Integrated analysis of differential lncRNA and mRNA expression in cholelithiasis based on high-throughput sequencing and bioinformatics

doi:10.21203/rs.3.rs-1708027/v1

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Integrated analysis of differential lncRNA and mRNA expression in cholelithiasis based on high-throughput sequencing and bioinformatics

https://doi.org/10.21203/rs.3.rs-1708027/v1

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Background:

The etiology of GSD (gallstone disease)has not been fully elucidated. Thus, the current study was designed to analyze the expression profiles of lncRNAs and mRNAs to unveil the potential mechanisms and investigate the role of lncRNA in GSD.

Methods:

Four gallstone and four control samples were collected and used for RNA sequencing. Differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were identified between gallstone and control samples by limma R package. The biological function of DElncRNAs and DEmRNAs were analyzed by clusterProfiler R package and IPA software. The Pearson correlation between DElncRNAs and DEmRNAs were calculated to construct the co-expression network of DElncRNAs and DEmRNAs. Moreover, to explore the role of lncRNA in gallstone, the cis- and trans-regulatory network of selected lncRNAs were constructed and visualized by Cytoscape software. In addition, we also constructed a ceRNA regulatory network in gallstone disease. To validate the RNA-sequencing data, we performed RT-qPCR to determine the expressions of top 4 DEmRNAs and DElncRNAs in gallstone and control samples.

Results:

A total of 934 DEmRNAs and 304 DElncRNAs were identified between gallstone and control samples, respectively. Functional enrichment analysis revealed that both DElncRNAs and DEmRNAs were involved in metabolism-related biological functions. The results of correlation analysis showed that the expressions of 597 DEmRNAs had extremely strong relationship with the expressions of 194 DElncRNAs. A cis-lncRNA-mRNA and trans-lncRNA-TF-mRNA regulatory network were constructed. In addition, a ceRNA composed of 24 DElncRNAs, 201 DEmRNAs and 120 predicted miRNAs was constructed by Cytoscape software.

Moreover, by RT-qPCR, we found that the expressions of AC004692.4, HECW1-IT1, SFRP4 and COMP were significantly higher, whereas the expressions of LINC01564, SLC26A3, RP1-27K12.2 and GSTA2 were remarkedly lower in gallstone samples compared with those in control ones, which were consistent with the sequencing results.

Conclusion:

Our study investigated the role of DElncRNAs and DEmRNAs in gallstone, which may help us understand the etiology of gallstone on the genetic level.

Gallstone

LncRNA

Cis- and trans-regulation

CeRNA

Etiology

Gallstone disease(GSD)is a common and frequently occurring disease on global scale. Its incidence rate in developed countries can reach 10%-15%^1,2, and 4–13% in different regions of China^3–6. Epidemiological studies have shown that GSD is the result of a combination of genetic, environmental, dietary and other factors^2,4,7. So far, numerous efforts have been been made to explore its mechanism that cholesterol-bile acid balance disorder^8–10, human intestine-liver axis structure destruction and/or function disorders^11,12, abnormal gallbladder contraction function^13,14, microbiota^10,15−17, imbalance of metabolic function of the body^18,19 and the influence of estrogen^6,20 all contribute to the development of GSD, but its exact pathogenesis is still not fully understood yet. Besides, impactful treatments of symptomatic GSD are predominantly invasive and are based on surgery²¹. There are no prophylactic drugs available for gallstones. Therefore, it is of great significance to further analyze the pathogenesis of GSD and provide new methods for the treatment and intervention of patients with gallbladder stones.

In recent years, long non-coding RNA (lncRNA) have been found to be closely related to many diseases^22–24. LncRNA is an RNA that does not code for protein, which regulates transcription, translation, mRNA cleavage, post-transcriptional modification and other processes to exert its biological effects such as regulating epigenetics, controlling the cell cycle, regulating differentiation and immune response^25–27. In recent years, with the maturity of sequencing and gene chip technology, more and more studies have confirmed the interaction between lncRNA and its regulated protein-coding genes, forming a highly complex regulatory network, which participate in a variety of life activities and disease progression. The mutation or expression abnormality of lncRNA has been reported to have close relationship with the occurrence and development of many diseases. However, the mining of lncRNAs that affect gallbladder stones has been limited, and its function in GSD is still unclear.

In this study, we utilized high-throughput sequencing to perform lncRNA and mRNA expression profiling in patients with or without gallstones, in order to identify significant differences in lncRNA and mRNA expression patterns. To our knowledge, this is the first analysis of lncRNA expression in gallstone disease used human gallbladder specimen. Our analyses provide both an integrated and comprehensive search for possible candidate lncRNAs and their mRNA targets for further studies of gallstone formation.

2.1 Patients and samples selection

All the samples of gallstone gallbladder tissue and normal gallbladder tissue(which were surgically removed due to liver hemangioma) were obtained from the Second Affiliated Hospital of Kunming Medical University (city of Kunming, Yunnan province, China) between March 2021 and July 2021. Criteria for selecting the subjects were as follows: (i) all patients were between the age of 20 and 55 years and without the use of any antibiotics within three months. (ii) all the patients were free of viral hepatitis, malignant tumor, underlying disease, and metabolic diseases. (iii) all patients were confirmed no obvious inflammation by pathology. Patients who met the criteria were randomly selected for inclusion in the study. Patients in the control group were definitively diagnosed with liver IV-V segments, without any gallbladder lesions, but the gallbladder was inevitably removed due to surgical approach, making it an ideal control group. Samples of gallbladder tissue were obtained from fresh surgery specimens, frozen in liquid nitrogen, then stored at -80℃. Four paired samples were detected by high-throughput deep sequencing. Additional 20 samples were collected for qRT-PCR validation analysis.

This study was approved by the ethics committee of The Second Affiliated Hospital of Kunming Medical University (Protocol Number:PJ-2021-79). The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individuals for the publication of any potentially identifiable images or data included in this article. Our research protocol meets the Helsinki declaration.

2.2 RNA extraction and library construction

RNA extraction, library construction and sequencing were carried out according to the previously reported steps²⁸. Total RNA was isolated and purified using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) following the manufacturer's procedure. The RNA amount and purity of each sample was quantified using NanoDrop ND-1000 (NanoDrop, Wilmington, DE, USA). The RNA integrity was assessed by Bioanalyzer 2100 (Agilent, CA, USA) with RIN number > 7.0, and confirmed by electrophoresis with denaturing agarose gel. Approximately 2µg of total RNA was used to remove ribosomal RNA according to the manuscript of the Epicentre Ribo-Zero Gold Kit (Illumina, San Diego, USA). Following purification, the ribo-minus RNA was fragmented into small pieces using Magnesium RNA Fragmentation Module (NEB, cat.e6150, USA) under 94℃ 5-7min. Then the cleaved RNA fragments were reverse-transcribed to create the cDNA by SuperScript™ II Reverse Transcriptase (Invitrogen, cat. 1896649, USA), which were next used to synthesize U-labeled second-stranded DNAs with E. coli DNA polymerase I (NEB, cat.m0209, USA), RNase H (NEB, cat.m0297, USA) and dUTP Solution (Thermo Fisher, cat.R0133, USA). An A-base is then added to the blunt ends of each strand, preparing them for ligation to the indexed adapters. Each adapter contains a T-base overhang for ligating the adapter to the A-tailed fragmented DNA. Single- or dual-index adapters are ligated to the fragments, and size selection was performed with AMPureXP beads. After the heat-labile UDG enzyme (NEB, cat.m0280, USA) treatment of the U-labeled second-stranded DNAs, the ligated products are amplified with PCR by the following conditions: initial denaturation at 95℃ for 3 min; 8 cycles of denaturation at 98℃ for 15 sec, annealing at 60℃ for 15 sec, and extension at 72℃ for 30 sec; and then final extension at 72℃ for 5 min. The average insert size for the final cDNA library was 300 ± 50 bp. At last, we performed the 2×150bp paired-end sequencing (PE150) on an illumina Novaseq™ 6000 (LC-Bio Technology CO., Ltd., Hangzhou, China) following the vendor's recommended protocol.

2.3 Data processing

Fastp²⁹was used to remove the reads that contained adaptor contamination, low quality bases and undetermined bases. Then sequence quality was also verified using fastp We used Bowtie2³⁰ and Tophat2³¹ to map reads to the genome of Homo sapiens GRCh38. The mapped reads of each sample were assembled using StringTie ³². Then, all transcriptome from all samples were merged to reconstruct a comprehensive transcriptome using gffcompare (https://github.com/gpertea/gffcompare/). After the final transcriptome was generated, StringTie was used to estimate the expression levels of all transcripts. Transcripts were annotated with known mRNAs, known long non-coding RNAs (lncRNAs) and transcripts shorter than 200 nt were discarded. Then we utilized CPC³³ and CNCI³⁴to predict transcripts with coding potential. All transcripts with CPC score <-1 and CNCI score < 0 were removed. The remaining transcripts with class code (I, j, o, u, x) were considered as lncRNAs. StringTie was used to perform expression level for mRNAs and lncRNAs by calculating FPKM (FPKM = [total_exon_fragments/mapped_reads(millions) × exon_length(kB)]). The differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) between gallstone and control samples were selected with |log2 (fold change)| >1 and with p-value < 0.05 by “limma” R package. The location of DElncRNAs were visualized by R package “circlize”.

2.4 Functional enrichment of DElncRNAs and DEmRNAs

“ClusterProfiler” R package was applied to perform GO and KEGG pathway enrichment analysis of DElncRNAs and DEmRNAs. Significantly enriched GO and KEGG pathways were identified with the threshold of adjusted p-value < 0.05. Furthermore, IPA analysis was performed to identify disease and function significantly associated with DElncRNAs and DEmRNAs (p-value < 0.05).

2.5 Construction of co-expression lnRNA-mRNA network and ceRNA network

To construct the coexpression network between DElncRNAs and DEmRNAs, the Pearson correlations between DElncRNAs and DEmRNAs were calculated. The criteria for co-expression was set to |cor| ≥0.97 and p-value < 0.0001. Then Cytoscape software was applied to construct and visualize the co-expression network. The miRWalk, TargentScan and miRDB were used to predict miRNAs targeting DEmRNAs. The starbase was used to predict DElncRNAs interacting with miRNAs. Then miRNA-DEmRNA and miRNA-DElncRNA were extracted according to their expression patterns to construct the ceRNA network.

2.6 Prediction of cis- and trans-regulation

For cis-regulation, we selected top five up-regulated and top five down-regulated DElncRNAs, which had the highest degrees in the co-expression network. According to the definition of cis-regulation³⁵, we searched for the adjacent genes less than 300kb upstream or downstream of above ten lncRNAs. Then those adjacent genes were intersected with DEmRNAs in the co-expression network. The overlapped DEmRNRAs were defined as cis-regulated genes. For trans-regulation, we are more interested in the way that lncRNA functions via transcription factors. Thus, TFcheckpoint database (http://tfcheckpoint.org) was used to get 3,479 TFs. Those TFs were intersected with DEmRNAs. Then TRRUST database (https://www.grnpedia.org/trrust/) was used to predict the targets of overlapped TFs. At last, the lncRNA-TF-mRNA network was constructed and visualized by Cytoscape software.

2.7 RT-qPCR

Total RNA were extracted by Nuclezol LS RNA Isolation Reagent (ABP Biosciences Inc, China) according to the instructions of the manufacturer. After detecting the concentration and the purity of RNA, qualified RNA was used for reverse transcription using SureScript-First-strand-cDNA-synthesis-kit (GeneCopoeia, USA). Then qPCR on a CFX96 Real-time PCR System (Bio-Rad, USA) was performed using BlazeTaq™ SYBR ® Green qPCR Mix 2.0 (GeneCopoeia, USA) under the thermal cycling conditions: 40 cycles at 95°C for 30 s, 95°C for 10 s, 60°C for 20 s and 72°C for 30s. The 2^−△△Ct method³⁶ was used to calculate gene expressions.

2.8 Statistical analysis

All data were shown as means ± SD. Comparisons between two groups were conducted using Student’s t-test. A p-value < 0.05 was considered statistically significant unless specified.

3.1 Identification and functional analysis of 304 DElncRNAs in gallstone

A total of 304 DElncRNAs, including 103 up-regulated and 201 down-regulated lncRNAs in gallstone samples relative to control ones, were identified (Fig. 1A and Table S1 in Supplementary Dataset). Circos image showed that those DElncRNAs were widely distributed on all chromosomes (Fig. 1B). To investigate the function of DElncRNAs, we utilized Multi Experiment Matrix online tool (http://biit.cs.ut.ee/mem/index.cgi) to predict the target genes of DElncRNAs by selecting “A-AFFY-44:Affymetrix GeneChip Human Genome U133 Plus 2.0[HG-U133_PLUS_2](2811 datasets)”. A total of 926 target genes were obtained (Table S2 in Supplementary Dataset), and they were significantly enriched into 60 biological processes (BP), 37 cellular components (CC) and 23 molecular functions (MF) (Table S3 in Supplementary Dataset). The top 30 GO terms were shown in Fig. 1C, that the potential target genes of DElncRNAs participate in multiple cellular functions. In addition, the potential target genes of DElncRNAs were significantly enriched into KEGG pathways of tyrosine metabolism, metabolism of xenobiotics by cytochrome P450, drug metabolism - cytochrome P450 (Fig. 1D). In addition, IPA analysis showed that DElncRNAs may be involved in cell cycle, cardiovascular system development and function, cell death and survival and cellular development, etc (Fig. 1E).

3.2 Identification and functional analysis of 934 DEmRNAs in gallstone

A total of 934 DEmRNAs, including 396 up-regulated and 538 down-regulated mRNAs in gallstone samples relative to control ones, were identified (Fig. 2A and Table S4 in Supplementary Dataset). DEmRNAs were significantly enriched into 723 BPs, 48 CCs and 96 MFs (Table S5 in Supplementary Dataset). Results of top 30 GO terms showed that they were mainly associated with metabolisms and extracellular matrix, such as hormone metabolic process, extracellular matrix organization, terpenoid metabolic process, diterpenoid metabolic process (Fig. 2B). Consistent with GO enrichment results, those DEmRNAs were significantly enriched into 25 KEGG pathways (Table S6 in Supplementary Dataset), top of which were relevant to metabolism and extracellular matrix related pathways (Fig. 2C), such as retinol metabolism, porphyrin and chlorophyll metabolism and ECM-receptor interaction. Moreover, we found that DEmRNAs had close relationship with metabolic effect of cytochrome P450 on exogenous substances, biosynthesis of steroid hormones, bile secretion, metabolism and protein digestion and absorption, biosynthesis of cofactors, pentose and glucuronic acid conversion metabolic pathways, etc (Fig. 2D).

3.3 Cis- and trans-regulatory functions of DElncRNAs in gallstone disease

By Pearson correlation, 597 DEmRNAs were found to be strongly correlated with 194 DElncRNAs. According to the correlation results, a co-expression network was constructed and visualized by Cytoscape software (Fig. 3A). Based the co-expression network, RP11-399H11.2, VCAN-AS1, LINC01564, RP11-499O7.7, LINC02306, ROR1-AS1, NAV2-AS2, LINC01725, AC005160.3 and RP11-708L7.6 were selected for the following cis-regulation analysis. A total of 51 genes were found to be adjacent to above ten lncRNAs, and the number of adjacent mRNAs for each lncRNA were not the same. For instance, RP11-399H11.2 had 21 adjacent mRNAs, whereas VCAN-AS1 had only two adjacent mRNAs (Fig. 3B). After overlapping adjacent mRNAs with mRNAs in the co-expression network, a cis-regulation network composed of 32 nodes and 34 edges (Fig. 3C) was constructed by Cytoscape software. For example, the down-regulated BCO2 and KLHL31 were cis-regulated by LINC02306. Meanwhile, we investigated the trans-regulatory function of lncRNAs. Firstly, 50 TFs were obtained by overlapping DEmRNAs with TFs in Tfcheckpoint database. Then the corresponding of TFs (DEmRNAs)-lncRNAs pairs were extracted from lncRNA-mRNA co-expression network (Fig. 4A). Next, using TRRUST database, 22 TFs out of 55 TFs were predicted to regulate the transcription of 150 targets, among which 13 targets were in the co-expression network. Thus, by Cytoscape software, we integrated TF-mRNA and lncRNA-mRNA co-expression network to construct the lncRNA-TF-mRNA regulatory network, which was composed of 927 nodes and 1,927 edges (Fig. 4B).

3.4 Construction of ceRNA network in gallstone

By miRWalk, TargentScan and miRDB, 245 miRNAs were found to be targeting 289 DEmRNAs. By starbase, 220 predicted miRNAs were found to interact with 24 DElncRNAs. In consideration of expression pattern of mRNA-miRNA and miRNA-lncRNA pairs, a total of 24 DElncRNAs, 201 DEmRNAs and 120 predicted miRNAs were extracted to construct the ceRNA network (Fig. 4C).

3.5 Verification of DEmRNAs and DElncRNAs by RT-qPCR

Moreover, we used RT-qPCR to validate the sequencing results. Top two up-regulated and down-regulated DEmRNAs and DElncRNAs between gallstone and control samples were selected. The results of RT-qPCR showed that the expressions of AC004692.4, HECW1-IT1, SFRP4 and COMP were significantly higher, whereas the expressions of LINC01564, SLC26A3, RP1-27K12.2 and GSTA2 were remarkedly lower in gallstone samples compared with those in control ones (Fig. 5). These results were consistent with the results of sequencing, suggesting the reliability of the sequencing.

In this study, we explored the differential expression of lncRNAs and mRNAs between GSD patients and controls based on sequencing technology. Functional enrichment analysis of these differential genes showed that they were associated with cytochrome P450, and biosynthesis of steroid hormones, bile secretion, etc. which is closely related to the formation of gallstones.

For GSD, although some researchers have done transcriptome sequencing of gallbladder polyps and gallbladder stones on gallbladder epithelial tissue³⁷, or constructed animal models of gallbladder stones in mice, using healthy mice as controls for sequencing and bioinformatics analysis. However, due to the similarity in the causes and mechanisms of the two diseases of gallbladder cholesterol polyps and gallbladder stones, and the animal model cannot completely replicate the human disease state, they are not the control group of the more ideal control group. The control group selected for this project was taken from patients undergoing surgical treatment for hepatic hemangiomas of liver Ⅳ-Ⅴ segments, which gallbladder tissue that could not be preserved during surgery. Preoperative examination shows that the size and morphology of the gallbladder are normal, the wall is thin and smooth, and the bile is well clear. Postoperative anatomical specimens observed no sediment deposition of bile, clear bile, and pathological examination confirmed as normal gallbladder tissue. Therefore, the control group sample selected for this project may be closer to the state of normal gallbladder in a healthy human body and more comparable.

In cells, cytochrome P450 is mainly distributed on the endoplasmic reticulum and intramitochondrial membrane, as a terminal oxygenase, involved in the synthesis of sterol hormones in the organism and other processes. Cytochrome P450 gene, cytochrome P450 family 7 subfamily members 1 (CYP7A1), CYP7B1, CYP27A1, etc. are involved in catalyzing various steps in cholesterol catabolism and bile acid synthesis³⁸. As a regulator of cholesterol, steroid biosynthesis can control the contraction of gallbladder on the one hand and alter the expression of factors regulating cholesterol metabolism on the other, promoting the secretion of lithogenic stone bile and the formation of stones³⁹. These biological processes and enrichment pathways are directly or indirectly involved in the regulation of gallbladder stone pathogenesis, including protein transport, lipid metabolism, which is in line with our expected results.

Subsequently, we used RT-qPCR to detect the top two up-regulated and down-regulated DEmRNAs and DElncRNAs, respectively, and the detection results were consistent with the sequencing results, indicating that the sequencing results were accurate and reliable. In addition, since the expression of these 8 DEmRNAs and DE-lncRNAs was most significantly different between the two groups, we speculate that they may play an important role in the occurrence and development of gallbladder stones. Of these, SFRP4 (secreted frizzled-related protein 4) is the largest member of the SFRP family and is strongly associated with many diseases, including obesity, type 2 diabetes, and malignancy⁴⁰. Studies have shown an association between human SFRP4 expression and insulin sensitivity and triglyceride levels, and many studies have demonstrated that SFRP4 promotes the de novo synthesis pathway and glycolysis of liver fat in hepatocytes, resulting in decreased islet β cell function, thereby exacerbating lipid buildup and insulin resistance in the liver^40–43. Lipid build-up and insulin resistance may lead to increased hepatic cholesterol secretion, decreased bile acid secretion, and dyskinesias of the gallbladder, leading to supersaturated bile formation, which may promote gallstone formation⁴⁴. The results of this study showed a significant upward trend of SFRP4 in the stone group, and the difference was better, which further supported these conclusions. Therefore, we can speculate that SFRP4 has the potential as a biomarker of gallbladder stones, playing an important role in regulating human cholesterol balance.

Glutathione S-transferase(GST)are one of the most important liver detoxification enzymes in the body⁴⁵ and also play an extremely important role in the metabolism of bile acids. As an important member of the cytoplasmic GSTs family, the Glutathione S-transferase alpha༈GSTA༉superfamily plays an important role in the metabolism of endogenous toxic compounds. GSTA can catalyze a wide range of substrates, bile acids themselves, as well as reactive oxygen species produced under cholestasis, non-polar compounds, etc., can be used as substrates. GSTA1-4 has been found to be significantly reduced in human obstructive cholestasis due to gallstone biliary obstruction⁴⁶. In the process of gallstone formation and pathogenesis, there is a state of cholestasis, which is also confirmed by the significant downregulation of GSTA2 in the stone group in our findings. In the cholestasis caused by stones, the downregulation of liver detoxification enzymes will weaken the liver's treatment of toxic bile acids and aggravate the damage of liver cells, and the specific downregulation mechanism of GSTA2 in this process still needs to be further studied and explored.

In addition, downregulation of LINC01564 was associated with genomic instability and metabolic adaptation to liver cancer^47,48, and SLC26A3 was associated with inflammatory bowel disease and infectious diarrhea⁴⁹. The upward revision of COMP and HECW1-IT1 is more commonly reported in cancer. The regulatory role of these genes in the mechanism of gallstone formation may need to be further studied. The remaining genes have not been reported, and are awaiting further discoveries in the future.

In summary, this study facilitates comprehensive understanding of lncRNA and mRNA expression profiles in GSD and further speculates the mechanisms of gallstone formation, which provided a new perspective for studying the molecular mechanism of the pathogenesis and progression of gallbladder stones. SFRP4 and GSTA2 may play an important regulatory role in GSD, but its more specific molecular regulatory mechanisms still need to be further studied, which also suggests our next research direction.

Data Availability Statement

The datasets generated for this study can be found in the NCBI SRAhttps://www.ncbi.nlm.nih.gov/bioproject/PRJNA825324/,accession number:PRJNA825324.

Competing interests

The authors declare no competing interests.

Author Contributions

CX and PX contributed to conception and design of the study. YS helped with data curation and funding acquisition. YL, QX, WL assisted with sample collection and statistical analysis. CX wrote the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

Funding

This research was funded by the Postgraduate Innovation Foundation of Kunming Medical University (Grant Number:2021S204) for experimental materials. We also received support from the Yunnan Fundamental Research projects (Grant Number:2019FE001-223) and Yunnan Provincial Medical Discipline Reserve Talent Training Program (Grant Number:H-2018067).

Acknowledgements

The authors thank the participants and participating doctors from the Second Affiliated Hospital of Kunming Medical University, China, as well as investigators and staff for making this research possible. They also thank the assistance from medical writers, proof-readers and editors.

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Integrated analysis of differential lncRNA and mRNA expression in cholelithiasis based on high-throughput sequencing and bioinformatics

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Abstract

Figures

1 Introduction

2 Materials And Methods

2.1 Patients and samples selection

2.2 RNA extraction and library construction

2.3 Data processing

2.4 Functional enrichment of DElncRNAs and DEmRNAs

2.5 Construction of co-expression lnRNA-mRNA network and ceRNA network

2.6 Prediction of cis- and trans-regulation

2.7 RT-qPCR

2.8 Statistical analysis

3 Results

3.1 Identification and functional analysis of 304 DElncRNAs in gallstone

3.2 Identification and functional analysis of 934 DEmRNAs in gallstone

3.3 Cis- and trans-regulatory functions of DElncRNAs in gallstone disease

3.4 Construction of ceRNA network in gallstone

3.5 Verification of DEmRNAs and DElncRNAs by RT-qPCR

4 Discussion

5 Conclusion

Declarations

Data Availability Statement

Competing interests

Author Contributions

Funding

Acknowledgements

References

Additional Declarations

Supplementary Files

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