Dataset on the transcriptomic responses of 'Fuji Hubrax' apples to deep seawater application

초록

Deep seawater (DSW) has attracted increasing interest as a mineral-rich resource for agricultural applications due to its stable composition and high concentrations of dissolved inorganic nutrients. Mineral-based treatments derived from DSW have the potential to influence plant growth, physiological performances, and stress responses [ 1 ]. Despite these growing interests, limited information is available on their impact on gene expression and associated biological pathways in apple, although such information would be crucial for optimized utilization of DSW as a natural fertilizer. 'Fuji Hubrax', a widely cultivated and economically important apple cultivar [ 2 ], was used to examine the transcriptional response associated with DSW application in apple (Malus domestica Borkh.). Peel tissues from control (HB-NT) and deep seawater treated samples (HB-DSW) of 'Fuji Hubrax' were subjected to paired-end RNA sequencing using the Illumina NovaSeq 60 0 0 platform. Sequencing generated 28.5 million reads for HB-NT, and 25.0 million reads for HB-DSW, corresponding to 2.9 Gb and 2.5 Gb of raw data, respectively. After quality filtering, 2.8 Gb and 2.5 Gb of clean reads were obtained. GC content was 47.17% (HB-NT) and 47.0% (HB-DSW), and the Q20 quality score exceeded 99% for both sequencing data. Approximately 95% of reads from the individual sample were mapped to the reference genome. In DSW-treated vs. control samples, the total number of upregulated and downregulated genes was 2274 and 1517, respectively. The sequencing datasets are publicly available in the NCBI BioProject database under the accession number www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd= search&db=pdb&doptcmdl=genbank&term=PRJNA1434662. These datasets provide transcriptional profiles of 'Fuji Hubrax' apple peel in response to deep seawater treatment, establishing a reference framework for subsequent genetic improvement and cross-study comparisons in this species. (c) 2026 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

키워드