Adela Mahida Putri

Homework 2 for Data 101 with Prof. Alraee

A comparative transcriptomic analysis, across different varietiescultivars, tissues, and flower developmental stages, was conducted to identify candidate TFs potentially regulating NUDX1-1a expression. Two different transcriptomic libraries described in Figure 2 3 were used. NUDX1-1a is highly transcribed from stage 2 and, thus, served as a proxy to define high- and low-expression groups for Ddifferential gene expression analysis. of each transcriptomic library was performed using DESeq2 (Love et al., 2014) to compare transcriptomic profiles between selected conditions, with NUDX1-1a expression levels used as a proxy to define high- and low-expression groups. The comparisons included: 1) Same developmental stage across different varietiescultivars, contrasting cultivars varieties with high NUDX1 1a expressionn, (R. chinensis ‘Old Blush’O (OB or R. × hybrida cultivar Papa Meilland®PM)) with one lacking NUDX1 1a expression (, (R. × hybrida cultivar Fetera®FE)). 2) Different developmental stages within the same varietycultivar (OB or PM), for example, comparing stage 1 (low expression) and stage 2 or 3 (high expression) in the same genotype with increasing NUDX1 1a expression during flower development., OB or PM. 3) Different tissues within the same varietycultivar, comparing leaves (low expression) with petals at stage 2 or 3 (high expression). In total 13 comparisons between conditions were performed. TFs typically are expressed in specific temporal windows before downstream target genes and once the target gene starts being transcribed, the expression of the TFs often decreases (Marand et al., 2023). Therefore, only stage 2 and 3 were selected for the comparisons between developmental stages as we hypothesize that at stage 4 transcripts of candidate TFs may not be significantly different between comparisons. After normalization and variance stabilization, the genes were found to be differentially expressed with an adjusted p-value (FDR) < 0.01. Among these, genes were significantly upregulated if the associated log2Foldchange was > 1 and genes were downregulated if < -1 in each condition relative to their comparison Figure 2 12. The distribution of differentially expressed genes (DEGs) was visualized in the MA plot and volcano plot. The DEGs from each comparison were annotated with the official Old Blush genome annotation (Raymond et al., 2018) along with Gene Ontology (GO) enrichment (Supp Figures 1 to 4). From the DEGs of each comparison only upregulated the genes classified as upregulated genes were extracted and combined, resulting in 98 common upregulated genes present in all comparisons including 3 of the 5 copies of NUDX1 1a. The full analytical pipeline including data preprocessing, group comparisons, DESeq2 analysis, and visualization was implemented in R and documented in an R Markdown file. This report, including code and results, has been published online.