Integrated analysis of lncRNA-mediated ceRNA network involved in immune regulation in the spleen of Meishan piglets

Abstract

Meishan pigs are a famous local pig breed in China, with high fertility and early sexual maturity, and stronger immunity compared to other breeds. The spleen is the largest lymphoid organ in pigs and performs essential functions, such as those relating to immunity and haematopoiesis. The invasion of many pathogenic microorganisms in pigs is associated with spleen damage. Long non-coding RNAs participate in a broad range of biological processes and have been demonstrated to be associated with splenic immune regulation. However, the expression network of mRNAs and lncRNAs in the spleen of Meishan pigs remains unclear. This study collected spleen tissues from Meishan piglets at three different ages as a model, and mRNA and lncRNA transcripts were profiled for each sample. Additionally, 1,806 differential mRNAs and 319 differential lncRNAs were identified. A complicated interaction between mRNAs and lncRNAs was identified via WGCNA, demonstrating that lncRNAs are a crucial regulatory component in mRNA. The results show that the modules black and red have similar mRNA and lncRNA transcription patterns and are mainly involved in the process of the immune defense response. The core genes (DHX58 and IFIT1) and key lncRNAs (TCONS-00002102 and TCONS-00012474) of piglet spleen tissue were screened using the ceRNA network. The expression of these genes is related to the immune response of pigs. Our research may contribute to a further understanding of mRNA and lncRNA expression in the spleen of piglets, and provide new ideas to improve the disease resistance of piglets.

Whole transcriptome sequencing reveals key genes and ceRNA regulatory networks associated with pimpled eggs in hens

“…Known lncRNAs were identified based on the criterion of genobiotype = “lncRNA.” To identify novel lncRNAs, we employed the following criteria to screen the assembled transcripts: 1) The transcript length ≥ 200 bp and exon number ≥ 2; 2) FPKM value for Transcripts ≥ 0.1; 3) Transcripts annotated with “i”, “x”, “u”, “o” or “e” were left for further screening ( Xiao et al, 2022 ). Finally, the coding potential of transcripts that passed the above filtering criteria was assessed using 4 coding potential assessment software CNCI, CPC2 and PLEK ( Kong et al, 2007 ; Sun et al, 2013 ; Li et al, 2014 ; Shi et al, 2022 ). The intersection of the results of the 4 software identifications identified novel lncRNAs.…”