LEAF-E: a tool to analyze grass leaf growth using function fitting

Structural rearrangement of elastin under oxidative stress

Reactive oxygen species (ROS) are key elements in several physiological processes. A high level of ROS leads to oxidative stress that damages biomolecules and is linked to many diseases like type-2 diabetes, cancer, inflammation, and many more. Here, our in-vitro study aimed to gauge the effect of ROS on the structural rearrangement of elastin through metal-catalyzed oxidation (MCO) at physiological temperature through laser light scattering, UV-vis, FTIR, and FESEM imaging. Light scattering data show a decrease in the hydrodynamic radius of elastin upon oxidation for the first hour. The rate of size reduction of ROS-treated elastin and the rate for self-assembly of bare elastin in the first two hours is found to be almost the same. However, the rate of association of ROS-treated is one order slower than the bare elastin after one hour. UV-vis absorption shows a blue shift accompanied by increased absorption, followed by a redshift and broadening of peak. FTIR data reveal changes in the secondary structures for both bare and oxidized elastin with time. While bare elastin coacervation increases unordered structure, the corresponding case of oxidized elastin saw a rise in β-sheet. FESEM images show the morphological changes occurring with time. Thus, we conclude that oxidative stress leads to structural rearrangement of the protein through interaction with the polar and hydrophobic domains, followed by aggregation. This study might be helpful for therapeutics focusing on preventing elastin degradation against aging.

Field and saccharification performances of poplars severely downregulated in CAD1

Lignin is one of the main factors causing lignocellulosic biomass recalcitrance to enzymatic hydrolysis. Glasshouse-grown poplars severely downregulated for CINNAMYL ALCOHOL DEHYDROGENASE 1 (CAD1), the enzyme catalysing the last step in the monolignol-specific branch of lignin biosynthesis, have increased saccharification yields and normal growth. Here, we assess the performance of these hpCAD poplars in the field under short rotation coppice culture for two consecutive rotations of 1 yr and 3 yr. While 1-yr-old hpCAD wood had 10% less lignin, 3-yr-old hpCAD wood had wild-type lignin levels. Because of their altered cell wall composition, including elevated levels of cinnamaldehydes, both 1-yr-old and 3-yr-old hpCAD wood showed enhanced saccharification yields upon harsh alkaline pretreatments (up to +85% and +77%, respectively). In contrast with previous field trials with poplars less severely downregulated for CINNAMYL ALCOHOL DEHYDROGENASE (CAD), the hpCAD poplars displayed leaning phenotypes, early bud set, early flowering and yield penalties. Moreover, hpCAD wood had enlarged vessels, decreased wood density and reduced relative and free water contents. Our data show that the phenotypes of CAD-deficient poplars are strongly dependent on the environment and underpin the importance of field trials in translating basic research towards applications.

The Modified Brière Equation and Its Applications

The Brière equation (BE) is widely used to describe the effect of temperature on the development rate of insects, and it can produce both symmetrical and asymmetrical bell-shaped curves. Because of its elasticity in curve fitting, the integrated form of BE has been recommended for use as a sigmoid growth equation to describe the increase in plant biomass with time. However, the start time of growth predicted by the sigmoid growth equation based on the BE is not completely comparable to empirical crop growth data. In the present study, we modified the BE by adding an additional parameter to further increase its elasticity for data fitting. We termed this new equation the modified Brière equation (MBE). Data for the actual height and biomass of 15 species of plants (with two cultivars for one species) were fit with the sigmoid growth equations based on both the BE and MBE assuming that the growth start time was zero for both. The goodness of fit of the BE and MBE sigmoid growth equations were compared based on their root-mean-square errors and the corresponding absolute percentage error between them when fit to these data. For most species, we found that the MBE sigmoid growth equation achieved a better goodness of fit than the BE sigmoid growth equation. This work provides a useful tool for quantifying the ontogenetic or population growth of plants.

Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies

Genome-wide association studies (GWAS) are effectively applied to detect the marker trait associations (MTAs) using whole genome-wide variants for complex quantitative traits in different crop species. GWAS has been applied in wheat for different quality, biotic and abiotic stresses, and agronomic and yield-related traits. Predictions for marker-trait associations are controlled with the development of better statistical models taking population structure and familial relatedness into account. In this review, we have provided a detailed overview of the importance of association mapping, population design, high-throughput genotyping and phenotyping platforms, advancements in statistical models and multiple threshold comparisons, and recent GWA studies conducted in wheat. The information about MTAs utilized for gene characterization and adopted in breeding programs is also provided. In the literature that we surveyed, as many as 86,122 wheat lines have been studied under various GWA studies reporting 46,940 loci. However, further utilization of these is largely limited. The future breakthroughs in area of genomic selection, multi-omics-based approaches, machine, and deep learning models in wheat breeding after exploring the complex genetic structure with the GWAS are also discussed. This is a most comprehensive study of a large number of reports on wheat GWAS and gives a comparison and timeline of technological developments in this area. This will be useful to new researchers or groups who wish to invest in GWAS.

Omics for the Improvement of Abiotic, Biotic, and Agronomic Traits in Major Cereal Crops: Applications, Challenges, and Prospects

Omics technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal crop breeding program, as they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in omics assure time efficiency and cost benefits to improve cereal crops. This review provides a comprehensive overview of the established omics methods in five major cereals, namely rice, sorghum, maize, barley, and bread wheat. We cover the evolution of technologies in each omics section independently and concentrate on their use to improve economically important agronomic as well as biotic and abiotic stress-related traits. Advancements in the (1) identification, mapping, and sequencing of molecular/structural variants; (2) high-density transcriptomics data to study gene expression patterns; (3) global and targeted proteome profiling to study protein structure and interaction; (4) metabolomic profiling to quantify organ-level, small-density metabolites, and their composition; and (5) high-resolution, high-throughput, image-based phenomics approaches are surveyed in this review.

A General Model for Describing the Ovate Leaf Shape

Many plant species produce ovate leaves, but there is no general parametric model for describing this shape. Here, we used two empirical nonlinear equations, the beta and Lobry–Rosso–Flandrois (LRF) equations, and their modified forms (referred to as the Mbeta and MLRF equations for convenience), to generate bilaterally symmetrical curves along the x-axis to form ovate leaf shapes. In order to evaluate which of these four equations best describes the ovate leaf shape, we used 14 leaves from 7 Neocinnamomum species (Lauraceae) and 72 leaves from Chimonanthus praecox (Calycanthaceae). Using the AIC and adjusted root mean square error to compare the fitted results, the modified equations fitted the leaf shapes better than the unmodified equations. However, the MLRF equation provided the best overall fit. As the parameters of the MLRF equation represent leaf length, maximum leaf width, and the distance from leaf apex to the point associated with the maximum leaf width along the leaf length axis, these findings are potentially valuable for studying the influence of environmental factors on leaf shape, differences in leaf shape among closely related plant species with ovate leaf shapes, and the extent to which leaves are bilaterally symmetrical. This is the first work in which temperature-dependent developmental equations to describe the ovate leaf shape have been employed, as previous studies lacked similar leaf shape models. In addition, prior work seldom attempted to describe real ovate leaf shapes. Our work bridges the gap between theoretical leaf shape models and empirical leaf shape indices that cannot predict leaf shape profiles.

High-throughput phenotyping for crop improvement in the genomics era

Tremendous progress has been made with continually expanding genomics technologies to unravel and understand crop genomes. However, the impact of genomics data on crop improvement is still far from satisfactory, in large part due to a lack of effective phenotypic data; our capacity to collect useful high quality phenotypic data lags behind the current capacity to generate high-throughput genomics data. Thus, the research bottleneck in plant sciences is shifting from genotyping to phenotyping. This article review the current status of efforts made in the last decade to systematically collect phenotypic data to alleviate this 'phenomics bottlenecks' by recording trait data through sophisticated non-invasive imaging, spectroscopy, image analysis, robotics, high-performance computing facilities and phenomics databases. These modern phenomics platforms and tools aim to record data on traits like plant development, architecture, plant photosynthesis, growth or biomass productivity, on hundreds to thousands of plants in a single day, as a phenomics revolution. It is believed that this revolution will provide plant scientists with the knowledge and tools necessary for unlocking information coded in plant genomes. Efforts have been also made to present the advances made in the last 10 years in phenomics platforms and their use in generating phenotypic data on different traits in several major crops including rice, wheat, barley, and maize. The article also highlights the need for phenomics databases and phenotypic data sharing for crop improvement. The phenomics data generated has been used to identify genes/QTL through QTL mapping, association mapping and genome-wide association studies (GWAS) for genomics-assisted breeding (GAB) for crop improvement.

Phenotyping a Dynamic Trait: Leaf Growth of Perennial Ryegrass Under Water Limiting Conditions

Water limitation is one of the major factors reducing crop productivity worldwide. In order to develop efficient breeding strategies to improve drought tolerance, accurate methods to identify when a plant reduces growth as a consequence of water deficit have yet to be established. In perennial ryegrass (Lolium perenne L.), an important forage grass of the Poaceae family, leaf elongation is a key factor determining plant growth and hence forage yield. Although leaf elongation has been shown to be temperature-dependent under non-stress conditions, the impact of water limitation on leaf elongation in perennial ryegrass is poorly understood. We describe a method for quantifying tolerance to water deficit based on leaf elongation in relation to temperature and soil moisture in perennial ryegrass. With decreasing soil moisture, three growth response phases were identified: first, a "normal" phase where growth is mainly determined by temperature, second a "slow" phase where leaf elongation decreases proportionally to soil water potential and third an "arrest" phase where leaf growth terminates. A custom R function was able to quantify the points which demarcate these phases and can be used to describe the response of plants to water deficit. Applied to different perennial ryegrass genotypes, this function revealed significant genotypic variation in the response of leaf growth to temperature and soil moisture. Dynamic phenotyping of leaf elongation can be used as a tool to accurately quantify tolerance to water deficit in perennial ryegrass and to improve this trait by breeding. Moreover, the tools presented here are applicable to study the plant response to other stresses in species with linear, graminoid leaf morphology.

Polyploidy Affects Plant Growth and Alters Cell Wall Composition

Polyploidization has played a key role in plant breeding and crop improvement. Although its potential to increase biomass yield is well described, the effect of polyploidization on biomass composition has largely remained unexplored. Here, we generated a series of Arabidopsis (Arabidopsis thaliana) plants with different somatic ploidy levels (2n, 4n, 6n, and 8n) and performed rigorous phenotypic characterization. Kinematic analysis showed that polyploids developed slower compared to diploids; however, tetra- and hexaploids, but not octaploids, generated larger rosettes due to delayed flowering. In addition, morphometric analysis of leaves showed that polyploidy affected epidermal pavement cells, with increased cell size and reduced cell number per leaf blade with incrementing ploidy. However, the inflorescence stem dry weight was highest in tetraploids. Cell wall characterization revealed that the basic somatic ploidy level negatively correlated with lignin and cellulose content, and positively correlated with matrix polysaccharide content (i.e. hemicellulose and pectin) in the stem tissue. In addition, higher ploidy plants displayed altered sugar composition. Such effects were linked to the delayed development of polyploids. Moreover, the changes in polyploid cell wall composition promoted saccharification yield. The results of this study indicate that induction of polyploidy is a promising breeding strategy to further tailor crops for biomass production.

Methodological approach for predicting and mapping the phenological adaptation of tropical maize (Zea mays L.) using multi-environment trials

BACKGROUND

The phenological development of the maize crop from emergence through flowering to maturity, usually expressed as a rate (i.e. 1/duration), is largely controlled by temperature in the tropics. Maize plant phenological responses vary between varieties and quantifying these responses can help in predicting the timing and duration of critical periods for crop growth that affect the quality and quantity of seed. We used routine multi-environment trials data of diverse tropical maize varieties to: (1) fit 82 temperature dependent phenology models and select the best model for an individual variety, (2) develop a spatial framework that uses the phenology model to predict at landscape level the length of the vegetative and reproductive phases of diverse varieties of maize in different agro-ecologies. Multi-environment trial data of 22 maize varieties from 16 trials in Kenya, Ethiopia, and Sudan was analyzed and the Levenberg-Marquardt algorithm combined with statistical criteria was applied to determine the best temperature-dependent model.

RESULTS

The Briere model, which is not often used in plant phenology, provided the best fit, with observed and predicted days to flowering showing good agreement. Linking the model with temperature and scaling out through mapping gave the duration from emergence to maturity of different maize varieties in areas where maize could potentially be grown.

CONCLUSION

The methodology and framework used in the study provides an opportunity to develop tools that enhance farmers' ability to predict stages of maize development for efficient crop management decisions and assessment of climate change impacts. This methodology could contribute to increase maize production if used to identify varieties with desired maturity for a specific agro-ecology in in the targeted regions.

Simulation of crop growth, time to maturity and yield by an improved sigmoidal model

Models that accurately estimate maximum crop biomass to obtain a reliable forecast of yield are useful in crop improvement programs and aiding establishment of government policies, including those addressing issues of food security. Here, we present a new sigmoidal growth model (NSG) and compare its performance with the beta sigmoidal growth model (BSG) for capturing the growth trajectories of eight crop species. Results indicated that both the NSG and the BSG fitted all the growth datasets well (R² > 0.98). However, the NSG performed better than the BSG based on the calculated value of Akaike’s information criterion (AIC). The NSG provided a consistent estimate for when maximum biomass occurred; this suggests that the parameters of the BSG may have less biological importance as compared to those in the NSG. In summary, the new sigmoidal growth model is superior to the beta sigmoidal growth model, which can be applied to capture the growth trajectory of various plant species regardless of the initial biomass values at the beginning of a growth period. Findings of this study will be helpful to understand the growth trajectory of different plant species regardless of their initial biomass values at the beginning of a growth period.

Natural variation and genetic make-up of leaf blade area in spring barley

KEY MESSAGE

GWAS analysis for leaf blade area (LA) revealed intriguing genomic regions associated with putatively novel QTL and known plant stature-related phytohormone and sugar-related genes. Despite long-standing studies in the morpho-physiological characters of leaf blade area (LA) in cereal crops, advanced genetic studies to explore its natural variation are lacking. The importance of modifying LA in improving cereal grain yield and the genes controlling leaf traits have been well studied in rice but not in temperate cereals. To better understand the natural genetic variation of LA at four developmental stages, main culm LA was measured from 215 worldwide spring barleys including 92 photoperiod-sensitive accessions [PHOTOPERIOD RESPONSE LOCUS 1 (Ppd-H1)] and 123 accessions with reduced photoperiod sensitivity (ppd-H1) locus under controlled greenhouse conditions (long-day; 16/8 h; ~ 20/~ 16 °C day/night). The LA of Ppd-H1-carrying accessions was always smaller than in ppd-H1-carrying accessions. We found that nine SNPs from the Ppd-H1 gene were present in the collection of which marker 9 (M9; G/T in the CCT-domain) showed the most significant and consistent effect on LA at all studied developmental stages. Genome-wide association scans (GWAS) showed that the accessions carrying the ppd-H1 allele T/M9 (late heading) possessed more genetic variation in LA than the Ppd-H1 group carrying G/M9 (early heading). Several QTL with major effects on LA variation were found close to plant stature-related heading time, phytohormone- and sugar-related genes. The results provide evidence that natural variation of LA is an important source for improving grain yield, adaptation and canopy architecture of temperate cereals.

Growth rate rather than growth duration drives growth heterosis in maize B104 hybrids

Research in maize is often performed using inbred lines that can be readily transformed, such as B104. However, because the B104 line flowers late, the kernels do not always mature before the end of the growing season, hampering routine seed yield evaluations of biotech traits introduced in B104 at many geographical locations. Therefore, we generated five hybrids by crossing B104 with the early-flowering inbred lines CML91, F7, H99, Mo17, and W153R and showed in three consecutive years that the hybrid lines proved to be suitable to evaluate seed yield under field conditions in a temperate climate. By assessing the two main processes driving maize leaf growth, being rate of growth (leaf elongation rate or LER) and the duration of growth (leaf elongation duration or LED) in this panel of hybrids, we showed that leaf growth heterosis was mainly the result of increased LER and not or to a lesser extent of LED. Ectopic expression of the transgenes GA20-oxidase (GA20-OX) and PLASTOCHRON1 (PLA1), known to stimulate the LER and LED, respectively, in the hybrids showed that leaf length heterosis can be stimulated by increased LER, but not by LED, indicating that LER rather than LED is the target for enhancing leaf growth heterosis.

What determines organ size differences between species? A meta-analysis of the cellular basis

Little is known about how the characteristic differences in organ size between species are regulated. At the cellular level, the size of an organ is strictly regulated by cell division and expansion during its development. We performed a meta-analysis of the growth parameters of roots, and Graminae and eudicotyledonous leaves, to address the question of how quantitative variation in these two processes contributes to size differences across a range of species. We extracted or derived cellular parameters from published kinematic growth analyses. These data were subjected to linear regression analyses to identify the parameters that determine differences in organ growth. Our results demonstrate that, across all species and organs, similar conclusions can be made: cell number rather than cell size determines the final size of plant organs; cell number is determined by meristem size rather than the rate at which cells divide; cells that are small when leaving the meristem compensate by expanding for longer; mature cell size is primarily determined by the duration of cell expansion. These results identify the regulation of the transition from cell division to expansion as the key cellular mechanism targeted by the evolution of organ size.

F-Box Protein FBX92 Affects Leaf Size in Arabidopsis thaliana

F-box proteins are part of one of the largest families of regulatory proteins that play important roles in protein degradation. In plants, F-box proteins are functionally very diverse, and only a small subset has been characterized in detail. Here, we identified a novel F-box protein FBX92 as a repressor of leaf growth in Arabidopsis. Overexpression of AtFBX92 resulted in plants with smaller leaves than the wild type, whereas plants with reduced levels of AtFBX92 showed, in contrast, increased leaf growth by stimulating cell proliferation. Detailed cellular analysis suggested that AtFBX92 specifically affects the rate of cell division during early leaf development. This is supported by the increased expression levels of several cell cycle genes in plants with reduced AtFBX92 levels. Surprisingly, overexpression of the maize homologous gene ZmFBX92 in maize had no effect on plant growth, whereas ectopic expression in Arabidopsis increased leaf growth. Expression of a truncated form of AtFBX92 showed that the contrasting effects of ZmFBX92 and AtFBX92 gain of function in Arabidopsis are due to the absence of the F-box-associated domain in the ZmFBX92 gene. Our work reveals an additional player in the complex network that determines leaf size and lays the foundation for identifying putative substrates.

Altered expression of maize PLASTOCHRON1 enhances biomass and seed yield by extending cell division duration

Maize is the highest yielding cereal crop grown worldwide for grain or silage. Here, we show that modulating the expression of the maize PLASTOCHRON1 (ZmPLA1) gene, encoding a cytochrome P450 (CYP78A1), results in increased organ growth, seedling vigour, stover biomass and seed yield. The engineered trait is robust as it improves yield in an inbred as well as in a panel of hybrids, at several locations and over multiple seasons in the field. Transcriptome studies, hormone measurements and the expression of the auxin responsive DR5rev:mRFPer marker suggest that PLA1 may function through an increase in auxin. Detailed analysis of growth over time demonstrates that PLA1 stimulates the duration of leaf elongation by maintaining dividing cells in a proliferative, undifferentiated state for a longer period of time. The prolonged duration of growth also compensates for growth rate reduction caused by abiotic stresses.

A geometrical model for testing bilateral symmetry of bamboo leaf with a simplified Gielis equation

The size and shape of plant leaves change with growth, and an accurate description of leaf shape is crucial for describing plant morphogenesis and development. Bilateral symmetry, which has been widely observed but poorly examined, occurs in both dicot and monocot leaves, including all nominated bamboo species (approximately 1,300 species), of which at least 500 are found in China. Although there are apparent differences in leaf size among bamboo species due to genetic and environmental profiles, bamboo leaves have bilateral symmetry with parallel venation and appear similar across species. Here, we investigate whether the shape of bamboo leaves can be accurately described by a simplified Gielis equation, which consists of only two parameters (leaf length and shape) and produces a perfect bilateral shape. To test the applicability of this equation and the occurrence of bilateral symmetry, we first measured the leaf length of 42 bamboo species, examining >500 leaves per species. We then scanned 30 leaves per species that had approximately the same length as the median leaf length for that species. The leaf‐shape data from scanned profiles were fitted to the simplified Gielis equation. Results confirmed that the equation fits the leaf‐shape data extremely well, with the coefficients of determination being 0.995 on average. We further demonstrated the bilateral symmetry of bamboo leaves, with a clearly defined leaf‐shape parameter of all 42 bamboo species investigated ranging from 0.02 to 0.1. This results in a simple and reliable tool for precise determination of bamboo species, with applications in forestry, ecology, and taxonomy.

Leaf Length Tracker: a novel approach to analyse leaf elongation close to the thermal limit of growth in the field

Leaf growth in monocot crops such as wheat and barley largely follows the daily temperature course, particularly under cold but humid springtime field conditions. Knowledge of the temperature response of leaf extension, particularly variations close to the thermal limit of growth, helps define physiological growth constraints and breeding-related genotypic differences among cultivars. Here, we present a novel method, called 'Leaf Length Tracker' (LLT), suitable for measuring leaf elongation rates (LERs) of cereals and other grasses with high precision and high temporal resolution under field conditions. The method is based on image sequence analysis, using a marker tracking approach to calculate LERs. We applied the LLT to several varieties of winter wheat (Triticum aestivum), summer barley (Hordeum vulgare), and ryegrass (Lolium perenne), grown in the field and in growth cabinets under controlled conditions. LLT is easy to use and we demonstrate its reliability and precision under changing weather conditions that include temperature, wind, and rain. We found that leaf growth stopped at a base temperature of 0°C for all studied species and we detected significant genotype-specific differences in LER with rising temperature. The data obtained were statistically robust and were reproducible in the tested environments. Using LLT, we were able to detect subtle differences (sub-millimeter) in leaf growth patterns. This method will allow the collection of leaf growth data in a wide range of future field experiments on different graminoid species or varieties under varying environmental or treatment conditions.

Overexpression of GA20-OXIDASE1 impacts plant height, biomass allocation and saccharification efficiency in maize

Increased biomass yield and quality are of great importance for the improvement of feedstock for the biorefinery. For the production of bioethanol, both stem biomass yield and the conversion efficiency of the polysaccharides in the cell wall to fermentable sugars are of relevance. Increasing the endogenous levels of gibberellic acid (GA) by ectopic expression of GA20-OXIDASE1 (GA20-OX1), the rate-limiting step in GA biosynthesis, is known to affect cell division and cell expansion, resulting in larger plants and organs in several plant species. In this study, we examined biomass yield and quality traits of maize plants overexpressing GA20-OX1 (GA20-OX1). GA20-OX1 plants accumulated more vegetative biomass than control plants in greenhouse experiments, but not consistently over two years of field trials. The stems of these plants were longer but also more slender. Investigation of GA20-OX1 biomass quality using biochemical analyses showed the presence of more cellulose, lignin and cell wall residue. Cell wall analysis as well as expression analysis of lignin biosynthetic genes in developing stems revealed that cellulose and lignin were deposited earlier in development. Pretreatment of GA20-OX1 biomass with NaOH resulted in a higher saccharification efficiency per unit of dry weight, in agreement with the higher cellulose content. On the other hand, the cellulose-to-glucose conversion was slower upon HCl or hot-water pretreatment, presumably due to the higher lignin content. This study showed that biomass yield and quality traits can be interconnected, which is important for the development of future breeding strategies to improve lignocellulosic feedstock for bioethanol production.

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement.

The seesaw effect of winter temperature change on the recruitment of cotton bollworms Helicoverpa armigera through mismatched phenology

Knowing how climate change affects the population dynamics of insect pests is critical for the future of integrated pest management. Rising winter temperatures from global warming can drive increases in outbreaks of some agricultural pests. In contrast, here we propose an alternative hypothesis that both extremely cold and warm winters can mismatch the timing between the eclosion of overwintering pests and the flowering of key host plants. As host plants normally need higher effective cumulative temperatures for flowering than insects need for eclosion, changes in flowering time will be less dramatic than changes in eclosion time, leading to a mismatch of phenology on either side of the optimal winter temperature. We term this the "seesaw effect." Using a long-term dataset of the Old World cotton bollworm Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) in northern China, we tested this seesaw hypothesis by running a generalized additive model for the effects of the third generation moth in the preceding year, the winter air temperature, the number of winter days below a critical temperature and cumulative precipitation during winter on the demography of the overwintering moth. Results confirmed the existence of the seesaw effect of winter temperature change on overwintering populations. Pest management should therefore consider the indirect effect of changing crop phenology (whether due to greenhouse cultivation or to climate change) on pest outbreaks. As arthropods from mid- and high latitudes are actually living in a cooler thermal environment than their physiological optimum in contrast to species from lower latitudes, the effects of rising winter temperatures on the population dynamics of arthropods in the different latitudinal zones should be considered separately. The seesaw effect makes it more difficult to predict the average long-term population dynamics of insect pests at high latitudes due to the potential sharp changes in annual growth rates from fluctuating minimum winter temperatures.

Comparison of dwarf bamboos (Indocalamus sp.) leaf parameters to determine relationship between spatial density of plants and total leaf area per plant

The relationship between spatial density and size of plants is an important topic in plant ecology. The self-thinning rule suggests a -3/2 power between average biomass and density or a -1/2 power between stand yield and density. However, the self-thinning rule based on total leaf area per plant and density of plants has been neglected presumably because of the lack of a method that can accurately estimate the total leaf area per plant. We aimed to find the relationship between spatial density of plants and total leaf area per plant. We also attempted to provide a novel model for accurately describing the leaf shape of bamboos. We proposed a simplified Gielis equation with only two parameters to describe the leaf shape of bamboos one model parameter represented the overall ratio of leaf width to leaf length. Using this method, we compared some leaf parameters (leaf shape, number of leaves per plant, ratio of total leaf weight to aboveground weight per plant, and total leaf area per plant) of four bamboo species of genus Indocalamus Nakai (I. pedalis (Keng) P.C. Keng, I. pumilus Q.H. Dai and C.F. Keng, I. barbatus McClure, and I. victorialis P.C. Keng). We also explored the possible correlation between spatial density and total leaf area per plant using log-linear regression. We found that the simplified Gielis equation fit the leaf shape of four bamboo species very well. Although all these four species belonged to the same genus, there were still significant differences in leaf shape. Significant differences also existed in leaf area per plant, ratio of leaf weight to aboveground weight per plant, and leaf length. In addition, we found that the total leaf area per plant decreased with increased spatial density. Therefore, we directly demonstrated the self-thinning rule to improve light interception.

Correlation analysis of the transcriptome of growing leaves with mature leaf parameters in a maize RIL population

BACKGROUND

To sustain the global requirements for food and renewable resources, unraveling the molecular networks underlying plant growth is becoming pivotal. Although several approaches to identify genes and networks involved in final organ size have been proven successful, our understanding remains fragmentary.

RESULTS

Here, we assessed variation in 103 lines of the Zea mays B73xH99 RIL population for a set of final leaf size and whole shoot traits at the seedling stage, complemented with measurements capturing growth dynamics, and cellular measurements. Most traits correlated well with the size of the division zone, implying that the molecular basis of final leaf size is already defined in dividing cells of growing leaves. Therefore, we searched for association between the transcriptional variation in dividing cells of the growing leaf and final leaf size and seedling biomass, allowing us to identify genes and processes correlated with the specific traits. A number of these genes have a known function in leaf development. Additionally, we illustrated that two independent mechanisms contribute to final leaf size, maximal growth rate and the duration of growth.

CONCLUSIONS

Untangling complex traits such as leaf size by applying in-depth phenotyping allows us to define the relative contributions of the components and their mutual associations, facilitating dissection of the biological processes and regulatory networks underneath.