Transcriptome dataset to investigate the effect of deep seawater on the gene expression and functional compounds of leaves of Ligularia stenocephala

利用转录组数据集研究深海海水对狭头橐吾叶片基因表达和功能化合物的影响

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作者:Dewi Komang Anggita ,Bimpe Suliyat Azeez ,Se-Jin Oh ,Jong-Kuk Na

Abstract

Seawater is often applied to improve crop quality by supplying minerals to the crop. Due to high salt concentration of seawater, one of key factors for successful utilization of seawater in agriculture would be optimal dilution ratios, which can be determined by physiological and genomic studies. However, genomic studies of crops treated with seawater have rarely been investigated. Ligularia stenocephala, a vegetable and medicinal crop [1], is used to examine the genomic changes in response to the application of deep seawater (DSW) from 605 m depth. RNA sequencing was carried out for three different leaf samples of L. stenocephala treated with 0% (NT), 5% (DSW5), or 10% (DSW10) of DSW using the Illumina NovaSeq 6000 sequencing system. The RNA sequencing generated 38.1 million raw reads for NT, 29.2 for DSW5, and 30.5 for DSW10, respectively. The length of total raw reads was 2.94 (DSW5), 3.08 (DSW10), and 3.85 Gb (NT), while the total length of filtered clean reads ranged between 2.88 Gb (DSW5) and 3.75 Gb (NT). GC contents range between 42.9% (DSW5) and 43.58 (DSW10), while the Q20 quality score ranged between 98.63% (DSW10) and 98.66% (DSW5). Due to the lack of the reference genome for read mapping, the three transcriptome data from this study were merged to generate a reference transcriptome. The percentage of mapped reads ranged from 89.63 (DSW10) to 98.66% (DSW5). The data is accessible at NCBI BioProject: PRJNA1149490. These data provide invaluable information not only for understanding genes responsive to deep seawater application in crop cultivation but also for determining the optimal dilution ratio of DSW without causing salt stress on crops by examining expression profiles of stress-responsive genes. Keywords: Differentially expressed genes; Illumina NovaSeq 6000; RNA-seq; Vegetable.

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