plants Article Light Deficiency Inhibits Growth by Affecting Photosynthesis Efficiency as well as JA and Ethylene Signaling in Endangered Plant Magnolia sinostellata Danying Lu 1,2 , Bin Liu 3 , Mingjie Ren 1,2 , Chao Wu 1,2 , Jingjing Ma 1,2, * and Yamei Shen 1,2, * 1 Zhejiang Provincial Key Laboratory of Germplasm Innovation and Utilization for Garden Plants, Zhejiang Agriculture & Forestry University, Hangzhou 311300, China; 2019105052023@stu.zafu.edu.cn (D.L.); 2020105011010@stu.zafu.edu.cn (M.R.); 2020105011013@stu.zafu.edu.cn (C.W.) 2 College of Landscape and Architecture, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China 3 Department of Plant Genomics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, 08193 Bellaterra, Spain; liu.bin@cragenomica.es * Correspondence: jingjingma@zafu.edu.cn (J.M.); Yameishen@zafu.edu.cn (Y.S.) Abstract: The endangered plant Magnolia sinostellata largely grows in the understory of forest and suf- fers light deficiency stress. It is generally recognized that the interaction between plant development and growth environment is intricate; however, the underlying molecular regulatory pathways by which light deficiency induced growth inhibition remain obscure. To understand the physiological   and molecular mechanisms of plant response to shading caused light deficiency, we performed photosynthesis efficiency analysis and comparative transcriptome analysis in M. sinostellata leaves, Citation: Lu, D.; Liu, B.; Ren, M.; Wu, C.; Ma, J.; Shen, Y. Light which were subjected to shading treatments of different durations. Most of the parameters relevant Deficiency Inhibits Growth by to the photosynthesis systems were altered as the result of light deficiency treatment, which was also Affecting Photosynthesis Efficiency as confirmed by the transcriptome analysis. Gene Ontology and KEGG pathway enrichment analyses well as JA and Ethylene Signaling in illustrated that most of differential expression genes (DEGs) were enriched in photosynthesis-related Endangered Plant Magnolia pathways. Light deficiency may have accelerated leaf abscission by impacting the photosynthesis sinostellata. Plants 2021, 10, 2261. efficiency and hormone signaling. Further, shading could repress the expression of stress responsive https://doi.org/10.3390/ transcription factors and R-genes, which confer disease resistance. This study provides valuable plants10112261 insight into light deficiency-induced molecular regulatory pathways in M. sinostellata and offers a theoretical basis for conservation and cultivation improvements of Magnolia and other endangered Academic Editor: Carmen Arena woody plants. Received: 19 September 2021 Keywords: light deficiency; RNA-seq; gene regulation; Magnolia sinostellata; endangered species Accepted: 13 October 2021 Published: 22 October 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in 1. Introduction published maps and institutional affil- Magnoliaceae plants are widely favored by people for their pleasant ornamental iations. characteristics and high scientific research values. The history of Magnoliaceae plants can be traced back to the Mesozoic Era [1]; however, the deciduous Magnoliaceae plants are now facing the danger of extinction in nature as the result of global climate change, forest vegetation renewal, and the succession of evergreen broad-leaved forest in subtropical Copyright: © 2021 by the authors. areas [2]. The natural distributions of the endangered species of Magnoliaceae are mostly Licensee MDPI, Basel, Switzerland. restricted to specific areas. This article is an open access article For example, a number of deciduous Magnoliaceae species, such as Magnolia stellata [3], distributed under the terms and M. wufengensis [4], M. Zenii [5], M. officinalis [6], and M. sinostellata [7], tend to grow conditions of the Creative Commons in coniferous community or forest gaps of broad-leaved communities, but are rarely Attribution (CC BY) license (https:// found in the evergreen broad-leaved community. M. sinostellata is an endangered species creativecommons.org/licenses/by/ with high ornamental value, which has been listed in the Red List of Magnoliaceae since 4.0/). Plants 2021, 10, 2261. https://doi.org/10.3390/plants10112261 https://www.mdpi.com/journal/plants Plants 2021, 10, 2261 2 of 21 2016 [8]. It is a perennial deciduous flowering shrub that blossoms in early spring in the subtropical regions. Although M. sinostellata is a sun-loving plant, in its natural habitats, it grows under canopy shade or nearby the brook of the north slope in coniferous forest communities, and sparsely distributes in broad-leaved or mixed forest communities [7]. Canopy shade of evergreen plants in the upper layer of forest community will affect the growth of deciduous plants in the understory [9], as it alters the light intensity as well as the light quality towards a lower ratio of red/far-red light (R/FR) in the forest community [10,11]. Shading is recognized as an important abiotic stress that affects the growth and development of shade-intolerant plants [12]. Under shading conditions, the hypocotyls and petioles of Arabidopsis were significantly elongated, and leaf lamina growth was inhibited [13]. Leaf expansion in Glycine max and Zea mays grown under shade was inhibited, which ultimately affected their seed yield [14,15]. Vegetable seedlings of tomato, cucumber, and eggplant often grow excessively under weak light conditions, leading to decreased yield in cultivation [16]. Similarly, shading increased the vegetative growth but repressed the production of lemon trees [17]. In ornamental plants, shading caused leaf chlorosis in tea [18] and faded flower color of Paeonia lactiflora [19]. As the severity of shading increased, the leaves of Tetrastigma hemsleyanum and Salvia officinalis turned yellow due to decreased chlorophyll content [20,21]. Similarly, the leaf yellowing was also observed in deciduous Acer pseudoplatanus, Fagussylvatica, Tilia cordata, and coniferous Abies alba grown under shade in arbor [22]. However, the shade response phenotype of Magnoliaceae plants remains unclear. Light changes under canopy shade can be sensed by phytochromes (PHY) [23], which sense changes in both light intensity and quality [24]. In Arabidopsis, the phytochrome family includes five members (phyA–phyE), among which phytochrome B plays a dom- inant role in shade avoidance responses including leaf expansion, stem elongation, and early flowering [25,26]. Changes in light quality with a low ratio of R/FR induce shade escape responses such as rapid stem elongation and increased apical dominance, which enable plants to reach above the upper vegetation to absorb sun light [27]. Low light intensity alters chloroplast ultrastructure and photosynthetic metabolism [28]. Due to inadequate energy supply, long term exposure to low light conditions can limit growth in plants and even cause cellular damage in shade sensitive plants [29,30]. The primary effect of canopy shade on understory plants is through the weakening of their photosynthesis capacity [9]. Light-harvesting antenna proteins have vital functions in the primary process in photosynthesis, which enables plants to perform photosynthesis under extreme low light environment [31]. Under low light intensities, to maximize photosynthetic efficiency, the size of the light harvesting antenna of the plants is often considerably larger than that grown under normal light [32]. However, the enlargement of the light-harvesting antenna is normally restricted within a certain size and, as a result, the energy generated by the photosynthesis reaction center is also limited under long term shading [32,33]. Due to the insufficient energy supply, carbohydrates transformation in the Calvin cycle was blocked under weak light [34]. The activity and content of ribulose 1,5-bisphosphate carboxylase/oxygenase (Ru- bisco) were significantly reduced under shade in Hordeum vulgare [35], which catalyze carbon assimilation in plants [36]. The impaired photosynthetic carbon assimilation would influence multiple metabolism pathways in plants, including starch and sucrose metabolism, amino acid metabolism, and other secondary metabolism pathways, as found in Camellia sinensis [37,38]. As the plant seedlings grow, the demand for light intensity increases. Consequently, the suboptimal light intensity inevitably affects the growth and reproduction of plants [39]. To cope with environmental stresses, the plants have evolved elaborate response mechanisms [40]. Phytohormones are known to have pivotal roles in regulating stress responses in plants [41]. Under low light conditions, ethylene production and signaling Plants 2021, 10, 2261 3 of 21 was induced to increase stress tolerance in Arabidopsis and rice [42,43], but its high level of release could increase the sensitivity to stress and even lead to plant death [44]. In addition, jasmonic acid (JA) is also known as plant stress hormones in higher plants [45]. JA signaling and its content accumulation are often recruited to counteract abiotic stress in tomatoes and rice [46–48]. JA interacts with ethylene signaling pathways to regulate abiotic stress tolerance and may act as a core signal in such an intertwined network [49]. Various studies found that light deficiency can alter stress tolerance and disease resistance in plants [50–56]. However, its molecular mechanisms in plants are complex and unclear. Numerous tran- scription factors (TFs) are involved in regulating molecular response in plants [57]. TIFY family genes are plant-specific and responsible to multiple abiotic stresses, most of which are stress inducible and able to enhance plant stress tolerance [58], as exemplified in Citrullus lanatus [59], Triticum aestivum [60], and G. max [61]. The mitochondrial transcription termination factor (mTERF) family was also found as essential for plant adaptation or tolerance to abiotic stresses by regulating transcription, translation and DNA replication in mitochondria in plants [62,63]. Furthermore, plant resistance (R) genes encode immune receptors that recognize specific avirulence (Avr) genes of pathogens [64], the expression levels of which are tightly associated with disease resistance and could be induced by environmental stress [65]. To our knowledge, the responses of TIFYs, mTERFs, and R-genes to weak light have not been investigated. Fur- ther, the regulatory pathways of molecular responses to light deficiency in M. sinostellata remain obscure. Previous studies have confirmed that weak light is the main factor that affect the distribution and growth of deciduous magnolia in the understory of forest community [5,7]. The light environment under canopy shade can be quite complex, containing low light intensity and inconsistent light quality [66,67]. To reduce the confounding factors, many studies focused on the impacts of low light intensity on a number of plant species, such as soybean [68], rice [69], Halimium halimifolium [70]. Accordingly, in this study, we mainly focused on the effect of shading caused light deficiency on M. sinostellata and black shade net was used to create light deficiency conditions. In the preliminary research, we found that low light intensity promoted leaf abscission in M. sinostellata, which is distinct from the response of model plants, such as Arabidopsis and rice. Photosynthesis efficiency analysis revealed that light deficiency altered photosyn- thesis systems related parameters. Comparative transcriptome analysis in M. sinostellata leaves with and without weak light treatment led to the identification of numerous core low-light responsive pathways, TFs, and R-genes. This study may offer a new insight into the light deficiency response mechanism, which forms a theoretical basis for the protection and conservation of M. sinostellata and other endangered woody plants. 2. Results 2.1. Light Deficiency Inhibited Growth of M. sinostellata Significant morphological changes in M. sinostellata seedlings under light deficiency treatment (LT), relative to the control (CK) seedlings, were observed (Figure 1A). The CK leaves of M. sinostellata were fully expanded, and no significant changes were observed in these seedlings at day 1. After being subjected to low light conditions for 5 d, seedlings began to wilt, and around 5% of leaves were shed (Supplementary Materials Figure S1). By 15 d of light deficiency treatment, severe leaf abscission was observed, 17% of leaves fell. After 20 d, most of the leaves were found to face downward, and approximately 28% of leaves were shed. Plants 2021, 10, 2261 4 of 21 Plants 2021, 10, x FOR PEER REVIEW 4 of 22 Figure1.1. Phenotypic Figure Phenotypic andand physiological physiologicalchanges changesofofM.M. sinostellata sinostellata seedlings seedlings under under lightlight deficiency. deficiency. (A) (A) Phenotypic Phenotypic shifting M.sinostellata shiftingofofM. sinostellata during during experiment. experiment. (B)photosynthesis (B) Net Net photosynthesis (C) Pn. rate, Pn.rate, Intercellular (C) COCO Intercellular 2 concentration, 2 Ci. concentration, (D) Ci. Stomatal (D) conductance, Stomatal Gs. conductance, (E) Transpiration Gs. (E) rate, Transpiration Tr. (F) Tr. rate, Light use efficiency, LUE. (G) Water use efficiency, WUE. (H) Rubiso activity. (I) Maximum (F) Light use efficiency, LUE. (G) Water use efficiency, WUE. (H) Rubiso activity. (I) Maximum Chl Chl fluorescence yield obtained with dark‐adapted leaf, Fm. (J) Minimum Chl fluorescence yield ob‐ fluorescence yield obtained with dark-adapted leaf, Fm. (J) Minimum Chl fluorescence yield obtained with dark-adapted leaf, Fo. (K) Maximal photochemical efficiency, Fv/Fm. (L) Excitation energy cap- ture efficiency of PSII, Fv’/Fm’. (M) Activity of PSII reaction centers, Fv/Fo. (N) Non-photochemical quenching, NPQ. (O) Photochemical quenching, qP. (P) Yield of PSII photochemistry, ΦPSII. Plants 2021, 10, 2261 5 of 21 Furthermore, the whole plants began to show evident phenotypic damage, which worsened as the light deficiency treatment progressed. After 25 d of the treatment, 34% of leaves were shed, and some leaves were completely dried up. After 30 d of the light deficiency stress, 40% of the leaves were shed. Such morphological changes confirm that M. sinostellata is highly sensitive to light deficiency. To investigate the potential changes in carbon assimilation as caused by light deficiency treatment, a number of photosynthetic parameters were measured in the M. sinostellata leaves, including net photosynthetic net (Pn ), intercellular CO2 concentration (Ci ), stomatal conductance (Gs ), and transpiration rate (Tr ). Under weak light, Pn initially increased by 20% after 10 d shade treatment, which were reduced to 60% of that of the controls after 30 d light deficiency treatment (Figure 1B). Ci (Figure 1C) also showed an initial increase prior to dropping at 25 d, while Gs (Figure 1D) and Tr (Figure 1E) consistently decreased. The light utilization efficiency (LUE) (Figure 1F) and water utilization efficiency (WUE) (Figure 1G) were also analyzed, which showed similar trends in response to weak light, both of which peaked at 10 d and then deceased. Rubisco activity was peaked at d5 before its sharp reduction (Figure 1H). Chlorophyll fluorescence parameters were also affected by light deficiency stress throughout the ex- periment (Figure 1I–P). The maximal fluorescence (Fm), maximal quantum yield of PSII (Fv/Fm), excitation energy capture efficiency of PSII (Fv’/Fm’), photochemical quenching (qP), active PSII reaction centers (Fv/Fo) and non-photochemical quenching (NPQ) values all decreased throughout the experiment. Fv’/Fm’ values rapidly decreased until 10 d, and then dropped down slowly thereafter. qP declined throughout the experiment, while the initial fluorescence (Fo) values increased consistently. The yield of PSII photochemistry (ΦPSII) value decreased until 5 d, followed by a sharp increase from 5 d to 15 d, before significantly dropping thereafter. 2.2. Summary of Transcriptome Assembly and Function Annotation in M. sinostellata Based on the results of the photosynthesis analysis, the samples of d 0 (mixed sample of CK and LT), d 5, and d 15 in both CK and LT were selected for transcriptome sequencing. A total of 15 samples in five groups (CK-D0, CK-D5, CK-D15, LT-D5, and LT-D15) were mixed equally, and used for the full-length transcriptome sequencing, which obtained a total of 50.13 GB data and 14,653,022 subreads. The length of subreads varied from 3420.95 bp to 188,350 bp (Figure S2). After de-redundancy, 246,481 unigenes were obtained in M. sinostellata with a total length of 270,112,156 bp, and the GC content was 43.97% (Table S2). BUSCO was used to evaluate the completeness of transcriptome assembly, which showed that full-length transcriptome of M. sinostellata was comprised of 88.78%, 4.95%, and 6.27% of the complete, fragmented and missing BUSCOs, respectively (Figure S3). All the unigenes were blasted against the seven public databases for functional annotation (Table S3). 173,103, 146,820, 128,216, 135,136, 128,718, 107,462, and 138,676 unigenes were identified in the database of Nr, Nt, Swissprot, KEGG, KOG, Pfam, and GO, respectively, which became the basis for the functional annotation of a total number of 191,343 unigenes. The high-quality full-length consensus sequences obtained by full-length transcrip- tome sequencing were employed as the reference gene set for M. sinostellata. To further elucidate the shade responsive patterns of M. sinostellata, de novo transcriptome sequenc- ing was performed on the 15 samples separately and a total of 697.63 M original reads were obtained (Table S4). When the clean reads obtained by the second-generation transcriptome sequencing were aligned to the reference gene set by Bowtie2, a total of 181,902 genes were detected in this de novo transcriptome sequencing. The mapped ratios were varied from 73.76% to 86.99% with the mean of 80.49% (Table S5). A box plot of the gene expression in FPKM value as calculated using RSEM illustrates the overall distribution of gene expression in each sample (Figure S4). A sample PCA map was generated by analyzing all the 15 samples by dimensionality reduction Plants 2021, 10, 2261 6 of 21 method (Figure S5), which shows a high level of correlation among the three biological replicates in five groups. 2.3. Identification of Differentially Expressed Gene in M. sinostellata In total, 11,850, 12,320, 7165, and 15,389 DEGs were detected in CK-D0-vs-LT-D5, CK- D5-vs-LT-D5, CK-D0-vs-LT-D15, and CK-D15-vs-LT-D15 comparison group, respectively (Figure S6A). Following the removal of overlapping DEGs detected in the four comparison groups, a total of 22,433 DEGs for light deficiency response were identified based on strict criteria (Fold change > 4 and p < 0.05). A Venn diagram showed that 3309 DEGs were significantly expressed throughout the treatment (Figure S6B). Among the 22,433 DEGs, GO analysis indicated that the top five enriched GO terms were directly related to pho- tosynthesis components (Figure 2A), which are all photosynthesis and thylakoid related terms (GO:0009765, GO:0009579, GO:0009522, GO:0034357, and GO:0009521). KEGG analysis showed consistent results with GO analysis. The top five enriched KEGG pathways were all associated with photosynthesis, carbohydrate metabolism or other secondary metabolism, among which ‘Photosynthesis—antenna proteins’ was the most enriched KEGG pathway, followed by ‘Phenylpropanoid biosynthesis’, ‘Glycine, serine and threonine metabolism’, ‘Cyanoamino acid metabolism’, and ‘Starch and sucrose metabolism’ (Figure 2B). Taken together, these results strongly suggest that photosynthesis, carbon fixation and other secondary metabolisms play important roles in response to light deficiency in M. sinostellata. 2.4. Expression Patterns of DEGs Involved in Photosynthesis Altered under Light Deficiency To further investigate the effects of light deficiency on the photosynthesis capacity of M. sinostellata, the expression patterns of DEGs involved in photosynthesis-related path- ways were analyzed. Under the low light condition, most of the genes that were predicted to function in antenna protein pathway (ko00196) [71] were significantly down regulated (Figure 2C). In this pathway, gene expression trend analysis indicated that 336 genes were consistently down regulated, whereas three genes were up regulated (Figure 2D). Heatmap analysis showed that expression level of most genes in light harvesting complex I (LHC I and LHCA1-5) and light harvesting complex II (LHC II and LHCB1-7) were decreased under light deficiency treatment (Figure 3A), suggesting that the activity of light-harvesting chlorophyll protein complex (LHC) of M. sinostellata was inhibited. Similarly, DEGs that are related to the photosynthesis pathway (Ko00195) were also mainly down regulated during light deficiency conditions, among which 568 DEGs were significantly down regulated, whereas 26 genes showed a trend of significant upregu- lation (Figure 2E,F). Compared with CK, the genes involved in the PSI, PSII, including Cytochrome b6/f complex, photosynthetic electron transport and F-type ATPase, were mostly down regulated under light deficiency treatment, consistent with the reductions in photosynthesis efficiency (Figure 3B). In the carbon fixation pathway (Ko00710), the expression of 328 genes declined, whereas 31 genes were dramatically up regulated (Figure 2G,H). The significant decrease in the transcription level of the key genes involved in Calvin cycle, including RbcLs, RbcSs, PGAs, GADPHs, GAPAs, and TPIs, may indicate that the carbon assimilation efficiency and further sucrose and starch metabolism were depressed in the shade treated M. sinostellata plants (Figure 3C). Plants 2021, 10, x FOR PEER REVIEW 7 of 22 Plants 2021, 10, 2261 7 of 21 Figure 2. Analysis of DEGs involved in photosynthesis related pathways in M. sinostellata. Figure 2. Analysis of DEGs involved in photosynthesis related pathways in M. sinostellata. (A) GO (A) GO enrichment enrichment analysis ofanalysis of 22,433 22,433 DEGs. (B)DEGs. KEGG(B) KEGG enrichment enrichment analysis analysis of 22,433 of 22,433 DEGs. DEGs. The top 20The GO top 20 GO and KEGG Terms with the smallest Qvalue were selected to plot the chart, and KEGG Terms with the smallest Qvalue were selected to plot the chart, respectively. (C) Volcano respectively. (C)of plots Volcano DEGs plots of DEGs involved involvedprotein. in antenna in antenna (D)protein. Trends(D) Trendsrelated of DEGs of DEGstorelated antennato antenna protein.protein. (E) Vol‐ (E)plots cano Volcano plots of of DEGs DEGs involved involved in photosynthesis. in photosynthesis. (F) Trends (F) Trends of DEGs of DEGs related related to photosynthesis. to photosynthesis. (G) (G) Volcano Volcano plots plots of of DEGs DEGs involved involved in carbon in carbon fixation. fixation. (H)(H) Trends Trends ofofDEGs DEGsrelated relatedto to carbon carbon fixation. fixation. 2.4. Expression Patterns of DEGs Involved in Photosynthesis Altered under Light Deficiency To further investigate the effects of light deficiency on the photosynthesis capacity of M. sinostellata, the expression patterns of DEGs involved in photosynthesis‐related path‐ ways were analyzed. Under the low light condition, most of the genes that were predicted to function in antenna protein pathway (ko00196) [71] were significantly down regulated In the carbon fixation pathway (Ko00710), the expression of 328 genes declined, whereas 31 genes were dramatically up regulated (Figure 2G,H). The significant decrease in the transcription level of the key genes involved in Calvin cycle, including RbcLs, RbcSs, PGAs, GADPHs, GAPAs, and TPIs, may indicate that the carbon assimilation effi‐ Plants 2021, 10, 2261 ciency and further sucrose and starch metabolism were depressed in the shade treated M. 8 of 21 sinostellata plants (Figure 3C). Figure 3. Heatmaps of DEGs involved in photosynthesis-related pathways in M. sinostellata. (A) Heatmaps of the expression Figure 3. Heatmaps of DEGs involved in photosynthesis‐related pathways in M. sinostellata. (A) Heatmaps of the expres‐ patterns of genes sion patterns involved of genes in ‘photosynthesis-antenna involved protein’ in ‘photosynthesis‐antenna pathway protein’ underunder pathway light deficiency and normal light deficiency light conditions. and normal light con‐ (B) Heatmaps of the expression patterns of DEGs participated in ‘photosynthesis’ pathway under ditions. (B) Heatmaps of the expression patterns of DEGs participated in ‘photosynthesis’ pathway under light light deficiency and deficiency normal light conditions. (C) Heatmaps of the expression patterns of DEGs related to and normal light conditions. (C) Heatmaps of the expression patterns of DEGs related to ‘carbon‘carbon fixation in photosynthetic photosynthetic organisms’ organisms’pathway pathwayunder under light light deficiency deficiency and and normal normal light light conditions. conditions. 2.5.Phytohormonal 2.5. PhytohormonalChanges ChangesininLeave LeaveofofM. M.sinostellata sinostellataunder underLowLowLight Light Transcriptome data analysis Transcriptome analysisshowed showedthat thatlight deficiency light deficiency mainly mainlyaffected ethylene affected and ethylene jasmonic acid signaling pathways. Under light deficiency treatment, the and jasmonic acid signaling pathways. Under light deficiency treatment, the ethylene sig‐ ethylene signaling promoting naling factors,factors, promoting such as such EIN3 asand ERFs, EIN3 and were significantly ERFs, up-regulated were significantly by weak light, up‐regulated by indicating weak light, the activation indicating the of ET mediated activation of ET signaling mediated pathway signaling(Figure pathway 4A). A number (Figure 4A). A of key genes related to JA signaling were down regulated by weak number of key genes related to JA signaling were down regulated by weak light, amonglight, among which JA signaling which inhibitorinhibitor JA signaling COI1 was the was COI1 mostthe significantly induced. most significantly induced. Further, the expression of stress response regulators Further, the expression of stress response regulators JAR1 JAR1andand JAZJAZ were were inhibited inhibited in in the the JA signaling pathway, which suggests that the JA-mediated stress JA signaling pathway, which suggests that the JA‐mediated stress response pathway was sup‐response pathway was suppressed pressed by(Figure by low light low light 4B).(Figure 4B).verify To further To further whetherverify weakwhether weak light affects light affects phytohormone phytohormone accumulation, the concentrations of endogenous ACC (ethylene precursors) and JA were measured during the experiment. After 15 d light deficiency treatment, the endogenous ACC level increased from 83.3 to 153.5 ng/g, Figure 4C. In contrast, the endogenous JA level dropped from 19.8 to 13.1 ng/g at 15 d after experiment (Figure 4D). The alteration in the expression patterns of the above mentioned core genes involved in plant hormone signaling were verified using qRT-PCR, which were consistent with the transcriptome analysis (Figure 4E). 2.6. Light Deficiency Affected Stress-Related Transcription Factors in M. sinostellata Given that low light intensity can impact stress tolerance in various plants, such as Calamus viminalis, Anoectochilus roxburghii, and Leymus chinensis [50–52], and light deficiency also weakened the resistance of M. sinostellata [53], stress response TFs were identified and analyzed in a genome wide range. TIFY and mitochondrial transcription termination factors (mTERFs) are related to stress response and have important roles in stress tolerance in plants [72,73]. Seven MsTIFYs were identified from the M. sinostellata transcriptome, and their physicochemical characters are listed in Table S6. accumulation, the concentrations of endogenous ACC (ethylene precursors) and JA were measured during the experiment. After 15 d light deficiency treatment, the endogenous ACC level increased from 83.3 to 153.5 ng/g, Figure 4C. In contrast, the endogenous JA level dropped from 19.8 to 13.1 ng/g at 15 d after experiment (Figure 4D). The alteration in the ex‐ pression patterns of the above mentioned core genes involved in plant hormone signaling Plants 2021, 10, 2261 9 of 21 were verified using qRT‐PCR, which were consistent with the transcriptome analysis (Figure 4E). Figure 4. The impact of light deficiency on plant hormone concentration and signaling pathways. (A) Heatmap of genes Figure 4. The impact of light deficiency on plant hormone concentration and signaling pathways. involved in ethylene signal transduction (A) Heatmap of genes involvedunder in light deficiency ethylene andtransduction signal normal lightunder conditions. (B) Heatmaps light deficiency andofnormal genes involved in jasmonic acid signaling under light deficiency and normal light conditions. (C) Concentrations light conditions. (B) Heatmaps of genes involved in jasmonic acid signaling under light deficiency of ethylene at d0 and d15 under light deficiency and normaland light normal light conditions. conditions. (D) Concentrations (C) Concentrations of jasmonic of ethylene acid d15 at d0 and at d0under and d15 under light light deficiency deficiency andconditions. and normal light normal light(E)conditions. (D) Concentrations qRT-PCR analysis of jasmonic of key genes involved acid hormone in plant at d0 andsignaling d15 under lightlight under defi‐ deficiency ciency and and control conditions fornormal 0 d, 5 d,light andconditions. (E) the 15 d. Data are qRT‐PCR meansanalysis of key genes of three biological involved replicates andinthree planttechnical hormonereplicates. The 2−∆∆ct method signaling wasunder employedlightto deficiency andgene conduct the control conditions differential for 0 d, 5analysis. expression d, and 15 d. Data are * indicates the means significant of differences in threethe comparison with biological replicates control groups and three technical corresponding to time replicates. points at pThe 2−ΔΔct method was employed to conduct < 0.05. the gene differential expression analysis. * indicates significant differences in comparison with the control groups corresponding Based on to time points FPKM valuesatof p 2 and q value < 0.05 were identified as DEGs, with a false discovery rate (FDR) < 0.05. The function of the DEGs was annotated using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The phyper function in R software was employed for enrichment analysis. 4.7. Bioinformatic Analysis DEGs that are involved in the light-regulated and plant hormone pathways were filtered based on GO and KEGG annotation. To identify stress-response TFs, the Getorf function in EMBOSS software was used to predict the open reading frames (ORFs) of the unigenes, from which the TF domains were searched using the Hmmsearch function. CLUSTALW was used to align the amino acid sequences of TFs, and the neighbor joining trees were constructed by using MEGA 5.0 software. The fasta format of DNA sequences of the unigenes was subjected to blast search against the plant disease resistance gene database (PRGDB) using the DIAMOND software. The R genes were filtered and obtained according to the query coverage and the identity of the blast results. Volcano plots were performed using R software. Heatmaps were generated using Morpheus (Morpheus, https://software.broadinstitute.org/morpheus, access date 12 October 2021). 4.8. qRT-PCR Analysis The total RNA of the 15 leaf samples was extracted using an RNAprep Pure Plant Plus kit (TIANGEN Biotech, Beijing, China) following the manufacturer’s instructions. Electrophoretic apparatus DYY-6C (LIUYI Biotech, Beijing, China), and agarose for elec- trophoresis use (Sangon Biotech, Shanghai, China) was used to analyze the integrity of RNAs. The purity and concentration of the total RNAs were analyzed by a NanoDrop system (Thermo Fisher Scientific, Waltham, MA, USA). The total RNAs were converted to cDNAs using the PrimeScript™ RT Master Mix (Takara Bio Inc., Shiga, Japan). Premier 5.0 was employed to design oligo primers for quantitative real time PCR (qRT-PCR), as listed in Table S1. qRT-PCR analysis was performed on LightCycler® 480 II (Roche Applied Science, Penzberg, Germany) using BCG qPCR Master Mix (Beijing Baikaiji Biotechnology Co., Ltd., Beijing, China) using a program that was set with an initial denaturing at 95 ◦ C for 30 s, which was followed by 40 cycles of 95 ◦ C for 5 s and 58 ◦ C for 30 s. Melting curves were generated after the end of the program from 65 ◦ C to 95 ◦ C with 0.2 ◦ C increments. M. sinostellata EF1-α was employed as the reference gene (Forward: 50 -GATGATTCCAACCAAGCCCA -30 , Reverse: 50 -CACCCACTGCAACAGTCTGG -30 ) and gene expression was determined using 2−∆∆Ct method [114]. All the qRT-PCR analysis experiments were performed in triplicate. The bar charts of the relative expression level were generated using the Graph pad software (Graph Pad Software, San Diego, CA, USA). SPSS software version 24.0 (SPSS, Inc., Chicago, IL, USA) was employed to analyze statistical significance. 4.9. Phytohormone Quantification In order to analysis the trend for change in phytohormones, leaf samples of d0 (mixed samples of CK-D0 and LT-D0) and d15 (CK-D15 and LT-D15) with three biological replicates were collected for phytohormone quantification. Approximately 500 mg of each sample was rapidly frozen in liquid nitrogen. The extraction and quantification of endogenous Plants 2021, 10, 2261 16 of 21 ACC (ethylene precursors) and JA were performed using an LC-ESI-MS/MS system (UPLC, Shim-pack UFLC SHIMADZU CBM30A system, http://www.shimadzu.com.cn/, access date 12 October 2021, Kyoto, Japan; MS/MS, Applied Biosystems, Foster City, CA, 6500 Quadrupole Trap, http://www.appliedbiosystems.com.cn/, access date 12 October 2021) by Wuhan Metware Biotechnology Co., Ltd. (Wuhan, China) [115–119]. 5. Conclusions We provided novel insights into the light deficiency response mechanism in an endan- gered ornamental tree species M. sinostellata through the analyses of transcriptome deep sequencing and photosynthesis efficiency. Under low light conditions, the intensity of light that captured by light harvesting complex was reduced. Then, the electron transport chains in PS I and PS II were affected. Due to the decline in ATP and NADPH production in the photosystem, the carbon fixation in the Calvin cycle and subsequent carbon metabolism were blocked. The signaling transduction and accumulation of ET were enhanced, while the content of JA was reduced in M. sinostellata. The expression of stress-responsive transcription TIFY and mTERF was repressed. In addition, most R-genes were downregulated under low-light conditions. Overall, light deficiency could impact on the growth of M. sinostellata plants Plants 2021, 10, x FOR PEER REVIEW through its direct effects on photosynthesis, phytohormone transduction, stress related 17 ofTFs, 22 and R-genes (Figure 6). The DEGs discovered in this study may facilitate further study on light deficiency responsive molecular mechanisms in plants. Figure 6. Hypothetical model of the light deficiency response mechanism in the endangered species M. sinostellata. Figure 6. Hypothetical model of the light deficiency response mechanism in the endangered species M. sinostellata. Supplementary Materials: The following are available online at https://www.mdpi.com/article/ Supplementary Materials: The following are available online at www.mdpi.com/xxx/s1, Figure S1: 10.3390/plants10112261/s1, Figure S1: Changes in leaf abscission rate during shading treatment, Changes in leaf abscission rate during shading treatment, Figure S2. Subread length distribution, Figure S2: Subread length distribution, Figure S3: BUSCO assembly evaluation results, Figure S4: Box Figure S3. BUSCO assembly evaluation results, Figure S4. Box plot of the expression levels of 15 plot of the expression levels of 15 samples, Figure S5: Principal component analysis of 15 samples, samples, Figure S5. Principal component analysis of 15 samples, Figure S6. Shade responsive DEGs identified in M. sinostellata. (A) Number of DEGs detected in four comparison groups. (B) Venn diagram of DEGs commonly or specifically expressed in M. sinostellata under shade treatment, Fig‐ ure S7: Shading treatment device used in this research, Table S1. Primers for quantitative real time PCR (RT‐qPCR), Table S2. Summary of the final transcript sequence obtained after de‐redundancy., Plants 2021, 10, 2261 17 of 21 Figure S6: Shade responsive DEGs identified in M. sinostellata. (A) Number of DEGs detected in four comparison groups. (B) Venn diagram of DEGs commonly or specifically expressed in M. sinostellata under shade treatment, Figure S7: Shading treatment device used in this research, Table S1: Primers for quantitative real time PCR (RT-qPCR), Table S2: Summary of the final transcript sequence obtained after de-redundancy, Table S3: Summary of function annotation result statistics, Table S4: Summary of filtered read quality statistics, Table S5: Summary of reference gene sequence alignment results, Table S6: Information of TIFY gene family in M. sinostellata, Table S7: Information of mTERF gene family in M. sinostellata, Table S8: The light intensity and quality in different conditions. Author Contributions: Conceptualization, D.L. and B.L.; methodology, D.L.; software, D.L.; vali- dation, J.M., M.R. and C.W.; formal analysis, B.L.; investigation, Y.S.; resources, Y.S.; data curation, C.W.; writing—original draft preparation, D.L.; writing—review and editing, Y.S.; visualization, M.R.; supervision, Y.S.; project administration, Y.S.; funding acquisition, Y.S. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Zhejiang Provincial Key Laboratory of Germplasm Innovation and Utilization for Garden Plants, grant number S2020004; 14th Five year Plan of Flower Variety Breeding in Zhejiang province, grant number 2021C02071-3; Key R&D project of Shanghai Municipal Science and Technology Commission ‘R&D and demonstration application of new varieties of white magnolia cultivation technology’, grant number 20DZ1203700. Data Availability Statement: The original transcriptome data used in this research was deposited in the National Center for Biotechnology Information (NCBI) with the accession number PRJNA770262. Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. References 1. Baranova, M. Systematic Anatomy of the Leaf Epidermis in the Magnoliaceae and Some Related Families. Int. Assoc. Plant Taxon. IAPT 1972, 21, 447–469. 2. Shen, Y.; Meng, D.; McGrouther, K.; Zhang, J.; Cheng, L. Efficient isolation of Magnolia protoplasts and the application to subcellular localization of MdeHSF1. Plant Methods 2017, 13, 44. [CrossRef] 3. Suzuki, S.; Kiyoshi, I.; Saneyoshi, U.; Yoshihiko, T.; Nobuhiro, T. 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