Bamboo is a fast-growing and ecologically significant plant with immense economic value due to its applications in construction, textiles, and bioenergy. However, research on bamboo has been hindered by its long vegetative period, unpredictable flowering cycles, and challenges in genetic transformation. Recent developments in advanced sequencing and genetic engineering technologies have provided new insights into bamboo's evolutionary history, developmental biology, and stress resilience, paving the way for improved conservation and sustainable utilization. This review synthesizes the latest findings on bamboo's genomics, biotechnology, and the molecular mechanisms governing its growth, development, and stress response. Key genes and regulatory pathways controlling its rapid growth, internode elongation, rhizome development, culm lignification, flowering, and abiotic stress responses have been identified through multi-omics and functional studies. Complex interactions among transcription factors, epigenetic regulators, and functionally important genes shape bamboo's unique growth characteristics. Moreover, progress in genetic engineering techniques, including clustered regularly interspaced short palindromic repeats-based genome editing, has opened new avenues for targeted genetic improvements. However, technical challenges, particularly the complexity of polyploid bamboo genomes and inefficient regeneration systems, remain significant barriers to functional studies and large-scale breeding efforts. By integrating recent genomic discoveries with advancements in biotechnology, this review proposes potential strategies to overcome existing technological limitations and to accelerate the development of improved bamboo varieties. Continued efforts in multi-omics research, gene-editing applications, and sustainable cultivation practices will be essential for harnessing bamboo as a resilient and renewable resource for the future. The review presented here not only deepens our understanding of bamboo's genetic architecture but also provides a foundation for future research aimed at optimizing its ecological and industrial potential.

Pineapple is the third most crucial tropical fruit worldwide and available in five varieties. Genomes of different pineapple varieties have been released to date; however, none of them are complete, with all exhibiting substantial gaps and representing only two of the five pineapple varieties. This significantly hinders the advancement of pineapple breeding efforts. In this study, we sequenced the genomes of three varieties: a wild pineapple variety, a fiber pineapple variety, and a globally cultivated edible pineapple variety. We constructed the first gap-free reference genome (Ref) for pineapple. By consolidating multiple sources of evidence and manually revising each gene structure annotation, we identified 26,656 protein-coding genes. The BUSCO evaluation indicated a completeness of 99.2%, demonstrating the high quality of the gene structure annotations in this genome. Utilizing these resources, we identified 7,209 structural variations across the three varieties. Approximately 30.8% of pineapple genes were located within ±5 kb of structural variations, including 30 genes associated with anthocyanin synthesis. Further analysis and functional experiments demonstrated that the high expression of AcMYB528 aligns with the accumulation of anthocyanins in the leaves, both of which may be affected by a 1.9-kb insertion fragment. In addition, we developed the Ananas Genome Database, which offers data browsing, retrieval, analysis, and download functions. The construction of this database addresses the lack of pineapple genome resource databases. In summary, we acquired a seamless pineapple reference genome with high-quality gene structure annotations, providing a solid foundation for pineapple genomics and a valuable reference for pineapple breeding.

Domestication has shaped the population structure and agronomic traits of tea plants, yet the complexity of tea population structure and genetic variation that determines these traits remains unclear. We here investigated the resequencing data of 363 diverse tea accessions collected extensively from almost all tea distributions and found that the population structure of tea plants was divided into eight subgroups, which were basically consistent with their geographical distributions. The genetic diversity of tea plants in China decreased from southwest to east as latitude increased. Results also indicated that Camellia sinensis var. assamica (CSA) illustrated divergent selection signatures with Camellia sinensis var. sinensis (CSS). The domesticated genes of CSA were mainly involved in leaf development, flavonoid and alkaloid biosynthesis, while the domesticated genes in CSS mainly participated in amino acid metabolism, aroma compounds biosynthesis, and cold stress. Comparative population genomics further identified ~730 Mb novel sequences, generating 6,058 full-length protein-encoding genes, significantly expanding the gene pool of tea plants. We also discovered 217,376 large-scale structural variations and 56,583 presence and absence variations (PAVs) across diverse tea accessions, some of which were associated with tea quality and stress resistance. Functional experiments demonstrated that two PAV genes (CSS0049975 and CSS0006599) were likely to drive trait diversification in cold tolerance between CSA and CSS tea plants. The overall findings not only revealed the genetic diversity and domestication of tea plants, but also underscored the vital role of structural variations in the diversification of tea plant traits.

Structural variations (SVs) are a feature of plant genomes that has been largely unexplored despite their significant impact on plant phenotypic traits and local adaptation to abiotic and biotic stress. In this study, we employed woolly grape (Vitis retordii), a species native to the tropical and subtropical regions of East Asia with both coastal and inland habitats, as a valuable model for examining the impact of SVs on local adaptation. We assembled a haplotype-resolved chromosomal reference genome for woolly grape, and conducted population genetic analyses based on whole- genome sequencing (WGS) data from coastal and inland populations. The demographic analyses revealed recent bottlenecks in all populations and asymmetric gene flow from the inland to the coastal population. In total, 1,035 genes associated with plant adaptive regulation for salt stress, radiation, and environmental adaptation were detected underlying local selection by SVs and SNPs in the coastal population, of which 37.29% and 65.26% were detected by SVs and SNPs, respectively. Candidate genes such as FSD2, RGA1, and AAP8 associated with salt tolerance were found to be highly differentiated and selected during the process of local adaptation to coastal habitats in SV regions. Our study highlights the importance of SVs in local adaptation; candidate genes related to salt stress and climatic adaptation to tropical and subtropical environments are important genomic resources for future breeding programs of grapevine and its rootstocks.

Incorporating genotype-by-environment (GE) interaction effects into genomic prediction (GP) models with multi-environment climate data can improve selection accuracy to accelerate crop breeding but has received little research attention. Here, we conducted a cross-region GP study of grain moisture content (GMC) and grain yield (GY) in maize hybrids in two major Chinese growing regions using data for 19 climatic factors across 34 environments in 2020 and 2021. Predictions were conducted in 2,126 hybrids generated from 475 maize inbred lines, using 9,355 single nucleotide polymorphism markers for genotyping. Models based on genomic best linear unbiased prediction (GBLUP) incorporating GE interaction effects of 19 climatic factors associated with day length, transpiration, temperature, and radiation (GBLUP-GE_19CF) trained on whole data set outperformed the traditional GBLUP or BayesB models in predicting GMC or GY by 10-fold cross-validation, achieving prediction accuracies of 0.731 and 0.331, respectively. To refine the climate data, we examined 84 statistical features associated with these climatic factors and identified nine factors most correlated with GMC or GY. Principal component analysis of climate data yielded nine principal components responsible for 97% of the variability in the data. Incorporating these nine factors or principal components into the GBLUP-GE framework with a similarity matrix of environments (GBLUP-GE_9CF and GBLUP-GE_PCA) provided similar prediction accuracies but could reduce the computational burden. In addition, increasing the number of test set environments in the training set from 8 to 14 increased the prediction accuracy of GBLUP-GE_19CF trained with monthly average climate data for 2020–2021. Examining prediction accuracy based on concordance, the proportion of overlapping hybrids between the top 50% of predicted and observed values for GMC and GY, indicated that concordance exceeded 50% for the GBLUP-GE_19CF model, confirming the reliability of our predictions. This study can provide practical guidance for optimizing GPs for maize breeding programs in multi-environment selection.

The Sapindaceae family, encompassing a wide range of plant forms such as herbs, vines, shrubs, and trees, is widely distributed across tropical and subtropical regions. This family includes economically important crops like litchi, longan, rambutan, and ackee. With the wide application of genomic technologies in recent years, several Sapindaceae plant genomes have been decoded, leading to an accumulation of substantial omics data in this field. This surge in data highlights the pressing need for a unified genomic data center capable of storing, sharing, and analyzing these data. Here, we introduced SapBase, that is, the Sapindaceae Genome Database. SapBase houses seven published plant genomes alongside their corresponding gene structure and functional annotations, small RNA annotations, gene expression profiles, gene pathways, and synteny block information. It offers user-friendly features for gene information mining, co-expression analysis, and inter-species comparative genomic analysis. Furthermore, we showcased SapBase's extensive capacities through a detailed bioinformatic analysis of a MYB gene in litchi. Thus, SapBase could serve as an integrative genomic resource and analysis platform for the scientific exploration of Sapinaceae species and their comparative studies with other plants.

Pitaya is an important perennial herbaceous fruit tree. The color of fruit determines pitaya nutritive (and attractive) value, which is considered as an important objective in breeding improvement. In this study, we reported the first telomere-to-telomere (T2T) gap-free genome of “Shuangse No. 1” pitaya (Hylocereus polyrhizus; red peel). Two high-quality genomes for “Dahong” (H. polyrhizus; red peel) and “Honghuaqinglong” (H. stenopterus; stay-green) were further assembled, aiming to explore the genetic diversity of pitaya genomes. In further analysis, we noticed a high proportion of viral contamination in pitaya tissues, which hindered the efficient utilization of transcriptomic data. To address this issue, we analyzed 111 pitaya transcriptome data from different geographic regions to characterize and separate viral components. Then we developed an efficient, novel, and universal transcript purification system for pitaya transcriptomes by applying it to 27 samples from different tissues and species, thereby enhancing the utility for transcriptomic and broader biological research. Combining the purified transcriptomic data with comparative genomic analyses, we identified HuERF72, a transcription factor (TF) that potentially regulates chlorophyll degradation in pitaya. Interaction assays and plant transformation elucidated that HuERF72 acts as a repressive TF by directly binding to the promoter of HuSGR1, a key structural gene in the chlorophyll degradation pathway. This study provides high-quality genomic resources and novel methodologies for molecular investigations in pitaya. Additionally, the proposed regulatory network advances our understanding of the transcriptional regulatory mechanisms underlying chlorophyll degradation, offering valuable insights into the genetic improvement of pitaya.

Wild species of domesticated crops provide valuable genetic resources for resistance breeding. Prunus davidiana, a wild relative of peach with high heterozygosity and diverse stress tolerance, exhibits high resistance against aphids. However, the highly heterozygous genome of P. davidiana makes determining the underlying factors influencing resistance traits challenging. Here, we present the 501.7 Mb haplotype-resolved genome assembly of P. davidiana. Genomic comparisons of the two haplotypes revealed 18,152 structural variations, 2,699 Pda_hap1-specific and 2,702 Pda_hap2-specific genes, and 1,118 allele-specific expressed genes. Genome composition indicated 4.1% of the P. davidiana genome was non-peach origin, out of which 94.5% was derived from almond. Based on the haplotype genome, the aphid resistance quantitative trait locus (QTL) was mapped at the end of Pda03. From the aphid resistance QTL, PdaWRKY4 was identified as the major dominant gene, with a 9-bp deletion in its promoter of the resistant phenotype. Specifically, PdaWRKY4 regulates aphid resistance by promoting PdaCYP716A1-mediated anti-aphid metabolite betulin biosynthesis. Moreover, we employed a genome design to develop a breeding workflow for rapidly and precisely producing aphid-resistant peaches. In conclusion, this study identifies a novel aphid resistance gene and provides insights into genome design for the development of resistant fruit cultivars.