Plant systems biology comes of age

Plant biomarkers as early detection tools in stress management in food crops: a review

MAIN CONCLUSION

Plant Biomarkers are objective indicators of a plant's cellular state in response to abiotic and biotic stress factors. They can be explored in crop breeding and engineering to produce stress-tolerant crop species. Global food production safely and sustainably remains a top priority to feed the ever-growing human population, expected to reach 10 billion by 2050. However, abiotic and biotic stress factors negatively impact food production systems, causing between 70 and 100% reduction in crop yield. Understanding the plant stress responses is critical for developing novel crops that can adapt better to various adverse environmental conditions. Using plant biomarkers as measurable indicators of a plant's cellular response to external stimuli could serve as early warning signals to detect stresses before severe damage occurs. Plant biomarkers have received considerable attention in the last decade as pre-stress indicators for various economically important food crops. This review discusses some biomarkers associated with abiotic and biotic stress conditions and highlights their importance in developing stress-resilient crops. In addition, we highlighted some factors influencing the expression of biomarkers in crop plants under stress. The information presented in this review would educate plant researchers, breeders, and agronomists on the significance of plant biomarkers in stress biology research, which is essential for improving plant growth and yield toward sustainable food production.

Physcomitrium patens CAD1 has distinct roles in growth and resistance to biotic stress

BACKGROUND

Physcomitrium patens provides an evolutionary link between green algae and vascular plants. Although the genome of P. patens includes orthologs of all the core lignin biosynthetic enzymes, the occurrence of lignin in moss is very controversial. Besides, little information is available about the lignin enzymes in moss to date. For example, cinnamyl alcohol dehydrogenase (CAD) is a crucial enzyme that catalyzes the last step of the lignin biosynthetic pathway, suggesting an ideal way to study the evolutionary process. By investigating the functions of CAD in evolution, this study will elucidate the evolutionary roles of lignin-like in the early stage of land colonization.

RESULTS

CAD multigene family in P. patens is composed of four genes. The PpCADs contain a conserved glycine-rich domain to catalyze NADPH-dependent reduction to their corresponding alcohols, indicating that PpCADs have the potential to synthesize monolignols by bioinformatics analysis. Even though PpCAD1 could produce lignin in theory, no conventional monomer was detected in the cell wall or cytoplasm of PpCAD1_OE plants. However, the phenylpropanoids were promoted in PpCAD1_OE transformants to modify gametophore architecture and development, making the distribution of phyllids more scarcity and the moss colony more giant, possibly due to the enhanced expression of the AUX-IAA family. The transcripts of at least one gene encoding the enzyme in the lignin biosynthetic pathway were increased in PpCAD1_OE plants. In addition, the PpCAD1_OE gametophore inhibited the Botrytis cinerea assault mainly by enhanced phenylpropanoids in the cell wall instead of influencing transcripts of defense genes pathogenesis-related 10 (PR10) and nonexpresser of PR genes 1 (NPR1). Likewise, ectopic expression of PpCAD1 in Arabidopsis led to a significant increase in lignin content, exhibiting chunky roots, robust seedlings, advanced flowering, and efficient resistance against pathogens.

CONCLUSION

PpCAD occurs in more than one copy, suggesting functional divergence in the ancestral plant. PpCAD1 catalyzes monolignol biosynthesis and has homologous functions with vascular plants. Despite no detected conventional monolignol, the increased phenylpropanoids in the PpCAD1_OE gametophore, possibly intermediate metabolites in the lignin pathway, had conserved functions during the evolution of terrestrial plants. The results inferred that the lignin enzyme of the early non-vascular plant played roles in stem elongation and resistance against pathogens of P. patens during the conquest of land.

Unsupervised and semi-supervised learning: the next frontier in machine learning for plant systems biology

Advances in high-throughput omics technologies are leading plant biology research into the era of big data. Machine learning (ML) performs an important role in plant systems biology because of its excellent performance and wide application in the analysis of big data. However, to achieve ideal performance, supervised ML algorithms require large numbers of labeled samples as training data. In some cases, it is impossible or prohibitively expensive to obtain enough labeled training data; here, the paradigms of unsupervised learning (UL) and semi-supervised learning (SSL) play an indispensable role. In this review, we first introduce the basic concepts of ML techniques, as well as some representative UL and SSL algorithms, including clustering, dimensionality reduction, self-supervised learning (self-SL), positive-unlabeled (PU) learning and transfer learning. We then review recent advances and applications of UL and SSL paradigms in both plant systems biology and plant phenotyping research. Finally, we discuss the limitations and highlight the significance and challenges of UL and SSL strategies in plant systems biology.

Enhanced production of 2-phenylethanol by salicylic acid and cyclodextrins in cell suspension cultures of the unexplored filamentous fungus Monochaetinula geoffroeana

BACKGROUND

2-Phenylethanol (PEA) is a higher aromatic alcohol with a rose-like odor, which is used in several industries. Although PEA can be synthesized, consumers are increasingly concerned about the toxicity of chemically synthesized products, and prefer natural aroma compound. PEA occurs naturally in the environment but concentrations are too low to justify extraction.

RESULTS

The present study offers a novel biological source of PEA: the filamentous fungi Monochaetinula geoffroeana. We report the highest recorded yield of PEA of fungal origin to date: 6.52 g L^-1 . The volatility and low water solubility of PEA can affect its use in many industries, for which reason complexation studies of PEA and cyclodextrins were carried out using the phase solubility technique. PEA formed 1:1 stoichiometric inclusion complexes with natural and modified CDs, the highest encapsulation constant being obtained with MβCD (K_1:1  = 299.88 L mol^-1 ). The complexation process significantly increased the water solubility of PEA. A computational study showed a high degree of correlation between computed scores and experimental values. Furthermore, this study reports the role of salicylic acid as an effective elicitor for improved PEA production by the studied fungi. Supplementation with 10 μmol L^-1 salicylic acid increased PEA production from 6.52 to 10.54 g L^-1 .

CONCLUSION

The best treatment to enhance PEA production by M. geoffroeana under laboratory conditions was to use salicylic acid 10 μmol L^-1 . Due to the commercial importance of PEA, further investigation is needed to improve PEA production by M. geoffroeana and to optimize culture conditions in order to standardize yields. © 2021 Society of Chemical Industry.

CPIELA: Computational Prediction of Plant Protein–Protein Interactions by Ensemble Learning Approach From Protein Sequences and Evolutionary Information

Identification and characterization of plant protein–protein interactions (PPIs) are critical in elucidating the functions of proteins and molecular mechanisms in a plant cell. Although experimentally validated plant PPIs data have become increasingly available in diverse plant species, the high-throughput techniques are usually expensive and labor-intensive. With the incredibly valuable plant PPIs data accumulating in public databases, it is progressively important to propose computational approaches to facilitate the identification of possible PPIs. In this article, we propose an effective framework for predicting plant PPIs by combining the position-specific scoring matrix (PSSM), local optimal-oriented pattern (LOOP), and ensemble rotation forest (ROF) model. Specifically, the plant protein sequence is firstly transformed into the PSSM, in which the protein evolutionary information is perfectly preserved. Then, the local textural descriptor LOOP is employed to extract texture variation features from PSSM. Finally, the ROF classifier is adopted to infer the potential plant PPIs. The performance of CPIELA is evaluated via cross-validation on three plant PPIs datasets: Arabidopsis thaliana, Zea mays, and Oryza sativa. The experimental results demonstrate that the CPIELA method achieved the high average prediction accuracies of 98.63%, 98.09%, and 94.02%, respectively. To further verify the high performance of CPIELA, we also compared it with the other state-of-the-art methods on three gold standard datasets. The experimental results illustrate that CPIELA is efficient and reliable for predicting plant PPIs. It is anticipated that the CPIELA approach could become a useful tool for facilitating the identification of possible plant PPIs.

Sequence-Based Prediction of Plant Protein-Protein Interactions by Combining Discrete Sine Transformation With Rotation Forest

Protein-protein interactions (PPIs) in plants are essential for understanding the regulation of biological processes. Although high-throughput technologies have been widely used to identify PPIs, they are usually laborious, expensive, and suffer from high false-positive rates. Therefore, it is imperative to develop novel computational approaches as a supplement tool to detect PPIs in plants. In this work, we presented a method, namely DST-RoF, to identify PPIs in plants by combining an ensemble learning classifier-Rotation Forest (RoF) with discrete sine transformation (DST). Specifically, plant protein sequence is firstly converted into Position-Specific Scoring Matrix (PSSM). Then, the discrete sine transformation was employed to extract effective features for obtaining the evolutionary information of proteins. Finally, these optimal features were fed into the RoF classifier for training and prediction. When performed on the plant datasets Arabidopsis, Rice, and Maize, DST-RoF yielded high prediction accuracy of 82.95%, 88.82%, and 93.70%, respectively. To further evaluate the prediction ability of our approach, we compared it with 4 state-of-the-art classifiers and 3 different feature extraction methods. Comprehensive experimental results anticipated that our method is feasible and robust for predicting potential plant-protein interacted pairs.

Infrastructures of systems biology that facilitate functional genomic study in rice

Rice (Oryza sativa L.) is both a major staple food for the worldwide population and a model crop plant for studying the mode of action of agronomically valuable traits, providing information that can be applied to other crop plants. Due to the development of high-throughput technologies such as next generation sequencing and mass spectrometry, a huge mass of multi-omics data in rice has been accumulated. Through the integration of those data, systems biology in rice is becoming more advanced.To facilitate such systemic approaches, we have summarized current resources, such as databases and tools, for systems biology in rice. In this review, we categorize the resources using six omics levels: genomics, transcriptomics, proteomics, metabolomics, integrated omics, and functional genomics. We provide the names, websites, references, working states, and number of citations for each individual database or tool and discuss future prospects for the integrated understanding of rice gene functions.

Salicylic acid as an effective elicitor for improved taxol production in endophytic fungus Pestalotiopsis microspora

Salicylic acid (SA) is an effective elicitor to increase taxol production in Pestalotiopsis microspora. Addition of SA at the concentration of 300 μM yielded taxol 625.47 μg L-1, 45- fold higher than that of the control. Elicitation of the role of SA in the fungal taxol biosynthetic pathway revealed that SA enhanced reactive oxygen species and lipid peroxidation of unsaturated fatty acids of P. microspora mycelia. This oxidative process stimulates isoprene biosynthetic pathway by triggering expression of the geranylgeranyl pyrophosphate synthase gene leading to improved biosynthesis of taxol in P. microspora.

An Integrated, High-Throughput Strategy for Multiomic Systems Level Analysis

Proteomics, metabolomics, and transcriptomics generate comprehensive data sets, and current biocomputational capabilities allow their efficient integration for systems biology analysis. Published multiomics studies cover methodological advances as well as applications to biological questions. However, few studies have focused on the development of a high-throughput, unified sample preparation approach to complement high-throughput omic analytics. This report details the automation, benchmarking, and application of a strategy for transcriptomic, proteomic, and metabolomic analyses from a common sample. The approach, sample preparation for multi-omics technologies (SPOT), provides equivalent performance to typical individual omic preparation methods but greatly enhances throughput and minimizes the resources required for multiomic experiments. SPOT was applied to a multiomics time course experiment for zinc-treated HL-60 cells. The data reveal Zn effects on NRF2 antioxidant and NFkappaB signaling. High-throughput approaches such as these are critical for the acquisition of temporally resolved, multicondition, large multiomic data sets such as those necessary to assess complex clinical and biological concerns. Ultimately, this type of approach will provide an expanded understanding of challenging scientific questions across many fields.

Omics Approaches for Engineering Wheat Production under Abiotic Stresses

Abiotic stresses greatly influenced wheat productivity executed by environmental factors such as drought, salt, water submergence and heavy metals. The effective management at the molecular level is mandatory for a thorough understanding of plant response to abiotic stress. Understanding the molecular mechanism of stress tolerance is complex and requires information at the omic level. In the areas of genomics, transcriptomics and proteomics enormous progress has been made in the omics field. The rising field of ionomics is also being utilized for examining abiotic stress resilience in wheat. Omic approaches produce a huge amount of data and sufficient developments in computational tools have been accomplished for efficient analysis. However, the integration of omic-scale information to address complex genetics and physiological questions is still a challenge. Though, the incorporation of omic-scale data to address complex genetic qualities and physiological inquiries is as yet a challenge. In this review, we have reported advances in omic tools in the perspective of conventional and present day approaches being utilized to dismember abiotic stress tolerance in wheat. Attention was given to methodologies, for example, quantitative trait loci (QTL), genome-wide association studies (GWAS) and genomic selection (GS). Comparative genomics and candidate genes methodologies are additionally talked about considering the identification of potential genomic loci, genes and biochemical pathways engaged with stress resilience in wheat. This review additionally gives an extensive list of accessible online omic assets for wheat and its effective use. We have additionally addressed the significance of genomics in the integrated approach and perceived high-throughput multi-dimensional phenotyping as a significant restricting component for the enhancement of abiotic stress resistance in wheat.

Innovative Approaches to Evaluate Sugar Beet Responses to Changes in Sulfate Availability

In this study, a system based on omics profiling was set-up for sugar beet (Beta vulgaris L. subsp. vulgaris) evaluation after changes in sulfate availability. Seedlings were grown on sulfate-deprived Hoagland solution. Six days after germination, 100 μM MgSO₄ was added to the solution. Root samples were collected 36 h after treatments. WinRHIZO root-scanning approach was used for the automated image analysis of plant root morphology. Inductively Coupled Plasma Spectrometry (ICP-OES) and quadrupole-time-of-flight mass spectrometry (Q-TOF) were used for ionomic and metabolic analysis, respectively. Nanofluidic real-time PCR (OpenArray system) was used for molecular profiling. OpenArray chips were designed with TaqMan probes for 53 sugar beet genes putatively involved in sulfate nutrition. At morphological level treated seedlings showed significantly higher values (P < 0.01) than untreated plants for root traits related to soil exploration and nutrient uptake, such as total root length, fine roots length and root tips number. ICP-OES, Q-TOF and transcriptomic data revealed changes due to sulfate availability in sugar beet samples. Two key results are highlighted in sulfate-supplied roots and leaves. Firstly, high expression levels of auxin efflux carrier component 1 (PIN) and 5-phosphoribosyl-anthranilate, precursor of tryptophan and auxin synthesis, were observed in roots. Secondly, high levels of 2-Cys peroxiredoxin BAS1, chloroplastic, thioredoxin reductase (NADPH) and cysteine synthase, chloroplastic/chromoplastic, O-acetylserine sulfhydrylase, involved in protection against oxidative stress and cysteine synthase activity, respectively, were observed in leaves. Based on our findings, the combination of evaluated omics approaches could become a key system for the evaluation of the nutritional status of sugar beet under different nutrient availability conditions.

Post photosynthetic carbon partitioning to sugar alcohols and consequences for plant growth

The occurrence of sugar alcohols is ubiquitous among plants. Physiochemical properties of sugar alcohols suggest numerous primary and secondary functions in plant tissues and are often well documented. In addition to functions arising from physiochemical properties, the synthesis of sugar alcohols may have significant influence over photosynthetic, respiratory, and developmental processes owing to their function as a large sink for photosynthates. Sink strength is demonstrated by the high concentrations of sugar alcohols found in plant tissues and their ability to be readily transported. The plant scale distribution and physiochemical function of these compounds renders them strong candidates for functioning as stress metabolites. Despite this, several aspects of sugar alcohol biosynthesis and function are poorly characterised namely: 1) the quantitative characterisation of carbon flux into the sugar alcohol pool; 2) the molecular control governing sugar alcohol biosynthesis on a quantitative basis; 3) the role of sugar alcohols in plant growth and ecology; and 4) consequences of sugar alcohol synthesis for yield production and yield quality. We highlight the need to adopt new approaches to investigating sugar alcohol biosynthesis using modern technologies in gene expression, metabolic flux analysis and agronomy. Combined, these approaches will elucidate the impact of sugar alcohol biosynthesis on growth, stress tolerance, yield and yield quality.

Food Legumes and Rising Temperatures: Effects, Adaptive Functional Mechanisms Specific to Reproductive Growth Stage and Strategies to Improve Heat Tolerance

Ambient temperatures are predicted to rise in the future owing to several reasons associated with global climate changes. These temperature increases can result in heat stress- a severe threat to crop production in most countries. Legumes are well-known for their impact on agricultural sustainability as well as their nutritional and health benefits. Heat stress imposes challenges for legume crops and has deleterious effects on the morphology, physiology, and reproductive growth of plants. High-temperature stress at the time of the reproductive stage is becoming a severe limitation for production of grain legumes as their cultivation expands to warmer environments and temperature variability increases due to climate change. The reproductive period is vital in the life cycle of all plants and is susceptible to high-temperature stress as various metabolic processes are adversely impacted during this phase, which reduces crop yield. Food legumes exposed to high-temperature stress during reproduction show flower abortion, pollen and ovule infertility, impaired fertilization, and reduced seed filling, leading to smaller seeds and poor yields. Through various breeding techniques, heat tolerance in major legumes can be enhanced to improve performance in the field. Omics approaches unravel different mechanisms underlying thermotolerance, which is imperative to understand the processes of molecular responses toward high-temperature stress.

Enhancement of Environmental Hazard Degradation in the Presence of Lignin: a Proteomics Study

Proteomics studies of fungal systems have progressed dramatically based on the availability of more fungal genome sequences in recent years. Different proteomics strategies have been applied toward characterization of fungal proteome and revealed important gene functions and proteome dynamics. Presented here is the application of shot-gun proteomic technology to study the bio-remediation of environmental hazards by white-rot fungus. Lignin, a naturally abundant component of the plant biomass, is discovered to promote the degradation of Azo dye by white-rot fungus Irpex lacteus CD2 in the lignin/dye/fungus system. Shotgun proteomics technique was used to understand degradation mechanism at the protein level for the lignin/dye/fungus system. Our proteomics study can identify about two thousand proteins (one third of the predicted white-rot fungal proteome) in a single experiment, as one of the most powerful proteomics platforms to study the fungal system to date. The study shows a significant enrichment of oxidoreduction functional category under the dye/lignin combined treatment. An in vitro validation is performed and supports our hypothesis that the synergy of Fenton reaction and manganese peroxidase might play an important role in DR5B dye degradation. The results could guide the development of effective bioremediation strategies and efficient lignocellulosic biomass conversion.

Dynamic Acclimation to High Light in Arabidopsis thaliana Involves Widespread Reengineering of the Leaf Proteome

Leaves of Arabidopsis thaliana transferred from low to high light increase their capacity for photosynthesis, a process of dynamic acclimation. A mutant, gpt2, lacking a chloroplast glucose-6-phosphate/phosphate translocator, is deficient in its ability to acclimate to increased light. Here, we have used a label-free proteomics approach, to perform relative quantitation of 1993 proteins from Arabidopsis wild type and gpt2 leaves exposed to increased light. Data are available via ProteomeXchange with identifier PXD006598. Acclimation to light is shown to involve increases in electron transport and carbon metabolism but no change in the abundance of photosynthetic reaction centers. The gpt2 mutant shows a similar increase in total protein content to wild type but differences in the extent of change of certain proteins, including in the relative abundance of the cytochrome b6f complex and plastocyanin, the thylakoid ATPase and selected Benson-Calvin cycle enzymes. Changes in leaf metabolite content as plants acclimate can be explained by changes in the abundance of enzymes involved in metabolism, which were reduced in gpt2 in some cases. Plants of gpt2 invest more in stress-related proteins, suggesting that their reduced ability to acclimate photosynthetic capacity results in increased stress.

Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis

BACKGROUND

Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response.

RESULTS

In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways.

CONCLUSIONS

Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome may respond with different extent to individual stress components. Their contrasting behavior in response to temperature stress highlights that the protein folding machinery effectively shields the metabolism from stress. Disentangling the complex relationships between transcriptome and metabolome in response to stress is an enormous challenge. As demonstrated by case studies with supporting evidence from additional data, the large dataset provided in this study may assist in determining linked genetic and metabolic features as candidates for future mechanistic analyses.

Drawing Links from Transcriptome to Metabolites: The Evolution of Aroma in the Ripening Berry of Moscato Bianco (Vitis vinifera L.)

Monoterpenes confer typical floral notes to "Muscat" grapevine varieties and, to a lesser extent, to other aromatic non-Muscat varieties. Previous studies have led to the identification and functional characterization of some enzymes and genes in this pathway. However, the underlying genetic map is still far from being complete. For example, the specific steps of monoterpene metabolism and its regulation are largely unknown. With the aim of identifying new candidates for the missing links, we applied an integrative functional genomics approach based on the targeted metabolic and genome-wide transcript profiling of Moscato Bianco ripening berries. In particular, gas chromatography-mass spectrometry analysis of free and bound terpenoid compounds was combined with microarray analysis in the skins of berries collected at five developmental stages from pre-veraison to over-ripening. Differentially expressed metabolites and probes were identified in the pairwise comparison between time points by using the early stage as a reference. Metabolic and transcriptomic data were integrated through pairwise correlation and clustering approaches to discover genes linked with particular metabolites or groups of metabolites. These candidate transcripts were further checked for co-localization with quantitative trait loci (QTLs) affecting aromatic compounds. Our findings provide insights into the biological networks of grapevine secondary metabolism, both at the catalytic and regulatory levels. Examples include a nudix hydrolase as component of a terpene synthase-independent pathway for monoterpene biosynthesis, genes potentially involved in monoterpene metabolism (cytochrome P450 hydroxylases, epoxide hydrolases, glucosyltransferases), transport (vesicle-associated proteins, ABCG transporters, glutathione S-transferases, amino acid permeases), and transcriptional control (transcription factors of the ERF, MYB and NAC families, intermediates in light- and circadian cycle-mediated regulation with supporting evidence from the literature and additional regulatory genes with a previously unreported association to monoterpene accumulation).

Medium term water deficit elicits distinct transcriptome responses in Eucalyptus species of contrasting environmental origin

Background

Climatic and edaphic conditions over geological timescales have generated enormous diversity of adaptive traits and high speciation within the genus Eucalyptus (L. Hér.). Eucalypt species occur from high rainfall to semi-arid zones and from the tropics to latitudes as high as 43°S. Despite several morphological and metabolomic characterizations, little is known regarding gene expression differences that underpin differences in tolerance to environmental change. Using species of contrasting taxonomy, morphology and physiology (E. globulus and E. cladocalyx), this study combines physiological characterizations with ‘second-generation’ sequencing to identify key genes involved in eucalypt responses to medium-term water limitation.

Results

One hundred twenty Million high-quality HiSeq reads were created from 14 tissue samples in plants that had been successfully subjected to a water deficit treatment or a well-watered control. Alignment to the E. grandis genome saw 23,623 genes of which 468 exhibited differential expression (FDR < 0.01) in one or both ecotypes in response to the treatment. Further analysis identified 80 genes that demonstrated a significant species-specific response of which 74 were linked to the ‘dry’ species E. cladocalyx where 23 of these genes were uncharacterised. The majority (approximately 80%) of these differentially expressed genes, were expressed in stem tissue. Key genes that differentiated species responses were linked to photoprotection/redox balance, phytohormone/signalling, primary photosynthesis/cellular metabolism and secondary metabolism based on plant metabolic pathway network analysis.

Conclusion

These results highlight a more definitive response to water deficit by a ‘dry’ climate eucalypt, particularly in stem tissue, identifying key pathways and associated genes that are responsible for the differences between ‘wet’ and ‘dry’ climate eucalypts. This knowledge provides the opportunity to further investigate and understand the mechanisms and genetic variation linked to this important environmental response that will assist with genomic efforts in managing native populations as well as in tree improvement programs under future climate scenarios.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3664-z) contains supplementary material, which is available to authorized users.

Identification and validation of reference genes for quantitative real-time PCR studies in long yellow daylily, Hemerocallis citrina Borani

Gene expression analysis using reverse transcription quantitative real-time PCR (RT-qPCR) requires the use of reference gene(s) in the target species. The long yellow daylily, Hemerocallis citrina Baroni. is rich in beneficial secondary metabolites and is considered as a functional vegetable. It is widely cultivated and consumed in East Asian countries. However, reference genes for use in RT-qPCR in H. citrina are not available. In the present study, six potential reference genes, actin (ACT), AP-4 complex subunit (AP4), tubulin (TUB), ubiquitin (UBQ), 18S and 60S ribosomal RNA, were selected and their expression stability in different developmental stages, organs and accessions was evaluated using four statistical software packages (geNorm, NormFinder, BestKeeper, and RefFinder). For commercial flower buds of different landraces, the combination of 60S, TUB, and AP4 was appropriate whereas ACT and 60S was suitable for normalization of different organs. In addition, AP4 exhibited the most stable expression in flower buds among different developmental stages. UBQ was less stable than the other reference genes under the experimental conditions except under different organs was 18S. The relative expression levels of two genes, primary-amine oxidase (HcAOC3) and tyrosine aminotransferase (HcTAT) which play important roles in alkaloid biosynthesis were also examined in different organs of the 'Datong' landrace, which further confirmed the results of selected reference genes. This is the first report to evaluate the stability of reference genes in the long yellow daylily that can serve as a foundation for RT-qPCR analysis of gene expression in this species.

Identification and validation of reference genes for quantitative real-time PCR studies in long yellow daylily, Hemerocallis citrina Borani

Gene expression analysis using reverse transcription quantitative real-time PCR (RT-qPCR) requires the use of reference gene(s) in the target species. The long yellow daylily, Hemerocallis citrina Baroni. is rich in beneficial secondary metabolites and is considered as a functional vegetable. It is widely cultivated and consumed in East Asian countries. However, reference genes for use in RT-qPCR in H. citrina are not available. In the present study, six potential reference genes, actin (ACT), AP-4 complex subunit (AP4), tubulin (TUB), ubiquitin (UBQ), 18S and 60S ribosomal RNA, were selected and their expression stability in different developmental stages, organs and accessions was evaluated using four statistical software packages (geNorm, NormFinder, BestKeeper, and RefFinder). For commercial flower buds of different landraces, the combination of 60S, TUB, and AP4 was appropriate whereas ACT and 60S was suitable for normalization of different organs. In addition, AP4 exhibited the most stable expression in flower buds among different developmental stages. UBQ was less stable than the other reference genes under the experimental conditions except under different organs was 18S. The relative expression levels of two genes, primary-amine oxidase (HcAOC3) and tyrosine aminotransferase (HcTAT) which play important roles in alkaloid biosynthesis were also examined in different organs of the 'Datong' landrace, which further confirmed the results of selected reference genes. This is the first report to evaluate the stability of reference genes in the long yellow daylily that can serve as a foundation for RT-qPCR analysis of gene expression in this species.

rosettR: protocol and software for seedling area and growth analysis

BACKGROUND

Growth is an important parameter to consider when studying the impact of treatments or mutations on plant physiology. Leaf area and growth rates can be estimated efficiently from images of plants, but the experiment setup, image analysis, and statistical evaluation can be laborious, often requiring substantial manual effort and programming skills.

RESULTS

Here we present rosettR, a non-destructive and high-throughput phenotyping protocol for the measurement of total rosette area of seedlings grown in plates in sterile conditions. We demonstrate that our protocol can be used to accurately detect growth differences among different genotypes and in response to light regimes and osmotic stress. rosettR is implemented as a package for the statistical computing software R and provides easy to use functions to design an experiment, analyze the images, and generate reports on quality control as well as a final comparison across genotypes and applied treatments. Experiment procedures are included as part of the package documentation.

CONCLUSIONS

Using rosettR it is straight-forward to perform accurate, reproducible measurements of rosette area and relative growth rate with high-throughput using inexpensive equipment. Suitable applications include screening mutant populations for growth phenotypes visible at early growth stages and profiling different genotypes in a wide variety of treatments.

Food Legumes and Rising Temperatures: Effects, Adaptive Functional Mechanisms Specific to Reproductive Growth Stage and Strategies to Improve Heat Tolerance

Ambient temperatures are predicted to rise in the future owing to several reasons associated with global climate changes. These temperature increases can result in heat stress- a severe threat to crop production in most countries. Legumes are well-known for their impact on agricultural sustainability as well as their nutritional and health benefits. Heat stress imposes challenges for legume crops and has deleterious effects on the morphology, physiology, and reproductive growth of plants. High-temperature stress at the time of the reproductive stage is becoming a severe limitation for production of grain legumes as their cultivation expands to warmer environments and temperature variability increases due to climate change. The reproductive period is vital in the life cycle of all plants and is susceptible to high-temperature stress as various metabolic processes are adversely impacted during this phase, which reduces crop yield. Food legumes exposed to high-temperature stress during reproduction show flower abortion, pollen and ovule infertility, impaired fertilization, and reduced seed filling, leading to smaller seeds and poor yields. Through various breeding techniques, heat tolerance in major legumes can be enhanced to improve performance in the field. Omics approaches unravel different mechanisms underlying thermotolerance, which is imperative to understand the processes of molecular responses toward high-temperature stress.

Identification and validation of reference genes for quantitative real-time PCR studies in Hedera helix L

Reference gene evaluation and selection are necessary steps in gene expression analysis, especially in new plant varieties, through reverse transcription quantitative real-time PCR (RT-qPCR). Hedera helix L. is an important traditional medicinal plant recorded in European Pharmacopoeia. Research on gene expression in H. helix has not been widely explored, and no RT-qPCR studies have been reported. Thus, it is important and necessary to identify and validate suitable reference genes to for normalizing RT-qPCR results. In our study, 14 candidate protein-coding reference genes were selected. Their expression stability in five tissues (root, stem, leaf, petiole and shoot tip) and under seven abiotic stress conditions (cold, heat, drought, salinity, UV-C irradiation, abscisic acid and methyl jasmonate) were evaluated using geNorm and NormFinder. This study is the first to evaluate the stability of reference genes in H. helix. The results show that different reference genes should be chosen for normalization on the basis of various experimental conditions. F-box was more stable than the other selected genes under all analysis conditions except ABA treatment; 40S was the most stable reference gene under ABA treatment; in contrast, EXP and UBQ were the most unstable reference genes. The expressions of HhSE and Hhβ-AS, which are two genes related to the biosynthetic pathway of triterpenoid saponins, were also examined for reference genes in different tissues and under various cold stress conditions. The validation results confirmed the applicability and accuracy of reference genes. Additionally, this study provides a basis for the accurate and widespread use of RT-qPCR in selecting genes from the genome of H. helix.

Oral secretions from Mythimna separata insects specifically induce defence responses in maize as revealed by high-dimensional biological data

Attack from insect herbivores poses a major threat to plant survival, and accordingly, plants have evolved sophisticated defence systems. Maize is cultivated as a staple crop worldwide, and insect feeding causes large production losses. Despite its importance in agriculture, little is known about how maize reacts to insect herbivory. Taking advantage of advances in sequencing and mass spectrometry technology, we studied the response of maize to mechanical wounding and simulated Mythimna separata (a specialist insect) herbivory by applying its oral secretions (OS) to wounds. In comparison to the responses induced by mechanical wounding, OS elicited larger and longer-lasting changes in the maize transcriptome, proteome, metabolome and phytohormones. Specifically, many genes, proteins and metabolites were uniquely induced or repressed by OS. Nearly 290 transcription factor genes from 39 families were involved in OS-induced responses, and among these, more transcription factor genes were specifically regulated by OS than by wounding. This study provides a large-scale omics dataset for understanding maize response to chewing insects and highlights the essential role of OS in plant-insect interactions.

Integration of multi-omics data for prediction of phenotypic traits using random forest

Background

In order to find genetic and metabolic pathways related to phenotypic traits of interest, we analyzed gene expression data, metabolite data obtained with GC-MS and LC-MS, proteomics data and a selected set of tuber quality phenotypic data from a diploid segregating mapping population of potato. In this study we present an approach to integrate these ~ omics data sets for the purpose of predicting phenotypic traits. This gives us networks of relatively small sets of interrelated ~ omics variables that can predict, with higher accuracy, a quality trait of interest.

Results

We used Random Forest regression for integrating multiple ~ omics data for prediction of four quality traits of potato: tuber flesh colour, DSC onset, tuber shape and enzymatic discoloration. For tuber flesh colour beta-carotene hydroxylase and zeaxanthin epoxidase were ranked first and forty-fourth respectively both of which have previously been associated with flesh colour in potato tubers. Combining all the significant genes, LC-peaks, GC-peaks and proteins, the variation explained was 75 %, only slightly more than what gene expression or LC-MS data explain by themselves which indicates that there are correlations among the variables across data sets. For tuber shape regressed on the gene expression, LC-MS, GC-MS and proteomics data sets separately, only gene expression data was found to explain significant variation. For DSC onset, we found 12 significant gene expression, 5 metabolite levels (GC) and 2 proteins that are associated with the trait. Using those 19 significant variables, the variation explained was 45 %. Expression QTL (eQTL) analyses showed many associations with genomic regions in chromosome 2 with also the highest explained variation compared to other chromosomes. Transcriptomics and metabolomics analysis on enzymatic discoloration after 5 min resulted in 420 significant genes and 8 significant LC metabolites, among which two were putatively identified as caffeoylquinic acid methyl ester and tyrosine.

Conclusions

In this study, we made a strategy for selecting and integrating multiple ~ omics data using random forest method and selected representative individual peaks for networks based on eQTL, mQTL or pQTL information. Network analysis was done to interpret how a particular trait is associated with gene expression, metabolite and protein data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1043-4) contains supplementary material, which is available to authorized users.

Phenomics for photosynthesis, growth and reflectance in Arabidopsis thaliana reveals circadian and long-term fluctuations in heritability

BACKGROUND

Recent advances in genome sequencing technologies have shifted the research bottleneck in plant sciences from genotyping to phenotyping. This shift has driven the development of phenomics, high-throughput non-invasive phenotyping technologies.

RESULTS

We describe an automated high-throughput phenotyping platform, the Phenovator, capable of screening 1440 Arabidopsis plants multiple times per day for photosynthesis, growth and spectral reflectance at eight wavelengths. Using this unprecedented phenotyping capacity, we have been able to detect significant genetic differences between Arabidopsis accessions for all traits measured, across both temporal and environmental scales. The high frequency of measurement allowed us to observe that heritability was not only trait specific, but for some traits was also time specific.

CONCLUSIONS

Such continuous real-time non-destructive phenotyping will allow detailed genetic and physiological investigations of the kinetics of plant homeostasis and development. The success and ultimate outcome of a breeding program will depend greatly on the genetic variance which is sampled. Our observation of temporal fluctuations in trait heritability shows that the moment of measurement can have lasting consequences. Ultimately such phenomic level technologies will provide more dynamic insights into plant physiology, and the necessary data for the omics revolution to reach its full potential.

Metabolomic profiling and genomic analysis of wheat aneuploid lines to identify genes controlling biochemical pathways in mature grain

Metabolomics is becoming an increasingly important tool in plant genomics to decipher the function of genes controlling biochemical pathways responsible for trait variation. Although theoretical models can integrate genes and metabolites for trait variation, biological networks require validation using appropriate experimental genetic systems. In this study, we applied an untargeted metabolite analysis to mature grain of wheat homoeologous group 3 ditelosomic lines, selected compounds that showed significant variation between wheat lines Chinese Spring and at least one ditelosomic line, tracked the genes encoding enzymes of their biochemical pathway using the wheat genome survey sequence and determined the genetic components underlying metabolite variation. A total of 412 analytes were resolved in the wheat grain metabolome, and principal component analysis indicated significant differences in metabolite profiles between Chinese Spring and each ditelosomic lines. The grain metabolome identified 55 compounds positively matched against a mass spectral library where the majority showed significant differences between Chinese Spring and at least one ditelosomic line. Trehalose and branched-chain amino acids were selected for detailed investigation, and it was expected that if genes encoding enzymes directly related to their biochemical pathways were located on homoeologous group 3 chromosomes, then corresponding ditelosomic lines would have a significant reduction in metabolites compared with Chinese Spring. Although a proportion showed a reduction, some lines showed significant increases in metabolites, indicating that genes directly and indirectly involved in biosynthetic pathways likely regulate the metabolome. Therefore, this study demonstrated that wheat aneuploid lines are suitable experimental genetic system to validate metabolomics-genomics networks.

Changes in polyphenol and sugar concentrations in wild type and genetically modified Nicotiana langsdorffii Weinmann in response to water and heat stress

In this study wild type Nicotiana langsdorffii plants were genetically transformed by the insertion of the rat gene (gr) encoding the glucocorticoid receptor or the rolC gene and exposed to water and heat stress. Water stress was induced for 15 days by adding 20% PEG 6000 in the growth medium, whereas the heat treatment was performed at 50 °C for 2 h, after that a re-growing capability study was carried out. The plant response to stress was investigated by determining electrolyte leakage, dry weight biomass production and water content. These data were evaluated in relation to antiradical activity and concentrations of total polyphenols, selected phenolic compounds and some soluble sugars, as biochemical indicators of metabolic changes due to gene insertion and/or stress treatments. As regards the water stress, the measured physiological parameters evidenced an increasing stress level in the order rolC < gr < WT plants (e.g. about 100% and 50% electrolyte leakage increase in WT and gr samples, respectively) and complied with the biochemical pattern, which consisted in a general decrease of antiradical activity and phenolics, together with an increase in sugars. As regard heat stress, electrolyte leakage data were only in partial agreement with the re-growing capability study. In fact, according to this latter evaluation, gr was the genotype less affected by the heat shock. In this regard, sugars and especially phenolic compounds are informative of the long-term effects due to heat shock treatment.

The female gametophyte: an emerging model for cell type-specific systems biology in plant development

Systems biology, a holistic approach describing a system emerging from the interactions of its molecular components, critically depends on accurate qualitative determination and quantitative measurements of these components. Development and improvement of large-scale profiling methods ("omics") now facilitates comprehensive measurements of many relevant molecules. For multicellular organisms, such as animals, fungi, algae, and plants, the complexity of the system is augmented by the presence of specialized cell types and organs, and a complex interplay within and between them. Cell type-specific analyses are therefore crucial for the understanding of developmental processes and environmental responses. This review first gives an overview of current methods used for large-scale profiling of specific cell types exemplified by recent advances in plant biology. The focus then lies on suitable model systems to study plant development and cell type specification. We introduce the female gametophyte of flowering plants as an ideal model to study fundamental developmental processes. Moreover, the female reproductive lineage is of importance for the emergence of evolutionary novelties such as an unequal parental contribution to the tissue nurturing the embryo or the clonal production of seeds by asexual reproduction (apomixis). Understanding these processes is not only interesting from a developmental or evolutionary perspective, but bears great potential for further crop improvement and the simplification of breeding efforts. We finally highlight novel methods, which are already available or which will likely soon facilitate large-scale profiling of the specific cell types of the female gametophyte in both model and non-model species. We conclude that it may take only few years until an evolutionary systems biology approach toward female gametogenesis may decipher some of its biologically most interesting and economically most valuable processes.

An integrated functional approach to dissect systemic responses in maize to arbuscular mycorrhizal symbiosis

Most terrestrial plants benefit from the symbiosis with arbuscular mycorrhizal fungi (AMF) mainly under nutrient-limited conditions. Here the crop plant Zea mays was grown with and without AMF in a bi-compartmented system separating plant and phosphate (Pi) source by a hyphae-permeable membrane. Thus, Pi was preferentially taken up via the mycorrhizal Pi uptake pathway while other nutrients were ubiquitously available. To study systemic effects of mycorrhizal Pi uptake on leaf status, leaves of these plants that display an increased biomass in the presence of AMF were subjected to simultaneous ionomic, transcriptomic and metabolomic analyses. We observed robust changes of the leaf elemental composition, that is, increase of P, S and Zn and decrease of Mn, Co and Li concentration in mycorrhizal plants. Although changes in anthocyanin and lipid metabolism point to an improved P status, a global increase in C versus N metabolism highlights the redistribution of metabolic pools including carbohydrates and amino acids. Strikingly, an induction of systemic defence gene expression and concomitant accumulation of secondary metabolites such as the terpenoids alpha- and beta-amyrin suggest priming of mycorrhizal maize leaves as a mycorrhiza-specific response. This work emphasizes the importance of AM symbiosis for the physiological status of plant leaves and could lead to strategies for optimized breeding of crop species with high growth potential.

The role of proteomics in progressing insights into plant secondary metabolism

The development of omics has enabled the genome-wide exploration of all kinds of biological processes at the molecular level. Almost every field of plant biology has been analyzed at the genomic, transcriptomic and proteomic level. Here we focus on the particular contribution that proteomic technologies have made in progressing knowledge and characterising plant secondary metabolism (SM) pathways since early expectations were created 15 years ago. We analyzed how three major issues in the proteomic analysis of plant SM have been implemented in various research studies. These issues are: (i) the selection of a suitable plant material rich in secondary metabolites of interest, such as specialized tissues and organs, and in vitro cell cultures; (ii) the proteomic strategy to access target proteins, either a comprehensive or a differential analysis; (iii) the proteomic approach, represented by the hypothesis-free discovery proteomics and the hypothesis-driven targeted proteomics. We also examine to what extent the most-advanced technologies have been incorporated into proteomic research in plant SM and highlight some cutting edge techniques that would strongly benefit the progress made in this field.

Multidimensional approaches for studying plant defence against insects: from ecology to omics and synthetic biology

The biggest challenge for modern biology is to integrate multidisciplinary approaches towards understanding the organizational and functional complexity of biological systems at different hierarchies, starting from the subcellular molecular mechanisms (microscopic) to the functional interactions of ecological communities (macroscopic). The plant-insect interaction is a good model for this purpose with the availability of an enormous amount of information at the molecular and the ecosystem levels. Changing global climatic conditions are abruptly resetting plant-insect interactions. Integration of discretely located heterogeneous information from the ecosystem to genes and pathways will be an advantage to understand the complexity of plant-insect interactions. This review will present the recent developments in omics-based high-throughput experimental approaches, with particular emphasis on studying plant defence responses against insect attack. The review highlights the importance of using integrative systems approaches to study plant-insect interactions from the macroscopic to the microscopic level. We analyse the current efforts in generating, integrating and modelling multiomics data to understand plant-insect interaction at a systems level. As a future prospect, we highlight the growing interest in utilizing the synthetic biology platform for engineering insect-resistant plants.

Transcriptional Regulatory Network Analysis of MYB Transcription Factor Family Genes in Rice

MYB transcription factor (TF) is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by "top-down" and "guide-gene" approaches. More than 50% of OsMYBs were strongly correlated under 50 experimental conditions with 51 hub genes via "top-down" approach. Further, clusters were identified using Markov Clustering (MCL). To maximize the clustering performance, parameter evaluation of the MCL inflation score (I) was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by "guide-gene" approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought response in rice. Thus, the co-regulatory network analysis facilitated the identification of complex OsMYB regulatory networks, and candidate target regulon genes of selected guide MYB genes. The results contribute to the candidate gene screening, and experimentally testable hypotheses for potential regulatory MYB TFs, and their targets under stress conditions.

Plant biotechnology for lignocellulosic biofuel production

Lignocelluloses from plant cell walls are attractive resources for sustainable biofuel production. However, conversion of lignocellulose to biofuel is more expensive than other current technologies, due to the costs of chemical pretreatment and enzyme hydrolysis for cell wall deconstruction. Recalcitrance of cell walls to deconstruction has been reduced in many plant species by modifying plant cell walls through biotechnology. These results have been achieved by reducing lignin content and altering its composition and structure. Reduction of recalcitrance has also been achieved by manipulating hemicellulose biosynthesis and by overexpression of bacterial enzymes in plants to disrupt linkages in the lignin-carbohydrate complexes. These modified plants often have improved saccharification yield and higher ethanol production. Cell wall-degrading (CWD) enzymes from bacteria and fungi have been expressed at high levels in plants to increase the efficiency of saccharification compared with exogenous addition of cellulolytic enzymes. In planta expression of heat-stable CWD enzymes from bacterial thermophiles has made autohydrolysis possible. Transgenic plants can be engineered to reduce recalcitrance without any yield penalty, indicating that successful cell wall modification can be achieved without impacting cell wall integrity or plant development. A more complete understanding of cell wall formation and structure should greatly improve lignocellulosic feedstocks and reduce the cost of biofuel production.

Plant systems biology: insights, advances and challenges

Plants dwelling at the base of biological food chain are of fundamental significance in providing solutions to some of the most daunting ecological and environmental problems faced by our planet. The reductionist views of molecular biology provide only a partial understanding to the phenotypic knowledge of plants. Systems biology offers a comprehensive view of plant systems, by employing a holistic approach integrating the molecular data at various hierarchical levels. In this review, we discuss the basics of systems biology including the various 'omics' approaches and their integration, the modeling aspects and the tools needed for the plant systems research. A particular emphasis is given to the recent analytical advances, updated published examples of plant systems biology studies and the future trends.

Modeling the effects of light and sucrose on in vitro propagated plants: a multiscale system analysis using artificial intelligence technology

BACKGROUND

Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology.

METHODOLOGY AND PRINCIPAL FINDINGS

In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122-130 µmol m(-2) s(-1).

CONCLUSIONS

Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work.

Molecular and functional characterization of cold-responsive C-repeat binding factors from Brachypodium distachyon

BACKGROUND

Adverse environmental conditions severely influence various aspects of plant growth and developmental processes, causing worldwide reduction of crop yields. The C-repeat binding factors (CBFs) are critical transcription factors constituting the gene regulatory network that mediates the acclimation process to low temperatures. They regulate a large number of cold-responsive genes, including COLD-REGULATED (COR) genes, via the CBF-COR regulon. Recent studies have shown that the CBF transcription factors also play a role in plant responses to drought and salt stresses. Putative CBF gene homologues and their downstream genes are also present in the genome of Brachypodium distachyon, which is perceived as a monocot model in recent years. However, they have not been functionally characterized at the molecular level.

RESULTS

Three CBF genes that are responsive to cold were identified from Brachypodium, designated BdCBF1, BdCBF2, and BdCBF3, and they were functionally characterized by molecular biological and transgenic approaches in Brachypodium and Arabidopsis thaliana. Our results demonstrate that the BdCBF genes contribute to the tolerance response of Brachypodium to cold, drought, and salt stresses by regulating downstream targets, such as DEHYDRIN5.1 (Dhn5.1) and COR genes. The BdCBF genes are induced under the environmental stress conditions. The BdCBF proteins possess transcriptional activation activity and bind directly to the promoters of the target genes. Transgenic Brachypodium plants overexpressing the BdCBF genes exhibited enhanced resistance to drought and salt stresses as well as low temperatures, and accordingly endogenous contents of proline and soluble sugars were significantly elevated in the transgenic plants. The BdCBF transcription factors are also functional in the heterologous system Arabidopsis. Transgenic Arabidopsis plants overexpressing the BdCBF genes were also tolerant to freezing, drought, and salt stresses, and a set of stress-responsive genes was upregulated in the transgenic Arabidopsis plants.

CONCLUSIONS

Taken together, our results strongly support that the BdCBF transcription factors are key regulators of cold stress responses in Brachypodium and the CBF-mediated cold stress signaling pathway is conserved in this plant species. We believe that this study would confer great impact on stress biology in monocot species and could be applied to engineer abiotic stress tolerance of bioenergy grass species.

The low energy signaling network

Stress impacts negatively on plant growth and crop productivity, caicultural production worldwide. Throughout their life, plants are often confronted with multiple types of stress that affect overall cellular energy status and activate energy-saving responses. The resulting low energy syndrome (LES) includes transcriptional, translational, and metabolic reprogramming and is essential for stress adaptation. The conserved kinases sucrose-non-fermenting-1-related protein kinase-1 (SnRK1) and target of rapamycin (TOR) play central roles in the regulation of LES in response to stress conditions, affecting cellular processes and leading to growth arrest and metabolic reprogramming. We review the current understanding of how TOR and SnRK1 are involved in regulating the response of plants to low energy conditions. The central role in the regulation of cellular processes, the reprogramming of metabolism, and the phenotypic consequences of these two kinases will be discussed in light of current knowledge and potential future developments.

OnPLS integration of transcriptomic, proteomic and metabolomic data shows multi-level oxidative stress responses in the cambium of transgenic hipI- superoxide dismutase Populus plants

BACKGROUND

Reactive oxygen species (ROS) are involved in the regulation of diverse physiological processes in plants, including various biotic and abiotic stress responses. Thus, oxidative stress tolerance mechanisms in plants are complex, and diverse responses at multiple levels need to be characterized in order to understand them. Here we present system responses to oxidative stress in Populus by integrating data from analyses of the cambial region of wild-type controls and plants expressing high-isoelectric-point superoxide dismutase (hipI-SOD) transcripts in antisense orientation showing a higher production of superoxide. The cambium, a thin cell layer, generates cells that differentiate to form either phloem or xylem and is hypothesized to be a major reason for phenotypic perturbations in the transgenic plants. Data from multiple platforms including transcriptomics (microarray analysis), proteomics (UPLC/QTOF-MS), and metabolomics (GC-TOF/MS, UPLC/MS, and UHPLC-LTQ/MS) were integrated using the most recent development of orthogonal projections to latent structures called OnPLS. OnPLS is a symmetrical multi-block method that does not depend on the order of analysis when more than two blocks are analysed. Significantly affected genes, proteins and metabolites were then visualized in painted pathway diagrams.

RESULTS

The main categories that appear to be significantly influenced in the transgenic plants were pathways related to redox regulation, carbon metabolism and protein degradation, e.g. the glycolysis and pentose phosphate pathways (PPP). The results provide system-level information on ROS metabolism and responses to oxidative stress, and indicate that some initial responses to oxidative stress may share common pathways.

CONCLUSION

The proposed data evaluation strategy shows an efficient way of compiling complex, multi-platform datasets to obtain significant biological information.

Navigating the transcriptional roadmap regulating plant secondary cell wall deposition

The current status of lignocellulosic biomass as an invaluable resource in industry, agriculture, and health has spurred increased interest in understanding the transcriptional regulation of secondary cell wall (SCW) biosynthesis. The last decade of research has revealed an extensive network of NAC, MYB and other families of transcription factors regulating Arabidopsis SCW biosynthesis, and numerous studies have explored SCW-related transcription factors in other dicots and monocots. Whilst the general structure of the Arabidopsis network has been a topic of several reviews, they have not comprehensively represented the detailed protein-DNA and protein-protein interactions described in the literature, and an understanding of network dynamics and functionality has not yet been achieved for SCW formation. Furthermore the methodologies employed in studies of SCW transcriptional regulation have not received much attention, especially in the case of non-model organisms. In this review, we have reconstructed the most exhaustive literature-based network representations to date of SCW transcriptional regulation in Arabidopsis. We include a manipulable Cytoscape representation of the Arabidopsis SCW transcriptional network to aid in future studies, along with a list of supporting literature for each documented interaction. Amongst other topics, we discuss the various components of the network, its evolutionary conservation in plants, putative modules and dynamic mechanisms that may influence network function, and the approaches that have been employed in network inference. Future research should aim to better understand network function and its response to dynamic perturbations, whilst the development and application of genome-wide approaches such as ChIP-seq and systems genetics are in progress for the study of SCW transcriptional regulation in non-model organisms.

Application of an improved proteomics method for abundant protein cleanup: molecular and genomic mechanisms study in plant defense

High abundance proteins like ribulose-1,5-bisphosphate carboxylase oxygenase (Rubisco) impose a consistent challenge for the whole proteome characterization using shot-gun proteomics. To address this challenge, we developed and evaluated Polyethyleneimine Assisted Rubisco Cleanup (PARC) as a new method by combining both abundant protein removal and fractionation. The new approach was applied to a plant insect interaction study to validate the platform and investigate mechanisms for plant defense against herbivorous insects. Our results indicated that PARC can effectively remove Rubisco, improve the protein identification, and discover almost three times more differentially regulated proteins. The significantly enhanced shot-gun proteomics performance was translated into in-depth proteomic and molecular mechanisms for plant insect interaction, where carbon re-distribution was used to play an essential role. Moreover, the transcriptomic validation also confirmed the reliability of PARC analysis. Finally, functional studies were carried out for two differentially regulated genes as revealed by PARC analysis. Insect resistance was induced by over-expressing either jacalin-like or cupin-like genes in rice. The results further highlighted that PARC can serve as an effective strategy for proteomics analysis and gene discovery.

Towards systems biological understanding of leaf senescence

The application of systems biology approaches has greatly facilitated the process of deciphering the molecular mechanisms underlying leaf senescence. Analyses of the leaf senescence transcriptome have identified some of the major biochemical events during senescence including protein degradation and nutrient remobilization. Proteomic studies have confirmed these findings and have suggested up-regulated energy metabolism during leaf senescence which might be important for cell viability maintenance. As a critical part of systems biology, studies involving transcription regulation networking and senescence-inducing signaling have deepened our understanding on the molecular regulation of leaf senescence. The important next steps towards a systems biological understanding of leaf senescence will be discussed.