The need for understanding the influence of the transcriptome on the phenotype of the cell in a clinical setting has governed the development of new generations of sequencing technologies. The first technology to enable a simultaneous detection of expression of a set of genes were DNA-microarrays. It was followed by the development of direct sequencing of RNA, called RNA-Seq, which was made possible by the next-generation sequencing technologies. Nanopore sequencing technology allows for the sequencing of whole transcripts, thus facilitating the bioinformatic analysis of the transcriptome. Due to its established role in the medical diagnostics, the method of reverse transcription and quantitative polymerase chain reaction has established itself as the “golden standard” of quantifying the expression level of individual genes.
As part of the master’s thesis, we compared the results of the analysis of differentially expressed genes between the HepG2 wild-type and the SC5D knockout cell line, which were detected by DNA-microarrays and nanopore sequencing. The expression was also measured by RT-qPCR and compared with the results of the other two methods. By nanopore sequencing, we determined a statistically significant change in expression of several genes, which was not previously detected by microarray analysis. In calculating the correlation between the
technologies and the results of the change in gene expression determined by RT-qPCR, we confirmed that the two methods are comparable. At the same time, the correlation with the results of the microarray analysis was surprisingly higher. We also report that we have for the first time determined the correlation between the values of the binary logarithm of the fold change in expression for statistically significantly expressed genes determined by both the microarrays and nanopore sequencing. The correlation factor is higher than the comparisons between the sequencing technologies using the sequencing by synthesis approach and microarrays that are described in the literature. During the master’s thesis, we developed a pipeline for bioinformatics analysis, compared tools for determining the differential expression of genes and successfully performed the gene set enrichment analysis. These will help develop further hypotheses on the role of the knocked-out gene SC5D in the cell phenotype.
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