MEI Yaoping, HOU Zhishuai, GAO Qinfeng, *, DONG Shuanglin, LI Xueqi, and XU Yuling

Transcriptome Analysis Reveals New Insights into the Respiration Metabolism Mechanism of Different Feeding Rations of Sea Cucumber ()

MEI Yaoping1), 2), HOU Zhishuai1), GAO Qinfeng1), 2), *, DONG Shuanglin1), 2), LI Xueqi1), 2), and XU Yuling1), 2)

1),,,266003,2),,266235,

Sea cucumber () is an excellent model for investigating effects of bottom-dwellers on carbon mig- ration and transformation. However, the molecular mechanism of respiratory metabolism process variation caused by feeding rations is poorly understood. In this study, treatment groups set as 1% (about 0.63g), 3%, and 7% of total body weight (named F1, F3 and F7 groups respectively). The potential molecular mechanisms behind the functions of respiratory tree and body wall were investigated by RNA-Seq. A total of 52411 expressed genes were identified from 89342 expressed transcripts. The results showed 759, 254 and 334 genes were up-regulated, and 334, 445 and 992 genes were down-regulated in respiratory tree of F1. F3, F1. F7 and F3. F7, respectively. Meanwhile, 2070, 1601 and 896 genes were up-regulated, and 1303, 1337 and 1144 genes were down-regulated in body wall between F1. F3, F1. F7 and F3. F7, respectively. Differentially expressed genes were enriched in salivary secretion and ECM-receptor interaction pathways in respiratory tree, and in various types of N-glycan biosynthesis, ribosome and sphingolipid metabolism pathways in body wall. These results suggested respiratory tree and body wall were involved in activation of respiratory metabolisms in response to different feeding rations. Our research provided valuable knowledge for physiological differences in respiratory metabolism.

transcriptomics;; feeding ration; respiration metabolism

1 Introduction

The sea cucumber () is an impor-tant aquaculture species in China due to its high nutritionalvalue (Kiew and Don, 2012). In recent decades, overex- ploitation of natural resources results in a significant decline of its population. The sea cucumber farming industry has developed rapidly to satisfy the increased consumption mar- kets (Liu., 2015; Ru., 2018). For example, Food and Agriculture Organization showed total production ofsea cucumber has reached about 201500tons in 2020, show- ing a 252% increase when compared to that in 2005 (FAO, 2022).

Feeding ration is an important abiotic factor in suitable feeding strategies in aquaculture. Previous studies reveal- ed the effects of different feeding rations on growth (Niu., 2015; Ghosh, 2017), metabolism (Luo., 2021) and behavior (Sun., 2015). For example, over-feed-ing ration caused low growth rate, reduced feed conversion efficiency, and deterioration of water quality (Tong., 2020; Luo., 2021), while a lower feeding ration result- ed in increased feed competition, reduced animal size ho- mogeneity and decreased survival rate (Millot., 2008; Wan, 2022). Therefore, an optimal feeding ration provides both aquaculture and environmental benefits. The optimal feeding ration needs to be determined in species-specific (Abidi and Khan, 2014; Li., 2016). Compared to pre- vious studies investigating optimal feeding ration in eco- nomy fishes, such as juvenile blunt snout bream () (Xu., 2016) and rainbow trout () (Weber., 2022), effects of feed- ing ration on sea cucumber respiratory metabolism still need to be investigated.

Respiration metabolism, as a basic physiological process for animals, can provide energy for life activities. Animals regulate energy trade off to improve their adaptivity in re- sponse to environmental changes, including feeding ration(Herrera., 2011), temperature (Sin., 2019), sali- nity (Urzúa and Urbina, 2017) and some other abiotic fac- tors (Shen., 2020). Previous studies indicate feeding rations are associated with respiratory physiology and me- tabolism (Yu., 2019). For example, feeding rations can affect enzyme activities and metabolites in respiratory me- tabolism, including pyruvate kinase (Luo., 2021), lac-tic dehydrogenase (Xing., 2021), glucose content (Niu., 2015) and lactate content (Li., 2016). However, transcriptional signatures related to respiratory metabolism are still needed to be investigated in sea cucumber.

Sea cucumber is able to modify various environmental nutrients’ contents and forms by feeding activities (Li., 2014; Hou., 2017). Therefore, sea cucumber can ser- ve as an excellent model for investigating the effects of bot- tom-dwellers on carbon migration and transformation. Pre- vious studies on sea cucumbers with RNA-Seq technology are more focused on responses to evisceration (Shi., 2020), environmental stress (Zhang., 2017a, 2018b) and Immunomodulation (Guo., 2021). In addition,many previous studies about the effects of feeding rationon respiratory metabolism have shown in osteichthyes (Lu-patsch., 2010; Stadtlander., 2013) and crustaceans(Brito., 2000; McGaw, 2007). However, studies on seacucumbers are still limited, especially the transcriptionalsignatures. In this study, the transcriptional signatures of respiratory tree and body wall in sea cucumber with diffe- rent feeding rations were determined. We aimed to conduct the genes related to respiratory metabolism in the respira- tory tree and body wall at different feeding rations and ex- plored the potential molecular mechanism. Our study pro- vided valuable information for better understanding their physiological process and ecological functions of sea cu- cumbers.

2 Materials and Methods

2.1 Experiment and Sample Collection

The healthy and similar sea cucumbers (12.67g±0.28g) were collected from a local commercial farm in Qingdao, China. Then individuals were transferred to 72L glass tanks with seawater at 16℃±0.5℃ and salinity 32. After accli- mation, all individuals were randomly and equally divided into 12 tanks. The commercial pelleted diet (Qingdao Hi- ford Ecology Technology Co., Ltd.) was fed once daily at 16:00, and the feeding rations were set at 1%, 3%, and 7% of total body weight (named F1, F3, and F7 respectively). After 32 days of experiment, the respiratory tree and body wall were obtained from F1, F3, and F7 for further ana- lyses.

2.2 Library Preparation

We used respiratory tree and body wall in F1, F3, and F7 for RNA-Seq analysis. Total RNA isolation was con- ducted by Trizol (Invitrogen, USA). The quality and quan- tity of the samples were evaluated. High-quality RNA sam- ples were used to construct sequencing libraries. All libra- ries were carried out on Illumina NovaSeq6000 and gene- rated 150bp paired reads. The libraries were named F1S1–F1S3 (F1 group respiratory tree libraries), F3S1–F3S3 (F3group respiratory tree libraries), F7S1–F7S3 (F7 group re- spiratory tree libraries), F1B1–F1B3 (F1 group body wall libraries), F3B1–F3B3 (F3 group body wall libraries), and F7B1–F7B3 (F7 group body wall libraries).

2.3 Differentially Expressed Genes (DEGs)Identification

Using SeqPrep and Sickle trimmed and quality control- led the raw paired-end reads. After removing all low-qua- lity reads, we obtained clean reads and calculated the Q20, Q30, and GC contents. All transcriptome sequence data havebeen uploaded and stored in NCBI database (accession num- ber PRJNA838696). Information needed was downloaded from NCBI database (Zhang., 2017b). The Hisat2 wasapplied to map clean reads to reference genome (Kim., 2019). The featureCounts software was employed to con- struct the counts matrix. The DESeq2 R package was used to compare the differences between two groups, which re- cognized differentially expressed genes (DEGs) (Love., 2014). |log2(Fold change)|>2 and adjusted-value<0.05were set as significant level.

2.4 Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Analysis

GO and KEGG enrichment analyses were performed us- ing Goatools (https://github.com/tanghaibao/Goatools) andKOBAS (http://kobas.cbi.pku.edu.cn/home.do) based on the whole-transcriptome background to investigate the poten- tial biological function of these DEGs. Bonferroni correct- ed-value<0.05 was regarded as significant level, which satisfied terms and pathways were defined as significant- ly enriched in DEGs. The results were visualized by ggplot2 R package.

2.5 Validation Accuracy by RT-qPCR

The total RNA samples were reversed transcription, then diluted and used for RT-qPCR. Specific primers of ten DEGs were designed and their sequences were listed in Table 1. The RT-qPCR experiments were performed on detection sys- tem. Detailed steps were referred to previous research (Mei., 2022). The amplification efficiencies of primer pairswere ranged from 97% to 104%. The 2?ΔΔCt(Livak and Sch- mittgen, 2001) method was used to determine the expres- sion levels of selected DEGs, while cytochrome b() was employed as reference gene. One-way ANOVAs with posthoc Tukey’s tests in SPSS v21.0 (IBM, Shanghai, Chi-na) was used for statistical analyses and<0.05 was set as significant level.

3 Results

3.1 Transcriptomic Information

Eighteen cDNA libraries of sea cucumber at F1, F3 and F7 were constructed to evaluate the effects of different feed- ing rations on transcriptional signatures (Table 2). Clean data were obtained from 117.16 Gb raw data. The Q20 (%) ranged from 97.55% to 98.01%, while Q30 (%) ranged from 93.10% to 94.24%, indicating high quality of sequencing results. The mapped rate of reads to reference genome ofin this study was around 52.79%–75.85%.

Table 1 Information of primers used for RT-qPCR

Notes: F represented forward primer; R represented reverse primer., putative regucalcin;, isocitrate dehydrogenase;, putative acetyl-coenzyme A synthetase 2-like, mitochondrial;, putative sorbitol dehydrogenase isoform X2;, hypothetical oxidative phosphorylation protein NADH dehydrogenase [ubiquinone] iron-sulfur protein 6, mitochondrial;, pyruvate dehydrogenase;, putative pyruvate kinase PKM;, putative ATP-citrate synthase;, putative phosphoenolpyruvate carboxykinase, cytosolic; and, putative malate dehydrogenase, cytoplasmic isoform X2.

Table 2 Basic characteristics of reads in eighteen libraries

3.2 Transcriptional Signature of Respiratory Tree in Different Feeding Rations

3.2.1 Identification of DEGs

Summary of 28178 genes were identified and annotat- ed from the libraries. DEGs between F1S. F3S, F1S. F7S, and F3S. F7S were 1093699, and 1326, respective-ly. Among these DEGs, 759 (334), 254 (445) and 334 (992) genes were up (down)-regulated in respiratory tree of F1S. F3S, F1S. F7S and F3S. F7S, respectively (Table 3). In addition, 12 common DEGs were identified in respi- ratory tree (Fig.1A).

3.2.2 GO and KEGG analyses

Top 20 enrichment categories of DEGs in respiratory tree between F1S. F3S, F1S. F7S and F3S. F7S were displayed (Fig.2A). DEGs in biological process, cellular process, metabolic process and biological regulation were mostly enriched. In molecular function, DEGs were signi- ficantly enriched in binding and catalytic activity, while they were enriched in cell part, organelle and membrane in cellular component.

Table 3 Statistical analyses of differentially expressed genes (DEGs) in respiratory tree and body wall at different feeding rations

Note: The ration levels included F1, F3 and F7.

Results of KEGG pathway enrichments in respiratory tree of F1S. F3S, F1S. F7S and F3S. F7S are shown in Fig.3. The DEGs were enriched in KEGG pathways in-cluding categories of signal transduction (77), signaling mo-lecules and interaction (45), digestive system (61), endocrinesystem (53), lipid metabolism (35), glycan biosynthesis and metabolism (29) and carbohydrate metabolism (24) (Fig.3A). Meanwhile, signal transduction (55), immune system (32), endocrine system (27), translation (17), lipid metabolism (16) and amino acid metabolism (13) were specifically en- riched in respiratory tree of F1S. F7S (Fig.3B). In res- piratory tree of F3S. F7S, DEGs were enriched in path- ways involved in respiration-related metabolism, such as signal transduction (86), signaling molecules and interaction (64), endocrine system (73), digestive system (61), im- mune system (49), glycan biosynthesis and metabolism (30) and lipid metabolism (27) (Fig.3C).

Top 20 generally enriched KEGG pathways in respira- tory tree were displayed in Fig.4A. In F1S. F7S, these KEGG pathways were associated with digestive system, signal transduction and metabolism, including ‘vitamin di- gestion and absorption (map04977)’, ‘salivary secretion (map04970)’, ‘protein digestion and absorption (map04974)’,‘ECM-receptor interaction (map04512)’, ‘TNF signaling pathway (map04668)’, ‘various types of N-glycan biosyn- thesis (map00513)’ and ‘steroid hormone biosynthesis (map- 00140)’. In F1S. F7S, pathways related to translation, im-munomodulation, signal transduction and metabolism were significantly enriched. The enriched KEGG pathways in- cluded ‘ribosome biogenesis in eukaryotes (map03008)’,‘NOD-like receptor signaling pathway (map04621)’, ‘RIG-I-like receptor signaling pathway (map04622)’, ‘ErbB sig- naling pathway (map04012)’, ‘PI3K-Akt signaling path- way (map04151)’, ‘NF-kappa B signaling pathway (map- 04064)’, ‘pyruvate metabolism (map00620)’, ‘propanoate metabolism (map00640)’ and ‘cysteine and methionine me- tabolism (map00270)’. In F3S. F7S, DEGs were enrich-ed in signal transduction, immunomodulation, digestive sys- tem and metabolism. The enriched KEGG pathways were ‘ECM-receptor interaction (map04512)’, ‘cell adhesion mo-lecules (map04514)’, ‘hematopoietic cell lineage (map- 04640)’, ‘complement and coagulation cascades (map0610)’,‘salivary secretion (map04970)’, ‘vitamin digestion and ab-sorption (map0977)’ and ‘various types of N-glycan bio- synthesis (map00513)’.

3.3 Transcriptional Signature of Body Wall in Different Feeding Rations

3.3.1 Identification of DEGs

Results showed 3373, 2938 and 2040 genes were diffe- rentially expressed between groups F1B. F3B, F1B. F7B, and F3B. F7B, respectively, with 2070, 1601, and 896 up-regulated genes and 1303, 1337, and 1144 down- regulated genes (Table 3). Totally 149 common DEGs were identified in body wall at the feeding rations of F1, F3, and F7 (Fig.1B).

3.3.2 GO and KEGG analyses

Top 20 GO terms of body wall in MF, CC, and BP are shown in Fig.2B. In BP, DEGs were enriched in cellular process, metabolic process and biological regulation. DEGs in MF were classified as catalytic activity and binding. In addition, DEGs enriched in CC included cell part, mem- brane, and organelle.

Results of KEGG pathway enrichments in body wall of F1B. F3B, F1B. F7B and F3B. F7B are shown in Fig.5. The results showed that signal transduction (275), endocrine system (179), digestive system (130), lipid me- tabolism (93) and translation (81) were enriched (Fig.5A). In F1B. F7B, signal transduction (223), endocrine sys- tem (144), digestive system (115), transport and catabolism (104), immune system (89) and lipid metabolism (83) were significantly enriched (Fig.5B). In F3B. F7B, the enrich- ed KEGG pathways included signal transduction (117), en- docrine system (82), digestive system (69), immune system (56), lipid metabolism (58), glycan biosynthesis and meta- bolism (42) and carbohydrate metabolism (41) (Fig.5C).

Fig.2 GO classifications analysis of DEGs (A) Distributions of DEGs in respiratory tree at different feeding rations; (B) Distributions of DEGs in body wall at different feeding rations; (C) Comparisons of DEGs at the same feeding ration between respiratory tree and body wall.

Fig.3 Histogram presentation of KEGG pathway classification in respiratory tree at different feeding rations.

Fig.4 KEGG pathways enrichment analysis of DEGs (A) Enriched pathways of DEGs in the respiratory tree at different feeding rations; (B) Enriched pathways of DEGs in the body wall at different feeding rations; (C) Enriched pathways of DEGs by comparing at the same feeding ration between respiratory trees and body walls.

Fig.5 Histogram presentation of KEGG pathway classification in body wall at different feeding rations.

Top 20 enriched KEGG pathways in body wall are dis- played in Fig.4B. In F1B. F3B, these KEGG pathways were involved in translation, metabolism, digestive system and endocrine system, including ‘ribosome (map03010)’, ‘sphingolipid metabolism (map00600)’, ‘lysosome (map- 04142)’, ‘vitamin digestion and absorption (map04977)’, ‘salivary secretion (map04970)’, ‘insulin signaling pathway(map04910)’ and ‘thyroid hormone synthesis (map04918)’. In F1B. F7B, pathways were classified into translation, metabolism, digestive system, endocrine system and signal transduction were significantly enriched. The enriched KEGG pathways included ‘ribosome (map03010)’, ‘vari- ous types of N-glycan biosynthesis (map00513)’, ‘sphingo- lipid metabolism (map00600)’, ‘vitamin digestion and ab- sorption (map04977)’, ‘parathyroid hormone synthesis, se-cretion and action (map04928)’, ‘thyroid hormone synthe- sis (map04918)’, ‘PI3K-Akt signaling pathway (map04151)’and ‘Wnt signaling pathway (map04310)’. In F3B. F7B, DEGs were enriched in signal transduction, metabolism and immunomodulation. The enriched KEGG pathways were ‘ECM-receptor interaction (map04512)’, ‘various types of N-glycan biosynthesis (map00513)’, ‘pyruvate metabo- lism (map00620)’, ‘glycolysis/gluconeogenesis (map00010)’,‘arachidonic acid metabolism (map00590)’, ‘sphingolipid metabolism (map00600)’, ‘glycerophospholipid metabolism (map00564)’, ‘synthesis and degradation of ketone bodies (map00072)’, ‘histidine metabolism (map00340)’ and ‘cy- tosolic DNA-sensing pathway (map04623)’.

3.4 Transcriptional Signature Between Respiratory Tree and Body Wall at Same Feeding Rations

3.4.1 Identification of DEGs

A total of 4351, 1135 and 5137 DEGs were identified be- tween respiratory tree and body wall in F1, F3 and F7. The results showed 1713, 319, and 2535 genes were up-regu- lated, while 2638, 816, and 2602 genes were down-regu- lated in F1S. F1B, F3S. F3B and F7S. F7B, respectively (Table 3). Furthermore, DEGs of 572 genes were observed between respiratory tree and body wall at same feeding rations (Fig.1C).

3.4.2 GO and KEGG analysis

The DEGs were enriched in BP of cellular process, me- tabolic process and biological regulation in F1S. F1B, F3S. F3B and F7S. F7B. Meanwhile, DEGs were en- riched in MF of catalytic activity and binding, and CC of cell part, membrane and organelle (Fig.2C).

In addition, the DEGs were functionally enriched betweenrespiratory tree and body wall in F1, F3 and F7 (Fig.6). For F1S. F1B, most of DEGs were enriched in signal trans- duction (344), endocrine system (218), digestive system (190), transport and catabolism (174), immune system (164), lipid metabolism (114), glycan biosynthesis and metabo- lism (98) (Fig.6A). In group of F3S. F3B, the significant- ly changed pathways were associated with signal transduc- tion (71), transport and catabolism (45), digestive system (46), endocrine system (43), glycan biosynthesis and me- tabolism (27) and lipid metabolism (26) (Fig.6B). More- over, the categories of signal transduction (400), endocrine system (264), digestive system (191), immune system (160), lipid metabolism (132), glycan biosynthesis and metabo- lism (123) and amino acid metabolism (96) were signifi- cantly enriched in F7S. F7B (Fig.6C).

Top 20 generally enriched KEGG pathways between two tissues at the same feeding rations were shown in Fig.4C. In F1S. F1B, these KEGG pathways were enriched in translation, digestive system, immunomodulation and me- tabolism, including ‘ribosome (map03010)’, ‘salivary se- cretion (map04970)’, ‘protein digestion and absorption (map04974)’, ‘complement and coagulation cascades (map-04610)’, ‘hematopoietic cell lineage (map04640)’ and ‘va- rious types of N-glycan biosynthesis (map00513)’. In F3S. F3B, pathways related to metabolism, digestive system and immunomodulation were significantly enriched. The enriched KEGG pathways included‘various types of N- glycan biosynthesis (map00513)’, ‘peroxisome (map04146)’,‘salivary secretion (map04970)’, ‘bile secretion (map04976)’,‘complement and coagulation cascades (map04610)’, ‘he- matopoietic cell lineage (map04640)’ and ‘NOD-like re- ceptor signaling pathway (map04621)’. In F7S. F7B, DEGs were enriched in immunomodulation, signal trans- duction, digestive system and metabolism. The enriched KEGG pathways were ‘complement and coagulation cas- cades (map04610)’, ‘hematopoietic cell lineage (map- 04640)’, ‘cell adhesion molecules (map04514)’, ‘ECM-re- ceptor interaction (map04512)’, ‘PI3K-Akt signaling path- way (map04151)’, ‘salivary secretion (map04970)’, ‘va- rious types of N-glycan biosynthesis (map00513)’ and ‘gly- cine, serine and threonine metabolism (map00260)’.

3.5 Validation Accuracy

Ten DEGs were randomly selected for validating accu- racy of RNA-Seq results (Fig.7). The results agreed with RNA-Seq data and the coefficient of determination2was estimated as 0.9447.

4 Discussion

Understanding the potential molecular mechanism in feeding ration on respiratory metabolism is very valuable, not only for understanding the physiological process and ecological functions, but also for the sustainable industrial development of sea cucumbers. Different feeding rations have been shown to regulate metabolism of aquatic animals, while limited studies were focused on sea cucumbers. In this study, we determined transcriptional signature of res- piratory tree and body wall of sea cucumber at different feeding rations. We showed integrated information on po- tential molecular mechanism involved in respiratory me- tabolism.

4.1 Common DEGs of Respiratory Tree and Body Wall

As a unique functional organ for sea cucumber, respira- tory tree has been suggested to act as main site for gas ex- change (Eisapour., 2022).andwere common DEGs detected in three comparison groups of re- spiratory trees.is a member of calcium-activated chloride channel regulator family, which serves as key role in respiratory tract epithelium in mammals and participates in innate immune responses (Liu and Shi, 2019). Previous studies onshowed that stressful re- sponses were triggered by decreased salinity, leading todown-regulation ofand an increased mucus in gill,which prevents normal respiration in the shrimp (Wen., 2021). This might explain the fact that F1 and F7 feeding rations were not conducive to respiratory metabolism in sea cucumber.is a fibrillar collagen gene that is criti- cal for the formation of extracellular matrix and participates in protein digestion and absorption (Zhang., 2018a). Previous studies were consistent with our present results, showingupregulation is more favorable to respi- ratory metabolism (Fett., 2022).

Fig.6 Histogram presentation of KEGG pathway classification in comparisons of DEGs at the same feeding ration between respiratory tree and body wall.

Fig.7 Validation of the RNA-Seq using qPCR experiment. Gene expression patterns of selected genes were determined and presented as log2(Fold change) and CYTB was used as the internal reference gene.

Because of dual respiratory characteristics and direct con- tact with the water environment, body wall of sea cucum- ber may also undertake part of the respiratory function (Wang and Tian, 2012). Therefore, several common DEGswere analyzed in different feeding rations in body wall. Ri- bosomal protein L38 () is up-regulated in inflamma-tory cells, leading to increased inflammatory cytokine se-cretion and extracellular matrix degradation (Shi., 2022). The metalloprotease gene () plays an important role in extracellular matrix turnover (Wang., 2019),and its expression is consistent with, suggesting that a fibronectin hydrolysis process may be activated in body wall of F1 or F7 group. Txk tyrosine kinase () isinvolved in inflammation-related signal transduction path-ways. An elevatedexpression may cause oxidative stress damage and mitochondrial dysfunction (Xu and Wu, 2021). Our results showedexpressions in body wall were significantly higher in F1 and F7 groups than in F3, indicating that unsuitable feeding rations were detrimental to the normal respiratory metabolism of sea cucumbers.

What’s more, very long-chain fatty acids protein 6 ()and excitatory amino acid transporter 3 () were dif-ferential genes common to the respiratory tree and the body wall. The protein expressed by the former is involved in energy balance and maintaining the metabolic balance of fatty acids (Li., 2020). The latter is a gene for amino acid transport, and its protein activity represents the abilityto transport amino acids (Liu., 2019). Both of them may provide energy or energy substances for animal respi- ratory metabolism. These two genes were down-regulated in the body wall at the same feeding level, indicating that their metabolic activities were weakened, revealing the tis- sue-specific expression patterns in response to different feeding levels.

4.2 Significant Enrichment of KEGG Pathways in Respiratory Tree and Body Wall

Most of DEGs were highly enriched in salivary secretion and ECM-receptor interaction pathways in respiratory tree. In this study, the salivary secretion pathway was signifi- cantly enriched in respiratory tree under F1S. F3S and F3S. F7S comparison groups. The salivary secretion path- way promoted the digestion of different nutrients, which plays an important role in digestive function. Previous stud- ies confirmed salivary secretion was regulated by neuro- endocrine in response to external stimuli, and feed supply was considered to be one of the primary external stimulus sources (Cappai., 2021). Our results indicated that DEGs of F3S enriched in salivary secretion pathway were significantly up-regulated when compared with other groups. Theis a secretory glycoprotein gene that is wide- ly expressed in all tissues, including mucosal epithelium of the respiratory and digestive systems. Decreased expressionofmight cause respiratory impairment and increase disease susceptibility (Jia., 2021). The down-regula- tion expression ofrespiratory tree function may be inhibited.is acGMP-dependent protein kinase gene, and its expressionproduct is involved in signal transduction processes during digestion and metabolism (Hou., 2020). Theexpression in respiratory tree of F3 was significantly high- er than those in other groups, indicating that high expres- sion might have prevented apoptosis and oxidative damage and promoted cell proliferation and metabolism (Shi., 2019).

DGEs showed tissue-specific enrichment of KEGG path- ways between respiratory tree and body wall. In F1B. F7B and F3B. F7B comparison groups of body wall, va- rious types of N-glycan biosynthesis pathways were signi- ficantly enriched. Differential expression of this pathway in F7 was higher than those in F1 and F3, but much lower than those of respiratory trees.is an enzyme cata- lyzes fucose transferation. A previous study indicated thatis involved in hypoxia regulation, and high expres- sion is generally induced by hypoxia (Ruan., 2021). These results showed respiratory metabolism of sea cucum- ber was inhibited under high feeding ration (F7). In addi- tion, under F1B. F3B and F1B. F7B comparison groups, ribosome and sphingolipid metabolism pathways were sig-nificantly enriched. In the body wall of different feeding ra- tions, DEGs enriched in ribosome pathway in F1 and F3 were expressed significantly higher than those in F7, and DEGs enriched in sphingolipid metabolism pathway in F1 and F7 were expressed with a lower level than those in F3. Our results revealed that the body wall of F1 and F3 had activated the translation process, while lipid metabolisms in F1 and F7 were inhibited. Previous studies showed that lipid digestion and metabolism are suppressed due to high dietary levels, which inhibit mitochondrial oxidation func-tion and finally affect respiratory metabolism (Guo., 2019; Sun., 2020).

The significantly enriched KEGG pathways between two tissues at same feeding ration were specific. In the F1 group, DEGs were significantly enriched in ribosome and salivary secretion pathways involved in transcription and digestion. In the present study, DEGs of KEGG pathways in bodywall showed higher expression levels than those in respira- tory trees, suggesting that body wall might play a more do-minant role in respiratory metabolism in low feeding ration. The results might be caused by low appetite of animals at F1, as low appetite can lead to lower respiratory metabolism (Lei., 2005; Xia., 2015). Furthermore, immunity and transduction-related pathways were significantly enrich-ed between two tissues in F7 group, such as complementand coagulation cascades, PI3K-Akt signaling pathway and ECM-receptor interaction. These results showed the high feeding ration inhibited signaling transduction but activated immune-related pathways in body wall. In the present study, F7 was over-feeding, which greatly limited the feed intake of sea cucumber (Wang., 2016). Previous studies show- ed it is a general adaptation mechanism for aquatic animals to preserve more energy under starvation state (Yu., 2019). Therefore, the low respiratory metabolism was ob- served in the F7 group. It has also been shown that over- feeding produces greater water pollution (Tong., 2020), leading to increased disease susceptibility in aquatic ani- mals. The immune-related pathways were activated in body wall to prevent oxidative damage resulting from high feed- ing ration (Luo., 2021).

5 Conclusions

In this study, transcriptional analyses were used to study the potential molecular mechanisms of respiratory meta- bolism in sea cucumber at different feeding rations.Feed- ing ration at 3% of total body weight was suggested to be optimal for sea cucumber, a lower and/or higher feeding ra- tion negatively affects respiratory metabolic process. In ad- dition, our results showed salivary secretion and ECM-re- ceptor interaction pathways in respiratory tree, and various types of N-glycan biosynthesis, ribosome and sphingolipid metabolism pathways in body wall might play important roles in regulating sea cucumber respiratory metabolism in response to different feeding rations.Our study provides deep insight into the molecular basis of respiratory meta- bolism in invertebrates, and is valuable for understanding physiological divergences in metabolic processes in res- ponse to different feeding rations.

Acknowledgement

This work was supported by the National Natural Science Foundation of China (No. 31672657).

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