stress-tolerant maize.The increasing world population coupled to environmental deterioration is creating ever greater pressure on our capacity for sustainable food productivity. Alongside biotic stresses, abiotic stresses such as drought, heat, salinity, and nutrient deficiency greatly reduce yields in crop fields either when present alone or in combination. Breeding for more resilient crops, therefore, is one of the major approaches to cope with the increasing challenges in world agriculture. Considerable research effort has thus been invested in order to dissect plant responses to individual stresses at various levels (for review, see Urano et al., 2010; Lopes et al., 2011; Obata and Fernie, 2012), but the interaction between different stresses has been far less investigated (Cairns et al., 2012b, 2013; Suzuki et al., 2014). In general, the combination of stresses additively affects plant physiology (i.e. the symptoms of the individual stresses appear simultaneously) and synergistically diminishes the yield and productivity of plants (Keleş and Öncel, 2002; Giraud et al., 2008; Vile et al., 2012; Suzuki et al., 2014). The molecular responses, however, are not simply additive and are rarely predicted from the responses to individual stresses (Rizhsky et al., 2002, 2004; Prasch and Sonnewald, 2013; Rasmussen et al., 2013). Information from carefully controlled greenhouse experiments has begun to dissect the molecular mechanisms by which plants, in particular Arabidopsis (Arabidopsis thaliana), respond to drought and temperature stresses (Skirycz et al., 2010, 2011; Skirycz and Inzé, 2010; Bowne et al., 2012; Tardieu, 2012; Verkest et al., 2015). Our knowledge of the molecular basis of the responses of crop species in a field environment, however, is considerably less well advanced (Araus et al., 2008; Cabrera-Bosquet et al., 2012). That said, a large number of genotypes have been generated on the basis of their resistance to both biotic and abiotic stresses (for review, see Bänziger et al., 2006; Takeda and Matsuoka, 2008; Cooper et al., 2014), and the genome sequencing and molecular characterization of a range of stress-tolerant plant species have recently been reported (Wu et al., 2012; Ma et al., 2013; Bolger et al., 2014; Tohge et al., 2014). These studies are not only important as basic research for further studies in crops but also are a prerequisite in the development of molecular marker-based approaches to improve crop tolerance to stress.As a first step toward this goal, a deeper understanding of the plant responses to the stressful environment, especially those to multiple stress conditions under field conditions, is crucial for the improvement of stress-tolerant crops. This is important on two levels: (1) in the field, singular abiotic stresses are rare; and (2) yield and stress adaptation are complex traits that render breeding gains slower than would be expected under optimal conditions (Bruce et al., 2002). Recent studies have revealed that the response of plants to combinations of two or more stress conditions is unique and cannot be directly extrapolated from their responses to the different stresses when applied individually. This would be a result of complex combinations of different, and sometimes opposing, responses in signaling pathways, including those that may interact and inhibit one another (Prasch and Sonnewald, 2013; Rasmussen et al., 2013; Suzuki et al., 2014).Maize (Zea mays) is grown in over 170 million ha worldwide, of which 130 million ha are in less-developed countries (FAO, 2014). In sub-Saharan Africa, maize is a staple crop; however, yields in this region have stagnated at less than 2 tons ha⁻¹, while maize yields worldwide have continued to increase (Cairns et al., 2012a). Low yields in sub-Saharan Africa are largely associated with drought stress (DS) and low soil fertility (Bänziger and Araus, 2007). Additionally, simulation studies indicate that maize yield in Africa is likely to be significantly impaired by heat stress (HS; Lobell and Burke, 2010; Lobell et al., 2011), such as can be anticipated as a result of the changes in climate predicted for the coming decades (Müller et al., 2011). Moreover, the sensitivity of maize yield to heat is exacerbated under drought conditions (Lobell et al., 2011; Cairns et al., 2012a, 2012b, 2013). Therefore, the development of maize germplasm tolerant to drought and heat conditions is of utmost importance to both increase yields and offset predicted yield losses under projected climate change scenarios (Easterling et al., 2007), especially in sub-Saharan Africa. While direct selection for grain yield under DS has resulted in admirable gains in grain yield under stress (Bänziger et al., 2006; Cairns et al., 2013), further improvement requires the incorporation of additional selection traits (Cairns et al., 2012a, 2012b). In recent years, genetic and phenotypic markers have been searched extensively for drought tolerance of maize by high-throughput genomic and phenotyping approaches, respectively (Tuberosa and Salvi, 2006; Wen et al., 2011; Araus et al., 2012; Cairns et al., 2013; Prasanna et al., 2013; Araus and Cairns, 2014; Tsonev et al., 2014). Moreover, metabolic markers started to draw attention due to their close relationship with yield phenotypes (Fernie and Schauer, 2009; Redestig et al., 2011; Riedelsheimer et al., 2012a, 2012b; Witt et al., 2012; Degenkolbe et al., 2013). The accumulation of some metabolites has been reported to be directly related to the performance of potato (Solanum tuberosum) cultivars in beetle resistance in the field (Tai et al., 2014). Additionally, identical genomic regions were mapped as both agronomic and metabolic quantitative trait loci in field-grown maize and wheat (Triticum aestivum), indicating the utility of metabolic traits for breeding selection (Riedelsheimer et al., 2012b; Hill et al., 2015). A recent study showed that genetic gains in maize grain yield under DS were higher using a molecular marker-based approach than conventional breeding (Beyene et al., 2015).Here, we focused on the relationship between leaf metabolites and grain yield under drought, heat, and simultaneous drought and heat conditions in the field. The negative effect of DS on maize yield is especially acute during the reproductive stage between tassel emergence and early grain filling (Grant et al., 1989), when it is believed to induce premature seed desiccation and to limit grain filling. Grain is more susceptible to DS than vegetative tissues; therefore, the prediction of grain yield from the physiological parameter of leaves is a challenge (Sangoi and Salvador, 1998; Khodarahmpour and Hamidi, 2011). Nevertheless, maize yield is dependent on both the assimilate supply to the kernel (source) and the potential of the kernel to accommodate this assimilate (sink potential; Jones and Simmons, 1983). Breeding for modern temperate hybrids has focused more on the sink potential, particularly under stress conditions (Tollenaar and Lee, 2006); therefore, there should be considerable potential remaining to improve source ability. DS and HS would be anticipated largely to affect leaf metabolism and especially photosynthesis, compromising the source capacity of leaves (Chaves et al., 2009; Lawlor and Tezara, 2009; Osakabe et al., 2014). In keeping with this, drought was found to have the most dramatic effect on the metabolite composition in leaves compared with other organs in our previous greenhouse experiments (Witt et al., 2012). Since the source ability is closely related to leaf metabolism, the leaf metabolite profile should have a close relationship to grain yield particularly under conditions of stress. Given that several recent studies have indicated the importance of metabolic preadaptation to various stress tolerances in plants (Sanchez et al., 2011; Benina et al., 2013), we also postulate that basal metabolite levels under optimal growth conditions could be correlated to stress tolerance. In order to test this, metabolite profiles of the leaf blades of 10 hybrids were analyzed in field experiments conducted at the International Maize and Wheat Improvement Center (CIMMYT) subtropical experimental station in 2010 and 2011 in which the plants were exposed to singular or combined drought and heat stresses (DS+HS; Cairns et al., 2012a, 2013). The results are discussed both in the context of current models of stress tolerance and with respect to their practical implications for future breeding strategies.     

Focus on Ethylene: Ethylene and the Regulation of Physiological and Morphological Responses to Nutrient Deficiencies

To cope with nutrient deficiencies, plants develop both morphological and physiological responses. The regulation of these responses is not totally understood, but some hormones and signaling substances have been implicated. It was suggested several years ago that ethylene participates in the regulation of responses to iron and phosphorous deficiency. More recently, its role has been extended to other deficiencies, such as potassium, sulfur, and others. The role of ethylene in so many deficiencies suggests that, to confer specificity to the different responses, it should act through different transduction pathways and/or in conjunction with other signals. In this update, the data supporting a role for ethylene in the regulation of responses to different nutrient deficiencies will be reviewed. In addition, the results suggesting the action of ethylene through different transduction pathways and its interaction with other hormones and signaling substances will be discussed.When plants suffer from a mineral nutrient deficiency, they develop morphological and physiological responses (mainly in their roots) aimed to facilitate the uptake and mobilization of the limiting nutrient. After the nutrient has been acquired in enough quantity, these responses need to be switched off to avoid toxicity and conserve energy. In recent years, different plant hormones (e.g. ethylene, auxin, cytokinins, jasmonic acid, abscisic acid, brassinosteroids, GAs, and strigolactones) have been implicated in the regulation of these responses (Romera et al., 2007, 2011, 2015; Liu et al., 2009; Rubio et al., 2009; Kapulnik et al., 2011; Kiba et al., 2011; Iqbal et al., 2013; Zhang et al., 2014).Before the 1990s, there were several publications relating ethylene and nutrient deficiencies (cited in Lynch and Brown [1997] and Romera et al. [1999]) without establishing a direct implication of ethylene in the regulation of nutrient deficiency responses. In 1994, Romera and Alcántara (1994) published an article in Plant Physiology suggesting a role for ethylene in the regulation of Fe deficiency responses. In 1999, Borch et al. (1999) showed the participation of ethylene in the regulation of P deficiency responses. Since then, evidence has been accumulating in support of a role for ethylene in the regulation of both Fe (Romera et al., 1999, 2015; Waters and Blevins, 2000; Lucena et al., 2006; Waters et al., 2007; García et al., 2010, 2011, 2013, 2014; Yang et al., 2014) and P deficiency responses (Kim et al., 2008; Lei et al., 2011; Li et al., 2011; Nagarajan and Smith, 2012; Wang et al., 2012, 2014c). Both Fe and P may be poorly available in most soils, and plants develop similar responses under their deficiencies (Romera and Alcántara, 2004; Zhang et al., 2014). More recently, a role for ethylene has been extended to other deficiencies, such as K (Shin and Schachtman, 2004; Jung et al., 2009; Kim et al., 2012), S (Maruyama-Nakashita et al., 2006; Wawrzyńska et al., 2010; Moniuszko et al., 2013), and B (Martín-Rejano et al., 2011). Ethylene has also been implicated in both N deficiency and excess (Tian et al., 2009; Mohd-Radzman et al., 2013; Zheng et al., 2013), and its participation in Mg deficiency has been suggested (Hermans et al., 2010).In this update, we will review the information supporting a role for ethylene in the regulation of different nutrient deficiency responses. For information relating ethylene to other aspects of plant mineral nutrition, such as N₂ fixation and responses to excess of nitrate or essential heavy metals, the reader is referred to other reviews (for review, see Maksymiec, 2007; Mohd-Radzman et al., 2013; Steffens, 2014).     

Naturally Occurring Disseminated Group B Streptococcus Infections in Postnatal Rats

Group B Streptococcus (Streptococcus agalactiae, GBS) is a gram-positive commensal and occasional opportunistic pathogen of the human vaginal, respiratory, and intestinal tracts that can cause sepsis, pneumonia, or meningitis in human neonates, infants, and immunosuppressed persons. We report here on a spontaneous outbreak of postnatal GBS-associated disease in rats. Ten of 26 (38.5%) 21- to 24-d-old rat pups died or were euthanized due to a moribund state in a colony of rats transgenic for the human diphtheria toxin receptor on a Munich–Wistar–Frömter genetic background. Four pups had intralesional coccoid bacteria in various organs without accompanying inflammation. GBS was isolated from the liver of 2 of these pups and from skin abscesses in 3 littermates. A connection with the transgene could not be established. A treatment protocol was evaluated in the remaining breeding female rats. GBS is a potentially clinically significant spontaneous infection in various populations of research rats, with some features that resemble late-onset postnatal GBS infection in human infants.Abbreviations: GBS, Group B Streptococcus; MWF, Munich Wistar Frömter; hDTR, human diphtheria toxin receptorStreptococci are gram-positive, coccoid bacteria that typically are classified according to their hemolytic capacity. α-hemolytic streptococci produce a zone of partial hemolysis that appears greenish on blood agar, whereas β-hemolytic streptococci produce a zone of complete hemolysis, and γ-hemolytic organisms produce no hemolysis on blood agar.²⁴ The β-hemolytic streptococci are further subdivided into Lancefield groups (A through G), according to cell-wall carbohydrate antigens.^24,29,39 The group B β-hemolytic Streptococcus (GBS) have been speciated as Streptococcus agalactiae.^28,39 It was first isolated as a causative agent of mastitis in cattle.²⁹ This organism has since been recognized as a cause of severe infection in human neonates.^28,39 In humans, GBS is harbored asymptomatically in the maternal genitourinary tract.^24,28 Infants can be infected and present with serious systemic disease in the first week of life (early-onset GBS) or from 1 wk to 3 mo of age (late-onset GBS).³⁹ In laboratory animals, rats have been used experimentally as models for neonatal^{1,6,7,20,37,38,43,44,47,50,51} or adult⁴⁵ GBS infection, but to our knowledge, GBS has not been associated with spontaneous disease in rats.     

Clinicopathologic Characteristics,Prevalence, and Risk Factors of Spontaneous Diabetes in Sooty Mangabeys (Cercocebus atys)

In 2008, clinical observations in our colony of sooty mangabeys (Cercocebus atys) suggested a high frequency of type 2 diabetes. Postmortem studies of diabetic animals revealed dense amyloid deposits in pancreatic islets. To investigate these findings, we screened our colony (97 male mangabeys; 99 female mangabeys) for the disease from 2008 to 2012. The overall prevalence of diabetes was 11% and of prediabetes was 7%, which is nearly double that reported for other primate species (less than 6%). Fructosamine and triglyceride levels were the best indicators of diabetes; total cholesterol and glycated hemoglobin were not associated with disease. Increasing age was a significant risk factor: prevalence increased from 0% in infants, juveniles, and young adults to 11% in adults and 19% in geriatric mangabeys. Sex, medroxyprogesterone acetate exposure, and SIV status were unrelated to disease. Weight was marginally higher in prediabetics, but body condition did not indicate obesity. Of the 49 mangabeys that were necropsied after clinical euthanasia or death from natural causes, 22 were diabetic; all 22 animals demonstrated pancreatic amyloid, and most had more than 75% of islets replaced with amyloid. We conclude that type 2 diabetes is more common in mangabeys than in other primate species. Diabetes in mangabeys has some unusual pathologic characteristics, including the absence of altered cholesterol levels and glycated hemoglobin but a robust association of pancreatic insular amyloidosis with clinical diabetes. Future research will examine the genetic basis of mangabey diabetes and evaluate additional diagnostic tools using imaging and serum markers.Abbreviations: HbA1c, glycated hemoglobin; MPA, medroxyprogesterone acetate; YNPRC, Yerkes National Primate Research CenterSooty mangabeys (Cercocebus atys) are Old World NHP that are native to West Africa. Historically their use in research has been limited to infectious disease studies, leprosy studies, and behavioral research.^14,25 Over the past 20 to 30 y, they have been used in HIV–AIDS research. Mangabeys are natural hosts of SIV_smm, which is recognized as the origin of HIV2 infection in humans.^7,8,30,36,42 SIV typically is nonpathogenic in mangabeys despite high levels of virus replication, which makes this species a unique and invaluable model in AIDS research.^7,30,36,42 Our facility maintains a colony of approximately 200 sooty mangabeys. In 2008 clinical observations of relative hyperglycemia, glucosuria, and weight loss in our colony suggested that type 2 diabetes mellitus occurred at a relatively high frequency in this population. Spontaneous diabetes was found in 10% of the colony, and 5% of animals were prediabetic; this incidence is higher than that typically reported for other NHP species, such as cynomolgus macaques (less than 1% to 2%)²² and chimpanzees (less than 1%).³⁷ The prevalence of spontaneous diabetes in humans is typically 8.3%.^2,6,22,37 In addition, necropsies revealed that many affected animals had dense amyloid deposits in pancreatic islet cells. Insular amyloidosis was seen on histology, with a total replacement of islets by amyloid deposition in advanced diabetes. Advanced diabetes was determined by increased weight loss and severity of relative hyperglycemia. The increased clinical prevalence of diabetes in our mangabey colony prompted additional characterization of the clinicopathologic profile, risk factors, and prevalence of diabetes in our mangabey colony.The form of diabetes in this mangabey colony is characterized as type 2 diabetes mellitus, as they have hyperglycemia, hypertriglyceridemia, and islet amyloidosis. Type 2 diabetes mellitus is the most common of the 3 forms of diabetes, and has been documented in humans and NHP,^22,31,37,55 including rhesus macaques (Macaca mulatta), cynomolgus macaques (Macaca fascicularis), Celebes crested macaques (Macaca nigra), bonnet macaques (Macaca radiate), pigtailed macaques (Macaca nemestrina), vervet monkeys (Chlorocebus pygerythrus), squirrel monkeys (Saimiri sciureus), chimpanzees (Pan troglodytes), and woolly monkeys (Lagothrix spp.).^{1,24,31,52,55} Type 2 diabetes is a chronic metabolic disorder in which insulin resistance occurs in liver, muscle, and adipose tissue. As type 2 diabetes progresses, it also can be characterized as a relative insulin deficiency.^{1,6,15,22,29,31,37,55} The initial clinical presentation of diabetes in humans and NHP includes polydipsia, polyuria, polyphagia, weight loss, and lethargy.^{1,6,22,27,31,37,55} Similar presentation was observed in our colony of diabetic mangabeys.Diagnostic criteria of diabetes in NHP species is similar to that for humans and is based on clinical symptoms and routine lab tests, including serum chemistry panel to evaluate persistent fasting hyperglycemia, hypertriglyceridemia, and hypercholesterolemia.^{2,6,11,16-18,21,22,29,31,37,48-50,52,55} Hypertriglyceridemia and hypercholesterolemia frequently are elevated due to diabetes and therefore are used as supportive diagnostic markers. In addition, the disease is characterized by transient hyperinsulinemia followed by insulin deficiency subsequent to glucose challenge. Urinalysis is used to evaluate glucosuria and ketonuria. These tests are not exclusive for diagnosing diabetes and can be inconsistent between species, thus making conclusive diagnosis challenging. For example, hyperglycemia can be a transient finding associated with recent food intake or stress associated with restraint for blood sample collection or anesthetic access, whereas hypertriglyceridemia can be seen in obese animals and those with other metabolic diseases such as pancreatitis and hypothyroidism.^1,22,37,55The typical clinical approach to the diagnosis of diabetes in NHP and other veterinary patients includes evaluation of fructosamine and glycated hemoglobin (HbA1c) levels and glucose tolerance testing. These tests are indices of glycemic control and are used in clinical settings primarily to assess prognosis and response to treatment; they are also useful for the initial diagnosis of diabetes when used in parallel with serum chemistry markers. Fructosamine and HbA1c can both provide information on long-term glycemic control, because fructosamine reflects average blood glucose levels over 2 to 3 wk whereas HbA1c reflects average blood glucose over 2 to 3 mo preceding blood collection. HbA1c is the primary test for diabetes in human medicine,^6,31,35,37 whereas fructosamine is commonly used in veterinary medicine. Glucose tolerance testing provides an indirect measure of insulin sensitivity, but it is not frequently used clinically in NHP because of the requirement for prolonged physical restraint or sedation.^{1,21,22,26,27,34,37,55}Prevention and management of diabetes in NHP and humans can be achieved by identifying potential risk factors, including age, weight, sex, genetics, hormone drug exposure, and viral status.^{1,6,15,22,29,31,37,42,55} Advanced age, obesity, sex, and genetics are associated with diabetes in some species of NHP and humans.^{1,6,15,22,29,31,37,55} In addition, exposure to drugs such as medroxyprogesterone acetate (MPA) is suspected to be linked to diabetes due to the hormonal effects of progesterone impacting glucoregulatory function.^{1,6,10,22,23,31,34,55} MPA exposure is of interest, because it is used regularly in our mangabey colony as both a contraceptive and as therapy for endometriosis. In addition, SIV status is being evaluated as a risk factor, because a portion of our colony is SIV positive. Although HIV is not thought to be associated with diabetes in people, SIV pathogenesis in mangabeys differs; therefore it was of interest to explore the possible association of SIV and diabetes in mangabeys.^7,30,36,42 Pancreatic insular amyloidosis has been documented to be associated with type 2 diabetes in several species. Amyloidosis is a group of disorders that are caused by extracellular deposition of misfolded proteins that can result in impaired function of any organ.^{15,20,23,28,32,43,45,48,49} Because a high incidence of pancreatic insular amyloid was noted at necropsy, we sought to document the relationship with clinical diabetes in mangabeys.Spontaneous type 2 diabetes mellitus has been well documented in several species of NHP. Because the literature contains little information regarding the clinicopathologic features (the ‘profile’), risk factors, and prevalence of spontaneous diabetes mellitus in sooty mangabeys, the primary aims of the current study were 1) to determine whether elevated levels of fasting blood glucose, fructosamine, HbA1c, triglycerides, and total cholesterol levels are reliable diagnostic markers of type 2 diabetes mellitus in this NHP species; 2) to determine whether age, sex, MPA exposure, and SIV status influence the risk of diabetes; 3) to determine whether body weight influences diabetic status; 4) to evaluate the relationship between pancreatic amyloidosis and diabetes mellitus; and 5) to characterize the prevalence of diabetes mellitus in the mangabey population at our institution. To our knowledge, this report is the first to describe the natural occurrence of type 2 diabetes mellitus within a captive colony of sooty mangabeys. We hypothesized that blood glucose, fructosamine, HbA1c, triglyceride, and total cholesterol would be reliable diagnostic markers and that age, sex, and MPA exposure would influence the risk of diabetes in this species.     

Responses of Arabidopsis and Wheat to Rising CO2 Depend on Nitrogen Source and Nighttime CO2 Levels

A major contributor to the global carbon cycle is plant respiration. Elevated atmospheric CO₂ concentrations may either accelerate or decelerate plant respiration for reasons that have been uncertain. We recently established that elevated CO₂ during the daytime decreases plant mitochondrial respiration in the light and protein concentration because CO₂ slows the daytime conversion of nitrate (NO₃−) into protein. This derives in part from the inhibitory effect of CO₂ on photorespiration and the dependence of shoot NO₃− assimilation on photorespiration. Elevated CO₂ also inhibits the translocation of nitrite into the chloroplast, a response that influences shoot NO₃− assimilation during both day and night. Here, we exposed Arabidopsis (Arabidopsis thaliana) and wheat (Triticum aestivum) plants to daytime or nighttime elevated CO₂ and supplied them with NO₃− or ammonium as a sole nitrogen (N) source. Six independent measures (plant biomass, shoot NO₃−, shoot organic N, ¹⁵N isotope fractionation, ¹⁵NO₃⁻ assimilation, and the ratio of shoot CO₂ evolution to O₂ consumption) indicated that elevated CO₂ at night slowed NO₃− assimilation and thus decreased dark respiration in the plants reliant on NO₃−. These results provide a straightforward explanation for the diverse responses of plants to elevated CO₂ at night and suggest that soil N source will have an increasing influence on the capacity of plants to mitigate human greenhouse gas emissions.The CO₂ concentration in Earth’s atmosphere has increased from about 270 to 400 µmol mol^–1 since 1800, and may double before the end of the century (Intergovernmental Panel on Climate Change, 2013). Plant responses to such increases are highly variable, but plant nitrogen (N) concentrations generally decline under elevated CO₂ (Cotrufo et al., 1998; Long et al., 2004). One explanation for this decline is that CO₂ inhibits nitrate (NO₃−) assimilation into protein in the shoots of C₃ plants during the daytime (Bloom et al., 2002, 2010, 2012, 2014; Cheng et al., 2012; Pleijel and Uddling, 2012; Myers et al., 2014; Easlon et al., 2015; Pleijel and Högy, 2015). This derives in part from the inhibitory effect of CO₂ on photorespiration (Foyer et al., 2009) and the dependence of shoot NO₃− assimilation on photorespiration (Rachmilevitch et al., 2004; Bloom, 2015).A key factor in global carbon budgets is plant respiration at night (Amthor, 1991; Farrar and Williams, 1991; Drake et al., 1999; Leakey et al., 2009). Nighttime elevated CO₂ may inhibit, have a negligible effect on, or stimulate dark respiration, depending on the plant species (Bunce, 2001, 2003; Wang and Curtis, 2002), plant development stage (Wang et al., 2001; Li et al., 2013), experimental approach (Griffin et al., 1999; Baker et al., 2000; Hamilton et al., 2001; Bruhn et al., 2002; Jahnke and Krewitt, 2002; Bunce, 2004), and total N supply (Markelz et al., 2014). The current study is, to our knowledge, the first to examine the influence of N source, NO₃− versus ammonium (NH₄+), on plant dark respiration at elevated CO₂ during the night.Plant organic N compounds account for less than 5% of the total dry weight of a plant, but conversion of NO₃− into organic N expends about 25% of the total energy in shoots (Bloom et al., 1989) and roots (Bloom et al., 1992). During the day, photorespiration supplies a portion of the energy (Rachmilevitch et al., 2004; Foyer et al., 2009), but at night, this energetic cost is borne entirely by the respiration of C substrates (Amthor, 1995) and may divert a substantial amount of reductant from the mitochondrial electron transport chain (Cousins and Bloom, 2004). The relative importance of NO₃− assimilation at night versus the day, however, is still a matter of intense debate (Nunes-Nesi et al., 2010). Here, we estimated NO₃− assimilation using several independent methods and show in Arabidopsis (Arabidopsis thaliana) and wheat (Triticum aestivum), two diverse C₃ plants, that NO₃− assimilation at night can be substantial, and that elevated CO₂ at night inhibits this process.     

Surveying Rubisco Diversity and Temperature Response to Improve Crop Photosynthetic Efficiency

The threat to global food security of stagnating yields and population growth makes increasing crop productivity a critical goal over the coming decades. One key target for improving crop productivity and yields is increasing the efficiency of photosynthesis. Central to photosynthesis is Rubisco, which is a critical but often rate-limiting component. Here, we present full Rubisco catalytic properties measured at three temperatures for 75 plants species representing both crops and undomesticated plants from diverse climates. Some newly characterized Rubiscos were naturally “better” compared to crop enzymes and have the potential to improve crop photosynthetic efficiency. The temperature response of the various catalytic parameters was largely consistent across the diverse range of species, though absolute values showed significant variation in Rubisco catalysis, even between closely related species. An analysis of residue differences among the species characterized identified a number of candidate amino acid substitutions that will aid in advancing engineering of improved Rubisco in crop systems. This study provides new insights on the range of Rubisco catalysis and temperature response present in nature, and provides new information to include in models from leaf to canopy and ecosystem scale.In a changing climate and under pressure from a population set to hit nine billion by 2050, global food security will require massive changes to the way food is produced, distributed, and consumed (Ort et al., 2015). To match rising demand, agricultural production must increase by 50 to 70% in the next 35 years, and yet the gains in crop yields initiated by the green revolution are slowing, and in some cases, stagnating (Long and Ort, 2010; Ray et al., 2012). Among a number of areas being pursued to increase crop productivity and food production, improving photosynthetic efficiency is a clear target, offering great promise (Parry et al., 2007; von Caemmerer et al., 2012; Price et al., 2013; Ort et al., 2015). As the gatekeeper of carbon entry into the biosphere and often acting as the rate-limiting step of photosynthesis, Rubisco, the most abundant enzyme on the planet (Ellis, 1979), is an obvious and important target for improving crop photosynthetic efficiency.Rubisco is considered to exhibit comparatively poor catalysis, in terms of catalytic rate, specificity, and CO₂ affinity (Tcherkez et al., 2006; Andersson, 2008), leading to the suggestion that even small increases in catalytic efficiency may result in substantial improvements to carbon assimilation across a growing season (Zhu et al., 2004; Parry et al., 2013; Galmés et al., 2014a; Carmo-Silva et al., 2015). If combined with complimentary changes such as optimizing other components of the Calvin Benson or photorespiratory cycles (Raines, 2011; Peterhansel et al., 2013; Simkin et al., 2015), optimized canopy architecture (Drewry et al., 2014), or introducing elements of a carbon concentrating mechanism (Furbank et al., 2009; Lin et al., 2014a; Hanson et al., 2016; Long et al., 2016), Rubisco improvement presents an opportunity to dramatically increase the photosynthetic efficiency of crop plants (McGrath and Long, 2014; Long et al., 2015; Betti et al., 2016). A combination of the available strategies is essential for devising tailored solutions to meet the varied requirements of different crops and the diverse conditions under which they are typically grown around the world.Efforts to engineer an improved Rubisco have not yet produced a “super Rubisco” (Parry et al., 2007; Ort et al., 2015). However, advances in engineering precise changes in model systems continue to provide important developments that are increasing our understanding of Rubisco catalysis (Spreitzer et al., 2005; Whitney et al., 2011a, 2011b; Morita et al., 2014; Wilson et al., 2016), regulation (Andralojc et al., 2012; Carmo-Silva and Salvucci, 2013; Bracher et al., 2015), and biogenesis (Saschenbrecker et al., 2007; Whitney and Sharwood, 2008; Lin et al., 2014b; Hauser et al., 2015; Whitney et al., 2015).A complementary approach is to understand and exploit Rubisco natural diversity. Previous characterization of Rubisco from a limited number of species has not only demonstrated significant differences in the underlying catalytic parameters, but also suggests that further undiscovered diversity exists in nature and that the properties of some of these enzymes could be beneficial if present in crop plants (Carmo-Silva et al., 2015). Recent studies clearly illustrate the variation possible among even closely related species (Galmés et al., 2005, 2014b, 2014c; Kubien et al., 2008; Andralojc et al., 2014; Prins et al., 2016).Until recently, there have been relatively few attempts to characterize the consistency, or lack thereof, of temperature effects on in vitro Rubisco catalysis (Sharwood and Whitney, 2014), and often studies only consider a subset of Rubisco catalytic properties. This type of characterization is particularly important for future engineering efforts, enabling specific temperature effects to be factored into any attempts to modify crops for a future climate. In addition, the ability to coanalyze catalytic properties and DNA or amino acid sequence provides the opportunity to correlate sequence and biochemistry to inform engineering studies (Christin et al., 2008; Kapralov et al., 2011; Rosnow et al., 2015). While the amount of gene sequence information available grows rapidly with improving technology, knowledge of the corresponding biochemical variation resulting has yet to be determined (Cousins et al., 2010; Carmo-Silva et al., 2015; Sharwood and Whitney, 2014; Nunes-Nesi et al., 2016).This study aimed to characterize the catalytic properties of Rubisco from diverse species, comprising a broad range of monocots and dicots from diverse environments. The temperature dependence of Rubisco catalysis was evaluated to tailor Rubisco engineering for crop improvement in specific environments. Catalytic diversity was analyzed alongside the sequence of the Rubisco large subunit gene, rbcL, to identify potential catalytic switches for improving photosynthesis and productivity. In vitro results were compared to the average temperature of the warmest quarter in the regions where each species grows to investigate the role of temperature in modulating Rubisco catalysis.     

Multiscale Metabolic Modeling: Dynamic Flux Balance Analysis on a Whole-Plant Scale

Plant metabolism is characterized by a unique complexity on the cellular, tissue, and organ levels. On a whole-plant scale, changing source and sink relations accompanying plant development add another level of complexity to metabolism. With the aim of achieving a spatiotemporal resolution of source-sink interactions in crop plant metabolism, a multiscale metabolic modeling (MMM) approach was applied that integrates static organ-specific models with a whole-plant dynamic model. Allowing for a dynamic flux balance analysis on a whole-plant scale, the MMM approach was used to decipher the metabolic behavior of source and sink organs during the generative phase of the barley (Hordeum vulgare) plant. It reveals a sink-to-source shift of the barley stem caused by the senescence-related decrease in leaf source capacity, which is not sufficient to meet the nutrient requirements of sink organs such as the growing seed. The MMM platform represents a novel approach for the in silico analysis of metabolism on a whole-plant level, allowing for a systemic, spatiotemporally resolved understanding of metabolic processes involved in carbon partitioning, thus providing a novel tool for studying yield stability and crop improvement.Plants are of vital significance as a source of food (Grusak and DellaPenna, 1999; Rogalski and Carrer, 2011), feed (Lu et al., 2011), energy (Tilman et al., 2006; Parmar et al., 2011), and feedstocks for the chemical industry (Metzger and Bornscheuer, 2006; Kinghorn et al., 2011). Given the close connection between plant metabolism and the usability of plant products, there is a growing interest in understanding and predicting the behavior and regulation of plant metabolic processes. In order to increase crop quality and yield, there is a need for methods guiding the rational redesign of the plant metabolic network (Schwender, 2009).Mathematical modeling of plant metabolism offers new approaches to understand, predict, and modify complex plant metabolic processes. In plant research, the issue of metabolic modeling is constantly gaining attention, and different modeling approaches applied to plant metabolism exist, ranging from highly detailed quantitative to less complex qualitative approaches (for review, see Giersch, 2000; Morgan and Rhodes, 2002; Poolman et al., 2004; Rios-Estepa and Lange, 2007).A widely used modeling approach is flux balance analysis (FBA), which allows the prediction of metabolic capabilities and steady-state fluxes under different environmental and genetic backgrounds using (non)linear optimization (Orth et al., 2010). Assuming steady-state conditions, FBA has the advantage of not requiring the knowledge of kinetic parameters and, therefore, can be applied to model detailed, large-scale systems. In recent years, the FBA approach has been applied to several different plant species, such as maize (Zea mays; Dal’Molin et al., 2010; Saha et al., 2011), barley (Hordeum vulgare; Grafahrend-Belau et al., 2009b; Melkus et al., 2011; Rolletschek et al., 2011), rice (Oryza sativa; Lakshmanan et al., 2013), Arabidopsis (Arabidopsis thaliana; Poolman et al., 2009; de Oliveira Dal’Molin et al., 2010; Radrich et al., 2010; Williams et al., 2010; Mintz-Oron et al., 2012; Cheung et al., 2013), and rapeseed (Brassica napus; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011), as well as algae (Boyle and Morgan, 2009; Cogne et al., 2011; Dal’Molin et al., 2011) and photoautotrophic bacteria (Knoop et al., 2010; Montagud et al., 2010; Boyle and Morgan, 2011). These models have been used to study different aspects of metabolism, including the prediction of optimal metabolic yields and energy efficiencies (Dal’Molin et al., 2010; Boyle and Morgan, 2011), changes in flux under different environmental and genetic backgrounds (Grafahrend-Belau et al., 2009b; Dal’Molin et al., 2010; Melkus et al., 2011), and nonintuitive metabolic pathways that merit subsequent experimental investigations (Poolman et al., 2009; Knoop et al., 2010; Rolletschek et al., 2011). Although FBA of plant metabolic models was shown to be capable of reproducing experimentally determined flux distributions (Williams et al., 2010; Hay and Schwender, 2011b) and generating new insights into metabolic behavior, capacities, and efficiencies (Sweetlove and Ratcliffe, 2011), challenges remain to advance the utility and predictive power of the models.Given that many plant metabolic functions are based on interactions between different subcellular compartments, cell types, tissues, and organs, the reconstruction of organ-specific models and the integration of these models into interacting multiorgan and/or whole-plant models is a prerequisite to get insight into complex plant metabolic processes organized on a whole-plant scale (e.g. source-sink interactions). Almost all FBA models of plant metabolism are restricted to one cell type (Boyle and Morgan, 2009; Knoop et al., 2010; Montagud et al., 2010; Cogne et al., 2011; Dal’Molin et al., 2011), one tissue or one organ (Grafahrend-Belau et al., 2009b; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011; Mintz-Oron et al., 2012), and only one model exists taking into account the interaction between two cell types by specifying the interaction between mesophyll and bundle sheath cells in C4 photosynthesis (Dal’Molin et al., 2010). So far, no model representing metabolism at the whole-plant scale exists.Considering whole-plant metabolism raises the problem of taking into account temporal and environmental changes in metabolism during plant development and growth. Although classical static FBA is unable to predict the dynamics of metabolic processes, as the network analysis is based on steady-state solutions, time-dependent processes can be taken into account by extending the classical static FBA to a dynamic flux balance analysis (dFBA), as proposed by Mahadevan et al. (2002). The static (SOA) and dynamic optimization approaches introduced in this work provide a framework for analyzing the transience of metabolism by integrating kinetic expressions to dynamically constrain exchange fluxes. Due to the requirement of knowing or estimating a large number of kinetic parameters, so far dFBA has only been applied to a plant metabolic model once, to study the photosynthetic metabolism in the chloroplasts of C3 plants by a simplified model of five biochemical reactions (Luo et al., 2009). Integrating a dynamic model into a static FBA model is an alternative approach to perform dFBA.In this study, a multiscale metabolic modeling (MMM) approach was applied with the aim of achieving a spatiotemporal resolution of cereal crop plant metabolism. To provide a framework for the in silico analysis of the metabolic dynamics of barley on a whole-plant scale, the MMM approach integrates a static multiorgan FBA model and a dynamic whole-plant multiscale functional plant model (FPM) to perform dFBA. The performance of the novel whole-plant MMM approach was tested by studying source-sink interactions during the seed developmental phase of barley plants.     

Endometrial Decidualization and Deciduosis in Aged Rhesus Macaques (Macaca mulatta)

Superficial decidualization of the endometrial stroma is an essential feature of the implantation stage of pregnancy in rhesus macaques and other primates. Decidualization involves proliferation of the endometrial stromal cells, with differentiation into morphologically distinct decidual cells. Previous reports involving nonpregnant rhesus monkeys have described localized and widespread endometrial decidualization in response to administration of progesterone and synthetic progestogens. Ectopic decidua or ‘deciduosis’ describes the condition in which groups of decidual cells are located outside of the endometrium, most often in the ovaries, uterus and cervix but also in various other organs. In humans, most cases of deciduosis are associated with normal pregnancy, and ectopic decidua can be found in the ovary in nearly all term pregnancies. Here we describe pronounced endometrial decidualization in 2 rhesus macaques. Both macaques had been treated long-term with medroxyprogesterone acetate for presumed endometriosis, which was confirmed in one of the macaques at postmortem examination. In one animal, florid extrauterine and peritoneal serosal decidualization was admixed multifocally with carcinomatosis from a primary colonic adenocarcinoma. Cells constituting endometrial and serosal decidualization reactions were immunopositive for the stromal markers CD10, collagen IV, smooth muscle actin, and vimentin and immunonegative for cytokeratin. In contrast, carcinomatous foci were cytokeratin-positive. To our knowledge, this report describes the first cases of serosal peritoneal decidualization in rhesus macaques. The concurrent presentation of serosal peritoneal decidualization with carcinomatosis is unique.Abbreviations: GnRH, gonadotropin-releasing hormone; PAS, periodic acid–Schiff; SMA, smooth-muscle actinSuperficial decidualization of the endometrial stroma is an essential feature of the implantation stage of pregnancy in rhesus macaques and other primates.^13,27,29,37 This process typically begins, and is most prominent, adjacent to the spiral arteries, eventually expanding to affect the endometrium uniformly.³⁵ The endometrial stroma surrounds and supports the endometrial glands and is composed mainly of endometrial stromal cells and blood vessels.³⁵ Decidualization involves proliferation of the endometrial stromal cells, with differentiation into morphologically distinct decidual cells.^7,27,38 Endometrial stromal cells transform into large, polyhedral, cytoplasm-rich cells with large amounts of stored glycogen and are often binucleated or polyploid in character.^{6,13,27,30,35} Ultrastructurally, decidualized cells have numerous ribosomes, prominent rough endoplasmic reticulum and Golgi complexes, and cytoplasmic accumulation of glycogen and lipid droplets.^13,35 Consistent with their stromal origin, decidualized cells express mesenchymal immunohistochemical markers, such as vimentin, desmin, and muscle-specific actin.^{6,7,14,16,20,22}Initiation of decidualization by attachment of the blastocyst to the uterine epithelium depends on previous sensitization by progesterone secretion, after a brief priming by estrogen.^12,13,27 Estrogen and progesterone regulate a series of complex interactions at the interface between the developing embryo and the cells in the stromal compartment, leading to the formation of a differentiated maternal tissue (decidua) that supports embryo growth and maintains early pregnancy.²⁷ Postovulatory levels of circulating progesterone increase and help maintain the differentiation of decidual cells.^{7,13,33,37,38}Ectopic decidua or ‘deciduosis’ describes the condition in which groups of decidual cells reside outside of the endometrium, most often in the ovaries, uterus, and cervix; the fallopian tubes, peritoneum, omentum, diaphragm, liver, skin, spleen, appendix, abdominal–pelvic lymph nodes, renal pelvis, and lungs of women have also been reported as affected.^{6,14,18,20,22,28,29,38} In humans, most cases of deciduosis are associated with normal pregnancy, and ectopic decidua have been reported in the ovary in 90.5% to 100% of term pregnancies.^{6-8,14,20,22,28-30,38} Occasional cases in nonpregnant or postmenopausal women have been attributed to progesterone-secreting active corpora lutea, progesterone secretion by the adrenal cortex, trophoblastic disease, exogenous progestational agents, and pelvic irradiation.^{6-8,14,18,20,22,28,38} Deciduosis is usually an incidental finding that regresses postpartum within 4 to 6 wk; rarely, florid reactions have been reported to cause peritonitis, adhesions, hydronephrosis and hematuria, acute bowel obstruction or perforation (or both), abdominal pain mimicking appendicitis, massive and occasionally fatal hemoperitoneum, vaginal bleeding, and pneumothorax.^{6,7,14,18,20,22,28,29,31}Previous reports involving nonpregnant rhesus macaques have described localized and widespread endometrial decidualization in response to the administration of progesterone, synthetic progestogens, or progesterone-releasing bioactive intrauterine devices and intravaginal rings and have referred to these changes as ‘pseudodecidualization’ to indicate the absence of pregnancy in these animals.^12,33,35,37 In macaques given low (but superphysiologic) levels of progestogens, decidual changes have been noted in localized regions (around spiral arteries and underneath superficial epithelium), whereas high doses of progesterone or synthetic progestagens can cause a more pronounced and extensive reaction.³⁵In cynomolgus macaques, extrauterine decidual cell plaques are rare histologic findings in the subcoelomic mesenchyme of the ovarian cortex.^8,30 Despite the frequency of the condition in women, deciduosis is postulated to be a rarely documented lesion in primates because it is most often observed in conjunction with pregnancy, and pregnant cynomolgus macaques are seldom used in toxicity studies.⁸ Here we describe the pronounced endometrial decidualization of 2 rhesus macaques, one of which also had florid extrauterine and peritoneal decidualization that was admixed multifocally with carcinomatosis. Both macaques had been treated long-term with medroxyprogesterone acetate for presumed endometriosis, which was confirmed in one of the macaques at postmortem examination. To our knowledge, this report describes the first cases of peritoneal decidualization in rhesus macaques as well as the concurrent occurrence of carcinomatosis, endometriosis and peritoneal decidualization in a macaque. The extensive intermixing of the cell populations presented a diagnostic challenge at pathologic examination, and accurate diagnosis was achieved only through the use of multiple immunohistochemical markers.     

Extracellular DNA Is Required for Root Tip Resistance to Fungal Infection

Plant defense involves a complex array of biochemical interactions, many of which occur in the extracellular environment. The apical 1- to 2-mm root tip housing apical and root cap meristems is resistant to infection by most pathogens, so growth and gravity sensing often proceed normally even when other sites on the root are invaded. The mechanism of this resistance is unknown but appears to involve a mucilaginous matrix or “slime” composed of proteins, polysaccharides, and detached living cells called “border cells.” Here, we report that extracellular DNA (exDNA) is a component of root cap slime and that exDNA degradation during inoculation by a fungal pathogen results in loss of root tip resistance to infection. Most root tips (>95%) escape infection even when immersed in inoculum from the root-rotting pathogen Nectria haematococca. By contrast, 100% of inoculated root tips treated with DNase I developed necrosis. Treatment with BAL31, an exonuclease that digests DNA more slowly than DNase I, also resulted in increased root tip infection, but the onset of infection was delayed. Control root tips or fungal spores treated with nuclease alone exhibited normal morphology and growth. Pea (Pisum sativum) root tips incubated with [³²P]dCTP during a 1-h period when no cell death occurs yielded root cap slime containing ³²P-labeled exDNA. Our results suggest that exDNA is a previously unrecognized component of plant defense, an observation that is in accordance with the recent discovery that exDNA from white blood cells plays a key role in the vertebrate immune response against microbial pathogens.Root diseases caused by soil-borne plant pathogens are a perennial source of crop loss worldwide (Bruehl, 1986; Curl and Truelove, 1986). These diseases are of increasing concern, as pesticides like methyl bromide are removed from the market due to environmental concerns (Gilreath et al., 2005). One possible alternative means of crop protection is to exploit natural mechanisms of root disease resistance (Nelson, 1990; Goswami and Punja, 2008; Shittu et al., 2009). Direct observation of root systems under diverse conditions has revealed that root tips, in general, are resistant to infection even when lesions are initiated elsewhere on the same plant root (Foster et al., 1983; Bruehl, 1986; Curl and Truelove, 1986; Smith et al., 1992; Gunawardena et al., 2005; Wen et al., 2007). This form of disease resistance is important for crop production because root growth and its directional movement in response to gravity, water, and other signals can proceed normally as long as the root tip is not invaded. The 1- to 2-mm apical region of roots houses the root meristems required for root growth and cap development, and when infection does occur, root development ceases irreversibly within a few hours even in the absence of severe necrosis (Gunawardena and Hawes, 2002). Mechanisms underlying root tip resistance to infection are unclear, but the phenomenon appears to involve root cap “slime,” a mucilaginous matrix produced by the root cap (Morré et al., 1967; Rougier et al., 1979; Foster, 1982; Chaboud, 1983; Guinel and McCully, 1986; Moody et al., 1988; Knee et al., 2001; Barlow, 2003; Iijima et al., 2008). Within the root cap slime of cereals, legumes, and most other crop species are specialized populations of living cells called root “border cells” (Supplemental Fig. S1; Hawes et al., 2000). Border cell numbers increase in response to pathogens and toxins such as aluminum, and the cell populations maintain a high rate of metabolic activity even after detachment from the root cap periphery (Brigham et al., 1995; Miyasaka and Hawes, 2000).As border cells detach from roots of cereals and legumes, a complex of more than 100 proteins, termed the root cap secretome, is synthesized and exported from living cells into the matrix ensheathing the root tip (Brigham et al., 1995). The profile of secreted proteins changes in response to challenge with soil-borne bacteria (De-la-Peña et al., 2008). In pea (Pisum sativum), root tip resistance to infection is abolished in response to proteolytic degradation of the root cap secretome (Wen et al., 2007). In addition to an array of antimicrobial enzymes and other proteins known to be components of the extracellular matrix and apoplast of higher plants, the DNA-binding protein histone H4 unexpectedly was found to be present among the secreted proteins (Wen et al., 2007). One explanation for the presence of histone is global leakage of material from disrupted nuclei in dead cells, but no cell death occurs during delivery of the secretome (Brigham et al., 1995; Wen et al., 2007). An alternative explanation for the presence of a secreted DNA-binding protein is that extracellular DNA (exDNA) also is present in root cap slime.exDNA has long been known to be a component of slimy biological matrices ranging from purulent localized human infections to bacterial capsules, biofilms, and snail exudate (Sherry and Goeller, 1950; Leuchtenberger and Schrader, 1952; Braun and Whallon, 1954; Smithies and Gibbons, 1955; Catlin, 1956; Fahy et al., 1993; Allesen-Holm et al., 2006; Spoering and Gilmore, 2006; Qin et al., 2007; Izano et al., 2008). Specialized white blood cells in humans and other species including fish recently have been shown to deploy a complex neutrophil extracellular “trap” (NET), composed of DNA and a collection of enzymes, in response to infection (Brinkmann et al., 2004; Brinkmann and Zychlinsky, 2007; Palić et al., 2007; Wartha et al., 2007; Yousefi et al., 2008). NETs appear to kill bacterial, fungal, and protozoan pathogens by localizing them within a matrix of antimicrobial peptides and proteins (Urban et al., 2006; Wartha et al., 2007; Guimaraes-Costa et al., 2009). Several extracellular peptides and proteins implicated in neutrophil function, including histone, also are present within the pea root cap secretome (Wen et al., 2007). exDNA linked with extracellular histone is a structural component of NETs, and treatment with DNase destroys NET integrity and function (Wartha et al., 2007). Moreover, human pathogens including group A Streptococcus and Streptococcus pneumoniae release extracellular DNase (Sherry and Goeller, 1950). When these activities are eliminated by mutagenesis of the encoding genes, bacteria lose their normal ability to escape the NET and multiply at the site of infection (Sumby et al., 2005; Buchanan et al., 2006). Here, we report that, in addition to histone and other secretome proteins, exDNA also is a component of root cap slime. When this exDNA is digested enzymatically, root tip resistance to infection is abolished.     

Estimating Breeding Values With Molecular Relatedness and Reconstructed Pedigrees in Natural Mating Populations of Common Sole,Solea Solea

Captive populations where natural mating in groups is used to obtain offspring typically yield unbalanced population structures with highly skewed parental contributions and unknown pedigrees. Consequently, for genetic parameter estimation, relationships need to be reconstructed or estimated using DNA marker data. With missing parents and natural mating groups, commonly used pedigree reconstruction methods are not accurate and lead to loss of data. Relatedness estimators, however, infer relationships between all animals sampled. In this study, we compared a pedigree relatedness method and a relatedness estimator (“molecular relatedness”) method using accuracy of estimated breeding values. A commercial data set of common sole, Solea solea, with 51 parents and 1953 offspring (“full data set”) was used. Due to missing parents, for 1338 offspring, a pedigree could be reconstructed with 10 microsatellite markers (“reduced data set”). Cross-validation of both methods using the reduced data set showed an accuracy of estimated breeding values of 0.54 with pedigree reconstruction and 0.55 with molecular relatedness. Accuracy of estimated breeding values increased to 0.60 when applying molecular relatedness to the full data set. Our results indicate that pedigree reconstruction and molecular relatedness predict breeding values equally well in a population with skewed contributions to families. This is probably due to the presence of few large full-sib families. However, unlike methods with pedigree reconstruction, molecular relatedness methods ensure availability of all genotyped selection candidates, which results in higher accuracy of breeding value estimation.To estimate genetic parameters, additive genetic relationships between individuals are inferred from known pedigrees (Falconer and Mackay 1996; Lynch and Walsh 1997). However, in natural populations (Ritland 2000; Thomas et al. 2002) and in captive species where natural mating in groups is used to obtain offspring (Brown et al. 2005; Fessehaye et al. 2006; Blonk et al. 2009) pedigrees are reconstructed. In these populations there is no control on mating structure, and typically unbalanced population structures with highly skewed parental contributions are obtained (Bekkevold et al. 2002; Brown et al. 2005; Fessehaye et al. 2006; Blonk et al. 2009). To reconstruct pedigrees, parental allocation methods are often used (Marshall et al. 1998; Avise et al. 2002; Duchesne et al. 2002). These methods require that all parents be known. For situations where parental information is not available, numerous DNA-marker-based methods for estimating molecular relatedness have been developed (Lynch 1988; Queller and Goodnight 1989; Ritland 2000; Toro et al. 2002). These relatedness estimators determine relationship values between individuals on a continuous scale. Evaluation of relatedness estimators within real and simulated data in both plants and animals (e.g., see Van de Casteele et al. 2001 ; Milligan 2003; Oliehoek et al. 2006; Rodríguez-Ramilo et al. 2007; Bink et al. 2008) has generally focused on bias and sampling error of estimated genetic variances or relatedness values. Relatively little attention has been paid to their efficiency for estimation of breeding values.Two types of relatedness estimators are currently available: method-of-moments estimators and maximum-likelihood estimators. Method-of-moments estimators (e.g., Queller and Goodnight 1989; Li et al. 1993; Ritland 1996; Lynch and Ritland 1999; Toro et al. 2002) determine relationships while calculating sharing of alleles between pairs in different ways. A variant of method-of-moments estimators is the transformation of continuous relatedness values to categorical genealogical relationships using “explicit pedigree reconstruction” (Fernández and Toro 2006) or thresholds (Rodríguez-Ramilo et al. 2007). However, correlations of transformed coancestries with known genealogical coancestries are low (Rodríguez-Ramilo et al. 2007). Several studies have compared different method-of-moments estimators but none revealed one single best estimator (Van de Casteele et al. 2001; Oliehoek et al. 2006; Rodríguez-Ramilo et al. 2007; Bink et al. 2008).Maximum-likelihood (ML) approaches classify animals into a limited number of relationship classes (Mousseau et al. 1998; Thomas et al. 2002; Wang 2004; Herbinger et al. 2006; Anderson and Weir 2007). For each pair a likelihood to fall into a possible relatedness class (e.g., full sib vs. unrelated) is calculated given its genotype and phenotype. ML techniques combined with a Markov chain Monte Carlo approach reconstruct groups with specific relationships jointly and are therefore more efficient than other ML approaches. To minimize standard errors, all discussed ML methods require balanced population structures, large sibling groups, and a large variance of relatedness (Thomas et al. 2002; Wang 2004; Anderson and Weir 2007). Therefore, these methods may not be suitable for natural mating systems.Unlike parental allocation methods, a benefit from relatedness estimators is that essentially all selection candidates are maintained for breeding value estimation, even with missing parents. The question is, however, whether such relatedness estimators also give accurate breeding values to perform selection.In this study, we test suitability of a relatedness estimator to obtain breeding values in a population of common sole, Solea solea (n = 1953) obtained by natural mating. First, we estimate breeding values using pedigree relatedness of animals for which a pedigree could be reconstructed (using parental allocation). This data set (n = 1338) is further referred to as “reduced data set.” We compare results with estimated breeding values using a simple but robust method-of-moments relatedness estimator: “molecular relatedness” (Toro et al. 2002, 2003). Next, we estimate breeding values using molecular relatedness in the full data set (n = 1953). Results show that accuracies of estimated breeding values obtained with molecular relatedness and pedigree relatedness are comparable. Accuracy increases when breeding values are estimated with molecular relatedness in the full data set. This implies that a molecular relatedness estimator can be used to estimate breeding values in captive natural mating populations.