OfIR: Osmanthus fragrans information resource
————A Multiomics Database for Osmanthus fragrans biological study
e.g. ACS1 or AT1G02970

About transcriptomics

We collected RNA sequencing data from a total of 11 previous studies, including different tissues, or under different treatment conditions. The tissues mainly come from root, stem, leaf, callus, and various tissues in flowers. Environmental stresses mainly include relatively low temperature stress, ethephon, sodidum thiosulfate and 5'-azacytidine.

The quality of the RNA sequencing reads was examined by FastQC (v0.11.9) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Barcode adaptors and low-quality reads (read quality < 80 for paired-end reads) were removed by Trimmomatic (v0.38) [1]. Then, the filtered reads were aligned to the O. fragrans "Liuyejingui" reference genome using Hisat2 (v2.1.0) [2] with default parameters. Bam files containing aligned reads were inputted into StringTie (v1.3.3b) [3] to measure the expression level of genes. Gene-level raw count data files were generated using featureCounts (v1.6.4) [4]. The raw count data were imported into Bioconductor package DESeq2 [5] in the R language to identify the differentially expressed genes. Genes had a log2-converted fold change ≥ 1 or ≤ -1 with an FDR (False Discovery Rate) ≤ 0.05 were considered as DEGs.

References

  1. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30:2114-2120.
  2. Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods 2015, 12:357-360.
  3. Pertea M, Kim D, Pertea GM, Leek JT, Salzberg SL. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat Protoc 2016, 11:1650-1667.
  4. Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 2014, 30:923-930.
  5. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014, 15:1-21.