Characterization and comparative analysis of the first mitochondrial genome of <i>Michelia</i> (Magnoliaceae)

Suyan Wang; Jing Qiu; Ning Sun; Fuchuan Han; Zefu Wang; Yong Yang; Changwei Bi; Suyan Wang; Jing Qiu; Ning Sun; Fuchuan Han; Zefu Wang; Yong Yang; Changwei Bi

doi:10.48130/gcomm-0025-0001

2025 Volume 2

Article Contents

Abstract

References

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ARTICLE Open Access

Characterization and comparative analysis of the first mitochondrial genome of Michelia (Magnoliaceae)

1.
State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Key Laboratory of Tree Genetics and Biotechnology of Educational Department of China, Key Laboratory of Tree Genetics and Silvicultural Sciences of Jiangsu Province, Nanjing Forestry University, Nanjing 210037, China
2.
College of Information Science and Technology & Artificial Intelligence, Nanjing Forestry University, Nanjing 210037, China
3.
Information Department, The First Affiliated Hospital of Naval Medical University, Shanghai 200433, China
4.
Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Fuyang 311400, China
^# Authors contributed equally: Suyan Wang, Jing Qiu

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Corresponding authors: yangyong@njfu.edu.cn; bichwei@njfu.edu.cn

Received: 24 November 2024
Revised: 03 January 2025
Accepted: 07 January 2025
Published online: 24 January 2025
Genomics Communications 2, Article number: e001 (2025) | Cite this article

Abstract

Genus Michelia has various functions and is valuable in medicine, food, and agriculture. Many plastid genomes (plastomes) of Michelia have been released, but no mitochondrial genomes (mitogenomes) have been reported. In this study, using third-generation HIFI sequencing techniques, Michelia figo (M. figo) mitogenome was de novo assembled into a circular chromosome spanning 773,377 bp with a total GC content of 46.83%. Sixty six genes in total were annotated, including 41 protein-coding genes, 21 tRNA genes, and three rRNA genes. The mitogenome contains 1,514 dispersed repeats (> 30 bp), 39 tandem repeats, and 262 simple sequence repeats. Eighty one fragments originating from the M. figo plastome were detected in its mitogenome and three tRNA genes (trnD-GUC, trnW-CCA, and trnV-GAC) completely transferred from the plastome to the mitogenome. Repeats and collinearity analyses of four Magnoliaceae mitogenomes reveal substantial structural variations, a relatively low degree of collinearity, and significant genetic diversity of this genus. Phylogenetic analysis showed that two phylogenetic trees constructed separately based on mitogenomes and plastomes accurately depict the phylogenetic relationship of M. figo. This study offers the first comprehensive comparative genomic and phylogenetic analysis of the M. figo mitogenome, facilitating the development of genetic markers, taxonomic classification, and resource exploration within the Michelia genus.
- Michelia figo,
- Mitochondrial genome,
- Comparative analysis,
- Phylogenetic analysis
Introduction

Plants are continuously subjected to unpredictable environmental conditions and encounter a multitude of stressors throughout their growth and development, posing a significant challenge to global crop production and food security^[1]. Heat and drought are undoubtedly the two most important stresses that have a huge impact on crops. Both elicit a wide array of biochemical, molecular, and physiological alterations and responses, impacting diverse cellular processes and ultimately influencing crop yield and quality^[2].

A primary physiological consequence of both stresses is the diminished photosynthetic capacity, partially resulting from the degradation of chlorophyll due to leaf senescence under stress conditions. Chlorophyll accumulation was diminished in numerous plants subjected to drought or heat stress conditions^[3,4]. Various environmental stresses prompt excessive generation of reactive oxygen species (ROS), initiating oxidative damage that compromises lipids, and proteins, and poses a serious threat to cellular functions^[2]. To mitigate oxidative stress and minimize damage, plants have developed various protective mechanisms to neutralize ROS. Several antioxidant enzymes, such as SOD, POD, and CAT, are integral to cellular antioxidative defense mechanisms. Additionally, antioxidants such as anthocyanins and proline serve as crucial ROS scavengers^[5,6]. The elevation in temperature typically induces the transient synthesis of heat shock proteins (Hsps), which function as molecular chaperones in protecting proteins from denaturation and aggregation, with their activity primarily regulated at the transcriptional level by heat shock factors (Hsfs)^[7]. The significance of Hsps and Hsfs in all organisms, including plants, has been assessed in various stress conditions that could disrupt cellular homeostasis and result in protein dysfunction^[7]. Drought stress can also trigger the transcription of a suite of marker genes, including RD29A, RD29B, NCED3, AREB1, Rab18, etc., which assist plants in mitigating cellular damage during dehydration and bolstering their resilience to stress^[8−10].

Previous research efforts focusing on the regulatory control of stress-related genes have largely centered around protein-coding genes. In recent years, non-protein-coding transcripts have emerged as important regulatory factors in gene expression. Among them, long non-coding RNAs (lncRNAs) lncRNAs have been identified as implicated in various abiotic stresses^[11,12]. LncRNAs are a class of non-coding RNAs (ncRNAs) exceeding 200 nucleotides in length. They possess minimal or no protein-coding potential^[13]. In plants, lncRNAs are specifically transcribed by RNA polymerases Pol IV, Pol V, Pol II, and Pol III^[14,15]. LncRNAs exhibit low abundance and display strong tissue and cellular expression specificity relative to mRNAs. Moreover, sequence conservation of lncRNAs is was very poor across different plant species^[13,16,17]. The widespread adoption of high-throughput RNA sequencing technology has revealed lncRNAs as potential regulators of plant development and environmental responses. In cucumber, RNA-seq analysis has predicted 2,085 lncRNAs to be heat-responsive, with some potentially acting as competitive endogenous RNAs (ceRNAs) to execute their functions^[18]. In radish, a strand-specific RNA-seq (ssRNA-seq) technique identified 169 lncRNAs that were differentially expressed following heat treatment^[19]. In Arabidopsis, asHSFB2a, the natural antisense transcript of HSFB2a was massively induced upon heat stress and exhibited a counteracted expression trend relative to HSFB2a. Overexpression of asHSFB2a entirely suppressed the expression of HSFB2a and impacted the plant's response to heat stress^[20]. For drought stress resistance, 244 lncRNAs were predicted in tomatoes to be drought responsive probably by interacting with miRNAs and mRNAs^[21]. Under drought stress and rehydration, 477 and 706 lncRNAs were differentially expressed in drought-tolerant Brassica napus Q2 compared to drought-sensitive B. napus, respectively^[22]. In foxtail millet and maize, 19 and 644 lncRNAs, respectively, were identified as drought-responsive^[23,24]. Despite the identification of numerous lncRNAs by high-throughput sequencing, which suggests their potential involvement in various abiotic stress processes, only a minority have been experimentally validated for function.

In our previous study, we characterized 1,229 differentially expressed (DE) lncRNAs in Chinese cabbage as heat-responsive, and subsequent bioinformatics analysis reduced this number to 81, which are more likely associated with heat resistance^[25]. lnc000283 and lnc012465 were selected from among them for further functional investigation. The findings indicated that both lnc000283 and lnc012465 could be promptly induced by heat shock (HS). Overexpression of either lnc000283 or lnc012465 in Arabidopsis plants enhanced their capacity to tolerate heat stress. Additionally, both lnc000283 and lnc012465 conferred drought tolerance to transgenic Arabidopsis.

Materials and methods

Plant materials, growth conditions, and stress treatment

The lncRNA sequences examined in this study were from Chiifu-401-42 Chinese cabbage and all Arabidopsis plants were of the Col-0 background. Transgenic plants expressing lnc000283 and lnc012465 were generated using the Agrobacterium tumefaciens-mediated floral dip method^[26]. Single-copy and homozygous T3 plants were identified through genetic segregation on an agar medium supplemented with kanamycin. The T3 generation plants, or their homozygous progeny, were utilized in the experiments.

For phenotypic assessment, Arabidopsis seeds were initially sown on filter paper moistened with ddH₂O and placed in a 4 °C freezer for 2 d. Subsequently, they were evenly planted in nutrient-rich soil and transferred to a growth chamber operating a 16-h day/8-h night cycle, with day/night temperatures of 22 °C/18 °C and a light intensity of 250 μmol·m⁻²·s⁻¹. After 10 d of growth, Arabidopsis plants with uniform growth were transferred to 50-hole plates. Arabidopsis plants grown in Petri dishes were firstly seed-sterilized and then sown on 1/2 MS medium supplemented with 10 g·L⁻¹ sucrose. The seeds were then placed in a 4 °C refrigerator for 2 d in the dark before transferring them to a light incubator. The day/night duration was set to 16 h/8 h, the day/night temperature to 21 °C/18 °C, and the light intensity to 100 μmol·m⁻²·s⁻¹.

For heat treatment, 3-week-old seedlings were subjected to 38 °C for 4 d within a light incubator, subsequently transferred to their original growth conditions under the same light/dark cycles. For drought treatment, 3-week-old Arabidopsis seedlings were deprived of water for 10 d, followed by rehydration to facilitate a 2-d recovery period. Plants were photographed and surveyed both before and after treatment.

Vector construction

The lncRNA sequences (lnc000283 and lnc012465) were chemically synthesized based on RNA-seq data, with restriction sites for BamH1 and Kpn1 engineered upstream and downstream. The resultant lncRNA constructs were subcloned into the pCambia2301 binary vector, incorporating a cauliflower mosaic virus (CaMV) 35S promoter. The recombinant vectors were transformed into Escherichia coli TOP10 competent cells (Clontech), incubated at 37 °C overnight, after which single clones were selected for PCR verification, and the confirmed positive colonies were submitted for sequencing. Following verification, the correct plasmids were introduced into A. tumefaciens strain GV3101 using the freeze-thaw method and subsequently transformed into Arabidopsis wild-type (Col) plants.

Chlorophyll and anthocyanin content determination

To quantify the chlorophyll content, the aerial portions of wild-type and transgenic Arabidopsis plants, grown in Petri dishes were weighed, minced, and then subjected to boiling in 95% ethanol until fully decolorized. Aliquots of 200 μL from the extract were transferred to a 96-well plate and the absorbance at 663 nm and 645 nm was measured via spectrophotometry by a microplate reader (Multiskan GO, Thermo Scientific, Waltham, MA, USA). Three biological replicates were analyzed for WT and each transgenic line. Chlorophyll content was determined according to the formula of the Arnon method^[27]: Chlorophyll a = (12.72A₆₆₃ − 2.59A₆₄₅) v/w, Chlorophyll b = (22.88A₆₄₅ − 4.67A₆₆₃) v/w, Total chlorophyll = (20.29A₆₄₅ + 8.05A₆₆₃) v/w.

The quantification of anthocyanin was performed as follows: aerial parts of wild-type and transgenic Arabidopsis plants, cultivated in Petri dishes, were weighed and ground to powder in liquid nitrogen. Subsequently, the samples were incubated in 600 μL of acidified methanol (containing 1% HCl) at 70 °C for 1 h. Following this, 1 mL of chloroform was added, and the mixture was vigorously shaken to remove chlorophyll. The mixture was then centrifuged at 12,000 rpm for 5 min, after which the absorbance of the aqueous phase was determined at 535 nm using a spectrophotometer (Shimadzu, Kyoto, Japan). Three biological replicates were analyzed for WT and each transgenic line. The relative anthocyanin content was calculated according to anthocyanin concentration and extraction solution volume. One anthocyanin unit is defined as an absorption unit at a wavelength of 535 nm in 1 mL of extract solution. In the end, the quantity was normalized to the fresh weight of each sample.

Physiological analysis

Three-week-old transgenic and WT A. thaliana plants, subjected to normal conditions or varying durations of heat or drought stress, were utilized for subsequent physiological assessments. All assays were performed in accordance with the method described by Chen & Zhang^[28]. In brief, 0.1 g of fresh leaf tissue was homogenized in 500 μL of 100 mM PBS (pH 7.8) while chilled on ice. The homogenate was then centrifuged at 4 °C, and the resultant supernatant was employed for further analysis. For the determination of MDA content, 100 μL of the supernatant was combined with 500 μL of a 0.25% thiobarbituric acid (TBA) solution (which was prepared by dissolving 0.125 g of TBA in 5 mL of 1 mol·L⁻¹ NaOH before being added to 45 mL of 10% TCA) and boiled for 15 min. Following a 5 min cooling period on ice, the absorbance was measured at 532 nm and 600 nm. The activity of POD was determined as follows: initially, 28 μL of 0.2% guaiacol and 19 μL of 30% H₂O₂ were sequentially added to 50 mL of 10mM PBS (pH 7.0), after thorough heating and mixing, 1 mL was transferred into a cuvette, then 50 μL of the supernatant was added to the cuvette and the absorbance at 470 nm was monitored every 15 s for 1 min. To determine the proline content, a reaction solution was prepared by mixing 3% sulfosalicylic acid, acetic acid, and 2.5% acidic ninhydrin in a ratio of 1:1:2, then 50 μL of the supernatant was added to 1 mL of the reaction solution, which was then subjected to a boiling water bath for 15 min (the solution turned red after the boiling water bath). Following cooling on ice, the absorbance at 520 nm was recorded. For the quantification of proline, an L-proline standard curve was prepared by dissolving 0, 5, 10, 15, 20, 25, and 30 μg of L-proline in 0.5 mL of ddH₂O, followed by the addition of 1 mL of the reaction solution and measuring the absorbance at 520 nm. The proline content in the samples was then determined based on the L-proline standard curve.

RNA isolation and qRT-PCR analysis

Total RNA was isolated from the aerial parts of Arabidopsis using the TaKaRa MiniBEST Plant RNA Extraction Kit, followed by purification and reverse transcription using the PrimeScript RT reagent Kit with gDNA Eraser (Takara). The cDNA product was diluted 10 times and real-time PCR was conducted in triplicate for each biological replicate using SYBR PCR Master Mix (Applied Biosystems) on the ABI 7500 system under the following conditions: 98 °C for 3 min, followed by 40 cycles of 98 °C for 2 s and 60 °C for 30 s. The relative expression levels of each gene were normalized against the transcript abundance of the endogenous control UBC30 (At5g56150) and calculated using the 2^−ΔCᴛ method. The specific primers employed for qRT-PCR are detailed in Supplemental Table S1.

Results

Screening and characterization of lncRNAs

In our prior investigation, dozens of lncRNAs associated with the heat stress response in Chinese cabbage were identified through informatics analysis. Two lncRNAs (lnc000283 and lnc012465) were chosen for genetic transformation in Arabidopsis to elucidate their functions comprehensively. Transcriptome data analysis indicated that the expression of lnc000283 and lnc012465 in Chinese cabbage were both induced by HS. To verify the accuracy, the expression patterns of lnc000283 and lnc012465 were confirmed through quantitative real-time PCR (qRT-PCR), and the results from qRT-PCR were consistent with those obtained from RNA-seq (Fig. 1a). The corresponding homologous genes in Arabidopsis were identified as CNT2088434 and CNT2088742, exhibiting sequence similarities of 88% and 87%, respectively (Supplemental Fig. S1). Subcellular localization predictions using the lnclocator database (www.csbio.sjtu.edu.cn/bioinf/lncLocator) suggested that both lncRNAs are localized within the nucleus (Supplemental Table S2). Bioinformatics analysis was conducted using the CPC tool (http://cpc.cbi.pku.edu.cn/) indicated that lnc000283 and lnc012465 are noncoding sequences, with coding probabilities of 0.0466805 and 0.0432148, respectively comparable to the well-characterized lncRNAs COLDAIR and Xist, but significantly lower than those of the protein-coding genes UBC10 and ACT2 (Fig. 1b).

Figure 1. Characteristics of lnc000283 and lnc012465. (a) Expression level of lnc000283 and lnc012465 in Chinese cabbage leaves treated at 38 °C at different time points, as determined by qRT-PCR and RNA-seq. CK is a representative plant before heating, and T1, T4, T8, and T12 denote plants that were subjected to 38 °C for 1, 4, 8, and 12 h, respectively. The expression levels were normalized to the expression level of Actin. (b) Analysis of coding potential for lnc000283 and lnc012465. The coding potential scores were calculated using the CPC program. UBC10 (At5g53300) and ACT2 (At3g18780) are positive controls that encode proteins. COLDAIR (HG975388) and Xist (L04961) serve as negative controls, exhibiting minimal protein-coding potential.

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Generation of lncRNA overexpression lines

To elucidate the role of lnc000283 and lnc012465 in response to abiotic stress, overexpression vectors were constructed for these lncRNAs, driven by the CaMV 35S promoter, and they were introduced into Arabidopsis thaliana (Col-0 ecotype). Through PCR identification and generational antibiotic screening, two homozygous positive lines for lnc012465 and lnc000283 were obtained. The relative expression levels of these lncRNAs were assessed using qRT-PCR (Fig. 2a). When plants were grown in 1/2 MS medium, with the consumption of nutrients, and reduction of water, the leaves of WT began to turn yellow, but the lnc000283 and lnc012465 overexpression lines developed a deep purple color of leaf veins (Fig. 2b). Examination of chlorophyll and anthocyanin contents in the plants revealed that both overexpression lines had higher levels of chlorophyll and anthocyanin compared to the WT, suggesting that the transgenic plants might possess enhanced resistance to nutritional or water stress (Fig. 2c, d).

Figure 2. Arabidopsis plants overexpressing lnc000283 and lnc012465 had higher anthocyanins and chlorophyll content. (a) The relative expression level of lnc000283 and lnc012465 in WT and different transgenic lines. UBC10 (At5g53300) was used as an internal control. Each value is mean ± sd (n = 3). (b) The phenotype of WT and Arabidopsis overexpressing lnc000283 or lnc012465 grown on 1/2 MS medium 50 d after sowing. The (c) anthocyanin and (d) chlorophyll content of WT and transgenic Arabidopsis overexpressing lnc000283 or lnc012465. The asterisks above the bars indicate statistical significance using Student's t-test (*, p < 0.05; **, p < 0.01).

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Effect of lncRNA overexpression on heat tolerance in Arabidopsis

Given that lnc000283 and lnc012465 were highly induced by heat, the thermotolerance of the overexpressing (OE) plants were compared to that of the wild type. Arabidopsis plants were initially exposed to a an HS treatment at 38 °C for 4 d, followed by recovery at room temperature. The death caused by HS was processive. Post-severe HS challenge for 4 d, OE plants initially appeared similar to WT, but upon recovery, their leaves started to fold or curl, followed by a transition to yellow, white, and eventually drying out (Fig. 3a). OE lnc000283 and OE lnc012465 plants exhibited enhanced thermotolerance compared to WT, with lnc012465 showing particularly strong tolerance (Fig. 3a; Supplemental Fig. S2a). After 5 d of recovery, leaf coloration indicated that transgenic plants maintained a significantly higher percentage of green leaves and a lower percentage of bleached leaves compared to WT (Fig. 3b; Supplemental Fig. S2b). Under non-heat-stress conditions, WT and OE plants possessed comparable water content. However, following heat stress, the fresh-to-dry weight ratio of OE lnc000283 and lnc012465 lines was significantly greater than that of WT (Fig. 3c; Supplemental Fig. S2c). Abiotic stresses frequently trigger the production of excessive reactive oxygen species (ROS), which are believed to cause lipid peroxidation of membrane lipids, leading to damage to macromolecules. Leaf MDA content is commonly used as an indicator of lipid peroxidation under stress conditions; therefore, the MDA content in both transgenic and WT plants was assessed. Figure 3d shows that the MDA content in WT plants progressively increased after heat treatment, whereas in the two lines overexpressing lnc012465, the MDA content increased only slightly and remained significantly lower than that in WT at all time points. In plants overexpressing lnc000283, the MDA content did not significantly differ from that of WT before heat stress. However, after 4 d of heat treatment, the MDA content was significantly lower compared to WT (Supplemental Fig. S2d). The results suggested that the expression of both lnc012465 and lnc000283 can mitigate injury caused by membrane lipid peroxidation under heat-stress conditions. Peroxidase (POD) is a crucial antioxidant enzyme involved in ROS scavenging. Figure 3e and Supplemental Fig. S2e demonstrate that POD activity increased in both transgenic and WT plants after heat treatment. However, the increase in WT plants was modest, whereas OE lnc000283 and OE lnc012465 plants exhibited consistently higher POD activity. As anticipated, proline levels were induced in response to stress in all studied plants (Fig. 3f; Supplemental Fig. S2f). However, under normal conditions and 2 d post-heat stress treatment, the proline content in OE lnc000283 and OE lnc012465 plants did not exhibit significant changes compared to WT (Fig. 3f; Supplemental Fig. S2f). Moreover, after 4 d of heat stress, the proline content in OE lnc012465 lines was significantly lower than in WT, and the OE lnc000283 transgenic line 12-6 also showed a marked decrease in proline content compared to WT (Fig. 3f; Supplemental Fig. S2f). The results indicated that the thermotolerance of plants overexpressing either lnc000283 or lnc012465 was independent of proline accumulation.

Figure 3. Overexpressing lnc012465 lines are more tolerant to heat stress. (a) Phenotypes of WT and OE lnc012465 plants were assessed before and after exposure to heat stress. The heat treatment was applied to 25-day-old Arabidopsis plants. (b) The percentage of leaves with different colors in Arabidopsis after heat treatment and recovery for 5 d. (c) The fresh-to-dry weight ratio of Arabidopsis leaves was measured before and after 38 °C heat treatment. (d)−(f) depict the MDA content, POD activity, and proline content in Arabidopsis leaves at varying durations of heat stress. The asterisks above the bars indicate statistical significance using Student's t-test (*, p < 0.05; **, p < 0.01; ***, p < 0.001).

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Effect of lncRNA overexpression on the expression quantity of genes related to high-temperature response in Arabidopsis

To elucidate the molecular mechanisms by which lncRNAs enhance thermotolerance in Arabidopsis, the expression of the Hsf gene HsfA7a and three Hsps (Hsp25.3, Hsa32, and Hsp18.1-CI) in OE lnc000283, OE lnc012465, and WT Arabidopsis plants were investigated at various time points following heat treatment. As shown in Fig. 4 and Supplemental Fig. S3, both Hsf and Hsps exhibited a rapid response to heat stress with strong induction. Notably, the transcripts of HsfA7a and Hsp25.3 were significantly upregulated at 1 h after heat exposure, then experienced a sharp decrease. Hsa32 and Hsp18.1-CI were highly induced at 1 h and, unlike the other proteins, sustained high expression levels at 3 h (Fig. 4; Supplemental Fig. S3). At 1 h post-heat treatment, the transcript levels of Hsa32 and HsfA7a in OE lnc000283 did not significantly differ from those in WT. However, by 3 h, Hsa32 expression was roughly 50% of the WT level, while HsfA7a expression was approximately double that of WT (Supplemental Fig. S3). The overexpression of lnc000283 did not significantly affect the transcript level of Hsp25.3 at any of the tested time points. Notably, Hsp18.1-CI expression in both lines overexpressing lnc000283 was significantly induced at all three detection points post-heat treatment, reaching approximately 4-9-fold higher levels than in the WT (Supplemental Fig. S3). In Arabidopsis plants with elevated expression of lnc012465, the expression patterns of all Hsp and Hsf genes were similar to those in plants overexpressing lnc000283, with the notable exception of Hsa32. Unlike the WT, Hsa32 did not show a trend of down-regulation at 3 h post-heat treatment (Fig. 4). The findings suggest that the substantial induction of Hsp18.1-CI may play a role in enhancing the thermotolerance of Arabidopsis plants overexpressing lnc000283 and lnc012465.

Figure 4. The expression of HSF and HSP genes in lnc012465 overexpressing lines before and after different heat treatment times. Gene expression levels were quantified using RT-qPCR and normalized to UBC10 (At5g53300). Each value represents the mean ± standard deviation (n = 3). The asterisks above the bars indicate statistical significance using Student's t-test (*, p < 0.05; **, p < 0.01; ***, p < 0.001).

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Effect of lncRNA overexpression on drought tolerance in Arabidopsis

Prior research has implicated a significant proportion of genes in conferring resistance to various abiotic stresses. To elucidate the functions of lnc000283 and lnc012465 more thoroughly, WT and transgenic plants were subjected to drought stress by depriving them of water for 9 d. It was noted that the majority of leaves in WT plants withered and dried, whereas the OE lnc000283 and OE lnc012465 plants exhibited reduced withering, with only a minority displaying dryness (Fig. 5a; Supplemental Fig. S4a). Eight days post-rewatering, a negligible fraction of WT seedlings exhibited recovery, whereas the overwhelming majority of transgenic plants regained vigorous growth (Fig. 5a; Supplemental Fig. S4a). The transgenic plants demonstrated a significantly higher survival rate compared to the WT plants. Following 9 d of water deficit treatment, less than 40% of the WT plants survived, whereas the OE 012465 lines 8-7 and 9-1 exhibited survival rates of 100% and 95%, respectively, and the OE 000283 lines 11-10 and 12-6 had survival rates of 87% each. (Fig. 5b; Supplemental Fig. S4b). Water loss serves as a critical metric for assessing plant drought tolerance, hence the fresh-to-dry weight ratio of excised leaves was assessed via desiccation analysis. Following 4 d of drought treatment, the fresh-to-dry weight ratio for WT plants was reduced to 43%, whereas for OE lnc000283 lines 11-10 and 12-6, it was reduced to 73% and 75%, respectively. For OE 012465 lines 8-7 and 9-1, the ratios were reduced to 67% and 62%, respectively (Fig. 5c; Supplemental Fig. S4c). The findings indicated that lnc000283 and lnc012465 endow the transgenic plants with drought tolerance.

Figure 5. Overexpressing lnc012465 lines are more tolerant to drought stress. (a) Phenotype of WT and OE lnc012465 plants before and after subjecting to drought stress. Drought treatment was carried out on 20-day-old Arabidopsis plants. (b) The percentage of leaves with different colors in Arabidopsis after heat treatment and recovery for 5 d. (c) The fresh weight to dry weight ratio of Arabidopsis leaves before and after undergoing 38 °C heat treatment. (d)−(f) MDA content, POD activity, and proline content in Arabidopsis leaves under different times of heat stress. The asterisks above the bars indicate statistical significance using Student's t-test (*, p < 0.05; **, p < 0.01; ***, p < 0.001)

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MDA content in leaves is a standard biomarker for assessing the extent of drought stress-induced damage. Prior to drought stress exposure, MDA levels in WT and transgenic plants were comparable. However, following 7 and 9 d of water deficit, the MDA content in the transgenic plants was markedly reduced compared to the WT, suggesting a less severe degree of membrane lipid peroxidation in the transgenic plants (Fig. 5d; Supplemental Fig. S4d). Oxidative stress frequently coincides with drought stress, hence the activity of POD was assessed to evaluate the ROS scavenging ability. The findings indicated that as the duration of drought treatment increased, POD activity progressively rose. Before drought exposure, the POD activity in lines 11-10 and 12-6 of OE 000283 was 2.4-fold and 2.2-fold higher than that of the WT, respectively (refer to Supplemental Fig. S4e). Following drought treatment, the POD activity in the transgenic lines remained significantly elevated compared to the wild type, although the enhancement was less pronounced than before the treatment (Supplemental Fig. S4e). In the OE 012465 plants, the POD activity in lines 8-7 and 9-1 significantly surpassed that of the wild type, with the discrepancy being more pronounced during drought stress (Fig. 5e). The proline content in WT and OE 000283 plants exhibited no significant differences before and after 7 d of treatment. However, after 9 d of drought, the proline content in OE 000283 plants was significantly lower compared to that in the WT (Supplemental Fig. S4f). OE 000465 plants showed no significant difference from the wild type before and after drought treatment (Fig. 5f). The findings were consistent with those under heat stress, indicating that the enhanced stress resistance due to the overexpression of lnc000283 and lnc012465 in Arabidopsis is not reliant on proline accumulation.

Following drought stress treatment, the expression levels of drought-related genes such as RD29A, RD29B, NCED3, AREB1, and Rab18 were significantly elevated in plants overexpressing lnc000283 and lnc012465 compared to WT plants. These findings suggest that lnc000283 and lnc012465 modulate Arabidopsis drought tolerance by regulating the expression of genes associated with the drought stress response (Fig. 6; Supplemental Fig. S5).

Figure 6. The expression of drought-responsive genes in lnc012465 overexpressing lines before and after different drought treatment time. Gene expression levels were determined by qRT-PCR normalized against UBC10 (At5g53300). Each value is mean ± sd (n = 3). The asterisks above the bars indicate statistical significance using Student's t-test (*, p < 0.05; **, p < 0.01; ***, p < 0.001).

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Discussion

The integrity of global food security is under threat due to the confluence of rapid population expansion and profound climatic shifts^[29]. Amidst the shifting climatic landscape, heat and drought stress have emerged as primary limitations to crop yield and global food security. Understanding how plants detect stress cues and acclimate to challenging conditions is a pivotal biological inquiry. Moreover, enhancing plant resilience to stress is essential for maintaining agricultural productivity and fostering environmental sustainability^[2]. Concurrently, the advancement of next-generation sequencing (NGS) technology has led to the identification of a substantial number of lncRNAs that participate in diverse stress responses, with functional analyses having been conducted on several of these molecules.^[30] For instance, in the case of potatoes, the lncRNA StFLORE has been identified to modulate water loss through its interaction with the homologous gene StCDF1^[31]. LncRNA TCONS_00021861 can activate the IAA biosynthetic pathway, thereby endowing rice with resistance to drought stress^[32]. In wheat, the expression of TalnRNA27 and TalnRNA5 was upregulated in response to heat stress^[33]. Our prior investigation identified a total of 81 lncRNAs in Chinese cabbage that engage in intricate interactions with their respective mRNA targets across various phases of heat treatment^[25]. Two lncRNAs, lnc000283 and lnc012465, were chosen for subsequent functional analysis. Findings confirmed that these lncRNAs endow transgenic Arabidopsis plants with enhanced tolerance to both heat and drought, thereby offering novel resources for enhancing stress resistance through genetic engineering.

Abiotic stresses frequently trigger the synthesis of anthocyanins, serving as natural antioxidants that mitigate oxidative damage by neutralizing surplus reactive oxygen species (ROS), thereby protecting plants from growth inhibition and cell death, allowing plants to adapt to abiotic stresses^[34,35]. For instance, during chilling stress, the accumulation of anthocyanins within leaves can mitigate oxidative damage, thereby enhancing the photosynthetic rate^[36]. Consequently, the level of abiotic stress tolerance can be inferred from the concentration of anthocyanins. The reduction of photosynthetic ability is one of the key physiological phenomena of stresses, which is partly due to the degradation of chlorophyll caused by leaf senescence during stress. The reduced accumulation of chlorophyll in the plants was seen in many plants when exposed to drought or heat stress conditions. The current investigation revealed that lncRNA-overexpressing plants cultivated in Petri dishes exhibited increased accumulation of both chlorophyll and anthocyanins in advanced growth phases, indicating that these transgenic plants, overexpressing lnc000283 and lnc012465, demonstrated enhanced stress tolerance and superior growth performance relative to WT (Fig. 2c, d).

Upon exposure to heat stress, there is a marked induction of transcription for numerous genes that encode molecular chaperones in plants, with the vast majority of these genes contributing to the prevention of protein denaturation-related damage and the augmentation of thermotolerance^[37−39]. The present investigation identified multiple heat-inducible genes in plants overexpressing lnc000283 and lnc012465, as well as in WT (Fig. 4; Supplemental Fig. S3). The findings indicated that of the four HSP or HSF genes examined, Hsp18.1-CI exhibited a significantly greater abundance in both OE lnc000283 and OE lnc012465 plants compared to the WT following heat treatment for several days. Hsp18.1-CI, formerly referred to as Hsp18.2 has been the subject of investigation since 1989.^[40] Following the fusion of the 5' region of Hsp18.2 in frame with the uidA gene of Escherichia coli, the activity of GUS, serving as the driver gene was observed to increase upon exposure to HS^[40]. The Arabidopsis hsfA2 mutant exhibited diminished thermotolerance after heat acclimation, with the transcript levels of Hsp18.1-CI being substantially reduced compared to those in wild-type plants following a 4-h recovery period^[41]. The findings revealed that the upregulation of Hsp18.1-CI protein is a critical mechanism by which plants achieve enhanced protection against heat stress in adverse environmental conditions, thereby bolstering their thermotolerance.

Plants cultivated in natural settings are often subjected to concurrent multiple abiotic stresses, which can exacerbate threats to their routine physiological functions, growth, and developmental processes^[42,43]. Elucidating the molecular mechanisms underlying plant responses to abiotic stress is crucial for the development of new crop varieties with enhanced tolerance to multiple abiotic stresses. Previous research has indicated that the overexpression of certain protein-coding genes can endow plants with resistance to a variety of abiotic stresses. For instance, tomatoes with robust expression of ShCML44 demonstrated significantly enhanced tolerance to drought, cold, and salinity stresses^[44]. Overexpression of PeCBF4a in poplar plants confers enhanced tolerance to a range of abiotic stresses^[45]. With respect to lncRNAs, transgenic Arabidopsis plants that overexpress lncRNA-DRIR displayed marked increased tolerance to salt and drought stresses compared to the wild-type^[46]. In the present study, both overexpression lines of lnc000283 and lnc012465 exhibited resistance to heat and drought stresses, thereby contributing to the enhancement of plant resilience against multiple stresses (Figs 3, 5; Supplemental Figs S2, S4).

The number of genes implicated in plant drought resistance is regulated by both ABA-dependent and ABA-independent pathways^[47,48]. It is well established that the expression of RD29A exhibits a high level of responsiveness to drought stress, operating through both ABA-dependent and ABA-independent mechanisms^[49]. RD29B, AREB1, and RAB18 are governed by an ABA-dependent regulatory pathway^[10,49,50]. NCED3 is involved in ABA biosynthesis^[51]. In the present study, the transcript levels of RD29A, RD29B, NCED3, AREB1, and RAB18 were significantly elevated in OE lnc000283 and OE lnc012465 plants compared to those in the WT plants (Fig. 6; Supplemental Fig. S5). The findings indicated that the drought tolerance imparted by OE lnc000283 and OE lnc012465 plants is contingent upon an ABA-dependent mechanism.

Prior research has indicated that certain long non-coding RNAs (lncRNAs) can assume analogous roles across diverse biological contexts. For example, the lncRNA bra-miR156HG has been shown to modulate leaf morphology and flowering time in both B. campestris and Arabidopsis^[52]. Heterogeneous expression of MSL-lncRNAs in Arabidopsis has been associated with the promotion of maleness, and similarly, it is implicated in the sexual lability observed in female poplars^[53]. In the present study, lnc000283 and lnc012465 were induced by heat in Chinese cabbage, and their heterologous expression was found to confer heat tolerance in Arabidopsis. Additionally, sequences homologous to lnc000283 and lnc012465 were identified in Arabidopsis (Supplemental Fig. S1). The data suggest that these sequences may share a comparable function to that of heat-inducible sequences, potentially accounting for the conservation of lnc000283 and lnc012465'os functionality across various species.

Conclusions

In conclusion, the functions of two heat-inducible lncRNAs, lnc000283 and lnc012465 have been elucidated. Transgenic Arabidopsis lines overexpressing these lncRNAs accumulated higher levels of anthocyanins and chlorophyll at a later stage of growth compared to the WT when grown on Petri dishes. Furthermore, under heat and drought stress conditions, these OE plants exhibited enhanced stress tolerance, with several genes related to the stress resistance pathway being significantly upregulated. Collectively, these findings offer novel insights for the development of new varieties with tolerance to multiple stresses.

Author contributions

The authors confirm contribution to the paper as follows: study conception and supervision: Li N, Song X; experiment performing: Wang Y, Sun S; manuscript preparation and revision: Wang Y, Feng X, Li N. All authors reviewed the results and approved the final version of the manuscript.

Data availability

All data generated or analyzed during this study are included in this published article and its supplementary information files.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (32172583), the Natural Science Foundation of Hebei (C2021209019), the Natural Science Foundation for Distinguished Young Scholars of Hebei (C2022209010), and the Basic Research Program of Tangshan (22130231H).

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary information

Supplementary Table S1 The relative synonymous codon usage of amino acids in the mitogenome of Michelia figo, Magnolia biondii, Magnolia officinalis, and Liriodendron tulipifera.
Supplementary Table S2 The frequency of codon usage in the mitogenome of Michelia figo, Magnolia biondii, Magnolia officinalis, and Liriodendron tulipifera.
Supplementary Table S3 Dispersed repeat sequences identified in the Michelia figo mitogenome.
Supplementary Table S4 Tandem repeat sequences identified in the Michelia figo mitogenome.
Supplementary Table S5 The simple sequence repeats identified in the Michelia figo mitogenome.
Supplementary Table S6 Dispersed repeat sequences identified in the Magnolia biondii mitogenome.
Supplementary Table S7 Dispersed repeat sequences identified in the Magnolia officinalis mitogenome.
Supplementary Table S8 Tandem repeat sequences identified in the Magnolia biondii mitogenome.
Supplementary Table S9 Tandem repeat sequences identified in the Magnolia officinalis mitogenome.
Supplementary Table S10 The simple sequence repeats identified in the Magnolia biondii mitogenome.
Supplementary Table S11 The simple sequence repeats identified in the Liriodendron tulipifera mitogenome.
Supplementary Table S12 The homologous DNA fragment between mitogenome and cpgenome of Michelia figo.
Supplementary Table S13 The collinear blocks between mitogenomes of Michelia figo and Magnolia officinalis.
Supplementary Table S14 The collinear blocks between mitogenomes of Michelia figo and Magnolia biondii.
Supplementary Table S15 The collinear blocks between mitogenomes of Magnolia biondii and Liriodendron tulipifera.
Supplementary Table S16 Genes used for phylogenetic analysis.
Supplementary Table S17 The genomic information of the species used in this study.
Supplementary Fig. S1 The map of genes containing introns. This diagram illustrates the distribution of cis- and trans-introns.
Supplementary Fig. S2 Heat maps of PCG and intron contents among 15 mitogenomes (a) Comparison of PCG contents among 15 mitogenomes. The gene numbers are shown on the top right. (b) Comparison of intron contents among 15 mitogenomes. The intron numbers are shown on the top right.

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Wang S, Qiu J, Sun N, Han F, Wang Z, et al. 2025. Characterization and comparative analysis of the first mitochondrial genome of Michelia (Magnoliaceae). Genomics Communications 2: e001 doi: 10.48130/gcomm-0025-0001

Wang S, Qiu J, Sun N, Han F, Wang Z, et al. 2025. Characterization and comparative analysis of the first mitochondrial genome of Michelia (Magnoliaceae). Genomics Communications 2: e001 doi: 10.48130/gcomm-0025-0001

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Introduction

Mitochondria, as semi-autonomous organelles with their unique genetic material and systems, play crucial roles in plant energy metabolism by generating ATP through oxidative phosphorylation^[1,2]. In plants, mitochondria not only participate in energy production, but also collaborate with other organelles to maintain cellular homeostasis^[3]. In addition, mitochondria also participate in regulating processes such as apoptosis, playing an important regulatory role in plant life activities^[4]. However, despite the undisputed significance of mitochondria, previous research on plant mitochondrial genomes (mitogenomes) has been scant. Initially, sequencing and assembly techniques which were primarily developed for nuclear genomes, encountered significant challenges in handling mitogenomes due to their complicated structures, leading to fragmented or incomplete mitogenome assemblies. Moreover, early bioinformatic tools were not optimized for the unique characteristics of mitogenomes. This limitation further hindered the accurate assembly and analysis of plant mitogenomes. Nevertheless, with the continuous advancement of sequencing technology, especially the widespread application of long-read sequencing, research on plant mitogenomes has gradually increased in recent years^[5−8].

The mitogenomes of most higher plants exhibit substantial variability in structure and size^[9]. Plant mitogenomes contain numerous repetitive sequences (repeats), leading to significant variations in size and structure through frequent recombination events^[10]. The size of plant mitogenomes is 100–1,000 times larger than that of animals (15-18 kb)^[11]. Plant mitogenomes stand out not just for their exceptional size, but also for the notable variation in size they display across diverse species. For example, Viscum scurruloideum^[12] has a mitogenome of only 66 kb, while the mitogenome of Larix sibirica is 11.7 Mb^[13]. Additionally, the intricate structure of plant mitogenomes further adds to their complexity, with most of them existing as a single circular molecule, while a minority exist as linear or branched molecules. It has been reported that the mitogenomes of Populus simonii^[14] and Fagopyrum esculentum^[15] are composed of three and ten circular molecules, respectively. Although plant mitogenomes differ significantly in terms of size and structure, the number of genes remains comparably stable and conserved, with a similar core set of PCGs, rRNAs, and tRNAs which are essential for respiratory function, and translation processes^[16]. Intracellular gene transfer (IGT) can further complicate the mitogenome, as sequences from both the plastid and nuclear genomes coexist in plant mitogenomes^[17]. For instance, the sequences of the nuclear and plastid genomes account for 46.5% and 1.4% of the Cucumis melo mitogenome, respectively^[18]. Therefore, the plant mitogenome, due to its complex characteristics, is an ideal system for exploring genome complexity.

Michelia figo (M. figo) belongs to the genus Michelia of the Magnoliaceae family, which is the second-largest genus and a relatively evolved group in the Magnoliaceae family. There are about 80 Michelia species in the world, predominantly distributed in tropical, subtropical, and temperate regions of Asia, of which approximately 70 species are distributed in China^[19,20]. The broad spectrum of physiological activities exhibited by the genus Michelia underscores its potential applications in medicine, food, agriculture, and other domains^[21]. The flowers, leaves, branches, and other parts of these species contain abundant aromatic oil that has been traditionally used in China, India, and other regions for treating fever, leprosy, inflammation, and other ailments^[22]. Michelia species usually serve as valuable sources of bioactive compounds, exhibiting antibacterial^[23], and antioxidant properties^[24]. Furthermore, the methanolic extract from the leaves of M. figo has a concentration-dependent vasodilatory effect, having widespread applications in medicine^[25].

A previous study has reported the complete plastome of M. figo and analyzed its phylogenetic relationship with other Michelia species based on (plastid genomes) plastomes^[26]. However, the mitogenome of M. figo and its phylogenetic status based on mitogenomes remain unexplored. Additionally, many plastomes of Michelia have been released^[27−29], but no mitogenomes have been reported for this genus. Consequently, to further explore the evolution and genetics of M. figo, this study has successfully assembled the complete mitogenome of M. figo. Comparative genomic and phylogenetic analyses were undertaken to elucidate the characteristics of the mitogenomes of M. figo and other Magnoliaceae species. These analyses will offer crucial theoretical and data-driven supports for genomic research, biological functions, and mitogenome evolution in M. figo and other Michelia species.

Materials and methods

DNA extraction and sequencing

In this study, we collected fresh leaves of M. figo at Nanjing Forestry University, Nanjing, Jiangsu Province, China (118.81° E, 32.07° S). Before DNA extraction, fresh leaves were immediately frozen in liquid nitrogen to preserve their integrity and subsequently stored in a laboratory freezer maintained at −80 °C. The total genomic DNA was extracted using the CTAB method^[30]. The quality of the DNA sample was evaluated using 1% agarose gel electrophoresis, while its concentration was accurately determined using a NanoDrop ND 2000 (ThermoFisher Scientific, Waltham, MA, USA)^[31]. The size of the genomic insert fragments is 15−18 kb. Then the sequencing libraries were constructed using the high-integrity genomic DNA through SMRTbell Express Template Prep Kit 2.0 (PacBio Biosciences, Menlo Park, CA, USA). We ultimately obtained the HiFi sequencing data from the PacBio Revio platform.

Mitogenome assembly and annotation
The HiFi sequencing data was fed into PMAT v1.31^[32] to assemble the mitogenome of M. figo. The parameters were 'autoMito -st hifi -g 2.2G -CPU 50'. The nuclear genome size of M. figo was estimated using the genome of Magnolia biondii as a reference^[33]. After using PMAT, the raw assembly graph of M. figo mitogenome was composed of 12 contigs, containing four pairs of repeats. Using Bandage^[34], we obtained the circular mitogenome of M. figo by decoding the raw assembly graph, taking into account the copy number of each contig. The mitogenome of M. figo was annotated using the online program PMGA^[35]. The rRNA and tRNA genes were then verified by BLASTN^[36] and tRNAscan-SE v2.0^[37], respectively. Finally, an online tool PMGmap^[38] was used to draw the mitogenome map.

Analysis of repeats and codon usage
The online tool MISA^[39] was used to detect simple sequence repeats (SSRs) of the M. figo, M. biondii, and M. officinalis mitogenomes. We set the repetition thresholds at 10, 5, 4, 3, 3, and 3 for mononucleotides, dinucleotides, trinucleotides, tetranucleotides, pentanucleotides, and hexanucleotides, respectively. The minimal distance between two SSRs was established as 100 bp. Meanwhile, the online tool TRF^[40] was utilized to detect tandem repeats with default parameters. REPuter^[41] was used to detect dispersed repeats and the parameters were set as follows: hamming distance of three, maximum computed repeats of 5000, and a minimal repeat size of 30 bp^[42]. Codon composition and usage of the M. figo mitogenome were analyzed using CondonW v1.4.4 (https://codonw.sourceforge.net/) with default parameters.

Mitochondrial plastid transfer (MTPT) and collinearity analysis
We obtained the plastid genome (plastome) of M. figo from the NCBI with the accession number of NC_053861.1. Then, we used BLASTN^[36] to identify the homologous fragments between the mitogenome and plastome, and utilized TBtools to visualize the results^[43]. We selected three mitogenomes of Magnoliaceae (L. tulipifera, M. biondii, and M. officinalis) for the collinearity analysis with M. figo. The collinear blocks were identified using MUMmer v4.0^[44] with default parameters. We chose collinear blocks that exceeded 5,000 bp for subsequent analysis. NGenomeSyn v1.0^[45] was finally used to visualize the results.

Phylogenetic analysis
To further clarify the phylogenetic location of M. figo, two phylogenetic trees were constructed using 15 plant mitogenomes and plastomes respectively, including two species of Gymnosperm (Cycas taitungensis, and Ginkgo biloba), three species of ANA clade (Amborella trichopoda, Nymphaea colorata, and Schisandra sphenanthera), four species of Magnoliidae (L. tulipifera, M. figo, M. officinalis, and M. biondii), three species of monocots (Apostasia shenzhenica, Cocos nucifera, and Sorghum bicolor), and three species of core eudicots (Ilex pubescens, Sapindis mukorossi, and Ficus carica). Among these plant species, C. taitungensis and G. biloba were selected as outgroups. We used in-house Python scripts to select shared genes and used MAFFT v7.407^[46] to compare the shared genes. After trimming the results using trimAl v1.4^[47], IQ-TREE v2.0.3^[48] was utilized to construct the phylogenetic trees based on the maximum likelihood (ML) method with 1,000 bootstraps.^[49]. Both plastid and mitochondrial trees were found to be best fit by the GTR + F + I + G4 model. Finally, the online tool iTOL^[50] was used to visualize and optimize the results.

Discussion

Plant mitogenomes frequently undergo recombination events mediated by repeats, resulting in great differences in their size^[51]. Despite the closely related species, notable variations in mitogenome size can still be observed. For example, the size of the Silene latifolia mitogenome (253 kb) differs by 45 times compared to that of S. conica (11.3 Mb)^[52]. The mitogenomes of Cucumis melo (2.9 Mb) and Citrullus lanatus (379 kb) differ by more than seven times^[53]. The frequent recombination events of plant mitogenomes may integrate a large amount of foreign DNA during evolution, potentially contributing to the great differences in plant mitogenomes size. In this study, the mitogenome length of M. figo (773,377 bp) is relatively short in Magnoliaceae, with the longest in M. biondii (967,100 bp), followed by M. officinalis (930,306 bp) and M. liliiflora (865,191 bp). The shortest mitogenome is L. tulipifera (551,806 bp), accounting for only 60% of the mitogenomes of M. biondii and M. officinalis.

Frequent recombination events not only lead to great differences in mitogenome size, but also contribute to complex and diverse structures of plant mitogenomes^[54], ranging from single circular and linear structures to more complex branched linear, branched circular, and other complex structures^[55]. It has been reported that the mitogenomes of Amborella trichopoda^[56], Rhopalocnemis phalloi^[57], and Panax notoginseng^[58] are complex dynamic structures resulting from recombination. The mitogenome structures of Magnoliaceae are relatively conserved, with the majority being assembled into a single circular chromosome (M. biondii, M. officinalis, M. figo, and L. tulipifera). However, the mitogenome of M. liliiflora exhibits a linear chromosome. Additionally, the mitogenomes of angiosperms exhibit rapid structural differentiation and loss of collinearity, even those of closely related species^[59,60]. In this study, using the nucmer program of MUMmer, numerous colinear regions and genomic rearrangements were identified among four Magnoliaceae mitogenomes. The lengths of these colinear blocks account for more than half of each mitogenome. The results of collinearity analysis reveal there may have been significant genomic rearrangements in the mitogenomes of Magnoliaceae species during their evolutionary history.

The mitogenomes of angiosperms generally encode a core set of 24 PCGs: nad1-7, 9, and 4L; cob; cox1-3; ccmB, C, Fc, and Fn; atp1, 4, 6, 8, and 9; mttB/tatC; and matR. Although these core genes are present in most mitogenomes, there are significant variations in their quantity, position, and arrangement, even within mutants of the same species. In addition to the 24 conserved PCGs, plant mitogenomes also possess 19 standard variable genes, consisting of five large subunits of ribosome proteins (rpl2, 5, 6, 10, and 16), 12 small subunits of ribosome proteins (rps1-4, 7, 8, 10-14, and 19), and two respiratory genes (sdh3-4). Among these variable genes, the large and small subunits of ribosome genes are missing relatively frequently^[61]. The mitogenome of M. figo harbors all 24 core PCGs, with only two variable PCGs (rpl6 and rps18) being lost. Similarly, the mitogenomes of M. biondii^[33] and L. tulipifera^[62] have retained nearly all ancestral PCGs. However, the Silene vulgaris mitogenome has nearly lost all variable PCGs with the exception of rps13. Moreover, the Viscum scurruloideum mitogenome has lost the entirety of 11 of the 24 core PCGs, including ccmB, matR, and all NADH dehydrogenase genes^[12]. The gene content in the mitogenomes of Magnoliaceae is relatively abundant^[63], suggesting that they may have undergone less gene loss during the mitogenome evolution.

Plant mitogenomes vary significantly in the number of introns. The Silene latifolia mitogenome has only 19 introns^[64], while the Selaginella moellendorffii mitogenome contains the largest number of 37 introns^[65]. The M. figo mitogenome contains 25 introns in 10 PCGs (ccmFc, rpl2, rps3, rps10, cox2, nad1, nad2, nad4, nad5, and nad7), consisting of 22 cis-splicing and three trans-splicing introns. Cis-splicing is prevalent in most introns of angiosperm mitogenomes, whereas nad1, nad2, and nad5 evolved a split structure that requires trans-splicing^[63]. Similar to the majority of angiosperm mitogenomes, the intron rps3i257 in the M. figo mitogenome is completely lost during differentiation^[66]. These results indicate that introns are frequently gained or lost during the evolution of plant mitogenomes (Supplementary Fig. S2)^[63].

Plant mitogenomes are characterized by the abundance of repeats, contributing to the complexity and diversity of mitogenome sizes and structures through frequent recombination events^[10]. The intense recombination events mediated by long repeats (> 500 bp) facilitate reversible recombination, regulate the molecular conformation of the mitogenome, and ultimately contribute to the expansion and complexity of plant mitogenomes^[54]. In this study, the M. figo mitogenome exhibits the lowest abundance of SSRs and long repeats (> 500 bp), whereas M. biondii mitogenome displays the highest abundance in Magnoliaceae. It can be inferred that it is likely to undergo less recombination events during the evolution of M. figo mitogenome, while the M. biondii mitogenome may experience more recombination events. Simultaneously, variations in the quantity of repeats may result in significant differences in the size of mitogenomes. For example, the mitogenome sizes of bryophytes remain relatively stable at approximately 110 kb, probably due to the scarcity of repeats within their mitogenomes. This scarcity contributes to the conserved and stable structure of the bryophyte mitogenomes. By contrast, the mitogenomes of ferns exhibit a significant number of repeats, accounting for their relatively large sizes^[10]. In this study, the mitogenomes of M. biondii and M. officinalis exhibit a significantly higher numbers of repeats compared to M. figo, potentially explaining the differences in their mitogenome sizes.

DNA fragment transfer events between the plastomes and mitogenome, as well as among different species, are recurrent phenomena that occur during the evolution of the plant mitogenome^[67]. The lengths and similarities of these cp-derived fragments vary among different species^[68]. The total length of MTPTs in the M. figo mitogenome is 42,791 bp, constituting 5.53% of the whole mitogenome. This proportion is significantly higher than that observed in numerous other mitogenomes, such as Arabidopsis thaliana (0.8%) , Glycine max (0.6%), Silene conica (0.2%), and Vigna angularis (0.1%)^[69]. At the other extreme, the length of MTPTs accounts for 10.5% of the Boea hygrometrica mitogenome^[70]. The MTPTs in the M. figo mitogenome are notably abundant, with the longest fragment spanning 4,666 bp, and the majority of MTPTs ranging from 50 to 500 bp. These sizable MTPTs are presumed to have significant impacts on plant mitogenome evolution, thereby contributing to genetic diversity^[17,71]. Additionally, it is frequently observed that these transferred fragments contain PCGs. The number of PCGs in MTPTs exhibits significant variation in plant mitogenomes, ranging from seven in Brassica to 22 in Nicotiana^[72]. In the mitogenome of M. figo, nine PCGs (psbL, psbF, psbE, petL, petG, rps8, rpl14, rps7, and ndhB) are located in MTPTs. However, PCGs in MTPTs turned out to degenerate as a result of sequence alterations and the absence of RNA editing^[73,74]. Consequently, PCGs in MTPTs may have limited functional significance in mitogenomes, potentially acting as non-essential sequences^[72].

In this study, we reconstructed two phylogenetic trees based on 18 mitochondrial and 61 plastid PCGs from 15 species, respectively. Both trees exhibit remarkable consistency, supporting that Michelia is closely related to Magnolia, which is consistent with previous studies^[26,75]. Additionally, the topological structure of the two phylogenetic trees is also highly consistent with the Angiosperm Phylogeny Group IV (APG IV) system^[76]. However, due to the scarcity of mitogenomes in Michelia, we are unable to expand our discussion on the phylogenetic relationships in this genus.

Group of genes	Name	Start codon	Stop codon	Length	Amino acids
ATP synthase	atp1	ATG	TGA	1,530	509
	atp4	ATG	TAA	582	193
	atp6	ATG	TAG	891	296
	atp8	ATG	TAA	480	159
	atp9	ATG	TAA	261	86
Cytochrome c biogenesis	ccmB	ATG	TGA	621	206
Cytochrome c biogenesis	ccmC	ATG	TAA	960	319
	ccmFc*	ATG	TAA	1,359	452
	ccmFn	ATG	TAG	1,806	602
Ubichinol cytochrome c reductase	cob	ATG	TGA	1,182	393
Cytochrome c oxidase	cox1	ACG	TAA	1,584	527
Cytochrome c oxidase	cox2**	ATG	TAA	759	252
	cox3	ATG	TGA	798	265
Maturases	matR	ATG	TAG	1,959	652
Transport membrane protein	mttB	ACG	TGA	768	255
NADH dehydrogenase	nad1***+	ACG	TAA	978	325
NADH dehydrogenase	nad2****	ATG	TAA	1,467	488
	nad3	ATG	TAA	357	118
	nad4***	ATG	TGA	1,488	495
	nad4L	ACG	TAA	303	100
	nad5**++	ATG	TAA	2,013	670
	nad6	ATG	TGA	735	244
	nad7****	ATG	TAG	1,185	394
	nad9	ATG	TAA	573	190
Large subunit of ribosome (LSU)	rpl10	ATG	TAA	471	156
Large subunit of ribosome (LSU)	rpl16	GTG	TAA	435	144
	rpl2*	ATG	TAG	1,665	697
	rpl5	ATG	TAA	561	186
Small subunit of ribosome (SSU)	rps1	ATG	TAA	606	201
Small subunit of ribosome (SSU)	rps10*	ATG	TGA	420	139
	rps11	ATG	TGA	552	183
	rps12	ATG	TGA	378	125
	rps13	ATG	TGA	351	116
	rps14	ATG	TAG	303	100
	rps19	ATG	TAA	282	93
	rps2	ATG	TAA	657	218
	rps3*	ATG	TAA	1,572	523
	rps4	ACG	TAA	1,071	356
	rps7 (2)	ATG/ATG	TAA/TAA	450	149
Succinate dehydrogenase	sdh3	ATG	TAA	330	109
Succinate dehydrogenase	sdh4	ATG	TGA	447	148
Ribosomal RNAs	rrn5	−	−	117	−
	rrnL	−	−	3,560	−
	rrnS	−	−	2,087	−
Transfer RNAs	trnC-GCA	−	−	71	−
	trnD-GUC	−	−	74	−
	trnE-UUC	−	−	72	−
	trnF-GAA	−	−	74	−
	trnfM-CAU	−	−	74	−
	trnG-GCC	−	−	73	−
	trnH-GUG	−	−	74	−
	trnI-CAU	−	−	81	−
	trnK-UUU	−	−	73	−
	trnM-CAU (2)	−	−	73/73	−
	trnN-GUU	−	−	72	−
	trnP-UGG (3)	−	−	75/74/75	−
	trnQ-UUG	−	−	72	−
	trnS-GCU	−	−	88	−
	trnS-UGA	−	−	87	−
	trnV-UAC	−	−	73	−
	trnW-CCA	−	−	74	−
	trnY-GUA	−	−	83	−
* Indicates the cis-spliced introns, and + indicates the trans-spliced introns. The number of * and + represents the number of introns. The number in parentheses represents the number of genes.

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Characterization and comparative analysis of the first mitochondrial genome of Michelia (Magnoliaceae)

Abstract

Introduction

Materials and methods

Plant materials, growth conditions, and stress treatment

Vector construction

Chlorophyll and anthocyanin content determination

Physiological analysis

RNA isolation and qRT-PCR analysis

Results

Screening and characterization of lncRNAs

Generation of lncRNA overexpression lines

Effect of lncRNA overexpression on heat tolerance in Arabidopsis

Effect of lncRNA overexpression on the expression quantity of genes related to high-temperature response in Arabidopsis

Effect of lncRNA overexpression on drought tolerance in Arabidopsis

Discussion

Conclusions

Author contributions

Data availability

Acknowledgments

Conflict of interest

Supplementary information

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Characterization and comparative analysis of the first mitochondrial genome of Michelia (Magnoliaceae)

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DNA extraction and sequencing

Mitogenome assembly and annotation

Analysis of repeats and codon usage

Mitochondrial plastid transfer (MTPT) and collinearity analysis

Phylogenetic analysis

Mitogenome features of M. figo

Analysis of codon usage

Analysis of repeats

Analysis of MTPTs

Collinearity analysis of four Magnoliaceae mitogenomes

Phylogenetic analysis

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DNA extraction and sequencing

Mitogenome assembly and annotation

Analysis of repeats and codon usage

Mitochondrial plastid transfer (MTPT) and collinearity analysis

Phylogenetic analysis

Mitogenome features of M. figo

Analysis of codon usage

Analysis of repeats

Analysis of MTPTs

Collinearity analysis of four Magnoliaceae mitogenomes

Phylogenetic analysis

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