Rose is a globally significant ornamental crop and an emerging genomics system for woody ornamental plants. In recent decades, the rapid evolution of high-throughput sequencing and robust technical platforms has yielded high-quality reference genomes and been propelling our understanding of rose biology to unprecedented depths. This review systematically synthesizes the current landscape of rose genomics, recent development of technical and resource platforms, and the molecular mechanisms underlying pivotal agronomic traits such as floral development, scent biosynthesis, petal lifespan, and stress resilience. Despite these strides, high genome heterozygosity, polyploidy, and recalcitrance to genetic transformation remain significant barriers. We discuss how integrating cutting-edge technologies, such as pangenomics, single-cell transcriptomics, AI-assisted genomic selection, and precise CRISPR-based editing, can bridge the gap between fundamental research and practical applications. Collectively, this review provides a strategic roadmap for accelerating the development of next-generation rose cultivars through trait-based biobreeding.
As the leading global producer of apples, China’s apple industry faces substantial challenges posed by abiotic stresses. Consequently, it is imperative to carry out an in-depth synthesis and refinement of the unique physiological and molecular mechanisms underlying apple stress resistance, as well as to comprehensively and precisely uncover their response patterns under diverse abiotic stress conditions. Such endeavors are crucial for fostering the sustainable development of the apple industry. Presently, research on abiotic stresses in Chinese apples is intricately linked to industrial issues prevalent in major apple-producing regions, with a primary emphasis on improving drought, cold, and salt-alkali tolerance. This review synthesizes studies on Chinese apples, spanning tree growth, physiological biochemistry, and molecular regulation. Key questions and future directions are outlined to inform research on stress resistance and precision breeding strategies.
Leaf mustard (Brassica juncea) is an important leafy vegetable highly valued for its diverse flavor and nutrient compounds, particularly glucosinolates. However, different varieties of leaf mustard exhibit substantial phenotypic variation and varying glucosinolate content. In this study, we systematically assessed the phenotypic variability and glucosinolate content among 86 genotypes of leaf mustard. The Shannon-Wiener index for qualitative traits ranged from 0.10 (leaf surface gloss) to 1.60 (leaf shape), while for quantitative traits, it ranged from 1.85 (petiole length) to 2.07 (leaf width). Cluster analysis grouped the accessions into three distinct clusters, with hierarchical clustering indicating that yield-related traits were the primary factors distinguishing these groups. Principal component analysis (PCA) revealed that eight components accounted for 87.44% of the total variance in yield and glucosinolate attributes. Based on comprehensive scoring, the top five genotypes (A645, A464, A512, A702, and A445), exhibiting diverse characteristics, were identified as promising candidates for breeding programs. Moreover, our results suggest that leaf mustard leaves with deeper or more numerous lobes contain higher concentrations of glucoraphanin. Collectively, these findings provide valuable genetic resources to advance leaf mustard breeding.
