Dissecting the phenotypic components and genetic architecture of maize stem vascular bundles using high-throughput phenotypic analysis

Genome-wide association study of stem structural characteristics that extracted by a high-throughput phenotypic analysis "LabelmeP rice" in rice

Stem is important for assimilating transport and plant strength; however, less is known about the genetic basis of its structural characteristics. In this study, a high-throughput method, "LabelmeP rice" was developed to generate 14 traits related to stem regions and vascular bundles, which allows the establishment of a stem cross-section phenotype dataset containing anatomical information of 1738 images from hand-cut transections of stems collected from 387 rice germplasm accessions grown over two successive seasons. Then, the phenotypic diversity of the rice accessions was evaluated. Genome-wide association studies identified 94, 83, and 66 significant single nucleotide polymorphisms (SNPs) for the assayed traits in 2 years and their best linear unbiased estimates, respectively. These SNPs can be integrated into 29 quantitative trait loci (QTL), and 11 of them were common in 2 years, while correlated traits shared 19. In addition, 173 candidate genes were identified, and six located at significant SNPs were repeatedly detected and annotated with a potential function in stem development. By using three introgression lines (chromosome segment substitution lines), four of the 29 QTLs were validated. LOC_Os01g70200, located on the QTL uq1.4, is detected for the area of small vascular bundles (SVB) and the rate of large vascular bundles number to SVB number. Besides, the CRISPR/Cas9 editing approach has elucidated the function of the candidate gene LOC_Os06g46340 in stem development. In conclusion, the results present a time- and cost-effective method that provides convenience for extracting rice stem anatomical traits and the candidate genes/QTL, which would help improve rice.

Plant microphenotype: from innovative imaging to computational analysis

The microphenotype plays a key role in bridging the gap between the genotype and the complex macro phenotype. In this article, we review the advances in data acquisition and the intelligent analysis of plant microphenotyping and present applications of microphenotyping in plant science over the past two decades. We then point out several challenges in this field and suggest that cross-scale image acquisition strategies, powerful artificial intelligence algorithms, advanced genetic analysis, and computational phenotyping need to be established and performed to better understand interactions among genotype, environment, and management. Microphenotyping has entered the era of Microphenotyping 3.0 and will largely advance functional genomics and plant science.

Investigating the genetic basis of maize ear characteristics: a comprehensive genome-wide study utilizing high-throughput phenotypic measurement method and system

The morphology of maize ears plays a critical role in the breeding of new varieties and increasing yield. However, the study of traditional ear-related traits alone can no longer meet the requirements of breeding. In this study, 20 ear-related traits, including size, shape, number, and color, were obtained in 407 maize inbred lines at two sites using a high-throughput phenotypic measurement method and system. Significant correlations were found among these traits, particularly the novel trait ear shape (ES), which was correlated with traditional traits: kernel number per row and kernel number per ear. Pairwise comparison tests revealed that the inbred lines of tropical-subtropical were significantly different from other subpopulations in row numbers per ear, kernel numbers per ear, and ear color. A genome-wide association study identified 275, 434, and 362 Single nucleotide polymorphisms (SNPs) for Beijing, Sanya, and best linear unbiased prediction scenarios, respectively, explaining 3.78% to 24.17% of the phenotypic variance. Furthermore, 58 candidate genes with detailed functional descriptions common to more than two scenarios were discovered, with 40 genes being associated with color traits on chromosome 1. After analysis of haplotypes, gene expression, and annotated information, several candidate genes with high reliability were identified, including Zm00001d051328 for ear perimeter and width, zma-MIR159f for ear shape, Zm00001d053080 for kernel width and row number per ear, and Zm00001d048373 for the blue color channel of maize kernels in the red-green-blue color model. This study emphasizes the importance of researching novel phenotypic traits in maize by utilizing high-throughput phenotypic measurements. The identified genetic loci enrich the existing genetic studies related to maize ears.

Maize Internode Autofluorescence at the Macroscopic Scale: Image Representation and Principal Component Analysis of a Series of Large Multispectral Images

A quantitative histology of maize stems is needed to study the role of tissue and of their chemical composition in plant development and in their end-use quality. In the present work, a new methodology is proposed to show and quantify the spatial variability of tissue composition in plant organs and to statistically compare different samples accounting for biological variability. Multispectral UV/visible autofluorescence imaging was used to acquire a macroscale image series based on the fluorescence of phenolic compounds in the cell wall. A series of 40 multispectral large images of a whole internode section taken from four maize inbred lines were compared. The series consisted of more than 1 billion pixels and 11 autofluorescence channels. Principal Component Analysis was adapted and named large PCA and score image montages at different scales were built. Large PCA score distributions were proposed as quantitative features to compare the inbred lines. Variations in the tissue fluorescence were clearly displayed in the score images. General intensity variations were identified. Rind vascular bundles were differentiated from other tissues due to their lignin fluorescence after visible excitation, while variations within the pith parenchyma were shown via UV fluorescence. They depended on the inbred line, as revealed by the first four large PCA score distributions. Autofluorescence macroscopy combined with an adapted analysis of a series of large images is promising for the investigation of the spatial heterogeneity of tissue composition between and within organ sections. The method is easy to implement and can be easily extended to other multi-hyperspectral imaging techniques. The score distributions enable a global comparison of the images and an analysis of the inbred lines' effect. The interpretation of the tissue autofluorescence needs to be further investigated by using complementary spatially resolved techniques.

Co-exposure of maize to polyethylene microplastics and ZnO nanoparticles: Impact on growth, fate, and interaction

Microplastics (MPs), especially polyethylene MPs (PE MPs), which are the primary component of mulch, have attracted increasing attention in recent years. ZnO nanoparticles (NPs), which constitute a metal-based nanomaterial commonly used in agricultural production, co-converge with PE MPs in the soil. However, studies revealing the behavior and fate of ZnO NPs in soil-plant systems in the presence of MPs are limited. In this study, a pot experiment was used to evaluate the effects of maize co-exposure to PE MPs (0.5 % and 5 % w/w) and ZnO NPs (500 mg/kg) on growth, element distribution, speciation, and adsorption mechanism. The results demonstrate that individual exposure to PE MPs posed no significant toxicity; however, it significantly decreased maize grain yield (essentially 0). ZnO NP-exposure treatments significantly increased the Zn concentration and distribution intensity in maize tissues. Among them, the Zn concentration in the maize root exceeded 200 mg/kg, compared with 40 mg/kg in the grain. Moreover, the Zn concentrations in various tissues decreased in the following order: stem, leaf, cob, bract, and grain. Reassuringly, ZnO NPs still could not be transported to the maize stem under co-exposure to PE MPs. ZnO NPs had been biotransformed (64 % of the Zn was associated with histidine, with the remainder being associated with P [phytate] and cysteine) in maize stem. This study provides new insights into the plant physiological risks of PE MP and ZnO NP co-exposure in the soil-plant system and assesses the fate of ZnO NPs.

Effects of drought stress on water content and biomass distribution in summer maize(Zea mays L.)

The resource allocation of different component organs of crops under drought stress is a strategy for the coordinated growth of crops, which also reflects the adaptability of crops to drought condition. In this study, maize variety namely 'Denghai 618', under the ventilation shed, two treatment groups of light drought (LD) and moderate drought (MD), and the same rehydration after drought are set, as well as the normal water supply for control in shed (CS). The drought experiment was conducted in the jointing-tasseling stage in 2021. The effects of different drought stress on the water content and biomass allocation of each component organ were analyzed. The results showed that (1) during the drought period, the water content of each component organ of summer maize decreased in general, but the Water content distribution ratio (WCDR) of the root increased by 1.83%- 2.35%. The WCDR of stem increased by 0.52%- 1.40%. (2) Under different drought treatments, the root biomass (RB) increased 33.94% ~ 46.09%, and fruit biomass (FB) increased 1.46% ~ 2.49%, the leaf biomass (LB) decreased by 8.2% and 1.46% respectively under LD and MD. (3) The allometric growth model constructed under sufficient water is not suitable for drought stress; the allometric exponent α under drought stress is lower than that of the CS: CS (α=1.175) > MD (α = 1.136) > LD (α = 1.048), which also indicates that the impact of existing climate change on grain yield may be underestimated. This study is helpful to understand the adaptive strategies of the coordinated growth of maize component organs under drought stress and provide a reference for the prediction of grain yield under climate change.

Characterization and genetic dissection of maize ear leaf midrib acquired by 3D digital technology

The spatial morphological structure of plant leaves is an important index to evaluate crop ideotype. In this study, we characterized the three-dimensional (3D) data of the ear leaf midrib of maize at the grain-filling stage using the 3D digitization technology and obtained the phenotypic values of 15 traits covering four different dimensions of the ear leaf midrib, of which 13 phenotypic traits were firstly proposed for featuring plant leaf spatial structure. Cluster analysis results showed that the 13 traits could be divided into four groups, Group I, -II, -III and -IV. Group I contains HorizontalLength, OutwardGrowthMeasure, LeafAngle and DeviationTip; Group II contains DeviationAngle, MaxCurvature and CurvaturePos; Group III contains LeafLength and ProjectionArea; Group IV contains TipTop, VerticalHeight, UpwardGrowthMeasure, and CurvatureRatio. To investigate the genetic basis of the ear leaf midrib curve, 13 traits with high repeatability were subjected to genome-wide association study (GWAS) analysis. A total of 828 significantly related SNPs were identified and 1365 candidate genes were annotated. Among these, 29 candidate genes with the highest significant and multi-method validation were regarded as the key findings. In addition, pathway enrichment analysis was performed on the candidate genes of traits to explore the potential genetic mechanism of leaf midrib curve phenotype formation. These results not only contribute to further understanding of maize leaf spatial structure traits but also provide new genetic loci for maize leaf spatial structure to improve the plant type of maize varieties.

Biomolecular Strategies for Vascular Bundle Development to Improve Crop Yield

The need to produce crops with higher yields is critical due to a growing global population, depletion of agricultural land, and severe climate change. Compared with the "source" and "sink" transport systems that have been studied a lot, the development and utilization of vascular bundles (conducting vessels in plants) are increasingly important. Due to the complexity of the vascular system, its structure, and its delicate and deep position in the plant body, the current research on model plants remains basic knowledge and has not been repeated for crops and applied to field production. In this review, we aim to summarize the current knowledge regarding biomolecular strategies of vascular bundles in transport systems (source-flow-sink), allocation, helping crop architecture establishment, and influence of the external environment. It is expected to help understand how to use sophisticated and advancing genetic engineering technology to improve the vascular system of crops to increase yield.

Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives

Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of genomics and environment on plants, limiting the progress of smart breeding and precise cultivation. High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits. Proximal and remote sensing (PRS) techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis. Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications. This progress covers most aspects of PRS application in PP, including patterns of global spatial distribution and temporal dynamics, specific PRS technologies, phenotypic research fields, working environments, species, and traits. Subsequently, we demonstrate how to link PRS to multi-omics studies, including how to achieve multi-dimensional PRS data acquisition and processing, how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance, and how to link PP to multi-omics association analysis. Finally, we identify three future perspectives for PRS-based PP: (1) strengthening the spatial and temporal consistency of PRS data, (2) exploring novel phenotypic traits, and (3) facilitating multi-omics communication.

End-to-End Fusion of Hyperspectral and Chlorophyll Fluorescence Imaging to Identify Rice Stresses

Herbicides and heavy metals are hazardous substances of environmental pollution, resulting in plant stress and harming humans and animals. Identification of stress types can help trace stress sources, manage plant growth, and improve stress-resistant breeding. In this research, hyperspectral imaging (HSI) and chlorophyll fluorescence imaging (Chl-FI) were adopted to identify the rice plants under two types of herbicide stresses (butachlor (DCA) and quinclorac (ELK)) and two types of heavy metal stresses (cadmium (Cd) and copper (Cu)). Visible/near-infrared spectra of leaves (L-VIS/NIR) and stems (S-VIS/NIR) extracted from HSI and chlorophyll fluorescence kinetic curves of leaves (L-Chl-FKC) and stems (S-Chl-FKC) extracted from Chl-FI were fused to establish the models to detect the stress of the hazardous substances. Novel end-to-end deep fusion models were proposed for low-level, middle-level, and high-level information fusion to improve identification accuracy. Results showed that the high-level fusion-based convolutional neural network (CNN) models reached the highest detection accuracy (97.7%), outperforming the models using a single data source (<94.7%). Furthermore, the proposed end-to-end deep fusion models required a much simpler training procedure than the conventional two-stage deep learning fusion. This research provided an efficient alternative for plant stress phenotyping, including identifying plant stresses caused by hazardous substances of environmental pollution.

Genome- and transcriptome-wide association studies show that pulmonary embolism is associated with bone-forming proteins

BACKGROUND

Pulmonary embolism (PE) is a leading cause of death in stroke patients and a severe health burden worldwide. There is a pressing need to understand the mechanisms by which it occurs and to identify at-risk patients efficiently and accurately.

OBJECTIVES

The aim of this paper was to analyze the genetic correlation between PE and human plasma proteins through genome-wide association study (GWAS) with transcriptome-wide association study (TWAS), in combination with mRNA expression profiling at three levels: DNA, RNA, and protein.

METHODS

First, based on data from GWAS in European populations, we performed a linkage disequilibrium score regression (LDSC) analysis of plasma proteins and PE in 3,283 individuals and additionally analyzed the genetic association between PE and fracture. Then, we performed a TWAS on PE GWAS data using skeletal muscle and blood for gene expression references. Finally, we validated the genetic correlation between PE and human plasma proteins by co-matching the genes encoding the identified proteins and those identified using TWAS with the differentially expressed genes obtained from mRNA expression profiling of PE (Figure1).

RESULTS

We identified five plasma proteins associated with PE, including hydroxycarboxylic acid receptor 2, defensin 118, and bone morphogenetic protein (BMP) 7, as well as a relationship between PE and fracture. Comparison of genes encoding these proteins with genes obtained from TWAS and then with differentially expressed genes obtained from PE mRNA expression profiling revealed that PE was highly correlated with the BMP family of genes.

Dissecting the Genetic Structure of Maize Leaf Sheaths at Seedling Stage by Image-Based High-Throughput Phenotypic Acquisition and Characterization

The rapid development of high-throughput phenotypic detection techniques makes it possible to obtain a large number of crop phenotypic information quickly, efficiently, and accurately. Among them, image-based phenotypic acquisition method has been widely used in crop phenotypic identification and characteristic research due to its characteristics of automation, non-invasive, non-destructive and high throughput. In this study, we proposed a method to define and analyze the traits related to leaf sheaths including morphology-related, color-related and biomass-related traits at V6 stage. Next, we analyzed the phenotypic variation of leaf sheaths of 418 maize inbred lines based on 87 leaf sheath-related phenotypic traits. In order to further analyze the mechanism of leaf sheath phenotype formation, 25 key traits (2 biomass-related, 19 morphology-related and 4 color-related traits) with heritability greater than 0.3 were analyzed by genome-wide association studies (GWAS). And 1816 candidate genes of 17 whole plant leaf sheath traits and 1,297 candidate genes of 8 sixth leaf sheath traits were obtained, respectively. Among them, 46 genes with clear functional descriptions were annotated by single nucleotide polymorphism (SNPs) that both Top1 and multi-method validated. Functional enrichment analysis results showed that candidate genes of leaf sheath traits were enriched into multiple pathways related to cellular component assembly and organization, cell proliferation and epidermal cell differentiation, and response to hunger, nutrition and extracellular stimulation. The results presented here are helpful to further understand phenotypic traits of maize leaf sheath and provide a reference for revealing the genetic mechanism of maize leaf sheath phenotype formation.

OsCOMT, encoding a caffeic acid O-methyltransferase in melatonin biosynthesis, increases rice grain yield through dual regulation of leaf senescence and vascular development

Melatonin, a natural phytohormone in plants, plays multiple critical roles in plant growth and stress responses. Although melatonin biosynthesis-related genes have been suggested to possess diverse biological functions, their roles and functional mechanisms in regulating rice grain yield remain largely unexplored. Here, we uncovered the roles of a caffeic acid O-methyltransferase (OsCOMT) gene in mediating rice grain yield through dual regulation of leaf senescence and vascular development. In vitro and in vivo evidence revealed that OsCOMT is involved in melatonin biosynthesis. Transgenic assays suggested that OsCOMT significantly delays leaf senescence at the grain filling stage by inhibiting degradation of chlorophyll and chloroplast, which, in turn, improves photosynthesis efficiency. In addition, the number and size of vascular bundles in the culms and leaves were significantly increased in the OsCOMT-overexpressing plants, while decreased in the knockout plants, suggesting that OsCOMT plays a positive role in vascular development of rice. Further evidence indicated that OsCOMT-mediated vascular development might owe to the crosstalk between melatonin and cytokinin. More importantly, we found that OsCOMT is a positive regulator of grain yield, and overexpression of OsCOMT increase grain yield per plant even in a high-yield variety background, suggesting that OsCOMT can be used as an important target for enhancing rice yield. Our findings shed novel insights into melatonin-mediated leaf senescence and vascular development and provide a possible strategy for genetic improvement of rice grain yield.

High-Throughput Phenotyping Accelerates the Dissection of the Phenotypic Variation and Genetic Architecture of Shank Vascular Bundles in Maize (Zea mays L.)

The vascular bundle of the shank is an important ‘flow’ organ for transforming maize biological yield to grain yield, and its microscopic phenotypic characteristics and genetic analysis are of great significance for promoting the breeding of new varieties with high yield and good quality. In this study, shank CT images were obtained using the standard process for stem micro-CT data acquisition at resolutions up to 13.5 μm. Moreover, five categories and 36 phenotypic traits of the shank including related to the cross-section, epidermis zone, periphery zone, inner zone and vascular bundle were analyzed through an automatic CT image process pipeline based on the functional zones. Next, we analyzed the phenotypic variations in vascular bundles at the base of the shank among a group of 202 inbred lines based on comprehensive phenotypic information for two environments. It was found that the number of vascular bundles in the inner zone (IZ_VB_N) and the area of the inner zone (IZ_A) varied the most among the different subgroups. Combined with genome-wide association studies (GWAS), 806 significant single nucleotide polymorphisms (SNPs) were identified, and 1245 unique candidate genes for 30 key traits were detected, including the total area of vascular bundles (VB_A), the total number of vascular bundles (VB_N), the density of the vascular bundles (VB_D), etc. These candidate genes encode proteins involved in lignin, cellulose synthesis, transcription factors, material transportation and plant development. The results presented here will improve the understanding of the phenotypic traits of maize shank and provide an important phenotypic basis for high-throughput identification of vascular bundle functional genes of maize shank and promoting the breeding of new varieties with high yield and good quality.

Exploring the Developmental Progression of Endosperm Cavity Formation in Maize Grain and the Underlying Molecular Basis Using X-Ray Tomography and Genome Wide Association Study

Endosperm cavity (EC) in maize grain reduces yield and causes grain breakage during mechanical harvesting, hence representing a major problem in the maize industry. Despite this, little is known regarding the biological processes governing EC formation. Here, we attempted to address this issue by (i) determining the spatial and temporal progression of EC in a non-invasive manner and (ii) identifying candidate genes that may be linked to the formation of EC by using a genome wide association study (GWAS). Visualization and measurement using X-ray micro-computed tomography established that EC first appeared at the central starch endosperm at about 12 days after pollination (DAP) and became enlarged thereafter. GWAS-based screening of a panel of 299 inbred lines with a wide range of EC size identified nine candidate genes that showed significant association with EC formation. Most of the candidate genes exhibited a decrease at 12 DAP, coinciding with the timing of EC appearance. Among them, ZmMrp11 was annotated as a member encoding a multidrug resistance-associated protein that has been shown in other studies to sequestrate toxic metabolites from the cytosol to the vacuole, thereby detoxifying the cellular environment. This, together with the reduced expression of ZmMrp11 in maize grains from 12 DAP, prompted us to propose that the low expression of ZmMrp11 may block cellular detoxification in the maize endosperm cells, leading to cell death and ultimately the formation of EC.

A Genome-Wide Association Study Dissects the Genetic Architecture of the Metaxylem Vessel Number in Maize Brace Roots

Metaxylem vessels in maize brace roots are key tissue, and their number (MVN) affects plant water and inorganic salt transportation and lodging resistance. Dissecting the genetic basis of MVN in maize brace roots can help guide the genetic improvement of maize drought resistance and lodging resistance during late developmental stages. In this study, we used 508 inbred lines with tropical, subtropical, and temperate backgrounds to analyze the genetic architecture of MVN in maize brace roots. The phenotypic variation in MVN in brace roots was evaluated in three environments, which revealed broad natural variation and relative low levels of heritability (h ² = 0.42). Stiff-stalk lines with a temperate background tended to have higher MVNs than plants in other genetic backgrounds. MVN was significantly positively correlated with plant height, tassel maximum axis length, ear length, and kernel number per row, which indicates that MVN may affect plant morphological development and yield. In addition, MVN was extremely significantly negatively correlated with brace root radius, but significantly positively correlated with brace root angle (BRA), diameter, and number, thus suggesting that the morphological function of some brace root traits may be essentially determined by MVN. Association analysis of MVN in brace roots combined 1,253,814 single nucleotide polymorphisms (SNPs) using FarmCPU revealed a total of nine SNPs significantly associated with MVN at P < 7.96 × 10^-7. Five candidate genes for MVN that may participate in secondary wall formation (GRMZM2G168365, GRMZM2G470499, and GRMZM2G028982) and regulate flowering time (GRMZM2G381691 and GRMZM2G449165). These results provide useful information for understanding the genetic basis of MVN in brace root development. Further functional studies of identified candidate genes should help elucidate the molecular pathways that regulate MVN in maize brace roots.

Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review

Linking phenotypes and genotypes to identify genetic architectures that regulate important traits is crucial for plant breeding and the development of plant genomics. In recent years, genome-wide association studies (GWASs) have been applied extensively to interpret relationships between genes and traits. Successful GWAS application requires comprehensive genomic and phenotypic data from large populations. Although multiple high-throughput DNA sequencing approaches are available for the generation of genomics data, the capacity to generate high-quality phenotypic data is lagging far behind. Traditional methods for plant phenotyping mostly rely on manual measurements, which are laborious, inaccurate, and time-consuming, greatly impairing the acquisition of phenotypic data from large populations. In contrast, high-throughput phenotyping has unique advantages, facilitating rapid, non-destructive, and high-throughput detection, and, in turn, addressing the shortcomings of traditional methods. Aim of Review: This review summarizes the current status with regard to the integration of high-throughput phenotyping and GWAS in plants, in addition to discussing the inherent challenges and future prospects. Key Scientific Concepts of Review: High-throughput phenotyping, which facilitates non-contact and dynamic measurements, has the potential to offer high-quality trait data for GWAS and, in turn, to enhance the unraveling of genetic structures of complex plant traits. In conclusion, high-throughput phenotyping integration with GWAS could facilitate the revealing of coding information in plant genomes.

The Effect of Guttation on the Growth of Bamboo Shoots

Guttation is the process of exudating droplets from the tips, edges, and adaxial and abaxial surfaces of the undamaged leaves. Guttation is a natural and spontaneous biological phenomenon that occurs in a wide variety of plants. Despite its generally positive effect on plant growth, many aspects of this cryptic process are unknown. In this study, the guttation phenomenon characteristic of bamboo shoots and the anatomical feature of these and culm sheaths were systematically observed. In addition, the water transport pathway and the compounds in guttation droplets of bamboo shoots were analyzed, and the effect of bamboo sheaths’ guttation on the growth of bamboo shoots was assessed. The results revealed that bamboo shoots began to exudate liquid in the evening through to the next morning, during which period the volume of guttation liquid gradually increases and then decreases before sunrise. Many vascular bundles are in bamboo shoots and culm sheaths to facilitate this water transport. The exudate liquid contains organic acids, sugars, and hormones, among other compounds. Our findings suggest that the regular guttation of the sheath blade is crucial to maintain the normal growth of bamboo shoots.

Responses of Maize Internode to Water Deficit Are Different at the Biochemical and Histological Levels

Maize feeding value is strongly linked to plant digestibility. Cell wall composition and structure can partly explain cell wall digestibility variations, and we recently showed that tissue lignification and lignin spatial distribution also contribute to cell wall digestibility variations. Although the genetic determinism of digestibility and cell wall composition has been studied for more than 20 years, little is available concerning that of tissue lignification. Moreover, maize yield is negatively impacted by water deficit, and we newly highlighted the impact of water deficit on cell wall digestibility and composition together with tissue lignification. Consequently, the aim of this study was to explore the genetic mechanisms of lignin distribution in link with cell wall composition and digestibility under contrasted water regimes. Maize internodes from a recombinant inbred line (RIL) population grown in field trials with contrasting irrigation scenarios were biochemically and histologically quantified. Results obtained showed that biochemical and histological traits have different response thresholds to water deficit. Histological profiles were therefore only modified under pronounced water deficit, while most of the biochemical traits responded whatever the strength of the water deficit. Three main clusters of quantitative trait locus (QTL) for histological traits were detected. Interestingly, overlap between the biochemical and histological clusters is rare, and one noted especially colocalizations between histological QTL/clusters and QTL for p-coumaric acid content. These findings reinforce the suspected role of tissue p-coumaroylation for both the agronomic properties of plants as well as their digestibility.

Darkfield and Fluorescence Macrovision of a Series of Large Images to Assess Anatomical and Chemical Tissue Variability in Whole Cross-Sections of Maize Stems

The proportion and composition of plant tissues in maize stems vary with genotype and agroclimatic factors and may impact the final biomass use. In this manuscript, we propose a quantitative histology approach without any section labelling to estimate the proportion of different tissues in maize stem sections as well as their chemical characteristics. Macroscopic imaging was chosen to observe the entire section of a stem. Darkfield illumination was retained to visualise the whole stem cellular structure. Multispectral autofluorescence images were acquired to detect cell wall phenolic compounds after UV and visible excitations. Image analysis was implemented to extract morphological features and autofluorescence pseudospectra. By assimilating the internode to a cylinder, the relative proportions of tissues in the internode were estimated from their relative areas in the sections. The approach was applied to study a series of 14 maize inbred lines. Considerable variability was revealed among the 14 inbred lines for both anatomical and chemical traits. The most discriminant morphological descriptors were the relative amount of rind and parenchyma tissues together with the density and size of the individual bundles, the area of stem and the parenchyma cell diameter. The rind, as the most lignified tissue, showed strong visible-induced fluorescence which was line-dependant. The relative amount of para-coumaric acid was associated with the UV-induced fluorescence intensity in the rind and in the parenchyma near the rind, while ferulic acid amount was significantly correlated mainly with the parenchyma near the rind. The correlation between lignin and the tissue pseudospectra showed that a global higher amount of lignin resulted in a higher level of lignin fluorescence whatever the tissues. We demonstrated here the potential of darkfield and autofluorescence imaging coupled with image analysis to quantify histology of maize stem and highlight variability between different lines.