RNA Sequencing and Differential Expression Analysis
The Qst-Fst test indicated that more floral characteristics showed local adaptation than other plant characteristics; thus, a bud stage was selected for transcriptome sequencing. Considering the abovementioned population genetic analysis results and clustering results for floral characteristics, ten populations were selected for transcriptome sequencing. Three samples were collected from each population as biological replicates to ensure the stability and reliability of the sequencing results (Table S1). Total RNA was extracted from the samples using TRIzol (Invitrogen, USA) according to the manufacturer’s protocol. A NanoDrop 2000 spectrophotometer (Thermo Scientific, USA) and gel electrophoresis were used to estimate the RNA quality. An Illumina Hiseq system at Novogene Technologies, Inc. (Beijing, China) was used for genomic library generation and sequencing with 2 × 150 bp paired reads. Raw reads were assessed using FastQC (Andrew, 2010) and filtered using Trimmomatic v.0.39 (Bolger, Lohse, & Usadel, 2014). The trimmed reads of each sample were mapped to the same reference genome employed above using STAR v.2.7.5c (Dobin et al., 2013), and the expression levels were estimated using RSEM v.1.3.0 (B. Li & Dewey, 2011). Based on the obtained read counts, the R package DESeq2 was used to calculate differential gene expression via pairwise comparisons (Love, Anders, & Huber, 2014). Transcripts with an absolute log2FoldChange (LFC) value greater than 1 were considered significant DEGs. All the DEGs were analyzed using the clusterProfiler package in R for Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis (Yu, Wang, Han, & He, 2012).