QTL for the Kinematic Traits That Define the Arabidopsis Root Elongation Zone and Their Relationship to Gravitropism.

Cell expansion in a discrete region called the elongation zone drives root elongation. Analyzing time lapse images can quantify the expansion in kinematic terms as if it were fluid flow. We used horizontal microscopes to collect images from which custom software extracted the length of the elongation zone, the peak relative elemental growth rate (REGR) within it, the axial position of the REGR peak, and the root elongation rate. Automation enabled these kinematic traits to be measured in 1575 Arabidopsis seedlings representing 162 recombinant inbred lines (RILs) derived from a cross of Cvi and Ler ecotypes. We mapped ten quantitative trait loci (QTL), affecting the four kinematic traits. Three QTL affected two or more traits in these vertically oriented seedlings. We compared this genetic architecture with that previously determined for gravitropism using the same RIL population. The major QTL peaks for the kinematic traits did not overlap with the gravitropism QTL. Furthermore, no single kinematic trait correlated with quantitative descriptors of the gravitropism response curve across this population. In addition to mapping QTL for growth zone traits, this study showed that the size and shape of the elongation zone may vary widely without affecting the differential growth induced by gravity.

Evaluating relationships between seed morphological traits and seed dormancy in Chenopodium quinoa Willd.

Introduction: Quinoa is a high-value, nutritious crop that performs well in variable environments, marginal soils, and in diverse crop rotations. Quinoa's many attributes make it an ideal crop for supporting human health in global communities and economies. To date, quinoa research has largely focused on traits in adult plants important for enhancing plant phenotypic plasticity, abiotic stress, disease resistance, and yield. Fewer studies have evaluated quinoa seed dormancy and suggest that most modern quinoa varieties have weak or no seed dormancy, and a narrow window of seed viability post-harvest. In other crops, diminished seed dormancy is a major risk factor for preharvest sprouting (PHS; germination on the panicle due to rain prior to harvest) and may also pose a similar risk for quinoa. Methods: This study (1) developed a dormancy screening assay to characterize seed dormancy strength in a large collection of quinoa varieties, (2) investigated if morphological variables including seed coat color, seed coat thickness, seed shape including eccentricity which evaluates the roundness or flatness of a seed, and other agronomic traits like crude protein content and seed moisture, contribute to quinoa seed dormancy, and (3) evaluated the use of a phenetic modeling approach to explore relationships between seed morphology and seed dormancy. Results: Dormancy screening indicated seed dormancy ranges in quinoa varieties from none to strong dormancy. Further, phenetic modeling approaches indicate that seed coat thickness and eccentricity are important morphological variables that impact quinoa seed dormancy strength. Conclusions: While dormancy screening and phenetic modeling approaches do not provide a direct solution to preventing PHS in quinoa, they do provide new tools for identifying dormant varieties as well as morphological variables contributing to seed dormancy.

Patch Track Software for Measuring Kinematic Phenotypes of Arabidopsis Roots Demonstrated on Auxin Transport Mutants.

Plant roots elongate when cells produced in the apical meristem enter a transient period of rapid expansion. To measure the dynamic process of root cell expansion in the elongation zone, we captured digital images of growing Arabidopsis roots with horizontal microscopes and analyzed them with a custom image analysis program (PatchTrack) designed to track the growth-driven displacement of many closely spaced image patches. Fitting a flexible logistics equation to patch velocities plotted versus position along the root axis produced the length of the elongation zone (mm), peak relative elemental growth rate (% h-1), the axial position of the peak (mm from the tip), and average root elongation rate (mm h-1). For a wild-type root, the average values of these kinematic traits were 0.52 mm, 23.7% h-1, 0.35 mm, and 0.1 mm h-1, respectively. We used the platform to determine the kinematic phenotypes of auxin transport mutants. The results support a model in which the PIN2 auxin transporter creates an area of expansion-suppressing, supraoptimal auxin concentration that ends 0.1 mm from the quiescent center (QC), and that ABCB4 and ABCB19 auxin transporters maintain expansion-limiting suboptimal auxin levels beginning approximately 0.5 mm from the QC. This study shows that PatchTrack can quantify dynamic root phenotypes in kinematic terms.

A comprehensive characterization of agronomic and end-use quality phenotypes across a quinoa world core collection.

Quinoa (Chenopodium quinoa Willd.), a pseudocereal with high protein quality originating from the Andean region of South America, has broad genetic variation and adaptability to diverse agroecological conditions, contributing to the potential to serve as a global keystone protein crop in a changing climate. However, the germplasm resources currently available to facilitate quinoa expansion worldwide are restricted to a small portion of quinoa's total genetic diversity, in part because of day-length sensitivity and issues related to seed sovereignty. This study aimed to characterize phenotypic relationships and variation within a quinoa world core collection. The 360 accessions were planted in a randomized complete block design with four replicates in each of two greenhouses in Pullman, WA during the summer of 2018. Phenological stages, plant height, and inflorescence characteristics were recorded. Seed yield, composition, thousand seed weight, nutritional composition, shape, size, and color were measured using a high-throughput phenotyping pipeline. Considerable variation existed among the germplasm. Crude protein content ranged from 11.24% to 17.81% (fixed at 14% moisture). We found that protein content was negatively correlated with yield and positively correlated with total amino acid content and days to harvest. Mean essential amino acids values met adult daily requirements but not leucine and lysine infant requirements. Yield was positively correlated with thousand seed weight and seed area, and negatively correlated with ash content and days to harvest. The accessions clustered into four groups, with one-group representing useful accessions for long-day breeding programs. The results of this study establish a practical resource for plant breeders to leverage as they strategically develop germplasm in support of the global expansion of quinoa.

BRXL4-LAZY1 interaction at the plasma membrane controls Arabidopsis branch angle and gravitropism.

Gravitropism guides growth to shape plant architecture above and below ground. Mutations in LAZY1 impair stem gravitropism and cause less upright inflorescence branches (wider angles). The LAZY1 protein resides at the plasma membrane and in the nucleus. The plasma membrane pool is necessary and sufficient for setting branch angles. To investigate the molecular mechanism of LAZY1 function, we screened for LAZY1-interacting proteins in yeast. We identified BRXL4, a shoot-specific protein related to BREVIS RADIX. The BRXL4-LAZY1 interaction occurred at the plasma membrane in plant cells, and not detectably in the nucleus. Mutations in the C-terminus of LAZY1, but not other conserved regions, prevented the interaction. Opposite to lazy1, brxl4 mutants displayed faster gravitropism and more upright branches. Overexpressing BRXL4 produced strong lazy1 phenotypes. The apparent negative regulation of LAZY1 function is consistent with BRXL4 reducing LAZY1 expression or the amount of LAZY1 at the plasma membrane. Measurements indicated that both are true. LAZY1 mRNA was three-fold more abundant in brxl4 mutants and almost undetectable in BRXL4 overexpressors. Plasma membrane LAZY1 was higher and nuclear LAZY1 lower in brxl4 mutants compared with the wild type. To explain these results, we suggest that BRXL4 reduces the amount of LAZY1 at the plasma membrane where it functions in gravity signaling and promotes LAZY1 accumulation in the nucleus where it reduces LAZY1 expression, possibly by suppressing its own transcription. This explanation of how BRXL4 negatively regulates LAZY1 suggests ways to modify shoot system architecture for practical purposes.

Leveraging orthology within maize and Arabidopsis QTL to identify genes affecting natural variation in gravitropism.

Plants typically orient their organs with respect to the Earth's gravity field by a dynamic process called gravitropism. To discover conserved genetic elements affecting seedling root gravitropism, we measured the process in a set of Zea mays (maize) recombinant inbred lines with machine vision and compared the results with those obtained in a similar study of Arabidopsis thaliana. Each of the several quantitative trait loci that we mapped in both species spanned many hundreds of genes, too many to test individually for causality. We reasoned that orthologous genes may be responsible for natural variation in monocot and dicot root gravitropism. If so, pairs of orthologous genes affecting gravitropism may be present within the maize and Arabidopsis QTL intervals. A reciprocal comparison of sequences within the QTL intervals identified seven pairs of such one-to-one orthologs. Analysis of knockout mutants demonstrated a role in gravitropism for four of the seven: CCT2 functions in phosphatidylcholine biosynthesis, ATG5 functions in membrane remodeling during autophagy, UGP2 produces the substrate for cellulose and callose polymer extension, and FAMA is a transcription factor. Automated phenotyping enabled this discovery of four naturally varying components of a conserved process (gravitropism) by making it feasible to conduct the same large-scale experiment in two species.

A novel high-throughput hyperspectral scanner and analytical methods for predicting maize kernel composition and physical traits.

Large-scale investigations of maize kernel traits important to researchers, breeders, and processors require high throughput methods, which are presently lacking. To address this bottleneck, we developed a novel flatbed platform that automatically acquires and analyzes multiwavelength near-infrared (NIR hyperspectral) images of maize kernels precisely enough to support robust predictions of protein content, density, and endosperm vitreousness. The upward facing-camera design and the automated ability to analyze the embryo or abgerminal sides of each individual kernel in a sample with the appropriate side-specific model helped to produce a superior combination of throughput and prediction accuracy compared to other single-kernel platforms. Protein was predicted to within 0.85% (root mean square error of prediction), density to within 0.038 g/cm3, and endosperm vitreousness percentage to within 6.3%. Kernel length and width were also accurately measured so that each kernel in a rapidly scanned sample was comprehensively characterized.

Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions.

Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 was genetically correlated with SD, SLA, gs, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.

Characterizing introgression-by-environment interactions using maize near isogenic lines.

KEY MESSAGE: Significant introgression-by-environment interactions are observed for traits throughout development from small introgressed segments of the genome. Relatively small genomic introgressions containing quantitative trait loci can have significant impacts on the phenotype of an individual plant. However, the magnitude of phenotypic effects for the same introgression can vary quite substantially in different environments due to introgression-by-environment interactions. To study potential patterns of introgression-by-environment interactions, fifteen near-isogenic lines (NILs) with > 90% B73 genetic background and multiple Mo17 introgressions were grown in 16 different environments. These environments included five geographical locations with multiple planting dates and multiple planting densities. The phenotypic impact of the introgressions was evaluated for up to 26 traits that span different growth stages in each environment to assess introgression-by-environment interactions. Results from this study showed that small portions of the genome can drive significant genotype-by-environment interaction across a wide range of vegetative and reproductive traits, and the magnitude of the introgression-by-environment interaction varies across traits. Some introgressed segments were more prone to introgression-by-environment interaction than others when evaluating the interaction on a whole plant basis throughout developmental time, indicating variation in phenotypic plasticity throughout the genome. Understanding the profile of introgression-by-environment interaction in NILs is useful in consideration of how small introgressions of QTL or transgene containing regions might be expected to impact traits in diverse environments.

Maize genomes to fields (G2F): 2014-2017 field seasons: genotype, phenotype, climatic, soil, and inbred ear image datasets.

OBJECTIVES: Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F's genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014-2017. DATA DESCRIPTION: Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.

The complex response of free and bound amino acids to water stress during the seed setting stage in Arabidopsis.

Free amino acids (FAAs) and protein-bound amino acids (PBAAs) in seeds play an important role in seed desiccation, longevity, and germination. However, the effect that water stress has on these two functional pools, especially when imposed during the crucial seed setting stage is unclear. To better understand these effects, we exposed Arabidopsis plants at the seed setting stage to a range of water limitation and water deprivation conditions and then evaluated physiological, metabolic, and proteomic parameters, with special focus on FAAs and PBAAs. We found that in response to severe water limitation, seed yield decreased, while seed weight, FAA, and PBAA content per seed increased. Nevertheless, the composition of FAAs and PBAAs remained unaltered. In response to severe water deprivation, however, both seed yield and weight were reduced. In addition, major alterations were observed in both FAA and proteome compositions, which indicated that both osmotic adjustment and proteomic reprogramming occurred in these naturally desiccation-tolerant organs. However, despite the major proteomic alteration, the PBAA composition did not change, suggesting that the proteomic reprogramming was followed by a proteomic rebalancing. Proteomic rebalancing has not been observed previously in response to stress, but its occurrence under stress strongly suggests its natural function. Together, our data show that the dry seed PBAA composition plays a key role in seed fitness and therefore is rigorously maintained even under severe water stress, while the FAA composition is more plastic and adaptable to changing environments, and that both functional pools are distinctly regulated.

Predicting Zea mays Flowering Time, Yield, and Kernel Dimensions by Analyzing Aerial Images.

Image analysis methods for measuring crop phenotypes may replace traditional measurements if they more efficiently and reliably capture similar or superior information. This study used a recreational-grade unmanned aerial vehicle carrying a spectrally-modified consumer-grade camera to collect images in which each pixel value is a vegetation index based on the normalized difference between the blue and near infrared wavelength bands (BNDVI). The subjects of the study were Zea mays hybrids with good yield potential grown in 4-row plots. Flights were conducted at least once per week during three successive growing seasons in south-central Wisconsin. Average BNDVI for each plot (genotype) rose steadily through June, peaked in July, and then declined as plants matured. BNDVI histograms changed shape over the season as the canopy concealed soil, became more uniformly green, then senesced. Principal Components Analysis (PCA) captured the change in histogram shape. PC1 represented canopy closure. PC2 represented the mean of the BNDVI distribution. PC3 represented the spread of the distribution. Correlation analysis showed that flowering time correlated with PC2 and PC3 best (r ≈ 0.5) a few days before the event (day in which 50% of the plants exhibited tassels). Three ears were picked from each plot to quantify kernel dimensions by image analysis before each plot was mechanically harvested to determine grain weight per plot. Correlations between this measurement of yield and PC2 were low in June but exceeded 0.4 within 10 days after flowering. Kernel length correlated similarly with PC2. The correlation between PC2 and kernel thickness displayed a similar but inverted time course. These results indicate that greater mid-season BNDVI values correlate positively with yield comprised of tall, thin kernels. Partial least squares regression performed on the BNDVI time courses predicted flowering time (r = 0.54-0.79) and yield (r = 0.4-0.69). This three-year experiment demonstrated that readily available hardware and software can create a phenotyping platform capable of predicting maize flowering time, yield, and kernel dimensions to a useful degree.

Correction: Genotype-by-environment interactions affecting heterosis in maize.

[This corrects the article DOI: 10.1371/journal.pone.0191321.].

Conservation of the genome-wide recombination rate in white-footed mice.

Despite being linked to the fundamental processes of chromosome segregation and offspring diversification, meiotic recombination rates vary within and between species. Recent years have seen progress in quantifying recombination rate evolution across multiple temporal and genomic scales. Nevertheless, the level of variation in recombination rate within wild populations-a key determinant of evolution in this trait-remains poorly documented on the genomic scale. To address this notable gap, we used immunofluorescent cytology to quantify genome-wide recombination rates in males from a wild population of the white-footed mouse, Peromyscus leucopus. For comparison, we measured recombination rates in a second population of male P. leucopus raised in the laboratory and in male deer mice from the subspecies Peromyscus maniculatus bairdii. Although we found differences between individuals in the genome-wide recombination rate, levels of variation were low-within populations, between populations, and between species. Quantification of synaptonemal complex length and crossover positions along chromosome 1 using a novel automated approach also revealed conservation in broad-scale crossover patterning, including strong crossover interference. We propose stabilizing selection targeting recombination or correlated processes as the explanation for these patterns.

Classifying cold-stress responses of inbred maize seedlings using RGB imaging.

Increasing the tolerance of maize seedlings to low-temperature episodes could mitigate the effects of increasing climate variability on yield. To aid progress toward this goal, we established a growth chamber-based system for subjecting seedlings of 40 maize inbred genotypes to a defined, temporary cold stress while collecting digital profile images over a 9-daytime course. Image analysis performed with PlantCV software quantified shoot height, shoot area, 14 other morphological traits, and necrosis identified by color analysis. Hierarchical clustering of changes in growth rates of morphological traits and quantification of leaf necrosis over two time intervals resulted in three clusters of genotypes, which are characterized by unique responses to cold stress. For any given genotype, the set of traits with similar growth rates is unique. However, the patterns among traits are different between genotypes. Cold sensitivity was not correlated with the latitude where the inbred varieties were released suggesting potential further improvement for this trait. This work will serve as the basis for future experiments investigating the genetic basis of recovery to cold stress in maize seedlings.

An Automated Image Analysis Pipeline Enables Genetic Studies of Shoot and Root Morphology in Carrot (Daucus carota L.).

Carrot is a globally important crop, yet efficient and accurate methods for quantifying its most important agronomic traits are lacking. To address this problem, we developed an automated image analysis platform that extracts components of size and shape for carrot shoots and roots, which are necessary to advance carrot breeding and genetics. This method reliably measured variation in shoot size and shape, petiole number, petiole length, and petiole width as evidenced by high correlations with hundreds of manual measurements. Similarly, root length and biomass were accurately measured from the images. This platform also quantified shoot and root shapes in terms of principal components, which do not have traditional, manually measurable equivalents. We applied the pipeline in a study of a six-parent diallel population and an F2 mapping population consisting of 316 individuals. We found high levels of repeatability within a growing environment, with low to moderate repeatability across environments. We also observed co-localization of quantitative trait loci for shoot and root characteristics on chromosomes 1, 2, and 7, suggesting these traits are controlled by genetic linkage and/or pleiotropy. By increasing the number of individuals and phenotypes that can be reliably quantified, the development of a rapid, automated image analysis pipeline to measure carrot shoot and root morphology will expand the scope and scale of breeding and genetic studies.

Regulation of Root Angle and Gravitropism.

Regulation of plant root angle is critical for obtaining nutrients and water and is an important trait for plant breeding. A plant's final, long-term root angle is the net result of a complex series of decisions made by a root tip in response to changes in nutrient availability, impediments, the gravity vector and other stimuli. When a root tip is displaced from the gravity vector, the short-term process of gravitropism results in rapid reorientation of the root toward the vertical. Here, we explore both short- and long-term regulation of root growth angle, using natural variation in tomato to identify shared and separate genetic features of the two responses. Mapping of expression quantitative trait loci mapping and leveraging natural variation between and within species including Arabidopsis suggest a role for PURPLE ACID PHOSPHATASE 27 and CELL DIVISION CYCLE 73 in determining root angle.

Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets.

OBJECTIVES: Crop improvement relies on analysis of phenotypic, genotypic, and environmental data. Given large, well-integrated, multi-year datasets, diverse queries can be made: Which lines perform best in hot, dry environments? Which alleles of specific genes are required for optimal performance in each environment? Such datasets also can be leveraged to predict cultivar performance, even in uncharacterized environments. The maize Genomes to Fields (G2F) Initiative is a multi-institutional organization of scientists working to generate and analyze such datasets from existing, publicly available inbred lines and hybrids. G2F's genotype by environment project has released 2014 and 2015 datasets to the public, with 2016 and 2017 collected and soon to be made available. DATA DESCRIPTION: Datasets include DNA sequences; traditional phenotype descriptions, as well as detailed ear, cob, and kernel phenotypes quantified by image analysis; weather station measurements; and soil characterizations by site. Data are released as comma separated value spreadsheets accompanied by extensive README text descriptions. For genotypic and phenotypic data, both raw data and a version with outliers removed are reported. For weather data, two versions are reported: a full dataset calibrated against nearby National Weather Service sites and a second calibrated set with outliers and apparent artifacts removed.

Distribution of Endogenous NO Regulates Early Gravitropic Response and PIN2 Localization in Arabidopsis Roots.

High-resolution and automated image analysis of individual roots demonstrated that endogenous nitric oxide (NO) contribute significantly to gravitropism of Arabidopsis roots. Lowering of endogenous NO concentrations strongly reduced and even reversed gravitropism, resulting in upward bending, without affecting root growth rate. Notably, the asymmetric accumulation of NO along the upper and lower sides of roots correlated with a positive gravitropic response. Detection of NO by the specific DAF-FM DA fluorescent probe revealed that NO was higher at the lower side of horizontally-oriented roots returning to initial values 2 h after the onset of gravistimulation. We demonstrate that NO promotes plasma membrane re-localization of PIN2 in epidermal cells, which is required during the early root gravitropic response. The dynamic and asymmetric localization of both auxin and NO is critical to regulate auxin polar transport during gravitropism. Our results collectively suggest that, although auxin and NO crosstalk occurs at different levels of regulation, they converge in the regulation of PIN2 membrane trafficking in gravistimulated roots, supporting the notion that a temporally and spatially coordinated network of signal molecules could participate in the early phases of auxin polar transport during gravitropism.