**Big Data Tools for Horticulture Research**

Genomics, through high-throughput sequencing technologies such as whole-genome sequencing and transcriptome sequencing, enables us to rapidly and comprehensively develop understanding of the composition, structure, and function of plant genomes. This provides a powerful tool for uncovering the functions, genetic variations, and evolution of plant genes. However, genomic data have not been effectively utilized. To address this gap and efficiently utilize big data, Zhou et al. [11] established the first multi-omics database focused on strawberries, storing all available genomic and transcriptomic data. They developed a series of bioinformatics tools, creating an integrated platform that will facilitate genetic and breeding research in strawberries. RNA-Seq analysis is a fundamental transcriptomics research method; Shi et al. [12] proposed a clustering-based correlation analysis method (C-CorA), which is an efficient approach for analyzing the correlation of various types of data across different dimensions. This method can be applied to RNA-Seq data for candidate gene detection in fruit quality research. Jin et al. [13] conducted genome re-sequencing of Gypsophila paniculata, constructed a whole-genome InDel marker system, and established the first genome-wide genetic map for Gypsophila paniculata, providing a complete marker system for molecular studies. This technology enables us to study and improve important traits in plants, such as disease resistance, stress tolerance, and yield.

Genomics and biotechnology have provided abundant data and tools for studying genetic diversity and evolution in plants. By comparing the genome sequences and conducting functional genomics studies of different plant species, we can determine the patterns and mechanisms of plant evolution, infer species relationships, and understand the genomic bases of plant adaptations to different environments. Using biotechnological tools such as gene knockout, gene expression regulation, and transgenic techniques, we can identify and validate the functions of plant genes, thus revealing their roles in biological processes.

**Funding:** F.C. acknowledges grants from National Natural Science Foundation of China (32172614), Science and Technology special fund of Hainan Province (ZDYF2023XDNY050). J.-Y.X. acknowledges the grant from the Fundamental Research Funds for the Central Universities (no. KYCXJC2022003).

**Acknowledgments:** We thank all the authors who contributed to this Special Issue.

**Conflicts of Interest:** The authors declare no conflict of interest.
