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At least 667 records · Page 37

Vertical canopy gradients of respiration drive plant carbon budgets and leaf area index

Despite its importance for determining global carbon fluxes, leaf respiration remains poorly constrained in land surface models (LSMs). We tested the sensitivity of the Energy Exascale Earth System Model Land Model – Functionally Assembled Terrestrial Ecosystem Simulator (ELM-FATES) to variation in the canopy gradients of leaf maintenance respiration (R dark ). We ran global and point simulations varying the canopy gradient of R dark to explore the impacts on forest structure, composition, and carbon cycling. In global simulations, steeper canopy gradients of R dark lead to increased understory survival and leaf biomass. Leaf area index (LAI) increased up to 77% in tropical regions compared with the default parameterization, improving alignment with remotely sensed benchmarks. Global vegetation carbon varied from 308 Pg C to 449 Pg C across the ensemble. In tropical forest simulations, steeper gradients of R dark had a large impact on successional dynamics. Results show the importance of canopy gradients in leaf traits and fluxes for determining plant carbon budgets and emergent ecosystem properties such as competitive dynamics, LAI, and vegetation carbon. The high-model sensitivity to canopy gradients in R dark highlights the need for more observations of how leaf traits and fluxes vary along light micro-environments to inform critical dynamics in LSMs.

59 BASIC BIOLOGICAL SCIENCES↗

Brachypodium SPEECHLESS2 Promoter Drives Expression of a Synthetic EPF to Reduce Stomatal Density in Sugarcane Without Pleiotropic Effects

Stomata are microscopic pores that regulate the exchange of CO 2 and water vapour, making them a major target for engineering plants with improved intrinsic water use efficiency (iWUE). Proof-of-concept studies have demonstrated the potential to increase iWUE by reducing stomatal density (SD) and stomatal conductance (g sw ) by ubiquitously expressing EPIDERMAL PATTERNING FACTOR (EPF) family genes. However, unwanted effects on leaf, stem and reproductive traits are often observed when EPFs are misexpressed in this fashion. We sought to test if these effects result from pleiotropy and to identify a targeted promoter that can circumvent the side effects while retaining the desired reduction in SD. A previously reported synthetic EPF (EPF syn ) was expressed in sugarcane ( Saccharum spp.) using two putatively tissue-specific promoters from Brachypodium distachyon (BdCESA7p and BdSPCH2p) and a ubiquitous control from Zea mays (ZmUBI4p). BdSPCH2p control reduced SD to statistically equivalent levels as ZmUBI4p on the abaxial (23%) and adaxial (23%) leaf surfaces. ZmUB4p and BdCESA7p induce expression in four tissue types often associated with pleiotropic effects in EPF-expressing low SD plants. Transgenic plants carrying either the BdCESA7p or ZmUBI4p EPF syn cassettes displayed leaf chlorosis, reduced leaf nitrogen and chlorophyll content, and altered stem architecture. However, transgenic events harboring the BdSPCH2p EPF syn cassette restricted EPF syn expression to the stomatal development zone and leaf nodal tissues and produced transgenic plants without the associated pleiotropic effects. These results represent an important step toward engineering low-SD crops since they show that targeted gene expression can engineer stomatal patterning without impairing agronomically important traits.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic QTL mapping for plant height in the hybrid population of Agropyron Gaertn.

Abstract Plant height (PH) plays a very important role for plant breeding and also serves as a model trait to dynamic development study. The dynamic quantitative trait locus (QTL) analysis for PH of Agropyron Gaertn. was carried out in a cross‐pollination (CP) hybrid population of A. Gaertn. based on the phenotypic data of PH at different developmental stages in four year‐sites and the constructed single‐nucleotide polymorphism (SNP) genetic map. The results showed that 69 QTL and nine major QTL were detected by unconditional QTL mapping. A total of 107 QTL and 13 major QTL were found using conditional QTL mapping. Forty‐seven QTL were detected by two methods. Two unconditional QTL, Qph2‐5 and Qph3‐4, were expressed as major and stable QTL for PH. Four major stable conditional QTL for PH, cQph4‐1 , cQph4‐8, cQph6‐2 and cQph6‐7 , were detected. Two conditional PH QTL, cQph3‐5 and cQPh3‐7 , were identified in four environments over multiple stages. The gene/QTL controlling PH was expressed in a certain spatiotemporal manner. These results could also provide a reference for genetic and breeding research of related plant.

Che, Yonghe↗

Source:sink imbalance detected with leaf and canopy-level spectroscopy in a field-grown crop

The finely-tuned balance between sources and sinks determines plant resource partitioning and regulates growth and development. Understanding and measuring metabolic indicators of source or sink limitation forms a vital part of global efforts to increase crop yield for future food security. Here, we measured metabolic profiles of Cucurbita pepo (zucchini) grown in the field under carbon sink limitation and control conditions. We demonstrate that these profiles can be measured non-destructively using hyperspectral reflectance at both leaf and canopy scales. Total non-structural carbohydrates (TNC) increased 82% in sink-limited plants; leaf mass per unit area (LMA) increased 38%; free amino acids increased 22%. Partial least-squares regression models link these measured functional traits with reflectance data, enabling high-throughput estimation of traits comprising the sink limitation response. Leaf- and canopy-scale models for TNC had R 2 values of 0.93 and 0.64 and %RMSE of 13% and 38% respectively. For LMA, R 2 values were 0.91 and 0.60 and %RMSE 7% and 14%; for free amino acids, R 2 was 0.53 and 0.21 with %RMSE 20% and 26%. Remote sensing can enable accurate, rapid detection of sink limitation in the field at the leaf and canopy scale, greatly expanding our ability to understand and measure metabolic responses to stress.

54 ENVIRONMENTAL SCIENCES↗

SNPeffect: identifying functional roles of SNPs using metabolic networks

Genetic sources of phenotypic variation have been a focus of plant studies aimed at improving agricultural yield and understanding adaptive processes. Genome-wide association studies identify the genetic background behind a trait by examining associations between phenotypes and single-nucleotide polymorphisms (SNPs). Although such studies are common, biological interpretation of the results remains a challenge; especially due to the confounding nature of population structure and the systematic biases thus introduced. Here, we propose a complementary analysis (SNPeffect) that offers putative genotype-to-phenotype mechanistic interpretations by integrating biochemical knowledge encoded in metabolic models. SNPeffect is used to explain differential growth rate and metabolite accumulation in A. thaliana and P. trichocarpa accessions as the outcome of SNPs in enzyme-coding genes. To this end, we also constructed a genome-scale metabolic model for Populus trichocarpa, the first for a perennial woody tree. As expected, our results indicate that growth is a complex polygenic trait governed by carbon and energy partitioning. The predicted set of functional SNPs in both species are associated with experimentally characterized growth-determining genes and also suggest putative ones. Functional SNPs were found in pathways such as amino acid metabolism, nucleotide biosynthesis, and cellulose and lignin biosynthesis, in line with breeding strategies that target pathways governing carbon and energy partition.

54 ENVIRONMENTAL SCIENCES↗

A chromosome-scale reference genome of trifoliate orange ( Poncirus trifoliata ) provides insights into disease resistance, cold tolerance and genome evolution in Citrus

Trifoliate orange (Poncirus trifoliata), a deciduous close relative of evergreen Citrus, has important traits for citrus production, including tolerance/resistance to citrus greening disease (Huanglongbing, HLB) and other major diseases, and cold tolerance. It has been one of the most important rootstocks, and one of the most valuable sources of resistance and tolerance genes for citrus. Here we present a high-quality, chromosomescale genome assembly of P. trifoliata. The 264.9-Mb assembly contains nine chromosomal pseudomolecules with 25 538 protein-coding genes, covering 97.2% of the estimated gene space. Comparative analyses of P. trifoliata and nine Citrus genomes revealed 605 species-specific genes and six rapidly evolving gene families in the P. trifoliata genome. Poncirus trifoliata has evolved specific adaptation in the C-repeat/ DREB binding factor (CBF)-dependent and CBF-independent cold signaling pathways to tolerate cold. We identified candidate genes within quantitative trait loci for HLB tolerance, and at the loci for resistance to citrus tristeza virus and citrus nematode. Genetic diversity analysis of Poncirus accessions and Poncirus/ Citrus hybrids shows a narrow genetic base in the US germplasm collection, and points to the importance of collecting and preserving more natural genetic variation. Two phenotypically divergent Poncirus accessions are found to be clonally related, supporting a previous conjecture that dwarf Flying Dragon originated as a mutant of a non-dwarfing type. The high-quality genome reveals features and evolutionary insights of Poncirus, and it will serve as a valuable resource for genetic, genomic and molecular research and manipulation in citrus.

54 ENVIRONMENTAL SCIENCES↗

RNAi and genome editing of sugarcane: Progress and prospects

SUMMARY Sugarcane, which provides 80% of global table sugar and 40% of biofuel, presents unique breeding challenges due to its highly polyploid, heterozygous, and frequently aneuploid genome. Significant progress has been made in developing genetic resources, including the recently completed reference genome of the sugarcane cultivar R570 and pan‐genomic resources from sorghum, a closely related diploid species. Biotechnological approaches including RNA interference (RNAi), overexpression of transgenes, and gene editing technologies offer promising avenues for accelerating sugarcane improvement. These methods have successfully targeted genes involved in important traits such as sucrose accumulation, lignin biosynthesis, biomass oil accumulation, and stress response. One of the main transformation methods—biolistic gene transfer or Agrobacterium ‐mediated transformation—coupled with efficient tissue culture protocols, is typically used for implementing these biotechnology approaches. Emerging technologies show promise for overcoming current limitations. The use of morphogenic genes can help address genotype constraints and improve transformation efficiency. Tissue culture‐free technologies, such as spray‐induced gene silencing, virus‐induced gene silencing, or virus‐induced gene editing, offer potential for accelerating functional genomics studies. Additionally, novel approaches including base and prime editing, orthogonal synthetic transcription factors, and synthetic directed evolution present opportunities for enhancing sugarcane traits. These advances collectively aim to improve sugarcane's efficiency as a crop for both sugar and biofuel production. This review aims to discuss the progress made in sugarcane methodologies, with a focus on RNAi and gene editing approaches, how RNAi can be used to inform functional gene targets, and future improvements and applications.

Brant, Eleanor [Agronomy Department, Plant Molecul↗

The mole genome reveals regulatory rearrangements associated with adaptive intersexuality

Linking genomic variation to phenotypical traits remains a major challenge in evolutionary genetics. In this study, we use phylogenomic strategies to investigate a distinctive trait among mammals: the development of masculinizing ovotestes in female moles. By combining a chromosome-scale genome assembly of the Iberian mole, Talpa occidentalis, with transcriptomic, epigenetic, and chromatin interaction datasets, we identify rearrangements altering the regulatory landscape of genes with distinct gonadal expression patterns. These include a tandem triplication involving CYP17A1, a gene controlling androgen synthesis, and an intrachromosomal inversion involving the pro-testicular growth factor gene FGF9, which is heterochronically expressed in mole ovotestes. Transgenic mice with a knock-in mole CYP17A1 enhancer or overexpressing FGF9 showed phenotypes recapitulating mole sexual features. Our results highlight how integrative genomic approaches can reveal the phenotypic impact of noncoding sequence changes.

59 BASIC BIOLOGICAL SCIENCES↗

Soil Origin and Plant Genotype Modulate Switchgrass Aboveground Productivity and Root Microbiome Assembly

Switchgrass (Panicum virgatum) is a model perennial grass for bioenergy production that can be productive in agricultural lands that are not suitable for food production. There is growing interest in whether its associated microbiome may be adaptive in low- or no-input cultivation systems. However, the relative impact of plant genotype and soil factors on plant microbiome and biomass are a challenge to decouple. To address this, a common garden greenhouse experiment was carried out using six common switchgrass genotypes, which were each grown in four different marginal soils collected from long-term bioenergy research sites in Michigan and Wisconsin. We characterized the fungal and bacterial root communities with high-throughput amplicon sequencing of the ITS and 16S rDNA markers, and collected phenological plant traits during plant growth, as well as soil chemical traits. At harvest, we measured the total plant aerial dry biomass. Significant differences in richness and Shannon diversity across soils but not between plant genotypes were found. Generalized linear models showed an interaction between soil and genotype for fungal richness but not for bacterial richness. Community structure was also strongly shaped by soil origin and soil origin × plant genotype interactions. Overall, plant genotype effects were significant but low. Random Forest models indicate that important factors impacting switchgrass biomass included NO 3 – , Ca 2+ , PO 4 3– , and microbial biodiversity. We identified 54 fungal and 52 bacterial predictors of plant aerial biomass, which included several operational taxonomic units belonging to Glomeraceae and Rhizobiaceae, fungal and bacterial lineages that are involved in provisioning nutrients to plants.

plant biomass↗

Metagenomic clustering links specific metabolic functions to globally relevant ecosystems

ABSTRACT Metagenomic sequencing has advanced our understanding of biogeochemical processes by providing an unprecedented view into the microbial composition of different ecosystems. While the amount of metagenomic data has grown rapidly, simple-to-use methods to analyze and compare across studies have lagged behind. Thus, tools expressing the metabolic traits of a community are needed to broaden the utility of existing data. Gene abundance profiles are a relatively low-dimensional embedding of a metagenome’s functional potential and are, thus, tractable for comparison across many samples. Here, we compare the abundance of KEGG Ortholog Groups (KOs) from 6,539 metagenomes from the Joint Genome Institute’s Integrated Microbial Genomes and Metagenomes (JGI IMG/M) database. We find that samples cluster into terrestrial, aquatic, and anaerobic ecosystems with marker KOs reflecting adaptations to these environments. For instance, functional clusters were differentiated by the metabolism of antibiotics, photosynthesis, methanogenesis, and surprisingly GC content. Using this functional gene approach, we reveal the broad-scale patterns shaping microbial communities and demonstrate the utility of ortholog abundance profiles for representing a rapidly expanding body of metagenomic data. IMPORTANCE Metagenomics, or the sequencing of DNA from complex microbiomes, provides a view into the microbial composition of different environments. Metagenome databases were created to compile sequencing data across studies, but it remains challenging to compare and gain insight from these large data sets. Consequently, there is a need to develop accessible approaches to extract knowledge across metagenomes. The abundance of different orthologs (i.e., genes that perform a similar function across species) provides a simplified representation of a metagenome’s metabolic potential that can easily be compared with others. In this study, we cluster the ortholog abundance profiles of thousands of metagenomes from diverse environments and uncover the traits that distinguish them. This work provides a simple to use framework for functional comparison and advances our understanding of how the environment shapes microbial communities.

54 ENVIRONMENTAL SCIENCES↗

Genetic modification of the shikimate pathway to reduce lignin content in switchgrass ( Panicum virgatum L.) significantly impacts plant microbiomes

Switchgrass (Panicum virgatum L.) is considered a sustainable biofuel feedstock, given its fast-impact growth, low input requirements, and high biomass yields. Improvements in bioenergy conversion efficiency of switchgrass could be made by reducing its lignin content. Engineered switchgrass that expresses a bacterial 3-dehydroshikimate dehydratase (QsuB) has reduced lignin content and improved biomass saccharification due to the rerouting of the shikimate pathway towards the simple aromatic protocatechuate at the expense of lignin biosynthesis. However, the impacts of this QsuB trait on switchgrass microbiome structure and function remain unclear. To address this, wild-type and QsuB-engineered switchgrass were grown in switchgrass field soils, and samples were collected from inflorescences, leaves, roots, rhizospheres, and bulk soils for microbiome analysis. We investigated how QsuB expression influenced switchgrass-associated fungal and bacterial communities using high-throughput Illumina MiSeq amplicon sequencing of ITS and 16S rDNA. Compared to wild-type, QsuB-engineered switchgrass hosted different microbial communities in roots, rhizosphere, and leaves. Specifically, QsuB-engineered plants had a lower relative abundance of arbuscular mycorrhizal fungi (AMF). Additionally, QsuB-engineered plants had fewer Actinobacteriota in root and rhizosphere samples. These findings may indicate that changes in the plant metabolism impact both AMF and Actinobacteriota similarly or potential interactions between AMF and the bacterial community. This study enhances understanding of plant-microbiome interactions by providing baseline microbial data for developing beneficial bioengineering strategies and by assessing nontarget impacts of engineered plant traits on the plant microbiome.

09 BIOMASS FUELS↗

Few-shot leaf segmentation

In this work, we use few-shot learning to segment the body and vein architecture of Populus trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the "vein density" trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code, we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes.

Lagergren, John [Oak Ridge National Lab. (ORNL), O↗

Structure-informed clustering for population stratification in association studies

Background: Identifying variants associated with complex traits is a challenging task in genetic association studies due to linkage disequilibrium (LD) between genetic variants and population stratification, unrelated to the disease risk. Existing methods of population structure correction use principal component analysis or linear mixed models with a random effect when modeling associations between a trait of interest and genetic markers. However, due to stringent significance thresholds and latent interactions between the markers, these methods often fail to detect genuinely associated variants. Results: To overcome this, we propose CluStrat, which corrects for complex arbitrarily structured populations while leveraging the linkage disequilibrium induced distances between genetic markers. It performs an agglomerative hierarchical clustering using the Mahalanobis distance covariance matrix of the markers. In simulation studies, we show that our method outperforms existing methods in detecting true causal variants. Applying CluStrat on WTCCC2 and UK Biobank cohorts, we found biologically relevant associations in Schizophrenia and Myocardial Infarction. CluStrat was also able to correct for population structure in polygenic adaptation of height in Europeans. Conclusions: CluStrat highlights the advantages of biologically relevant distance metrics, such as the Mahalanobis distance, which captures the cryptic interactions within populations in the presence of LD better than the Euclidean distance.

59 BASIC BIOLOGICAL SCIENCES↗

Metapangenomics reveals depth-dependent shifts in metabolic potential for the ubiquitous marine bacterial SAR324 lineage

Abstract Background Oceanic microbiomes play a pivotal role in the global carbon cycle and are central to the transformation and recycling of carbon and energy in the ocean’s interior. SAR324 is a ubiquitous but poorly understood uncultivated clade of Deltaproteobacteria that inhabits the entire water column, from ocean surface waters to its deep interior. Although some progress has been made in elucidating potential metabolic traits of SAR324 in the dark ocean, very little is known about the ecology and the metabolic capabilities of this group in the euphotic and twilight zones. To investigate the comparative genomics, ecology, and physiological potential of the SAR324 clade, we examined the distribution and variability of key genomic features and metabolic pathways in this group from surface waters to the abyss in the North Pacific Subtropical Gyre, one of the largest biomes on Earth. Results We leveraged a pangenomic ecological approach, combining spatio-temporally resolved single-amplified genome, metagenomic, and metatranscriptomic datasets. The data revealed substantial genomic diversity throughout the SAR324 clade, with distinct depth and temporal distributions that clearly differentiated ecotypes. Phylogenomic subclade delineation, environmental distributions, genomic feature similarities, and metabolic capacities revealed strong congruence. The four SAR324 ecotypes delineated in this study revealed striking divergence from one another with respect to their habitat-specific metabolic potentials. The ecotypes living in the dark or twilight oceans shared genomic features and metabolic capabilities consistent with a sulfur-based chemolithoautotrophic lifestyle. In contrast, those inhabiting the sunlit ocean displayed higher plasticity energy-related metabolic pathways, supporting a presumptive photoheterotrophic lifestyle. In epipelagic SAR324 ecotypes, we observed the presence of two types of proton-pumping rhodopsins, as well as genomic, transcriptomic, and ecological evidence for active photoheterotrophy, based on xanthorhodopsin-like light-harvesting proteins. Conclusions Combining pangenomic and both metagenomic and metatranscriptomic profiling revealed a striking divergence in the vertical distribution, genomic composition, metabolic potential, and predicted lifestyle strategies of geographically co-located members of the SAR324 bacterial clade. The results highlight the utility of metapangenomic approaches employed across environmental gradients, to decipher the properties and variation in function and ecological traits of specific phylogenetic clades within complex microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗

Long-term nitrogen deposition enhances microbial capacities in soil carbon stabilization but reduces network complexity

Background: Anthropogenic activities have increased the inputs of atmospheric reactive nitrogen (N) into terrestrial ecosystems, affecting soil carbon stability and microbial communities. Previous studies have primarily examined the effects of nitrogen deposition on microbial taxonomy, enzymatic activities, and functional processes. Here, we examined various functional traits of soil microbial communities and how these traits are interrelated in a Mediterranean type grassland administrated with 14 years of 7 g m –2 year –1 of N amendment, based on estimated atmospheric N deposition in areas within California, USA, by the end of the twenty-first century. Results: Soil microbial communities were significantly altered by N deposition. Consistent with higher aboveground plant biomass and litter, fast-growing bacteria, assessed by abundance-weighted average rRNA operon copy number, were favored in N deposited soils. The relative abundances of genes associated with labile carbon (C) degradation (e.g., amyA and cda) were also increased. In contrast, the relative abundances of functional genes associated with the degradation of more recalcitrant C (e.g., mannanase and chitinase) were either unchanged or decreased. Compared with the ambient control, N deposition significantly reduced network complexity, such as average degree and connectedness. The network for N deposited samples contained only genes associated with C degradation, suggesting that C degradation genes became more intensely connected under N deposition. Conclusions: We propose a conceptual model to summarize the mechanisms of how changes in above- and belowground ecosystems by long-term N deposition collectively lead to more soil C accumulation.

59 BASIC BIOLOGICAL SCIENCES↗

Induction of kidney-related gene programs through co-option of SALL1 in mole ovotestes

Changes in gene expression represent an important source of phenotypic innovation. Yet how such changes emerge and impact the evolution of traits remains elusive. Here, we explore the molecular mechanisms associated with the development of masculinizing ovotestes in female moles. By performing integrative analyses of epigenetic and transcriptional data in mole and mouse, we identified the co-option of SALL1 expression in mole ovotestes formation. Chromosome conformation capture analyses highlight a striking conservation of the 3D organization at the SALL1 locus, but an evolutionary divergence of enhancer activity. Interspecies reporter assays support the capability of mole-specific enhancers to activate transcription in urogenital tissues. Through overexpression experiments in transgenic mice, we further demonstrate the capability of SALL1 to induce kidney-related gene programs, which are a signature of mole ovotestes. Our results highlight the co-option of gene expression, through changes in enhancer activity, as a plausible mechanism for the evolution of traits.

59 BASIC BIOLOGICAL SCIENCES↗

Data for "Genetics of flooding tolerance in an F2 Miscanthus sacchariflorus ssp. lutarioriparius × M. sinensis population"

This dataset contains all data and supplementary materials from "Genetics of flooding tolerance in an F2 Miscanthus sacchariflorus ssp. lutarioriparius × M. sinensis population". 1. The dataset S1 table contains the raw phenotypic data collected during the experiment. 2. The dataset S2 table contains the LSmean values for the 24 traits studied. 3. The dataset S3 table contains the TASSEL GBSv2 map, marker information, and genotype data used for mapping. 4. The dataset S4 table contains information on candidate genes found in each of the QTL intervals. 5. The dataset S5 table contains the GO annotations and KEGG enrichment analyses for those candidate genes. 6. The dataset S6 table contains information on the sequences used to classify AP2 ERF transcription factors. 7. The dataset S7 table contains information on AP2 ERF orthologs between Miscanthus and rice based on synteny. 8. Supplementary file 1 contains the ANOVA results using the raw phenotypic data collected from protocol "A". 9. Supplementary file 2 contains the ANOVA results using the raw phenotypic data collected from protocol "B". 10. Supplementary file 3 contains notes on the comparison of SNP calling methods. 11. Supplementary file 4 is a script for analyzing candidate genes found in QTL intervals.

Miscanthus, flood, partial submergence, complete s↗

Data for "Enhancing Lipid Production in Plant Cells through Automated High-Throughput Genome Engineering and Phenotyping"

Plant bioengineering is a time-consuming and labor-intensive process with no guarantee of achieving desired traits. Here, we present a fast, automated, scalable, high-throughput pipeline for plant bioengineering (FAST-PB) in maize (Zea mays) and Nicotiana benthamiana. FAST-PB enables genome editing and product characterization by integrating automated biofoundry engineering of callus and protoplast cells with single-cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrated that FAST-PB could streamline Golden Gate cloning, with the capacity to construct 96 vectors in parallel. Using FAST-PB in protoplasts, we found that PEG2050 increased transfection efficiency by over 45%. For proof-of-concept, we established a reporter-gene-free method for CRISPR editing and phenotyping via mutation of high chlorophyll fluorescence 136. We show that diverse lipids were enhanced up to 6-fold using CRISPR activation of lipid controlling genes. In callus cells, an automated transformation platform was employed to regenerate plants with enhanced lipid traits through introducing multigene cassettes. Lastly, FAST-PB enabled high-throughput single-cell lipid profiling by integrating MALDI-MS with the biofoundry, protoplast, and callus cells, differentiating engineered and unengineered cells using single-cell lipidomics. These innovations massively increase the throughput of synthetic biology, genome editing, and metabolic engineering and change what is possible using single-cell metabolomics in plants.

AI/ML↗