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The plant circadian clock coordinates developmental, physiological, and metabolic processes with diel changes in light and temperature throughout the year. The balance between the persistence and plasticity of the clock in response to predictable and unpredictable environmental changes may be key to the clock’s adaptive nature across temporal and spatial scales. Studies under controlled conditions have uncovered critical signaling pathways involved in light and temperature perception by the clock; however, they don’t account for the natural lag of temperature behind photoperiod. Studies in natural environments provide key insights into the clock’s adaptive advantage under more complex natural settings. Here, we discuss the role of the circadian clock in light and temperature perception and signaling, how the clock integrates these signals for a coordinated and adaptive response, and the adaptive advantage conferred by the clock across time and space in natural environments.

Transcriptome profiling of maize inbred and hybrid seedlings subjected to heat or cold stress was used to identify key cis-regulatory elements and develop models to predict gene expression responses., Changes in gene expression are important for responses to abiotic stress. Transcriptome profiling of heat- or cold-stressed maize genotypes identifies many changes in transcript abundance. We used comparisons of expression responses in multiple genotypes to identify alleles with variable responses to heat or cold stress and to distinguish examples of cis- or trans-regulatory variation for stress-responsive expression changes. We used motifs enriched near the transcription start sites (TSSs) for thermal stress-responsive genes to develop predictive models of gene expression responses. Prediction accuracies can be improved by focusing only on motifs within unmethylated regions near the TSS and vary for genes with different dynamic responses to stress. Models trained on expression responses in a single genotype and promoter sequences provided lower performance when applied to other genotypes but this could be improved by using models trained on data from all three genotypes tested. The analysis of genes with cis-regulatory variation provides evidence for structural variants that result in presence/absence of transcription factor binding sites in creating variable responses. This study provides insights into cis-regulatory motifs for heat- and cold-responsive gene expression and defines a framework for developing models to predict expression responses across multiple genotypes.

Environmental variation along an elevational gradient can yield phenotypic differentiation resulting from varying selection pressures on plant traits related to seasonal responses. Thus, genetic clines can evolve in a suite of traits, including the circadian clock, that drives daily cycling in varied traits and that shares its genetic background with adaptation to seasonality. We used populations of annual Mimulus laciniatus from different elevations in the Sierra Nevada in California to explore among-population differentiation in the circadian clock, flowering responses to photoperiod, and phenological traits (days to cotyledon emergence, days to flowering, and days to seed ripening) in controlled common-garden conditions. Further, we examined correlations of these traits with environmental variables related to temperature and precipitation. We observed that the circadian period in leaf movement was differentiated among populations sampled within about 100 km, with population means varying by 1.6 h. Significant local genetic variation occurred within 2 populations in which circadian period among families varied by up to 1.8 h. Replicated treatments with variable ecologically relevant photoperiods revealed marked population differentiation in critical day length for flowering that ranged from 11.0 to 14.1 h, corresponding to the time period between late February and mid-May in the wild. Flowering time varied among populations in a 14-h photoperiod. Regardless of this substantial population-level diversity, obvious linear clinality in trait variability across elevations could not be determined based on our genotypic sample; it is possible that more complex spatial patterns of variation arise in complex terrains such as those in the Sierra Nevada. Moreover, we did not find statistically significant bivariate correlations between population means of different traits. Our research contributes to the understanding of genetic variation in the circadian clock and in seasonal responses in natural populations, highlighting the need for more comprehensive investigations on the association between the clock and other adaptive traits in plants.

As sessile organisms, plants are finely tuned to respond dynamically to developmental, circadian, and environmental cues. Genome-wide studies investigating these types of cues have uncovered the intrinsically different ways they can impact gene expression over time. Recent advances in single cell sequencing and time-based bioinformatic algorithms are now beginning to reveal the dynamics of these time-based responses within individual cells and plant tissues. Here, we review what these techniques have revealed about the spatiotemporal nature of gene regulation, paying particular attention to the three distinct ways in which plant tissues are time sensitive. (i) First, we discuss how studying plant cell identity can reveal developmental trajectories hidden in pseudotime. (ii) Next, we present evidence which indicates that plant cell types keep their own local time through tissue specific regulation of the circadian clock. (iii) Finally, we review what determines the speed of environmental signaling responses, and how they can be contingent on developmental and circadian time. By these means, this review sheds light on how these different scales of time-based responses can act with tissue and cell-type specificity to elicit changes in whole plant systems.

Motivation Clustering spatial-resolved gene expression is an essential analysis to reveal gene activities in the underlying morphological context by their functional roles. However, conventional clustering analysis does not consider gene expression co-localizations in tissue for detecting spatial expression patterns or functional relationships among the genes for biological interpretation in the spatial context. In this article, we present a convolutional neural network (CNN) regularized by the graph of protein–protein interaction (PPI) network to cluster spatially resolved gene expression. This method improves the coherence of spatial patterns and provides biological interpretation of the gene clusters in the spatial context by exploiting the spatial localization by convolution and gene functional relationships by graph-Laplacian regularization. Results In this study, we tested clustering the spatially variable genes or all expressed genes in the transcriptome in 22 Visium spatial transcriptomics datasets of different tissue sections publicly available from 10× Genomics and spatialLIBD. The results demonstrate that the PPI-regularized CNN constantly detects gene clusters with coherent spatial patterns and significantly enriched by gene functions with the state-of-the-art performance. Additional case studies on mouse kidney tissue and human breast cancer tissue suggest that the PPI-regularized CNN also detects spatially co-expressed genes to define the corresponding morphological context in the tissue with valuable insights. Availability and implementation Source code is available at https://github.com/kuanglab/CNN-PReg. Supplementary information Supplementary data are available at Bioinformatics online.

Changes in gene expression are important for response to abiotic stress. Transcriptome profiling performed on maize inbred and hybrid genotypes subjected to heat or cold stress identifies many transcript abundance changes in response to these environmental conditions. Motifs that are enriched near differentially expressed genes were used to develop machine learning models to predict gene expression responses to heat or cold. The best performing models utilize the sequences both upstream and downstream of the transcription start site. Prediction accuracies could be improved using models developed for specific co-expression clusters compared to using all up- or down-regulated genes or by only using motifs within unmethylated regions. Comparisons of expression responses in multiple genotypes were used to identify genes with variable response and to identifycis-ortrans-regulatory variation. Models trained on B73 data have lower performance when applied to Mo17 or W22, this could be improved by using models trained on data from all genotypes. However, the models have low accuracy for correctly predicting genes with variable responses to abiotic stress. This study provides insights intocis-regulatory motifs for heat- and cold-responsive gene expression and provides a framework for developing models to predict expression response to abiotic stress across multiple genotypes.One sentence summaryTranscriptome profiling of maize inbred and hybrid seedlings subjected to heat or cold stress was used to identify key cis-regulatory elements and develop models to predict gene expression responses.

The globally important crop Brassica rapa, a close relative of Arabidopsis, is an excellent system for modeling our current knowledge of plant growth on a morphologically diverse crop. The long history of B. rapa domestication across Asia and Europe provides a unique collection of locally adapted varieties that span large climatic regions with various abiotic and biotic stress tolerance traits. This diverse gene pool provides a rich source of targets with the potential for manipulation towards the enhancement of productivity of crops both within and outside the Brassicaceae. To expand the genetic resources available to study natural variation in B. rapa, we constructed an Advanced Intercross Recombinant Inbred (AI-RIL) population using B. rapa subsp. trilocularis (Yellow Sarson) R500 and the B. rapa subsp. parachinensis (Cai Xin) variety L58. Our current understanding of genomic structure variation across crops suggests that a single reference genome is insufficient for capturing the genetic diversity within a species. To complement this AI-RIL population and current and future B. rapa genomic resources, we generated a de novo genome assembly of the B. rapa subsp. trilocularis (Yellow Sarson) variety R500, the maternal parent of the AI-RIL population. The genetic map for the R500 x L58 population generated using this de novo genome was used to map QTL for seed coat color and revealed the improved mapping resolution afforded by this new assembly.

Throughout plant evolution the circadian clock has expanded into a complex signaling network, coordinating physiological and metabolic processes with the environment. Early land plants faced new environmental pressures that required energy-demanding stress responses. Integrating abiotic stress response into the circadian system provides control over daily energy expenditure. Here, we describe the evolution of the circadian clock in plants and the limited, yet compelling, evidence for conserved regulation of abiotic stress. The need to introduce abiotic stress tolerance into current crops has expanded research into wild accessions and revealed extensive variation in circadian clock parameters across monocot and eudicot species. We argue that research into the ancestral links between the clock and abiotic stress will benefit crop improvement efforts.

Environmental variation along an elevational gradient can yield phenotypic differentiation resulting from varying selection pressures on plant traits related to seasonal responses. Thus, genetic clines can evolve in a suite of traits, including the circadian clock, that drives daily cycling in varied traits and that shares its genetic background with adaptation to seasonality. We used populations of annual Mimulus laciniatus from different elevations in the Sierra Nevada in California to explore among-population differentiation in the circadian clock, flowering responses to photoperiod, and phenological traits (days to cotyledon emergence, days to flowering, and days to seed ripening) in controlled common-garden conditions. Further, we examined correlations of these traits with environmental variables related to temperature and precipitation. We observed that the circadian period in leaf movement was differentiated among populations sampled within about 100 km, with population means varying by 1.6 h. Significant local genetic variation occurred within 2 populations in which circadian period among families varied by up to 1.8 h. Replicated treatments with variable ecologically relevant photoperiods revealed marked population differentiation in critical day length for flowering that ranged from 11.0 to 14.1 h, corresponding to the time period between late February and mid-May in the wild. Flowering time varied among populations in a 14-h photoperiod. Regardless of this substantial population-level diversity, obvious linear clinality in trait variability across elevations could not be determined based on our genotypic sample; it is possible that more complex spatial patterns of variation arise in complex terrains such as those in the Sierra Nevada. Moreover, we did not find statistically significant bivariate correlations between population means of different traits. Our research contributes to the understanding of genetic variation in the circadian clock and in seasonal responses in natural populations, highlighting the need for more comprehensive investigations on the association between the clock and other adaptive traits in plants.

The increasing availability of -omics data is driving the development of computational methods for integrating these datasets to connect the underlying molecular mechanisms to phenotypes. Building gene regulatory networks (GRNs) from transcriptomic studies often results in a static view of gene expression, which can make it difficult to disentangle pathway structure. Increasing the temporal resolution of any experimental design provides the opportunity to model the dynamic nature of a regulatory pathway response to a stimulus. Many transient intermediate states can separate the initial prestimulus state from the final poststimulus state; time-series analyses permit the detection and integration of these intermediate steps into the pathway. The difficulty is to incorporate these time-dependent changes to determine causal relationships within the GRN, such as which transcription factor (TF) regulates which target genes. In PNAS, Varala et al. (1) address this challenge by integrating time into their GRN to unravel the temporal cascade of nitrogen signaling. Their time-based analysis offers a potent and general approach to uncover the temporal transcriptional logic for any plant or animal response system. Nitrogen (N) commonly limits plant production and the widespread application of mineral N fertilizer has greatly increased crop yields (2). Unfortunately, the production of mineral N fertilizer is expensive in terms of fossil energy. Furthermore, plant assimilation of applied N is inefficient; for example, cereals such as maize, rice, and wheat take up less than 40% of the applied N (3). The remaining N is lost to the environment through processes including denitrification and volatilization, releasing greenhouse gases, leaching, contaminating groundwater, and surface runoff, causing eutrophication of fresh and estuarine waters (4). Therefore, the excessive use of N fertilizer both increases the cost of crop production and causes environmental pollution. One might expect that, consequently, plant N use efficiency (NUE) would represent a major target for … [↵][1]1To whom correspondence should be addressed. Email: c.robertson.mcclung{at}Dartmouth.edu. [1]: #xref-corresp-1-1

The TIR1/AFB auxin co-receptors mediate diverse responses to the plant hormone auxin. The Arabidopsis genome encodes six TIR1/AFB proteins representing three of the four clades that were established prior to angiosperm radiation. To determine the role of these proteins in plant development we performed an extensive genetic analysis involving the generation and characterization of all possible multiply mutant lines. We find that loss of all six TIR1/AFB proteins results in defects in embryogenesis as early as the 8-cell stage, and possibly earlier. Mutant embryos progress but exhibit frequent cell division errors followed by proliferation of the suspensor, and eventually seed abortion. Despite this dramatic phenotype, a single wild-type allele ofTIR1orAFB2is sufficient to support growth throughout plant development. Further, gametophytic expression of theTIR1/AFBgenes is not essential for development of the male or female gametophyte. Our analysis reveals extensive functional overlap between even the most distantly relatedTIR1/AFBgenes except forAFB1. Surprisingly, the AFB1 protein has a specialized function in rapid auxin-dependent inhibition of root growth and early phase of root gravitropism. This activity may be related to a difference in subcellular localization compared to the other members of the family.

Circadian clocks have evolved independently in all three domains of life, and fitness benefits of a functional clock have been demonstrated in experimental genotypes in controlled conditions. Still, little is known about genetic variation in the clock and its fitness consequences in natural populations from heterogeneous environments. Using Wyoming populations of the Arabidopsis relative Boechera stricta as our study system, we demonstrate that genetic variation in the clock can occur at multiple levels: means of circadian period among populations sampled at different elevations differed by less than 1 h, but means among families sampled within populations varied by as much as 3.5 h. Growth traits also varied among and within populations. Within the population with the most circadian variation, we observed evidence for a positive correlation between period and growth and a negative correlation between period and root-to-shoot ratio. We then tested whether performance tradeoffs existed among families of this population across simulated seasonal settings. Growth rankings of families were similar across seasonal environments, but for root-to-shoot ratio, genotype × environment interactions contributed significantly to total variation. Therefore, further experiments are needed to identify evolutionary mechanisms that preserve substantial quantitative genetic diversity in the clock in this and other species.

Several factors affect the yield potential and geographical range of crops including the circadian clock, water availability, and seasonal temperature changes. In order to sustain and increase plant productivity on marginal land in the face of both biotic and abiotic stresses, we need to more efficiently generate stress-resistant crops through marker-assisted breeding, genetic modification, and new genome-editing technologies. To leverage these strategies for producing the next generation of crops, future transcriptomic data acquisition should be pursued with an appropriate temporal design and analyzed with a network-centric approach. The following review focuses on recent developments in abiotic stress transcriptional networks in economically important crops and will highlight the utility of correlation-based network analysis and applications.

The dynamics of local climates make development of agricultural strategies challenging. Yield improvement has progressed slowly, especially in drought-prone regions where annual crop production suffers from episodic aridity. Underlying drought responses are circadian and diel control of gene expression that regulate daily variations in metabolic and physiological pathways. To identify transcriptomic changes that occur in the crop Brassica rapa during initial perception of drought, we applied a co-expression network approach to associate rhythmic gene expression changes with physiological responses. Coupled analysis of transcriptome and physiological parameters over a two-day time course in control and drought-stressed plants provided temporal resolution necessary for correlation of network modules with dynamic changes in stomatal conductance, photosynthetic rate, and photosystem II efficiency. This approach enabled the identification of drought-responsive genes based on their differential rhythmic expression profiles in well-watered versus droughted networks and provided new insights into the dynamic physiological changes that occur during drought., eLife digest Around 60% of the food produced worldwide relies entirely on rain for its water supply. However, in the decades ahead global climate change is predicted to cause droughts to happen more often and become more severe in many regions. Therefore, in order to sustain our food supply we need to better understand how plants respond to drought and then use that knowledge to improve the ability of crops to cope with it. Unlike animals, plants cannot move away from drought or other stressful situations so they must face these difficulties ‘head on’. For example, when water is in short supply, plants close pores known as stomata on the surface of their leaves to reduce water loss. However, these pores need to be open to allow carbon dioxide gas, which plants use to make sugars in a process called photosynthesis, to enter the plant. Their response to drought must therefore be carefully controlled to make sure that the plant is still capable of performing photosynthesis. Turnip, napa cabbage, bok choy and field mustard are all varieties of a crop species known as Brassica rapa. These crops are grown in relatively dry regions such as the Canadian prairies and northern China, making drought stress a major threat to production. Previous studies had shown that drought stress causes changes in the activities of genes at certain times of day. To investigate this further, Greenham, Guadagno et al. studied how young B. rapa plants grown in a controlled environment with a steady supply of water responded when watering stopped. The experiments show that, even before the plants show obvious signs of drought stress such as wilting, there are extensive changes in the activity of many genes and processes inside plant cells that vary according to the time of day. Greenham, Guadagno et al. used an analysis technique to bring together all of the data into a network based on similar patterns of changes over time. This identified groups of genes whose changes in activity match the timing of the observed changes in the opening and closing of stomata, photosynthesis and other processes. These represent very early responses to drought stress in the plant. This work emphasizes the importance of time of day on plant stress responses. Changes that occurred only in the morning could not have been detected by measurements taken in the afternoon, and vice versa. The next step is to find out which of the changes observed in this work are most important in making plants resistant to drought. In the future, these findings may help researchers to develop strategies that would improve drought resistance in crop plants.

The native auxin, indole-3-acetic acid (IAA), is a major regulator of plant growth and development. Its nonuniform distribution between cells and tissues underlies the spatiotemporal coordination of many developmental events and responses to environmental stimuli. The regulation of auxin gradients and the formation of auxin maxima/minima most likely involve the regulation of both metabolic and transport processes. In this article, we have demonstrated that 2-oxindole-3-acetic acid (oxIAA) is a major primary IAA catabolite formed in Arabidopsis thaliana root tissues. OxIAA had little biological activity and was formed rapidly and irreversibly in response to increases in auxin levels. We further showed that there is cell type-specific regulation of oxIAA levels in the Arabidopsis root apex. We propose that oxIAA is an important element in the regulation of output from auxin gradients and, therefore, in the regulation of auxin homeostasis and response mechanisms.

The increasing demand for improved agricultural production will require more efficient breeding for traits that maintain yield under heterogeneous environments. The internal circadian oscillator is essential for perceiving and coordinating environmental cues such as day length, temperature, and abiotic stress responses within physiological processes. To investigate the contribution of the circadian clock to local adaptability, we have analyzed circadian period by leaf movement in natural populations of Mimulus guttatus and domesticated cultivars of Glycine max. We detected consistent variation in circadian period along a latitudinal gradient in annual populations of the wild plant and the selectively bred crop, and this provides novel evidence of natural and artificial selection for circadian performance. These findings provide new support that the circadian clock acts as a central regulator of plant adaptability and further highlight the potential of applying circadian clock gene variation to marker-assisted breeding programs in crops.

The plant hormone auxin is perceived by a family of F-box proteins called the TIR1/AFBs. Phylogenetic studies reveal that these proteins fall into four clades in flowering plants called TIR1, AFB2, AFB4, and AFB6. Genetic studies indicate that members of the TIR1 and AFB2 groups act as positive regulators of auxin signaling by promoting the degradation of the Aux/IAA transcriptional repressors. In this report, we demonstrate that both AFB4 and AFB5 also function as auxin receptors based on in vitro assays. We also provide genetic evidence that AFB4 and AFB5 are targets of the picloram family of auxinic herbicides in addition to indole-3-acetic acid. In contrast to previous studies we find that null afb4 alleles do not exhibit obvious defects in seedling morphology or auxin hypersensitivity. We conclude that AFB4 and AFB5 act in a similar fashion to other members of the family but exhibit a distinct auxin specificity.

The plant hormone auxin is perceived by a family of F-box proteins called the TIR1/AFBs. Phylogenetic studies reveal that these proteins fall into four clades in flowering plants called TIR1, AFB2, AFB4, and AFB6 (Parry et al. 2009). Genetic studies indicate that members of the TIR1 and AFB2 groups act as positive regulators of auxin signaling by promoting the degradation of the Aux/IAA transcriptional repressors (Dharmasiri et al. 2005; Parry et al. 2009). In this report we demonstrate that both AFB4 and AFB5 also function as auxin receptors based on in vitro assays. We also provide genetic evidence that both AFB4 and AFB5 are targets of the picloram family of auxinic herbicides. In contrast to previous studies we find that null afb4 alleles do not exhibit obvious defects in seedling morphology or auxin hypersensitivity. We conclude that AFB4 and AFB5 act in a similar fashion to other members of the family but exhibit a distinct auxin specificity.

Background A well characterized output of the circadian clock in plants is the daily rhythmic movement of leaves. This process has been used extensively in Arabidopsis to estimate circadian period in natural accessions as well as mutants with known defects in circadian clock function. Current methods for estimating circadian period by leaf movement involve manual steps throughout the analysis and are often limited to analyzing one leaf or cotyledon at a time. Results In this study, we describe the development of TRiP (Tracking Rhythms in Plants), a new method for estimating circadian period using a motion estimation algorithm that can be applied to whole plant images. To validate this new method, we apply TRiP to a Recombinant Inbred Line (RIL) population in Arabidopsis using our high-throughput imaging platform. We begin imaging at the cotyledon stage and image through the emergence of true leaves. TRiP successfully tracks the movement of cotyledons and leaves without the need to select individual leaves to be analyzed. Conclusions TRiP is a program for analyzing leaf movement by motion estimation that enables high-throughput analysis of large populations of plants. TRiP is also able to analyze plant species with diverse leaf morphologies. We have used TRiP to estimate period for 150 Arabidopsis RILs as well as 5 diverse plant species, highlighting the broad applicability of this new method. Electronic supplementary material The online version of this article (doi:10.1186/s13007-015-0075-5) contains supplementary material, which is available to authorized users.

Many processes critical to plant growth and development are regulated by the hormone auxin. Auxin responses are initiated through activation of a transcriptional response mediated by the TIR1/AFB family of F-box protein auxin receptors as well as the AUX/IAA and ARF families of transcriptional regulators. However, there is little information on how auxin regulates a specific cellular response. To begin to address this question, we have focused on auxin regulation of cell expansion in the Arabidopsis hypocotyl. We show that auxin-mediated hypocotyl elongation is dependent upon the TIR1/AFB family of auxin receptors and degradation of AUX/IAA repressors. We also use microarray studies of elongating hypocotyls to show that a number of growth-associated processes are activated by auxin including gibberellin biosynthesis, cell wall reorganization and biogenesis, and others. Our studies indicate that GA biosynthesis is required for normal response to auxin in the hypocotyl but that the overall transcriptional auxin output consists of PIF-dependent and -independent genes. We propose that auxin acts independently from and interdependently with PIF and GA pathways to regulate expression of growth-associated genes in cell expansion.

Nature Reviews Genetics 16, 598–610 (2015) In this article, the authors have updated Figure 1 by removing the repressive post-translational regulation arrow originally linking ZEITLUPE (ZTL) to the evening complex (EC), which is a multi-protein complex consisting of EARLY FLOWERING 4 (ELF4), ELF3 and LUX ARRHYTHMO (LUX).