RNA-Sequencing of spinach tissues with contrasting oxalate contents

Purpose: The goals of this study are to compare differentially expressed transcripts in roots and leaves of spinach cultivars with distinct oxalate contents using transcriptome profiling (RNA-seq) Methods: Leaf and root samples for RNA Seq analysis were collected from three independent spinach plants of cultivar PI175311 and Bloomsdale were flash-frozen in liquid nitrogen for further analysis. Results: The clustering of the index-coded samples was performed on a cBot Cluster Generation System using PE Cluster Kit cBot-HS (Illumina) according to the manufacturer’s instructions. After cluster generation, the libraries were sequenced on an Illumina Hiseq platform, and 150 bp paired-end reads were generated. Raw reads of fastq format were processed to obtain clean reads by removing the adapter, reads containing ploy-N, and low quality reads from raw data. At the same time, Q20, Q30, and GC content, the clean data were calculated. Reference genome and gene model annotation files were downloaded from SpinachBase (http://spinachbase.org/). Index of the reference genome was built using Bowtie v2.2.3, and paired-end clean reads were aligned to the reference genome using TopHat v2.0.12. : HTSeq v0.6.1 was used to count the reads mapped to each gene. Reads Per Kilobase of exon per Megabase of library size (RPKM) were calculated from mapped read by featureCounts. Differential expression analysis of High N and Low N conditions (three biological replicates per tissue per treatment) was performed using the DESeq R package (1.18.0) (Anders and Huber, 2010). Genes with P-value < 0.05 found by DESeq were assigned as differentially expressed. Conclusions: The transcriptomic changes in leaf and root tissues was used for RNA-Seq analysis. A total of six libraries from leaf and root tissue were sequenced for each cultivar using the Illumina HiSeq platform. On average, 60 and million raw reads were generated from leaf tissues for bothe the cultivars. Across all reads , the Q20 and Q30 percentage was more than 98 and 94%, respectively (sequencing error rate was less than 0.02%), and GC content for the libraries was ~43%. Among all the libraries, the ratio of total mapped reads was above 85%, of which ~81 % reads uniquely mapped to the reference genome . The data generated from all libraries provided a foundation for quality analyses.