Abstract
With dwindling natural resources on earth, current and future generations will need to explore space to new planets that will require travel under no or varying gravity conditions. Hence, long-term space missions and anticipated impacts on human biology such as changes in immune function are of growing research interest. Here, we reported new findings on mechanisms of immune response to microgravity with a focus on macrophage as a cellular model. We employed a superconducting magnet to generate a simulated microgravity environment and evaluated the effects of simulated microgravity on RAW 264.7 mouse macrophage cell line in three time frames: 8, 24, and 48 h. As study endpoints, we measured cell viability, phagocytosis, and used next-generation sequencing to explore its changing mechanism. Macrophage cell viability and phagocytosis both showed a marked decrease under microgravity. The differentially expressed genes (DEG) were identified in two ways: (1) gravity-dependent DEG, compared μg samples and 1 g samples at each time point; (2) time-dependent DEG, compared time-point samples within the same gravitational field. Through transcriptome analysis and confirmed by molecular biological verification, our findings firstly suggest that microgravity might affect macrophage phagocytosis by targeting Arp2/3 complex involved cytoskeleton synthesis and causing macrophage immune dysfunction. Our findings contribute to an emerging body of scholarship on biological effects of space travel.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10867-021-09581-w.
Keywords: Microgravity, Macrophage, RNA-seq, Differentially expressed genes
Introduction
Long-term space flight will be a major mission for the International Space Administration. However, exposure to space flight and lack of gravity might have diverse biological and health consequences, including changes in immune function. It has been shown that exposure to space flight results in immune system dysfunction [1, 2] and could be a serious health risk to astronauts and crewmembers participating in lunar or Mars missions. Therefore, the objective to understand the mechanisms of immune response under simulated microgravity environment is a key research topic in integrative biology.
The macrophage is one of the most important immune cells, playing key roles in both innate and adaptive immune systems [3–5]. Its major function is phagocytosis, in which it engulfs a solid particle or pathogen to form an internal compartment known as a phagosome. Accumulative evidence suggests that macrophage can be regulated by biophysical cues. Mechanosensory on the membranes of macrophage converts external biophysical stimuli into intracellular structures such as the cytoskeleton and modulates macrophage functions [6–10]. For example, by mimicking the effect of arterial stiffness on macrophages in atherosclerosis, previous work showed that matrix stiffness could modulate macrophage behaviors through miRNAs signaling pathways [11]. Additionally, spaceflight-based experiments and ground-based flight models have reported that the number of macrophages in blood was decreased and its cytokine release as well as oxidative burst was suppressed under simulated microgravity environment, which might be one of the major reasons for immune dysfunction [12–16].
Recently, studies have reported that macrophage-related receptors and genes in the signaling pathways were altered under simulated microgravity environment. For example, LPS-dependent Jun-N-terminal kinase activation was impaired at simulated microgravity environment [17], suggesting that microgravity leads to incomplete transfer of downstream signaling pathway in the immune response. Another recent study used microarray technique to identify the gene expression pattern before and immediately following the spaceflight. They found that immune-related genes were differentially expressed [18]. Meanwhile, Intercellular Cell Adhesion Molecule-1 (ICAM-1), a molecular regulating macrophage migration, showed a reduction expression after 11 days flight [19]. One epigenetics study discovered that microgravity resulted in changes of DNA methylation and gene expression [20]. However, one real-time on-orbit experiment measured the oxidative burst reaction but showed a fast adaptation to gravity of macrophage [21]. Another research that examined the linkages between microgravity-induced skeletal muscle atrophy and immune function deregulation revealed the role of microRNA in the immune system under microgravity [22]. Besides, to shed light on the role of non-coding RNAs in response to microgravity and radiation, one research studied the expression profiles of miRNA, lncRNA, and mRNA in human lymphoblastoid cells, which revealed different expression patterns [23]. Taken together, macrophages are known to be affected under the simulated microgravity environment, but how the immune cells respond to the microgravity with time change has not been clear. More importantly, the ability of macrophage phagocytosis as well as the mechanism of immune response under simulated microgravity environment still remains to be established.
In the present study, we employed a superconducting magnet to generate a simulated microgravity, mouse macrophage cell line (RAW 264.7) under simulated microgravity (μg) and normal gravity (1 g), and evaluated the effects in three different time frames: 8, 24, and 48 h. As study endpoints, we measured cell viability and phagocytosis function and used next-generation sequencing (NGS) to obtain differentially expressed genes (DEG) at each time point. Through transcriptome analysis, our findings suggest that microgravity might affect phagocytosis function through Arp2/3 complex signal pathway mediated cytoskeleton synthesis in vitro as measured in a macrophage cell model.
Materials and methods
Cell culture and exposure to simulated microgravity
Mouse macrophage cell lines (RAW264.7) were obtained from ATCC (Manassas, VA, USA). The cells were maintained in 75 cm2 cell flasks at 37 °C with 5% CO2 and grown in RPMI 1640 medium (Gibco) supplemented with 10% FBS (Biological Industries) and 1% (w/v) penicillin–streptomycin (Sigma-Aldrich). Stock cultures were maintained at no more than 60% confluency.
The cells were exposed to simulated microgravity generated by magnetic levitation as previously described [24, 25]. The temperature was kept at 37 °C by heating circulating water baths, and the concentration of CO2 was 5% calibrated by a CO2 analyzer (Geotech, Leamington, UK). The cells were harvested at three time points (8 h, 24 h, and 48 h) and used for further analysis. Each condition had three replicates; therefore, a total number of 18 samples were collected.
Viability and phagocytosis experiments
Cell Counting Kit-8 (CCK8, Beyotime Biotechnology) was used to evaluate the cell viability. After exposure to the microgravity with various time, the original medium of different samples was replaced by 500 μL 10% FBS medium containing 50 μL CCK-8 and incubated at 37 °C for 2 h according to the manufacturer’s instructions. The optical density (OD) value was recorded at 450 nm by microplate spectrophotometer system (Biotek). The experiment was independently repeated 3 times.
The neutral red assay was used for testing phagocytosis. Briefly, the samples from different groups were incubated with neutral red dye (100 μg/mL) in FBS-free medium for 2 h. Then, the cells were washed with phosphate-buffered saline (PBS) 3 times and the absorbance was recorded at 540 nm using microplate spectrophotometer system. The experiment was independently repeated 3 times.
RNA-Seq and analysis
A total number of 18 samples were sequenced by the BGI platform (3 time points, each time point had 6 samples with 3 replicates for each condition). Raw reads were trimmed by Trimmomatic (version 0.32) [26]. RSEM (version 1.2.30) program was used to align cleaned reads to mouse reference genome (version GRCm38) and quantify gene expression level [27, 28]. DESeq2 package was used to identify differentially expressed genes [29]. Cluster analysis and principal component analysis were done in R software.
Gene ontology enrichment analysis and KEGG pathway
Online resources implemented in DAVID (https://david.ncifcrf.gov) were used to conduct the gene ontology enrichment analysis and KEGG pathway analysis [30].
Nucleic acid extraction and quantitative real-time PCR analysis
Total RNA was extracted using TRIzol reagent (Invitrogen) according to the manufacturer’s protocol. The extracted RNA was digested with RNase-free DNase (Qiagen) and the cDNA was synthesized using M-MLV reverse transcriptase (Promega). The real-time quantitative reverse transcription (qRT)-PCR was performed with CFX Connect™ system (Bio-Rad). The genes included four receptors related to macrophage phagocytosis (TLR2, FcγR1, CD11b, CD18) and four proteins related to Arp2/3 complex signal pathway (RAC1, WASP2, WAVE2, Arp2) were analyzed using primers listed in Supplementary table S1. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as the reference gene and relative gene expression were calculated using 2−ΔΔCT method. The qRT-PCR experiments were performed in triplicate.
Statistical analysis
Data were expressed as mean ± SD of at least three independent experiments (n ≥ 3). The P-value was calculated by t-test (version 19 SPSS Statistics, IBM). Significance level was indicated as P-value < 0.05 as *, P-value < 0.01 as **, P-value < 0.001 as ***, and P-value < 0.0001 as ****.
Results
Macrophage viability and phagocytosis declined under simulated microgravity environment
The viability and phagocytosis function of macrophages between simulated microgravity (μg) and normal gravity (1 g) were compared at three different time frames: 8, 24, and 48 h. Results are shown in Fig. 1. The viability and phagocytosis function of macrophage exhibited a significant decrease under simulated microgravity environment (Fig. 1A–F, P-value < 0.05), indicating simulated microgravity led to a reduction of macrophage cell number and immune dysfunction.
Fig. 1.
The macrophage viability and phagocytosis of macrophage under simulated microgravity (μg) and normal condition (1 g). A–C The viability of macrophage at 8 h (A), 24 h (B), and 48 h (C) treatment under microgravity and normal condition. D–F The phagocytosis of macrophage at 8 h (D), 24 h (E), and 48 h (F) treatment under microgravity and normal condition. Significance level was labeled as P-value < 0.05 as *, P-value < 0.01 as **, and P-value < 0.001 as ***
RNA-seq identified gravity-dependent differentially expressed genes (DEG) and time-dependent DEG
In order to explore the molecular mechanism, we used next-generation sequencing to obtain DEG. We sequenced a total number of 18 samples, 6 samples for each time point. After obtaining the clean reads, we mapped to reference genome. The average mapping rate was 88.75%. Then we identified DEG in two ways: (1) gravity-dependent DEG, compared μg samples and 1 g samples at each time point; (2) time-dependent DEG, compared time-point samples within the same gravitational field. The threshold was defined as FDR < = 0.01 and log2FC > = ± 2. The number of DEG that passed this threshold is shown in Table 1. Then we have plotted a Venn diagram that showed the common DEG between time-dependent and gravity-dependent (Supplementary figure S1). The cross area between them is the gravity-time-dependent genes (gene number is 483). The number for gravity-dependent only genes was 658, and for time-dependent only was 792.
Table 1.
The number of differentially expressed genes (DEG)
| Category | Comparison | Condition | Total DEG | Upregulated genes |
|---|---|---|---|---|
| Gravity-dependent DEG | 1 g vs μg | 8 h | 308 | 307 |
| 24 h | 49 | 49 | ||
| 48 h | 897 | 397 | ||
| Time-dependent DEG | 1 g | 8 h vs 24 h | 139 | 66 |
| 8 h vs 48 h | 748 | 357 | ||
| 24 h vs 48 h | 565 | 222 | ||
| μg | 8 h vs 24 h | 270 | 152 | |
| 8 h vs 48 h | 616 | 428 | ||
| 24 h vs 48 h | 243 | 187 |
In order to better reflect the effects of microgravity on immune cells, we next focused more on the gravity-dependent DEG at three time points (8 h, 24 h, and 48 h). We performed a hierarchical cluster analysis, wherein the data in the same cluster displayed high similarity. Then, we used heatmaps to visualize the cluster result. From the heatmap, the μg group and 1 g group were clearly divided into two clusters (Fig. 2A–C), indicating these DEG can be used as potential markers to differentiate control and simulated microgravity groups.
Fig. 2.
Heatmap of cluster analysis and principal component analysis (PCA) using differentially expressed genes (DEG). A–C Cluster analysis at 8 h (A), 24 h (B), and 48 h (C) between μg group and 1 g group. D–F PCA results at 8 h (D), 24 h (E), and 48 h (F) between μg group and 1 g group
We also carried out a principal component analysis (PCA), a statistical procedure to transform data from high dimension into low dimension. Through PCA, the distribution and variance of the data were shown. In PCA results, all μg group and 1 g group were separated adequately (Fig. 2D–F). The 1 g group was in one cluster while μg group in another cluster, indicating the accuracy of the DEG. In addition, PC1 explained 39% (8 h), 35% (24 h), and 44% (48 h) variance, while PC2 explained 23% (8 h), 24% (24 h), and 17% (48 h) variance.
Gene ontology (GO) enrichment analysis and KEGG pathway analysis associated DEG with biological processes and pathways
GO enrichment analysis and KEGG pathways analysis were performed on gravity-dependent DEG. The threshold was taken as P-value < 0.05. The GO analysis consists of three parts: biological process, cellular component, and molecular function. Terms that were significant in each part were plotted as a bar graph (Fig. 3A–C). The biological process was the most interesting and informative one. At 8 h simulated microgravity environment, the significant terms in biological process were nucleosome assembly, transcription DNA-templated, apoptotic process, DNA methylation on cytosine, regulation of gene expression, regulation of cell proliferation, and regulation of cell adhesion. At 48 h simulated microgravity environment, the significant terms in biological process were glycolytic process, protein folding, cholesterol biosynthetic process, lipid metabolic process, metabolic process, oxidation–reduction process, inflammatory response, regulation of MAPK cascade, immune system process, regulation of apoptotic process, and regulation of cell migration. At 8 h simulated microgravity, processes related to nucleus and transcription were significant, whereas processes related to metabolism such sugar and lipid were significant at 48 h simulated microgravity.
Fig. 3.
Bar graph of gene ontology (GO) enrichment analysis and the bubble map of KEGG pathway analysis using differentially expressed genes (DEG). A GO analysis at 8 h microgravity. B GO analysis at 24 h microgravity. C GO analysis at 48 h microgravity. D KEGG pathway analysis at 8 h microgravity. E KEGG pathway analysis at 24 h microgravity. F KEGG pathway analysis at 48 h microgravity
In KEGG pathway analysis, significant pathways at each time point were plotted in the bubble diagram (Fig. 3D–F). At 8 h simulated microgravity environment, significant pathways were MAPK signaling pathway, arginine biosynthesis, FoxO signaling pathway, complement and coagulation cascades, protein processing in endoplasmic reticulum, estrogen signaling pathway, p53 signaling pathway, TNF signaling pathway, ABC transporters, arginine and proline metabolism, and PI3K-Akt signaling pathway. At 48 h simulated microgravity environment, significant pathways were glycolysis, galactose metabolism, steroid biosynthesis, carbon metabolism, fructose and mannose metabolism, biosynthesis of amino acids, pyruvate metabolism, lysosome, p53 signaling pathway, cytokine-cytokine receptor interaction, NF-κB signaling pathway, phagosome, TNF signaling pathway, Ras signaling pathway, and FcγR-mediated phagocytosis. Significant pathways were compared among three time points. It was consistent with GO analysis result, which the mechanism and response were different.
We noticed that at 8 h simulated microgravity environment, the significant terms and the most interesting biological processes were regulation of cell proliferation and regulation of cell adhesion, which is associated closely to cytophagocytic process. These terms were also significant at 24 h and 48 h, which leads us to focus on these pathways. In KEGG pathway analysis, the TNF signaling pathway, NF-κB signaling pathway, phagosome, and FcγR-mediated phagocytosis appeared multiple times, which contributed to the initiation and transduction of cytophagocytic signals, further influenced the function of macrophage phagocytosis. These results were consistent with GO analysis. Therefore, we mainly chose cytophagocytic and Arp2/3 complex signal pathways in the downstream analysis.
Phagocytic function-related genes expression level tested by quantitative PCR (qPCR)
After observing the above results, in order to confirm the molecular mechanism that relates to phagocytic changes, real-time qPCR were used to verify the expression level of eight genes. These genes fell into two classes. One was receptors that related to initiation and transduction of the signals of phagocytosis, including TLR2, FcγR1, CD11b, and CD18. The other related to Arp2/3 complex signal pathway which is responsible for cytoskeleton synthesis including RAC1, WASP2, WAVE2, and ARP2. We collected samples at 8 h, 24 h, and 48 h after simulated microgravity treatment and the qPCR results showed that these genes expression decreased under simulated microgravity environment (Fig. 4A–C, P-value < 0.05). The decreased expression of these genes led to a reduction of cytoskeleton synthesis and further influenced the morphology of cells. Therefore, it resulted in a macrophage phagocytosis dysfunction.
Fig. 4.
Gene expression level tested by qPCR. A Expression level at 8 h microgravity. B Expression level at 24 h microgravity. C Expression level at 48 h microgravity. Significance level was labeled as P-value < 0.05 as *, P-value < 0.01 as **, and P-value < 0.001 as ***
Discussion
In the present study, using a mouse macrophage in vitro model contributed to an emerging body of scholarship on biological effects of space travel under simulated microgravity environment. We employed a superconducting magnet to generate the simulated microgravity environment. The immune system is known to be affected under the simulated microgravity environment, but how the immune cells respond to the simulated microgravity dynamically has not been clear.
We collected samples at 8, 24, and 48 h under simulated microgravity environment. Compared with normal gravity, the viability and phagocytosis of macrophages were significantly decreased under simulated microgravity environment (Fig. 1A–F, P-value < 0.05). This is not only for short-term microgravity treatment (8 h) but also for long-term microgravity (48 h), indicating simulated microgravity led to a significant reduction of macrophage activity and immune dysfunction (Supplementary figure S2). Through transcriptome analysis, the DEG and pathway analysis revealed the acute effects of simulated microgravity on macrophage. After carefully comparing DEG and pathways at 8 h, 24 h, and 48 h, we observed different immune response mechanisms. First, the number of DEG showed large variation, which DEG at 24 h had a minimum number of 49 (Table 1). However, when treated at 48 h microgravity, the number of DEG increased to 897, which may suggest a non-reversible immune dysfunction. The second difference of DEG was the expression trend. The DEG identified at 8 h and 24 h microgravity had more upregulated genes, but DEG at 48 h had more downregulated genes (Table 1). This might be related to cell stress response. At 8 h and 24 h simulated microgravity environment, cells started to respond to the abnormal gravity and genes related to stress signal pathways were all activated, leading to an increasing number of upregulated DEG such as transcription factors. However, at 48 h microgravity, it has been a longer abnormal gravity, and macrophage immune function had disrupted. As a result, more downregulated DEG were shown. These two differences revealed the acute effects of simulated microgravity on macrophages.
In order to better understand the differences, we took a closer look at the top 20 DEG at 8 h and 48 h simulated microgravity environment (Table 2 and Table 3). We discovered that at 8 h simulated microgravity, genes related to nucleus were the first ones responding to abnormal gravity, for example, small nuclear RNA (snRNA) and nuclear receptor subfamily 4 (NR4A3). The other group was genes related to signal transduction or receptors such as protein phosphatase regulatory (PPP1R15A) and FBJ osteosarcoma oncogene B (FOSB), indicating a rapid change of signaling pathways. However, these DEG were not shown up at 48 h condition, which suggested a different response mechanism. At 48 h simulated microgravity environment, not only immune-related genes, but also metabolism-related genes were altered. For example, S1PR1 and SORBS3 showed decreased expression under 48 h simulated microgravity while GPER1 and HSPA1B showed upregulation, suggesting cells adjusted signal transduction and metabolism pathways to adapt to microgravity (Table 3). In addition, this different response was also observed in the GO analysis and KEGG pathway analysis, which revealed that macrophage has a dynamic mechanism responding to microgravity.
Table 2.
Top 20 (largest log2FC) differentially expressed genes (DEG) at 8 h simulated microgravity environment
| Name | log2FC | FDR | Description |
|---|---|---|---|
| snRNA | 5.05 | 1.96E-100 | Rn7SK small nuclear RNA |
| NR4A3 | 4.43 | 1.09E-70 | Nuclear receptor subfamily 4 |
| PPP1R15A | 3.83 | 3.84E-126 | Protein phosphatase regulatory (inhibitor) |
| FOSB | 3.40 | 2.87E-33 | FBJ osteosarcoma oncogene B |
| PIM1 | 3.39 | 2.55E-169 | Proviral integration site 1 |
| TBC1D9 | 3.02 | 1.17E-34 | TBC1 domain family |
| NR4A2 | 2.93 | 1.33E-61 | Nuclear receptor subfamily 4 |
| NUPR1 | 2.86 | 7.67E-40 | Nuclear protein transcription regulator 1 |
| GPER1 | 2.75 | 3.04E-19 | G protein-coupled estrogen receptor 1 |
| NECTIN4 | 2.68 | 1.48E-18 | Nectin cell adhesion molecule 4 |
| NEDD4 | 2.63 | 2.78E-35 | Neural precursor cell expressed |
| FGFR4 | 2.55 | 1.62E-16 | Fibroblast growth factor receptor 4 |
| GEM | 2.55 | 4.58E-17 | GTP binding protein |
| MAFF | 2.52 | 7.31E-26 | V-maf musculoaponeurotic fibrosarcoma oncogene family |
| FHDC1 | 2.42 | 3.61E-24 | FH2 domain containing 1 |
| CELSR2 | 2.38 | 2.49E-14 | Cadherin |
| RASGEF1B | 2.36 | 7.96E-24 | RasGEF domain family |
| FAM46C | 2.36 | 4.53E-14 | Family with sequence similarity 46 |
| HIST1H4N | 2.36 | 4.62E-14 | Histone cluster 1 |
| PLAT | 2.36 | 6.30E-18 | Plasminogen activator |
Table 3.
Top 20 (largest log2FC) differentially expressed genes (DEG) at 48 h simulated microgravity environment
| Name | log2FC | FDR | Description |
|---|---|---|---|
| HSPA1B | 4.55 | 1.90E-46 | Heat shock protein 1B |
| GPER1 | 4.19 | 1.01E-31 | G protein-coupled estrogen receptor 1 |
| THSD4 | 3.86 | 1.73E-24 | Thrombospondin type domain containing 4 |
| DMPK | 3.52 | 4.16E-58 | Dystrophia myotonica-protein kinase |
| SLC17A6 | 3.44 | 1.35E-15 | Solute carrier family 17 (sodium-dependent inorganic phosphate cotransporter) member 6 |
| GUCY2G | 3.41 | 1.46E-20 | Guanylate cyclase 2 g |
| COX6A2 | -3.39 | 6.42E-37 | Cytochrome c oxidase subunit VIa polypeptide 2 |
| FAM20A | 3.39 | 2.04E-14 | Family with sequence similarity 20 member A |
| AKR1B3 | 3.35 | 1.68E-32 | Aldo–keto reductase family 1 member B3 (aldose reductase) |
| S1PR1 | − 3.26 | 2.27E-85 | Sphingosine-1-phosphate receptor 1 |
| SORBS3 | − 3.25 | 1.59E-26 | Sorbin and SH3 domain containing 3 |
| SCN11A | 3.23 | 2.67E-20 | Sodium channel voltage-gated type XI alpha |
| SOAT2 | − 3.23 | 2.63E-29 | Sterol O-acyltransferase 2 |
| ARID5A | − 3.23 | 1.90E-19 | AT rich interactive domain 5A (MRF1-like) |
| CLCA2 | 3.21 | 2.48E-11 | Chloride channel accessory 2 |
| TRIB3 | − 3.10 | 1.46E-20 | Tribbles pseudokinase 3 |
| PAQR5 | 3.03 | 2.12E-12 | Progestin and adipoQ receptor family member V |
| PHOSPHO1 | 2.98 | 5.82E-25 | Phosphatase orphan 1 |
| DDIT3 | − 2.96 | 1.26E-17 | DNA-damage inducible transcript 3 |
| COL15A1 | − 2.84 | 1.09E-12 | Collagen type XV alpha 1 |
Next, according to current knowledge, the growth and assemble of actin filaments are critical steps for macrophage phagocytosis [31–33], and then we focused on RAC-WAVE-ARP2/3 signaling pathway that was related to cell cytoskeleton synthesis. The genes involved in RAC-WAVE-ARP 2/3 signaling pathway, including TLR2, FcγR1, CD11b, CD18, RAC1, WASP2, WAVE2, and ARP2, were detected by real-time qPCR at 3 time points. Results showed that these genes expression decreased under μg condition (Fig. 4A–C, P-value < 0.05), which were consistent with RNA-seq results. The decreased expression of these genes led to a reduction of cytoskeleton synthesis and further influenced the morphology of cells. Therefore, it resulted in a macrophage phagocytosis dysfunction.
Taken together, we have demonstrated that microgravity simulated by magnetic levitation might inhibit macrophage phagocytosis by reducing the expression of molecules in RAC-WAVE-ARP 2/3 signaling pathway. These results offered novel insights for understanding the brief principles and mechanisms of microgravity-induced immune dysfunction to macrophage. On the other hand, our results can provide potential therapeutic intervention to strengthen the immune response, which may assist astronauts’ or crew members’ health during frequent or prolonged missions.
Conclusion
In conclusion, we evaluated the effects of simulated microgravity treatment on mouse macrophage cell line. As study endpoints, we measured cell propagation and phagocytosis function and used next-generation sequencing (NGS) to obtain differentially expressed genes (DEG) at each time point. Through transcriptome analysis and confirmed by molecular biological verification, our findings firstly suggest that simulated microgravity might affect macrophage phagocytosis by targeting Arp 2/3 complex involved cytoskeleton synthesis and causing macrophage immune dysfunction. Our findings contribute to an emerging body of scholarship on biological effects of space travel.
Supplementary Information
Below is the link to the electronic supplementary material.
Funding
This work was funded by the National Natural Science Foundation of China (31800781, 61927810, 12002285), China Postdoctoral Science Foundation (2018M631198), Key Research and Development Program of Shaanxi (2020JZ-11), Natural Science Basic Research Program of Shaanxi (2020JQ-126), Fundamental Research Funds for the Central Universities (G2020KY05203), and the Seed Foundation of Innovation and Creation for Graduate Students in Northwestern Polytechnical University (ZZ2018240).
Data availability
The authors confirm that the data supporting the findings of this study are available within the article [and/or] its supplementary materials. RNA-seq reads have been deposited into NCBI SRA database (PRJNA551509).
Declarations
Conflict of interest
There are no conflicts of interest to declare.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Sufang Wang and Nu Zhang contributed equally
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The authors confirm that the data supporting the findings of this study are available within the article [and/or] its supplementary materials. RNA-seq reads have been deposited into NCBI SRA database (PRJNA551509).