How Light and Internal Clocks Work Together to Control Plant Growth and Stress Responses

Light serves as both an energy source and a key environmental signal, enabling plants to optimize their growth and survival. Photoreceptors, including phytochromes (red/far-red sensors), cryptochromes (blue/UV-A receptors), and UVR8 (UV-B sensor), decode light cues to regulate processes such as photomorphogenesis, shade avoidance, and photoperiodic flowering [8]. For example, in darkness, phytochromes suppress skotomorphogenesis by promoting the degradation of PIF transcription factors, while cryptochromes stabilize HY5, a master regulator of light-responsive genes [9]. Concurrently, internal processes are synchronized by the circadian clock—a self-sustaining molecular oscillator that generates ~24 h rhythms (e.g., stomatal movement, hormone synthesis) in alignment with external day–night cycles [10]. This temporal coordination enhances photosynthetic efficiency, as seen in the diurnal regulation of RBCS (RuBisCO small subunit) and starch metabolism. Together, light and circadian systems form a dynamic network that balances growth with stress resilience, ensuring adaptation to fluctuating environments [11,12].

The role of the circadian clock extends beyond timekeeping; it gates light sensitivity to optimize various plant responses. For example, Arabidopsis plants usually exhibit heightened light-induced gene expression during dawn and the clock primes photoreceptor signaling at this time [13]. Similarly, the circadian clock modulates thermomorphogenesis by controlling PIF4 levels through evening complex (EC)-mediated repression of its transcription and light-dependent inhibition of its activity via phyB-, DELLA-, and CRY1-mediated mechanisms, ensuring its accumulation aligns with the appropriate time of day [14]. Disruption of these networks, as seen in CCA1/LHY double mutants, leads to arrhythmic growth and reduced fitness under field conditions. Such explorations in various studies have underscored the necessity of light–clock crosstalk for survival in natural ecosystems. Moreover these also influence agricultural settings, where predictable and unpredictable stressors co-exist [15], as illustrated in Figure 1, which provides a schematic overview of these interactions.

The integration of light and circadian signaling is evolutionarily ancient, with origins tracing back to early land plants. Bryophytes such as Marchantia polymorpha possess simplified versions of angiosperm photoreceptors and clock components, suggesting conserved mechanisms for terrestrial adaptation [16]. For instance, UV-B stress responses in Marchantia are mediated by UVR8, similar to Arabidopsis, while dehydration tolerance—a key trait for terrestrial colonization—is regulated by its circadian clock [17]. These systems are further diversified in gymnosperms; for example, pine PHYO retains far-red sensitivity, which is used to manage canopy shade—a feature lost in later-evolving angiosperms. These evolutionary innovations highlight how light–clock networks were co-opted to address terrestrial challenges, from UV radiation to competition for sunlight [18].

Both natural and artificial selective pressures have shaped light–clock interactions in crops, allowing adaptation to local climates. Rice (Oryza sativa), for example, exhibits unique alleles of Ghd7 (plant height, grain number, and heading date), a clock-associated gene that delays flowering under long days in temperate regions [19]. Mutations in ZmCCT—a homolog of Arabidopsis PRR7—cause tropical maize varieties to display reduced photoperiod sensitivity [20]. Such adaptations in tropical plants highlight the plasticity of light–clock networks and highlight their potential as targets for breeding crops with increased resistance to climate change [21]. These examples from both natural and artificial selection also highlight the inherent plasticity of light–clock networks, proving them to be invaluable targets for modern breeding programs aimed at enhancing crop resilience and adaptability.

This review provides a comprehensive synthesis of the molecular and physiological integration of light and circadian signaling pathways in plants, with a specific focus on their convergence within shared gene regulatory networks (GRNs). We systematically address three primary objectives that structure this analysis. First, we synthesize the current understanding of core molecular mechanisms, detailing how diverse photoreceptors—including phytochromes, cryptochromes, and UVR8—decode light quality, intensity, and duration and how the core circadian oscillator, comprising components such as CCA1, LHY, and TOC1, maintains temporal precision through interlocking feedback loops. A central focus is elucidating their bidirectional crosstalk, wherein light signals entrain the circadian clock, and reciprocally, the clock gates light sensitivity through mechanisms like temporal priming of photoreceptor activity and expression, ensuring internal physiology remains synchronized with external diurnal and seasonal cycles [22,23].

Second, we evaluate the functional outcomes of this integration in critical adaptive processes, including photomorphogenesis, photoperiodic flowering, and abiotic stress resilience. This involves examining how key integrator hubs, such as the evening complex (ELF3-ELF4-LUX) acting as a thermosensory node and HY5 coordinating flavonoid biosynthesis, translate convergent signals into optimized growth and defense strategies [24,25]. Finally, we critically assess the translational applications of this knowledge, exploring how emerging biotechnologies—from CRISPR screens and single-cell omics to synthetic biology circuits—enable the precise engineering of light–clock networks to develop climate-resilient crops and optimize agricultural productivity in both field and controlled environment systems [26,27]. By bridging fundamental molecular insights with applied agricultural challenges, this review aims to chart a course for harnessing plant chronobiology for sustainable food security. A comprehensive list of key genes discussed is provided in Supplementary Table S1.

In general, plants deploy a sophisticated array of photoreceptors to decode light signals across the electromagnetic spectrum, enabling specific responses to different environmental cues [32]. Photomorphogenesis is regulated through phytochromes (PHYA-PHYE), which are possibly red/far-red light sensors involved in shade avoidance and flowering [33]. As an example, two interconvertible forms of PHYB exist, viz., Pr (inactive form) and Pfr (active form). At the time of exposure to red light, PHYB translocates to the nucleus, where it interacts with phytochrome-interacting factors (PIFs) to suppress skotomorphogenesis and promote photomorphogenesis [34]. Recent structural studies reveal that PHYB-PIF binding induces conformational changes that inhibit PIF DNA-binding activity, a mechanism critical for the transition from skotomorphogenesis (growth in darkness) to photomorphogenesis (growth in light) [35]. Cryptochromes (CRY1/2), which are blue/UV-A receptors, regulate hypocotyl elongation and circadian entrainment. They can possibly do it through inhibiting the COP1/SPA ubiquitin ligase complex, thereby stabilizing HY5 and CO (CONSTANS) to activate light-responsive genes. CRYs also mediate temperature-dependent growth. For instance, CRY1-PIF4 interactions under warm conditions enhance thermomorphogenesis, illustrating the convergence of light and thermal signals in plant development [36].

Phototropins (PHOT1/PHOT2) and UVR8 expand light-sensing capabilities. Phototropins mediate phototropism and chloroplast positioning via blue-light-induced autophosphorylation, optimizing photosynthetic efficiency [37]. UVR8, a UV-B sensor, monomerizes upon UV-B exposure to interact with COP1, initiating stress acclimation and flavonoid biosynthesis [38]. Downstream hubs like HY5 (a bZIP transcription factor) integrate signals from multiple photoreceptors, activating genes such as chalcone synthase (CHS) and RBCS while stabilizing circadian outputs [39]. Conserved roles of these components across plant lineages are summarized in Table 1. The COP1/SPA E3 ubiquitin ligase complex acts as a central repressor of photomorphogenesis in darkness by targeting positive regulators for degradation [40]. Recent work highlights post-translational modifications, like PIF phosphorylation by CK2 kinase, as key regulators of signal specificity, ensuring context-appropriate responses to fluctuating light conditions.

The plant circadian clock is a cell-autonomous, endogenous oscillator that generates ~24 h rhythms, enabling the anticipation of daily and seasonal environmental changes [49]. Its core mechanism consists of multiple, interlocked transcriptional–translational feedback loops (TTFLs) that provide both robustness and flexibility [50]. The central loop involves the reciprocal regulation between morning-expressed MYB transcription factors (TFs), Circadian Clock Associated 1 (CCA1) and Late Elongated Hypocotyl (LHY), and the evening-expressed Pseudo-Response Regulator 1 (TOC1/PRR1) [22]. CCA1 and LHY proteins bind to the evening element (EE) in the TOC1 promoter to repress its transcription around dawn. As CCA1 and LHY levels decline throughout the day, TOC1 expression is derepressed, peaking in the evening [51]. TOC1 protein then feeds back to indirectly suppress CCA1 and LHY expression, completing the cycle.

Emerging studies reveal tissue-specific clock dynamics. Single-cell RNA-seq in Arabidopsis roots identified distinct circadian rhythms in cortical versus epidermal cells, suggesting localized regulatory networks [52]. Additionally, reveille 8 (RVE8), a clock-output gene, integrates auxin signaling with circadian rhythms to regulate hypocotyl growth, demonstrating how clock outputs interface with hormonal pathways [53]. These insights show the clock's adaptability, enabling plants to tailor circadian rhythms to ecological niches, a trait exploitable for crop improvement.

Light serves as the primary Zeitgeber (time-giving cue) for entraining the circadian clock to environmental cycles. Photoreceptors directly modulate core clock components to reset rhythmicity [54]. For instance, phytochromes (PHYA/PHYB) and cryptochromes (CRY1/CRY2) interact with EC proteins (ELF3, ELF4, LUX) to adjust clock phase under varying photoperiods [55]. Red light-activated PHYB destabilizes ELF3, shortening the circadian period under long days [56], while CRY1 stabilizes TOC1 in blue light, delaying evening-phase gene expression [57]. This photoreceptor–clock crosstalk ensures precise synchronization with dawn and dusk.

The clock also gates light sensitivity, creating temporal windows during which plants maximally respond to specific wavelengths—a mechanism termed gating [58]. For example, CCA1 expression peaks at dawn, priming the clock for PHYB-mediated red light signals, whereas TOC1 induction at dusk enhances CRY-dependent responses to blue light [59]. Such temporal partitioning prevents conflicting signals, such as moonlight disrupting photoperiodic flowering. Some reported studies in Arabidopsis have demonstrated disrupted gating, viz., in elf3 mutants, which highlights its ecological significance [60]. It usually leads to arrhythmic growth along with impaired shade avoidance, also highlighting its ecological significance. This integration ensures that light signals are interpreted within a temporal context, optimizing both energy use and stress resilience [61]. Molecular interactions and epigenetic regulation are detailed in Figure 2.

Reciprocal control over light signaling pathways is exerted via the circadian clock, fine-tuning photoreceptor activity and downstream transcriptional responses [62]. Clock components regulate photoreceptor gene expression; for example, PHYB and CRY1 transcripts oscillate diurnally, peaking at dawn and dusk, respectively [63]. These rhythms ensure photoreceptor availability aligns with anticipated light conditions. The clock also modulates light-responsive TFs: PIF4 expression is temporally regulated, peaking at dusk under warm temperatures, which avoids midday heat stress while enabling thermomorphogenesis [64]. Similarly, HY5 accumulation is possibly gated through the clock, restricting UV-B responses to midday when UV radiation is most intense [23].

Such clock and light signals usually integrate through specialized post-translational mechanisms. The F-box protein ZTL usually and specifically degrades TOC1 in a light-dependent manner, whereas CRY1 stabilizes ZTL in blue light. This possibly results in a feedback loop that couples clock stability with photoperiod [55]. Additionally clock-regulated kinases like CK2 phosphorylate PIFs, altering their DNA-binding affinity in a time-of-day-specific manner. As witnessed, PIF5 phosphorylation at dawn enhances its degradation via COP1, ultimately preventing premature shade avoidance [65]. Such regulation ensures that light responses are temporally constrained, preventing energy-intensive processes, including flavonoid synthesis, during the night.

Coordination of gene expression is achieved through light and circadian signals, which converge at shared transcriptional hubs. Core clock components such as CCA1 and LHY directly bind to the promoters of light-responsive genes such as PIF4 and HY5, integrating temporal and environmental cues [66]. In contrast, HY5 stabilizes PRR7 transcription, linking light quality to clock precision. The EC acts as a thermosensory hub, repressing PIF4 during nighttime. This repression is released under warm temperatures, enabling temperature–photoperiod synergy during growth regulation [67].

Epigenetic mechanisms underpin this crosstalk. Histone acetylation at HY5 promoters peaks at midday, coinciding with high HY5 activity under light, while clock-regulated histone methyltransferases (e.g., ATX1) suppress PIF expression at dawn [68]. Single-cell ATAC-seq studies reveal that chromatin accessibility at light–clock hubs, viz., PRR9, GI, varies rhythmically, creating permissive states for TF binding [69]. These hubs also mediate stress adaptation: drought-induced ABA signaling recruits HY5 to NCED3 (a key ABA biosynthesis gene), a process gated by the clock to restrict water loss in daylight hours. Such integration allows plants to prioritize competing demand—growth versus survival—based on environmental conditions [70].

Photomorphogenesis is jointly regulated by light and circadian signals, ensuring seedlings optimize growth during early development. PIFs promote skotomorphogenesis in darkness (etiolation), characterized by elongated hypocotyls and closed cotyledons [9]. When a plant is exposed to light, phytochromes translocate to the nucleus, triggering PIF degradation and activating HY5. This initiates photomorphogenesis, shortens hypocotyls, and expands chloroplasts [4]. The circadian clock gates this transition; HY5 expression peaks at dawn, coinciding with maximal light sensitivity, while PIFs oscillate inversely. Recent studies show that the clock component RVE8 directly activates PIF4 at dusk under shade conditions, enhancing hypocotyl elongation to outcompete neighbors [53]. This temporal regulation ensures shade avoidance responses are timed to minimize energy trade-offs with daytime photosynthesis. Agricultural applications leverage this crosstalk; modulating PIF expression in crops like tomato improves canopy architecture and yield under dense planting [73].

This precise temporal control prevents premature elongation during the night, conserving energy for vigorous photosynthetic development at dawn. Furthermore, the clock's regulation of auxin signaling pathways ensures that growth responses to variable light conditions are both rapid and appropriately phased, maximizing fitness in competitive environments [74]. Field trials with lnk1 mutants demonstrate improved shade tolerance, suggesting targets for breeding crops resilient to light competition in intercropping systems. Figure 3 visualizes diurnal hypocotyl elongation and stress metabolite rhythms.

Plants constantly face abiotic and biotic stresses such as drought, extreme temperatures, and pathogen attacks. Emerging evidence reveals that light and circadian regulatory networks are intricately linked with stress signaling pathways, enabling plants to anticipate and efficiently respond to adverse conditions [75]. For example, circadian gating modulates the timing and amplitude of stress-responsive genes, optimizing resource allocation during periods of environmental challenge. Photoreceptors such as phytochromes and cryptochromes have been shown to directly influence the expression of stress-related genes [76], while core clock components (e.g., CCA1, TOC1) interact with key stress regulators like DREB and ABF transcription factors. This integration ensures that stress responses are synchronized with daily and seasonal environmental fluctuations, enhancing plant survival and productivity [77]. Understanding these connections opens new avenues for engineering crops with improved resilience to multiple stressors in a changing climate.

Photoperiodic flowering, a hallmark of light–clock integration, ensures reproductive success by aligning flowering with favorable seasons. In long-day plants like Arabidopsis, the clock-regulated gene Constans (CO) accumulates at dusk under long days, activating Flowering Locus T (FT) to induce flowering [78]. The GIGANTEA (GI)-FKF1 complex degrades CO repressors (e.g., CDFs) in a blue-light-dependent manner, creating a photoperiodic "gate" for floral induction [79]. For example, in rice—a short-day crop—orthologs such as Heading Date 1 (Hd1) and Hd3a (an FT homolog) exhibit inverted regulatory logic, ultimately suppressing flowering under long days [80]. Moreover, CRISPR-edited Hd1 variants have enabled rice cultivation at non-native latitudes, addressing climate-driven shifts in growing seasons.

Temperature further modulates this pathway. Warm nights accelerate the clock, advancing CO expression in Arabidopsis, while chilling represses Hd1 in rice, delaying flowering [81]. The EC mediates this thermosensitivity; elf3 mutants fail to delay flowering under high temperatures, linking circadian thermoregulation to reproductive timing [82]. Such insights inform breeding for photoperiod-insensitive crops, critical for adapting to erratic seasonal patterns caused by global warming.

Light–clock crosstalk enhances abiotic stress resilience by timing stress responses to coincide with predictable environmental challenges. Drought-responsive genes like NCED3 (9-cis-epoxycarotenoid dioxygenase 3), involved in ABA biosynthesis, are gated by the clock to peak at midday when water loss is highest. HY5 binds the NCED3 promoter under high light, synergizing ABA production with stomatal closure [83]. Similarly, the clock regulates the expression of ion transporters such as Salt Overly Sensitive 1 (SOS1), confining salt stress responses to daylight hours to align with osmotic adjustment needs and photosynthetic activity [84]. This reliance on a functional clock means that its disruption can itself be a potent stressor. For instance, specific changes in the light–dark regime trigger severe jasmonic acid (JA)-dependent cell death in Arabidopsis plants with reduced cytokinin levels or defective clock function, particularly in mutants lacking proper CCA 1 and LHY activity [85].

This phenomenon, known as photoperiod stress, is characterized by reactive oxygen species (ROS) production, accumulation of JA and salicylic acid (SA), and the induction of pathogen-response genes, remarkably leading to enhanced immunity against subsequent biotic challenges [86]. Thermomorphogenesis is also under dual control; the EC represses PIF4 transcription at night [47], while PHYB and CRY1 inhibit PIF4 activity during the day, ensuring thermoresponsive growth is prioritized at dusk under warm conditions [4]. This prevents conflicting responses and optimizes resource allocation, as energy-intensive stress acclimation is coordinated with light availability for photosynthesis. Engineering ELF3 variants in wheat has improved yield stability under heat waves, demonstrating translational potential.

Diurnal metabolic rhythms, orchestrated by light–clock integration, optimize carbon fixation and resource allocation. The clock is reported to regulate starch synthesis genes like granule-bound starch synthase (GBSS) to peak at dusk. This ensures the starch reserves can last until dawn [87]. HY5 usually activates the phytoene synthase (PSY) gene during high-light periods, and it coordinates carotenoid production through photosynthetic activity [88]. Similarly, in tomato, silencing HY5 disrupts fruit carotenoid content, linking light quality with the nutritional quality [89].

Secondary metabolites, viz., flavonoids and glucosinolates, are reported to exhibit circadian accumulation to balance UV protection as well as herbivore defense [90]. UVR8 involves inducing flavonoid biosynthesis genes, viz., CHS, at midday, whereas the clock gates their expression to save the plant from nighttime resource depletion. Moreover, CRISPR-edited Arabidopsis lines with arrhythmic CHS exhibit increased oxidative damage when exposed to UV-B, highlighting the adaptive value of such regulation [91]. Such types of rhythms are harnessed for precision agriculture, viz., timing pesticide applications to coincide with peak defense metabolite production enhances efficacy.

The principles of light–clock integration are critically important for modern controlled environment agriculture (CEA), particularly in plant factories with artificial lighting (PFALs) and vertical farms where plants experience fundamentally different conditions than in natural environments. In these systems, plants are frequently exposed to non-24 h photoperiods, irregular light–dark cycles, and constant light—conditions that create a mismatch between the endogenous circadian clock and the external light environment, leading to a novel physiological challenge termed photoperiodic stress [85,86]. This stress is not merely an extension of traditional light signaling but represents a unique condition where the circadian system itself is disrupted, triggering a suite of adverse responses. Research has shown that such abnormal circadian regimes can induce jasmonic-acid-dependent cell death, particularly in genetically sensitive plants like those deficient in cytokinin, highlighting a crucial interaction between circadian disruption, hormone signaling, and viability [85]. Furthermore, photoperiodic stress elicits an oxidative-burst-like response characterized by increased apoplastic peroxidase activity and decreased catalase function, pointing to a significant redox imbalance [92]. Notably, the transcriptional response to this stress in Arabidopsis thaliana resembles that activated during pathogen infection, suggesting that plants perceive a severely misaligned circadian clock as a significant threat to cellular integrity, mobilizing defense-related pathways [93].

Understanding the molecular basis of photoperiodic stress is paramount for designing sustainable CEA systems. The evening complex components, particularly ELF3, emerge as critical mediators, as their function in gating light sensitivity and maintaining circadian phase is essential for interpreting non-canonical light cycles. The strategic manipulation of light delivery—through optimized LED spectra, intensity modulation, and photoperiod duration—can mitigate these stresses by better aligning artificial environments with the plant's innate rhythmicity [94,95]. Beyond environmental adjustments, there is significant potential in engineering crop varieties with enhanced resilience to circadian disruption. This could involve selecting or using gene-editing technologies to develop alleles of core clock genes that confer flexibility or robustness under the erratic light schedules common in PFALs. By integrating an understanding of photoperiodic stress into both environmental management and crop breeding strategies, we can enhance productivity and resource-use efficiency in CEA, ensuring its role in achieving food security for urban and non-arable regions without imposing unsustainable energetic costs.

Recent advances witnessed in system biology have been responsible for revolutionizing our ability to dissect light–clock regulatory networks through integrating multi-omics datasets. Several dynamic hubs have been identified through transcriptomic, proteomic, and metabolomic profiling under varying light and circadian conditions, e.g., PIF4 and HY5 which are found to coordinate growth and stress responses [98]. As a reference a reported study combining time-series RNA-seq with ChIP-seq data to map the diurnal binding patterns of PIF4 and ELF3 in Arabidopsis has revealed their antagonistic roles during thermomorphogenesis [99]. Some network modeling tools, like weighted gene co-expression analysis (WGCNA), have further uncovered modules that link clock genes with drought-responsive pathways, highlighting PRR7 as a hub in osmotic stress adaptation [100]. Machine learning algorithms trained on these multi-omics datasets can now predict gene functions with higher accuracies; a model forecasted novel clock-regulated miRNAs that fine-tune photoperiodic flowering in rice [101]. Such approaches have provided a holistic view of GRNs, ultimately enabling researchers to prioritize targets for crop-engineering-based improvements.

Single-cell and spatial omics technologies are resolving tissue-specific light–clock interactions. Single-cell RNA-seq in Arabidopsis roots revealed that endodermal cells exhibit stronger circadian rhythms than epidermal cells, with distinct light-responsive gene clusters [102]. Spatial transcriptomics in maize leaves showed that ZmCCA1 expression gradients correlate with photosynthetic efficiency across mesophyll layers, suggesting localized clock regulation of carbon fixation [103]. Coupled with CRISPR-based lineage tracing, these tools are uncovering how cell-type-specific GRNs optimize resource allocation. For instance, companion cells in phloem uniquely express HY5, coordinating systemic light signaling with root development [104]. Such insights are guiding precision breeding strategies to enhance sink–source relationships in crops.

CRISPR-Cas9 has become indispensable for validating light–clock gene functions and engineering climate-resilient traits. In Arabidopsis, multiplex editing of PIF4, PIF5, and HY5 demonstrated their redundant roles in shade avoidance, with triple mutants showing stunted growth under canopy shade [105]. Base editors have enabled precise nucleotide changes; a 2024 study introduced a heat-tolerant allele of ELF3 in wheat by converting a single cysteine to arginine, stabilizing the protein under high temperatures [106]. Prime editing further refined this approach, creating photoperiod-insensitive Ghd7 alleles in rice that flower earlier under long days, adapting to shifting growing seasons [107]. These tools are accelerating the translation of basic research into agronomic solutions.

CRISPR interference (CRISPRi) screening in tomato revealed that repressing SlPIF3 enhances fruit carotenoid content under low light, linking photoreceptor signaling to nutritional quality [26]. These studies highlight the potential of CRISPR not only for functional genomics but also for trait stacking—editing multiple genes, viz., PHYB, PRR7, to optimize growth and resilience [108]. Field trials of CRISPR-edited OsPRR37 rice in Southeast Asia demonstrated a 20% yield increase under erratic rainfall, underscoring the translational impact of these technologies. Figure 4 shows CRISPR editing workflows and field validation.

Recent technological breakthroughs are fundamentally transforming our capacity to decode the intricate spatiotemporal dynamics of light–clock networks at unprecedented resolution [109]. Single-cell omics approaches have emerged as particularly powerful tools, revealing tissue-specific circadian rhythms and light responses that were completely obscured in traditional bulk analyses. For instance, single-cell RNA sequencing in Arabidopsis roots has demonstrated strikingly distinct circadian regulation between epidermal and cortical cells, suggesting specialized physiological functions in different tissue layers that reflect their unique roles in the plant [110]. Similarly, spatial transcriptomics in maize leaves has revealed expression gradients of core clock genes like ZmCCA1 across mesophyll layers that correlate directly with photosynthetic efficiency, indicating localized clock regulation of carbon fixation processes. These technologies are uncovering how companion cells in the phloem uniquely express key integrators like HY5, coordinating systemic light signaling with root development [103]. The emerging picture is one of remarkable cellular specialization within light–clock networks, where different cell types maintain distinct but coordinated rhythmic programs, enabling plants to optimize resource allocation and environmental responses at a microscopic scale that was previously inaccessible to researchers [49].

CRISPR-based technologies have revolutionized both functional validation and targeted engineering of light–clock networks with extraordinary precision [111]. Beyond simple gene knockouts, advanced applications like multiplex editing have revealed genetic redundancies and interactions—as demonstrated when simultaneous editing of PIF4, IF5, and HY5 in Arabidopsis uncovered their cooperative roles in shade avoidance, with triple mutants showing dramatically stunted growth under canopy shade conditions [112]. The development of more sophisticated base editing and prime editing techniques now enables single-nucleotide precision, allowing researchers to create beneficial alleles without disrupting native gene structure [113], such as the conversion of a single cysteine to arginine in wheat ELF3 that stabilizes the protein under high-temperature stress. These approaches facilitate the targeted manipulation of key network hubs while minimizing pleiotropic effects that often plagued traditional breeding approaches [114]. Furthermore, CRISPR interference (CRISPRi) screens in crops like tomato have identified novel regulators, such as the discovery that repressing SIPIF3 enhances fruit carotenoid content under low light conditions, directly linking photoreceptor signaling to nutritional quality in agriculturally relevant contexts [115].

Artificial intelligence and machine learning algorithms are increasingly employed to integrate complex multi-omics datasets and predict emergent network behaviors that escape conventional analysis [116]. These computational approaches can identify subtle patterns across temporal dimensions, as demonstrated when models trained on time-series transcriptomic data successfully identified novel clock-regulated miRNAs in rice that fine-tune photoperiodic flowering [117]. More sophisticated neural networks have predicted optimal gene combinations for specific environments, such as GI-CO allelic combinations that maximize yield across varied daylengths, with subsequent validation in soybean confirming these computational predictions [118]. The true power of these approaches lies in their ability to model complex genotype–environment interactions by integrating diverse data types—from transcriptomic and proteomic profiles to environmental sensor data and field phenotyping metrics. Machine learning frameworks like weighted gene co-expression network analysis (WGCNA) have further uncovered functional modules that link clock genes with drought-responsive pathways, highlighting PRR7 as an unexpected hub in osmotic stress adaptation and suggesting novel targets for crop engineering that might not have been identified through conventional hypothesis-driven research alone [119].

Climate change is altering critical environmental parameters, including photoperiods, light quality, and temperature, disrupting the synchronization between plant GRNs and external conditions [120]. Shifts in daylength due to latitudinal temperature increases are decoupling photoperiodic cues from traditional growing seasons. For example, in temperate regions, earlier springs extend daylight exposure before crops like wheat are developmentally primed to flower, leading to mismatches in resource allocation and reduced grain yields [121]. Concurrently, urban light pollution, particularly blue-rich LED emissions, extends perceived daylength, suppressing melatonin synthesis in crops like tomato and delaying fruit ripening by disrupting circadian rhythms [122]. Increased UV-B radiation from stratospheric ozone depletion further exacerbates stress, activating UVR8-mediated flavonoid biosynthesis at the expense of growth, as observed in high-altitude quinoa cultivars [123].

Rising temperatures destabilize the circadian clock's thermosensory mechanisms. Warm nights accelerate clock speed, causing Arabidopsis to flower prematurely under non-inductive photoperiods [124]. In rice, elevated nighttime temperatures reduce grain quality by desynchronizing starch metabolism genes (e.g., GBSS) from their circadian expression peaks [125]. These disruptions highlight the vulnerability of light–clock networks to climate volatility, necessitating adaptive strategies to maintain productivity.

Targeting light–clock hubs offers a pathway to engineering climate resilience. CRISPR editing of PRR genes in barley has generated lines with expanded photoperiod flexibility, enabling cultivation at higher latitudes [126]. Natural variation in photoperiodic pathways is also being exploited; Ghd7 haplotypes from Chinese rice landraces, which confer long-day flowering inhibition, are now introgressed into tropical varieties to counteract premature flowering caused by warmer winters [127].

Most probably the field trials show the promise of these approaches in upcoming years. As an instance in maize, CRISPR-edited ZmCCT mutants, that have been found lacking photoperiod sensitivity, have already achieved stable yields across diverse latitudes in sub-Saharan Africa, addressing climate-driven seasonality [128]. Table 2 compiles key translational achievements in major crops. Moreover, overexpression of HY5 in soybean has been witnessed to enhance UV-B tolerance and flavonoid content without compromising growth. This trait is considered very important in fields which are exposed to increasing solar radiation [129]. Integrating multi-omics data with machine learning is accelerating gene discovery; a recently reported model has successfully predicted PIF4 as a key target for improving shade tolerance in densely planted rice paddies. This has been further validated by field phenotyping efficiently [130]. Such innovations may be able to highlight the potential of tailoring light–clock networks to mitigate climate impacts in the near future.

While translating research achievement into agricultural practices it is required to have interdisciplinary collaborations along with policy support. It has been witnessed that public–private partnerships are significantly advancing CRISPR-edited crops through regulatory frameworks, as we have seen the approval of photoperiod-insensitive OsPRR37 rice [142]. Moreover, various digital agriculture tools including IoT-enabled smart greenhouses have been using real-time light and temperature data. This will help in the adjustment of circadian-aligned LED spectra, optimizing tomato growth under erratic climates [143]. Policy initiatives such as the EU's "Farm2Fork" strategy can now prioritize circadian-informed cropping systems for the reduced agrochemical use, leveraging natural pest resistance peaks timed to circadian gating.

Despite significant progress, fundamental questions regarding the spatiotemporal dynamics and evolutionary plasticity of light–clock networks remain unresolved. A primary challenge is explaining tissue- and cell-type-specific GRNs. While core mechanisms are well-characterized in model species like Arabidopsis, how these networks operate across different tissues such as the distinct circadian rhythms observed in root endodermis versus epidermis is poorly understood [144]. The role of non-coding RNAs (like miRNAs and lncRNAs) in controlling the link between light and the clock is becoming an important topic. For example, recent studies suggest that miR172 and miR156 show daily rhythms and control flowering time by targeting the clock genes TOC1 and GI, but their complete roles are still not known [145].

Another major gap lies in understanding the evolutionary dynamics of these networks. While core components are conserved, their functional interactions have diversified across lineages. For example, the ELF3 gene has acquired novel roles in thermosensing in eudicots, while in monocots like barley, ELF3 orthologs primarily regulate photoperiodic flowering [60]. Decoding how these evolutionary innovations arose through gene duplication, neofunctionalization, or changes in protein–protein interactions will provide insights into the adaptive potential of crops [146]. Additionally, the integration of novel photoreceptors from algae or bacteria into plant circadian systems, an area of synthetic biology, could reveal fundamental principles of network evolution and create new opportunities for engineering.

Translating mechanistic information from controlled laboratory environments to unpredictable field conditions presents a formidable challenge. Genotype-by-environment (GxE) interactions often mask the benefits of engineered traits; for example, a CRY1 overexpression allele that enhances yield in one maize hybrid may reduce it in another due to epistatic interactions. Furthermore, climate change introduces compounding stressors (e.g., drought + heat + high light) that may disrupt synergies within light–clock networks, leading to unexpected phenotypes. Overcoming these barriers requires a more complete understanding of how environmental cues are integrated at the whole-plant level.

It is obvious that future progress mainly hinges through integrating molecular biology, ecology, and data-driven sciences. With the help of artificial intelligence (AI) optimal light–clock gene combinations could be predicted, keeping in view the target environments [147]. Recently, a neural network has been reported to be trained on Arabidopsis accessions that has successfully predicted GI-CO allelic combinations assumed to maximize yield through varied daylengths and validated in tomato field trials [148]. Similarly, synthetic biology tools like optogenetically controlled TOC1 circuits have the potential to enable real-time clock adjustments in response to satellite weather forecasts. It is assumed that this system will ultimately be used in optimizing growth in precision agriculture paradigms [149].

Collaborative efforts are essential and the Climate-Resilient Crops Consortium (CRCC), a global initiative, unites plant biologists, climatologists, and farmers to test circadian-informed breeding strategies across 50+ crop species. Such partnerships should be expanded to include policymakers and indigenous communities that could ensure solutions that are equitable and context-specific.

The integration of multi-omics data with sophisticated computational modeling represents a critical frontier for deciphering the complex, dynamic interactions between light, circadian rhythms, and stress responses [73]. While transcriptomic studies have successfully mapped rhythmic gene expression, it is increasingly clear that a comprehensive understanding requires moving beyond a single omics layer. Proteomic and metabolomic analyses consistently reveal that the rhythms of proteins and metabolites often deviate from their corresponding mRNA patterns, highlighting the significant roles of post-translational modifications, protein turnover, and metabolic feedback loops in shaping the final physiological output [150]. This multi-layered regulation creates a complex system where transcriptional changes are merely the first step in a cascade of events. To accurately capture this regulatory hierarchy, advanced computational frameworks are essential. These frameworks must integrate high-resolution time-series data from transcriptomics, proteomics, and metabolomics to reconstruct dynamic network models that more accurately represent the flow of information from gene to phenotype, moving from correlation to causation in our understanding of how environmental signals are processed and translated into adaptive growth and resilience strategies [151].

These integrative models are already yielding profound insights. For instance, models that combine protein–protein interaction networks with transcriptomic data have elucidated how light-induced phosphorylation dictates the activity of PIF transcription factors, a key regulatory event that occurs independently of transcriptional changes [152]. Similarly, the integration of metabolomic flux data with transcriptional networks has clarified how the circadian clock gates the expression of flavonoid biosynthesis genes, ensuring UV-B protective compounds are synthesized precisely when needed while avoiding costly metabolic investments during the night [153]. Emerging machine learning approaches, such as weighted gene co-expression network analysis applied to multi-omics datasets, are now identifying previously unknown hub genes that connect circadian timing with drought-responsive pathways [154]. The power of single-cell omics further refines this picture by revealing how these integrated networks operate with distinct dynamics in different cell types, such as the unique circadian rhythms observed in the root endodermis compared to the epidermis, suggesting a level of specialized functional organization that was previously invisible to bulk analysis [155].

Looking forward, the field must prioritize the development of multi-scale models that can span from molecular interactions to whole-plant physiology and performance in the field. The ultimate challenge and goal are to create in silico predictive models that can forecast how genetic perturbations—such as CRISPR edits to PRR7 or ELF3—will influence crop resilience under specific, fluctuating environmental conditions, such as heatwaves combined with altered photoperiods. This ambitious endeavor requires not only the integration of diverse omics data but also the incorporation of environmental sensor data, high-throughput field phenotyping, and detailed information on soil and microclimate. Such a holistic, systems-level approach is indispensable for transforming our mechanistic insights into robust, predictive knowledge.