Comparative transcriptome analysis of Labeo calbasu (Hamilton, 1822) from polluted and non-polluted rivers in India

Abstract

Labeo calbasu (L. calbasu) is an important detrivore fish in an ecosystem. So, the present transcriptome study was undertaken in relation to polluted and non-polluted water sources from a natural perennial river system. The Illumina NovaSeq 6000 platform was used to perform transcriptome analysis on liver samples of L. calbasu that were collected from the Ganga and Yamuna rivers. From 8744 differentially expressed genes (DEGs), 2538 were upregulated, and 6206 were downregulated in response to pollution stress. Biologic process (BP), cellular component (CC), molecular function (MF), and Gene Ontology (GO) demonstrated that relevant genes were associated with peptide metabolic process, cytosol, RNA binding, etc. In the Kyoto Encyclopedia of Genes and Genome (KEGG) analysis, ribosomal and metabolic pathways were more important due to the high False discovery rate (FDR) and the involvement of many genes. Transcripts of uncertain coding potential (TUCP) and various RNAs like mRNAs and long noncoding RNAs (lncRNAs) orchestrate fish cellular responses to environmental stressors in polluted waters, where aquatic ecosystems are threatened. FGG mRNA is co-expressed in both up and down-regulation in the liver of L. calbasu. In conclusion, L. calbasu collected from the Yamuna River have highly pollution-induced ribosomal pathways involving genes like Rpl19, rpl23Ae, rps2e, rps10e, rps15e, and rps7e, etc, which is important for pollution biomarker study. RANBP2 and egr1 lncRNA are the most significantly interlinked with ndc1 and fosab lncRNA.

Fig 1. Geographical Map Showing the water and sediment sampling sites.

Water and sediments were collected from the river Ganga at Daspara Ghat, Barrackpore (as a non-polluted site), and Yamuna Ghat, New Delhi (as a polluted site), which was generated by Canva Pro (https://www.canva.com/en_in/pro/).

Fig 2. Volcano Plot of Differential Gene Expression Between Pristine and Contaminated Groups.

The volcano plot illustrates gene expression differences between the pristine and contaminated groups. Each point represents a gene, with red and blue dots indicating significantly upregulated and downregulated genes, respectively. The x-axis represents the log-fold change in gene expression between the two groups, while the y-axis represents the statistical significance (−log10 of the FDR-adjusted P-value). Genes with an FDR-adjusted P-value <  0.05 are considered significantly differentially expressed (DEGs), highlighting key genetic variations associated with contamination.

Fig 3. The GO analysis was conducted using a p-value of less than 0.05, and it was categorized according to

(A) biological process (BP), (B) cellular component (CC), and (C) molecular function (MF). The large red circle represents the highly significant enriched genes, and the other coloured circles are also significantly enriched according to the node size analyzed through the R package. The (D) KEGG pathways for DEGs were analyzed through the R package based on a p-value of < 0.05. The large red circle represents the highly significant enriched genes, and the other coloured circles are also significantly enriched according to the node size.

Fig 4. (A) Overview of ribosome pathways, illustrating key molecular interactions involved in protein synthesis. (B) Treemap visualization of different types of enriched RNAs, mapped using the KEGG pathway database, providing insights into their functional significance.

Fig 5. Circos plot visualization of top 20 upregulated and downregulated mRNAs of significant genes, illustrating differential gene expression patterns and their potential regulatory interactions.

Fig 6. Visualization of 35 significant lncRNA interaction networks, constructed using the STRING database and analyzed through network topology in Cytoscape 3.9.1.

This representation highlights key connections and interactions among lncRNAs, providing insights into their functional roles.