Transcriptome analysis reveals potential function of long non-coding RNAs in 20-hydroxyecdysone regulated autophagy in Bombyx mori

Qiao, Huili; Wang, **gya; Wang, Yuanzhuo; Yang, Juanjuan; Wei, Bofan; Li, Miaomiao; Wang, Bo; Li, **aozhe; Cao, Yang; Tian, Ling; Li, Dandan; Yao, Lunguang; Kan, Yunchao

doi:10.1186/s12864-021-07692-1

Transcriptome analysis reveals potential function of long non-coding RNAs in 20-hydroxyecdysone regulated autophagy in Bombyx mori

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Published: 22 May 2021

Volume 22, article number 374, (2021)
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Transcriptome analysis reveals potential function of long non-coding RNAs in 20-hydroxyecdysone regulated autophagy in Bombyx mori

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Huili Qiao¹,
**gya Wang^1,2,
Yuanzhuo Wang¹,
Juanjuan Yang¹,
Bofan Wei¹,
Miaomiao Li^1,2,
Bo Wang¹,
**aozhe Li¹,
Yang Cao^3,4,
Ling Tian⁴,
Dandan Li¹,
Lunguang Yao¹ &
…
Yunchao Kan¹

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Abstract

Background

20-hydroxyecdysone (20E) plays important roles in insect molting and metamorphosis. 20E-induced autophagy has been detected during the larval–pupal transition in different insects. In Bombyx mori, autophagy is induced by 20E in the larval fat body. Long non-coding RNAs (lncRNAs) function in various biological processes in many organisms, including insects. Many lncRNAs have been reported to be potential for autophagy occurrence in mammals, but it has not been investigated in insects.

Results

RNA libraries from the fat body of B. mori dissected at 2 and 6 h post-injection with 20E were constructed and sequenced, and comprehensive analysis of lncRNAs and mRNAs was performed. A total of 1035 lncRNAs were identified, including 905 lincRNAs and 130 antisense lncRNAs. Compared with mRNAs, lncRNAs had longer transcript length and fewer exons. 132 lncRNAs were found differentially expressed at 2 h post injection, compared with 64 lncRNAs at 6 h post injection. Thirty differentially expressed lncRNAs were common at 2 and 6 h post-injection, and were hypothesized to be associated with the 20E response. Target gene analysis predicted 6493 lncRNA-mRNA cis pairs and 42,797 lncRNA-mRNA trans pairs. The expression profiles of LNC_000560 were highly consistent with its potential target genes, Atg4B, and RNAi of LNC_000560 significantly decreased the expression of LNC_000560 and Atg4B. These results indicated that LNC_000560 was potentially involved in the 20E-induced autophagy of the fat body by regulating Atg4B.

Conclusions

This study provides the genome-wide identification and functional characterization of lncRNAs associated with 20E-induced autophagy in the fat body of B. mori. LNC_000560 and its potential target gene were identified to be related to 20-regulated autophagy in B. mori. These results will be helpful for further studying the regulatory mechanisms of lncRNAs in autophagy and other biological processes in this insect model.

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Background

Macroautophagy (hereafter autophagy) is an essential, evolutionarily conserved cellular degradation and recycling process in all eukaryotes [1]. The role of autophagy is to maintain cellular homeostasis by degrading intracellular components. Autophagy is a process involving induction, cargo recognition and packaging, vesicle formation, and breakdown. A series of autophagy-related (Atg) genes are required for the initiation, nucleation, expansion, and completion of bodies known as autophagosomes, which eventually fuse with lysosomes [2]. Autophagy is essential to many physiological and developmental processes, and defects in autophagy are often associated with diseases and tumor progression [3, 4].

Autophagy is regulated by several ATG proteins, which are evolutionary conserved from yeast to mammals, ATG proteins are classified into six functional complexes including ATG1-kinase complex, phosphatidylinositol-3-kinase complex, ATG2-ATG18 complex, ATG9 membrane protein, ATG8 conjugation system and ATG12 conjugation system [5]. ATG4 is the only cysteine protease specific to ATG8, and essential for the conjugation and deconjugation of ATG8. Although ATG4 and ATG8 are evolutionarily conserved, higher eukaryotes have multiple homologs for both proteins. In contrast to the Atg4 and Atg8 in yeast, there are four ATG4 and six ATG8 homologs in mammals, the protease activity of the ATG4 homologs is markedly different, but ATG4B exhibits much higher activity than the other homologs [6, 7]. ATG4 homologs are important for autophagosome formation, autophagy is inhibited by suppressing ATG4 expression [8]. In B. mori, 15 Atgs have been identified in the genome [9, 16]. In the last decades, advances in transcriptome sequencing have led to the identification of a large number of lncRNAs in various eukaryotic organisms using new technologies and bioinformatics methods [17,18,19,20,21,22], but there are still few studies into their functions. Recently, lncRNAs have attracted attention because of their critical roles in organismal growth, development, senescence, and death. There is evidence that lncRNAs participate in a range of biological processes, such as X-chromosome silencing [Full size image

Based on these results, and those of previous studies [Full size image

Because Atg4B has not been functionally identified in B. mori, the phylogenic analysis of ATG4B homologs from different species was performed. The results showed that Atg4B of B. mori was more conserved with the homologs from other lepidopteran species and D. melanogaster Atg4A. The sequence identitiy was 100 % identical to the Atg4B of B. mandarina, 88 % to Helicoverpa armigera and Manduca sexta Atg4B, 50 % to the D. melanogaster Atg4A, 47 % to Homo sapiens ATG4B, and 46 % to Mus musculus ATG4B, but only 33 % identities to the B. mori Atg4-like, 30 % to the Drosophila Atg4B, and 25 % to the Saccharomyces cerevisiae Atg4 (Fig. 8). The alignment of the sequences showed that the predicted functional domain, peptidase C54, was evolutionary conservation among the different ATG4 homologs (Fig. 9).

Since Atg4B is an essential protein involved in autophagy, to further study the function of lncRNA in 20E-induced autophagy, we focused on LNC_000560 and its target gene Atg4B to explore the regulatory function of lncRNAs in the silkworm. We further analyzed the expression profiles of LNC_000560 and Atg4B in the fat body at 2, 6, 12, and 24 h.p.i.20E, at different developmental stages and in different tissues of silkworm larvae. LNC_000560 and Atg4B showed highly similar expression patterns in the fat body. The expression of LNC_000560 and Atg4B was significantly increased at 2, 6, and 12 h.p.i.20E, and decreased to basal levels at 24 h.p.i.20E (Fig. 10).

Their expression trend at different developmental stages was also consistent, while several peaks were detected from the second day of 5th instar larvae to the adult stage. Especially both exhibited expression peaks at the later stage of larvae and pupae, as well as on the second day of the pupal stage (Fig. 11a). The expression of LNC_000560 in larval tissues was high in the epidermis and fat body, and relatively low in other tissues, with no expression in the hemolymph or midgut (Fig. 11b). Atg4B showed a similar expression pattern as LNC_000560, although its highest expression was observed in testis (Fig. 11c).

RNA interference of lncRNA

To further study the regulation relation between LNC_000560 and Atg4B, we performed RNAi experiment to knockdown the expression of LNC_000560 in the fat body of silkworm larvae. Compared with dsEGFP control, we found that the expression of LNC_000560 and Atg4B in fat body was significantly decreased after LNC_000560 knockdown, which indicated that the expression of LNC_000560 was successfully down-regulated and it could indirectly participate in the regulation of autophagy by regulating its target gene Atg4B (Fig. 12).

Discussion

In insects, the fat body undergoes dramatic changes, via a process known as fat body remodeling, during metamorphosis from larva to pupa [34, 46, 60]. Raw read data in FASTQ format were processed using custom Perl scripts. In this step, clean data were obtained by removing reads containing adapter or ploy-N, and low-quality reads, from the raw data. The Q20, Q30, and GC contents of the clean reads were calculated. All downstream analysis were based on the clean, high quality reads. Reference genome and gene annotation files of silkworm B. mori were downloaded from SilkDB website (http://silkworm.genomics.org.cn/) and NCBI genome site (https://www.ncbi.nlm.nih.gov/genome/). An index of the reference genome was built using Bowtie v2.0.6 and paired-end clean reads were aligned to the reference genome using TopHat v2.0.9 (http://ccb.jhu.edu/software/tophat/index.shtml) [61].

Transcriptome assembly

The mapped reads of each sample were assembled using both Scripture (beta2) [62] and Cufflinks v2.1.1 (http://cole-trapnell-lab.github.io/cufflinks/) [63] in a reference-based approach. Both methods use spliced reads to determine exon connectivity, but the methods use two different approaches. Scripture uses a statistical segmentation model to distinguish expressed loci from experimental noise, and uses spliced reads to assemble expressed segments. It reports all statistically significantly expressed isoforms at each locus. Cufflinks uses a probabilistic model to simultaneously assemble and quantify the expression level of a minimal set of isoforms which provides a maximum likelihood explanation of the expression data in each locus.

LncRNA identification and classification

The putative lncRNAs were screened and identified from the silkworm transcriptome. The filtering process included five steps: (1) single exon transcripts were eliminated; (2) transcripts of ≤ 200 bp were removed; (3) transcripts that overlapped with any protein-coding exon in the sense orientation were filtered out; (4) transcripts with fragments per kilobase of transcripts per million mapped reads (FPKM) < 0.5 were removed; and (5) transcripts with protein-coding potential as predicted by either CPC or PFAM were excluded, while transcripts without protein-coding potential made up the candidate set of lncRNAs [64, 65]. The putative lncRNAs were classified into two groups, lincRNA and antisense lncRNA, using the class code module in Cuffcompare (http://cole-trapnell-lab.github.io/cufflinks/cuffcompare/) [66].

Expression analysis of lncRNAs and mRNAs

The expression levels of both lncRNAs and protein-coding genes in each sample were measured using Cuffdiff (v2.1.1) [66]. Gene FPKMs were calculated by summing the FPKMs of transcripts in each gene group. FPKM stands for fragments per kilobase of exon per million mapped fragments, which is calculated based on the length of the fragments and reads count mapped to each fragment. Cuffdiff provides statistical routines for determining differential expression in digital transcript or gene expression data, using a model based on the negative binomial distribution. Transcripts with a q-value < 0.05 were identified as differentially expressed.

Co-location analysis and functional enrichment

Cis-regulatory lncRNAs target and regulate the neighboring protein-coding genes [67, 68]. We searched the protein-coding genes within 100 kb / 10 kb upstream or downstream of all the identified lncRNAs, and then analyzed their function by functional enrichment. All co-located genes were used for GO enrichment analysis and KEGG enrichment analysis. GO enrichment analysis of the neighbor genes were implemented using goseq [69]. KEGG metabolic pathway enrichment analysis was carried out using KOBAS2.0 [70]. GO terms and KEGG pathways with p-values < 0.05 were considered significantly enriched.

Co-expression analysis

The expression levels of the identified lncRNAs and mRNAs from the two different stages were used to analyze the co-expression relationships of lncRNAs and protein-coding genes. Pearson’s correlation coefficients between the expression levels of 1035 lncRNAs and 14,622 mRNAs were calculated with custom scripts (r > 0.95 or r < − 0.95), and the candidate lncRNA target genes were used for functional enrichment analysis to predict the function of lncRNAs. Hypergeometric test and Benjamini–Hochberg FDR (false discovery rate) correction were used for statistically analysis, and only GO terms or KEGG pathways with corrected p-values < 0.05 or FDR < 0.05 were considered significant.

Expression validation of the selected lncRNAs and mRNAs

Atg1 is required for autophagosome initiation and is sensitive to 20E injection, Atg8 is the protein most widely used to monitor autophagy [71, 72]. The expression of the autophagy-related genes, Atg1 and Atg8, in the fat body at 2, 6, 12, and 24 h.p.i.20E was evaluated using qRT-PCR. The relative expression levels of the differentially expressed lncRNAs was confirmed using qRT-PCR. Total RNA from silkworm fat body 2, 6, 12, and 24 h.p.i.20E, and different developmental stages and tissues were used for the first-strand cDNA synthesis using RevertAid First Strand cDNA Synthesis Kits (Thermo Fisher, USA), according to the manufacturer’s instructions. qRT-PCR was carried out using Roche FastStart Universal SYBR Green Master (Rox) (Roche, Switzerland). Each reaction was performed on a BIO-RAD CFX96 Real-Time PCR Detection System with three biological replicates. The relative expression levels of lncRNAs were calculated using the 2^−ΔΔCt method [73]. Silkworm actinA3 (GenBank accession number U49854) was used as a reference gene. All the primers were designed using Primer 5.0 software (Additional file 11: Table S11). The PCR products were sequenced by the Bei**g Genomics Institute (BGI, Bei**g).

RNA interference

The primers of LNC_000560 and EGFP containing the T7 promoter sequence were designed for RNA interference. Their double-stranded RNA (dsRNA) were synthesized using T7 RiboMAX™ Express RNAi system (Promega, P1700) according to the manufacturer’s instruction. The dsRNA (10 µg per larva) of LNC_000560 was injected into 2-day-old 5th instar larvae, and EGFP dsRNA was injected as a control. After injection for 24 h, the fat body was dissected for qRT-PCR analysis. All the primers used in this study are listed in Additional file 11 (Table S11).

Bioinformatics analysis

Phylogenetic analysis was performed using MEGA5.0 software and the neighbor-joining method. The alignment of the peptidase C54 domain of ATG4B homologs was performed using the programs MultAlin [74] and ESPript [75]. All sequences were obtained from the NCBI and SilkDB databases.

Statistics analysis

Statistical analysis were performed using Prism 5, figures were prepared using Prism 5 and Adobe Illustrator CS5. The experimental data were analyzed using two-tailed, paired t-tests, *p < 0.05, **p < 0.01, ***p < 0.001. The values are shown as mean ± standard deviation of three independent experiments.

Availability of data and materials

The datasets generated during the current study are available in the SRA database of the NCBI system with accession number of PRJNA672230 (https://dataview.ncbi.nlm.nih.gov/object/PRJNA672230?reviewer=um7or07tegs52t8kec6smbtne5).

Abbreviations

LncRNA:: Long non-coding RNA
20E:: 20-hydroxyecdysone
Atg:: Autophagy related
JH:: Juvenile hormone
EcR:: Ecdysone receptor
HR3:: Hormone receptor 3
PI3K:: Phosphatidylinositol 3-kinase
TORC:: Target of rapamycin complex
h.p.i.:: Hours post-injection
FPKM:: Fragments Per Kilobase of exon model per Million mapped fragments
CPC:: Coding Potential Calculator
PFAM:: Protein Families Database
ORF:: Open Reading Frame
GO:: Gene Ontology
KEGG:: Kyoto Encyclopedia of Genes and Genomes
AMPK:: Adenosine 5’-monophosphate (AMP)-activated protein kinase

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Acknowledgements

We thank Bei**g Novogene Bioinformatics Institute, Bei**g, China for assisting in sequencing and bioinformatic analysis. We also thank Muwang Li for providing the Bombyx mori strains from the Sericultural Research Institute, Chinese Academy of Agricultural Sciences, and Camilo AYRA-PARDO for reviewing the manuscript and his editorial assistance.

Funding

This work was supported by grants from the National Natural Science Foundation of China (No. 31201754 and 32070503). The funding bodies had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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Authors and Affiliations

China-UK-NYNU-RRes Joint Laboratory of insect biology, Henan Key Laboratory of Insect Biology in Funiu Mountain, Nanyang Normal University, 473061, Nanyang, Henan, China
Huili Qiao, **gya Wang, Yuanzhuo Wang, Juanjuan Yang, Bofan Wei, Miaomiao Li, Bo Wang, **aozhe Li, Dandan Li, Lunguang Yao & Yunchao Kan
School of Life Science, Zhengzhou University, 450001, Zhengzhou, Henan, China
**gya Wang & Miaomiao Li
State Key Laboratory of Silkworm Genome Biology / Biological Science Research Center, Southwest University, 400716, Chongqing, China
Yang Cao
Guangdong Laboratory for Lingnan Modern Agriculture/Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, 510642, Guangzhou, Guangdong, China
Yang Cao & Ling Tian

Authors

Huili Qiao
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**gya Wang
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Yuanzhuo Wang
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Juanjuan Yang
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Bofan Wei
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Miaomiao Li
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Bo Wang
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**aozhe Li
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Yang Cao
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Ling Tian
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Dandan Li
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Lunguang Yao
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Yunchao Kan
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Contributions

YK conceived the idea and supervised this research. HQ designed the study, performed data analysis and wrote the manuscript. YK and HQ obtained the research funds. HQ, JW and YW detected and collected samples for the library construction. JW and JY performed RNA extraction and expression analysis of the identified lncRNAs. BFW, ML, BW, and XL participated in rearing, injection and sampling of B. mori. YC and LT provided technical assistance and coordination. DL and LY assisted in the data analysis and revision. All authors read and approved the final manuscript.

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Correspondence to Yunchao Kan.

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Supplementary Information

Additional file 1.

Summary of RNA-seq data of 12 silkworm samples.

Additional file 2.

Detailed information of lncRNAs identified in this study.

Additional file 3.

LncRNA and mRNA features.

Additional file 4.

Common differentially expressed lncRNAs and mRNAs in the two groups.

Additional file 5.

The significantly enriched GO terms detected in the two groups (cis).

Additional file 6.

The top 20 enriched KEGG pathways in the two groups (cis).

Additional file 7.

The significantly enriched GO terms detected in the two groups (trans).

Additional file 8.

The top 20 enriched KEGG pathways in the two groups (trans).

Additional file 9.

The significantly enriched GO terms of differentially expressed mRNAs in the two groups.

Additional file 10.

The top 20 enriched KEGG pathways of differentially expressed mRNAs in the two groups.

Additional file 11.

The primers of the selected lncRNAs and mRNAs.

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Qiao, H., Wang, J., Wang, Y. et al. Transcriptome analysis reveals potential function of long non-coding RNAs in 20-hydroxyecdysone regulated autophagy in Bombyx mori. BMC Genomics 22, 374 (2021). https://doi.org/10.1186/s12864-021-07692-1

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Received: 09 February 2021
Accepted: 06 May 2021
Published: 22 May 2021
DOI: https://doi.org/10.1186/s12864-021-07692-1

Transcriptome analysis reveals potential function of long non-coding RNAs in 20-hydroxyecdysone regulated autophagy in Bombyx mori

Abstract

Background

Results

Conclusions

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Background

RNA interference of lncRNA

Discussion

Transcriptome assembly

LncRNA identification and classification

Expression analysis of lncRNAs and mRNAs

Co-location analysis and functional enrichment

Co-expression analysis

Expression validation of the selected lncRNAs and mRNAs

RNA interference

Bioinformatics analysis

Statistics analysis

Availability of data and materials

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