Mangrove plants play an ecologically invaluable role as crucial buffers between terrestrial and marine ecosystems in tropical and subtropical regions. They contribute significantly to stabilizing coastal sediments, effectively reducing erosion and safeguarding shorelines against storm surges and sea-level rise. Currently, there are 70 known mangrove species with at least 27 independent evolutionary origins globally (He et al. 2022). It is divided into true mangroves, semi-mangroves and mangrove associates. The diversity of growth forms in mangroves, from woody to herbaceous/ferny, which reflects adaptive radiation to heterogeneous intertidal environments. This diversity is mainly a testament to their evolutionary success through functional convergence. The true mangroves and semi-mangroves have evolved remarkable adaptations to endure challenging environmental stresses, such as high salinity, cold damage, waterlogged soils and fluctuating tides. Some species possess specialized features like salt-excreting glands, viviparous seed development and complex root systems that enable efficient oxygen uptake in hypoxic conditions. Moreover, by integrating growth form variation into ecological frameworks, we gain a more nuanced understanding of mangrove resilience and can better inform conservation strategies in the face of global change. In recent years, an amount of mangroves transcriptome data (MTDB) and whole-genome sequencing (WGS) data emerged (He et al. 2022; Friis et al. 2024; Ma et al. 2022), offering new opportunities to study gene expression regulation network and deepen our understanding on molecular mechanisms in mangroves. In this issue of Plant, Cell and Environment, the study by Xu et al. (2025) built an interactive web-based database platform MangroveDB, based on 942 transcriptome data, 386 WGS data, representing a significant advancement in the study of mangrove plants. Notably, MangroveDB integrates various multi-omic databases available online, providing a powerful platform for future research in this field (Figure 1). Mangrove plants, consisting of approximately 70–80 species belonging to over 20 different families, are specialized woody plants adapted to grow in intertidal zones. Different species of mangrove plants play significant roles in the ecosystem and exhibit marked differences in their evolutionary and developmental pathways, as well as in their physiological responses to environmental stressors and climate change (Beckett et al. 2023, 2024; Inoue et al. 2025). In the past, extensive research has been conducted, and data have been collected in the fields of genomics, transcriptomics, proteomics and metabolomics. However, this vast amount of data has been fragmented and has not been cohesively integrated, thus impeding a profound understanding of mangrove plants. Therefore, Xu et al. (2025) integrated a large amount of diverse omics data in their database, which has links to the data source. With this kind of ‘one-stop service’, a comprehensive service model, users can easily download the original research data set and utilize these toolkits for in-depth search and study. Moreover, the data set integrated in the MangroveDB covers over 20 genera of plants and records multi-omics analyses under different environmental stresses, such as cold, salinity and waterlogging. This provides an important resource for a profound understanding of the mangrove forestry, a specific intertidal ecosystem. Authors also demonstrated the practical applications through several case studies using the toolkits they provided, including Differential Gene Expression Analysis, Tissue-Specific Gene Expression Analysis, Condition-Specific Gene Expression Analysis, Time-Series Gene Expression Analysis, Visualization for Results of Population Genetics Analysis. With these case studies, even users with limited bioinformatics knowledge can conduct their own research projects. They can not only create case studies but also obtain personalized and visualized research results based on the data collected from their own projects, which can potentially be shared within the research community to promote the exchange and generation of new knowledge. The mangrove plants have faced the most extreme challenges in the harsh environments between terrestrial and marine ecosystems. As a result, the extinction of certain mangrove species has occurred frequently throughout their evolutionary history. Twenty-seven independent evolutionary events may cause origin of mangroves, reflecting the global climate and coastal changes in geographic history (He et al. 2022). A platform with mega database and reliable algorithms may help people to clarify this evolutionary mist to understand the origin of adaptability of these plants. We hope that the MangroveDB can include more semi-mangroves, to deepen our understanding to the plant species with different tolerance to salt-stresses (Wang et al. 2011). In the current global climate crisis, it can assess the reproductive strategies and status of mangrove plants to formulate scientifically sound and rational conservation strategies (Fang et al. 2024). By comparing genomic data across different populations, researchers can determine how many distinct populations exist and their geographical distribution, providing a wealth of information that is vital for the seedling cultivation, coastal restoration, ecological application and rare conservation of mangrove plants. However, the MangroveDB included mostly the woody plants in mangroves. Although there is currently a lack of genomic and transcriptomic data for various herbaceous plants, that is, Acanthus spp., it can be predicted that incorporating these databases into MangroveDB will provide new data that can better support the breeding of plants such as salt-tolerant rice. Additionally, the Acrostichum spp. being the few fern species in mangroves, presents an opportunity for genomic research that may enhance our understanding of significant ‘land colonization’ events in the evolutionary history of plants. With the employment of multi-omics technologies, researchers are also granted a window into the genetic orchestration of invasion, discerning which genes are elevated or suppressed during this process, thus illuminating their potential roles and the intricate mechanisms by which they operate. thereby providing a comprehensive understanding of the tenacity and versatility of invasive species. The construction of the MangroveDB omics database by Xu et al. (2025) represents a pivotal step forward in mangrove research. This database not only deepens our understanding of mangrove genetics and biology but also contributes substantially to global efforts in conserving these ecologically vital ecosystems. Given the importance of mangroves in maintaining coastal ecological balance, conducting gene function verification research using the mangrove genome data resources becomes both highly necessary and pressing. Furthermore, establishing transgenic systems referring to the poplar genetic transformation system. Identifying genetic markers associated with favourable traits, like disease resistance and growth rate, can also support breeding programs aimed at restoring mangrove populations. Although significant progress has been made in sequencing mangrove genomes, the functional annotation of these genomes remains relatively limited. Investigating the function of selected genes in mangrove biology and their roles in adaptation and survival is essential. Moreover, conducting controlled field experiments with transgenic lines to evaluate their performance under natural conditions, while taking into account potential ecological impacts, is of great importance. Promoting gene function verification research will fill the gap between genomic sequencing and practical application, providing a more comprehensive understanding of mangrove biology and facilitating further breakthroughs in related fields such as plant science, genomics and ecology. The findings from gene function research can then be applied to optimize and enhance conservation and reproductive practices. This website collects and integrates a large amount of data and provides an easy-to-use toolbox. Additionally, it offers resources for learning and researching rapidly developing artificial intelligence tools. In bioinformatics analysis and research, we have recognized that while humans can pose innovative questions, it is nearly impossible to rely solely on human efforts for massive computations. By integrating the data aggregator with AI, the website can more effectively process the collected and integrated data. Specifically, deep-learning-based AI tools can analyze complex data patterns, identify hidden relationships and make predictions. We also look forward to the authors continuously integrating more multi-omics data on the MangroveDB platform, which will significantly accelerate our understanding of mangrove plants, advance genetic breeding efforts, and promote the development of ‘blue carbon’ enhancement technologies for mangrove wetlands. In the context of global warming and frequent extreme weather, integrating past multi-species, multi-omics data under various environmental stresses can provide us with valuable insights and the greatest possible assistance in addressing an uncertain future. The authors received funding from the Beijing Municipal Natural Science Foundation (6232027), Hainan Normal University Talent Research Start-up Fund Project Funding (HSZK-KYQD-202436). The authors declare no conflicts of interest. Data sharing is not applicable to this article as no data sets were generated or analyzed during the current study.
Xu et al. (Mon,) studied this question.