Integrated analysis of lncRNAs and mRNAs reveals key trans-target genes associated with ETEC-F4ac adhesion phenotype in porcine small intestine epithelial cells

Augustino, Serafino M. A.; Xu, Qiang; Liu, Xueqin; Mi, Siyuan; Shi, Liangyu; Liu, Yibing; Wen, Hui; Wang, Di; Liu, Lei; Zhang, Qin; Yu, Ying

doi:10.1186/s12864-020-07192-8

Cited by 14 publications

(10 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As anticipated, expression profiles of lncRNAs and mRNAs vary between the AN and SE groups. Comparisons revealed 772 DE mRNAs and 190 DE lncRNAs, of which the number of upregulated DE mRNAs and DE lncRNAs were relatively lower than that of downregulated DE mRNAs and DE lncRNAs, similar to the results reported previously for a variety E. coli challenged experiments ( 42 – 44 ). Hence, an unstable transcriptional profile may be the main reason for the serve diarrhea seen in SE lambs.…”

Section: Discussionsupporting

confidence: 88%

Insights Into Long Non-Coding RNA and mRNA Expression in the Jejunum of Lambs Challenged With Escherichia coli F17

Chen

Zhang

et al. 2022

Front. Vet. Sci.

View full text Add to dashboard Cite

It has long been recognized that enterotoxigenic Escherichia coli (ETEC) is the major pathogen responsible for vomiting and diarrhea. E. coli F17, a main subtype of ETEC, is characterized by high morbidity and mortality in young livestock. However, the transcriptomic basis underlying E. coli F17 infection has not been fully understood. In the present study, RNA sequencing was conducted to explore the expression profiles of mRNAs and long non-coding RNAs (lncRNAs) in the jejunum of lambs who were identified as resistant or sensitive to E. coli F17 that was obtained in a challenge experiment. A total of 772 differentially expressed (DE) mRNAs and 190 DE lncRNAs were detected between the E. coli F17—resistance and E. coli F17-sensitive lambs (i.e., TFF2, LOC105606142, OLFM4, LYPD8, REG4, APOA4, TCONS_00223467, and TCONS_00241897). Then, a two-step machine learning approach (RX) combination Random Forest and Extreme Gradient Boosting were performed, which identified 16 mRNAs and 17 lncRNAs as potential biomarkers, within which PPP2R3A and TCONS_00182693 were prioritized as key biomarkers involved in E. coli F17 infection. Furthermore, functional enrichment analysis showed that peroxisome proliferator-activated receptor (PPAR) pathway was significantly enriched in response to E. coli F17 infection. Our finding will help to improve the knowledge of the mechanisms underlying E. coli F17 infection and may provide novel targets for future treatment of E. coli F17 infection.

show abstract

Section: Discussionsupporting

confidence: 88%

Insights Into Long Non-Coding RNA and mRNA Expression in the Jejunum of Lambs Challenged With Escherichia coli F17

Chen

Zhang

et al. 2022

Front. Vet. Sci.

View full text Add to dashboard Cite

show abstract

“…We used BEDTools.v2.1.2 software to search for cis -target genes from all identified mRNAs located within 10 kb upstream and downstream of DElncRNAs. The trans target genes were predicted from DElncRNAs and DEmRNAs by correlation analysis between lncRNAs and mRNAs [ 32 ]. Finally, 364 and 101,094 DElncRNA cis -target pairs were identified in Mock-vs-PDCoV_12h, and 34 and 2902 DElncRNA trans -target pairs were identified in the other comparison group (Additional file 4 : Table S4–1, Table S4–2, Table S4–3, and Table S4–4).…”

Section: Resultsmentioning

confidence: 99%

Identification and integrated analysis of lncRNAs and miRNAs in IPEC-J2 cells provide novel insight into the regulation of the innate immune response by PDCoV infection

Jiang

Chen

et al. 2022

BMC Genomics

View full text Add to dashboard Cite

Background Noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), are pivotal regulators involved in the pathogenic mechanism of multiple coronaviruses. Porcine deltacoronavirus (PDCoV) has evolved multiple strategies to escape the innate immune response of host cells, but whether ncRNAs are involved in this process during PDCoV infection is still unknown. Results In this study, the expression profiles of miRNAs, lncRNAs and mRNAs in IPEC-J2 cells infected with PDCoV at 0, 12 and 24 hours postinfection (hpi) were identified through small RNA and RNA sequencing. The differentially expressed miRNAs (DEmiRNAs), lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were screened from the comparison group of IPEC-J2 cells at 0 and 12 hpi as well as the comparison group of IPEC-J2 cells at 12 and 24 hpi. The target genes of these DEncRNAs were predicted. The bioinformatics analysis of the target genes revealed multiple significantly enriched functions and pathways. Among them, the genes that were associated with innate immunity were specifically screened. The expression of innate immunity-related ncRNAs and mRNAs was validated by RT–qPCR. Competing endogenous RNA (ceRNA) regulatory networks among innate immunity-related ncRNAs and their target mRNAs were established. Moreover, we found that the replication of PDCoV was significantly inhibited by two innate immunity-related miRNAs, ssc-miR-30c-3p and ssc-miR-374b-3p, in IPEC-J2 cells. Conclusions This study provides a data platform to conduct studies of the pathogenic mechanism of PDCoV from a new perspective and will be helpful for further elucidation of the functional role of ncRNAs involved in PDCoV escaping the innate immune response.

show abstract

“…The expression of functional genes was regulated by various factors, such as TFs, miRNAs, and lncRNAs [ 53 – 55 ]. As transcriptional regulators, lncRNAs affect the expression of functional genes directly or indirectly [ 56 ].…”

Section: Discussionmentioning

confidence: 99%

“…To determine the cis-target transcripts of lncRNAs, we searched for PCTs within 100 Kb upstream and 100 Kb downstream of the lncRNAs [ 53 ]. The Pearson correlation coefficient (PCC) between the lncRNA and the corresponding PCT was then calculated based on their expression levels.…”

Section: Methodsmentioning

confidence: 99%

Integrated analysis of long non-coding RNAs and mRNAs reveals the regulatory network of maize seedling root responding to salt stress

et al. 2022

View full text Add to dashboard Cite

Background Long non-coding RNAs (lncRNAs) play important roles in response to abiotic stresses in plants, by acting as cis- or trans-acting regulators of protein-coding genes. As a widely cultivated crop worldwide, maize is sensitive to salt stress particularly at the seedling stage. However, it is unclear how the expressions of protein-coding genes are affected by non-coding RNAs in maize responding to salt tolerance. Results The whole transcriptome sequencing was employed to investigate the differential lncRNAs and target transcripts responding to salt stress between two maize inbred lines with contrasting salt tolerance. We developed a flexible, user-friendly, and modular RNA analysis workflow, which facilitated the identification of lncRNAs and novel mRNAs from whole transcriptome data. Using the workflow, 12,817 lncRNAs and 8,320 novel mRNAs in maize seedling roots were identified and characterized. A total of 742 lncRNAs and 7,835 mRNAs were identified as salt stress-responsive transcripts. Moreover, we obtained 41 cis- and 81 trans-target mRNA for 88 of the lncRNAs. Among these target transcripts, 11 belonged to 7 transcription factor (TF) families including bHLH, C2H2, Hap3/NF-YB, HAS, MYB, WD40, and WRKY. The above 8,577 salt stress-responsive transcripts were further classified into 28 modules by weighted gene co-expression network analysis. In the salt-tolerant module, we constructed an interaction network containing 79 nodes and 3081 edges, which included 5 lncRNAs, 18 TFs and 56 functional transcripts (FTs). As a trans-acting regulator, the lncRNA MSTRG.8888.1 affected the expressions of some salt tolerance-relative FTs, including protein-serine/threonine phosphatase 2C and galactinol synthase 1, by regulating the expression of the bHLH TF. Conclusions The contrasting genetic backgrounds of the two inbred lines generated considerable variations in the expression abundance of lncRNAs and protein-coding transcripts. In the co-expression networks responding to salt stress, some TFs were targeted by the lncRNAs, which further regulated the salt tolerance-related functional transcripts. We constructed a regulatory pathway of maize seedlings to salt stress, which was mediated by the hub lncRNA MSTRG.8888.1 and participated by the bHLH TF and its downstream target transcripts. Future work will be focused on the functional revelation of the regulatory pathway.

show abstract

Integrated analysis of lncRNAs and mRNAs reveals key trans-target genes associated with ETEC-F4ac adhesion phenotype in porcine small intestine epithelial cells

Cited by 14 publications

References 29 publications

Insights Into Long Non-Coding RNA and mRNA Expression in the Jejunum of Lambs Challenged With Escherichia coli F17

Insights Into Long Non-Coding RNA and mRNA Expression in the Jejunum of Lambs Challenged With Escherichia coli F17

Identification and integrated analysis of lncRNAs and miRNAs in IPEC-J2 cells provide novel insight into the regulation of the innate immune response by PDCoV infection

Integrated analysis of long non-coding RNAs and mRNAs reveals the regulatory network of maize seedling root responding to salt stress

Contact Info

Product

Resources

About