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[…] Sequence reads from all samples were cleaned using the FASTX toolkit ( First all the reads containing ‘N’ were discarded using a perl script, then adapter sequences were removed using the fastx_clipper program, followed by removal of quality < 5 bases from the 3′ end with fastq_quality_trimmer, requiring a minimum sequence length of 50 bp. Finally the reads with at least 90% bases > quality 20 were chosen using fastq quality filter for further assembly. De novo transcriptome assembly was performed using Trinity RNA-seq assembly v2013-02-25 with default parameters [PMID: 21572440].Meanwhile, all sequence reads generated by Illumina sequencing were aligned to the reference transcriptome dataset using SOAP2 software []. [...] Based on the Trinity assembly results, the number of reads for each contig from each sample (control, defoliation, and grazing) was converted to reads per kilobase per million (RPKM) []. The MARS (MA-plot-based method with random-sampling model) module in the DEGseq package was used to calculate the differential expression of each contig between the analyzed samples []. The package DEGseq is a free R package for identifying DEGs from RNA-seq data. We used an FDR (false discovery rate) to determine the threshold p-value. An FDR < 0.001 was considered to indicate a significant difference in expression between the control and treated samples. [...] The sheepgrass transcriptome sequencing data had previously undergone Gene ontology (GO) annotation using a BLASTP search against the Swiss-Prot and TrEMBL databases with an E-value ≤ 1e-5 []. A GO functional classification was performed using WEGO software ( to understand the distribution of gene functions in grazed sheepgrass [].In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation was performed using the KEGG Automatic Annotation Server (KAAS) with the bi-directional best-hit method. For KEGG, KAAS annotates every submitted sequence with a KEGG orthology (KO) identifier representing an orthologous group of genes directly linked to an object in the KEGG pathways and BRITE functional hierarchy [, ]. KEGG pathway enrichment analysis was conducted using KOBAS 2.0 (, []).Finally, EuKaryotic Orthologous Groups (KOG) annotation was carried out against the NCBI KOG database with a typical cut-off E-value ≤ 1e-5. The KOG annotations of the DEGs were classified into 25 protein functions and compared between the defoliation and grazing treatments. KOG enrichment analysis was conducted through hypergeometric distribution testing using the Phyper function in the R software package ( The Bonferroni correction was used to adjust the p-values. The significantly enriched functional clusters were selected based on a corrected q-value (< 0.05). […]

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