Transcriptome analysis of perforated small cocoon from Bombyx mori mutants

Abstract

The metabolism of substances such as amino acids and carbohydrates plays a crucial role in the growth and development of silkworms. Analyzing the differential expression of key genes associated with these metabolic processes can help elucidate the molecular mechanisms underlying abnormal development in silkworm mutants. This study conducted and compared transcriptome analyses of individuals from the silkworm mutant perforated small cocoon(psc) and the wild-type XueSong KD(XSKD) at the third-instar larval stage. A total of 716 differentially expressed genes were identified, including 354 upregulated genes and 362 downregulated genes. Functional annotation based on the KEGG database indicates that these differentially expressed genes were mainly enriched in metabolic pathways related to amino acids, carbohydrates, and lipids, as well as pathways involving neuroactive ligand-receptor interactions. Some key enzyme genes involved in substance metabolism and important neuroreceptor genes played a crucial role in the formation of the psc. In addition, by selecting some differentially expressed genes for qRT-PCR verification, the results indicated that the identification of differentially expressed genes were reliable. This study utilized RNA sequencing technology to screen for differentially expressed genes between the psc mutant and the XSKD. These findings provide important insights into the molecular mechanisms underlying the formation of the abnormal phenotypes in the psc mutant, and they also have certain guiding significance for the breeding of high-quality large cocoon silkworm varieties.

Bombyx mori is a significant insect species in the production of cocoon silk. Throughout its growth and development, essential substances, including amino acids, carbohydrates, fats, and nucleotides, are metabolized in a synergistic manner under the precise regulation of various molecular biological mechanisms, such as gene expression and signal transduction, thereby providing the necessary material and energy foundation for the life activities of silkworms^1,2. The metabolic pathways of these essential substances are crucial to the growth and development of silkworms. If the expression of some key genes in the pathway is abnormal, metabolic disorders will be caused, which will affect the growth and development of individual silkworm, and eventually lead to changes in cocoon size and yield. Therefore, it is of great significance to analyze the regulation mechanism of related factors of silkworm growth and development for cocoon silk production³. For example, lipid metabolism is a key pathway for energy production, storage, and signaling regulation in silkworms. Abnormal expression of acetyl-CoA carboxylase, fatty acyl-CoA reductase and other enzyme genes will cause fatty acid metabolism disorders, interfere with the development process of silkworms, and lead to blocked silk protein synthesis and decreased reproductive ability⁴. However, the knockout of LAT1 (SLC7A5) gene leads to the obstruction of leucine signal transmission through TORC1 pathway, resulting in the arrest of larva development and the reduction of silk protein synthesis, indicating that amino acid metabolism pathway can directly affect the growth and development of silkworm and the amount of silk production⁵. At the same time, the growth and development of Bombyx mori are also regulated by various hormones^6,7. Among them, juvenile hormone and molt hormone regulate the growth and development of silkworm and molt metamorphosis respectively. In the larval stage, juvenile hormone can maintain the larval state and promote the growth of larval size by inhibiting the activity of corpus allatum. Ecdysone initiates the ecdysone process and induces metamorphosis by regulating the expression of ecdyst-related genes. The main form of molting hormone is 20-hydroxyecdysone (20E), and its precursor is synthesized in the prothoracic gland. Following synthesis, these precursors are released into the hemolymph and transported to peripheral tissues, where they are enzymatically converted into the active form 20E. Once activated, 20E binds to its receptor and regulates gene expression associated with molting and other developmental processes. Research shows that cytochrome P450 enzymes are involved in regulating the metabolic pathways of these hormones^8–10. In addition, external factors such as temperature, humidity, and whether the mulberry leaves consumed are contaminated with trace pesticides or other harmful substances can significantly affect the growth and development of silkworms. For instance, high-temperature stress can disrupt the activity of certain digestive enzymes and impede nutrient transport in silkworms, leading to reduced digestion and nutrient absorption, which adversely affects their overall growth and development¹¹.

During the growth and development of silkworms, numerous physiological behaviors demonstrate a high degree of programmability. For instance, during the larval stage, they typically molt after a specific period of development to transition into the next instar. This process continues until the fifth instar is complete, after which the silkworms spin silk to form a cocoon of a defined shape, followed by pupation, ultimately emerging as moths. Although these behaviors are regulated by environmental factors, hormones, and gene expression, the primary regulatory hub is located within the neuroactive ligand-receptor interaction pathway. This pathway is primarily responsible for transmitting signals in the nervous system, coordinating activities between tissues and organs, and plays a decisive role in morphogenesis, metamorphosis, and the development of behavioral patterns. For example, the NGR-A16 gene encodes a neuropeptide receptor that belongs to the G Protein-Coupled Receptors (GPCR) family in insects, which plays an important role in regulating insect foraging behavior, motor ability and stress response^12,13. The Hippo signaling pathway restricts cell proliferation in animal tissues by inhibiting YAP and transcriptional activators with PDZ domains. This mechanism controls the organ size of the organism, thereby regulating overall body size^14,15. Through ligand diversity, receptor specificity, and complex signaling networks, the neuroactive ligand-receptor interaction pathway achieves precise regulation of all aspects of the organism. If the expression of a receptor gene in this pathway is abnormal, the growth and development of the organism will be significantly impaired. For example, if the expression of nuclear receptor gene BmHR38 is inhibited by genome editing CRISPR / Cas9 method in the silkworm pupal stage, the development of the pupal stage will be abnormal and the emergence will fail¹⁶.

The perforated cocoon is also known as the piercing cocoon and the thin head cocoon. The thickness of the cocoon layer is significantly thinner at both ends or at one end compared to other parts. Due to significant deficiencies in its surface, it can hardly be used in silk reeling¹⁷. Studies have shown that the generation of perforated cocoons is closely related to changes in environmental factors such as temperature, humidity, and airflow in the cocooning environment¹⁸. In silkworm breeding, obtaining individuals that are large, high-yielding, and produce high-quality silk is an important goal. If the individuals are small, it can severely impact cocoon yield. Additionally, the presence of small holes on the cocoon can cause silk breakage during reeling, resulting in shorter silk lengths and lower quality grades. Individuals exhibiting these phenotypes are typically eliminated during silkworm variety selection, which is why there are relatively few reports on related silkworm mutants.

The perforated small cocoon mutant of the silkworm was discovered in the silkworm wild-type strain XueSong KD. After more than seven generations of breeding and investigation, it was confirmed that the occurrence of this perforated small cocoon was not caused by environmental factors, but was due to a gene mutation within the silkworm’s body, and it has stable heritability. During its larval stage, the body size of psc was smaller than that of the wild-type XSKD at the same period. The shape of the cocoons and the total cocoon quantity were also less than those of XSKD. Moreover, we found that from the start of feeding in the third instar, psc fed on mulberry very slowly, showing much lower developmental levels compared to the wild type at the same growth stage. The subsequent stages showed fewer significant differences than at the initial third instar. Currently, there remains a lack of in-depth analysis regarding which gene expressions and signaling pathways have undergone systematic alterations during the critical early developmental stages in such a stably inherited perforated small cocoon phenotype, thereby leading to restricted body size development and defects in the cocoon layer. To elucidate the molecular basis of the psc mutant phenotype, this study performs transcriptome sequencing and comparative analysis using whole larvae of psc and the wild-type XSKD at the beginning of the third instar. The work aims to systematically identify differentially expressed genes that emerge at this early developmental stage and to explore key signaling pathways potentially involved in regulating body size growth and cocoon shell development in the silkworm. This work represents the first transcriptome-wide investigation to reveal the molecular signature of the perforated small cocoon mutant at a critical developmental stage, providing a key theoretical foundation for breeding high-quality, large-cocoon silkworm varieties.

Materials and methods

Silkworm rearing and sample Preparation

The wild-type strain XSKD and the mutant psc were all preserved and provided by the Sericultural Scientific Research Center, Chinese Academy of Agricultural Sciences. All varieties were raised in the same environment: fresh mulberry leaves were selected, the temperature was 25 ± 1℃, the relative humidity was 80% ± 5%, and the light and darkness alternated for 12 h each. The feeding time of mulberry in each instar was recorded. The feeding rate and development process of psc mutants were similar to those of the wild-type XSKD at the first and second ages, except that the psc individual was slightly smaller. However, the feeding rate of psc slowed down from the third instar, and the growth rate of individual size obviously lagged behind that of the wild-type. Similarly, the growth status of the subsequent fourth and fifth instars was consistent. Therefore, transcriptome sequencing and qRT‑PCR were performed on third-instar larvae of the mutant psc and wild-type XSKD silkworms. For each strain, three biological replicates were established, with each replicate consisting of a single individual larva (no pooling). The samples were designated as follows: wild type (XSKD‑1, XSKD‑2, XSKD‑3) and mutant (psc‑1, psc‑2, psc‑3). Then, on the 7th day of the 5th instar, 30 moths were randomly selected from each moth population to investigate body weight, body length, and body width (measuring the third abdominal segment). Three days after pupation, cocoon length, width, total cocoon amount, cocoon layer amount and cocoon layer rate (cocoon layer amount/total cocoon quantity × 100%) were measured, and all data were statistically analyzed and tested accordingly.

RNA extraction and sequencing

Total RNA was isolated and purified using TRIzol (Invitrogen, CA, USA) reagent following the manufacturer’s instructions. The concentration and purity of RNA were then measured with a NanoDrop ND-1000 ultraviolet spectrophotometer (NanoDrop, Wilmington, DE, USA). Simultaneously, 1% agarose gel electrophoresis was performed to detect RNA degradation or contamination, followed by integrity evaluation using a Bioanalyzer 2100 (Agilent, CA, USA). After the quality of RNA was confirmed, subsequent sequencing was performed.

Library construction and transcriptome sequencing were performed by Hangzhou Lianchuan Biotechnology Co., Ltd. The polyadenylated mRNA was specifically captured by two rounds of purification using Oligo(dT) beads. The captured mRNA was fragmented using the NEBNext^® Magnesium RNA Fragmentation Module (USA) under high temperature conditions at 94℃ for 5–7 min. cDNA was synthesized from the fragmented RNA by means of Invitrogen SuperScript™ II Reverse Transcriptase (CA, USA). E. coli DNA polymerase I (NEB, USA) and RNase H (NEB, USA) were then used to perform double-strand synthesis, converting these DNA-RNA complex double strands into DNA double strands. At the same time, dUTP Solution (Thermo Fisher, CA, USA) was added to the double-stranded DNA, preparing it for blunt-end ligation. Then an A base was added to each end of it, so that it can be connected with the terminal with T base joints, and the fragment size was screened and purified by magnetic beads. The two chains were digested with UDG enzyme (NEB, MA, US) and then PCR was conducted, starting with pre-denaturation at 95℃ for 3 min, denatured at 98℃ for a 8 cycles of 15 s each, annealed at 60℃ for 15 s, extended at 72℃ for 30 s, and finally extended at 72℃ for 5 min to form a library with fragment size of 300 bp ± 50 bp. Finally, they were sequenced using the illumina Novaseq™ 6000 sequencer (LC Bio Technology CO.,Ltd. Hangzhou, China) in a PE150 sequencing mode, according to the standard procedure.

Sequencing data analysis

The original data is in fastq format, and fastp¹⁹ software v 0.18.0 is used for quality control of the original data, including (1) removing reads containing adapters; (2) removing reads containing more than 10% N (N means that base information cannot be determined); (3) removing low-quality reads (the number of bases with a mass value of Q ≤ 20 accounts for more than 50% of the entire read) to obtain pure reads. HISAT2.2.4²⁰ software was used to clean reads, and the silkworm genome and genetic model file were downloaded from the NCBI reference (https://www.ncbi.nlm.nih.gov/). The gene or transcript was assembled using StringTie v1.3.1 software, and the FPKM (expected number of kilobase fragments per million base pairs of sequenced transcript sequence fragments) of each gene was calculated for expression level analysis. DESeq2 v1.16.1 software was used to analyze differential gene expression among samples, and candidate genes were selected by referring to the differential gene detection method of Audic et al²¹. Multiple hypothesis testing adjustments were made to the tested P-values, and then the false discovery rate (padj) ≤ 0.05^22,23,24 was taken as the threshold standard for screening Differentially expressed genes (DEG), thus screening out related genes²⁴. Screening criteria were q < 0.05 and | log2 (Foldchange) |≥ 1. Finally, DAVID software (https://david.ncifcrf.gov/) was used for GO functional gene enrichment and KEGG pathway enrichment analysis.

qRT-PCR verification of differentially expressed genes

In order to verify the reliability of the data, 16 differential genes were randomly selected, including B. mori actin 3 (A3, GenBank ID: NM_001126254), as internal reference genes. Gene sequences were obtained from the NCBI database (https://www.ncbi.nlm.nih.gov/) using Primer Premier 5.0 software to design primers (Table 1), which were sent to Shanghai Sangon Biological synthesis. Whole silkworms from the same batch of XSKD and psc were selected as the template for real-time quantitative fluorescent PCR (qRT-PCR) verification. Total RNA was extracted using the RNAiso Plus (TaKaRa, China) method, treated with DNase (TaKaRa, China) and then using the M-MLV reverse transcriptase (RNase H-) kit (TaKaRa, China). The cDNA was obtained and diluted to 100 ng/µL as a template for qRT-PCR. The reaction system had a volume of 20 µL, including 0.5 µL of specific primer (10 µM), 1 µL of cDNA, 10 µL of SYBR^® Premix Ex Taq™ (TliRNaseH Plus) (2×), and ddH₂O was added to bring the total volume to 20 µL before being centrifuged and reacted on a Light Cycler^® 96 quantitative PCR apparatus. The reaction conditions were as follows: predenaturation at 95℃ for 30 s, denaturation at 95℃ for 5 s, annealing at 60℃ for 30 s, extension at 72℃ for 10 s, and a total of 40 cycles were performed. The melting curve was generated after the PCR reaction. The data were analyzed by Light Cycle^®96 software and the relative expression levels of each gene were calculated by the 2^−ΔΔCt method²⁵.

Table 1.

qRT-PCR primers of differentially expressed genes.

Gene ID	Primer sequence
LOC101740055	F: ACTGACGATCCTACAACGGC
	R: TGTCGAACGAAGGTACAGCC
LOC101742829	F: AACTCCAACAGAGCCAGAGC
	R: GCGTCTTTAATCGGCGTGTC
LOC101740487	F: GACACCAGCGGAAATAATAGCAG
	R: GCCGTTCTTGTGGGCGTATA
LOC119629305	F: CCATGCTACTACAGGTCAACGAAC
	R: TTATCTTGGACATTGGACTCTTGC
LOC101743790	F: GAAGTACGATGACCCCGACG
	R: GGTGCTGTTGTAAGATAGAGTGCC
LOC101740086	F: TCGGACGGTGCGAAGAAGA
	R: GCGATAGATGATGTAGGGCTGTTTT
CPR15	F: TAACGGTGTCCAGTCCCAAGG
	R: TCACGGGCGTTCTGTTCCA
LOC692769	F: TCAATATGTGGCTTGTGGCG
	R: AGCTAGGGGCATTCAGGTCG
LOC101741492	F: ATAGTGGCGGTGGAGGATCT
	R: GGAAGTTTACGTGCATGGCG
LOC101741338	F: GCTGGCGGCAAGTTTAAGAG
	R: AAATCGGCTATGGTTTTCGGT
LOC101741137	F: TCTGGCTATCAGTATCTACGGTCAA
	R: CGTCCAGTGGCGGTATTAGG
LOC692390	F: TGCGACCCTGCCAATAAAGA
	R: CCGAAAGCCCAACAACTGC
Slp	F: TAGGAACGGCTACGGATGGTG
	R: GGCGGTTGTAGATGTAGAACAGGAC
LOC732939	F: GTGGTACTTGGGATGCTTTTGG
	R: TGGACTTGTAGTCGCTCCTTGTG

Results

Phenotypic properties of Psc mutants

The psc mutant (after more than 7 generations of breeding, reproduction, and stabilization) was reared and observed in a standard temperature and humidity environment alongside the wild-type silkworm strain XSKD. At the first and second instar stages, the psc mutant showed no significant difference in developmental processes from the wild type XSKD, only that it had a slightly smaller body size. However, since the third instar, the feeding of psc on mulberry was obviously slow and intermittent, and the growth rate and body size of psc individuals significantly lagged behind that of the wild type XSKD during the same period; the growth status of fourth and fifth instars was also similar. In addition, the mulberry feeding time of psc mutant at the third instar was 16 h longer than that of XSKD, and there was little difference between the mulberry feeding time of other instars and XSKD (Table 2). Compared with XSKD, the larvae of psc were thinner, shorter, and had smaller body weights (Fig. 1A; Table 3). The cocoon of XSKD was normal and large. The psc cocoon was a small cocoon with small holes at either end or one end, with the other ends without holes being thinner, resulting in a perforated cocoon (Fig. 1B). The total amount of cocoons produced by psc was less than half of that of XSKD, with the cocoon layer amount being about one-third of XSKD, and the cocoon layer rate being approximately 70% of XSKD (Table 4; Fig. 2). The above phenomena indicated that psc had mutated into a small, thin silkworm with a small cocoon, which was perforated.

Table 2.

The feeding process of mulberry larvae at different instars.

Strain	First instar	Second instar	Third instar	Forth instar	Fifth instar
XSKD	3:00	2:00	2:00	3:00	7:00
psc	3:00	2:00	2:16	3:00	7:00

Fig. 1.

Individual phenotypes of larvae and cocoons of XSKD and psc. (A)Phenotypes of 5th instar 7-day-old larvae: normal wild-type XSKD (left) and psc (right); (B) Normal cocoon (upper) and perforated small cocoon (lower).

Table 3.

XSKD and individual phenotype of Psc larvae.

Strain	Body length (mm)	Body width (mm)	Body weight (g)
XSKD	58.66 ± 0.71	9.04 ± 0.03	3.35 ± 0.02
psc	48.81 ± 0.63	7.12 ± 0.12	2.11 ± 0.04

Note: Body length, Body width, Body weight p < 0.01.

Table 4.

XSKD and individual phenotype of Psc cocoons.

Strain	Cocoon length (cm)	Cocoon Width (cm)	Cocoon weight (g)	Cocoon shell weight (g)	Cocoon shell rate (%)
XSKD	3.62 ± 0.08	1.68 ± 0.04	1.71 ± 0.02	0.363 ± 0.008	21.26 ± 0.71
psc	2.63 ± 0.03	1.16 ± 0.04	0.81 ± 0.02	0.120 ± 0.010	14.92 ± 1.59

Note: Cocoon length, Cocoon width, Cocoon weight, Cocoon shell weight, Cocoon shell rate p < 0.01.

Fig. 2.

The individual phenotype measurement results of XSKD and psc cocoons. (A) Cocoon length; (B) Cocoon width; (C) Cocoon weight; (D) Cocoon shell weight; (E) Cocoon shell rate. **p<0.01;***p<0.001; ****p<0.0001 (t-test).

Basic situation and analysis of transcriptome data

Based on high-throughput sequencing technology, whole-silkworm transcriptome analysis of third-instar silkworms with XSKD and psc was conducted to explore the key molecular mechanisms leading to the phenotype of psc mutants. The sequencing results showed (Table 5): the number of original reads ranged from 35,767,334 to 40,452,752, while the number of clean reads obtained after quality control ranged from 34,987,662 to 39,611,808, with a filtered base number ranging from 5.25 to 5.94 Gb. The effective rates were above 97%. A total of 31,725 valid reads were obtained by splicing and assembling. A total of 17,047 genes were detected and expressed in the transcriptome assembly and clustering analysis. Q20 and Q30 are above 99% and 97%, respectively, and the GC content is between 45% and 46%. The above results indicated that the sequencing data of this sample were reliable and could be used for further analysis. The original sequencing data have been uploaded to NCBI’s Sequence Read Archive (SRA) database with entry number PRJNA1243052.

Table 5.

Quality of transcriptome sequencing data.

Sample Name	Raw reads	Clean reads (%)	Clean bases	Valid Ratio(reads)	Q20 (%)	Q30 (%)	GC (%)
XSKD-1	39,248,262	38,359,240 (97.73%)	5.75G	97.73	99.79	97.68	45
XSKD-2	40,452,752	39,611,808 (97.92%)	5.94G	97.92	99.80	97.90	45.50
XSKD-3	35,767,334	34,987,662 (97.82%)	5.25G	97.82	99.79	97.72	45.50
psc−1	37,547,744	36,734,016 (97.83%)	5.51G	97.83	99.79	97.69	46
psc−2	39,135,596	38,176,238 (97.55%)	5.73G	97.55	99.77	97.68	45
psc−3	37,913,052	37,028,748 (97.67%)	5.55G	97.67	99.77	97.63	46

Consistency of qRT-PCR and sequencing data

Sixteen differentially expressed genes were randomly selected to validate the reliability of the transcriptome data using qRT-PCR technology. The expression trends of the 16 genes were consistent with the results of the transcriptome sequencing (Fig. 3), indicating that the RNA-seq results had a high level of reliability and that the transcriptome results could be used for further analysis.

Fig. 3.

Accuracy of transcriptome data verified by qRT-PCR. In the figure, black represents the wild-type XSKD, and gray represents the mutant psc. (A) Up-regulation of 8 genes; (B) down-regulation of 8 genes.

Analysis of differentially expressed genes

The differentially expressed genes between the groups were analyzed using a volcano plot and displayed as a histogram (Fig. 4). A total of 716 differentially expressed genes (DEGs) were identified, including 354 up-regulated genes and 362 down-regulated genes. In order to better analyze the function of DEGs in vivo and their related pathways, we performed GO enrichment and KEGG analysis of DEGs detected in two groups of silkworms.

Fig. 4.

Volcano and histogram of differentially expressed genes of XSKD and psc silkworms. (A)Differential Gene Volcano Plot; (B) Bar chart of the number of up-regulated and down-regulated genes; Red indicates up-regulated genes, and blue indicates down-regulated genes. |log₂fc|>=1 & q < 0.05.

GO enrichment analysis of differentially expressed genes

The results of the GO (http://www.geneontology.org) enrichment analysis showed that the differentially expressed genes were significantly enriched in biological processes, cellular components, and molecular functions across the three categories (Fig. 5).In biological processes, DEGs related to obsolete oxidation-reduction processes, proteolysis, transmembrane transport, DNA recombination, receptor-mediated endocytosis, and long-chain fatty-acyl-CoA metabolic processes were identified, among which the entries with the most significant enrichment of down-regulated genes were DNA recombination, and those with the most significant enrichment of up-regulated genes were obsolete oxidation-reduction processes. These biological processes were closely related to metabolic processes, gene expression regulation and cell signal transduction. Among the cellular components, the differentially expressed genes related to the nucleus, cytoplasm and membrane were found, among which the down-regulated genes were most significantly enriched for the intrinsic components involved in membrane expression, while the up-regulated genes were most significantly enriched for the differential expressions involved in cytoplasmic components. These differentially expressed genes may have caused abnormalities in cell morphology, structure and function, thus affecting metabolism, cell proliferation and differentiation. In terms of molecular function, there were differentially expressed genes related to metal ion binding, oxidoreductase activity, structural constituent of cuticle, RNA-directed DNA polymerase activity, and protein binding, among which the entries with the most significant down-regulated gene enrichment were those involved in metal ion binding. The most significant items of up-regulated gene enrichment were associated with protein binding and the expression of structural constituents of the cuticle. The differential expression and regulation of these genes were key to the growth and development of silkworms, such as affecting the immune capacity, hormone levels, and energy metabolism of silkworm.

Fig. 5.

GO enrichment analysis of differentially expressed genes in XSKD and psc silkworms. |log₂fc|>=1 & q < 0.05.

KEGG enrichment analysis of differentially expressed genes

Analysis of the KEGG database (http://www.genome.jp/kegg/kegg) indicated that approximately 89 DEGs were associated with 69 pathways, the majority of which were related to metabolic pathways. Specifically, 41 DEGs were linked to these pathways, with 14 exhibiting increased expression and 27 showing decreased expression. The differentially expressed genes in these metabolic pathways were primarily located in the tyrosine metabolism pathway, fatty acid metabolism pathway, biosynthesis of unsaturated fatty acids, purine metabolism pathway, caffeine metabolism pathway, and drug metabolism pathway, among others. These pathways involved the metabolism of important substances such as fats, amino acids, purines, and hormones, which were extremely important for the growth and development of the silkworm. Among the other DEGs, the most significantly associated pathway was the peroxisome, with 7 up-regulated and 5 down-regulated DEGs. In addition, in the neuroactive ligand-receptor interaction pathway, there were 2 up-regulated DEGs and 6 down-regulated DEGs. The remaining DEGs were distributed in the carbohydrate metabolism pathway, the autophagy-animal pathway and endocytosis (Fig. 6). The above indicated that these differentially expressed genes played a very important role in substance metabolism and signal regulation, cell proliferation, differentiation, apoptosis, and the coordination of immune system defense responses. We speculated that these findings were likely closely associated with the biological characteristics exhibited by the psc mutants.

Fig. 6.

KEGG enrichment analysis of differentially expressed genes in XSKD and psc silkworms. |log₂fc|>=1 & q < 0.05.

Analysis of differentially expressed genes in different physiological processes of silkworm

Metabolic pathways played a key role in the growth and development of silkworms, silk protein synthesis, immune defense, and environmental adaptation, among which amino acid metabolism pathways, lipid metabolism pathways, and carbohydrate metabolism pathways were particularly important. The relevant genes in the pathways were verified by qRT-PCR, as shown in Table 6.

Table 6.

Comparison of FPKM and qRT-PCR.

Team	Gene ID	description	Difference multiple		Concordant
			FPKMa	qRT-PCRb	Up	Down
A	NGR-A15	neuropeptide receptor A15	5.99	2.68	√
	LOC101742482	trypsin, alkaline A	2.08	1.12	√
	NGR-A16	neuropeptide receptor A16	0.41	0.77		√
	NGR-A25	neuropeptide receptor A25	0.002	0.05		√
	NGR-A9	neuropeptide receptor A9	0.001	0.19		√
	NGR-A14	neuropeptide receptor A14	0.43	0.73		√
	LOC101742329	trypsin, alkaline C	0.37	0.57		√
	LOC101737824	trypsin, alkaline A	0.37	0.34		√
B	LOC100862799	acyl-CoA Delta(11) desaturase	1115.42	21.70	√
	LOC732939	3-hydroxyacyl-CoA dehydratase 1	0.48	0.62		√
	Desat3	acyl-CoA desaturase	0.48	0.36		√
	LOC101742625	fatty acid synthase	0.23	0.08		√
C	LOC101738607	uncharacterized LOC101738607	3.85	1.08	√
	LOC101742965	allantoicase	0.37	0.38		√
	LOC101737205	2-oxo-4-hydroxy-4-carboxy-5-ureidoimidazoline decarboxylase	0.36	0.21		√
	LOC101738209	xanthine dehydrogenase	0.35	0.20		√
	Aox2	aldehyde oxidase 2	0.38	0.52		√
	LOC101738746	probable aldehyde oxidase gad-3	0.20	0.72		√
D	Amy	alpha-amylase	0.14	0.22		√
	LOC100862812	UDP-glucosyltransferase 2	0.39	0.43		√
	UGT340C1	UDP-glycosyltransferase UGT340C1	0.37	0.62		√
	LOC101739464	glucose dehydrogenase [FAD, quinone]	2.04	1.75	√
E	LOC101737492	L-dopachrome tautomerase yellow-f	0.10	0.18		√
	LOC101737351	L-dopachrome tautomerase yellow-f-like	0.06	0.04		√
	LOC101741665	L-dopachrome tautomerase yellow-f2	0.16	0.12		√
	LOC101743564	MIF-like protein mif-2	0.47	0.70		√

Note: (A) Neuroactive ligand-receptor interaction pathway (B) Lipid metabolism pathway (C) Purine metabolism pathway (D) Carbohydrate metabolism pathway (E) Amino acid metabolism pathway.

^aFold change (psc/XSKD) of gene expression in FPKM.

^bFold change (psc/XSKD) of gene expression in qRT-PCR.

Analysis of differentially expressed genes of amino acid metabolic pathway

In the amino acid metabolic pathway, we found that psc mutants had 9 down-regulated genes and 2 up-regulated genes. Among them, a greater number of genes were differentially expressed in the tyrosine metabolic pathway, and 4 of them were down-regulated (Fig. 7)^26–28. Based on the relevant tyrosine metabolic pathways where the differential genes were located, it was understood that tyrosine could undergo a series of enzymatic reactions to produce dopachrome. Under the action of certain enzymes, dopachrome could ultimately generate melanin through two distinct pathways. Among these, dopa quinone produced 5, 6-dihydroxyindole-2-carboxylic acid (DHICA) in this pathway. We observed a down-regulation in the expression of several enzymes from the yellow gene family in psc mutants, which likely led to a reduced synthesis of 5, 6-indoloquinone carboxylic acid (5,6-IQCA), thereby affecting melanin production. In the pathway leading to the formation of 2-hydroxy-3-(4-hydroxy-phenyl) acrylate from tyrosine via 3-(4-hydroxy-phenyl) pyruvate, the expression of the mif-2 gene was also down-regulated, which may have resulted in a decrease in the synthesis of 2-hydroxy-3-(4-hydroxy-phenyl) acrylate. Other genes exhibiting down-regulated expression included AGXT2 (involved in alanine decomposition and glycine synthesis) and GADL1 (catalyzing the decarboxylation of acidic amino acids, such as glutamic acid to γ-aminobutyric acid, along with other related neurotransmitters, thereby regulating neurotransmitter levels). Two genes were upregulated: one encoding an unknown protein and the GRHPR (involved in gluconeogenesis and energy metabolism). These genes play a critical role in energy metabolism and the amino acid metabolic pathway; their differential expression may have influenced the synthesis of specific proteins and energy metabolism, potentially leading to abnormal growth and development in silkworms.

Fig. 7.

Local diagram of tyrosine metabolic pathway. The green background of the gene indicates that it is down-regulated.

Differential gene analysis of carbohydrate metabolic pathway

Carbohydrate metabolism served as the cornerstone of energy metabolism by facilitating the degradation of starch, glucose, and other carbohydrates through a series of enzymatic reactions. This process provided a rapid supply of energy to organisms, thereby supporting growth and developmental processes. As illustrated in Fig. 8, α-amylase in silkworms was a key enzyme that converted starch, glycogen, or maltodextrin into maltose²⁹. Additionally, the glucosyltransferase associated with uridine diphosphate played a crucial role in catalyzing glucuronic acid and detoxifying secondary metabolites from mulberry leaves, such as DNJ in silkworms^30,31. We identified four genes related to carbohydrate metabolism that were differentially expressed; three of these genes, namely the alpha-amylase (Amy) gene, UDP-glucosyltransferase 2 (UGT2) gene, and UDP-glycosyltransferase UGT340C1 (UGT340C1) gene, were down-regulated. In contrast, the expression of the glucose dehydrogenase (GLD) gene was up-regulated. The abnormal expression of these genes may have disrupted energy metabolism processes and consequently affected the growth and development of silkworms.

Fig. 8.

Schematic diagram of carbohydrate metabolism pathway involved in α-amylase. The green background of the gene indicates that it is down-regulated.

Differential gene analysis of lipid metabolism pathway

Lipid metabolism plays a key role in energy metabolism through a series of enzymatic reactions, primarily serving as energy storage and supply. It also regulates growth and development through the synthesis and degradation of certain hormones. As shown in Fig. 9A, fatty acid synthase, the rate-limiting enzyme of fatty acid synthesis, catalyzed the condensation reaction of acetyl-CoA and malonyl-CoA, gradually extending the carbon chain through cyclic steps such as reduction and dehydration, ultimately generating fatty acid molecules of varying chain lengths³². The enzyme 3-hydroxyacyl-CoA dehydratase was essential in the β-oxidation pathway of fatty acids. By catalyzing the dehydration reaction of 3-hydroxyacyl-CoA, fatty acid molecules were oxidized and degraded into acetyl-CoA, which subsequently entered the tricarboxylic acid cycle to release energy³³. The core function of acyl-CoA desaturase was to catalyze the desaturation of acyl-CoA, introducing double bonds into the fatty acid carbon chain (Fig. 9B) and converting saturated fatty acids into unsaturated fatty acids³⁴. We found four differentially expressed genes involved in lipid metabolism in psc mutants, among which three down-regulated genes were FASN, Hacd1 and Desat3. Another gene that was up-regulated is Desat11.The differential expression of these genes likely caused changes in the synthesis and degradation of lipid metabolites.

Fig. 9.

Schematic diagram of lipid metabolism pathway. (A) Schematic diagram of fatty acid synthesis pathway involved in fatty acid synthase. In the figure, FASN enzymes are required to act on green parts and arrows; (B) Schematic diagram of unsaturated fatty acid production involving acyl-CoA desaturase. A gene with a green background indicates it is down-regulated, and a gene with a red background indicates it is up-regulated.

Differential gene analysis of purine metabolic pathways

The purine metabolic pathway, also known as the nucleotide metabolic pathway, plays a crucial role in synthesizing genetic material and regulates development and metabolism by producing signaling molecules, among other functions. In psc mutants, six differentially expressed genes associated with purine metabolic pathways were identified. Among these, five genes were down-regulated: xanthine dehydrogenase (XDH), aldehyde oxidase 2 (Aox2), possible aldehyde oxidase (gad-3), 2-oxo-4-hydroxy-4-carboxy-5-urea-imidazoline decarboxylase (LOC101737205), and allantoidase, while the unannotated gene LOC101738607 was up-regulated. As illustrated in Fig. 10, hypoxanthine was converted to xanthine by aldehyde oxidase and xanthine dehydrogenase, which was then regenerated into urate. This urate was subsequently transformed into allantoate through a series of reactions, ultimately producing urea under the action of allantoidase. Therefore, changes in the expression of these genes in silkworm psc mutants were likely to disrupt purine metabolism.

Fig. 10.

Local diagram of purine metabolic pathway. A gene with a green background indicates it is down-regulated, and a gene with a red background indicates it is up-regulated.

Differential gene analysis

The neuroactive ligand-receptor interaction pathway plays a key role in nervous system signal transmission, behavior regulation and physiological homeostasis maintenance³⁵. Neuromedin U Receptor (NMUR) and Hypocretin Receptor (HCRTR) are both G-protein-coupled receptors (GPCRs) located on cell membranes, which are activated by Neuromedin U (NMU) and Hypocretin (HCRT), respectively. The binding of NMU and HCRT to their receptors initiates signaling pathways^36,37.

After NMUR is activated, phospholipase C (PLC) is activated by Gαq protein, and then the membrane phospholipid PIP₂ is hydrolyzed to produce inositol triphosphate (IP₃) and diacylglycerol (DAG). IP₃ induces the release of calcium ions (Ca²⁺) in the ER, while DAG works synergistically with the Ca²⁺ to activate protein kinase C (PKC). PKC regulates gene expression through phosphorylated transcription factors (such as NF-KB), thereby affecting energy metabolism and stress response. Activation of HCRTR follows two pathways: After binding to HCRT, the PLC-PKC pathway (similar to NMUR) is activated by the Gαq protein. Adenylate cyclase (AC) is activated by Gαs protein, which catalyzes the generation of cAMP, thereby activating protein kinase A (PKA). PKA regulates gene expression through phosphorylated transcription factors (such as CREB), thereby ultimately acting on sleep-wake cycles, appetite, and nerve excitability (Fig. 11).

Fig. 11.

Intracellular signaling processes induced by binding of NMUS and HCRT ligands to their receptors NMUR and HCRTR.A gene with a green background indicates that it is down-regulated, a red background indicates a key signaling molecule, and a blue background indicates a protein kinase.

We identified eight differentially expressed genes associated with neuroactive ligand-receptor interaction pathways in psc mutants. Six genes were down-regulated, including four neuropeptide receptor genes: A16 (NGR-A16), A25 (NGR-A25), A9 (NGR-A9), and A14 (NGR-A14) and two trypsin genes: basic C (LOC101742329) and A (LOC101737824). All four NGRS encode G-protein-coupled receptors; NGR-A16 was a member of HCRTR and NGR-A25 was a member of NMUR. The two trypsin genes of the alkaline type were protease-activating receptor-related sequences. Two up-regulated genes were: trypsin, alkaline A (LOC101742482) and neuropeptide receptor A15 (NGR-A15). The differential expression of these genes may have resulted in abnormalities in certain signal transduction processes in silkworms.

Discussion

Silkworm is a model organism of Lepidoptera. Its growth and development process is extremely complex, involving the precise regulation of core metabolic pathways such as amino acids, carbohydrates and lipids¹. Perforated small cocoon is a newly identified silkworm mutant with stable inheritance, and its molecular mechanisms have not yet been elucidated. To analyze the phenotypic causes, this study selected the third instar silkworm, a crucial developmental stage, and conducted a whole-silkworm transcriptome comparison between psc and wild-type XSKD, aiming to systematically identify the early differentially expressed genes and changes in signaling pathways.

Amino acids are essential nutrients for the growth and development of silkworms, and their metabolism is mainly carried out in the amino acid metabolic pathway. Tyrosine is a precursor to the synthesis of melanin, which is produced by a series of enzymatic reactions. During the molting stage of the silkworm, the deposition of melanin in the new epidermis can enhance its hardness and resistance to damage, thus protecting it from external damage³⁸. At the same time, dopamine derived from tyrosine metabolism may act as neurotransmitters or hormones to regulate the growth and development of silkworms³⁹. In addition, tyrosine is also an essential amino acid component of silk protein, so tyrosine metabolism is a very important amino acid metabolic pathway in silkworms. Studies have shown that the expression products of the yellow gene family, specifically yellow, yellow-f, and yellow-f2, can catalyze the conversion of dopamine into the corresponding pigment compounds^40,41, and play a major role in melanin deposition in late pupae and adults⁴¹. Therefore, the yellow gene family plays a key role in melanin deposition⁴². In addition, MIF-2 also plays an important role in the melanination process of insects⁴³. In psc mutants, the expression of yellow-f, yellow-f2, yellow-f-like and mif-2 genes were down-regulated, which may have affected the synthesis of melanin in psc. Since melanin was an important component of epidermal chitin sclerosis, its reduced synthesis may have impaired the hardening of mouthparts, thereby affecting the feeding efficiency of psc mutants. In actual rearing observations, we found that the psc mutants exhibited slow and intermittent feeding on mulberry leaves at the start of the third instar, which is consistent with the speculation of reduced melanin synthesis. Additionally, the differential expression of other genes in the amino acid pathway—related to silk protein metabolism, energy metabolism, and other processes—may collectively contribute to the growth and developmental retardation observed in the psc mutant. In the future, gene editing techniques can be employed to knock out or overexpress members of the yellow gene family or mif-2, followed by examination of their effects on mouthpart hardness, feeding behavior on mulberry leaves, and melanin content, in order to verify this hypothesis.

Apart from the local defect in amino acid metabolism, the overall insufficient energy supply of the organism might be another core factor restricting its growth. Silkworms metabolize carbohydrates, such as glucose and sucrose, present in mulberry leaves through glycolysis, the tricarboxylic acid cycle, and other metabolic pathways. This process results in the production of ATP, which provides energy for various life activities such as growth, feeding, and exercise. α-amylase (Amy) is a key enzyme in the digestive system of silkworms, and its activity is dynamically regulated by hormones and nutritional states in silkworms. During the feeding period, amylase activity increases to accelerate starch digestion. Before molting, the enzyme activity decreases correspondingly, which reduces energy consumption to match the metabolic adjustments during the developmental stage^44,45. Additionally, glucosyltransferase (UGT) can effectively remove the potential toxicity of mulberry leaf alkaloids and other secondary metabolites by catalyzing the glycosylation reaction⁴⁶. The expression of the Amy gene and the UGT gene was significantly down-regulated in psc mutants, which may have decreased the activities of these two enzymes. Considering that the psc mutant exhibits slow feeding and reduced food intake on mulberry leaves, its requirements for starch breakdown and detoxification are correspondingly lower. Therefore, the downregulation of these two genes in the carbohydrate metabolic pathway may align with the phenotypic characteristics of the psc mutant, including its restricted feeding behavior and impaired growth and development. Subsequent studies will involve enzyme activity assays or gene loss-of-function experiments to clarify the impact of these gene expression changes on starch digestion and detoxification capacity, thereby further elucidating their causal relationship with the psc phenotype.

The storage and utilization of energy also depend on normal lipid metabolism, and this process is disrupted in the psc mutant as well. During the growth and development of silkworms, the fat body is an important energy storage organ. The normal growth and development of silkworms and the completion of the metamorphosis process are inseparable from the dynamic lipid accumulation in this organ, which largely depends on the synergistic regulation of carbohydrate, lipid, and amino acid metabolic pathways⁴⁷. Fatty acid synthase (FASN), 3-hydroxyacyl-CoA dehydratase (Hacd1), and acyl-CoA desaturase (Desat3) are the rate-limiting enzymes in lipid metabolic pathways. Compared to the XSKD, the expression of these three genes was significantly down-regulated in the silkworm psc mutants, which may have indicated a decrease in the expression activity of these three key enzymes, potentially leading to abnormalities in fat synthesis or decomposition. Studies have shown that lipid metabolism plays a key role in the reproductive development stage of silkworms, and abnormal metabolism can lead to delayed ovarian development, resulting in ovum development disorders and a decline in quality⁴⁸. The oviposition phenotype of psc mutants (few eggs and a low fertilization rate) suggested that the mutants may have been deficient in lipid metabolism. In addition, the Bmdesat5 gene can affect the satiety and food intake of Bombyx mori by regulating fatty acid metabolism, thus affecting individual size and growth processes⁴⁹. The down-regulated expression of the Bmdesat5 gene in psc mutants of Bombyx mori may have partly explained the phenotypic characteristics of psc mutants, who exhibited slow feeding on mulberry leaves and decreased appetite. Future functional validation of these key lipid metabolism genes will help clarify their specific roles in the growth, developmental, and reproductive defects observed in the psc mutant.

Abnormal excretion of metabolic waste is another phenotype that deserves attention, and it may be related to changes in purine metabolism. Purine metabolic pathways are involved in many important physiological processes through the synthesis, decomposition, and transformation of purines, and are crucial for maintaining physiological homeostasis and reproductive adaptability of silkworms⁵⁰. Xanthine dehydrogenase (XDH), as a rate-limiting enzyme in purine catabolism, completes the key steps of purine metabolism by catalyzing the oxidation of xanthine to uric acid⁵¹. Aldehyde oxidase 2 (Aox2) exhibits dual catalytic functions: it collaborates with xanthine dehydrogenase (XDH) to facilitate the conversion of xanthine to uric acid, while also reducing oxidative stress by oxidizing aldehydes, thereby protecting the structural integrity of cells⁵². In psc mutants, the expression of XDH and Aox2 were down-regulated, while the expression of unannotated LOC101738607 was up-regulated, which may have led to the disruption of purine metabolism. In our feeding observations, we found that although psc mutants were significantly smaller than wild-type XSKD moths upon emergence, individual psc moths excreted substantially more urine compared to their wild-type counterparts. This increased excretion suggested that psc mutants may have had abnormal purine metabolism.

The aforementioned extensive metabolic disorders suggest that there might be a more upstream regulatory system that coordinates physiology and behavior that has malfunctioned. Our data point to the neural signaling system as the source of this problem. As the largest family of membrane receptor proteins that exist in vivo, G protein-coupled receptors (GPCRs) bind to ligands, such as neuropeptides, to form complexes that activate downstream G protein signaling pathways. This activation facilitates transmembrane signal transduction and plays a crucial role in metabolic regulation, nerve conduction, and other physiological processes⁵³. In insects, GPCRs are mainly involved in regulating physiological activities such as feeding behavior, motor ability, and the developmental process⁵⁴. For example, the dopamine/ecdysone receptor (DmDopEcR) can be activated by 20E to regulate insect development^55,56. It is worth noting that 20E can also bind to ErGPCR-3 and induce a homologous dimer of ErGPCR-3 to form a homologous tetramer, thereby increasing intracellular ecdysone signal concentration and promoting insect metamorphosis development⁵⁷. We identified four significantly down-regulated GPCR genes in psc mutants, of which NGR-A16 belongs to the orexin receptor (HCRTR) subfamily and NGR-A25 belongs to the neurointerhormone U receptor (NMUR) subfamily. By regulating orexin signals, HCRTR receptors coordinate energy intake and metabolism to ensure that the energy requirements of organisms at different growth stages are met⁵⁸. When the expression of genes related to HCRTR is downregulated in an organism, it may imply a reduced ability to perceive appetite signals, which could explain the observed reductions in feeding rate and hypoactivity in the psc mutant. NMUR is a receptor for interleukin U, which regulates the excitability and synaptic plasticity of neurons by mediating interleukin U (NMU) signaling. Consequently, it plays a critical role in regulating the behavioral rhythms of organisms, including feeding and motor coordination⁵⁹. Under normal circumstances, silkworms need to precisely control the direction of silk by swinging their heads when forming cocoons, so as to form cocoons with a dense structure and no holes. This process relies on the precise regulation of muscle movement by the nervous system to ensure the consistency and regularity of the silk spinning behavior. Cocoons produced by psc mutants frequently exhibit perforations at both ends. We hypothesize that this observation may be attributed to the downregulation of NMUR receptor gene expression within their bodies, consequently leading to altered rhythmicity in their silk-spinning behavior. Future functional studies on these neuropeptide receptor genes, such as gene knockdown or overexpression combined with behavioral analysis, will be essential for validating these hypotheses.

In addition, cytochrome P450 enzymes can play a key role in the development process of insects by regulating the synthesis and metabolism of ecdysone^41,43,60,61. The psc mutants had three genes related to cytochrome P450 enzymes with differential expression, which may disturb ecdysone homeostasis and further affect the temporal regulation of ecdysone processes. The prolongation of the third instar of the psc mutants may be potentially related to this.

In summary, this study found that the psc mutant exhibited transcriptional dysregulation in multiple systems during the third instar stage of the silkworm. These changes did not occur in isolation: The inhibition of gene expression in the neural activity ligand-receptor interaction pathways (particularly NMUR and HCRTR) may have affected feeding drive and behavioral rhythms. Concomitant with the reduction in nutrient intake, it is associated with the downregulation of a large number of key enzyme genes in the metabolic pathways of carbohydrates, lipids and amino acids, jointly leading to insufficient energy supply and the synthesis of key substances. These interrelated abnormalities collectively form the molecular basis for the retarded development, small body size, and eventual formation of the perforated small cocoon in the psc mutant larvae.

This study is the first to conduct a comprehensive transcriptomic analysis at key developmental stages for the novel psc windbreak small cocoon mutant. This work has for the first time revealed the potential correlations between neural signals, behaviors and multi-system metabolism, providing the first molecular-level insights into the overall understanding of the body size and shell development defects. However, the current results are mainly based on the association analysis of transcriptome data. In the future, it is necessary to utilize technologies such as CRISPR/Cas9 gene editing to conduct functional validation of the above key pathways and genes, thereby ultimately clarifying the precise molecular mechanism of the psc mutant trait formation and providing important theoretical targets for silkworm breeding.

Conclusions

This study conducted transcriptomic analysis on the mutant strain of the silkworm and identified a total of 716 differentially expressed genes. These genes were mainly involved in amino acid, carbohydrate, and lipid metabolism, as well as nerve signaling pathways. The study revealed that metabolic disorders and abnormal neural regulation are among the causes of developmental retardation, reduced mulberry feeding, and cocoon defects in the mutants, providing an important basis for the study of the mechanisms of growth and development and the improvement of silkworm varieties.

Author contributions

K. Z. performed the majority of the experiments and wrote the original draft. X. W., D. S. and H. Q. conducted parts of the experiments and were responsible for data curation. X. Z., D. X. and Q. Z. provided supervision. Z. Q. designed and supervised the research project, acquired funding, and reviewed and edited the manuscript. All authors have read and agreed to the final version of the manuscript.

Funding

This work was supported by China Agriculture Research System[CARS-18-ZJ0101].

Data availability

The original sequencing data have been uploaded to NCBI’s Sequence Read Archive (SRA) database with entry number PRJNA1243052.

Declarations

Competing interests

The authors declare no competing interests.