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Data Brief
Data Brief
Data in Brief
2352-3409
Elsevier

S2352-3409(24)00863-1
10.1016/j.dib.2024.110900
110900
Data Article
Transcriptome datasets of maize plant cultures treated with humic- and amino acids
Decsi Kincső a
Ahmed Mostafa mostafa.ahmed.abdelmagid@agr.cu.edu.eg
bc⁎
Rizk Roquia ac
Abdul-Hamid Donia d
Vaszily Zsolt e
Tóth Zoltán a
a Institute of Agronomy, Georgikon Campus, Hungarian University of Agriculture and Life Sciences, 8360 Keszthely, 7 Festetics street, Hungary
b Festetics Doctoral School, Institute of Agronomy, Georgikon Campus, Hungarian University of Agriculture and Life Sciencess, 8360 Keszthely, 16 Deák Ferenc street, Hungary
c Department of Agricultural Biochemistry, Faculty of Agriculture, Cairo University, Giza 12613, University Street, Egypt
d Heavy Metals Department, Central Laboratory for The Analysis of Pesticides and Heavy Metals in Food (QCAP), Dokki, Cairo 12311, 77 Nadi El-said street, Egypt
e Huminisz Ltd., 8315 Gyenesdiás, 16 Iparosok route, Hungary
⁎ Corresponding author. mostafa.ahmed.abdelmagid@agr.cu.edu.eg
10 9 2024
12 2024
10 9 2024
57 11090013 8 2024
26 8 2024
27 8 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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.

Keywords

RNA-seq
Humic- and amino acid treatments
Zea mays
Illumina NGS
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pmcSpecifications TableSubject	Plant Science: Plant Physiology	
Specific subject area	Plant leaf samples were collected from untreated and foliar-treated maize stands with humic acid and amino acid solutions of various compositions, and raw RNA-seq data were obtained from these samples using the Illumina-NGS method.	
Type of data	Filtered, preprocessed datasets
Tables
Analyzed data	
Data collection	The leaves of corn plants grown under arable conditions were treated with solutions containing humic acid and amino acids. 5 days after the treatments in the vegetative phase, about 40-50 mg of the leaves were collected from each treatment. mRNA was purified from leaf tissue samples containing RIN≥7 total RNA with paramagnetic NEXTFLEX® Poly(A) Beads 2.0 beads and, after fragmentation, strand-specific library preparation was performed using the NEXTFLEX® Rapid Directional RNA-Seq kit 2.0 kit. The completed pooled libraries were sequenced on the Illumina NovaSeq 6000 genome sequencing platform, from which we obtained an average of 22-25 million bp single end reads per sample, which were 63 bp in length. After preprocessing, the raw reads were used for de novo transcriptome assembly. SRA datasets and TSA were used to perform further comparative studies.	
Data source location	Data were collected and stored in Keszthely, Hungary, on the fields of the Hungarian University of Agricultural and Life Sciences, Georgikon Campus.	
Data accessibility	The Bioproject and the SRA-s (RNA-seq reads) are available in National Center for Biotechnology Information (NCBI) database under the accessions:
Repository name: Maize treated by humic acid content plant conditioner
Data identification number: PRJNA1141959
Direct URL to data: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1141959
Repository name: Maize_control_R1
Data identification number: SRR30037659
Direct URL to data: https://www.ncbi.nlm.nih.gov/sra/?term=SRR30037659
Repository name: Maize_humic acid_R1
Data identification number: SRR30037658
Direct URL to data: https://www.ncbi.nlm.nih.gov/sra/?term=SRR30037658
Repository name: Maize_humic acid_N_R1
Data identification number: SRR30037657
Direct URL to data: https://www.ncbi.nlm.nih.gov/sra/?term=SRR30037657
Repository name: Maize_humic acid_B_S_R1
Data identification number: SRR30037656
Direct URL to data: https://www.ncbi.nlm.nih.gov/sra/?term=SRR30037656
Repository name: Maize_humic acid_amino acid_R1
Data identification number: SRR30037655
Direct URL to data: https://www.ncbi.nlm.nih.gov/sra/?term=SRR30037655
The TSA (Transcriptome Shotgun Assembly), the blasted, mapped, annotated contigs from the pre-processed datasets (annotation table) and the count table from the RNA-seq read quantification are deposited in the Mendeley database, and named in this article as Supplementary files.
Repository name: Decsi et al., 2024_DIB_article
Data identification number: doi: 10.17632/dj9ppg9mt3.2
Direct URL to data: https://data.mendeley.com/datasets/dj9ppg9mt3/1	
Related research article	None.	

1 Value of the Data

• The majority of plant conditioners utilized in public cultivation nowadays are products that are based on humic acid. These products possess not only natural qualities but also exhibit environmental friendliness, high efficiency, and competitiveness. They are designed to meet the requirements of producers and are widely distributed worldwide. An increasing number of gene expression examinations are available in connection with these active substances [[1], [2], [3], [4], [5], [6]], which shows that the scientific public is also interested in the topic.

• Humic acid plant conditioners possess the shared attribute of not only catalyzing specific life processes, but also aiding in the maintenance of a balanced physiological state suitable for the plant's stage of development. Additionally, they promote and bolster the growth and development of the plant.

• Amino acids serve as the fundamental constituents of proteins, contributing to their structural integrity and performing essential biochemical and physiological roles. Precursors play a crucial role in numerous physiological processes. They create enzymes that aid in biochemical reactions and have a vital function in the synthesis of plant hormones.

• The objective of the study was to gain a deeper comprehension of the impact of pure humic acid-based treatments on the genetic level and to explore the potential applications of combining humic acids with amino acids.

• The datasets can enhance precision in understanding the impact of preparations including humic and/or amino acids, either individually or in conjunction, on plant physiological processes. By doing so, they can actively promote the widespread use of sustainable and eco-friendly plant production techniques, helping to minimize our ecological impact.

• Nowadays, research into the globally occurring abiotic stress effects and environmentally friendly defense solutions against them is increasingly coming in the focus. The datasets published in the announcement can help other research groups carry out studies related to stress effects, as sequences can be individually searched and identified using the datasets. Monitoring the gene expression changes of the identified sequences can create diverse research opportunities (e.g. monitoring changes in biochemical life processes as a result of humic and/or amino acid treatments, in stress-free and/or stressful environments, etc.).

2 Background

Although humic- and amino acids are often used, there is limited scientific evidence supporting their effects based on gene-level analysis, with particular regard to the use of amino acid plant conditioners [7]. Our objective was to examine the alterations in plant physiological processes at the molecular level by analyzing gene expression in the presence of humic acid alone, humic acid with additional nitrogen, humic acid with additional boron and sulfur, and humic acid with additional natural amino acids.

3 Data Description

One approach we employed involved applying humic acid to the leaves using solutions of varying compositions. These solutions were mostly composed of peat and earthworm humus. We obtained vital organic compounds for plants from these components through a range of physical and chemical extraction methods.

On the other hand, we also tested a foliage fertilizer that, in addition to peat and earthworm humus, contains dudarite and five types of natural amino acids.

In all cases, the solutions were administered at the same time, under the same conditions and in the same amount of active ingredient, due to the comparability of the treatment results. The treatments were:Untreated plants: Maize_control_R1

Treatment with humic acid solution: Maize_humic acid_R1

Treatment with humic acid solution and added nitrogen: Maize_humic acid_N_R1

Treatment with humic acid solution and added boron or sulfur: Maize_humic acid_B_S_R1

Treatment containing humic acid solution and amino acid solution together: Maize_humic acid_amino acid_R1.

The humic acid solutions were applied at a dose of 5 l/ha, and the solution containing both humic and amino acids at a dose of 2.5 l/ha on the corn plants at the stage of 8-10 leaves. The original purpose of the humic acid treatments was general plant conditioning, treatment of stress effects, treatment of heterogeneous stock, quality improvement. The application of the solution containing both humic and amino acids was used in the first phase of the vegetation for explosive development, to promote rooting, as well as to supply nutrients and increase the quality and quantity of the crop.

The experiment took place on a 20-hectare field provided by Georgikon Tanüzem Ltd., around ​​the Hungarian University of Agricultural and Life Sciences. Plant leaf samples were collected on 13 June 2022 from P9718E WAXY (FAO 390), an early maturing maize hybrid.

After shallow mRNA sequencing of the collected samples on the Illumina Novaseq-6000 platform, raw reads with a length of 63 bp were obtained, which were subjected to further processing after quality screening.

After preprocessing, the filtered raw reads were used to generate a de novo transcriptome (Supplementary files_Maize_humic_acid_super_transcripts.fasta). The statistical data of the de novo transcriptome are shown in Fig. 1.Fig. 1 Statistical overview of de novo transcriptome assembly.

Fig 1

The blasted, mapped, annotated version of all 1731 contigs of the completed de novo transcriptome can be found in Supplementary files_excel_worksheet 1.

Count table produced by the result of RNA-seq read quantification made from TSA (Transcriptome Shotgun Assembly) is located on the Supplementary files_excel_worksheet_2. A statistical summary of the count table with the number of TSA-aligned raw reads and the percentage of not-aligned reads per treatment is shown in Fig. 2. Fig. 3 shows the effective number of aligned reads per treatment.Fig. 2 Statistical overview of the aligned raw sequences.

Fig 2

Fig. 3 The effective number of aligned reads to de novo transcriptome per treatment.

Fig 3

De novo transcriptome compiled from the raw reads, then blasted, mapped and annotated, as well as the count table form the basis of further analyses, which enable the individual impact assessment of each treatment, and the analyses of the differences between treatments.

4 Experimental Design, Materials and Methods

4.1 Plant materials

P9718E waxy corn hybrid plants were treated on 06/08/2022 with different humic acid-based plant conditioning solutions. On the 5th day after treatment (June 13, 2022), approximately 40–50 mg of leaf tissue was collected from the plants of the untreated control and the four treated stands, in 4-4 biological replications. The samples were placed in 1-1 ml RNALater (Invitrogen by Thermo Fisher Scientific) solution and then stored at −20 °C until further processing.

4.2 NGS library preparation

mRNA was purified from leaf tissue samples containing RIN≥7 total RNA with paramagnetic NEXTFLEX® Poly(A) Beads 2.0 beads and, after fragmentation, strand-specific library preparation was performed using the NEXTFLEX® Rapid Directional RNA-Seq kit 2.0 kit. The completed pooled libraries were sequenced on the Illumina NovaSeq 6000 genome sequencing platform, from which we obtained an average of 22–25 million bp single-end reads per sample, which was 63 bp in length.

4.3 Read pre-processing

Quality parameters were checked and adjusted using the FastQC software [8] by the sequencing service company. Further pre-filtration of the raw reads was carried out using the Trimmomatic software [9], which was used to remove low-quality bases.

4.4 DNA-seq de novo assembly

DNA-seq de novo assembly was made using the deposited SRA datasets [10]. In this case, no prior information about the raw reads is needed, i.e. no reference genome is needed for its preparation. The main goal is to produce longer, and thus more interpretable, contigs from short reads.

4.5 RNA-seq read quantification

Transcript-level quantification is a method to estimate the expression level of transcripts [11].

With the help of the method, we use the de novo transcript to obtain the expression level of each transcript, and in the case of multiple treatments, the expression level of all transcripts in each treatment. Thus, differences in the expression levels between treatments can be individually measured. Transcript abundances were calculated and written into a count table data file.

4.6 Functional analysis

Contigs of the transcriptome obtained from de novo assembly can be identified if we perform functional analysis on the data set. The unknown contigs are thus transformed into a blasted, mapped, annotated data set (annotation table), which information identifies each contig. After these processes, they show the biological function of the given sequence, and its participation in individual biochemical processes. Annotation table was prepared including Gene Ontology (GO) analyses using OmicsBox.BioBam [12].

Limitations

None.

Ethics Statement

All authors of the above scientific data reporting publication acknowledge and confirm that the authors have read and adhere to the ethical requirements for publication in Data in Brief and confirm that the current work does not involve human subjects, animal testing or data collected from social media platforms.

CRediT Author Statement

Kincső Decsi: Writing – original draft, Conceptualization, Visualization, Validation, Supervision. Mostafa Ahmed: Writing—review and editing, Validation, Visualization. Roquia Rizk: Investigation, Validation. Donia Abdul-Hamid: Investigation, Validation. Zsolt Vaszily: Investigation. Zoltán Tóth: Supervision, Financialization.

Appendix Supplementary materials

Image, application 1

Data Availability

Decsi et al., 2024_DIB_article (Original data) (Mendeley Data).

Acknowledgements

We express our gratitude to Huminisz Ltd. and personally to the managing director István Pais for providing us with the plant conditioning chemicals that are the subject of the study and thereby supporting the preparation of the research article.

This work was supported by the Research Excellence Programme of the Hungarian University of Agriculture and Life Sciences and by the Flagship Research Groups Programme of the Hungarian University of Agriculture and Life Sciences.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.dib.2024.110900.
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