Core Insights - Zhejiang University has developed an AI-based breeding platform called "AI Breeder," which significantly enhances cotton hybrid breeding efficiency by 20 times and reduces the breeding cycle from 6-8 years to 3-4 years [1][2]. Group 1: Technological Advancements - The "AI Breeder" utilizes a comprehensive analysis of over 5,000 cotton varieties and decodes 79,642 genes to identify over 1,000 gene loci related to yield and quality [1]. - A multi-omics database platform named COTTONOMICS has been established, which has recorded over 90,000 visits in three years, serving as a knowledge center for cotton research [1]. Group 2: Collaborative Efforts - The project is a collaboration between Zhejiang University, Huawei Technologies, and Beijing Earthworm Digital Technology Co., Ltd., showcasing a strong partnership in agricultural technology innovation [1]. Group 3: User-Friendly Features - The platform allows breeding personnel to query high-yield, quality, or disease-resistant genes by simply inputting questions, and it can quickly generate optimal breeding plans based on target traits [2]. - "AI Breeder" is designed with multi-crop expansion capabilities and is gradually being applied to breeding research for rice, soybeans, rapeseed, watermelon, and broccoli [2].

Core Viewpoint - The PeachMD database, developed by the Peach genetic breeding team at the Zhengzhou Fruit Research Institute of the Chinese Academy of Agricultural Sciences, integrates multiple omics data for peach, providing significant support for molecular breeding and functional genomics research [1][4]. Group 1: Database Features - PeachMD is the first database to integrate peach genome, epigenome, population genetic variation, and multidimensional phenotype data [1][4]. - The database includes 12 published peach genomes, 329 transcriptome datasets, 102 whole-genome bisulfite sequencing data, and 1313 whole-genome resequencing data, covering key agronomic traits [4][5]. - It supports CRISPR design and GWAS analysis tools, facilitating a comprehensive approach from gene mining to molecular design [5]. Group 2: Technological Advancements - The rapid development of high-throughput sequencing technology and the significant reduction in sequencing costs have led to an exponential increase in biological big data [3]. - The accumulation of multi-omics data presents unprecedented opportunities for understanding peach evolution and identifying key genes for important traits [4]. Group 3: Challenges and Solutions - The main challenge faced by researchers is the efficient integration and deep mining of complex multi-omics data to extract valuable biological information [4]. - The establishment of multi-omics databases like PeachMD is crucial for advancing peach genetic breeding research [4].