Analysis of lncRNAs and mRNA Expression in the ZBTB1 Knockout Monoclonal EL4 Cell Line and Combined Analysis With miRNAs and circRNAs

In previous experiments, we identified the effect of deletion of the Zbtb1 gene on circRNAs and microRNAs. In this study, we examined the expression profiles of lncRNAs and mRNAs using the RNA-seq method for Zbtb1-deficient EL4 cells and performed a clustering analysis of differentially expressed lncRNAs and mRNAs. GO term histograms and KEGG scatter plots were drawn. For the experimental results, a joint analysis was performed, which predicted the regulatory relationships among lncRNAs, mRNAs, microRNAs and circRNAs. For the regulatory relationship between lncRNAs and target genes, the chromatin structure and the degree of openness were verified for the possible target gene locations regulated by lncRNA using experimental methods such as Hi-C and ATAC-seq. Ultimately, the possible differential regulation of the Brcal and Dennd5d genes by lncRNAs and the differential changes in transcription factor binding sites in the promoter region were identified. For neRNA-regulated target genes with significantly differentially expressed mRNAs, a combined screen was performed, and the final obtained candidate target genes were subjected to GO and KEGG term enrichment analyses. Our results illustrate that the Zbtb1 gene can not only function as a regulatory factor but also regulate EL4 cells from multiple perspectives based on ceRNA theory.

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RNA-Seq Reveals the Expression Profiles of Long Non-Coding RNAs in Lactating Mammary Gland from Two Sheep Breeds with Divergent Milk Phenotype

Animals ◽

10.3390/ani10091565 ◽

2020 ◽

Vol 10 (9) ◽

pp. 1565

Author(s):

Zhiyun Hao ◽

Yuzhu Luo ◽

Jiqing Wang ◽

Jiang Hu ◽

Xiu Liu ◽

...

Keyword(s):

Mammary Gland ◽

Signaling Pathway ◽

Target Genes ◽

Mammary Epithelial Cells ◽

Expression Profiles ◽

Wnt Signaling Pathway ◽

Mammary Epithelial ◽

Differentially Expressed ◽

Rna Seq ◽

Non Coding Rnas

Long non-coding RNAs (lncRNAs) are a kind of non-coding RNA with >200 nucleotides in length. Some lncRNAs have been proven to have clear regulatory functions in many biological processes of mammals. However, there have been no reports on the roles of lncRNAs in ovine mammary gland tissues. In the study, the expression profiles of lncRNAs were studied using RNA-Seq in mammary gland tissues from lactating Small-Tailed Han (STH) ewes and Gansu Alpine Merino (GAM) ewes with different milk yield and ingredients. A total of 1894 lncRNAs were found to be expressed. Compared with the GAM ewes, the expression levels of 31 lncRNAs were significantly up-regulated in the mammary gland tissues of STH ewes, while 37 lncRNAs were remarkably down-regulated. Gene Ontogeny (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that the target genes of differentially expressed lncRNAs were enriched in the development and proliferation of mammary epithelial cells, morphogenesis of mammary gland, ErbB signaling pathway, and Wnt signaling pathway. Some miRNA sponges of differentially expressed lncRNAs, reported to be associated with lactation and mammary gland morphogenesis, were found in a lncRNA-miRNA network. This study reveals comprehensive lncRNAs expression profiles in ovine mammary gland tissues, thereby providing a further understanding of the functions of lncRNAs in the lactation and mammary gland development of sheep.

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Identification and Characterization of New Microrna Biomarkers and Target Genes in Drug-Insensitive CD34+ CML Stem/Progenitor Cells Using Global Comparative RNA-Seq Analyses

Blood ◽

10.1182/blood.v126.23.1567.1567 ◽

2015 ◽

Vol 126 (23) ◽

pp. 1567-1567

Author(s):

Hanyang Lin ◽

Jonathan Zeng ◽

Katharina Rothe ◽

Jens Ruschmann ◽

Oleh Petriv ◽

...

Keyword(s):

Progenitor Cells ◽

Mirna Target ◽

Target Genes ◽

Expression Profiles ◽

Therapeutic Targets ◽

Mapk Signaling ◽

Differentially Expressed ◽

Rna Seq ◽

Cd34 Cells ◽

Differentially Expressed Mirnas

Abstract Therapeutic targeting of BCR-ABL with selective ABL tyrosine kinase inhibitors (TKIs) has led to a significant survival benefit for early phase CML. However, TKI monotherapies are rarely curative, with persistence of leukemic stem cells, emergence of resistance and relapses remaining as challenges. To identify differentially expressed and new miRNAs in CD34+ CML stem/progenitor cells that might serve as potential biomarkers and/or therapeutic targets, we have performed Illumina Deep Sequencing to obtain absolute miRNA expression profiles of highly purified CD34+ cells obtained at newly diagnosed stage from six CML patients. Three of the patients were classified retrospectively, after imatinib (IM) therapy, as IM-responders and three as IM-nonresponders. CD34+ cells isolated from five normal bone marrow (NBM) samples were similarly analyzed as controls. Bioconductor DESeq2 analysis revealed 63 differentially expressed miRNAs between CML and NBM samples (adjusted P<0.05). Most differentially expressed miRNAs identified were down-regulated in CML compared to NBM, while 17 were up-regulated. Interestingly, 12 miRNAs were found to be differentially expressed between the IM-responders and IM-nonresponders. In addition, 34 novel miRNAs were identified in the CD34+ CML stem/progenitor cells. We next validated the sequencing data in a larger cohort of samples. CD34+ cells from IM-responders (n=12), IM-nonresponders (n=10) and normal individuals (n=11) were analyzed using a high-throughput qPCR microfluidics device. These studies confirmed the differential expression in CD34+ CML cells of 32 of the 63 miRNAs (adjusted P<0.05), including an increased level of oncomirs miR-155 and miR-17-92, and a decreased level of tumor suppressors miR-145, miR-151, and miR-452. Importantly, significant changes in some of these miRNAs were detected in CD34+ cells from CML patients (n=60) after three months of nilotinib (NL) treatment compared to the same patient samples before the treatment: expression of 18 miRNAs were normalized after NL therapy, whereas 10 showed little change. To further identify potential miRNA target genes, RNA-seq analysis was performed on the same RNA samples to correlate miRNA profiles with corresponding mRNA expression changes. Bioconductor RmiR analysis was performed to match miRNA target genes whose expression was inversely correlated with the expression of deregulated miRNAs based on three of six prediction algorithms (mirBase, TargetScan, miRanda, tarBase, mirTarget2, and PicTar). We have identified 1,210 differentially expressed mRNAs that are predicted targets of the deregulated miRNAs in the comparison of CML and NBM data. Interestingly, only seven differentially expressed genes were predicted targets of the deregulated miRNAs identified in a comparison of IM-responders and IM-nonresponders. Most of the predicted target genes are involved in cell cycle regulation, MAPK signaling and TGF-beta signaling pathways according to DAVID Bioinformatics Resources analysis, which clusters predicted target genes to known KEGG pathways. To elucidate the biological significance of the differentially expressed miRNAs in TKI-insensitive CML stem/progenitor cells, a number of functional assays were performed. An initial screen of eight miRNAs, selected for their novelty and CML-related potential target genes, was performed by transiently transfecting CML cells with miRNA mimics or inhibitors, and chemically synthesized RNAs which mimic or inhibit mature endogenous miRNAs. Four of the eight miRNA mimics/inhibitors transfected cells displayed significant growth disadvantages and enhanced sensitivity to TKI treatments based on trypan-blue exclusion, thymidine incorporation, apoptosis, and colony-forming cell assays. Q-RT-PCR analysis further showed reduced expression of their predicted target genes in cells transfected with miRNA mimics. Taken together, we have identified aberrant, differentially expressed miRNAs and their target genes in TKI-insensitive CML stem/progenitor cells that may serve as useful biomarkers to predict clinical response of CML patients to TKI therapy and ultimately lead to identification of new therapeutic targets for improved treatment options in CML. Disclosures No relevant conflicts of interest to declare.

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Joint analysis of lncRNA m6A methylome and lncRNA/mRNA expression profiles in gastric cancer

Cancer Cell International ◽

10.1186/s12935-020-01554-8 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Zhi Lv ◽

Liping Sun ◽

Qian Xu ◽

Chengzhong Xing ◽

Yuan Yuan

Keyword(s):

Gastric Cancer ◽

Mrna Expression ◽

Expression Analysis ◽

Target Genes ◽

Expression Profiles ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Joint Analysis ◽

Gene Enrichment Analysis ◽

Gene Enrichment

Abstract Background N6-methyladenosine (m6A) modification might be closely associated with the genesis and development of gastric cancer (GC). Currently, the evidence established by high-throughput assay for GC-related m6A patterns based on long non-coding RNAs (lncRNAs) remains limited. Here, a joint analysis of lncRNA m6A methylome and lncRNA/mRNA expression profiles in GC was performed to explore the regulatory roles of m6A modification in lncRNAs. Methods Three subjects with primary GC were enrolled in our study and paired sample was randomly selected from GC tissue and adjacent normal tissue for each case. Methylated RNA Immunoprecipitation NextGeneration Sequencing (MeRIP-Seq) and Microarray Gene Expression Profiling was subsequently performed. Then co-expression analysis and gene enrichment analysis were successively conducted. Results After data analysis, we identified 191 differentially m6A-methylated lncRNAs, 240 differentially expressed lncRNAs and 229 differentially expressed mRNAs in GC. Furthermore, four differentially m6A-methylated and expressed lncRNAs (dme-lncRNAs) were discovered including RASAL2-AS1, LINC00910, SNHG7 and LINC01105. Their potential target genes were explored by co-expression analysis. And gene enrichment analysis suggested that they might influence the cellular processes and biological behaviors involved in mitosis and cell cycle. The potential impacts of these targets on GC cells were further validated by CCLE database and literature review. Conclusions Four novel dme-lncRNAs were identified in GC, which might exert regulatory roles on GC cell proliferation. The present study would provide clues for the lncRNA m6A methylation-based research on GC epigenetic etiology and pathogenesis.

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RNA-sequencing reveals the expression profiles of tsRNAs and their potential carcinogenic role in cholangiocarcinoma

10.21203/rs.3.rs-35126/v2 ◽

2021 ◽

Author(s):

Li-rong Yan ◽

Ang Wang ◽

Qian Xu ◽

Ben-gang Wang

Keyword(s):

Signaling Pathway ◽

Rna Sequencing ◽

High Throughput ◽

Target Genes ◽

Expression Profiles ◽

Biological Effects ◽

Differentially Expressed ◽

Rna Seq ◽

Normal Tissues ◽

Qrt Pcr

Abstract Background Recently, the incidence of cholangiocarcinoma (CCA) has gradually increased. As CCA has a poor prognosis, the ideal survival rate is scarce for patients. The abnormal expressed tsRNAs may regulate the progression of a variety of tumors, and tsRNAs is expected to become a new diagnostic biomarker of cancer. However, the expression of tsRNAs is obscure and should be elucidated in CCA. Methods High-throughput RNA sequencing technology (RNA-seq) was utilized to determine the overall expression profiles of tsRNAs in 3 pairs CCA and adjacent normal tissues and to screen the tsRNAs that were differentially expressed. The target genes of dysregulated tsRNAs were predicted and the biological effects and potential signaling pathways of these target genes were explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate 11 differentially expressed tRFs with 12 pairs CCA and adjacent normal tissues. Results High-throughput RNA-seq totally demonstrated 535 dysregulated tsRNAs, of which 241 tsRNAs were upregulated and 294 tsRNAs were downregulated in CCA compared with adjacent normal tissues (|log2 (fold change) |≥1 and P value < 0.05). GO and KEGG enrichment analyses indicated that the target genes of dysregulated tRFs (tRF-34-JJ6RRNLIK898HR, tRF-38-0668K87SERM492V and tRF-39-0668K87SERM492E2) were mainly enriched in the Notch signaling pathway, Hippo signaling pathway, cAMP signaling pathway and in growth hormone synthesis, secretion and action, etc. qRT-PCR result showed that tRF-34-JJ6RRNLIK898HR/tRF-38-0668K87SERM492V/tRF-39-0668K87SERM492E2 was down-regulated (P = 0.021) and tRF-20-LE2WMK81 was up-regulated in CCA (P = 0.033). Conclusion Differentially expressed tRFs in CCA are enriched in many pathways associated with neoplasms, which may impact the tumor progression and have potential to be diagnostic biomarkers and therapeutic targets of CCA.

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RNA-sequencing reveals the expression profiles of tsRNAs and their potential carcinogenic role in cholangiocarcinoma

10.21203/rs.3.rs-35126/v1 ◽

2020 ◽

Author(s):

Li-rong Yan ◽

Ang Wang ◽

Qian Xu ◽

Ben-gang Wang

Keyword(s):

Signaling Pathway ◽

High Throughput ◽

Target Genes ◽

Expression Profiles ◽

Biological Effects ◽

Differentially Expressed ◽

P Value ◽

Hippo Signaling ◽

Rna Seq ◽

Normal Tissues

Abstract Background: Recently, the incidence of cholangiocarcinoma (CCA) has gradually increased. As CCA has a poor prognosis, the ideal survival rate is scarce for patients. The abnormal expressed tsRNA may regulate the progression of a variety of tumors, and tsRNA is expected to become a new diagnostic marker of cancer. However, the expression of tsRNA is obscure and should be elucidated in CCA.Methods: We collected CCA tissues and adjacent normal tissues from three patients. High-throughput RNA-seq was utilized to determine the overall expression profiles of tsRNA in CCA and adjacent normal tissues and to screen the tsRNAs that were differentially expressed. The biological effects and potential signaling pathways of dysregulated tsRNAs between the CCA and adjacent normal tissues were explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.Results: High-throughput RNA-seq totally demonstrated 535 dysregulated tsRNAs, of which 241 tsRNAs were upregulated and 294 tsRNAs were downregulated in CCA compared with adjacent normal tissues (|log2 (fold change)| >=1 and p value< 0.05). GO and KEGG enrichment analyses indicated that the target genes of dysregulated tRFs (tRF-34-JJ6RRNLIK898HR, tRF-38-0668K87SERM492V, tRF-39-0668K87SERM492E2) were mainly enriched in the Notch signaling pathway, Hippo signaling pathway, and cAMP signaling pathway and in growth hormone synthesis, secretion and action.Conclusion: Differentially expressed tRFs in CCA are enriched in many pathways associated with neoplasms, which may impact the progression of CCA.

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Construction and Bioinformatics Analysis of the miRNA-mRNA Regulatory Network in Diabetic Nephropathy

Journal of Healthcare Engineering ◽

10.1155/2021/8161701 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Yameng Li ◽

Yukun Xu ◽

Yawei Hou ◽

Rui Li

Keyword(s):

Diabetic Nephropathy ◽

Regulatory Network ◽

Target Genes ◽

Differentially Expressed ◽

Ras Signaling ◽

Regulatory Relationship ◽

Downstream Target ◽

Differentially Expressed Mirnas ◽

Candidate Target ◽

Geo Database

Background. MicroRNA (miRNA) has been confirmed to be involved in the occurrence, development, and prevention of diabetic nephropathy (DN), but its mechanism of action is still unclear. Objective. With the help of the GEO database, bioinformatics methods are used to explore the miRNA-mRNA regulatory relationship pairs related to diabetic nephropathy and explain their potential mechanisms of action. Methods. The DN-related miRNA microarray dataset (GSE51674) and mRNA expression dataset (GSE30122) are downloaded through the GEO database, online analysis tool GEO2R is used for data differential expression analysis, TargetScan, miRTarBase, and miRDB databases are used to predict potential downstream target genes regulated by differentially expressed miRNAs, and intersection with differential genes is used to obtain candidate target genes. According to the regulatory relationship between miRNA and mRNA, the miRNA-mRNA relationship pair is clarified, and the miRNA-mRNA regulatory network is constructed using Cytoscape. DAVID is used to perform GO function enrichment analysis and KEGG pathway analysis of candidate target genes. By GeneMANIA prediction of miRNA target genes and coexpressed genes, the protein interaction network is constructed. Results and Conclusions. A total of 67 differentially expressed miRNAs were screened in the experiment, of which 42 were upregulated and 25 were downregulated; a total of 448 differentially expressed mRNAs were screened, of which 93 were upregulated and 355 were downregulated. Using TargetScan, miRTarBase, and miRDB databases to predict downstream targets of differentially expressed miRNAs, 2283 downstream target genes coexisting in 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 96 candidate target genes. Finally, 44 miRNA-mRNA relationship pairs consisting of 12 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out; further analysis showed that miRNA regulatory network genes may participate in the occurrence and development of diabetic nephropathy through PI3K/Akt, ECM-receptor interaction pathway, and RAS signaling pathway.

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Comprehensive analysis of differentially expressed lncRNAs and associated ceRNA networks in Patau syndrome

10.21203/rs.3.rs-96719/v1 ◽

2020 ◽

Author(s):

Jieping Chen ◽

Jun Zhou ◽

Zhiyang Hu ◽

Huiyan He ◽

Weiguo Sui ◽

...

Keyword(s):

Cord Blood ◽

Peripheral Blood ◽

Target Gene ◽

Target Genes ◽

Expression Profiles ◽

Differentially Expressed ◽

Rna Seq ◽

Biological Functions ◽

Patau Syndrome ◽

Differentially Expressed Mirnas

Abstract Objective: LncRNAs are a class of competing for endogenous RNAs (ceRNAs) with no coding ability and have miRNA binding sites that competitively bind to miRNAs and inhibit miRNA-mediated regulation of target genes. In recent years, an increasing number of studies have recognized the biological functions of lncRNAs.Methods: Illumina RNA-Seq technology was used to analyze the cord blood with Patau syndrome (PS) fetal and the peripheral blood of pregnant women to obtain differential expression profiles of lncRNAs, miRNAs, and mRNAs. Further, Combined with bioinformatics analysis of the biological functions of differentially expressed lncRNAs (DElncRNAs). Results: The results showed that 467 DElncRNAs, 8512 differentially expressed mRNAs (DEmRNAs), and 18 differentially expressed miRNAs (DEmiRNAs) were found to be co-expressed in cord blood and peripheral blood. The hsa-miR-15a-5p is located on chromosome 13. We constructed the ceRNA network with hsa-miR-15a-5p, lncRNAs as the bait, and mRNAs as the targe. Conclusion: We consider that the DElncRNAs may indirectly regulate the target gene CLASRP or KARS by binding hsa-miR-15a-5p to participate in the occurrence of PS.

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Effects of Dinotefuran on Brain miRNA Expression Profiles in Young Adult Honey Bees (Hymenopptera: Apidae)

Journal of Insect Science ◽

10.1093/jisesa/ieaa131 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Minjie Huang ◽

Jie Dong ◽

Haikun Guo ◽

Deqian Wang

Keyword(s):

Honey Bee ◽

Honey Bees ◽

Target Genes ◽

Expression Profiles ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Lethal Concentration ◽

Wild Plants ◽

Small Rna Sequencing ◽

Candidate Target

Abstract Honey bees are important pollinators of wild plants and crops. MicroRNAs (miRNAs) are endogenous regulators of gene expression. In this study, we initially determined that the lethal concentration 50 (LC50) of dinotefuran was 0.773 mg/l. Then, the expression profiles and differentially expressed miRNAs (DE miRNAs) in honey bee brains after 1, 5, and 10 d of treatment with the lethal concentration 10 (LC10) of dinotefuran were explored via deep small-RNA sequencing and bioinformatics. In total, 2, 23, and 27 DE miRNAs were identified after persistent exposure to the LC10 of dinotefuran for 1, 5, and 10 d, respectively. Some abundant miRNAs, such as ame-miR-375-3p, ame-miR-281-5p, ame-miR-3786-3p, ame-miR-10-5p, and ame-miR-6037-3p, were extremely significantly differentially expressed. Enrichment analysis suggested that the candidate target genes of the DE miRNAs are involved in the regulation of biological processes, cellular processes, and behaviors. These results expand our understanding of the regulatory roles of miRNAs in honey bee Apis mellifera (Hymenopptera: Apidae) responses to neonicotinoid insecticides and facilitate further studies on the functions of miRNAs in honey bees.

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Genome-wide transcriptome profiling uncovers differential miRNAs and lncRNAs in ovaries of Hu sheep at different developmental stages

Scientific Reports ◽

10.1038/s41598-021-85245-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Samina Shabbir ◽

Prerona Boruah ◽

Lingli Xie ◽

Muhammad Fakhar-e-Alam Kulyar ◽

Mohsin Nawaz ◽

...

Keyword(s):

Target Genes ◽

Expression Profiles ◽

Ovarian Follicle ◽

Follicular Development ◽

Differentially Expressed ◽

Ovary Development ◽

Estrogen Metabolism ◽

Genome Wide ◽

Micro Rnas ◽

Hu Sheep

AbstractOvary development is an important determinant of the procreative capacity of female animals. Here, we performed genome-wide sequencing of long non-coding RNAs (lncRNAs) and mRNAs on ovaries of 1, 3 and 8 months old Hu sheep to assess their expression profiles and roles in ovarian development. We identified 37,309 lncRNAs, 45,404 messenger RNAs (mRNAs) and 330 novel micro RNAs (miRNAs) from the transcriptomic analysis. Six thousand, seven hundred and sixteen (6716) mRNAs and 1972 lncRNAs were significantly and differentially expressed in ovaries of 1 month and 3 months old Hu sheep (H1 vs H3). These mRNAs and target genes of lncRNAs were primarily enriched in the TGF-β and PI3K-Akt signalling pathways which are closely associated with ovarian follicular development and steroid hormone biosynthesis regulation. We identified MSTRG.162061.1, MSTRG.222844.7, MSTRG.335777.1, MSTRG.334059.16, MSTRG.188947.6 and MSTRG.24344.3 as vital genes in ovary development by regulating CTNNB1, CCNA2, CDK2, CDC20, CDK1 and EGFR expressions. A total of 2903 mRNAs and 636 lncRNAs were differentially expressed in 3 and 8 months old ovaries of Hu sheep (H3 vs H8); and were predominantly enriched in PI3K-Akt, progesterone-mediated oocyte maturation, estrogen metabolism, ovulation from the ovarian follicle and oogenesis pathways. These lncRNAs were also found to regulate FGF7, PRLR, PTK2, AMH and INHBA expressions during follicular development. Our result indicates the identified genes participate in the development of the final stages of follicles and ovary development in Hu sheep.

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Pineal gland transcriptomic profiling reveals the differential regulation of lncRNA and mRNA related to prolificacy in STH sheep with two FecB genotypes

BMC Genomic Data ◽

10.1186/s12863-020-00957-w ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Chunyan Li ◽

Xiaoyun He ◽

Zijun Zhang ◽

Chunhuan Ren ◽

Mingxing Chu

Keyword(s):

Pineal Gland ◽

Expression Pattern ◽

Noncoding Rna ◽

Target Genes ◽

Expression Profiles ◽

Enrichment Analysis ◽

Rna Seq ◽

Important Regulator ◽

Gsh Metabolism ◽

Transcriptome Expression

Abstract Background Long noncoding RNA (lncRNA) has been identified as important regulator in hypothalamic-pituitary-ovarian axis associated with sheep prolificacy. However, little is known of their expression pattern and potential roles in the pineal gland of sheep. Herein, RNA-Seq was used to detect transcriptome expression pattern in pineal gland between follicular phase (FP) and luteal phase (LP) in FecBBB (MM) and FecB++ (ww) STH sheep, respectively, and differentially expressed (DE) lncRNAs and mRNAs associated with reproduction were identified. Results Overall, 135 DE lncRNAs and 1360 DE mRNAs in pineal gland between MM and ww sheep were screened. Wherein, 39 DE lncRNAs and 764 DE mRNAs were identified (FP vs LP) in MM sheep, 96 DE lncRNAs and 596 DE mRNAs were identified (FP vs LP) in ww sheep. Moreover, GO and KEGG enrichment analysis indicated that the targets of DE lncRNAs and DE mRNAs were annotated to multiple biological processes such as phototransduction, circadian rhythm, melanogenesis, GSH metabolism and steroid biosynthesis, which directly or indirectly participate in hormone activities to affect sheep reproductive performance. Additionally, co-expression of lncRNAs-mRNAs and the network construction were performed based on correlation analysis, DE lncRNAs can modulate target genes involved in related pathways to affect sheep fecundity. Specifically, XLOC_466330, XLOC_532771, XLOC_028449 targeting RRM2B and GSTK1, XLOC_391199 targeting STMN1, XLOC_503926 targeting RAG2, XLOC_187711 targeting DLG4 were included. Conclusion All of these differential lncRNAs and mRNAs expression profiles in pineal gland provide a novel resource for elucidating regulatory mechanism underlying STH sheep prolificacy.

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