Suppliment Tables: Transcriptome Analysis Sheds Light on the Resilience and Nickel Phytoremediation Potential of Plantago major L.
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Suppliment Tables: Transcriptome Analysis Sheds Light on the Resilience and Nickel Phytoremediation Potential of Plantago major L.
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RNA-Seq data processing Raw reads were processed to remove low-quality reads, trim adaptors, and eliminate poor-quality bases using Trimmomatic v0.39 (Bolger et al., 2014). High-quality clean reads were mapped to the genome of P. major (Lyu et al., 2023) using HISAT2 v2.2.1 (Kim et al., 2015). Gene expression abundance was quantified in terms of Transcripts Per Million (TPM) using Stringtie v2.1.2 (Pertea et al., 2015). Read counts were used to identify different expression genes (DEGs) with the criteria of |log2FC| > 1 and q value < 0.05 by DESeq2 v1.34.0 (Love et al., 2014). DEGs were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. For accurate functional enrichment, we annotated genes using the most recent databases. The GO terms were obtained by annotating the final representative transcripts with blast2go (Conesa et al., 2005) and assigning KEGG Orthology terms using blastkoala (https://www.kegg.jp/blastkoala/). The compared GO and KEGG enrichment were employed by the R package clusterProfiler v4.8.2 (Yu et al., 2012). The GO enrichment analysis was conducted using the Cytoscape plugin BiNGO v3.0.3 (Maere et al., 2005; Shannon et al., 2003). The Enrichment Map v3.3.6 (Merico et al., 2010) and AutoAnnotate v1.4.1 (Kucera et al., 2016) were employed to depict the GO categories that were enhanced as a consequence. The clustering process, utilizing the R package ClusterGVis v.0.1.1 (https://github.com/junjunlab/ClusterGVis) and employing the ComplexHeatmap's K-means clustering of row_km, was used to discern gene clusters corresponding to distinct treatment modalities based on their expression trends. Subsequently, GO enrichment analysis was executed for each of these identified clusters. For transcript factor (TF) analysis, PlantTFDB v4.0 (Jin et al., 2016) was used for TF prediction. Gene set enrichment analysis by the GSEA function in clusterProfiler package (v4.8.2) (Yu et al., 2012) was used to determine whether there was statistically significant bias in the distribution within a TF gene set.