Comprehensive phenotyping reveals interactions and functions of Arabidopsis thaliana TCP genes in yield determination

Exploring the Structure and Substance Metabolism of a Medicago sativa L. Stem Base

The stem base of alfalfa is a critical part for its overwintering, regeneration, and yield. To better understand the specificity and importance of the stem base, we analyzed the structure, metabolic substances, and transcriptome of the stem base using anatomical techniques, ultra-high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS), and RNA sequencing (RNA-seq), and compared it with stems and roots. The anatomical structure shows that the ratio of xylem to phloem changes at the base of the stem. A total of 801 compounds involved in 91 metabolic pathways were identified from the broadly targeted metabolome. Transcriptome analysis revealed 4974 differentially expressed genes (DEGs) at the stem base compared to the stem, and 5503 DEGs compared to the root. Comprehensive analyses of differentially accumulated compounds (DACs) and DEGs, in the stem base vs. stem, identified 10 valuable pathways, including plant hormone signal transduction, zeatin biosynthesis, α-Linolenic acid metabolism, histidine metabolism, carbon metabolism, carbon fixation in photosynthetic organisms, pentose phosphate pathway, galactose metabolism, and fructose and mannose metabolism. The pathways of plant hormone signal transduction and carbon metabolism were also identified by comparing the stem base with the roots. Taken together, the stem base of alfalfa is the transition region between the stem and root in morphology; in terms of material metabolism, its growth, development, and function are regulated through hormones and sugars.

Genome-wide identification and expression analysis of TCP family genes in Catharanthus roseus

Introduction

The anti-tumor vindoline and catharanthine alkaloids are naturally existed in Catharanthus roseus (C. roseus), an ornamental plant in many tropical countries. Plant-specific TEOSINTE BRANCHED1/CYCLOIDEA/PCF (TCP) transcription factors play important roles in various plant developmental processes. However, the roles of C. roseus TCPs (CrTCPs) in terpenoid indole alkaloid (TIA) biosynthesis are largely unknown.

Methods

Here, a total of 15 CrTCP genes were identified in the newly updated C. roseus genome and were grouped into three major classes (P-type, C-type and CYC/TB1).

Results

Gene structure and protein motif analyses showed that CrTCPs have diverse intron-exon patterns and protein motif distributions. A number of stress responsive cis-elements were identified in promoter regions of CrTCPs. Expression analysis showed that three CrTCP genes (CrTCP2, CrTCP4, and CrTCP7) were expressed specifically in leaves and four CrTCP genes (CrTCP13, CrTCP8, CrTCP6, and CrTCP10) were expressed specifically in flowers. HPLC analysis showed that the contents of three classic TIAs, vindoline, catharanthine and ajmalicine, were significantly increased by ultraviolet-B (UV-B) and methyl jasmonate (MeJA) in leaves. By analyzing the expression patterns under UV-B radiation and MeJA application with qRT-PCR, a number of CrTCP and TIA biosynthesis-related genes were identified to be responsive to UV-B and MeJA treatments. Interestingly, two TCP binding elements (GGNCCCAC and GTGGNCCC) were identified in several TIA biosynthesis-related genes, suggesting that they were potential target genes of CrTCPs.

Discussion

These results suggest that CrTCPs are involved in the regulation of the biosynthesis of TIAs, and provide a basis for further functional identification of CrTCPs.

Evolutionary analyses and expression patterns of TCP genes in Ranunculales

TCP transcription factors play a role in a large number of developmental processes and are at the crossroads of numerous hormonal biosynthetic and signaling pathways. The complete repertoire of TCP genes has already been characterized in several plant species, but not in any species of early diverging eudicots. We focused on the order Ranunculales because of its phylogenetic position as sister group to all other eudicots and its important morphological diversity. Results show that all the TCP genes expressed in the floral transcriptome of Nigella damascena (Ranunculaceae) are the orthologs of the TCP genes previously identified from the fully sequenced genome of Aquilegia coerulea. Phylogenetic analyses combined with the identification of conserved amino acid motifs suggest that six paralogous genes of class I TCP transcription factors were present in the common ancestor of angiosperms. We highlight independent duplications in core eudicots and Ranunculales within the class I and class II subfamilies, resulting in different numbers of paralogs within the main subclasses of TCP genes. This has most probably major consequences on the functional diversification of these genes in different plant clades. The expression patterns of TCP genes in Nigella damascena were consistent with the general suggestion that CIN and class I TCP genes may have redundant roles or take part in same pathways, while CYC/TB1 genes have more specific actions. Our findings open the way for future studies at the tissue level, and for investigating redundancy and subfunctionalisation in TCP genes and their role in the evolution of morphological novelties.

Genetic dissection of morphological variation in rosette leaves and leafy heads in cabbage (Brassica oleracea var. capitata)

Correlations between morphological traits of cabbage rosette leaves and heads were found. Genome-wide association studies of these traits identified 50 robust quantitative trait loci in multiple years. Half of these loci affect both organs. Cabbage (Brassica oleracea var. capitata) is an economically important vegetable crop cultivated worldwide. Cabbage plants go through four vegetative stages: seedling, rosette, folding and heading. Rosette leaves are the largest leaves of cabbage plants and provide most of the energy needed to produce the leafy head. To understand the relationship and the genetic basis of leaf development and leafy head formation, 308 cabbage accessions were scored for rosette leaf and head traits in three-year field trials. Significant correlations were found between morphological traits of rosette leaves and heads, namely leaf area with the head area, height and width, and leaf width with the head area and head height, when heads were harvested at a fixed number of days after sowing. Fifty robust quantitative trait loci (QTLs) for rosette leaf and head traits distributed over all nine chromosomes were identified with genome-wide association studies. All these 50 loci were identified in multiple years and generally affect multiple traits. Twenty-five of the QTL were associated with both rosette leaf and leafy head traits. We discuss thirteen candidate genes identified in these QTL that are expressed in heading leaves, with an annotation related to auxin and other phytohormones, leaf development, and leaf polarity that likely play a role in leafy head development or rosette leaf expansion.

Genome-Wide Analysis of the TCP Gene Family and Their Expression Pattern Analysis in Tea Plant (Camellia sinensis)

TEOSINTE BRANCHED1/CYCLOIDEA/PCF (TCP) transcription factors TEOSINTE BRANCHED1/CYCLOIDEA/PCF have been suggested to control the cell growth and proliferation in meristems and lateral organs. A total of 37 CsTCP genes were identified and divided into two classes, class I (PCF, group 1) and class II (CIN CYC/TB1, groups 2, and 3). The residues of TEOSINTE BRANCHED1/CYCLOIDEA/PCF of Camellia sinensis (Tea plant) (CsTCP) proteins between class I and class II were definitely different in the loop, helix I, and helix II regions; however, eighteen conserved tandem was found in bHLH. There are a large number of CsTCP homologous gene pairs in three groups. Additionally, most CsTCP proteins have obvious differences in motif composition. The results illuminated that CsTCP proteins in different groups are supposed to have complementary functions, whereas those in the same class seem to display function redundancies. There is no relationship between the number of CsTCP gene members and genome size, and the CsTCP gene family has only expanded since the divergence of monocots and eudicots. WGD/segmental duplication played a vital role in the expansion of the CsTCP gene family in tea plant, and the CsTCP gene family has expanded a lot. Most CsTCP genes of group 1 are more widely and non-specifically expressed, and the CsTCP genes of group 2 are mainly expressed in buds, flowers, and leaves. Most genes of group 1 and some genes of group 2 were up-/downregulated in varying degrees under different stress, CsTCP genes of group 3 basically do not respond to stress. TCP genes involved in abiotic stress response mostly belong to PCF group. Some CsTCP genes may have the same function as the homologous genes in Arabidopsis, but there is functional differentiation.

Genome-wide TCP transcription factors analysis provides insight into their new functions in seasonal and diurnal growth rhythm in Pinus tabuliformis

BACKGROUND

Pinus tabuliformis adapts to cold climate with dry winter in northern China, serving as important commercial tree species. The TEOSINTE BRANCHED 1, CYCLOIDEA, and PROLIFERATING CELL FACTOR family(TCP)transcription factors were found to play a role in the circadian clock system in Arabidopsis. However, the role of TCP transcription factors in P. tabuliformis remains little understood.

RESULTS

In the present study, 43 TCP genes were identified from P. tabuliformis genome database. Based on the phylogeny tree and sequence similarity, the 43 TCP genes were classified into four groups. The motif results showed that different subfamilies indeed contained different motifs. Clade II genes contain motif 1, clade I genes contain motif 1, 8, 10 and clade III and IV contain more motifs, which is consistent with our grouping results. The structural analysis of PtTCP genes showed that most PtTCPs lacked introns. The distribution of clade I and clade II on the chromosome is relatively scattered, while clade III and clade IV is relatively concentrated. Co-expression network indicated that PtTCP2, PtTCP12, PtTCP36, PtTCP37, PtTCP38, PtTCP41 and PtTCP43 were co-expressed with clock genes in annual cycle and their annual cycle expression profiles both showed obvious seasonal oscillations. PtTCP2, PtTCP12, PtTCP37, PtTCP38, PtTCP40, PtTCP41, PtTCP42 and PtTCP43 were co-expressed with clock genes in diurnal cycle. Only the expression of PtTCP42 showed diurnal oscillation.

CONCLUSIONS

The TCP gene family, especially clade II, may play an important role in the regulation of the season and circadian rhythm of P. tabuliformis. In addition, the low temperature in winter may affect the diurnal oscillations.

CIN-like TCP13 is essential for plant growth regulation under dehydration stress

A dehydration-inducible Arabidopsis CIN-like TCP gene, TCP13, acts as a key regulator of plant growth in leaves and roots under dehydration stress conditions. Plants modulate their shape and growth in response to environmental stress. However, regulatory mechanisms underlying the changes in shape and growth under environmental stress remain elusive. The CINCINNATA (CIN)-like TEOSINTE BRANCHED1/CYCLOIDEA/PCF (TCP) family of transcription factors (TFs) are key regulators for limiting the growth of leaves through negative effect of auxin response. Here, we report that stress-inducible CIN-like TCP13 plays a key role in inducing morphological changes in leaves and growth regulation in leaves and roots that confer dehydration stress tolerance in Arabidopsis thaliana. Transgenic Arabidopsis plants overexpressing TCP13 (35Spro::TCP13OX) exhibited leaf rolling, and reduced leaf growth under osmotic stress. The 35Spro::TCP13OX transgenic leaves showed decreased water loss from leaves, and enhanced dehydration tolerance compared with their control counterparts. Plants overexpressing a chimeric repressor domain SRDX-fused TCP13 (TCP13pro::TCP13SRDX) showed severely serrated leaves and enhanced root growth. Transcriptome analysis of TCP13pro::TCP13SRDX transgenic plants revealed that TCP13 affects the expression of dehydration- and abscisic acid (ABA)-regulated genes. TCP13 is also required for the expression of dehydration-inducible auxin-regulated genes, INDOLE-3-ACETIC ACID5 (IAA5) and LATERAL ORGAN BOUNDARIES (LOB) DOMAIN 1 (LBD1). Furthermore, tcp13 knockout mutant plants showed ABA-insensitive root growth and reduced dehydration-inducible gene expression. Our findings provide new insight into the molecular mechanism of CIN-like TCP that is involved in both auxin and ABA response under dehydration stress.

TCP7 interacts with Nuclear Factor-Ys to promote flowering by directly regulating SOC1 in Arabidopsis

The success of plant reproduction depends on the timely transition from the vegetative phase to reproductive growth, a process often referred to as flowering. Although several plant-specific transcription factors belonging to the Teosinte Branched 1/Cycloidea/Proliferating Cell Factor (TCP) family are reportedly involved in the regulation of flowering in Arabidopsis, the molecular mechanisms, especially for Class I TCP members, are poorly understood. Here, we genetically identified Class I TCP7 as a positive regulator of flowering time. Protein interaction analysis indicated that TCP7 interacted with several Nuclear Factor-Ys (NF-Ys), known as the 'pioneer' transcription factors; CONSTANS (CO), a main photoperiod regulator of flowering. SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1) was differentially expressed in the dominant-negative mutant of TCP7 (lcu) and the loss-of-function mutant of Class I TCP members (septuple). Additionally, we obtained genetic and molecular evidence showing that TCP7 directly activates the flowering integrator gene, SOC1. Moreover, TCP7 synergistically activated SOC1 expression upon interacting with CO and NF-Ys in vivo. Collectively, our results provide compelling evidence that TCP7 synergistically interacts with NF-Ys to activate the transcriptional expression of the flowering integrator gene SOC1.

Time-Series Growth Prediction Model Based on U-Net and Machine Learning in Arabidopsis

Yield prediction for crops is essential information for food security. A high-throughput phenotyping platform (HTPP) generates the data of the complete life cycle of a plant. However, the data are rarely used for yield prediction because of the lack of quality image analysis methods, yield data associated with HTPP, and the time-series analysis method for yield prediction. To overcome limitations, this study employed multiple deep learning (DL) networks to extract high-quality HTTP data, establish an association between HTTP data and the yield performance of crops, and select essential time intervals using machine learning (ML). The images of Arabidopsis were taken 12 times under environmentally controlled HTPP over 23 days after sowing (DAS). First, the features from images were extracted using DL network U-Net with SE-ResXt101 encoder and divided into early (15-21 DAS) and late (∼21-23 DAS) pre-flowering developmental stages using the physiological characteristics of the Arabidopsis plant. Second, the late pre-flowering stage at 23 DAS can be predicted using the ML algorithm XGBoost, based only on a portion of the early pre-flowering stage (17-21 DAS). This was confirmed using an additional biological experiment (P < 0.01). Finally, the projected area (PA) was estimated into fresh weight (FW), and the correlation coefficient between FW and predicted FW was calculated as 0.85. This was the first study that analyzed time-series data to predict the FW of related but different developmental stages and predict the PA. The results of this study were informative and enabled the understanding of the FW of Arabidopsis or yield of leafy plants and total biomass consumed in vertical farming. Moreover, this study highlighted the reduction of time-series data for examining interesting traits and future application of time-series analysis in various HTPPs.

Identification of a consensus DNA-binding site for the TCP domain transcription factor TCP2 and its important roles in the growth and development of Arabidopsis

TEOSINTE BRANCHED 1/CYCLOIDEA/PROLIFERATING CELL FACTOR 1 (TCP) transcription factors control multiple aspects of growth and development in various plant species. However, few genes were reported to be directly targeted and regulated by them through their specific binding sites, and then uncover their functions in plants. A consensus DNA-binding site motif of TCP2 was identified by random binding site selection (RBSS). DNA recognized by TCP2 contained the motif G(G/T)GGNCC(A/C), which showed high consistency with motifs bound by other TCP domain proteins. Consequently, this motif was regarded as the specific DNA-binding sites of TCP2. Circadian clock associated 1 (CCA1) and EARLY FLOWERING 3 (ELF3) were subsequently considered as potential target genes owing to the containing of the similar TCP2 binding sites or core binding sites GGNCC and found to be positively regulated by TCP2 via DNA binding. Phenotype analysis results showed that mutation and over-expression of TCP2 resulted in variations in leaf morphogenesis, especially the double or triple mutations of TCP2, 4 and 10. Mutations in TCPs caused late flowering. Finally, TCP2 was shown to influence hypocotyl elongation by mediating the jasmonate signaling pathway. Overall, these results provide a basis for future studies aimed at distinguishing the target genes of TCP2 and elucidating the important roles of TCP2 in plant growth and development.

Machine learning in plant science and plant breeding

Technological developments have revolutionized measurements on plant genotypes and phenotypes, leading to routine production of large, complex data sets. This has led to increased efforts to extract meaning from these measurements and to integrate various data sets. Concurrently, machine learning has rapidly evolved and is now widely applied in science in general and in plant genotyping and phenotyping in particular. Here, we review the application of machine learning in the context of plant science and plant breeding. We focus on analyses at different phenotype levels, from biochemical to yield, and in connecting genotypes to these. In this way, we illustrate how machine learning offers a suite of methods that enable researchers to find meaningful patterns in relevant plant data.

High-Throughput Phenotyping (HTP) Data Reveal Dosage Effect at Growth Stages in Arabidopsis thaliana Irradiated by Gamma Rays

The effects of radiation dosages on plant species are quantitatively presented as the lethal dose or the dose required for growth reduction in mutation breeding. However, lethal dose and growth reduction fail to provide dynamic growth behavior information such as growth rate after irradiation. Irradiated seeds of Arabidopsis were grown in an environmentally controlled high-throughput phenotyping (HTP) platform to capture growth images that were analyzed with machine learning algorithms. Analysis of digital phenotyping data revealed unique growth patterns following treatments below LD50 value at 641 Gy. Plants treated with 100-Gy gamma irradiation showed almost identical growth pattern compared with wild type; the hormesis effect was observed >21 days after sowing. In 200 Gy-treated plants, a uniform growth pattern but smaller rosette areas than the wild type were seen (p < 0.05). The shift between vegetative and reproductive stages was not retarded by irradiation at 200 and 300 Gy although growth inhibition was detected under the same irradiation dose. Results were validated using 200 and 300 Gy doses with HTP in a separate study. To our knowledge, this is the first study to apply a HTP platform to measure and analyze the dosage effect of radiation in plants. The method enabled an in-depth analysis of growth patterns, which could not be detected previously due to a lack of time-series data. This information will improve our knowledge about the effects of radiation in model plant species and crops.

Transcriptome profiling of kenaf (Hibiscus cannabinus L.) under plumbic stress conditions implies the involvement of NAC transcription factors regulating reactive oxygen species-dependent programmed cell death

Heavy metal contamination of soils has become a serious global issue, and bioremediation has been proposed as a potential solution. Kenaf (Hibiscus cannabinus L.) is a fast growing, non-woody multipurpose annual plant that is suitable for removing excess heavy metals from soils. However, there has been relatively little research on the kenaf molecular mechanisms induced in response to an exposure to heavy metal stress. Thus, whole kenaf seedlings grown under control (normal) and stress (plumbic treatment) conditions were sampled for transcriptome sequencing. Unigenes generated through the de novo assembly of clean reads were functionally annotated based on seven databases. Transcription factor (TF)-coding genes were predicted and the physiological traits of the seedlings were analyzed. A total of 44.57 Gb high-quality sequencing data were obtained, which were assembled into 136,854 unigenes. These unigenes included 1,697 that were regarded as differentially expressed genes (DEGs). A GO enrichment analysis of the DEGs indicated that many of them are related to catalytic activities. Moreover, the DEGs appeared to suggest that numerous KEGG pathways are suppressed (e.g., the photosynthesis-involving pathways) or enhanced (like the flavonoid metabolism pathways) in response to Pb stress. Of the 2,066 predicted TF-coding genes, only 55 were differentially expressed between the control and stressed samples. Further analyses suggested that the plumbic stress treatment induced reactive oxygen species-dependent programmed cell death in the kenaf plants via a process that may be regulated by the differentially expressed NAC TF genes.

Overexpression of TCP8 delays Arabidopsis flowering through a FLOWERING LOCUS C-dependent pathway

BACKGROUND

Flowering is a key process in the life cycle of plants. The transition from vegetative to reproductive growth is thus under sophisticated regulation by endogenous and environmental signals. The plant-specific Teosinte Branched 1/Cycloidea/Proliferating Cell Factors (TCP) family transcription factors are involved in many biological processes, but their roles in regulating flowering have not been totally elucidated.

RESULTS

We explored the role of Arabidopsis TCP8 in plant development and, especially, in flowering control. Overexpression of TCP8 significantly delayed flowering under both long-day and short-day conditions and dominant repression by TCP8 led to various growth defects. The upregulation of TCP8 led to more accumulated mRNA level of FLOWERING LOCUS C (FLC), a central floral repressor of Arabidopsis. TCP8 functions in an FLC-dependent manner, as TCP8 overexpression in the flc-6 loss-of-function mutant failed to delay flowering. The vernalization treatment could reverse the late flowering phenotype caused by TCP8 overexpression.

CONCLUSIONS

Our results provide evidence for a role of TCP8 in flowering control and add to our knowledge of the molecular basis of TCP8 function.

Transcription Factor Networks in Leaves of Cichorium endivia: New Insights into the Relationship Between Photosynthesis and Leaf Development

Cichorium endivia is a leafy crop closely related to Lactuca sativa that comprises two major botanical varieties characterized by a high degree of intraspecific morphological variation: var. latifolium with broad leaves (escarole) and var. crispum with narrow crisp curly leaves (endive). To investigate the relationship between leaf morphology and photosynthetic activity, escaroles and endives were used as a crop model due to the striking morphological diversity of their leaves. We constructed a leaf database for transcription factors (TFs) and photosynthesis-related genes from a refined C. endivia transcriptome and used RNA-seq transcriptomic data from leaves of four commercial endive and escarole cultivars to explore transcription factor regulatory networks. Cluster and gene co-expression network (GCN) analyses identified two main anticorrelated modules that control photosynthesis. Analysis of the GCN network topological properties identified known and novel hub genes controlling photosynthesis, and candidate developmental genes at the boundaries between shape and function. Differential expression analysis between broad and curly leaves suggested three novel TFs putatively involved in leaf shape diversity. Physiological analysis of the photosynthesis properties and gene expression studies on broad and curly leaves provided new insights into the relationship between leaf shape and function.