The introduction of RNA-sequencing (RNA-Seq) technology into biological research has encouraged bioinformatics developers to build various analysis pipelines. The chosen bioinformatics pipeline mostly depends on the research goals and organisms of interest because a single pipeline may not be optimal for all cases. As the first step in most pipelines, alignment has become a crucial step that will affect the downstream analysis. Each alignment tool has its default and parameter settings to maximise the output. However, this poses great challenges for the researchers as they need to determine the alignment tool most compatible with the correct settings to analyse their samples accurately and efficiently. Therefore, in this study, the duplication of real data of the HeLa RNA-seq was used to evaluate the effects of data qualities on four commonly used RNA-Seq tools: HISAT2, Novoalign, TopHat and Subread. Furthermore, these data were also used to evaluate the optimal settings of each aligner for our sample. These tools’ performances, precision, recall, F-measure, false discovery rate, error tolerance, parameter stability, runtime and memory requirements were measured. Our results showed significant differences between the settings of each alignment tool tested. Subread and TopHat exhibited the best performance when using optimised parameters setting. In contrast, the most reliable performance was observed for HISAT2 and Novoalign when the default setting was used. Although HISAT2 was the fastest alignment tool, the highest accuracy was achieved using Novoalign with the default setting.

Background: Recent years have witnessed major development of novel therapeutic agents like chemotherapy, targeted therapy and immune checkpoint inhibitors for cervical cancer. However, cervical cancer remains prevalent, leading to a large number of deaths worldwide. A better understanding of the cervical cancer biology and signaling pathways might lead to the development of targeted therapies in reducing the incidence and mortality rate. Methods: In this study, the RNA-Seq reads of HeLa cells treated with C. nutans were compared to the untreated sample. The reads of these two sample groups were firstly aligned to the human reference genome. The results in BAM files format that were generated were then sorted before being assembled. The output of assembly which was in coverage table form was ready for downstream statistical analyses for differential expression. Differentially expressed genes were obtained and the cell-death related pathway were identified by canonical pathway, QIAGEN Ingenuity Pathway Analysis (IPA). The verification of significant genes was carried out using qRT-PCR by including GAPDH as a housekeeping gene Results: With this, we identified a total of 668 upregulated and 479 downregulated analysis-ready genes across observations upon cut-off setting log2FoldChange at 0.5 and P-value 0.05. A total of 28 cell-death related canonical pathways and 4 activation of cell-death related functions were identified. Upon analyses, we identified four significant genes (Casp9, KAI1, REL and FOXO4) that hold important role in promoting cell death. These findings were also verified against the quantification using qRT-PCR by including GAPDH as a housekeeping gene. Conclusions: This study provides an insight on the potential role of DCM fraction of C. nutans in activating Casp9, KAI1, REL and FOXO4 genes in mediating apoptosis in cervical cancer cells.

Background Recent years have witnessed major development of novel therapeutic agents like chemotherapy, targeted therapy and immune checkpoint inhibitors for cervical cancer. However, cervical cancer remains prevalent, leading to a large number of deaths worldwide. A better understanding of the cervical cancer biology and signaling pathways might lead to the development of targeted therapies in reducing the incidence and mortality rate. Methods In this study, the RNA-Seq reads of HeLa cells treated with C. nutans were compared to the untreated sample. The reads of these two sample groups were firstly aligned to the human reference genome. The results in BAM files format that were generated were then sorted before being assembled. The output of assembly which was in coverage table form was ready for downstream statistical analyses for differential expression. Differentially expressed genes were obtained and the cell-death related pathway were identified by canonical pathway, QIAGEN Ingenuity Pathway Analysis (IPA). The verification of significant genes was carried out using qRT-PCR by including GAPDH as a housekeeping gene Results With this, we identified a total of 668 upregulated and 479 downregulated analysis-ready genes across observations upon cut-off setting log2FoldChange at 0.5 and P-value 0.05. A total of 28 cell-death related canonical pathways and 4 activation of cell-death related functions were identified. Upon analyses, we identified four significant genes (Casp9, KAI1, REL and FOXO4) that hold important role in promoting cell death. These findings were also verified against the quantification using qRT-PCR by including GAPDH as a housekeeping gene. Conclusions This study provides an insight on the potential role of DCM fraction of C. nutans in activating Casp9, KAI1, REL and FOXO4 genes in mediating apoptosis in cervical cancer cells.