Poplar (Populus) is a well-established model system for tree genomics and molecular breeding, and hybrid poplar is widely used in forest plantations. However, distinguishing its diploid homologous chromosomes is difficult, complicating advanced functional studies on specific alleles. In this study, we applied a trio-binning design and PacBio High-Fidelity long-read sequencing to obtain haplotype-phased telomere-to-telomere genome assemblies for the two parents of the well-studied F₁ hybrid “84K” (Populus alba × P. tremula var. glandulosa). Almost all chromosomes, including the telomeres and centromeres, were completely assembled for each haplotype subgenome apart from two small gaps on one chromosome. By incorporating information from these haplotype assemblies and extensive RNA-seq data, we analyzed gene expression patterns between the two subgenomes and alleles. Transcription bias at the subgenome level was not uncovered, but extensive expression differences were detected between alleles. We developed machine-learning (ML) models to predict allele-specific expression (ASE) with high accuracy and identified underlying genome features most highly influencing ASE. One of our models with 15 predictor variables achieved 77% accuracy on the training set and 74% accuracy on the testing set. ML models identified gene body CHG methylation, sequence divergence, and transposon occupancy both upstream and downstream of alleles as important factors for ASE. Our haplotype-phased genome assemblies and ML strategy highlight an avenue for functional studies in Populus and provide additional tools for studying ASE and heterosis in hybrids.

Jasmonate ZIM-domain (JAZ) family genes, which belong to TIFY family, are plant-specific transcriptional repressors. As key regulators of the jasmonic acid signaling pathway, JAZ proteins play crucial roles in various aspects of plant biology. However, the identification and functional characterization of JAZ genes in sweet cherry (Prunus avium L.) fruit remain unknown. In the present study, we identified nine JAZ members in the sweet cherry genome. We systematically analyzed the gene structures, protein domains, evolutionary relationships, and physicochemical properties of these members and also evaluated their expression levels across different fruit developmental stages, as well as under methyl jasmonate (MeJA) treatment. Among these members, our results revealed a previously uncharacterized JAZ member, PavJAZ8, as a crucial regulator of fruit aroma traits. Specifically, RT-qPCR analysis showed that PavJAZ8 overexpression modulates the expression of genes involved in the biosynthesis of aroma volatiles, such as PavLOX2, PavLOX3, PavHPL1, PavADH1.1, PavADH1.2, and PavADH7, which are involved in the synthesis of aldehydes and alcohols. Consistent with the gene expression data, analysis of volatile metabolites revealed that PavJAZ8 overexpression significantly inhibited the accumulation of several related aldehydes and alcohols, including hexanal, geraniol, and benzyl alcohol. Furthermore, PavJAZ8 expression was highly responsive to phytohormone treatments, such as abscisic acid (ABA) and MeJA. Further analysis showed that PavJAZ8 interacts with PavMYC2, thereby mediating JA signal transduction. Our results highlight PavJAZ8 as a novel regulator of fruit aroma quality, offering a valuable genetic target for sweet cherry improvement.

Background: The Rhododendron genus ( Rhododendron L.), recognized as the most extensive woody plant genus in the Northern Hemisphere, captivates with its strikingly beautiful corollas and variety of flower colors. In addition, the Rhododendron genus exhibits a complex evolutionary history and substantial species diversification. To comprehensively understand the genomic complexity and flower color diversity within this genus, comparative genomics has emerged as a promising approach, enabling analysis at a super-species level. Results: Here, we collected whole-genome data from seven rhododendrons of different subgenera to investigate the patterns of interspecific genomic and sequence divergence, as well as evolutionary dynamics of gene family related to flower color. We discovered that approximately 50% of Rhododendron genomes are composed of transposable elements (TEs), with over half of them being long terminal repeat retrotransposons (LTR-RTs). TEs significantly associate with genomic differentiation and structural variances within the genus. Additionally, the duplication and loss of genes associated with flower color and their corresponding expression over time are potentially driven by TEs. Conclusion: Our comparative genomic analysis accentuates the critical role of TEs in genome divergence within the Rhododendron genus, highlighting their potential role as a key factor governing speciation and interspecific variability within the genus.

Processing quality in chestnut (Castanea spp.) is a complex trait jointly determined by fruit development, postharvest metabolic changes, and responses to processing. However, its genetic basis and regulatory networks remain poorly understood. This review provides an integrated framework linking product-specific processing requirements with their biochemical basis, candidate genes, and molecular breeding strategies. Starch composition and fine structure primarily determine cooked texture, storage hardening, and digestibility; starch degradation and sugar metabolism affect sweetness and thermally induced flavor formation; and phenolic substrates, together with oxidative enzymes, determine browning potential and color stability. We review the biochemical basis underlying these traits and summarize candidate genes and regulatory pathways involved in starch synthesis and structural modification, starch-to-sugar conversion, enzymatic browning, flavor formation, and the accumulation of nutritional and bioactive compounds. Nevertheless, stable quantitative trait loci, favorable haplotypes, and causal genes associated with chestnut processing quality remain insufficiently validated. Future research should develop product-oriented, standardized phenotyping systems and integrate multi-environment genetic analyses, multi-omics network dissection, marker-assisted selection, genomic selection, and gene editing to elucidate the genetic mechanisms underlying chestnut processing quality and enable the precision breeding of processing-specific cultivars.

Nursery-plant grading relies on morphological traits, but leaf metabolic variation associated with nursery-plant grade remains unclear. In this study, untargeted HPLC-QTOF-MS metabolomics was applied to mature and young leaves of Grade I, II, and III apple nursery plants to explore grade-associated metabolic variation and its relationship with growth performance. After quality filtering, 198 positive-ion features were retained from mature leaves, while 259 positive-ion and 8 negative-ion features were retained from young leaves. Multivariate analysis showed clear grade-associated separation in both leaf types, with stronger discrimination in young leaves. A combination of orthogonal partial least squares (OPLS) modeling and trend analysis identified 20 and 28 differential features in mature and young leaves, respectively. Cross-model prioritization further highlighted key metabolites putatively annotated as methyl nicotinate and 1-palmitoyl-sn-glycero-3-phosphocholine in mature leaves, and methyl nicotinate, nicotinamide riboside, cis-jasmone, and methyl (9Z,14Z)-12,13,16-trihydroxyoctadeca-9,14-dienoate in young leaves. These key metabolites were potentially associated with NAD precursor metabolism, membrane lipid remodeling, and oxylipin-related signaling. Correlation analysis showed that they were associated with both initial grading traits and post-transplant growth performance. These metabolites represent candidate molecular correlates of grade-associated physiological variation and growth performance in apple nursery plants.