Transcriptome data for Hevea brasiliensis associated with powdery Mildew infection

被引:1
|
作者
Kamerkar, Urwashi [1 ]
Othman, Ahmad Sofiman [1 ,2 ]
机构
[1] Univ Sains Malaysia, Sch Biol Sci, Minden 11800, Pulau Pinang, Malaysia
[2] Univ Sains Malaysia, Ctr Chem Biol, Bayan Lepas 11900, Pulau Pinang, Malaysia
来源
DATA IN BRIEF | 2022年 / 42卷
关键词
Transcriptomics; RNA-Seq; Oidium heveae; Hevea brasiliensis; Pathogen resistance;
D O I
10.1016/j.dib.2022.108254
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The Hevea brasiliensis or rubber tree belongs to the Euphorbiaceae family and is the only economically viable natural rubber source worldwide. The development of enhanced rubber tree clones with agronomically important traits is critical due to the growing demand for natural rubber around the world. Throughout the years, numerous disease-causing pathogens of H. brasiliensis have been identified and studied. One of the more prominent diseases affecting H. brasiliensis is powdery mildew caused by Oidium heveae. Oidium heveae primarily infects the newly formed leaves and buds of H. brasiliensis. Severe Oidium heveae infections cause extensive defoliation and yield loss. We performed RNA sequencing (RNA-Seq) for healthy and O. heveae-infected leaf tissues from RRIM 2025 and RRIM 929 rubber tree clones using the Illumina HiSeq 20 00 platform. RNA-Seq generated 92007684 (12.9 GB) and 96070286 (13.5 GB) paired raw reads for healthy H. brasiliensis clones RRIM 2025 and RRIM 929 respectively. Similarly, RNA-Seq generated 93747858 (13.2 GB) and 93324564 (13.1 GB) paired raw reads for disease-infected H. brasiliensis clones RRIM 2025 and RRIM 929 respectively. The raw data were deposited in the NCBI under bio-project accession number PRJNA723431. The raw reads were quality trimmed and the reference-based transcriptome assembly was generated using the H. brasiliensis genome (ASM165405v1). The data were used to identify between the significantly differentially expressed genes of the healthy and diseased samples. (C) 2022 The Author(s). Published by Elsevier Inc.
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页数:7
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