2.4. Expression profiling based on long-reads
The long-read digital MinION signals were converted from POD5 to the FAST5 format using the pod5-file-format program (https://github.com/nanoporetech/pod5-file-format). Next, the transcriptomic sequences were basecalled by Guppy v.6.0.0 (https://nanoporetech.com/support). The FASTQ raw reads were quality-checked and passed to the mapping steps (as a referenceRiccia fluitans genome), supported by minimap2 v.2.26 software with default parameters . Similar to short-reads analysis, the gene expression profiles produced by the long-reads sequencing method were also estimated using stringtie, featureCounts and DESeq2 softwares. For transcript level expression quantification, the above proceed BAM files were used again by bambu v3.2.4 software to estimate the transcript count expression matrix for multiple samples . The differentially expressed genes (DEGs) and differentially expressed transcripts (DETs) statistical significance was determined with the following parameters: padj < 0.05 and absolute log2FoldChange > 1. The results from both methods (short - and long-reads) were intersected and only common results were considered as final transcriptomic DEGs and DETs results. Additionally, the transcriptomic sequences were divided into coding and non-coding groups. Two potential coding prediction softwares, CPC2 v.1.0.1 and PLEK v.1.2 , classified transcripts into separate groups. According to those classifications, significant genes were named differentially protein-coding genes and differentially long non-coding RNAs (DELs). If there were discrepancies in identification of coding potential between the two programs, those RNA were signed as OtherRNA. Relationships between DEGs, DELs and OtherRNA were estimated by co-expression analysis. Pairs of DEGs-DELs, DEGs-OtherRNA, and DELs-OtherRNA with similar transcriptomic profiles were characterized based on the Pearson correlation coefficient (r > 0.8 and p < 0.05). The results were visualised using the ggplot2 v.3.4.4 and circlize v.0.4.15 R Bioconductor v.3.18 packages.