| Autor: |
Kozlova, Anna, Sarygina, Elizaveta, Deinichenko, Kseniia, Radko, Sergey, Ptitsyn, Konstantin, Khmeleva, Svetlana, Kurbatov, Leonid, Spirin, Pavel, Prassolov, Vladimir, Ilgisonis, Ekaterina, Lisitsa, Andrey, Ponomarenko, Elena |
| Předmět: |
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| Zdroj: |
Biology (2079-7737); Dec2023, Vol. 12 Issue 12, p1494, 13p |
| Abstrakt: |
Simple Summary: In this study, we evaluated the differences in the alternative splicing (AS) profiles between normal liver tissue, HepG2 malignant cells, and Huh7 malignant cells using a description of AS profiles as arrays of genes characterized by the degree of AS (defined as the number of detected splice variants per gene). In brief, we demonstrated that this new metric can be employed to successfully identify biological pathways that are influenced by the alterations in AS, thereby utilizing a mathematical algorithm previously developed for gene enrichment analysis based on gene expression profiles. Furthermore, since long-read RNA sequencing allows one to also describe the AS profiles as arrays of quantified single transcript isoforms, we employed Yanai's tissue specificity index (suggested for gene expression analysis) to select groups of genes expressing only one or two splice variants specifically in liver tissue, HepG2 malignant cells, and Huh7 malignant cells, thus providing additional information to that derived from the analysis of gene expression profiles alone. The most of these splice variants were translated into protein products that can contribute to phenotypes of normal and malignant human hepatocytes, thereby making them of interest for the further studying of the mechanisms underlying cell malignization. The long-read RNA sequencing developed by Oxford Nanopore Technologies provides a direct quantification of transcript isoforms, thereby making it possible to present alternative splicing (AS) profiles as arrays of single splice variants with different abundances. Additionally, AS profiles can be presented as arrays of genes characterized by the degree of alternative splicing (the DAS—the number of detected splice variants per gene). Here, we successfully utilized the DAS to reveal biological pathways influenced by the alterations in AS in human liver tissue and the hepatocyte-derived malignant cell lines HepG2 and Huh7, thus employing the mathematical algorithm of gene set enrichment analysis. Furthermore, analysis of the AS profiles as abundances of single splice variants by using the graded tissue specificity index τ provided the selection of the groups of genes expressing particular splice variants specifically in liver tissue, HepG2 cells, and Huh7 cells. The majority of these splice variants were translated into proteins products and appeal to be in focus regarding further insights into the mechanisms underlying cell malignization. The used metrics are intrinsically suitable for transcriptome-wide AS profiling using long-read sequencing. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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