A view of transcriptome during cold stress in sugarcane using Saccharum spontaneum genome
DOI:
https://doi.org/10.15835/nbha50312765Keywords:
bioinformatics, pipeline, RNA-SeqAbstract
Transcriptomic data of two sugarcane cultivars ‘ROC22’ and ‘GT08-1108’ were investigated for the expression analysis of cold responsive genes. The raw RNA Seq data of the sugarcane cultivars were downloaded from the SRA NCBI database and were reanalyzed and mapped by using Saccharum spontaneum genome. In the Saccharum spontaneum reference genome, 83826 unigenes were annotated and, among these, 46,159 (55%) were functionally annotated with Gene Ontology (GO) categories. In the transcriptome-based analysis, 183,515 unigenes were assembled and, among these, 110,021 (60%) were functionally annotated with GO categories. For the cultivar GT08-1108, using the reference genome pipeline, 11,652 (13.9%) unigenes were differentially expressed (7,238 upregulated; 4,414 downregulated), while 16,145 (8.8%) were differentially expressed (8,965 upregulated; 7,180 downregulated) using transcriptome-based pipeline. In the cultivar ROC22, 11,516 (13.7%) genes were differentially expressed (7,174 upregulated; 4,342 downregulated) and 20,317 (11.1%) (10,898 upregulated; 9,419 downregulated) for the genome and transcriptome-based analysis, respectively. In the genome analyses, among downregulated genes, 3,248 were coincident between the two cultivars, the remaining 1,166 differentially expressed only in ‘GT-1180’ and 1,094 only in ‘ROC22’. With the transcriptome assembly, 13,113 genes were deferentially expressed in both cultivars, the remaining 3,032 unique to ‘GT08-1108’ and 7,204 in ‘ROC22’. We concluded that sugarcane in response to cold stress expresses many genes, although the transcriptome assembly overestimated the number of unigenes and, consequently, a higher number of differentially expressed genes. This may be due to difficulties in separating homeologues from paralogue genes. When a reference genome is available, we recommend its use since genes predicted on a reference genome tend to be more accurate.
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