Long non-coding RNAs (lncRNAs) (>200 nt) are expressed at levels lower than those of the protein-coding mRNAs, and in all eukaryotic model species where they have been characterized, they are transcribed from thousands of different genomic . In humans, some four dozen lncRNAs have been studied in detail, and they have been shown to play important roles in transcriptional regulation, acting in conjunction with transcription factors and epigenetic marks to modulate the tissue-type specific programs of transcriptional gene activation and repression. In , around 10,000 lncRNAs have been identified in previous works. However, the limited number of RNA-sequencing (RNA-seq) libraries that had been previously assessed, together with the use of old and incomplete versions of the genome and protein-coding transcriptome annotations, have hampered the identification of all lncRNAs expressed in the parasite. Here we have used 633 publicly available RNA-seq libraries from whole worms at different stages (n = 121), from isolated tissues (n = 24), from cell-populations (n = 81), and from single-cells (n = 407). We have assembled a set of 16,583 lncRNA transcripts originated from 10,024 genes, of which 11,022 are novel lncRNA transcripts, whereas the remaining 5,561 transcripts comprise 120 lncRNAs that are identical to and 5,441 lncRNAs that have gene overlap with lncRNAs already reported in previous works. Most importantly, our more stringent assembly and filtering pipeline has identified and removed a set of 4,293 lncRNA transcripts from previous publications that were in fact derived from partially processed mRNAs with intron retention. We have used weighted gene co-expression network analyses and identified 15 different gene co-expression modules. Each parasite life-cycle stage has at least one highly correlated gene co-expression module, and each module is comprised of hundreds to thousands lncRNAs and mRNAs having correlated co-expression patterns at different stages. Inspection of the top most highly connected genes within the modules' networks has shown that different lncRNAs are hub genes at different life-cycle stages, being among the most promising candidate lncRNAs to be further explored for functional characterization.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752179PMC
http://dx.doi.org/10.3389/fgene.2019.00823DOI Listing

Publication Analysis

Top Keywords

gene co-expression
16
lncrna transcripts
12
lncrnas
10
weighted gene
8
long non-coding
8
hub genes
8
genes life-cycle
8
life-cycle stages
8
previous works
8
rna-seq libraries
8

Similar Publications

Integrating machine learning with mendelian randomization for unveiling causal gene networks in glioblastoma multiforme.

Discov Oncol

January 2025

Department of Medical Imaging, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, China.

Background: Glioblastoma multiforme (GBM) is a highly aggressive brain cancer with poor prognosis and limited treatment options. Despite advances in understanding its molecular mechanisms, effective therapeutic strategies remain elusive due to the tumor's genetic complexity and heterogeneity.

Methods: This study employed a comprehensive analysis approach integrating 113 machine learning algorithms with Mendelian Randomization (MR) analysis to investigate the molecular underpinnings of GBM.

View Article and Find Full Text PDF

Association of Arachidonic Acid Metabolism Related Genes With Endometrial Immune Microenvironment and Oxidative Stress in Coupes With Recurrent Implantation Failure.

Am J Reprod Immunol

January 2025

State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, China.

Background: Alterations in lipid metabolism were reported to impact human fertility; however, there is limited evidence on the association of lipid metabolism with embryo implantation as well as the etiology of recurrent implantation failure (RIF), especially regarding arachidonic acid metabolism.

Methods: Experimental verification research (16 RIF patients and 30 control patients) based on GEO database analysis (24 RIF patients and 24 control patients). The methods in bioinformatics included differential gene screening, functional enrichment analysis, protein-protein interaction network, cluster analysis, weighted gene co-expression network analysis, and so forth.

View Article and Find Full Text PDF

Background: Lung transplantation is the only effective therapeutic option for patients with end-stage lung disease. However, ischemia/reperfusion injury (IRI) during transplantation is a leading cause of primary graft dysfunction (PGD). Ferroptosis, a form of iron-dependent cell death driven by lipid peroxidation, has been implicated in IRI across various organs.

View Article and Find Full Text PDF

Purpose: Glioma is the most prevalent tumor of the central nervous system. The poor clinical outcomes and limited therapeutic efficacy underscore the urgent need for early diagnosis and an optimized prognostic approach for glioma. Therefore, the aim of this study was to identify sensitive biomarkers for glioma.

View Article and Find Full Text PDF

Age-related muscle wasting, sarcopenia is an extensive loss of muscle mass and strength with age and a major cause of disability and accidents in the elderly. Mechanisms purported to be involved in muscle ageing and sarcopenia are numerous but poorly understood, necessitating deeper study. Hence, we employed high-throughput RNA sequencing to survey the global changes in protein-coding gene expression occurring in skeletal muscle with age.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!