Walnut husk transcriptome dataset of codling moth (Cydia pomonella) infestation at different times

IF 1 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2025-02-06 DOI:10.1016/j.dib.2025.111366
Xiaoyan Cao , Xiaoqin Ye , Adil Sattar
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Abstract

Walnuts, along with almonds, cashews, and hazelnuts, are renowned as the world's “four famous nuts,” with walnuts being the foremost among them. Walnut fruit is rich in nutrients, including proteins, fats, polyphenols, sugars, phospholipids, melatonin, sterols, flavonoids, iron, zinc, manganese, and other trace elements, as well as dietary fiber. However, the codling moth poses a significant threat to walnut fruits as a major pest. Despite its importance, the transcriptomic changes in walnut husk at different times of codling moth infestation have not been fully explored. In this study, we employed the Illumina NovaSeq 6000 platform to sequence the transcriptome of walnut husk at various time points (0, 12, 24, 36, 48, and 72 hours) after codling moth infestation. The RNA-seq libraries yielded between 41,402,492 and 48,358,932 clean reads, resulting in a total of 120.34 Gb of clean data after filtering out low-quality reads. In total, 936 million reads were generated, with approximately 90% aligning uniquely to the reference genome. Differential expression analysis revealed the number of differentially expressed genes (DEGs) at each time point, including 21 genes associated with plant hormone synthesis. The results of this study provide new insights into the transcriptional changes in walnut husk induced by codling moth infestation and lay a foundation for future research on walnut husk defense mechanisms. The raw FASTQ files from this transcriptome experiment are publicly available in the NCBI Sequence Read Archive (SRA) under the BioProject accession number PRJNA1140835.
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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