Abstract
Objectives
Peach is a deciduous tree widely cultivated in temperate and subtropical regions that requires a process of bud endodormancy to produce normal flowering and fruiting. This release requires a certain accumulation of cold, named chilling requirement (CR). CR is genotype dependent and with varies levels among different species and accessions. Thus, we collected the bud transcriptomic data of two peaches with different CR levels and conduct a series standard basic analysis. The peach bud transcriptomic data we gathered provides a valuable dataset for exploring the relationships between gene expression and peach CR levels.
Data description
We extracted and sequenced the RNA of different CR peach buds at the same status in three endodormancy stages. Each stages have three biological replicates. A total of 18 RNA-seq libraries were obtained and mapped to the reference genome after quality control. The gene expression level was normalized by two methods (TPM and FPKM). Differentially expressed genes (DEGs) analysis revealed that a total of 2,481 unique genes with an absolute value of log2 fold change (FC) greater than 1.0. Homologous functional annotation of these DEGs were conducted which provided further information for CR potential related genes identified and functional genomics studies.
Keywords: Transcriptomic, Peach, Chilling requirement, RNA-seq
Objective
Peach [Prunus persica (L.) Batsch] is a representative deciduous fruit tree that is grown worldwide, especially in temperature and subtropical regions. Similar to most deciduous fruit trees, peaches require a certain amount of winter chill, known as chilling requirement (CR), to promote the release of bud endodormancy and ensure subsequent normal flowering and fruiting [1, 2]. High CR can withhold peach buds from initiating growth in response to transient warm temperatures, thereby preventing subsequent frost damage in late winter or early spring, but the inability to obtain sufficient CR in warm climates limits its cultivation areas [3, 4]. Therefore, breeding for CR can be a significant consideration in the development of new cultivars, broadening growing regions, and promoting the use of protected cropping systems, as cultivar adaption to the specific climatic condition of the growing area is essential to ensure peach production. As CR is a heritable quantitative trait [4–8], identifying the genes that relate to CR is the priority task for peach CR breeding [9–14]. We selected a high CR peach variety (ZY4, CR = 700 h) and a low CR peach variety (NG, CR = 200 h) and conducted RNA-seq at different endodormancy release stages, aiming to find or verify candidate genes that control CR at the gene expression level. This first-time public data was previously used only as verification evidence for candidate gene functional experiments conducted in our laboratory, helping us find some candidate genes that control CR in peach. Overall, this dataset is valuable for identifying candidate genes related to CR in peach.
Data description
The peach buds used in this study are collected from the Wuhan Botanical Garden, Chinese Academy of Sciences (Wuhan, China) from October 2022 to February 2023. Samples were collected at three stages, the heavy leaf fall stage (S1) were deemed as endodormancy induction stage, the endodormancy maintenance stage (S2), and the bud slightly sprouting (S3) was deemed as endodormancy release stage. Total RNA isolation was performed using the RNAprep Pure Plant Kit (TianGen, Beijing, China) according to the manufacturer. After adjusting concentration and eliminating any potential genomic DNA contamination during the RNA extractions, the cDNA libraries were constructed according to the MGIEasy Kit (MGI, Wuhan, China). A total of 18 libraries were used for RNA sequencing by MGISEQ-T7 in paired-end sequencing model with a length of 150-bp. Raw sequencing reads quality control was conducted by fastp [15] with default parameters and obtain clean reads. The clean reads were mapped to the reference genome LoveII v2.0a1 [16, 17] using HISAT2 [18] with default parameters. Gene expression levels were normalized as per kilobase million (TPM) and fragments per kilobase of exon per million fragments mapped (FPKM) by StringTie [19]. Differentially expressed genes (DEGs) analysis was performed by DESeq2 [20]. Read counts matrix was obtained from prepDE.py scripts included in StringTie. There are 1,567, 1,645 and 3,930 DEGs in S1, S2 and S3, respectively. A total of 2,481 unique DEGs were identified among three stages. Homologous functional annotation was performed by blastp [21].
Limitations
More samples with different CR levels should be collected and sequenced for transcriptome comparing. If it is possible to determine a more detailed endodormancy period by measuring relevant hormone levels or observing under a microscope, it would be more reasonable to increase the sampling density.
Acknowledgements
We thank the workers in our institute’s orchards.
Abbreviations
- CR
Chilling Requirement
- TPM
Per Kilobase Million
- FPKM
Fragments Per Kilobase of exon per Million fragments mapped
- FC
Fold Change
- DEG
Differentially Expressed Genes
Author contributions
W.Z. and L.L. conceived this project. Y.H. and L.L. collected these samples. Y.S. performed RNA extraction. W.Z. performed data analysis and wrote the manuscript. B.W. and H.L. checked the data and reviewed the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by the Opening Project of Guangxi Key Laboratory of Germplasm Innovation and Utilization of Specialty Commercial Crops in North Guangxi (GASCKF202406), the Key Special Project of Intergovernmental International Cooperation of the National Key R&D Program of China (2023YFE0125100), and the China Agriculture Research System (CARS-30).
Data availability
The data described in this Data note can be freely and openly accessed on Figshare under 10.6084/m9.figshare.26838976.v1. Please see Table 1 for details and links to the data.
Table 1.
Overview of data files/data sets
| Label | Name of data file/data set | File types (file extension) |
Data repository and identifier (DOI or accession number) |
|---|---|---|---|
| Data file 1 | Gene expression level normalized as TPM | MS Excel file (.xlsx) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 2 | Gene expression level normalized as FPKM | MS Excel file (.xlsx) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 3 | Gene count matrix | CSV files (.csv) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 4 | DEGs in S1 between high-CR peach and low-CR peach | CSV files (.csv) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 5 | DEGs in S2 between high-CR peach and low-CR peach | CSV files (.csv) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 6 | DEGs in S3 between high-CR peach and low-CR peach | CSV files (.csv) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 7 | Function annotation of DEGs | MS Excel file (.xlsx) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 8 | Raw sequencing data | fastq file (.fastq.gz) | NCBI (https://identifiers.org/ncbi/insdc.sra:SRP528936) [23] |
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Baoxiong Wan, Email: wan77118@163.com.
Liao Liao, Email: liao168000@wbgcas.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data described in this Data note can be freely and openly accessed on Figshare under 10.6084/m9.figshare.26838976.v1. Please see Table 1 for details and links to the data.
Table 1.
Overview of data files/data sets
| Label | Name of data file/data set | File types (file extension) |
Data repository and identifier (DOI or accession number) |
|---|---|---|---|
| Data file 1 | Gene expression level normalized as TPM | MS Excel file (.xlsx) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 2 | Gene expression level normalized as FPKM | MS Excel file (.xlsx) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 3 | Gene count matrix | CSV files (.csv) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 4 | DEGs in S1 between high-CR peach and low-CR peach | CSV files (.csv) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 5 | DEGs in S2 between high-CR peach and low-CR peach | CSV files (.csv) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 6 | DEGs in S3 between high-CR peach and low-CR peach | CSV files (.csv) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 7 | Function annotation of DEGs | MS Excel file (.xlsx) | Figshare (10.6084/m9.figshare.26838976.v1) [22] |
| Data file 8 | Raw sequencing data | fastq file (.fastq.gz) | NCBI (https://identifiers.org/ncbi/insdc.sra:SRP528936) [23] |