Global analysis of gene expression in maize leaves treated with low temperature. II. Combined effect of severe cold (8 °C) and circadian rhythm

The Roles of Circadian Clock Genes in Plant Temperature Stress Responses

Plants monitor day length and memorize changes in temperature signals throughout the day, creating circadian rhythms that support the timely control of physiological and metabolic processes. The DEHYDRATION-RESPONSE ELEMENT-BINDING PROTEIN 1/C-REPEAT BINDING FACTOR (DREB1/CBF) transcription factors are known as master regulators for the acquisition of cold stress tolerance, whereas PHYTOCHROME INTERACTING FACTOR 4 (PIF4) is involved in plant adaptation to heat stress through thermomorphogenesis. Recent studies have shown that circadian clock genes control plant responses to temperature. Temperature-responsive transcriptomes show a diurnal cycle and peak expression levels at specific times of throughout the day. Circadian clock genes play essential roles in allowing plants to maintain homeostasis by accommodating temperature changes within the normal temperature range or by altering protein properties and morphogenesis at the cellular level for plant survival and growth under temperature stress conditions. Recent studies revealed that the central oscillator genes CIRCADIAN CLOCK ASSOCIATED 1/LATE ELONGATED HYPOCOTYL (CCA1/LHY) and PSEUDO-RESPONSE REGULATOR5/7/9 (PRR5/7/9), as well as the EVENING COMPLEX (EC) genes REVEILLE4/REVEILLE8 (REV4/REV8), were involved in the DREB1 pathway of the cold signaling transcription factor and regulated the thermomorphogenesis gene PIF4. Further studies showed that another central oscillator, TIMING OF CAB EXPRESSION 1 (TOC1), and the regulatory protein ZEITLUPE (ZTL) are also involved. These studies led to attempts to utilize circadian clock genes for the acquisition of temperature-stress resistance in crops. In this review, we highlight circadian rhythm regulation and the clock genes involved in plant responses to temperature changes, as well as strategies for plant survival in a rapidly changing global climate.

Genomic-regions associated with cold stress tolerance in Asia-adapted tropical maize germplasm

Maize is gaining impetus in non-traditional and non-conventional seasons such as off-season, primarily due to higher demand and economic returns. Maize varieties directed for growing in the winter season of South Asia must have cold resilience as an important trait due to the low prevailing temperatures and frequent cold snaps observed during this season in most parts of the lowland tropics of Asia. The current study involved screening of a panel of advanced tropically adapted maize lines to cold stress during vegetative and flowering stage under field conditions. A suite of significant genomic loci (28) associated with grain yield along and agronomic traits such as flowering (15) and plant height (6) under cold stress environments. The haplotype regression revealed 6 significant haplotype blocks for grain yield under cold stress across the test environments. Haplotype blocks particularly on chromosomes 5 (bin5.07), 6 (bin6.02), and 9 (9.03) co-located to regions/bins that have been identified to contain candidate genes involved in membrane transport system that would provide essential tolerance to the plant. The regions on chromosome 1 (bin1.04), 2 (bin 2.07), 3 (bin 3.05-3.06), 5 (bin5.03), 8 (bin8.05-8.06) also harboured significant SNPs for the other agronomic traits. In addition, the study also looked at the plausibility of identifying tropically adapted maize lines from the working germplasm with cold resilience across growth stages and identified four lines that could be used as breeding starts in the tropical maize breeding pipelines.

Contrasting transcriptomic patterns reveal a genomic basis for drought resilience in the relict fir Abies pinsapo Boiss

Climate change challenges the adaptive capacity of several forest tree species in the face of increasing drought and rising temperatures. Therefore, understanding the mechanistic connections between genetic diversity and drought resilience is highly valuable for conserving drought-sensitive forests. Nonetheless, the post-drought recovery in trees from a transcriptomic perspective has not yet been studied by comparing contrasting phenotypes. Here, experimental drought treatments, gas-exchange dynamics and transcriptomic analysis (RNA-seq) were performed in the relict and drought-sensitive fir Abies pinsapo Boiss. to identify gene expression differences over immediate (24 h) and extended drought (20 days). Post-drought responses were investigated to define resilient and sensitive phenotypes. Single nucleotide polymorphisms (SNPs) were also studied to characterize the genomic basis of A. pinsapo drought resilience. Weighted gene co-expression network analysis showed an activation of stomatal closing and an inhibition of plant growth-related genes during the immediate drought, consistent with an isohydric dynamic. During the extended drought, transcription factors, as well as cellular damage and homeostasis protection-related genes prevailed. Resilient individuals activate photosynthesis-related genes and inhibit aerial growth-related genes, suggesting a shifting shoot/root biomass allocation to improve water uptake and whole-plant carbon balance. About, 152 fixed SNPs were found between resilient and sensitive seedlings, which were mostly located in RNA-activity-related genes, including epigenetic regulation. Contrasting gene expression and SNPs were found between different post-drought resilience phenotypes for the first time in a forest tree, suggesting a transcriptomic and genomic basis for drought resilience. The obtained drought-related transcriptomic profile and drought-resilience candidate genes may guide conservation programs for this threatened tree species.

Physio-Biochemical Responses of Sweet Cherry Leaf to Natural Cold Conditions

Trees of the sweet cherry cultivar 'Grace Star' (Prunus avium L.) were exposed to low temperatures without frost for two consecutive nights under natural conditions 36 d after flowering, to study the effects on the physiological properties and metabolic status of leaves. The response was studied by measuring chlorophyll fluorescence and gas exchange parameters and by analyzing chloroplast pigments (i) immediately after exposure, (ii) 24 h and (iii) 48 h later. The first exposure at 2.4 (±0.2) °C and a minimum of 0.8 °C elicited more changes than the second exposure at 4.9 (±0.3) °C and a minimum of 2.4 °C. After the first exposure, the maximum quantum yield of PS II (Fv/Fm), effective quantum efficiency of PS II, net photosynthesis (P_N), stomatal conductance (g_s), transpiration, and intercellular CO₂ concentration were significantly lower, and after the second exposure, the content of chlorophyll b, total chlorophyll, β-carotene, and lutein were lower. The content of antheraxanthin and zeaxanthin was higher immediately after both exposures, and that of antheraxanthin was also higher 24 h later. Recovery took longer in trees that were exposed twice. Fv/Fm recovered within 48 h, but the de-epoxidation state of the xanthophyll cycle pool, P_N, and g_s did not reach the level of controls, indicating that the stress effect lasted several days which is probably sufficient to cause fruit drop and reduce yield.

Full-length transcriptome analysis of maize root tips reveals the molecular mechanism of cold stress during the seedling stage

BACKGROUND

As maize originated in tropical or subtropical zones, most maize germplasm is extremely sensitive to low temperatures during the seedling stage. Clarifying the molecular mechanism of cold acclimation would facilitate the breeding of cold tolerant maize varieties, which is one of the major sustainability factors for crop production. To meet this goal, we investigated two maize inbred lines with contrasting levels of cold tolerance at the seedling stage (IL85, a cold tolerant line; B73, a cold sensitive line), and performed full-length transcriptome sequencing on the root tips of seedlings before and after 24 h of cold treatment.

RESULTS

We identified 152,263 transcripts, including 20,993 novel transcripts, and determined per-transcript expression levels. A total of 1,475 transcripts were specifically up-regulated in the cold tolerant line IL85 under cold stress. GO enrichment analysis revealed that 25 transcripts were involved in reactive oxygen species (ROS) metabolic processes and 15 transcripts were related to the response to heat. Eight genes showed specific differential alternative splicing (DAS) in IL85 under cold stress, and were mainly involved in amine metabolism. A total of 1,111 lncRNAs were further identified, 62 of which were up-regulated in IL85 or B73 under cold stress, and their corresponding target genes were enriched in protein phosphorylation.

CONCLUSIONS

These results provide new insights into the molecular mechanism of cold acclimation during the seedling stage in maize, and will facilitate the development of cultivars with improved cold stress tolerance.

Can we improve the chilling tolerance of maize photosynthesis through breeding?

Chilling tolerance is necessary for crops to thrive in temperate regions where cold snaps and lower baseline temperatures place limits on life processes; this is particularly true for crops of tropical origin such as maize. Photosynthesis is often adversely affected by chilling stress, yet the maintenance of photosynthesis is essential for healthy growth and development, and most crucially for yield. In this review, we describe the physiological basis for enhancing chilling tolerance of photosynthesis in maize by examining nine key responses to chilling stress. We synthesize current knowledge of genetic variation for photosynthetic chilling tolerance in maize with respect to each of these traits and summarize the extent to which genetic mapping and candidate genes have been used to understand the genomic regions underpinning chilling tolerance. Finally, we provide perspectives on the future of breeding for photosynthetic chilling tolerance in maize. We advocate for holistic and high-throughput approaches to screen for chilling tolerance of photosynthesis in research and breeding programmes in order to develop resilient crops for the future.

Transcriptome Analysis of Near-Isogenic Lines Provides Novel Insights into Genes Associated with Seed Low-Temperature Germination Ability in Maize (Zea mays L.)

Maize originated from tropical regions and is extremely sensitive to low temperature during germination. Our previous work identified a major QTL, qp1ER1-1, for low temperature germination ability (LTGA) of maize. Here, we introgressed qp1ER1-1 from the tolerant line L220 into the sensitive line PH4CV to generate two near isogenic lines NIL^220-3 and NIL^220-25. When germinated under cold temperature for 25 days (Cold-25), the NILs showed similar seedling root length and shoot length to L220, but significantly higher than PH4CV. However, when germinated under cold temperature for 15 days (Cold-15) or under normal temperature (25 °C) for 3 days (CK-3), all lines showed similar seedling performance, indicating that introgression of qp1ER1-1 from L220 into PH4CV could improve LTGA of NIL^220-3 and NIL^220-25. The whole seedlings, including root and shoot, of Cold-15 and CK-3 were harvested for transcriptome analysis, when both stayed at a similar developmental stage. Dry seed embryo was sequenced as a non-germination control (CK-0). Compared with PH4CV, the tolerant line (L220, NIL^220-3, and NIL^220-25) specifically expressed genes (different expressed genes, DEGs) were identified for CK-0, Cold-15, and CK-3. Then, DEGs identified from Cold-15, but not from CK-0 or CK-3, were defined as tolerant line specifically expressed LTGA genes. Finally, 1786, 174, and 133 DEGs were identified as L220, NIL^220-3, and NIL^220-25 specifically expressed LTGA genes, respectively. Of them, 27 were common LTGA genes that could be identified from all three tolerant lines, with two (Zm00001d031209 and Zm00001d031292) locating in the confidence interval of qp1ER1-1. In addition, GO analysis revealed that L220 specifically expressed LTGA genes were majorly enriched in the cell division process and plasma membrane related categories. Taken together, these results provided new insight into the molecular mechanism of maize seed LTGA and facilitated the cloning of the qp1ER1-1 gene.

EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture

Envirotyping is an essential technique used to unfold the nongenetic drivers associated with the phenotypic adaptation of living organisms. Here, we introduce the EnvRtype R package, a novel toolkit developed to interplay large-scale envirotyping data (enviromics) into quantitative genomics. To start a user-friendly envirotyping pipeline, this package offers: (1) remote sensing tools for collecting (get_weather and extract_GIS functions) and processing ecophysiological variables (processWTH function) from raw environmental data at single locations or worldwide; (2) environmental characterization by typing environments and profiling descriptors of environmental quality (env_typing function), in addition to gathering environmental covariables as quantitative descriptors for predictive purposes (W_matrix function); and (3) identification of environmental similarity that can be used as an enviromic-based kernel (env_typing function) in whole-genome prediction (GP), aimed at increasing ecophysiological knowledge in genomic best-unbiased predictions (GBLUP) and emulating reaction norm effects (get_kernel and kernel_model functions). We highlight literature mining concepts in fine-tuning envirotyping parameters for each plant species and target growing environments. We show that envirotyping for predictive breeding collects raw data and processes it in an eco-physiologically smart way. Examples of its use for creating global-scale envirotyping networks and integrating reaction-norm modeling in GP are also outlined. We conclude that EnvRtype provides a cost-effective envirotyping pipeline capable of providing high quality enviromic data for a diverse set of genomic-based studies, especially for increasing accuracy in GP across untested growing environments.

EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture

Envirotyping is an essential technique used to unfold the nongenetic drivers associated with the phenotypic adaptation of living organisms. Here, we introduce the EnvRtype R package, a novel toolkit developed to interplay large-scale envirotyping data (enviromics) into quantitative genomics. To start a user-friendly envirotyping pipeline, this package offers: (1) remote sensing tools for collecting (get_weather and extract_GIS functions) and processing ecophysiological variables (processWTH function) from raw environmental data at single locations or worldwide; (2) environmental characterization by typing environments and profiling descriptors of environmental quality (env_typing function), in addition to gathering environmental covariables as quantitative descriptors for predictive purposes (W_matrix function); and (3) identification of environmental similarity that can be used as an enviromic-based kernel (env_typing function) in whole-genome prediction (GP), aimed at increasing ecophysiological knowledge in genomic best-unbiased predictions (GBLUP) and emulating reaction norm effects (get_kernel and kernel_model functions). We highlight literature mining concepts in fine-tuning envirotyping parameters for each plant species and target growing environments. We show that envirotyping for predictive breeding collects raw data and processes it in an eco-physiologically smart way. Examples of its use for creating global-scale envirotyping networks and integrating reaction-norm modeling in GP are also outlined. We conclude that EnvRtype provides a cost-effective envirotyping pipeline capable of providing high quality enviromic data for a diverse set of genomic-based studies, especially for increasing accuracy in GP across untested growing environments.

Leaf transcriptomic response mediated by cold stress in two maize inbred lines with contrasting tolerance levels

Maize (Zea mays L.) is a thermophilic plant and a minor drop in temperature can prolong the maturity period. Plants respond to cold stress through structural and functional modification in cell membranes as well as changes in the photosynthesis and energy metabolism. In order to understand the molecular mechanisms underlying cold tolerance and adaptation, we employed leaf transcriptome sequencing together with leaf microstructure and relative electrical conductivity measurements in two maize inbred lines, having different cold stress tolerance potentials. The leaf physiological and transcriptomic responses of maize seedlings were studied after growing both inbred lines at 5 °C for 0, 12 and 24 h. Differentially expressed genes were enriched in photosynthesis antenna proteins, MAPK signaling pathway, plant hormone signal transduction, circadian rhythm, secondary metabolites related pathways, ribosome, and proteasome. The seedlings of both genotypes employed common stress responsive pathways to respond to cold stress. However, the cold tolerant line B144 protected its photosystem II from photooxidation by upregulating D1 proteins. The sensitive line Q319 was unable to close its stomata. Collectively, B144 exhibited a cold tolerance owing to its ability to mediate changes in stomata opening as well as protecting photosystem. These results increase our understanding on the cold stress tolerance in maize seedlings and propose multiple key regulators of stress responses such as modifications in photosystem II, stomata guard cell opening and closing, changes in secondary metabolite biosynthesis, and circadian rhythm. This study also presents the signal transduction related changes in MAPK and phytohormone signaling pathways in response to cold stress during seedling stage of maize.

Enviromic Assembly Increases Accuracy and Reduces Costs of the Genomic Prediction for Yield Plasticity in Maize

Quantitative genetics states that phenotypic variation is a consequence of the interaction between genetic and environmental factors. Predictive breeding is based on this statement, and because of this, ways of modeling genetic effects are still evolving. At the same time, the same refinement must be used for processing environmental information. Here, we present an "enviromic assembly approach," which includes using ecophysiology knowledge in shaping environmental relatedness into whole-genome predictions (GP) for plant breeding (referred to as enviromic-aided genomic prediction, E-GP). We propose that the quality of an environment is defined by the core of environmental typologies and their frequencies, which describe different zones of plant adaptation. From this, we derived markers of environmental similarity cost-effectively. Combined with the traditional additive and non-additive effects, this approach may better represent the putative phenotypic variation observed across diverse growing conditions (i.e., phenotypic plasticity). Then, we designed optimized multi-environment trials coupling genetic algorithms, enviromic assembly, and genomic kinships capable of providing in-silico realization of the genotype-environment combinations that must be phenotyped in the field. As proof of concept, we highlighted two E-GP applications: (1) managing the lack of phenotypic information in training accurate GP models across diverse environments and (2) guiding an early screening for yield plasticity exerting optimized phenotyping efforts. Our approach was tested using two tropical maize sets, two types of enviromics assembly, six experimental network sizes, and two types of optimized training set across environments. We observed that E-GP outperforms benchmark GP in all scenarios, especially when considering smaller training sets. The representativeness of genotype-environment combinations is more critical than the size of multi-environment trials (METs). The conventional genomic best-unbiased prediction (GBLUP) is inefficient in predicting the quality of a yet-to-be-seen environment, while enviromic assembly enabled it by increasing the accuracy of yield plasticity predictions. Furthermore, we discussed theoretical backgrounds underlying how intrinsic envirotype-phenotype covariances within the phenotypic records can impact the accuracy of GP. The E-GP is an efficient approach to better use environmental databases to deliver climate-smart solutions, reduce field costs, and anticipate future scenarios.

Isoform Sequencing Provides Insight Into Freezing Response of Common Wheat (Triticum aestivum L.)

The objective of the study is to reveal the freezing tolerance mechanisms of wheat by combining the emerging single-molecule real-time (SMRT) sequencing technology PacBio Sequel and Illumina sequencing. Commercial semiwinter wheat Zhoumai 18 was exposed to -6°C for 4 h at the four-leave stage. Leaves of the control group and freezing-treated group were used to perform cDNA library construction. PacBio SMRT sequencing yielded 51,570 high-quality isoforms from leaves of control sample of Zhoumai 18, encoded by 20,366 gene loci. In total, 73,695 transcript isoforms, corresponding to 23,039 genes, were identified from the freezing-treated leaves. Compared with transcripts from the International Wheat Genome Sequencing Consortium RefSeq v1.1, 57,667 novel isoforms were discovered, which were annotated 21,672 known gene loci, as well as 3,399 novel gene loci. Transcriptome characterization including alterative spliced events, alternative polydenylation sites, transcription factors, and fusion transcripts were also analyzed. Freezing-responsive genes and signals were uncovered and proved that the ICE-ERF-COR pathway and ABA signal transduction play a vital role in the freezing response of wheat. In this study, PacBio sequencing and Illumina sequencing were applied to investigate the freezing tolerance in common wheat, and the transcriptome results provide insights into the molecular regulation mechanisms under freezing treatment.

Maize Response to Low Temperatures at the Gene Expression Level: A Critical Survey of Transcriptomic Studies

Maize is a cold-sensitive plant whose physiological reactions to sub-optimal temperatures are well understood, but their molecular foundations are only beginning to be deciphered. In an attempt to identify key genes involved in these reactions, we surveyed several independent transcriptomic studies addressing the response of juvenile maize to moderate or severe cold. Among the tens of thousands of genes found to change expression upon cold treatment less than 500 were reported in more than one study, indicating an astonishing variability of the expression changes, likely depending on the experimental design and plant material used. Nearly all these "common" genes were specific to either moderate or to severe cold and formed distinct interaction networks, indicating fundamentally different responses. Moreover, down-regulation of gene expression dominated strongly in moderate cold and up-regulation prevailed in severe cold. Very few of these genes have ever been mentioned in the literature as cold-stress-related, indicating that most response pathways remain poorly known at the molecular level. We posit that the genes identified by the present analysis are attractive candidates for further functional studies and their arrangement in complex interaction networks indicates that a re-interpretation of the present state of knowledge on the maize cold-response is justified.

Seedling response to water stress in valley oak (Quercus lobata) is shaped by different gene networks across populations

Drought is a major stress for plants, creating a strong selection pressure for traits that enable plant growth and survival in dry environments. Many drought responses are conserved species-wide responses, while others vary among populations distributed across heterogeneous environments. We tested how six populations of the widely distributed California valley oak (Quercus lobata) sampled from contrasting climates would differ in their response to soil drying relative to well-watered controls in a common environment by measuring ecophysiological traits in 93 individuals and gene expression (RNA-seq) in 42 individuals. Populations did not differ in their adjustment of turgor loss point during soil drying, suggesting a generalized species-wide response. Differential expression analysis identified 689 genes with a common response to treatment across populations and 470 genes with population-specific responses. Weighted gene co-expression network analysis (WGCNA) identified groups of genes with similar expression patterns that may be regulated together (gene modules). Several gene modules responded differently to water stress among populations, suggesting regional differences in gene network regulation. Populations from sites with a high mean annual temperature responded to the imposed water stress with significantly greater changes in gene module expression, indicating that these populations may be locally adapted to respond to drought. We propose that this variation among valley oak populations provides a mechanism for differential tolerance to the increasingly frequent and severe droughts in California.

Transcriptomic profiling revealed genes involved in response to cold stress in maize

Maize is an important food crop. Chilling stress can decrease maize production by affecting seed germination and seedling growth, especially in early spring. We analysed chlorophyll fluorescence, membrane lipids, secondary metabolites and the transcriptome of two maize inbred lines (chilling-tolerant M54 and chilling-sensitive 753F) after 0, 4 and 24 h cold stress. M54 showed better ability to protect PSII and accumulate secondary metabolites. From RNA sequencing data, we determined that the majority of cold-affected genes were involved in photosynthesis, secondary metabolism, and signal transduction. Genes important for maintaining photosystem structure and for regulating electron transport were less affected by cold stress in M54 than in 753F. Expression of genes related to secondary metabolism and unsaturated fatty acid synthesis were upregulated more strongly in M54 than in 753F and M54 accumulated more unsaturated fatty acids and secondary metabolites. As a result, M54 achieved relatively high cold tolerance by protecting the photosystems and maintaining the stability of cell membranes.

Low-temperature tolerance in land plants: Are transcript and membrane responses conserved?

Plants' tolerance of low temperatures is an economically and ecologically important limitation on geographic distributions and growing seasons. Tolerance for low temperatures varies significantly across different plant species, and different mechanisms likely act in different species. In order to survive low-temperature stress, plant membranes must maintain their fluidity in increasingly cold and oxidative cellular environments. The responses of different species to low-temperature stress include changes to the types and desaturation levels of membrane lipids, though the precise lipids affected tend to vary by species. Regulation of membrane dynamics and other low-temperature tolerance factors are controlled by both transcriptional and post-transcriptional mechanisms. Here, we review low-temperature induced changes in both membrane lipid composition and gene transcription across multiple related plant species with differing degrees of low-temperature tolerance. We attempt to define a core set of changes for transcripts and lipids across species and treatment variations. Some responses appear to be consistent across all species for which data are available, while many others appear likely to be species or family-specific. Potential rationales are presented, including variance in testing, reporting and the importance of considering the level of stress perceived by the plant.

OsRACK1A, encodes a circadian clock-regulated WD40 protein, negatively affect salt tolerance in rice

The receptor for activated C kinase 1 (RACK1) is a WD40 type protein that is involved in multiple signaling pathways and is conserved from prokaryotes to eukaryotes. Here we report that rice RACK1A (OsRACK1A) is regulated by circadian clocks and plays an important role in the salt stress response. OsRACK1A was found to follow a rhythmic expression profile under circadian conditions at both the transcription and the translation levels, although the expression was arrhythmic under salt stress. Analysis of plant survival rates, fresh weight, proline content, malondialdehyde, and chlorophyll showed that suppression of OsRACK1A enhanced tolerance to salt stress. The ion concentration in both roots and leaves revealed that OsRACK1A-suppressed transgenic rice could maintain low Na⁺ and high K⁺ concentrations. Furthermore, OsRACK1A-suppressed transgenic rice accumulated significantly more abscisic acid (ABA) and more transcripts of ABA- and stress-inducible genes compared with the wild-type plants. Real-time quantitative polymerase chain reaction analysis revealed that many stress-related genes, including APETALA 2/Ethylene Responsive Factor (AP2/ERF) transcription factors, were upregulated in the OsRACK1A-suppressed transgenic rice line. We identified putative interactors of OsRACK1A, and found that OsRACK1A interacted with many salt stress-responsive proteins directly. These results suggest that OsRACK1A is regulated by circadian rhythm, and involved in the regulation of salt stress responses.