Biology subjects

Marshall-Colon, A.

Publications and source records attributed to Marshall-Colon, A..

12 recordsLinked to original sources

bioRxiv2025

GNC is a regulator of metabolic and productivity responses to elevated CO2 in Arabidopsis thaliana

Despite established understanding of plant physiological responses to elevated [CO2], the underlying genes are poorly understood. Soybean transcriptomics previously identified a GATA transcription factor, involved in carbon and nitrogen metabolism, as responsive to elevated [CO2]. Supported by in silico modeling, we therefore hypothesized that this gene plays a previously unrecognized role in responding to elevated [CO2]. Wildtype and a T-DNA insertion line of Arabidopsis thaliana for GNC (GATA, Nitrate Inducible, Carbon Metabolism Involved) were grown under three treatments: sustained ambient [CO2], sustained elevated [CO2], and transfer from ambient to elevated [CO2], to assess changes in their physiology, biochemistry, and transcriptome. Photosynthetic and biomass responses to elevated [CO2] and transfer [CO2] in plants lacking GNC were significantly weaker than WT. A lag of 25-73 hrs in transcriptomic responses after transfer to elevated [CO2] was consistent with indirect sensing, presumably via sugar signals. The breakdown of the gene expression network around GNC was most pronounced in the transfer treatment and suggests targets for further study of interactions between elevated [CO2] and sulfur and nitrogen metabolism. This work provides a case study of a CO2-responsive transcription factor that may be a compelling target for adapting crops to future growing conditions after further characterization. Summary StatementA GATA transcription factor modulates plant metabolic and productivity responses to elevated CO2.

plant biology↗

bioRxiv2025

Stage-resolved gene regulatory network analysis reveals developmental reprogramming and genes with robust stem-preferred expression in sorghum

BackgroundSorghum bicolor is a deep-rooted, heat- and drought-tolerant crop that thrives on marginal lands and is increasingly valued for its applications in biofuel, bioenergy, and biopolymer production. The sorghum stem, which can reach 4-5 meters in length, serves as the primary reservoir of both lignocellulosic biomass and soluble sugars, making it a promising bioenergy feedstock. Although recent advances in genetic, genomic, and transcriptomic resources have improved our understanding of sorghum biology, comprehensive genome-wide analyses of functional dynamics across diverse organ types and developmental stages remain limited. In particular, candidate genes with stem preferred expression pattern or their associated cis-regulatory elements, which may program key stem-related functions and enable organ- or tissue-specific engineering, have not yet been identified. ResultsTo address these gaps, we reanalyzed a published RNA-seq dataset to identify genes with organ-preferential expression and to infer representative organ functions across major developmental stages. Our analysis revealed that the sorghum stem exhibits distinct temporal functional signatures, which correlate with the developmental dynamics of stem-specific genes and their associated regulatory elements. We further identified a set of genes with ubiquitous stem-specific expression across diverse sorghum genotypes, suggesting their universal importance and broad potential for genetic engineering applications. Among them, SbTALE03 and SbTALE04 emerged as stem hub transcription factors (TF). Both genes were empirically validated for their stem specificity across stages. Gene regulatory network analysis further indicated that these TFs participate in stage-specific transcriptional programs that maintain and regulate stem development. ConclusionsThis study presents a genome-wide analysis of organ-specific gene expression, functions, and regulatory networks in sorghum, with a focus on genes preferentially-expressed in stems and their promoter motifs. We identified a set of core stem-specific genes with ubiquitous expression across genotypes and developmental stages, including two experimentally validated transcription factors with potential roles in stem development. These findings offer valuable candidates for further functional characterization and genetic engineering aimed at improving sorghum stem biomass and composition.

plant biology↗

bioRxiv2025

High and low exogenous nitrate concentrations produce distinct calcium signatures in Arabidopsis roots

Calcium (Ca2+) acts as a secondary messenger in plant responses to many stimuli, including nitrate (NO -) signaling in roots. Nitrate uptake in plants occurs through two distinct transporter systems that have different affinities for the anion, which result in divergent downstream regulatory responses. However, it is unknown if the concentration dependent NO - response is linked to differential Ca2+ response. In this study, we used an Arabidopsis transgenic line expressing CBL1-mRuby2-GCaMP6s to investigate if there are unique Ca2+ signatures in intact root tissue in response to high and low NO - concentrations. A significant Ca2+ response was observed in root hairs in response to both high (5 mM) and low (0.25 mM) NO - concentrations. A distinct Ca2+ wave was observed in the low NO - treated roots, and an asynchronous Ca2+ response was captured in individual root epidermal cells. Cell-specific analysis revealed a distinct Ca2+ profile, comprising waves and spikes in response to NO -, and prominent in root hairs but not in non-root hair bearing epidermal cells. The findings from this study demonstrate that there are distinct cell-specific and NO - condition-specific Ca2+ signatures in Arabidopsis roots.

plant biology↗

bioRxiv2025

Regulatory Analysis of Root Architectural and Anatomical Adaptation to Nitrate and Ammonium in Brachypodium distachyon

Root system architecture plays an important role in nitrate and ammonium uptake, the two primary nitrogen (N) forms essential for plant growth. Plants deploy different strategies to optimize the N uptake by roots, based on a complicated regulatory network that controls root phenotype and physiology. Here, we studied the response of root architecture to varying N applications in the model species Brachypodium distachyon. Using a combination of phenotypic and transcriptomic analyses, we examined how different forms and concentrations of ammonium and nitrate affect root growth, biomass allocation, and N uptake. N concentrations significantly influence root traits such as root length, root hair development, and aerenchyma formation in response to nitrate and ammonium. Plants grown in ammonium conditions had thin but highly branched roots, whereas nitrate application resulted in shorter, thicker roots with denser root hair at higher nitrate concentrations. Furthermore, using advanced co-expression network analysis, we identified an Atypical Aspartic Protease (APs) gene encoding an aspartyl protease family protein and a phosphoenolpyruvate carboxylase 1 (PEPC1) gene in brachypodium, which potentially control the root architectural and anatomical adaptions to different N form. APs expression showed a positive correlation with total root length and lateral root development, along with a negative correlation with root hair density. In contrast, PEPC1 exhibited positive correlations with cortex, stele, root cross-sectional areas, and root hair density, while showing a negative correlation with total root length. These genes likely play an important role in the transcriptional regulatory networks involved in these adaptive responses, which highlight the complex interplay between root morphology, nitrogen metabolism, and environmental nutrient conditions.

plant biology↗

bioRxiv2023

The stem cell-type transcriptome of bioenergy sorghum reveals the spatial regulation of secondary cell wall networks

Bioenergy sorghum is a low-input, drought-resilient, deep-rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghums 4-5 m stems account for [~]80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about stem cell-type gene expression and regulation was available to enable engineering. To obtain this information, Laser Capture Microdissection (LCM) was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell-type specific gene regulatory networks (GRNs) revealed that unique TF families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell-specific transcriptome data was combined with a stem developmental transcriptome dataset to identify the GRN that differentially activates the secondary cell wall (SCW) formation in stem xylem sclerenchyma and epidermal cells. The cell-type transcriptomic dataset provides a valuable source of information about the function of sorghum stem cell types and GRNs that will enable the engineering of bioenergy sorghum stems.

plant biology↗

bioRxiv2021

The complex genetics of symbiotic extended phenotypes across environments in a model mutualism

A goal of modern biology is to develop the genotype-phenotype (G[->]P) map, a predictive understanding of how genomic information generates trait variation that forms the basis of both natural and managed communities. As microbiome research advances, however, it has become clear that many of these traits are symbiotic extended phenotypes, being governed by genetic variation encoded not only by the hosts own genome, but also by the genomes of myriad cryptic symbionts. Building a reliable G[->]P map therefore requires accounting for the multitude of interacting genes and even genomes involved in symbiosis. Here we use naturally-occurring genetic variation in 191 strains of the model microbial symbiont Sinorhizobium meliloti paired with two genotypes of the host Medicago truncatula in four genome-wide association studies to study the genomic architecture of a key symbiotic extended phenotype - partner quality, or the fitness benefit conferred to a host by a particular symbiont genotype, within and across environmental contexts and host genotypes. We define three novel categories of loci in rhizobium genomes that must be accounted for if we want to build a reliable G[->]P map of partner quality; namely, 1) loci whose identities depend on the environment, 2) those that depend on the host genotype with which rhizobia interact, and 3) universal loci that are likely important in all or most environments. IMPORTANCEGiven the rapid rise of research on how microbiomes can be harnessed to improve host health, understanding the contribution of microbial genetic variation to host phenotypic variation is pressing, and will better enable us to predict the evolution of (and select more precisely for) symbiotic extended phenotypes that impact host health. We uncover extensive context-dependency in both the identity and functions of symbiont loci that control host growth, which makes predicting the genes and pathways important for determining symbiotic outcomes under different conditions more challenging. Despite this context-dependency, we also resolve a core set of universal loci that are likely important in all or most environments, and thus, serve as excellent targets both for genetic engineering and future coevolutionary studies of symbiosis.

evolutionary biology↗

bioRxiv2021

Positive Selection and Heat-Response Transcriptomes Reveal Adaptive Features of the Arabidopsis Desert Relative, Anastatica hierochuntica

O_LIPlant adaptation to a desert environment and its endemic heat stress is poorly understood at the molecular level. The naturally heat-tolerant Brassicaceae species Anastatica hierochuntica is an ideal extremophyte model to identify genetic adaptations that have evolved to allow plants to tolerate heat stress and thrive in deserts. C_LIO_LIWe generated an A. hierochuntica reference transcriptome and pinpointed extremophyte adaptations by comparing Arabidopsis thaliana and A. hierochuntica transcriptome responses to heat and identifying positively selected genes in A. hierochuntica. C_LIO_LIThe two species exhibit similar transcriptome adjustment in response to heat and the A. hierochuntica transcriptome does not exist in a constitutive heat "stress-ready" state. Furthermore, the A. hierochuntica global transcriptome as well as heat-responsive orthologs, display a lower basal and higher heat-induced expression than in A. thaliana. Genes positively selected in multiple extremophytes are associated with stomatal opening, nutrient acquisition, and UV-B induced DNA repair while those unique to A. hierochuntica are consistent with its photoperiod-insensitive, early-flowering phenotype. C_LIO_LIWe suggest that evolution of a flexible transcriptome confers the ability to quickly react to extreme diurnal temperature fluctuations characteristic of a desert environment while positive selection of genes involved in stress tolerance and early flowering could facilitate an opportunistic desert lifestyle. C_LI

plant biology↗

bioRxiv2020

Sorghum bicolor cultivars have divergent and dynamic gene regulatory networks that control the temporal expression of genes in stem tissue

The genetic engineering of value-added traits such as the accumulation of bioproducts in high biomass C4 grass stems is one promising strategy to make plant-derived biofuels more economical for industrial use. A first step toward achieving this goal is to identify stem-specific promoters that can drive the expression of genes of interest with good temporal and spatial specificity. However, a comprehensive characterization of the spatial-temporal regulatory elements of stem tissue-specific promoters for C4 grasses has not been reported. Therefore, we performed an in-silico analysis on Sorghum bicolor cv BTx623 transcriptomes from multiple tissues over development to identify stem-expressed genes. The analysis identified 10 genes that are “Always-On-Stem-Specific,” 59 genes that are “Temporally-Stem-Specific during early development,” and 21 genes that are “Temporally-Stem-Specific during late development.” Promoter analysis revealed common and/or unique cis-regulatory elements in promoters of genes within each of the three categories. Subsequent gene regulatory network (GRN) analysis revealed that different transcriptional regulatory programs are responsible for the temporal activation of the stem-expressed genes. The analysis of temporal stem GRNs between sweet (cv Della) and grain (cv BTx623) sorghum varieties revealed genetic variation that could influence the regulatory landscape. This study provides new insights about sorghum stem biology, and information for future genetic engineering efforts to fine-tune the spatial-temporal expression of transgenes in C4 grass stems.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2020

Granger-Causal Testing for Irregularly Sampled Time Series with Application to Nitrogen Signaling in Arabidopsis

Motivation Identification of system-wide causal relationships can contribute to our understanding of long-distance, intercellular signaling in biological organisms. Dynamic transcriptome analysis holds great potential to uncover coordinated biological processes between organs. However, many existing dynamic transcriptome studies are characterized by sparse and often unevenly spaced time points that make the identification of causal relationships across organs analytically challenging. Application of existing statistical models, designed for regular time series with abundant time points, to sparse data may fail to reveal biologically significant, causal relationships. With increasing research interest in biological time series data, there is a need for new statistical methods that are able to determine causality within and between time series data sets. Here, a statistical framework was developed to identify (Granger) causal gene-gene relationships of unevenly spaced, multivariate time series data from two different tissues of Arabidopsis thaliana in response to a nitrogen signal.Results This work delivers a statistical approach for modelling irregularly sampled bivariate signals which embeds functions from the domain of engineering that allow to adapt the model’s dependence structure to the specific sampling time. Using Maximum-Likelihood to estimate the parameters of this model for each bivariate time series, it is then possible to use bootstrap procedures for small samples (or asymptotics for large samples) in order to test for Granger-Causality. When applied to the Arabidopsis thaliana data, the proposed approach produced 3,078 significant interactions, in which 2,012 interactions have root causal genes and 1,066 interactions have shoot causal genes. Many of the predicted causal and target genes are known players in local and long-distance nitrogen signaling, including genes encoding transcription factors, hormones, and signaling peptides. Of the 1,007 total causal genes (either organ), 384 are either known or predicted mobile transcripts, suggesting that the identified causal genes may be directly involved in long-distance nitrogen signaling through intercellular interactions. The model predictions and subsequent network analysis identified nitrogen-responsive genes that can be further tested for their specific roles in long-distance nitrogen signaling.Availability The method was developed with the R statistical software and is made available thorugh the R package “irg” hosted on the GitHub repository https://github.com/SMAC-Group/irg. A sample data set is made available as an example to apply the method and the complete Arabidopsis thaliana data can be found at: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE97500.Contact amymc{at}illinois.eduCompeting Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2019

WRKY1 mediates transcriptional crosstalk between light and nitrogen signaling pathways in Arabidopsis thaliana

Plant responses to multiple stimuli must be integrated to trigger transcriptional cascades that lead to changes in plant metabolism and development. Light (L) and nitrogen (N) are two signaling pathways that are intimately connected to each other and to plant energy status. Here, we describe the functional role of the WRKY1 transcription factor in mediating the regulation between L and N signaling pathways in Arabidopsis thaliana. WRKY1 participates in genome-wide transcriptional reprogramming in leaves in response to individual and combined L and N signals. A regulatory network was identified, consisting of 724 genes regulated by WRKY1 and involved in both N and L signaling pathways. The loss of WRKY1 gene function has marked effects on the L and N response of genes involved in N uptake and assimilation (primary metabolism) as well as stress response pathways (secondary metabolism). Our results support a model in which WRKY1 enables plants to activate genes involved in the recycling of cellular carbon resources when L is limiting but N is abundant, and up-regulate amino acid metabolism genes when both L and N are limiting. In this potential energy conservation mechanism, WRKY1 integrates responses to N and light-energy status to trigger changes in plant metabolism.\n\nSummaryBased on transcriptome analysis, the WRKY1 transcription factor mediates regulation of nitrogen and light signaling pathways in a potential energy conservation mechanism.

plant biology↗

bioRxiv2019

Combining gene network, metabolic, and leaf-level models show means to future-proof soybean photosynthesis under rising CO2.

Global population increase coupled with rising urbanization underlies the predicted need for 60% more food by 2050, but produced on the same amount of land as today. Improving photosynthetic efficiency is a largely untapped approach to addressing this problem. Here, we scale modeling processes from gene expression through photosynthetic metabolism to predict leaf physiology in evaluating acclimation of photosynthesis to rising [CO2]. Model integration with the yggdrasil interface enabled asynchronous message passing between models. The multiscale model of soybean photosynthesis calibrated to physiological measures at ambient [CO2] successfully predicted the acclimatory changes in the photosynthetic apparatus that were observed at 550 ppm [CO2] in the field. We hypothesized that genetic alteration is necessary to achieve optimal photosynthetic efficiency under global change. Flux control analysis in the metabolic system under elevated [CO2] identified enzymes requiring the greatest change to adapt optimally to the new conditions. This predicted that Rubisco was less limiting under elevated [CO2] and should be down-regulated allowing re-allocation of resource to enzymes controlling the rate of regeneration of ribulose-1:5 bisphosphate (RubP). By linking the GRN through protein concentration to the metabolic model it was possible to identify transcription factors (TF) that matched the up- and down-regulation of genes needed to improve photosynthesis. Most striking was TF GmGATA2, which down-regulated genes for Rubisco synthesis while up-regulating key genes controlling RubP regeneration and starch synthesis. The changes predicted for this TF most closely matched the physiological ideotype that the modeling predicted as optimal for the future elevated [CO2] world.

plant biology↗

bioRxiv2018

HRS1/HHOs GARP transcription factors and reactive oxygen species are regulators of Arabidopsis nitrogen starvation response.

Plants need to cope with strong variations in the nitrogen content of the soil solution. Although many molecular actors are being discovered concerning how plants perceive NO3- provision, it is less clear how plants recognize a lack of Nitrogen. Indeed, following N removal plants activate their Nitrogen Starvation Response (NSR) being characterized in particular by the activation of very high affinity nitrate transport systems (NRT2.4, NRT2.5) and other sentinel genes such as GDH3. Here we show using a combination of functional genomics (via TF perturbation) and molecular physiology studies, that the GARP Transcription Factors (TFs) belonging the HHO sub-family are important regulators of the NSR through two potential mechanisms. First, HHOs directly repress NRT2.4 and NRT2.5 high-affinity nitrate transporters. Genotypes affected in HHO genes (mutants and overexpressors) display modified high-affinity nitrate transport activities opening interesting perspectives in biotechnology applications. Second, we show that Reactive Oxygen Species (ROS) are important to control NSR in wild type plants and that HRS1 and HHO1 overexpressors are affected in their ROS content, defining a potential feedforward branch of the signaling pathway. Taken together our results define two new classes of molecular actors in the control of NSR including ROS and the first transcription factors to date. This work (i) opens perspectives on a poorly understood nutrient related signaling pathway, and (ii) defines targets for molecular breeding of plants with enhanced NO3- uptake.

plant biology↗