For the identification of putative soybean ELF4 genes and proteins, the corresponding Arabidopsis ELF4 protein sequence (encoded by AT2G40080) was used as a query in BLAST searches (TBLASTN tool) (Altschul et al., 1990) of the G. max genome version Wm82.a2.v1, available from the Phytozome database¹, using a cutoff Expect value (E-value) of 1E-12. The soybean ELF4 genes and proteins are representative of the respective gene model ‘Glymas.’ The ELF4 homologous proteins in plant species were searched for in the NCBI protein database², using keyword searches and are represented by their respective GenInfo Identifier number (GI number).

Phylogenetic relationships between the soybean and other plant ELF4 proteins were considered. For this purpose, after removing the redundancy, the amino acid sequences were subjected to global alignment using the ClustalW algorithm from the Molecular Evolutionary Genetics Analysis version 5.0 (MEGA 5) software package (Tamura et al., 2011), and a phylogenetic tree was constructed using the neighbor-joining (NJ) method with the following parameters: Poisson correction, pairwise deletion and bootstrap (1000 replicates; random seed). Given that the functional domains have importance for the function and classification of ELF4 proteins, the conserved amino acid domains of the ELF4 proteins were analyzed using the motif discovery tool MEME program version 4.11.2³.

In a previous study, we identified a GmELF4 candidate gene Glyma.18G027500 (former Glyma18g03130) and showed its daily expression pattern of mRNA using RT-qPCR (Marcolino-Gomes et al., 2014). In the present study, the gene expression patterns of all ELF4 soybean paralogous genes were assessed through analysis of an RNA-Seq database⁴, built from soybean plants of the BR16 genotype (Rodrigues et al., 2015). Plants were grown in 14 h light/10 h dark cycles, with 500 μmol m^-2 s^-1 of white light (provided by cool white fluorescent bulbs), under 28°C/20°C temperature cycles during the light and the dark periods, respectively. Sampling was performed 15 days after germination, when the plants reached the V2 developmental stage (Fehr et al., 1971), at which fully expanded V1 leaves were collected from the three plants at 4-h intervals from the time the lights came on [Zeitgeiber time (ZT) 0].

Total RNA was extracted from leaves using the RNA Plant Reagent^® according to the manufacturer’s instructions (Ambion, Austin, TX, USA) and treated with DNAse (Invitrogen, Carlsbad, CA, USA). High-quality total RNA (RIN ≥ 8.0) was used to analyze the transcripts for each time point: ZT0, 4, 8, 12, 16, and 20. Equimolar quantities of purified total RNA samples from two independent biological replicates were pooled into one template for library synthesis. For each time period/treatment, three independent libraries were synthesized. The RNA-Seq libraries were built using the NuGEN OvationH kit according to the manufacturer’s instructions (NuGEN Technologies, Inc., San Carlos, CA, USA). The libraries obtained were subjected to sequencing by an Illumina HiSeq 2000 system (Illumina, San Diego, CA, USA), using the paired-end mode. Mapping of the reads was performed with the soybean genome (Phytozome Glycine max version 1.1) using the GeneSifter platform⁵. To compare gene expression profiles between different times and treatments (control and drought stress), we log₂-transformed the normalized reads [mapped reads per million (RPM)]. The gene expression data obtained at the RNA-seq analyses was validated by qPCR (Rodrigues et al., 2015).

The coding sequence (CDS) of the GmELF4 gene (Glyma.18G027500) was amplified from genomic DNA from soybean (genotype Williams 82) by PCR reactions using the specific 5′-CACCATGGAAGACCCCTC-3′ and 5′-TTATTTGGAGGAGTTTTTGGAG-3′ forward and reverse primers, respectively, and the Platinum^® Taq DNA Polymerase High Fidelity (ThermoFisher Scientific, Waltham, MA, USA). The sequence 5′-CACC-3′ was added to the 5′ upstream region of the forward primer to ensure directional subcloning of the CDS with the pENTR^TM/D-TOPO^® (ThermoFisher Scientific, Waltham, MA, USA) entry vector. After confirmation by sequencing, the GmELF4 CDS was transferred to the destination overexpression vector p^∗7WG2D (Karimi et al., 2002) using the Invitrogen^TM Gateway^TM recombination cloning system (ThermoFisher Scientific, Waltham, MA, USA). With the p^∗7WG2D binary vector, the GmELF4 CDS is constitutively expressed due the effect of the Cauliflower mosaic virus 35S (CaMV35S) promoter. In addition, the construct cassette harbors a rolD promoter fused to the CDS of the enhanced green-fluorescent protein (GFP) linked to an endoplasmic reticulum-targeting signal (pRolD-EgfpER-T35S), used as a fluorescence marker (Karimi et al., 2002).

The resultant gene construct was used for Arabidopsis thaliana ecotype Columbia (Col-0) transformation mediated by Agrobacterium tumefaciens (strain GV 3101) using the floral dip method (Zhang et al., 2006). Seeds were screened in 1% agar containing Murashige and Skoog (MS) medium containing 15 μg mL^-1 hygromycin B, as described by Harrison et al. (2006). Hygromycin-resistant plants were confirmed via PCR using specific primers for the gene construct (described above). Since the selection of transgenic lines with low T-DNA copy number is advised to prevent transgene silencing, in our study, we carefully evaluated the T-DNA segregation during three generations, selecting lines that presented Mendelian inheritance for a single characteristic [three transformed plants: one wild-type (WT); 3:1], which would carry just one copy of the transgene. Three independent T3 homozygous lines containing a single copy of the transgene were obtained for further analysis.

The development of plants from three transgenic lines was monitored in growth chambers with controlled temperature (22 ± 2°C) and relative humidity (50 ± 10%). Plants were cultivated under LD and SD conditions, with 16 and 10 h of light, respectively. After plant emergence, the rosette leaf numbers, flowering time and progression of silique formation were monitored weekly. Each line was evaluated via 10 biological replicates. Transgenic plants developmental features were compared to those of non-transformed plants (WT) in both photoperiodic conditions.

Green-fluorescent protein fluorescence was evaluated in leaves and roots of 5-day-old plants. Fresh tissue was analyzed with an Axio Scope A1 microscope (Zeiss, Oberkochen, Germany) equipped with a GFP filter (Zeiss filter set 38; Zeiss) coupled to a charge-coupled device (CCD) camera (Motic, Causeway Bay, Hong Kong) for image acquisition Image was captured using Motic Image Plus version 2.0 software (Motic, Causeway Bay, Hong Kong) with the following parameters: exposure = 500, gain = 2.38, gamma = 0.10/191 and size = 2592 × 1944 pixels. The image was magnified by a factor of 100x, which corresponds to the product of the objective magnification (10x) and the eyepiece lens (10x).

Image analysis for GFP quantitation was performed with ImageJ software version 1.51 h⁶. In this analysis, images were converted to 32-bit type and the mean gray values were measured using the ROI analysis tool. The mean gray values of WT plants were used for background normalization of GFP intensity in transgenic plants, generating the relative intensity values. A total of 30 independent sample areas were analyzed in each image.

The overexpression of GmELF4 (Glyma.18G027500) and the expression of the Arabidopsis flowering genes AtFT (AT1G65480) and AtCO (AT5G15840) were evaluated in transgenic Arabidopsis via RT-qPCR assays.

Primers for GmELF4 (forward 5′-TGATTCAGCAGGTGAACGAG-3′ and reverse 5′-GACAACCTTGGAGATGTTGC-3′) were designed with the Primer3 Plus online tool (Rozen and Skaletsky, 1999)⁷, based on the Glyma.18G027500.1 transcript sequence⁸. The Arabidopsis AtCO and AtFT primer sequences were retrieved from Ito et al. (2012).

Gene expression was evaluated in rosette leaves of three independent transgenic lines and in WT plants, cultivated in LD and SD conditions, with 16 and 10 h of light, respectively. For RNA extraction, each replicate tissue was ground to a fine powder in liquid nitrogen, and total RNA was isolated using TRIzol reagent (Invitrogen), according to the manufacturer’s instructions. Contaminating DNA in the total RNA was removed using a TURBO DNA-free Kit, according to the manufacturer’s instructions (Life Technologies, Grand Island, NY, USA). High-quality total mRNA was used to synthesize cDNA strands (Superscript III First Strand Synthesis, Invitrogen/Life Technologies, Grand Island, NY, USA). The quality of the cDNA and contamination with genomic DNA were examined using a standard PCR assay with primers that spanned an intronic region of the β-ACTIN Arabidopsis gene (AT5G09810). High-quality cDNA was used to analyze the transcripts in each treatment.

RT-qPCR amplifications were performed in a 7300 RT-qPCR Thermocycler (Applied Biosystems/Life Technologies, Grand Island, NY, USA) with the following cycling parameters: 50°C for 2 min; 95°C for 10 min; and 45 cycles of 95°C for 2 min, 60°C for 30 s and 72°C for 30 s. Standard curves were produced from serial dilutions of a cDNA pool to estimate the efficiency of the PCR amplification with each pair of primers. The primer concentrations were adjusted to achieve efficiency rates higher than 85%.

After carrying out the efficiency analysis, the expression levels of the transgene (GmELF4) and flowering genes (AtFT and AtCO) were analyzed separately in transgenic and WT plants, cultivated in LD and SD conditions. The reactions were performed in triplicate, with cycling parameters similar to those described above for the amplification efficiency analysis. Expression of target genes was normalized using the Arabidopsis endogenous gene PP2A (AT1G13320) (forward primer 5′-ACGTGGCCAAAATGATGCAA-3′ and reverse primer 5′-TCATGTTCTCCACAACCGCT-3′). The flowering genes (AtFT and AtCO) relative expression was calibrated using WT plants grown under the same environmental conditions. The gene expression analysis was performed using the Rest2009 software package version 2.0.13 (Pfaffl et al., 2002).

The GmELF4 gene co-expression regulatory network was evaluated with the Soybean Functional Genomics Database (SFGD) platform (Yu et al., 2014). The SFGD database contains microarray gene expression profiles of 255 samples from experiments of 14 groups and mRNA-Seq data of 30 samples from experiments of four groups, including spatial and temporal transcriptome data for different soybean developmental stages and environmental stresses, providing a robust database for functional analysis of genes of interest. This platform is publically accessible⁹. Pearson’s correlation coefficients (PCCs) and mutual rank (MR) for gene co-expression (Obayashi and Kinoshita, 2009) were used to construct the GmELF4 network. A table including the top 50 genes with the greatest MR values was constructed. The Cytoscape Web software program version 3.4.0 (Lopes et al., 2011) was used to display the GmELF4 (central node) and all its co-expression genes, sorted according to MR values.

In this study, the soybean ELF4 candidate genes were identified using Arabidopsis ELF4 coding-sequences for in silico searches of the soybean genome. Nine GmELF4-like genes were identified (Glyma.07G037300, Glyma.09G067300, Glyma.18G027500, Glyma.11G229700, Glyma.13G108600, Glyma.14G193700, Glyma.15G176300, Glyma.16G006700, and Glyma.17G050800). To establish the relationships between the soybean ELF4 candidates and ELF4 proteins of Arabidopsis and other plants, we performed global alignments, followed by phylogenetic analysis and construction of a phylogenetic tree (Figure 1). This tree indicates three large groups of ELF4 proteins. The soybean proteins encoded by GmELF4-like2 genes are gathered into group 1 with the Arabidopsis ELF4-like2, ELF4-like3, and ELF-like4 as well as with ELF4-like proteins from several other organisms. In group 2, the soybean ELF4 proteins encoded by Glyma.11G229700 and Glyma.18G027500 show close relation to the Arabidopsis ELF4 major protein (AT2G40080) (Figure 1). Group 3 constitutes the ELF4-like1 proteins from Arabidopsis, soybean and other plants (Figure 1).

Considering the importance of the functional domain for the classification and for investigating more deeply the putative function of the soybean candidates of ELF4, we performed a motif analysis of nine soybean ELF4 proteins together with 30 other plant ELF4 proteins (Figure 2). Our analysis revealed the presence of a DUF1313 motif conserved in all 39 ELF4 proteins, including the soybean ELF4 candidate genes Glyma.11G229700 and Glyma.18G027500. The Arabidopsis ELF 4 belongs to the DUF1313 family, whose members are divided into three major types, according to the substitution of four amino acid residues: IARV type, I(S/T/F)(K/R)V type and IRRV type, where the IRRV type is the largest (158 genes) (Li et al., 2015). Our analysis shows that the GmELF4 putative genes contain residues belonging to the IRRV type genes (Figure 2).

To compare the diurnal oscillation of gene expression of ELF4 in soybeans and Arabidopsis, we evaluated the transcription levels of eight GmELF4 homologous genes by re-analyzing a validated RNA-Seq library published by Rodrigues et al. (2015). The expression profiles of the soybean ELF4 candidates were determined in V2-stage soybean plants under LD conditions (14 h light/10 h dark) and temperature (28°C/20°C) cycles over a 24-h time course under well-watered conditions (Figure 3).

The mRNA levels of Glyma.18G027500, Glyma.11G229700, and Glyma.14G193700 peak at ZT12. The peak of transcripts of Glyma.07G037300 also occurs at ZT12, but, differently from the former genes, this peak is extended to ZT16. In contrast, Glyma.17G050800, Glyma.13G108600, and Glyma.09G067300 show two peaks of transcripts: one at ZT4 and another at ZT20. For instance, the Glyma.15G176300 expression level rises gradually throughout the day, peaking at ZT16 (Figure 3).

To functionally characterize a soybean ELF4 homolog (GmELF4), we transformed Arabidopsis plants to overexpress constitutively the CDS of Glyma.18G027500. This soybean ELF4 homologous gene was selected due its resemblance to the features of AtELF4 at the phylogenetic and transcriptomic levels: the protein sequence of Glyma.18G027500 is very closely related to that of AtELF4 (Figure 1), and its transcripts oscillate throughout the day with the same profile of the AtELF4 transcripts (Figure 3).

To better understand the function of the putative GmELF4 (Glyma.18G027500) in soybeans, we retrieved functionally related genes by constructing a co-expressed gene network using the SFGD database. The top 50 co-expressed genes from the GmELF4 network are listed in Table 1. A graphical representation of this network (Supplementary Figure 5) shows GmELF4 at the core of a network composed of genes that connect directly or indirectly to the core gene. Among those genes are several homologes of the circadian clock genes, including the GmELF4 paralog Glyma.11G229700, JUMONJI (Glyma.12G055000), CO-like (Glyma.02G223700, Glyma.16G050900, and Glyma.14G190400), and EARLY FLOWERING 3 (Glyma.04G050200) as well as the gene encoding GIGANTEA (GI) (Glyma.16G163200) (Table 1).

Interestingly, some of the GmELF4 network genes encode proteins related to abiotic stress responses, such as DnaJ chaperones (Glyma.07G197600 and Glyma.12G130000), chaperonins (Glyma.15G111400), a cold regulated protein (Glyma.17G242100) and a heat shock protein (Glyma.02G288700) (Table 1).

ELF4 is a circadian clock gene essential for the maintenance of circadian rhythms and control of flowering in Arabidopsis. A previous study identified five ELF4-like genes in Arabidopsis: ELF4, ELF4-like1, ELF4-like2, ELF4-like3, and ELF4-like4 (Khanna et al., 2003). Here we identified a greater number of ELF4-like genes in soybean (nine), which agrees with a previous analysis of the soybean genome that shows the presence of complex circadian clock circuitry, generally composed of a greater number of components than that in Arabidopsis (Jung et al., 2012; Marcolino-Gomes et al., 2014; Rodrigues et al., 2015). Interestingly, all the soybean ELF4 candidates have a DUF1313 motif (IRRV-type) (Figure 2), a highly conserved domain exclusively found in plants, characteristic of ELF4 proteins (Li et al., 2015), supporting the function of the soybean candidates to ELF4 genes/proteins in soybean.

The re-evaluation of a validated RNA-seq library (Rodrigues et al., 2015) allowed us to assess novel data regards the gene expression of the ELF4 soybean homologes along the day. These data reveals that the mRNA levels of Glyma.18G027500, Glyma.11G229700, and Glyma.14G193700 peak at ZT12 (Figure 3), in a similar manner as the Arabidopsis ELF4 gene (Doyle et al., 2002). This expression profile was validated in Glyma.18G027500 by RT-qPCR in a previous study (Marcolino-Gomes et al., 2014). Interestingly, other GmELF4 genes showed diverse expression patterns throughout the day (Figure 3).

It is known that the accurate oscillation of the transcript levels of the circadian components throughout the day is crucial for accuracy of the circadian rhythms. The Arabidopsis ELF4 transcripts peak at specific periods allows it to interact with other circadian components to guarantee circadian precision and normal clock function (McWatters et al., 2007; Herrero et al., 2012). Thus, how can the differences found in the mRNA peaks observed for the different ELF4 genes from soybean be explained? The answer for this question may reside within the evolutionary history of soybean. The current soybean genome is the result of three rounds of polyploidy: (i) a genome triplication before the origin of the rosids (∼130 to 240 million years ago), shared with grape, poplar and Arabidopsis; (ii) a genome duplication early in the legumes (∼58 million years ago); and (iii) a duplication in the Glycine lineage (∼13 million years ago) (Severin et al., 2011).

An important feature of duplication is that it produces genetic redundancy, and a duplicated locus creates the opportunity for duplicates to explore new evolutionary functions (Flagel and Wendel, 2009). In a previous study of flowering genes in soybean, it was postulated that the differential accumulation of gene copies between soybean and Arabidopsis would be a possible evolutionary innovation that distinguishes the two species from one another (Jung et al., 2012). In addition, it has been verified that, if given sufficient time, one copy of a duplicate pair of genes can accumulate mutations that result in function divergence, or ‘neofunctionalization’ (Flagel and Wendel, 2009). The phylogenetic analyses of Arabidopsis and other angiosperms ELF4 genes reveals a complex gene history of duplication and loss within the ELF4 family (Kolmos et al., 2009). In this context, the different gene expression patterns observed for the ELF4 genes in soybean may be a reflex of functional divergence due modifications that occurred in this group of genes during the dynamic evolutionary history of the soybean genome. This divergence is possible because the role of sustaining the circadian oscillator, played by ELF4, can be fulfilled by the genes that oscillate to peak levels at ZT12 (such as Glyma.11G229700 and Glyma.18G027500), while the other paraloges may assume additional roles in the plant molecular circuitry. Furthermore, this mechanism may contribute to the evolution the circadian clock complexity of plants.

The close phylogenetic relation between Glyma.18G027500 and the Arabidopsis ELF4 major protein (AT2G40080) (Figure 1), together with the similar expression patters between these ortholog genes (Figure 3) encouraged us to investigate the function of Glyma.18G027500 as a putative GmELF4 gene. The quantitation of the transcript levels of the putative GmELF4 in transgenic versus WT plants confirmed that the transgene was highly expressed in line EF7 for both SD and LD, while lines EF14 and EF15 had lower transcript levels (Figures 4A,C).

It is known that gene activity is not exclusively determined by the promoter that controls transcription (in our case, the CaMV35S promoter): epigenetic mechanisms also influence expression levels by blocking gene transcription or inhibiting mRNA accumulation. Thus, the difference of the transgene expression among lines EF7, EF14, and EF15 (Figures 4A,C) can be attributed to several factors including DNA methylation, production of aberrant RNAs, ectopic DNA–DNA interactions and the effect of the locus where the transgene was inserted (Stam et al., 1997; Butaye et al., 2005).

The most striking phenotype of the transgenic GmELF4-ox lines compared to WT plants was flowering delay. Similarly, McWatters et al. (2007) reported that the constitutive overexpression of the endogenous ELF4 gene in Arabidopsis resulted in flowering delay under inductive (LD) photoperiods, whereas under non-inductive conditions (SD) plants showed no additional delay in flowering. According to these authors, this phenotype resulted from the role of ELF4 as a floral repressor that coordinates floral transition as part of the photoperiod pathway. Our data reveal that the soybean ELF4 homologous gene (Glyma.18G027500) is capable of delay Arabidopsis flowering, suggesting the molecular function of GmELF4 as a flowering repressor. Nonetheless, differently from the AtELF4 gene, the soybean homolog is also able to produce altered phenotypes (flowering delay) in SD conditions (Figures 5A,C and Supplementary Figure 4), indicating that this gene interacts differently with the Arabidopsis flowering control network.

In addition, the transgenic plants also presented a higher number of rosette leaves compared to WT plants (Figure 6A). This phenotype is likely a consequence of the flowering delay caused by GmELF4 overexpression, which allowed the plants to invest more in vegetative development, resulting in higher biomass accumulation (Figure 6B). Previous analysis of flowering control and biomass yield in Medicago truncatula mutants reveals that delayed flowering genotypes produce double the amount of biomass, with less lignin, compared to WT plants, showing that delaying floral initiation could be employed as a convenient biotechnology tool to improve simultaneously biomass quantity and quality in plants (Tadege et al., 2015). In this context, the GmELF4-ox phenotypes obtained in this study have great potential for the improvement of crops, such as legume forages, grasses and sugarcane, where flowering delay and improvement of biomass accumulation constitute the main goal.

In Arabidopsis, flowering occurs due the action of the FLOWERING LOCUS T (FT) protein, and the amount of FT transcript is directly induced by the transcriptional activator CO protein, which is controlled by the circadian clock and light signaling (Kim et al., 2012, 2013). In turn, the AtELF4 protein is able to bind to the GI protein and target it to subnuclear compartments in the nucleus, sequestering GI from the CO promoter, negatively affecting CO expression levels and decreasing the amount of FT transcript, which results in absence of flower induction (Kim et al., 2012, 2013). Interestingly, our data evidence that the overexpression of GmELF4 caused a substantial reduction in expression of AtFT and AtCO (Figures 4B,D).

Our phenotypic and molecular data suggest that GmELF4 may play the role of its homologous gene (AtELF4) in reducing the expression of CO and FT, which results in flowering delay. Further analysis should be carried on to confirm the ability of GmELF4 in sequestering GI from the CO promoter.

A previous study showed that the overexpression of an ELF4 gene from Doritaenopsis Happy Smile × Happy Valentine (DhEFL4) alters transgenic Arabidopsis phenotypes by postponing flowering by 12–14 days, indicating that the function of ELF4 is highly conserved among plants (Chen et al., 2015). Our data shows similar phenotypic results for the GmELF4 gene, which have not been previously characterized, and our study also provides unpublished data regarding the molecular mechanisms behind these phenotypes.

Structural analysis of the ELF4 protein reveals that it forms a tight homodimer with α-helical composition, critical for the protein function (Kolmos et al., 2009). Thus, studies about the occurrence of this structure in GmELF4 would contribute to a deeper understanding of this protein function. Furthermore, the capacity of the GmELF4 to form dimers could be extended to the formation of a complex with the AtELF4 protein, allowing this complex to act synergistically to generate the delayed flowering phenotypes observed in our transgenic lines.

According to previous studies, the function of every gene is believed to rely on that of another gene(s), and together these genes form complex and intricate networks. Thus, gene co-expression databases are useful resources for predicting gene networks, because co-expressed genes are generally expected to be involved in related cellular functions (Obayashi and Kinoshita, 2009; Obayashi et al., 2009). These analyses show that GmELF4 network is composed by several homologes of the circadian clock and flowering genes (Table 1 and Supplementary Figure 5), supporting the participation of GmELF4 as a component of the soybean circadian clock and flowering genes. Functional studies about the AtELF4 gene reveals that it functions as a small dimer, and its action is critical for buffering perturbations to the circadian clock evening-loop (Kolmos et al., 2009), a function that may be shared by the GmELF4 homolog.

Curiously, we also identified many abiotic stress responsive genes composing the GmELF4 network (Table 1 and Supplementary Figure 5). Several studies have shown connections between the plant responses to abiotic stresses (e.g., heat, cold, and drought) and the circadian clock (Fowler et al., 2005; Bieniawska et al., 2008; Legnaioli et al., 2009; Wilkins et al., 2010; Marcolino-Gomes et al., 2014; Rodrigues et al., 2015), suggesting a close connection between both pathways. In a previous study, we showed that severe drought stress imposition strongly represses the expression of GmELF4 in soybean (Marcolino-Gomes et al., 2014). Together, this evidences that GmELF4 contributes to multiple important plant physiological responses, including the circadian clock, flowering control and responses to abiotic stresses, such as drought. The drought escape strategy entails the completion of the lifecycle in advance of the effects of drought and is a common strategy among annual plants, such as soybean; in Brassica rapa, for example, drought escape by early flowering has been proven to be an important adaptive mechanism acquired during plant evolution (Franks, 2011).

Based on our data, we suggest that GmELF4 may acts as a key negative flowering controller in soybean plants, in the same manner it does in transgenic Arabidopsis plants. Furthermore, its repression in response to drought stress may be part of a mechanism to promote early flowering to escape drought. Additional analyses in transgenic soybean plants (GmELF4-ox and/or elf mutants) are encouraged to provide additional insights about the flowering control mechanisms in this organism.