Introduction

The apple snail, Pomacea canaliculata (Lamarck, 1819) is a large freshwater snail that typically inhabits rivers, ditches, and rice fields in the tropics and subtropics1. Due to its rapid reproduction ability, strong environmental adaptability and the habit of migrating with the water flow, coupled with the trend of global warming, the distribution range of the apple snail has spread from the tropical regions to temperate regions2. The apple snail has a unique "gill-lung" respiratory system, which can not only breathe with gills in the water, but also exchange gas in the air through the lung3. This snail has a wide range of food habits and a large food intake, and often eats aquatic crops such as lotus root, rice and wild rice, which not only poses a threat to agricultural production activities, but also seriously persecutes the ecological niche of local snails, causing great damage to the local ecosystem and species diversity4. In addition, apple snails have a large number of internal parasites, and people can suffer from serious health problems such as eosinophilic meningoencephalitis when they accidentally ingest apple snails parasitized by zoonotic parasites5. In view of its harmful effects on the ecosystem and human health, the International Union for Conservation of Nature (IUCN) recognized the apple snail as one of the world’s 100 pernicious invasive alien species in 20006.

Air exposure stress refers to exposing aquatic animals to air away from the water body, which will cause water imbalance in the aquatic organism7. The apple snail, when sensing the absence of water in the environment, rapidly secretes mucus to close the shell opening, stops feeding and all activities, and enters a dormant state8. This state can pose new challenges to the survival of the apple snail, including oxidative stress, accumulation of toxic metabolites, muscle atrophy due to prolonged inactivity, and degradation of internal organs due to prolonged starvation9. This survival strategy has been found in several animals, including amphibians, reptiles, mollusks, and fish, which survive long periods of dormancy by suppressing metabolic rate and respiration to reduce water loss and energy expenditure8. For example, the Xenopus laevis (Daudin, 1802) enters a state of dormancy by burying itself in the soil and remaining still in the face of seasonal droughts in lake habitats. During this period, African clawed frogs face severe dehydration, losing 25 to 30% of their body water, resulting in increased blood concentration and hypoxic stress due to impeded oxygen transport, and then shift from aerobic to anaerobic metabolism to meet the energy requirements of dormant hypoxic conditions. Although prolonged resting as well as starvation during dormancy can lead to atrophy of muscles, liver and intestine. However, the liver and muscle tissues remain intact and are able to resume normal activity at the end of dormancy10,11. The Chondrina avenacea (Bruguière, 1792) lives on the surface of rock walls and is exposed to environmental drought and waterlessness during the hot summer months when they go directly into dormancy. The coat membrane tightly closes the shell opening to remain highly impermeable to water during dormancy, and the mouth cap formed by mucopolysaccharides secreted by the coat membrane tightly seals the shell opening to further reduce water evaporation, and energy is conserved by intermittent opening of the respiratory pores for gas exchange and by reducing the metabolic rate to 30% of the normal state12,13.

Past studies on the tolerance of the apple snail to air exposure have focused on physiology, biochemistry, and behavior14. Studies have been conducted to induce dormancy in apple snails by air exposure stress, observed behavioral changes and examined the peroxide and antioxidant contents8,15. The results of the study revealed that uric acid acts as a non-enzymatic antioxidant during dormancy in apple snails. In addition, superoxide dismutase and catalase, two key enzymes for defense against oxidative stress, continued to function throughout the dormancy period. By treating apple snails with air exposure, Guo et al. found that air exposure had an inhibitory effect on the growth of apple snails and that the activities of digestive enzymes and antioxidant enzymes were enhanced in apple snails16. The current research on the molecular mechanisms of adversity adaptation in apple snails is insufficient and requires further investigation.

Transcriptome sequencing, a technique for sequencing and analyzing mRNAs in tissues or cells using high-throughput sequencing technology, can help to gain a deeper understanding of the gene transcription of the apple snail under air-exposure treatment conditions17,18. In this study, we analyzed the gene transcripts of apple snails at different periods. Meanwhile, we also studied gene transcripts before and after exposure to air and before and after return to water. The objective of this study was to explore key drought tolerance genes and pathways in apple snails. This provides a theoretical basis for the study of apple snail biological defense and control. Furthermore, the screening of genes that are specifically expressed and regulate drought tolerance, dormancy and awakening in apple snails will facilitate the control of their population size through the utilization of molecular regulatory techniques. This approach will consequently reduce the ecological impact of apple snails.

Results

Gene function annotation

The results of gene function annotation of the apple snail gene sequences (ASM307304v1) in the Interpor, GO, eggNOG, KOG, Swissprot, Nr, Pfam, and KEGG databases are shown in Table S1. A total of 17,423 sequences were annotated, accounting for 95.40% of the total gene count. Among them, 17,350 sequences were annotated by Nr database, with an annotation rate of 95.00%, followed by InterPro, eggNOG, Pfam, GO, Swissprot, KOG, and KEGG databases in the order of the number of sequences getting annotated were 14,664 (80.29%), 13,858 (75.88%), 12,890 (70.58%), 12,774 (69.94%), 11,806 (64.64%), 9,440 (51.69%), 8,112 (44.42%).

Mechanisms of drought tolerance in the apple snail

Assessment of correlation between samples

The degree of correlation between the samples was assessed using principal component analysis and heatmap (Figure S1). The results showed good intra-group correlations with reliable biological replicates, poor inter-group correlations and significant differences between groups.

Differentially expressed genes analysis

To investigate the drought tolerance mechanism of apple snails under air exposure stress, we analyzed the differentially expressed genes (DEGs) between the control group (CK) and three different air exposure duration groups (DRY05, DRY15, DRY30), respectively (Figure S2). A total of 5446 DEGs were screened in DRY05 vs CK; a total of 3278 DEGs were screened in DRY15 vs CK; a total of 9527 DEGs were screened in DRY30 vs CK; the number of DEGs shared by DRY05 vs CK, DRY15 vs CK, and DRY30 vs CK, was 1521 (Fig. 1A).

Fig. 1
figure 1

DEGs analyses and functional enrichment analyses between control samples and the three treatment groups (DRY05, DRY15, and DRY30). (A). Relationships between the DEGs sets resulting from the three treatment groups compared with the CK group. (B). KEGG enrichment analysis of shared DEGs between the CK group and the three treatment groups. (C). GSEA in the three treatment groups compared to the CK group. (D). Heatmap of the DEGs in the 10 pathways obtained by GSEA in relation to the samples.

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Functional enrichment analysis

KEGG enrichment results showed that 1521 shared DEGs were significantly enriched (P < 0.05) in the pathways of biosynthesis of secondary metabolites, metabolism of xenobiotics by cytochrome P450, drug metabolism – cytochrome P450, adherens junction, starch and sucrose metabolism, linoleic acid metabolism, glutathione metabolism, adipocytokine signaling pathway, glycosaminoglycan degradation, alpha-linolenic acid metabolism, caffeine metabolism, pentose phosphate pathway, and phenylpropanoid biosynthesis (Fig. 1B). Gene set enrichment analysis (GSEA) further illustrated significant down-regulation (NES < 0; P < 0.05) of metabolism-related pathways such as alpha-linolenic acid metabolism, caffeine metabolism, and starch and sucrose metabolism in the three air-exposed treatment groups (Fig. 1C). The expression levels of PLA2G16 (P._canaliculata16483) and CYP3A (P._canaliculata03081), genes involved in the pathway of linoleic acid metabolism, were found to be significantly lower (P < 0.05) in all three groups exposed to air treatment compared to the control group. Specifically, the fold changes for PLA2G16 and CYP3A were 0.14 and 0.12 in DRY05 vs. CK, 0.11 and 0.06 in DRY15 vs. CK, and 0.03 and 0.05 in DRY30 vs. CK, respectively (Table S2). This finding indicates that the apple snail exhibits a reduced capacity for synthesizing and metabolizing linoleic acid in response to extended periods of air exposure. In addition, the dynamic expression of other genes in the ten pathways enriched by GSEA as illustrated in Fig. 1C, is demonstrated in Fig. 1D and Table S3.

Weighted correlation network analysis (WGCNA)

The soft threshold value of 16 is chosen for subsequent scale-free network construction (Figure S3). The gene cluster dendrogram is shown in Fig. 2A. All genes were classified into 49 modules, and the modules with an absolute value of module-sample correlation greater than 0.6 were filtered as key modules, which were MElightgreen, MEplum1, MEmagenta, and MEskyblue3 (Fig. 2B-C).

Fig. 2
figure 2

Screening of gene modules with high relevance to the apple snail dormancy process by WGCNA. (A). Cluster dendrogram showing the distribution of gene modules. (B). Heatmap of correlation between modules and samples. (C). Screening of modules highly correlated with changes in sample information with a correlation threshold of 0.6.

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The results of the functional enrichment analysis of the genes in the key modules are shown in Fig. 3A-B. The results showed that the genes in the key modules were significantly enriched (P < 0.05) in pathways related to the immune system and immune signaling, including toll-like receptor signaling pathway, NF-kappa B signaling pathway, TNF signaling pathway, IL − 17 signaling pathway, B cell receptor signaling pathway, and T cell differentiation etc. GSEA screened for two pathways toll-like receptor signaling pathway and adherens junction, which were significantly down-regulated (P < 0.05; NES < 0) in all groups compared to the CK group (Fig. 3C). The heatmap of the correlation between genes (in the Toll-like receptor signaling pathway) and samples is shown in Fig. 3D. Genes in the key sub-network obtained using MCODE analysis included CASP2 (P._canaliculata06368), CASP10 (P._canaliculata08497) and TRAF3 (P._canaliculata10481, P._canaliculata10483), etc. (Fig. 3E). All four genes reached minimum values on day 30 of dormancy for fold changes of 0.28, 0.44, 0.21 and 0.21, respectively (Table S2).

Fig. 3
figure 3

Functional enrichment analysis of key modules in WGCNA and PPI network construction of genes in key pathways. (A). KEGG enrichment analysis of genes in key modules. (B). GO-based GSEA for genes in key modules. (C). KEGG-based GSEA for genes in key modules. (D). Heatmap of the relationship between DEGs in the key pathway Toll-like receptor signaling pathway obtained by KEGG-based GSEA and samples (E). Key sub-networks obtained using the MCODE plug-in after constructing PPI networks using genes in the Toll-like receptor signaling pathway.

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Mechanisms of dormancy and awakening in apple snails

DEGs analysis

To investigate the mechanisms by which the apple snail enters dormancy under air-exposure stress and awakens in water, we analyzed DEGs between the DRY01 and CK groups (DRY01 vs CK) and between the RCY01 and DRY30 groups (RCY01 vs DRY30), respectively (Fig. 4A). A total of 443 DEGs were screened in DRY01 vs CK; a total of 4297 DEGs were screened in RCY01 vs DRY30 (Figure S4).

Fig. 4
figure 4

Analysis of DEGs and functional enrichment of apple snails before and after dormancy (DRY01 vs CK) and before and after awakening (RCY01 vs DRY30). (A). Volcano plot of DEGs in DRY01 vs CK and RCY01 vs DRY30. (B). GO enrichment analysis of DEGs. Specific information on GO terms is shown in Figure S5. (C). KEGG-based GSEA searches for pathways with opposite mechanisms of dormancy and awakening in apple snails. (D). GO-based GSEA.

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GO enrichment analysis

GO enrichment analysis illustrated that the DEGs of DRY01 vs. CK were significantly enriched (P < 0.05) in GO terms such as cilium assembly, cilium organisation, plasma membrane bounded cell projection assembly, and cell projection assembly, and most of them showed increased expression levels (log2FoldChang > 1). The DEGs in RCY01 vs. DRY30 were also significantly enriched (P < 0.05) in these GO terms, but the difference was that most of the DEGs had decreased expression levels (log2FoldChang > 1; Fig. 4B and Figure S5). This suggests that genes associated with cell signaling, cell motility and cell-to-cell interactions play a key role in the entry and exit from dormancy in apple snails.

Gene set enrichment analysis

GSEA obtained 11 KEGG pathways which were significantly down-regulated in DRY01 vs. CK (P < 0.05, NES < 0) and up-regulated (P < 0.05, NES > 0) in RCY01 vs. DRY30, including toll-like receptor signaling pathway, regulation of actin cytoskeleton, proteoglycans in cancer, NOD-like receptor signaling pathway, NF-kappa B signaling pathway, necroptosis, influenza A, hepatitis C, focal adhesion, cell adhesion molecules, and adherens junction. These pathways are closely related to the immune system and intercellular adhesion. In addition, seven KEGG pathways significantly up-regulated in DRY01 vs CK and down-regulated in RCY01 vs DRY30 were obtained for vitamin digestion and absorption, protein processing in endoplasmic reticulum, proteasome, meiosis—yeast, cell cycle—yeast, cell cycle and ABC transporters (Fig. 4C). Significant up-regulation of protein processing in endoplasmic reticulum (P < 0.01, NES = 1.77) and cell cycle (P < 0.01, NES = 1.69) after air exposure leads to dormancy in apple snails may be activated by protein misfolding and DNA damage. Similar results were obtained for GO-based GSEA (Fig. 4D). The results illustrated that genes associated with cell cycle were significantly up-regulated when the apple snail entered dormancy and down-regulated after rehydration. Genes associated with the immune system and intercellular adhesion similarly showed opposite expression patterns when the apple snail entered dormancy and after awakening.

Validation of transcriptome data using qPCR

The real-time quantitative PCR (qPCR) validation results are shown in Fig. 5. The results showed that the qPCR results of the 8 DEGs (HSP90A, CRYZ, CCT7, PSAT1, CPT1A, ARG1, PCK1, GPX1, and HPGDS) matched with the RNA-seq results, so the results of the sequencing analysis had high confidence.

Fig. 5
figure 5

The results of transcriptome analysis were verified by qPCR. Horizontal coordinates are gene numbers from transcriptome sequencing, vertical coordinates are log2FoldChange (RNA-seq) or log2(2−ΔΔCT/2−ΔΔCT) (qPCR). HPGDS, Hematopoietic Prostaglandin D Synthase; CRYZ, Crystallin Zeta; CPT1A, Carnitine Palmitoyltransferase 1A; PCK1, Phosphoenolpyruvate Carboxykinase 1; PSAT1, Phosphoserine Aminotransferase 1; CCT7, Chaperonin Containing TCP1 Subunit 7; HSP90A, Heat Shock Protein 90 Alpha Family; GPX1, Glutathione Peroxidase 1.

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Discussion

Air exposure is a phenomenon in which aquatic organisms are removed from the water environment and exposed to air. To survive the stress of air exposure, some aquatic organisms rapidly enter a state of dormancy19,20,21. Dormancy is a common physiological state in amphibians, reptiles, invertebrates, mollusks, echinoderms, and fish in response to extreme environmental stresses such as high or low temperatures, drought, or food shortages. The existence of dormancy in some organisms as early as 200 million years ago can be demonstrated by fossil evidence from Pleistocene earthworm burrows, Devonian to Cretaceous lungfish burrows, Permian earthworm burrows, and Permian to Triassic bivalve burrows22. Apple snails tend to protect themselves from air exposure stress by entering dormancy. In this study, we induced dormancy in apple snails by air exposure and comparatively analyzed the differences in gene transcript levels in the liver tissue of apple snails in the CK group and at 5, 15, and 30 days (DRY30) of dormancy to explore the mechanisms of drought tolerance during dormancy in apple snails. KEGG enrichment analysis of shared DEGs revealed that these genes were significantly enriched in metabolism-related pathways, such as Starch and sucrose metabolism, Linoleic acid metabolism, Glutathione metabolism, Glycosaminoglycan degradation, etc. While in GSEA similarly several metabolism-related pathways were found to be significantly up-regulated in the control group compared to the experimental group. This can be interpreted as an indication that the metabolic functions of the apple snail are suppressed during dormancy, and the organism reduces energy consumption by lowering the metabolic rate to ensure that it can maintain prolonged life activities without external water and food sources23,24,25. Linoleic acid is one of the basic components of cell membranes26. Down-regulation of linoleic acid metabolism may contribute to the maintenance of normal cell morphology during dormancy in apple snails. However, the down-regulation of linoleic acid metabolism, as a precursor of arachidonic acid, also implies that neural development and growth will be affected27. Abnormalities in Glycosaminoglycan degradation and Glutathione metabolic pathways during dormancy in apple snails are of interest. Glycosaminoglycans have a variety of biological functions. For example, they are an important component of the extracellular matrix and are hydrophilic, which provides structural support for cells and retains water in cells28,29. When animals are dormant, metabolic activities are inhibited and the synthesis of biomolecules such as glycosaminoglycans is slowed down accordingly. Therefore, down-regulation of the glycosaminoglycan degradation pathway in the apple snail under the stress of air exposure contributes to the maintenance of intracellular glycosaminoglycan content, which can help the apple snail to maintain the stability of the cytoplasmic matrix and the storage of intracellular water. In addition, glycosaminoglycans have antioxidant properties that scavenge excess free radicals from the body30. Glutathione is also an antioxidant and plays an important role in the proper functioning of the immune system by resisting oxidative damage and integrating detoxification31.

WGCNA results showed that air exposure stress significantly affected apoptosis, cell–cell adherens junction, insulin resistance and immune status in apple snails. Caspases are the main enzymes that execute apoptosis32. In this study, CASP2, CASP10 and TRAF3 associated with apoptosis were screened as hub genes. Apple snails are starved for a long-time during dormancy and need to consume their own stored energy substances to maintain their life activities, a process that may be accompanied by damage to body tissues and further lead to organ degeneration. Previous studies have shown that organs such as the gastrointestinal tract, liver and pancreas of the Apostichopus japonicus (Selenka, 1867) deteriorate during dormancy due to prolonged periods of non-feeding, which is closely related to apoptosis33,34. The onset of apoptosis is influenced by many interrelated processes. The immune system and immune signaling are involved in the regulation of apoptosis35. In the present study, significant differences in immune status were found between the control group and all other groups, and toll-like receptor signaling pathway was screened to be significantly down-regulated in all experimental groups compared to the control group in the GSEA results. Toll-like receptor activation can further activate downstream nuclear factor kappa-B or interferon regulatory factors through a myeloid differentiation primary response protein 88-dependent pathway, which in turn induces the secretion of cytokines such as tumor necrosis factor, interleukin, and interferon, and thus exerts immune functions36. This process is significantly down-regulated during dormancy in apple snails and may be related to the level of immune cells in apple snails. The vital activities of immune cells require a lot of energy, and the reduction of autoimmune levels during dormancy may help the apple snail to achieve conservation of energy consumption37. Changes in insulin resistance are of equal interest. Many dormant animals such as the Protopterus annectens (Owen, 1839) increase their fat reserves prior to dormancy and rely on these reserves to provide them with metabolic fuel during dormancy, possibly through the mechanism of insulin resistance, which regulates the uptake and oxidation of glucose, promotes the process of gluconeogenesis in the liver and inhibits anabolism throughout the body to conserve energy38,39,40. In this study, the expression of PEPCK (Phosphoenolpyruvate carboxykinase; P._canaliculata11272) was significantly lower in the control group than in the groups during apple snail dormancy. PEPCK is the rate-limiting enzyme of hepatic and renal gluconeogenesis and a key regulator of the tricarboxylic acid cycle41,42. Elevated PEPCK expression during dormancy implies that more non-glycans may be converted to glucose in the organism via the gluconeogenesis. In addition, another gene in the insulin resistance pathway, CPT1A (carnitine O-palmitoyltransferase 1; P._canaliculata05988), was found to be significantly more expressed in the control group than in the groups during dormancy of apple snails in this study. CPT1A generates acylcarnitines by catalyzing the binding of long-chain acyl coenzyme A to carnitine. This step is the first step in driving fatty acids across the mitochondrial membrane from the cytoplasmic matrix into the mitochondria for β-oxidation43. The low expression of CPT1A during dormancy corresponds to the low metabolic state of the apple snail.

In order to explore the molecular mechanisms underlying the entry into dormancy and the awakening of apple snails after rehydration, the present study comparatively analyzed the differences in gene transcript levels between the CK group and the DRY01 group shortly after entry into dormancy, as well as between the DRY30 group, which had been dormant for 30 days, and the RCY01 group, which had awakened after dormancy. The results show that functions related to cell cycle, immune status and intercellular adhesion are significantly affected when apple snails enter dormancy or awakening. Specifically, upon entering dormancy, the cell cycle-related functions of the apple snail were up-regulated, and the immune state and intercellular adhesion-related functions were down-regulated, whereas upon awakening the cell cycle-related energy was down-regulated and the immune state and intercellular adhesion-related functions were up-regulated. The relationship between the cell cycle and dormancy is complex and subtle. The cell cycle is a process of cell growth and division that includes multiple phases, whereas dormancy is a cellular state in which cells temporarily stop proliferating but remain alive44,45. It has been shown that the dormant state of tumor cells is associated with specific phases of the cell cycle46. Changes in the cell cycle during dormancy-awakening in apple snails may be due to specific cellular responses to stress, which needs to be explored in further studies. In addition, the present study suggests that the apple snail rapidly enters a hypometabolic state by significantly lowering its immune level shortly after entering dormancy, and that the immune level rapidly rebounds upon awakening in the water. While previous studies have generally concluded that normal sleep induces inflammatory activity, which strengthens the body’s resistance to pathogens, dormancy due to air exposure in the apple snail does not appear to be the same as normal sleep, leading to the results of this study47,48,49. In the present study, the changes in function related to intercellular adhesion when the apple snail enters dormancy and when it rehydrates and awakens may be due to the fact that the dormant state requires a reduction in energy expenditure, and that reducing intercellular adhesion reduces the amount of energy required by the cell to maintain these adhesions. At the same time, the reduction of intercellular adhesion also helps the cells to change their state quickly when needed in order to reactivate quickly in response to appropriate signals50. In some cases, the reduction of intercellular adhesions due to dormancy also causes the cell to lose polarity, and the loss of cell polarity helps the cell to enter a more quiescent state51.

Conclusions

In summary, this study revealed that pathways related to metabolic functions such as starch and sucrose metabolism, linoleic acid metabolism, glutathione metabolism, and glycosaminoglycan degradation were suppressed during dormancy in apple snails. WGCNA screened for two key pathways, the toll-like receptor signaling pathway and adherens junction. We suggest that down-regulation of these pathways may help apple snails to reduce energy expenditure and maintain vital activities under air exposure. A further analysis was conducted on the alterations in transcript levels in apple snails, both prior to and following dormancy, as well as before and after awakening, respectively. The gene functions and pathways obtained from the enrichment analyses were then classified into three categories: cell cycle, immune system and intercellular adhesion. In this study, the mechanisms of drought tolerance in the apple snail were investigated. A number of key pathways and genes were screened, such as PLA2G16 and CYP3A in linoleic acid metabolism, CPY1A in insulin resistance, and CASP2, CASP10, and TRAF3 in toll-like receptor signaling pathway. The expression of these genes was found to be significantly affected by air exposure stress, thus constituting an important component of the molecular mechanisms by which apple snails respond to environmental stress. This study provides fundamental research for the future application of molecular regulatory techniques to control the population size of this species, which will contribute to reducing the ecological impact of apple snails.

Materials and methods

Sample collection

The apple snails were collected from the suburbs of Hangzhou (Zhejiang, China), and kept in tanks with water changed every two days and fed with fresh greens. After a period of feeding, the apple snails of similar weight (24.25 ± 2.04 g) and shell length (47.60 ± 2.65 mm) were selected and placed equally (40 snails per tank) in three dry tanks for air exposure. After a day, the apple snails stood still and went into dormancy. The air exposure phase lasted for 30 days, during which time the ambient temperature ranged from 24 ℃ to 26 ℃ and the relative humidity ranged from 45 to 50%. After 30 days of air exposure, the remaining apple snails were returned to 24 ℃ water to reawaken.

Samples were taken on four days (days 1, 5, 15, and 30) of the air exposure phase and one day after resubmerged in water. Grouped in chronological order of sampling are named DRY01, DRY05, DRY15, DRY30 and RCY01. Non-air exposed apple snails were taken as control (CK). Liver tissues from three snails in each tank was collected per sampling for RNA extraction. All liver tissues were rapidly frozen using liquid nitrogen at the time of sampling and later stored in a refrigerator at a temperature set to − 80 ℃.

Total RNA extraction

Total RNA was extracted from 18 liver tissue samples of apple snails using TRIzol (Invitrogen, USA) reagent in the following steps: 1) Take the liver tissue in a centrifuge tube, add 1 ml Trizol reagent, and homogenize thoroughly, leave for 5 min at room temperature; 2) Centrifuge at 10,000 g at 4 ℃ for 10 min, take the supernatant; 3) Add 0.2 ml of chloroform, shake vigorously, and incubate for 3 min at room temperature; 4) Centrifuge the mixed sample at 12,000 g for 10 min at 4 °C and aspirate the supernatant; 5) Add 0.5 ml isopropanol to the supernatant, mix the liquid in the tube gently, and leave it at room temperature for 10 min; 6) Centrifuge at 12,000 g for 10 min at 4 °C. Remove the supernatant and retain the precipitate; 7) Add 1 ml of 75% pre-cooled ethanol to the precipitate and shake; 8) Centrifuge at 12000 g for 5 min at 4 °C, remove the supernatant and retain the precipitate; 9) Add 20 μl of DEPC-treated double-distilled deionized water to dissolve RNA and incubate at 60 ℃ for 5 min; 10) RNA integrity was detected using an Agilent 2100 (Agilent, USA) instrument; sample RNA integrity was analyzed by an agarose gel electrophoresis test, and RNA concentration and purity were detected using a NanoDrop (NanoDrop, USA) instrument.

Transcriptome analysis

Analysis of sequencing data

Total RNA samples were sent to the Frasergen Information Company (Wuhan, China) for sequencing. Raw reads obtained from sequencing were weeded out of spliced and low-quality reads by the Trimomatic v0.39 tool to obtain high-quality clean reads (Table S4). Functional prediction was performed by downloading the reference genome of the apple snail (ASM307304v1) at the National Center for Biotechnology Information (NCBI), and all protein sequences of the apple snail reference genome were aligned with Nr, InterPor, GO, eggNOG, KOG, Swissprot, Pfam, KEGG and other databases to obtain gene function and pathway annotations. HISAT2 v2.0.4 software was used to compare the clean reads to the reference genome of the apple snail (Table S5), and Samtools v1.20 tool was used to organize the alignment hits in the order of the reference sequences. Based on the alignment results, the gene expression was estimated with the help of StringTie v1.3.4 software, and the number of read segments located in the exons of the genes after alignment and the FPKM values were extracted from the results using Stringtie and Ballgown.

Differential expression analysis

Differential expression analysis using Bioconductor’s R package DESeq2: the Read counts matrix was entered, the grouping information was constructed as a condition vector, and the DESeqDataSet object was constructed, including the normalization of expression values, and the DESeq function was used to calculate the fold change and significance p-values of genes. Input Read counts matrix, construct the condition vector from the grouping information, construct the DESeqDataSet object, including the normalization of the expression values, and use the DESeq function to calculate the gene’s differential fold change and significance P value. Genes where |log2FoldChange|> 1 and P < 0.05 can be defined as DEGs.

Functional enrichment analysis

GO enrichment analysis and KEGG enrichment analysis of DEGs using the DAVID database (https://david.ncifcrf.gov/). GSEA used GSEA software and the MSigDB database. P < 0.05 indicate statistical significance.

Weighted correlation network analysis

WGCNA is mainly carried out using the WGCNA package in R programming language. Calculate the soft threshold using the pick Soft Threshold () function; choose an appropriate soft threshold based on the analysis of network topology for various soft thresholding powers; use the blockwiseModules() function for network construction and module identification, setting minModuleSize = 30, deepSplit = 3, mergeCutHeight = 0.1; modules were sorted and gene cluster dendrogram was drawn. The key modules were filtered by calculating the correlation between the modules and the sample-info, and then the key modules were analyzed for functional enrichment.

Protein–protein interaction network construction

Protein–protein interaction network was analyzed by applying the interactions in the STRING protein interaction database (http://string-db.org). The results were visualized using cytoscape software. Key subnetworks and genes are screened by the MCODE plugin.

Real-time quantitative PCR

To confirm the reliability of the transcriptome analysis results, we analyzed the relative expression of the 8 DEGs in all groups using qPCR. The methods of qPCR experiments and calculation of relative gene expression are the same as those of Pang et al.52. The log2(2−ΔΔCT/2−ΔΔCT) was calculated to compare with the log2FoldChang value in the transcriptome results. Information on the primers is given in Table S6.