Morphological, transcriptomics and biochemical characterization of new dwarf mutant of Brassica napus

Accepted Manuscript Title: Morphological, Transcriptomics and Biochemical Characterization of New Dwarf Mutant of Brassica napus Authors: Chao Wei, Lixia Zhu, Jing Wen, Bin Yi, Chaozhi Ma, Jinxing Tu, Jinxiong Shen, Tingdong Fu PII: DOI: Reference:

S0168-9452(17)31048-8 https://doi.org/10.1016/j.plantsci.2018.01.021 PSL 9758

To appear in:

Plant Science

Received date: Revised date: Accepted date:

4-11-2017 16-1-2018 19-1-2018

Please cite this article as: Chao Wei, Lixia Zhu, Jing Wen, Bin Yi, Chaozhi Ma, Jinxing Tu, Jinxiong Shen, Tingdong Fu, Morphological, Transcriptomics and Biochemical Characterization of New Dwarf Mutant of Brassica napus, Plant Science https://doi.org/10.1016/j.plantsci.2018.01.021 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Morphological, Transcriptomics and Biochemical Characterization of New Dwarf Mutant of Brassica napus Chao Wei, Lixia Zhu, Jing Wen, Bin Yi, Chaozhi Ma, Jinxing Tu, Jinxiong Shen*, Tingdong Fu

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National Key Laboratory of Crop Genetic Improvement, National Center of Rapeseed Improvement in Wuhan, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, P.R. China * Corresponding Author: [email protected] Email addresses: Chao Wei: [email protected] Lixia Zhu: [email protected]

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Jing Wen: [email protected] Bin Yi: [email protected]

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Jinxing Tu: [email protected]

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Chaozhi Ma: [email protected]

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Tingdong Fu: [email protected]

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Highlights  We obtained a dwarf mutant line in B. napus and compared its phenotypes to the wild type. Transcriptome analysis of shoot apex samples uncovered DEGs involved in many pathways.

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Auxin-KANADI1 crosstalk plays a major role in root development.

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Pleiotropic phenotypes of the mutant result from complicated networks.

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Abstract

Plant height is a key trait of plant architecture, and is responsible for both yield and lodging resistance in Brassica napus. A dwarf mutant line (bnaC.dwf) was obtained by chemical mutagenesis of an inbred line T6. However, the molecular mechanisms and changed biological processes of the dwarf mutant remain to be determined. In this study, a comparative transcriptome analysis between bnaC.dwf and T6 plants was performed to identify genome-wide differentially expressed genes (DEGs) and possible biological processes that may explain the phenotype variations in bnaC.dwf. As a result of this analysis, 60,134,746– 60,301,384 clean reads were aligned to 60,074 genes in the B. napus genome, and accounted for 60.03% of the annotated genes. In total, 819 differentially expressed genes were used for GO

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(Gene Ontology) term and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses with a FDR (false discovery rate) criterion of < 0.001, |log2Ratio| ≥ 1. We focused on plant hormone signal transduction pathways, plant-pathogen interaction pathway, protein phosphorylation and degradation pathways and sugar metabolism pathways. Taken together, the decrease in local auxin (IAA) levels, the variation in BnTCH4, BnKAN1, BnERF109, COI1-JAZ9-MYC2, auxin response genes (BnGH3.11, BnSAUR78, and AUX/IAA19), and ABA (abscisic acid) signaling genes (BnADP5, BnSnRK2.1, BnABF3.1) partially accounted for variations of cell proliferation in internodes, shoot and root apical meristem maintenance, abiotic and biotic stress resistance, and pre-harvest sprouting. As a comprehensive consequence of the cross-talk between plant hormones, sugar metabolism, plant-pathogen interactions and protein metabolism, bnaC.dwf presents distinct phenotypes from T6. These results will be helpful for shedding light on molecular mechanisms in the dwarf mutant, and give insight into further molecular breeding of semi-dwarf B. napus. Keywords: Brassica napus, dwarf, transcriptome, auxin, hormone signaling, differentially expressed genes, sugar and protein metabolisms Intruduction

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Plant height become one of the most important targets for modern crop breeding and ideal plant architecture breeding [1] after the green revolution introduced semi-dwarf varieties of cereal crops [2] that could increase harvest index and contribute to higher yields partially because of improved lodging resistance [3]. Lodging can increase yield loss and harvesting difficulty, and the more the degree of lodging, the more reduced yield in B. napus [4]. To avoid lodging, besides identifying dwarf or semi-dwarf resources, we also can find genes of lignin- and lodging-related traits [5]. As a crucial target for ideal plant architecture, plant height increases the presence of other traits during targeted breeding, such as narrow leaves [6] and higher tiller numbers [7, 8]. Apart from growth conditions, many other factors can shape plant height, such as blue light and shade [9, 10], phytohormones [11], microRNAs (miRNAs) [12, 13], transcription factors (TFs) [14, 15], the plant skeletal system [16], and cell wall related genes [17]. Among the plant hormones, gibberellin (GA), auxin and brassinosteroid (BR) are considered to be major determinants of plant height partially by affecting cell proliferation and differentiation [11]. In addition, strigolactone (SL) biosynthetic and signaling pathways and the associated miRNAs that target genes involved in SL signaling regulate plant height as well [18]. Many dwarf genes and mutants involved in hormone biosynthetic and signal transduction pathways have been identified in rice, wheat, and maize, particularly in the GA [19] and BR pathways.

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As one of the most vital edible oil sources from the Brassicaceae family, rapeseed (Brassica napus L., allotetraploid, AACC, 2n = 38) was formed by natural hybridization ~7,500 years ago between the two ancestors Brassica rapa (Asian cabbage or turnip, AA, n = 10) and Brassica oleracea (Mediterranean cabbage, CC, n = 9) [20]. The genome of B. napus multiplied 72× as a consequence of three paleohexaploidy events (γ, β and α), whole-genome triplication (WGT), and natural allopolyploidization [21-24]. The semi-dwarf trait is a key index for B. napus breeding and many dwarf and/or semi-dwarf mutants have been obtained either by natural or induced mutation, such as 99CDAM [25], Bnrga1-d (repressor of ga1-3) [26] and Bzh [17, 27]. Meanwhile, many major dwarf genes (ds-1, ndf-1, BnDWF1, DS-3) [28-31] and minor QTLs [32, 33] have been identified, all of which can be combined with yield-related genes to support and promote molecular and post-genomics breeding.

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Recently, with the rapid development of high-throughput sequencing methods, RNA-seq not only has made a figure in obtaining differentially expressed genes between a few samples, but also in analyzing transcriptome maps [34], phylogenomics [35], and phyletic evolution [36] in a larger number of accessions. That is to say, RNA-seq analysis has already been successfully in transcriptome comparisons to find differentially expressed genes [37, 38], RNA editing [39], alternative splice sites, lncRNA (Long non-coding RNA) [40], etc., and also has advantages in identifying associated SNPs or genes by bulked segregant RNA-seq [41] and associative transcriptomics [42]. Furthermore, researches about ceRNA (competitive endogenous RNA) [43] and single-molecular sequencing for eukaryotic gene prediction [44] are still ongoing.

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Plant hormones play key roles during plant growth, development and growth-defense to coordinate abiotic and biotic stress-responses. Their integrative actions in organogenesis, cell differentiation and elongation, apical meristem development, disease defense, and seed germination and maturation have been highlighting all the time. CKs (cytokinins), auxin, BRs and their cross-talks are main regulators in the maintenance of SAMs (shoot apical meristems), RAMs (root apical meristems), and even axillary meristems [45-48]. Cell differentiation in the root vascular bundle system requires the intimate relationship between CKs, IAA and KAN1 (KANADI1) [49-51]. With respect to cell and stem elongation, GA [19], the GA-GID1-DELLA module (GID1, GIBBERELLIN-INSENSITIVE DWARF1) [52], Br2, and SAUR2 (small auxin up RNA) [53, 54] involved in IAA signaling jointly regulate height and internode elongation. During root development, auxin, CKs, ET (ethylene), and ABA (abscisic acid) are responsible for RAM development and root cell growth [47, 55, 56]. In addition, many kinds of hormones have a hand in seed germination and maturation, especially GA and ABA [57, 58]. Finally, ABA, salicylic acid (SA), jasmonates (JAs), and ET are crucial regulators of the plant-pathogen trade-off between growth and survival [59, 60]. Above all, plant hormone coordination involved in whole plant growth and development processes and the ongoing investigation of these networks are more complicated as initially expected.

Materials and Methods

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In this work, we aimed to uncover differentially expressed genes and their associated metabolic pathways by aligning our results to the B. napus database and subsequently present possible reasons for the resulting pleiotropic effects in the dwarf mutant. Enrichment of GO terms and KEGG pathways were followed by cluster analysis of DEGs. Meanwhile, semi-thin sections and hormone content measurements were performed. Additionally, qRT-PCR of some DEGs involved in hormone signaling and IAA/tZ treatments were performed to validate these genes had indeed changed. These results will shed light on differential molecular mechanisms in the dwarf mutant compared to the T6 line, and give further insight into productive rapeseed molecular breeding strategies.

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Plant materials and growth conditions Field cultivation of plants

The dwarf mutant line bnaC.dwf was obtained through chemical mutagenesis using ethyl methanesulfonate (EMS) treatment of the Brassica napus inbred line T6. The wild type T6 was used as a control in all experiments. Both bnaC.dwf inbred line and T6 line were sown and grown in a field under similar conditions in Wuhan, China. Each planting row was 1.5 m wide and was spaced 0.20 m apart. The F2 populations used for statistical analysis of plant height were derived from a cross between Zhong Shuang 11 (ZS11, a widespread used rapeseed variety with normal plant height in China) and bnaC.dwf contained 1359 plants in May 2015 and 556 plants in March 2016 in Wuhan. The shoot apexes or lateral branch buds from 5-10 T6 and the mutant plants at full-bloom stage in 3

March 2016 were collected for RNA-seq, histological observation and hormone extraction and content measurement. Meanwhile, leaves and stem surfaces of topmost internode were also used for histological observation. Plant in vitro culture

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For IAA/tZ treatments, more than 135 seeds of two genotypes of bnaC.dwf and T6 were grown on culture medium with or without hormones for 10 days, and each treatment of different concentrations set 3 repeats. The culture medium consisted of 1/2× MS salts (Murashige and Skoog, Duchefa Biochemie, Holland) and agar (CAS: 9002-18-0, BR500G, Japan). Three concentration gradient of IAA (Indole-3-acetic acid, Mr: 175.18 g/mol, Sangon Biotech) and tZ (6-trans-4-hydroxy-3-methyl-2-butenylamino purine, Mr: 219.24 g/mol, Sangon Biotech) were implemented in culture medium with final concentrations of 1, 3, 10 µM and 1, 4, 8 mg/l, which marked as A1, A2, A3 and T1, T2, T3, respectively. The seedlings were used for the measurement of primary roots (PR) and hypocotyl. Plant hydroponic culture

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10-20 seeds of the WT (T6) and the mutant were planted on the same gauze which was submerged in modified Hoagland-Arnon nutrient solution (pH 5.8) [61] for 55 days. Both genotypes were grown in a plastic tray in a greenhouse (16h photoperiod, temperature 24°C/20°C (d/n), and 60–80% relative humidity). The solution was replaced once a week. For LED light effect experiment, another about 80 seeds of the two materials were planted on the 1/2× MS culture medium for 6 days. Half of the T6 and the mutant seeds were grown in a greenhouse as mentioned above and the other half of seeds under the dark conditions all the time. Shoot apexes collected from 55-day-old plants and root tips of 10-day-old hydroponic seedlings of the T6 and its mutant were used for histologic observation. Tissues were prepared as semi-thin sections (2.5–6 µm) obtained with a semi-automatic rotary type slicer (Leica RM2245; Germany).

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Sample collection for RNA-seq and Illumina sequencing

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To reduce the individual difference and environmental influence on gene expression, we sampled and pooled shoot apexes of the main stems and lateral branch buds at full-bloom stage from 3–5 individual dwarf mutant and T6 plants used for RNA-seq and transcriptome analysis. As each pool consisted of mixed samples, we just set two bilogical replications of each bnaC. dwf and the control, which were named bnaC.dwf 1, bnaC.dwf 2, control 1, and control 2. Total RNA was extracted using the TRIzol reagent (Invitrogen, USA), then treated with DNase I (ThermoScientific, USA). The mRNA was isolated from total RNA by magnetic oligo (dT) beads. Four cDNA libraries were constructed separately by enriching for poly-A+ mRNA that was used as PCR templates. Quality controls for all libraries were done with an Agilent 2100 Bioanalyzer and ABI StepOnePlus Real-Time PCR system according to the manufacture’s protocol. Finally, qualified cDNA libraries were sequenced on a platform of Illumina HiSeqTM 2000 system (BGItech, Shenzhen, China). Quality controls were followed the sequencing process and all raw reads were filtered using SOAPnuke software to acquire clean reads, which were used for aligning to the reference sequences subsequently. Clean read alignment for the B. napus reference genome and transcriptome analysis

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The clean reads were aligned to the B. napus reference genome and these sequence data and corresponding gene annotation files were downloaded from the genome website http://www.genoscope.cns.fr/brassicanapus [20]. The BWA software was used to map the reads to a reference genome, and the Bowtie software was used for mapping the reference genes [62]. The alignment results were visualized by IGV (Integrative Genomics Viewer). The genome rate and gene mapping rates (the ratio of reads that were mapped to a corresponding gene in the gene annotation file) were calculated from the two software programs previously mentioned. After estimating the alignment results for the quality control of the alignment, the level of each gene expression was measured as FPKM (fragments per kilobase per million reads) by RSEM (RNA-Seq by Expectation Maximization). This measurement method can avoid the influences of transcript size and sequencing depth of the different cDNA libraries. Identification of DEGs and functional analysis

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Based on a previous study [63], we exploited a strict arithmetic to screen DEGs from samples in each replicate. The threshold of corrected p-value was determined by the FDR and the criteria for identifying DEGs was described previously [64] with a few modifications as FDR < 0.001, |log2Ratio| ≥ 1.

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For functional analysis, all DEGs were subjected to GO annotation terms (http://www.geneontology.org/) and KEGG (http://www.genome.jp/kegg/) pathway enrichment analyses. The GO term and KEGG pathway enrichment results were considered significant with p-values amended by Bonferroni (Q-value) ≤ 0.05. Furthermore, the WEGO software was used for statistics of GO functional categories, and the top 20 statistics from KEGG pathway enrichment are shown as a scatter diagram.

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In addition, some DEGs associated with selected GO terms and KEGG pathways were analyzed by HemI 1.0 for drawing gene expression heat maps. First, we selected hormone signaling-related genes identified from KEGG pathway analysis and investigated their expression patterns. We first developed a general map of transcriptional variation that shows the involvement of these genes in hormone signal transduction pathways. Second, we compiled the DEGs related to hormone signal transduction pathways and GO term were identified to construct heat maps to investigate the expression patterns more visually. To confirm the identity and eliminate the background between the two experimental pairs, control 1 vs. bnaC.dwf 1 and control 2 vs. bnaC.dwf 2, the DEGs (Additional file 4: Table S4) involved in hormone signal transduction pathways that were present in both pairs were chosen to be visible by a heatmap. Validation of quantitative Real-Time PCR (qRT-PCR)

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Ten DEGs involved in hormone signal transduction pathways that were identified from Illumina sequencing were chosen to do qRT-PCR. The total RNA from shoot apexes which was used for RNA sequencing and root tips of 10-day-old seedlings were extracted and used as templates for qRT-PCR. Gene-specific primers were designed and their quality and specificity were verified online (http://sg.idtdna.com/primerquest/Home/Index; https://www.ncbi.nlm.nih.gov/tools/primer-blast/; http://www.idtdna.com/UNAFold) and are presented in Additional file 6: Table S6. After treatment with DNase I (Takara, Japan), 1 µg of total RNA was used to synthesize first-strand cDNA using the RevertAid First Strand cDNA Synthesis Kit (Thermo, USA) according to the manufacturer’s instructions. The first strand cDNA was diluted ~100-fold for qRT-PCR and the total reaction volume of 20 µl was composed of 8 µl dilute cDNA, 2 µl each forward and reverse primers, and 10 µl SYBR Green Realtime PCR Master Mix (TOYOBO, Japan); the reactions were performed in a 5

Bio-Rad CFX96 instrument. Total RNA was extracted from four independent samples and used for cDNA synthesis and qRT-PCR, which was performed with three technical replicates. The actin 7 (AT5G09810.1) gene was used as a control to normalize the expression quantities. The relative expression level was calculated using the 2−ΔΔCt method. Semi-thin sections and light microscopy for histologic observation All the tissues (see 2.1.3) were first fixed in FAA (5 formalin: 5 acetic acid: 90 alcohol by volume)

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overnight at 4°C, and then dehydrated in a graded ethanol series (50, 70, 95, and 100%) before being embedded in Technovit 7100 resin (Heraeus). After drying the samples for about seven days at 37°C, transverse sections and longitudinal sections were cut from the embedded blocks. The sections were stained with 0.1% toluidine blue O (Sigma-Aldrich) for 30–60 seconds at room temperature and observed with a Nikon Eclipse 80i microscope (Nikon, Japan). Images of all were captured with a Nikon DS-RiL camera (Nikon, Japan). Extraction and measurement of endogenous free IAA, ABA, SA and JA

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Statistical analysis

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Endogenous free IAA, ABA, SA, and JA were extracted and quantified as described previously by [65] and [66]. Briefly, for the WT and the mutant plants, more than 0.5 g fresh tissues were finely ground with a mortar and pestle in liquid nitrogen. The frozen material was collected for three replicates and each should be ~100 mg. All samples were extracted twice with 750 or 450 µl cold extraction buffer (80 methanol:19 water:1 acetic acid, v/v/v, all HPLC grade) in 1.5 ml tubes. The buffer for the first treatment was supplemented with internal standards (10 ng 2H6ABA for ABA, 10 ng DHJA for JA, 5 ng D2-IAA for IAA, and 3 μg NAA for SA). Ultra-Fast Liquid Chromatography-Electrospray Ionization Tandem Mass Spectrometry (UFLC-ESI-MS/MS) for hormone quantification was performed in UFLC with an autosampler (Shimadzu Corporation, Japan) and an ABI 4000 Q-Trap (Applied Biosystems). Please note that all the SA extraction solutions were diluted 200-fold for further quantification.

Results

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All data including plant height, root length, internode numbers and length, hypocotyl length, lateral root numbers, and qRT-PCR data are collected in Excel 2010. Statistical analysis of all differences between the means was produced by a two-tailed t-test with the IBM SPSS statistics 19 program. Graphs were generated by either Excel 2010 or GraphPad Prism 5.0.

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Distinct phenotypes between bnaC.dwf and the control (T6) B. napus plants Differences in plant height, shoot apical meristem (SAMs) anatomy, and leaves in bnaC.dwf plants compared to T6 plants

BnaC.dwf has a distinct dwarf plant phenotype at full-bloom stage (Figure 1A, F; p < 0.01), but the difference in height between the mutant and T6 plants decreases during the stage of final flowering (Figure 1F; p < 0.05). Meanwhile, both the frequency distribution of plant height of two F2 populations showed approximately normal distribution (Additional file 7: Figure S1). In 55-day-old hydroponic seedlings, morphological characteristics such as architecture, leaf shrinkage, and root length were obviously different from the control. The dwarf mutant plants show smaller plant architecture, smaller leaves, and shorter root length (Figure 1B-D; p < 0.01). In bnaC.dwf, each 6

internode was significantly different in an interval of 9-16 internodes counted from the bottom, even at the final flowering stage, when compared to the control. Furthermore, the number of internodes whose length was longer than 1 cm was distinct from those measured in the control plants (p < 0.05; Figure 1F).

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Seed pre-harvest sprouting and response to light

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BnaC.dwf had a relatively slow growth rate when it is concerns to the size and shape of the SAM. As shown in Figure 2A and E, axillary buds of the control plants had already formed at 55 days while the central zone (CZ) of the bnaC.dwf had just bulged for cell division and the peripheral zone (PZ) had just appeared. However, bnaC.dwf plants with lateral buds in the full-bloom stage were not obviously different from the control plants in aspect of SAM size and cell division (Figure 2B, F) except that leaf and stem surfaces of bnaC.dwf were crimped and shriveled (Figure 1B). In other words, the lower leaf epidermis was curved and intercellular spaces of spongy parenchyma were bigger than those observed in the control leaves (Figure 2C, G). Moreover, epidermis cells of the uppermost stem were more narrow and slender than the control plants, which lead to a scabrous stem surface (Figure 2D, H). These data indicate that the changes in plant height and root development had less relationship with cell size but related to cell layer number and cell growth rate.

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Besides the differences in plant architecture between the two genotypes, seed growth and development were also affected in the dwarf mutant lines. The seeds of bnaC.dwf are reddish-brown in color and wrinkled compared to the black and plump seeds of the control plants (Figure 3A). These characteristics are consistent with the seeds of bnaC.dwf discontinuing grain filling earlier at the final flowering stage than T6 plants. As typical indicators of pre-harvest sprouting, the seeds cannot be full-grown if seeds sprout in siliques when both seed coat and siliques are still green [67].

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For light response test, the dark condition cannot make up for seedling elongation deficiency compared to that of T6. However, compared to itself in light, the hypocotyl of bnaC.dwf indeed elongates (Figure 3B-C), which imply that hypocotyl growth of bnaC.dwf was also influenced by the light signaling pathways. In addition, germination experiments showed that the seedling survival rate (69.11% compared to 98.53%, n=68) is lower in bnaC.dwf. RNA-seq data analysis and functional annotation of DEGs in the bnaC.dwf mutant

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RNA-seq generated 60,268,740 (control 1), 60,224,408 (control 2), 60,301,384 (bnaC.dwf 1), and 60,134,746 (bnaC.dwf 2) clean reads after quality control and filtering from raw reads. A summary of the RNA-seq alignment results is shown in Table 1. Approximately 75.71–76.88% of the clean reads were mapped to the reference genome of B. napus and 58.88–60.03% aligned to gene locations, suggesting high-quality and credible sequencing results. After trimming and taking the means of each pair, 308 genes were found to be up-regulated and 511 genes were down-regulated in bnaC.dwf (Additional file 2: Table S2), suggesting that most of the genes had unstable expression patterns because of individual difference and environment effect. All the DEGs were jointly expressed in the paralleled pairs, control 1 vs. bnaC.dwf 1 and control 2 vs. bnaC.dwf 2, which were used for hierarchical cluster analysis and represented as a heat map (Additional file 8: Figure S2). After the initial sequence analysis, GO term and KEGG pathway enrichments were used to elucidate the functional annotations of the DEGs. To identify biological processes enriched in the DEGs, all of the 819 genes (Additional file 1: Table S1) were assigned to GO terms (Figure 4). These GO functional classifications were categorized into 41 secondary functional GO terms under three top-level ontologies that included 21 functional groups for biological process, 10 cellular component 7

groups, and 10 molecular function groups. Specifically, a larger number of genes related to “cellular process,” “metabolic process,” “response to stimulus,” and “single-organism process” was grouped in the biological process category. The “signaling” term was present in 46 out of 518 genes as well. In the cellular component category, the top three GO terms were “cell,” “cell part” and “organelle.” In the molecular function category, a majority of the genes were gathered into the “binding” and “catalytic activity” GO categories.

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To identify potential biological pathways enriched in the transcriptomes of both the mutant and the control plants, the KEGG database was utilized. A total of 488 DEGs were assigned to 98 KEGG pathways. Some selected KEGG pathways are displayed in Table 2 and the top 20 statistically significant enriched pathways are shown in Figure 5. The pathways involved in plant–pathogen interactions, oxidative phosphorylation, and amino sugar and nucleotide sugar metabolism are highlighted in red boxes. Overall, the pathways and GO functional categories identified suggest that the DEGs related to biosynthesis of secondary metabolites, plant–pathogen interactions, oxidative phosphorylation, protein degradation, photosynthesis processes, and plant hormone signal transduction account for the phenotypes of the dwarf mutant.

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Quantification of hormones in shoot apexes and signal transduction pathways enriched from RNA-seq data

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Concentration variation of endogenous hormones in the dwarf mutant

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The concentrations of the five hormones, GAs, IAA, ABA, SA, and JA only slightly changed in shoot apexes of bnaC.dwaf compared to the control. To make it clear whether free hormone content contributed to plant height, we determined the presence of these five hormones in samples identical to the RNA-seq analysis. Except for increasing of GA content, the others in the dwarf mutant showed no statistical difference to those of the control (Figure 6A-D). These results indicate that bnaC.dwf plant height may not be sensitive to or dependent on changes in hormone homeostasis.

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To further understand of the relationship between hormone concentration and root development, four genes involved in auxin and cytokinin biosynthesis were quantified by qRT-PCR. Overexpression of CYP83B1-5 (cytochrome p450, BnaA08g04520D) and BnSUR1 (sulfonylurea receptor 1, BnaA07g00460D) are involved in auxin homeostasis and may reduce IAA content by altering IAOX (Indole-3-acetaldoxime)-dependent IAA biosynthesis, by which IAOX may be channeled into indole glucosinolate biosynthesis [69]. Highly significant overexpression of BnSUR1 in bnaC.dwf (p < 0.0001) may lead to reduced IAA concentrations (Figure 11K-L). However, BnCKX1 (cytokinin oxidase/dehydrogenase 1, BnaA03g19500D) and BnIPT3 (ATP/ADP-isopentenyltransferase 3, BnaA09g55640D) are two genes involved in biosynthesis of CKs that were not significantly changed in the mutant (Figure 11 M-N). These data indicate that the content of IAA could be closely related to the mutant root characteristics such as root length, adventitious root number, and the size of the QC (quiescent center) (Figure 1E; Figure 10A, I). Expression pattern of plant hormone signal transduction-related genes

Subsequently, we focused on DEGs involved in plant hormone signal transduction. First, we developed a general map of transcriptional variation that shows the involvement of these genes in hormone signal transduction pathways (Figure 7). Second, the DEGs (Additional file 3: Table S3) related to hormone signal transduction pathways (Figure 8C) and GO term (Figure 8B) were chosen to construct heat maps to investigate the expression patterns more visually. Most selected DEGs had a consistent expression pattern, although the fold-change in expression displayed small fluctuations between the two replicates (Figure 8A-B). However, the expression quality of some genes like 8

BnaC07g44670D, BnaCnng59530D and BnaA09g42140D fluctuated to a greater degree (Figure 8A) because of tissue-dependent gene expression. Taken together, the expression patterns of the selected DEGs were dependable and consistent. Gene function of these DEGs can be further explained by each single hormone signaling pathway in Figure 7.

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To take a good look at the general transcriptional landscape of plant hormone signal transduction pathways (Figure 7), DEGs associated with IAA, CK, ABA, ET, BR, and JA signal transduction were chosen for further functional annotation. Firstly, the DEG transcriptome data indicated an abundance of important proteins involved in the auxin signal transduction pathway were changed. A good case in point is the auxin-responsive genes, such as BnAUX/IAA19 (auxin/indole-3-acetic acid 19, BnaC03g39170D), BnGH3.11/FIN219 (BnaC04g01170D), and BnSAUR78 (BnaA07g30180D). A particularly interesting finding was the down-regulation of BnKAN1 (BnaA03g06110D) in the mutant; this genes is a key cross-talk factor between auxin signaling and Class III HOMEODOMAIN-LEUCINE ZIPPER (HD-ZIPIII) TFs that regulate lateral organ and root vascular differentiation [70, 71]. In DEGs associated with CK signaling, BnLUX/PCL1 (LUX ARRYTHMO/PHYTOCLOCK 1, BnaA06g17950D, and BnaCnng37560D), which is regulated by type-A response regulators A-ARRs (authentic response regulators) and might be involved in the circadian clock [72], were also down-regulated in bnaC.dwf. DEGs associated with ABA signaling, such as ABA response factors, BnAPD5 (ARABIDOPSIS PP2C CLADE D 5, BnaC07g44600D), and BnABF3.1 (ABA-responsive element-binding factors 3, BnaC07g44670D) were up-regulated in the bnaC.dwf mutant; while the ABA activated BnSNRK2.1 (SNF1-related protein kinases 2, BnaA03g02580D) was down-regulated in shoot apexes of the dwarf mutant. These results indicate that the plant hormone signal transduction pathways were indeed affected in the dwarf mutant.

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In addition to these three plant hormones, pathways of ET, BR and JA hormone signaling were also altered in bnaC.dwf compared to T6 lines. Of the ET signaling genes, BnCTR1 (CONSTITUTIVE TRIPLE RESPONSE 1, BnaA03g01030D) and BnMPK16 (MITOGEN-ACTIVATED PROTEIN KINASE 16, BnaAnng22780D) were down-regulated, and BnERF109 (ETHYLENE RESPONSE FACTOR 109, BnaA08g11220D and BnaC03g66140D) was up-regulated simultaneously in the bnaC.dwf mutant. Additionally, three BnTCH4 genes that are related to cell wall expansion [73] and are activated by BR signaling were also up-regulated in bnaC.dwf. Finally, BnJAR1 (JASMONATE RESISTANT 1, BnaC04g01170D), BnJAZ9 (JASMONATE-ZIM 9, BnaC06g31830D), and BnaC04g46850D (AT2G40200.1, AtMYC2) are involved in JA signaling pathway and were all down-regulated in the bnaC.dwf mutant compared to the T6 control. Root development defects in bnaC.dwf mutants are rescued by exogenous IAA treatment

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Root development in the dwarf mutant is apparent in their reduced length compared to T6 roots (Figure 1E). Additionally, lateral root (LR) number (11.71 ± 1.57) was significant reduced in bnaC.dwf compared to the control (20.29 ± 2.13), which was counted from 1-4 cm of the PR in 10-day-old seedlings (p < 0.05). To better understand the effects of exogenous hormones on root growth, we performed a concentration gradient treatment of IAA and tZ of seedlings grown in MS medium (Figure 9). In 10-day-old seedlings, the root and hypocotyl lengths were not significant different between bnaC.dwf and the T6 control when treated with 1 or 10 µM exogenous IAA (Figure 9A-C; Table 3). Interesting, the root length of bnaC.dwf had less reduced when treated with concentration gradient of 1, 3, and 10µM IAA, while the hypocotyl length had similar variation to the control. From these data, we conclude that the dwarf mutant may have some defects or less sensitivity in auxin biosynthesis or signaling pathway and exogenous IAA can restore most of them. As to root and cotyledon growth in tZ treatment, bnaC.dwf seedlings presented little change of growth tendency and sensibility (Figure 9D-F). 9

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To further clarify what on earth the developmental changes in roots and hypocotyls of the bnaC.dwf mutant, we made semi-thin sections of these organs to visualize their longitudinal and transverse anatomies. Not only were zones of cell division and elongation in the dwarf mutant shortened, but the QC zone was also lost. In addition, the vascular bundle system of root tips were destroyed, especially the xylem and phloem, which differentiated in a mess, and were too indistinct to be individually identified (compare Figure 10A, E to I, M). Interestingly, in the bnaC.dwf mutant neither the root maturation zone (Figure 10B, F) nor seedling hypocotyls (Figure 10C, G) were different from the control when observed in both longitudinal and transverse sections. In addition, when treated with 1 µM IAA, the root differentiation and root development defects in the dwarf mutant were rescued, whereas the root QC zone of the control plants were smaller and its growth rate was suppressed. With the exception of being shorter root length (Table 3), root anatomies in bnaC.dwf were almost the same as the control without IAA (Figure 10D, H). However, when the control plants were treated with 1 µM IAA there were some side effects, including altered size of the QC (Figure 10L), although the cell differentiation in vascular structures did not changed at all (Figure 10P). In conclusion, the appropriate concentration of exogenous IAA could resolve root development of the dwarf mutant.

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Identification of other DEGs involved in plant-pathogen interactions, oxidative phosphorylation, protein ubiquitination and photosynthesis

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The dwarf mutant has shorter inflorescence, roots, and shriveled leaves that could restrict its ability to capture enough nutrients, water, light energy, and resist pathogens. Therefore, we investigated potential DEGs involved in plant–pathogen interactions and carbohydrate metabolism. First, the bnaC.dwf mutant seeds have lower seedling survival rate and easier to be infected (Figure 3B-C); therefore, we foremost investigated the plant–pathogen related DEGs in bnaC.dwf that resulted from our screen. As a result, five genes involved in plant–pathogen interaction pathway were significantly down-regulated in bnaC.dwf. These genes were identified as two BnPGIP2 genes (POLYGALACTURONASE INHIBITING PROTEIN 2, BnaA03g55630D and BnaA03g55660D), two BnLecRKs (L-TYPE LECTIN RECEPTOR KINASE, BnaA03g08230D and BnaA03g00760D), and one BnWRKY75-1 (WRKY DNA-binding protein 75-1, BnaA03g04160D) gene. Second, nine out of 11 genes (Figure 8D; Additional file 5: Table S5) involved in an oxidative phosphorylation pathway were down-regulated; BnCI51 (51 KDA SUBUNIT OF COMPLEX I, BnaA03g55790D), BnATP5 (DELTA SUBUNIT OF MT ATP SYNTHASE, BnaA03g04340D), and BnPPA6 (PYROPHOSPHORYLASE 6, BnaAnng37560D) were the top three representative genes in this category. Third, we concentrated on how the protein ubiquitination and proteasome pathways (Figure 8F; Additional file 5: Table S5) changed in the dwarf mutant as their indispensable and particular role in the plant hormone signal transduction pathways (Kelley and Estelle, 2012). Except for BnUBC19 (UBIQUITIN-CONJUGATING ENZYME19, BnaC06g03670D), another 10 genes were down-regulated in the dwarf mutant compared to the T6 control. Among these genes, the top four down-regulated genes were BnMIEL1 (MYB30-INTERACTING E3 LIGASE 1, BnaA03g07230D), BnRPT3 (REGULATORY PARTICLE TRIPLE-A ATPASE 3, BnaA03g09830D), BnAE3 (ASYMMETRIC LEAVES ENHANCER 3, BnaA03g01760D), and BnRPN5A (REGULATORY PARTICLE NON-ATPASE SUBUNIT 5A, BnaA03g55850D). In sugar metabolism pathways (Figure 8E; Additional file 5: Table S5), three TCA (tricarboxylic acid) cycle-related genes and four carbon fixation-related genes identified in bnaC.dwf from our DEG analysis were down-regulated. BnIDH-V (ISOCITRATE DEHYDROGENASE V, BnaA03g00820D), BnaA03g02450D, and BnaA03g04970D are involved in the TCA cycle, have NAD+-dependent isocitrate dehydrogenase activity, and are mainly located in mitochondria for dissimilation and 10

energy generation. Simultaneously, BnNADP-ME2 (BnaA03g03440D), BnYLS4 (YELLOW-LEAF-SPECIFIC GENE 4, BnaA03g03400D), NADP-MDH (BnaA03g09800D) and BnaA03g02560D which may contribute to the supply energy required for the carbon fixation pathway were both down-regulated in the dwarf mutant transcriptome. Validation of DEGs using qRT-PCR

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Among 10 DEGs that were present in two replicates and involved in hormone signaling pathways, 9 qRT-PCR profiles were agreed with those from the original RNA-seq results, although expression quality was variable and only BnaA03g02580D differed in two of the expression profiles (Figure 11 A-J). These data were consistent in both the qRT-PCR and RNA-seq analysis, and confirmed the robustness of our RNA-seq data and analysis. Discussion

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The identified DEGs and enriched pathways and GO terms in the dwarf mutant can help us better understand the molecular mechanisms and biological processes which lead to the distinct and specific phenotypes in the dwarf mutant. We mainly discuss plant hormones may affect plant height and root anatomic structure, and may involve in biotic and abiotic stress resistance of bnaC.dwf. Some other factors interplayed with hormone signaling are also discussed to better interpreting the phenotype variations in bnaC.dwf.

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Plant height is balanced and compromised by expression of DEGs in IAA signaling

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Plant height, mainly defined by stem elongation after the start of reproductive growth, is promoted and determined by cell division and SAM cell elongation [11, 19]. Auxin and CKs act antagonistically in the control of SAM size and activity [46, 48]. During internode elongation, Br2 in maize [53] and SAUR76 in Arabidopsis [74] involve the polar transport and perception of auxin. However, while the dwarf mutant used in this study exhibited some changes in SAM size and cell size of internodes (Figure 2A, B, D), we deduced that CKs were acting to maintain SAM size and may have little to do with the dwarf phenotype. However, the cell division and cell proliferation degree were both decreased, suggesting that IAA signal transduction could be affected by small changes in IAA concentration (Figure 6C).

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Auxin regulates plant growth and development by influencing cell expansion and division. The auxin receptor TIR1/AFBs can bind to AUX/IAAs and other transcription repressors in auxin signaling, and lead to the repressors degradation by the Skp, Cullin, F-box (SCF)TIR1/AFB E3 ligase complex via the ubiquitin-proteasome pathway [75]. AUX/IAAs, GH3 and SAURs are three main auxin response gene families [76]. As previously shown, BnGH3.11, which was down-regulated in bnaC.dwf, may promote growth of plants and hypocotyls by mediating phytochrome A and COP1 (constitutively photomorphogenic 1) in a light-dependent mechanism of plant development [77]. However, BnAUX/IAA19, a positive regulator of plant growth in grape [78], and BnSAUR78 may involve in cell proliferation and cell expansion [74]. Both of these genes were up-regulated in the bnaC.dwf mutant. The three genes coordinately regulate SAM growth rate and internode elongation, and lead to dynamic changes in height during the process of plant growth and development (Figure 1F). All of these results indicate that plant height was balanced and compromised by different expression patterns of DEGs in auxin signaling and perception during the reproductive stage. In addition, light, BRs and auxin play very important roles in hypocotyl elongation (Farquharson, 2016). Photoreceptors that interact with PIFs (phytochrome-interacting factors) link to auxin and BR 11

signaling to regulate cell expansion of hypocotyl. However, in the dark, they cannot make up for hypocotyl elongation defect in the dwarf mutant (Figure 3B-C), while exogenous IAA did rescue hypocotyl to the control level (Figure 9A-C). These results suggest that light transduction of bnaC.dwf maybe not affected, but auxin response genes are indeed altered such that hypocotyl growth is compromised. Auxin-KANADI1 crosstalk plays a major role in root development

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Auxin biosynthesis and transporters drive the correct localization and auxin response maximum (i.e. QC maintenance) that is partially responsible for balancing cell proliferation and differentiation in the RAM [47]. It has been recently shown that CKs and ET integrate into auxin signaling to regulate root cell elongation and proliferation through the auxin influx carrier AUX1 and auxin signaling repressor SHY2 (SHORT HYPOCOTYL 2) [79]. The BnSUR1 gene encodes an auxin conjugated enzyme that regulates auxin homeostasis and was dramatically up-regulated in bnaC.dwf (Figure 11L); the local auxin levels were decreased and could lead to a defect in cell proliferation subsequently. Furthermore, low local bio-activated IAA levels have a strong impact on the QC maintenance and RAM size in bnaC.dwf plants (Figure 10A), which seriously restrict PR development. One hypothesis for this phenotype is that exogenous IAA can make up for the QC stem niche (Figure 10D). By the way, the level of endogenous GAs in stems of bnaC.dwf is higher according to a previous study [68], and some genes involved in GA signaling were dramatically down-regulated in mutant roots (Figure 11O; Additional file 9: Figure S3); we expect that GA may also influence root development in bnaC.dwf by controlling ARR1 expression [47].

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Auxin-KAN1 cross-talk and auxin-JA cross-talk play main roles in PR vasculature development, especially during cell division and differentiation in the protoxylem. Hormones, transcription factors, microRNAs, and many other factors are involved in controlling vascular patterning [51, 56]. In addition, Class III HD-ZIP and KANADI genes regulate adaxial xylem development and abaxial phloem development respectively, while auxin signaling regulates (pre)procambium development. Class III HD-ZIP genes and KAN1 control radical patterning in the roots by promoting and restricting the canalization of auxin flow, respectively [50, 51, 80]. As BnKAN1 is down-regulated in bnaC.dwf, we infer that auxin-KAN1 crosstalk mainly controls PR vascular bundle development and inhibits xylem formation. Additionally, JA-mediated inhibition of PR growth may include the COI1-JAZ-MYC2 (COI1=CORONATINE INSENSITIVE 1) gene trio at least by the suppression of the expression of PLETHORA1 (PLT1) and PLT2, which are involved in the auxin signaling pathway and eventually controls RAM activity and stem cell maintenance in roots [81]. However, BnJAZ9 and BnaC04g46850D (AtMYC2) were both down-regulated in bnaC.dwf to keep the JA-auxin mediated inhibition of root growth in balance. Thus, the auxin-KAN1 cross-talk and auxin-JA cross-talk make a figure in root development in bnaC.dwf.

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As for LR and adventitious root (AR) formation in the dwarf mutant, the interplay between auxin-ET signaling pathways plays a prominent role in the LR and adventitious root (AR) formation in the dwarf mutant because the homeostasis of CKs may not change in root tip (Figure 11M-N). In the dwarf mutant, local auxin levels decreased not only reduces AR number [82], but also influents lateral root initiation and then shrinkages LR number (Figure 1E) [83].What is more, two DEGs, BnCTR1 and BnERF109 are involved in ET signaling and perception respectively, which mediate JA-auxin crosstalk during LR formation [84] and may affect LR numbers to some extent. In addition, BnKAN1 also mediates LR initiation downstream auxin signaling [50]. We conclude that mainly the auxin-ET interplay results in the changes to root architecture in bnaC.dwf.

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Hormones and plant-pathogen interaction genes control biotic and abiotic stress responses in bnaC.dwf

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On one hand, ABA is known to affect JA biosynthesis in plant resistance to pathogens [85], and JA-mediated defense responses against herbivores and necrotrophic pathogens have been widely endorsed [60]. On the other hand, ABA response factors, ABF and bZIP transcription factors, and the JA-mediated COI1-JAZ-MYC2 signaling complex both have a hand in salt tolerance, dehydration tolerance, and other abiotic stress resistances [86-88]. The ABA receptor complex PYR1/PYL (PYRABACTIN RESISTANCE1/PYR1-LIKE) inhibits PP2Cs (Type 2C protein phosphatases), resulting in the activation of SnRK2s that phosphorylate specific targets. The abiotic stress tolerance in bnaC.dwf may be affected by two ABA response DEGs, namely BnAPD5 and BnSNRK2.1, and an ABA-responsive element-binding factor BnABF3.1. Interestingly, the down-regulated gene BnSNRK2.1 may have something to do with seed pre-harvest sprouting and short seed dormancy of bnaC.dwf (Figure 3A) as suggested by a previous study [67].

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In addition, the weakened ability of JA-mediated biotic and abiotic stress resistance in bnaC.dwf may also lead to weaker seed vitality (Figure 3C) and weaker plant resistance to pathogens, as suggested by the down-regulation of BnJAR1, BnJAZ9 and BnaC04g46850D (AtMYC2) [60, 87]. What is more, two BnPGIP2 genes, two BnLecRKs, and one BnWRKY75-1 that positively regulate pattern-triggered immunity and contribute to plant pathogen defense [89-91], were all down-regulated. Furthermore, the up-regulation of BnAUX/IAA19 may more or less relieve the dramatically decreased defense to abiotic stress in bnaC.dwf [92]. Above all, changes in ABA-JA crosstalk and plant-pathogen interaction-related genes mainly contribute to the weaker abiotic and biotic stress resistance in bnaC.dwf compared to the T6 control plants. Other processes responsible for the bnaC.dwf phenotypes

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Oxidative phosphorylation and sugar metabolism, especially the TCA cycle supply energy for plant growth and development, and can cover the high demand for ATP in disease defense as well. Most of the DEGs involved in oxidative phosphorylation pathway were down-regulated including BnPPA6, a gene may relate to pathogen response [93]. All DEGs involved in sugar metabolism pathways were down-regulated, including BnNADP-MDH and BnNADP-ME2. The ubiquitously expressed NADP-dependent malic enzyme NADP-ME2 may affect root development and stress tolerance in Arabidopsis thaliana [94]. From the change of expression pattern of these related genes, we can infer that less energy produced for supporting biological processes.

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Similarly, protein ubiquitination and proteasome pathways are predominantly involved in hormone signaling pathways and are crucial for plant growth and development under complex abiotic and biotic stress [95]. A good case in point is BnRPN5A which is involved in embryogenesis and seedling growth [96]. That is to say, phenotype variations in the mutant are related to changes of these genes expression pattern. Finally, MAPK (mitogen-activated protein kinase) cascades may participate in ET, auxin, and abiotic stress response signaling pathways to regulate plant growth and development [97, 98]. For an example, MAP kinase not only regulates phosphorylation of the auxin transport protein, but also interacts with auxin signaling by changing gene expression patterns, and regulates plant growth and development [97]. A set of three continuously acting protein kinases, MAPK (MPK), MAPK kinase (MAPKK), and MAPKK kinase (MAP3K), phosphorylates downstream receptors step by step in each MAPK cascade. The CTR1 subgroup belongs to the MAP3K group, and their corresponding DEGs were mostly down-regulated in bnaC.dwf compared to the control (Figure 7). Therefore, 13

coupled with the down-regulation of BnMPK16, altered MAPK cascades may mediate organogenesis in bnaC.dwf. 5

Conclusions

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In light of the results from this study, we can construct complicated networks among plant hormones, plant pathogen, sugar metabolism, plant height and root development (Figure 12). In these networks, our findings about the new mutant show as follows: (1) Auxin plays a predominant role in organogenesis in bnaC.dwf, such as photomorphogenesis, cell proliferation and expansion of SAMs and internodes; (2) DEGs in auxin-KAN1 and auxin-JA cross-talks affect root development and abiotic stress tolerance of the mutant; (3) The changes in ABA and three plant-pathogen interaction-related genes are partially responsible for weaker biotic stress resistance in bnaC.dwf; (4) ABA signaling may result in pre-harvest sprouting in bnaC.dwf; (5) The ubiquitination-proteasome pathway takes part in regulating growth and development by mediating hormone signal transduction pathways; (6) ET signaling and MAPK cascades more or less affect phosphorylation levels and organogenesis; (7) Expression pattern of some genes related to oxidative phosphorylation and sugar metabolism may lead to less energy produced for the support of all the biological processes discussed above.

Declarations

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In a word, complicated regulation networks are responsible for the pleiotropic phenotypes of bnaC.dwf. These networks can partially interpret the changes in biological processes in shaping the dwarf mutant and may be helpful to genetic improvement of the dwarf mutant by applying modern crop breeding strategies.

Ethics approval and consent to participate

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We declare that none of the manuscript report data collected from humans or animals and do not involve any human participants and do not report any health related outcomes. Consent to publish

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No individual person and related information included. Availability of supporting data

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The project was submitted to NCBI BioProject with Bio-Project ID: PRJNA193477 (http://www.ncbi.nlm.nih.gov/bioproject/?term= PRJNA382037). The raw reads were deposited in NCBI SRA (Short Read Archive) with the accession number SRP103285 (http://www.ncbi.nlm.nih.gov/sra/?term=SRP103285). Other data sets supporting the results of this article are included within the article and its additional files. Competing interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding

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This work was financially supported by the National Key Research and Development Program of China (grant number 2016YFD0101300), and the Program for Modern Agricultural Industrial Technology System of China (grant number nycytx-00501). Author Contributions

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CW, LZ and JS conceived and designed the study project. JW, BY, CM, JT, and TF gave advises to the experimental design. CW performed all the experiments and analyses and then wrote the manuscript. All authors reviewed and edited this manuscript. Acknowledgments No acknowledgements here. 7

Additional files

Additional file 1: Table S1. All filtered DEGs from control vs. bnaC.dwf comparisons.

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Additional file 2: Table S2. Summary of gene numbers expressed differentially between bnaC.dwf and the control.

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Additional file 3: Table S3. DEGs related to plant hormone signal transduction pathways and their hormone-mediated signaling GO term.

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Additional file 4: Table S4. The original RNA-seq expression pattern information of DEGs involved in hormone pathways from profiles of two replicates of control 1 vs. bnaC.dwf1 and control 2 vs. bnaC.dwf 2. in

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phosphorylation,

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Additional file 5: Table S5. DEGS involved ubiqitination-proteasome, and TCA cycle pathways.

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Additional file 6: Table S6. Primers used for qRT-PCR analysis.

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Additional file 7: Figure S1. Plant height frequency distribution of two F2 populations derived from a cross between ZS11 and bnaC.dwf measured at the initial flowering stage with 1-5 flowers in March 2016 in Wuhan ( magenta bars), and at the final flowering stage in May 2015 (blue bars).

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Additional file 8: Figure S2. The heat map and hierarchical analysis of all DEGs jointly expressed in two parallel pairs of control 1 vs. bnaC.dwf 1 and control 2 vs. bnaC.dwf 2. The colored bar represents the FPKM log2Ratio. Additional file 9: Figure S3. Relative expressions of key genes involved in GA signaling in the root tips of the control and bnaC.dwf plants. The relative mRNA levels from three biological replicates were calculated using the 2−ΔΔCt method. The error bars indicate SEM. *p < 0.05, **p < 0.01, ***p < 0.001. These genes are annotated in Arabidopsis thaliana database with high homology to B. napus genes. 8

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Figures

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FIGURE 1 Plant height, leaf surface, root length, and internode comparison of bnaC.dwf and the control T6 plants. (A) Plant height of the control and bnaC.dwf plants at the full-bloom stage. (B) The leaf morphology of the control and bnaC.dwf plants after 55 days of hydroponic growth. (C, D) The phenotypes and t-test of root length of 55-day-old plants, respectively. Error bar is SD. (E) A growth test for roots and hypocotyls on medium for 10 days as described in the methods. A partially enlarged detail present lateral root number and growth. The five seedlings on the left are bna.dwf and five on the right are the control. (F) The histogram of internode number of the control and bnaC.dwf plants at the final flowering stage and the stacked bar graph of each internode length at two growth stages. Internodes whose length is more than 1 centimeter (cm) were counted. Error bar is SEM. Scale bars = 5 cm. *p < 0.05, **p < 0.01, ***p < 0.001. BnaC.dwf was set on the left and the control on the right.

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FIGURE 2 Semi-thin sections of the shoot apex, leaf, and uppermost internode in bnaC.dwf and the control T6 plants. (A, E) The longitudinal sections of shoot apexes of bnaC.dwf and the control hydroponically grown seedlings at 55 days and (B, F) axillary bud apexes at the full-bloom stage. AbM, Axillary bud meristem; CZ, Central zone; LP, Leaf primordium; PZ, Peripheral zone; SAM, Shoot apical meristem; YL, Young leaf. The arrow indicates a developing vascular strand. Cross-sections of leaves from (C) bnaC.dwf and (G) the control plants. bs, bundle sheath; pp, palisade parenchyma; sp, spongy parenchyma. The arrowhead indicates a looser pp in bnaC.dwf compared to the control. The longitudinal sections of the uppermost internode surfaces in (D) bnaC.dwf and (H) the control. The stars indicate the denser and more slender cells in the bnaC.dwf samples. All scale bars = 100 μm.

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FIGURE 3 Seed pre-harvest sprouting and the effects of light on plant growth. (A) Comparison of seed color, seed shape, and seed pre-harvest sprouting (shown in the partially enlarged details) between bnaC.dwf and the control plants. The scale bars = 2 mm. (B) The effects of dark and (C) light conditions on growth in bnaC.dwf and the control plants. The seeds showed in the partial enlarged detail were much easier to infect phathogens hidden in seed coats of bnaC.dwf at the final stage of seed development. Scale bars = 2 cm.

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FIGURE 4 Clusters of annotated GO terms in the biological process, cellular component, and molecular function categories enriched in 819 DEGs from shoot apexes of control and bnaC.dwf plants. The horizontal ordinate represents the number of genes in each category. The signaling category is shown in the red box.

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FIGURE 5 Scatter diagram of the top 20 statistics from KEGG pathway enrichment for control vs. bnaC.dwf. The Q-value was amended by the Bonferroni method. The “richfactor” positively correlates with the degree of enrichment. Red boxes indicate the pathways highlighted in our analysis. FIGURE 6 | Concentrations of ABA (A), JA (B), IAA (C), and SA (D) in shoot or axillary bud apexes of control and bnaC.dwf. All of them are not significant different between bnaC.dwf and the control plants. The units are ng/g for all. Error bars are SEM. FIGURE 7 Transcriptional changes in plant hormone signal transduction pathways in bnaC.dwf. All DEGs were mapped to the KEGG pathway database and some were enriched in plant 24

hormone signaling pathways. Up- and down-regulation gene expression patterns are boxed in green and red, respectively.

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FIGURE 8 Transcript profiles and heat maps of DEGs involved in enriched GO categories or KEGG pathways. Log2Ratios of bnaC.dwf and control gene expressions were used for clustering analysis in HemI. (A) DEGs involved in hormone signal transduction pathways in two replicates, control 1 vs. bnaC.dwf 1 and control 2 vs. bnaC.dwf 2. (B) DEGs with the GO category of hormone-mediated signaling pathway. (C) DEGs expressed in bnaC.dwf and the control plants that are involved in the plant hormone transduction pathway. DEGs associated with (D) oxidative phosphorylation, (E) the TCA cycle and carbon fixation, and (F) protein ubiquitination and the proteasome.

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FIGURE 9 Exogenous IAA and tZ treatments on 10-day-old bnaC.dwf and control seedlings. Five seeds of bnaC.dwf and control were each treated with exogenous IAA at different final concentrations marked in figures as (A) A1 (1 µM), (B) A2 (3 µM), and (C) A3 (10 µM). (D-F) Treatments with different tZ final concentrations marked in figures as (D) T1 (1 mg/l), (E) T2 (4 mg/l), and (F) T3 (8 mg/l). The growth conditions conform to the method of this paper. All scale bars = 3 cm.

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FIGURE 10 Histologic observations of hypocotyl and root anatomies with/without 1 µM IAA treatment of bnaC.dwf control 10-day-old seedlings. (A, I) Semi-thin longitudinal and (E, M) cross sections of the roots of seedlings grown in culture medium with no IAA supplemented. (A) The QC and (E) protoxylem (procambium) were lost and disorganized. The proximal meristem and elongation zone in root tips in (A, E) bnaC.dwf were both smaller than that in (I, M) control samples. However, (B, F, J, N) the maturation zone and (C, G, K, O) hypocotyl anatomies of bnaC.dwf was of normal size with little change. (D, H) Root tip structure of bnaC.dwf and (L, P) control seedlings after treatment with 1 µM IAA. Exogenous IAA rescues the root development defects observed in bnaC.dwf. (D) The QC and (H) protoxylem development were restored in IAA treated mutant seedlings. (L) The QC size of control seedlings shrunk (indicated with “*”), but its (P) protoxylem was not destroyed. QC, quiescent center; a, epidermis; b, cortex parenchymal cell; c, pericycle cell; d, protoxylem; e, protophloem; f, messed procambium. All scale bars = 100 µm.

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FIGURE 11 Validation of 10 selected DEGs by qRT-PCR and the relative expression of genes involved in IAA and CKs homeostasis. (A-J) Validation of 10 selected DEGs by qRT-PCR. Relative expression is set on the left Y-axis with blue columns and RNA-seq data in FPKM (fragments per kilobase per million reads) are on right the Y-axis with red lines. All of the genes except for BnaA03g02580D exhibited consistent expression patterns between qRT-PCR and RNA-seq analyses. (K-N) Relative expression of each two genes participated in (K-L) IAA and (M-N) CKs homeostasis. (O) A gene involved in SCFSLY1 E3 ligase complex mediated ubiquitination process of RGA, a DELLA protein involved in GA signaling. The gene names were modified by adding “Bn” to the front of homologous Arabidopsis genes. The relative mRNA levels of the three biological replicates were calculated using the 2−ΔΔCt method. Error bars are SEM. ***p < 0.001. FIGURE 12 A schematic of the complex networks of the changed biological processes and predicted genes that contribute to the phenotypic variations in bnaC.dwf. Red font indicates up-regulated genes and dark blue front indicates down-regulated genes in the bnaC.dwf mutant. Each pathway is indicated with arrows of different colors and plant hormones are marked with boxes. The red arrows indicate crosstalk between each pathway and black arrows attached to the green boxes represent the possible functions for each gene in regulating plant growth and development. “GA?” 25

indicates that GA may take part in root development through BnSLY1 (Sleepy 1) referred to in the figure as 11O. CTR1 in both dark blue and red shows that CTR1 group contains two subgroups with different expression patterns.

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TABLE 1 Summary of RNA-seq data from shoot apexes of the control (T6) and bnaC.dwf plants Clean reads

control 1 control 2 bnaC.dwf 1 bnaC.dwf 2

60268740 60224408 60301384 60134746

Genome map rate 76.88% 75.86% 76.33% 75.71%

Gene map rate 59.83% 58.88% 59.15% 60.03%

Expressed gene 59301 59429 58579 60074

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Sample name

TABLE 2 Analysis of selected KEGG pathways for DEGs identified between T6 and bnaC.dwf Pathway Biosynthesis of secondary metabolites Plant-pathogen interaction Plant hormone signal transduction

DEGs with pathway annotation (488) 58 (11.89%) 42 (8.61%) 26 (5.33%)

All genes with pathway annotation (48096) 6100 (12.68%) 3571 (7.42%) 3174 (6.6%)

Q value

Pathway ID

3.12e-04 8.78e-01 9.64e-01

ko01110 ko04626 ko04075

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4 (0.82%) 1 (0.2%) 14 (2.87%) 7 (1.43%) 4 (0.82%) 11 (2.25%) 9 (1.84%) 4 (0.82%) 4 (0.82%) 3 (0.61%)

485 (1.01%) 264 (0.55%) 1324 (2.75%) 905 (1.88%) 306 (0.64%) 685 (1.42%) 581 (1.21%) 81 (0.17%) 343 (0.71%) 276 (0.57%)

8.92e-04 9.64e-01 9.54e-01 9.64e-01 9.44e-01 7.61e-01 8.92e-04 9.75e-03 1.39e-01 9.64e-01

ko00906 ko00908 ko04141 ko04120 ko03050 ko00190 ko00520 ko00196 ko00710 ko00020

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Carotenoid biosynthesis Zeatin biosynthesis Protein processing in endoplasmic reticulum Ubiquitin mediated proteolysis Proteasome Oxidative phosphorylation Amino sugar and nucleotide sugar metabolism Photosynthesis-antenna proteins Carbon fixation in photosynthetic organisms Citrate cycle (TCA cycle)

TABLE 3 Seedling phenotypes after treatment with different IAA concentrations

bnaC.dwf

Hypocotyl length 2.02± 0.16 2.52± 0.26

PR length 5.69± 0.23 5.10± 0.54

A2 (3 µM)

Hypocotyl length 2.4± 0.24 2.74± 0.21

PR length 3.06± 0.32* 4.33± 0.40

Hypocotyl length 2.30± 0.51 2.30± 0.44

A3 (10 µM)

PR length 2.63± 0.22 2.92± 0.30

Hypocotyl length 2.10± 0.36 2.46± 0.22

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PR length 8.15± 0.32* 10.47± 0.65

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The “*” represents a statistical difference of p < 0.05 between bnaC.dwf and the control samples (n ≥ 5, 10 days, cm).

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