ABSTRACT
Genetic selection for whole-plant water use efficiency (yield per transpiration; WUEplant ) in any crop-breeding programme requires high-throughput phenotyping of component traits of WUEplant such as intrinsic water use efficiency (WUEi ; CO2 assimilation rate per stomatal conductance). Measuring WUEi by gas exchange measurements is laborious and time consuming and may not reflect an integrated WUEi over the life of the leaf. Alternatively, leaf carbon stable isotope composition (δ13 Cleaf ) has been suggested as a potential time-integrated proxy for WUEi that may provide a tool to screen for WUEplant . However, a genetic link between δ13 Cleaf and WUEplant in a C4 species has not been well established. Therefore, to determine if there is a genetic relationship in a C4 plant between δ13 Cleaf and WUEplant under well watered and water-limited growth conditions, a high-throughput phenotyping facility was used to measure WUEplant in a recombinant inbred line (RIL) population created between the C4 grasses Setaria viridis and S. italica. Three quantitative trait loci (QTL) for δ13 Cleaf were found and co-localized with transpiration, biomass accumulation, and WUEplant . Additionally, WUEplant for each of the δ13 Cleaf QTL allele classes was negatively correlated with δ13 Cleaf , as would be predicted when WUEi influences WUEplant . These results demonstrate that δ13 Cleaf is genetically linked to WUEplant , likely to be through their relationship with WUEi , and can be used as a high-throughput proxy to screen for WUEplant in these C4 species.
Subject(s)
Plant Leaves/metabolism , Setaria Plant/metabolism , Alleles , Carbon Isotopes/metabolism , Genes, Plant/genetics , Plant Transpiration/genetics , Quantitative Trait Loci/genetics , Quantitative Trait, Heritable , Setaria Plant/genetics , Water/metabolismABSTRACT
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.
Subject(s)
Environment, Controlled , Quantitative Trait Loci/genetics , Setaria Plant/genetics , Alleles , Biomass , Chromosome Mapping , Genome, Plant , Genotype , Multifactorial Inheritance/genetics , Phenotype , Setaria Plant/growth & developmentABSTRACT
Plant growth and water use are interrelated processes influenced by genetically controlled morphological and biochemical characteristics. Improving plant water use efficiency (WUE) to sustain growth in different environments is an important breeding objective that can improve crop yields and enhance agricultural sustainability. However, genetic improvement of WUE using traditional methods has proven difficult due to the low throughput and environmental heterogeneity of field settings. To overcome these limitations, this study utilizes a high-throughput phenotyping platform to quantify plant size and water use of an interspecific Setaria italica × Setaria viridis recombinant inbred line population at daily intervals in both well-watered and water-limited conditions. Our findings indicate that measurements of plant size and water use are correlated strongly in this system; therefore, a linear modeling approach was used to partition this relationship into predicted values of plant size given water use and deviations from this relationship at the genotype level. The resulting traits describing plant size, water use, and WUE all were heritable and responsive to soil water availability, allowing for a genetic dissection of the components of plant WUE under different watering treatments. Linkage mapping identified major loci underlying two different pleiotropic components of WUE. This study indicates that alleles controlling WUE derived from both wild and domesticated accessions can be utilized to predictably modulate trait values given a specified precipitation regime in the model C4 genus Setaria.
Subject(s)
Multifactorial Inheritance , Setaria Plant/genetics , Water/physiology , Alleles , Chromosome Mapping , Genotype , Phenotype , Setaria Plant/growth & development , Setaria Plant/physiologyABSTRACT
Cultivated potato is a clonally propagated autotetraploid species with a highly heterogeneous genome. Phased assemblies of six cultivars including two chromosome-scale phased genome assemblies revealed extensive allelic diversity, including altered coding and transcript sequences, preferential allele expression, and structural variation that collectively result in a highly complex transcriptome and predicted proteome, which are distributed across the homologous chromosomes. Wild species contribute to the extensive allelic diversity in tetraploid cultivars, demonstrating ancestral introgressions predating modern breeding efforts. As a clonally propagated autotetraploid that undergoes limited meiosis, dysfunctional and deleterious alleles are not purged in tetraploid potato. Nearly a quarter of the loci bore mutations are predicted to have a high negative impact on protein function, complicating breeder's efforts to reduce genetic load. The StCDF1 locus controls maturity, and analysis of six tetraploid genomes revealed that 12 allelic variants of StCDF1 are correlated with maturity in a dosage-dependent manner. Knowledge of the complexity of the tetraploid potato genome with its rampant structural variation and embedded deleterious and dysfunctional alleles will be key not only to implementing precision breeding of tetraploid cultivars but also to the construction of homozygous, diploid potato germplasm containing favorable alleles to capitalize on heterosis in F1 hybrids.
Subject(s)
Solanum tuberosum , Tetraploidy , Alleles , Chromosomes , Plant Breeding , Proteome/genetics , Solanum tuberosum/genetics , Transcriptome/geneticsABSTRACT
Field-based, rapid, and nondestructive techniques for assessing plant productivity are needed to accelerate the discovery of genotype-to-phenotype relationships in next-generation biomass grass crops. The use of hemispherical imaging and light attenuation modeling was evaluated against destructive harvest measures with respect to their ability to accurately capture phenotypic and genotypic relationships in a field-grown grass crop. Plant area index (PAI) estimated from below-canopy hemispherical images, as well as a suite of thirteen traits assessed by manual destructive harvests, were measured in a Setaria recombinant inbred line mapping population segregating for aboveground productivity and architecture. A significant correlation was observed between PAI and biomass production across the population at maturity (r 2 = .60), as well as for select diverse genotypes sampled repeatedly over the growing season (r 2 = .79). Twenty-seven quantitative trait loci (QTL) were detected for manually collected traits associated with biomass production. Of these, twenty-one were found in four clusters of colocalized QTL. Analysis of image-based estimates of PAI successfully identified all four QTL hot spots for biomass production. QTL for PAI had greater overlap with those detected for traits associated with biomass production than with those for plant architecture and biomass partitioning. Hemispherical imaging is an affordable and scalable method, which demonstrates how high-throughput phenotyping can identify QTL related to biomass production of field trials in place of destructive harvests that are labor, time, and material intensive.
ABSTRACT
Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.