用腐殖酸和氨基酸处理的玉米植物培养物的转录组数据集

IF 1 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2024-09-10 DOI:10.1016/j.dib.2024.110900
Kincső Decsi , Mostafa Ahmed , Roquia Rizk , Donia Abdul-Hamid , Zsolt Vaszily , Zoltán Tóth
{"title":"用腐殖酸和氨基酸处理的玉米植物培养物的转录组数据集","authors":"Kincső Decsi ,&nbsp;Mostafa Ahmed ,&nbsp;Roquia Rizk ,&nbsp;Donia Abdul-Hamid ,&nbsp;Zsolt Vaszily ,&nbsp;Zoltán Tóth","doi":"10.1016/j.dib.2024.110900","DOIUrl":null,"url":null,"abstract":"<div><p>There has been a global surge in the need for commercially accessible plant conditioners that are derived from natural ingredients and are therefore environmentally benign. Currently, sustainable agriculture and minimizing the ecological impact are of great importance. Preparations that contain commonly used humic acids and/or natural amino acids are ideal for meeting these criteria. An investigation was conducted to examine the impact of three plant foliar fertilizers containing humic acid and one fertilizer containing a combination of humic and amino acids on maize crops. By employing the shallow mRNA sequencing technique, we acquired datasets that, once processed, are ideal for investigating the impacts of the foliar fertilizers examined in the study. Five SRA datasets were uploaded to NCBI. These datasets include the TSA (Transcriptome Shotgun Assembly), the contigs that were blasted, mapped, and annotated from the pre-processed datasets, as well as the count table obtained from the RNA-seq read quantification. All of these data are included in the Mendeley database. In the future, the databases will enable the investigation of alterations in plant biochemical processes at the gene expression level.</p></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352340924008631/pdfft?md5=152a44db8367a396385a4cf4700ddc8b&pid=1-s2.0-S2352340924008631-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Transcriptome datasets of maize plant cultures treated with humic- and amino acids\",\"authors\":\"Kincső Decsi ,&nbsp;Mostafa Ahmed ,&nbsp;Roquia Rizk ,&nbsp;Donia Abdul-Hamid ,&nbsp;Zsolt Vaszily ,&nbsp;Zoltán Tóth\",\"doi\":\"10.1016/j.dib.2024.110900\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>There has been a global surge in the need for commercially accessible plant conditioners that are derived from natural ingredients and are therefore environmentally benign. Currently, sustainable agriculture and minimizing the ecological impact are of great importance. Preparations that contain commonly used humic acids and/or natural amino acids are ideal for meeting these criteria. An investigation was conducted to examine the impact of three plant foliar fertilizers containing humic acid and one fertilizer containing a combination of humic and amino acids on maize crops. By employing the shallow mRNA sequencing technique, we acquired datasets that, once processed, are ideal for investigating the impacts of the foliar fertilizers examined in the study. Five SRA datasets were uploaded to NCBI. These datasets include the TSA (Transcriptome Shotgun Assembly), the contigs that were blasted, mapped, and annotated from the pre-processed datasets, as well as the count table obtained from the RNA-seq read quantification. All of these data are included in the Mendeley database. In the future, the databases will enable the investigation of alterations in plant biochemical processes at the gene expression level.</p></div>\",\"PeriodicalId\":10973,\"journal\":{\"name\":\"Data in Brief\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2352340924008631/pdfft?md5=152a44db8367a396385a4cf4700ddc8b&pid=1-s2.0-S2352340924008631-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data in Brief\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352340924008631\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340924008631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

全球对从天然成分中提取的、对环境无害的、可在市场上买到的植物调节剂的需求激增。目前,可持续农业和最大限度地减少对生态的影响非常重要。含有常用腐植酸和/或天然氨基酸的制剂是满足这些标准的理想选择。本研究调查了三种含腐植酸的植物叶面肥和一种含腐植酸和氨基酸的复合肥对玉米作物的影响。通过采用浅层 mRNA 测序技术,我们获得了数据集,经过处理后,这些数据集非常适合研究中考察的叶面肥的影响。我们向 NCBI 上传了五个 SRA 数据集。这些数据集包括 TSA(转录组散弹枪组装)、从预处理数据集中爆破、映射和注释的等位基因,以及从 RNA-seq 读数量化中获得的计数表。所有这些数据都包含在 Mendeley 数据库中。未来,这些数据库将有助于在基因表达水平上研究植物生化过程的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Transcriptome datasets of maize plant cultures treated with humic- and amino acids

There has been a global surge in the need for commercially accessible plant conditioners that are derived from natural ingredients and are therefore environmentally benign. Currently, sustainable agriculture and minimizing the ecological impact are of great importance. Preparations that contain commonly used humic acids and/or natural amino acids are ideal for meeting these criteria. An investigation was conducted to examine the impact of three plant foliar fertilizers containing humic acid and one fertilizer containing a combination of humic and amino acids on maize crops. By employing the shallow mRNA sequencing technique, we acquired datasets that, once processed, are ideal for investigating the impacts of the foliar fertilizers examined in the study. Five SRA datasets were uploaded to NCBI. These datasets include the TSA (Transcriptome Shotgun Assembly), the contigs that were blasted, mapped, and annotated from the pre-processed datasets, as well as the count table obtained from the RNA-seq read quantification. All of these data are included in the Mendeley database. In the future, the databases will enable the investigation of alterations in plant biochemical processes at the gene expression level.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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.
期刊最新文献
Dataset of dendrometer and environmental parameter measurements of two different species of the group of genera known as eucalypts in South Africa and Portugal Bulk mRNA-sequencing data of the estrogen and androgen responses in the human prostate cancer cell line VCaP A refined spirometry dataset for comparing segmented (piecewise) linear models to that of GAMLSS Shotgun metagenomics sequencing data of root microbial community of Huanglongbing-infected Citrus nobilis BEEHIVE: A dataset of Apis mellifera images to empower honeybee monitoring research
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1