Agarwood is a resinous part of the non-timber Aquilaria tree, which is a highly valuable product for medicine and fragrance purposes. To protect the endangered Aquilaria species, mass plantation of Aquilaria trees has become a sustainable way in Asian countries to obtain the highly valuable agarwood. As only physiologically triggered Aquilaria tree can produce agarwood, effective induction methods are long sought in the agarwood industry. In this paper, we attempt to provide an overview for the past efforts toward the understanding of agarwood formation, the evolvement of induction methods and their further development prospects by integrating it with high-throughput omics approaches.

Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties’ resistance to salt stress is a viable solution for meeting global food demand. Adaptation to salt stress is a multifaceted process that involves interacting physiological traits, biochemical or metabolic pathways, and molecular mechanisms. The integration of multi-omics approaches contributes to a better understanding of molecular mechanisms as well as the improvement of salt-resistant and tolerant rice varieties. Firstly, we present a thorough review of current knowledge about salt stress effects on rice and mechanisms behind rice salt tolerance and salt stress signalling. This review focuses on the use of multi-omics approaches to improve next-generation rice breeding for salinity resistance and tolerance, including genomics, transcriptomics, proteomics, metabolomics and phenomics. Integrating multi-omics data effectively is critical to gaining a more comprehensive and in-depth understanding of the molecular pathways, enzyme activity and interacting networks of genes controlling salinity tolerance in rice. The key data mining strategies within the artificial intelligence to analyse big and complex data sets that will allow more accurate prediction of outcomes and modernise traditional breeding programmes and also expedite precision rice breeding such as genetic engineering and genome editing.

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.

The application of miRNA mimic technology for silencing mature miRNA began in 2007. This technique originated from the discovery of the INDUCED BY PHOSPHATE STARVATION 1 (IPS1) gene, which was found to be a competitive mimic that prevents the cleavage of the targeted mRNA by miRNA inhibition at the post-transcriptional level. To date, various studies have been conducted to understand the molecular mimic mechanism and to improve the efficiency of this technology. As a result, several mimic tools have been developed: target mimicry (TM), short tandem target mimic (STTM), and molecular sponges (SPs). STTM is the most-developed tool due to its stability and effectiveness in decoying miRNA. This review discusses the application of STTM technology on the loss-of-function studies of miRNA and members from diverse plant species. A modified STTM approach for studying the function of miRNA with spatial–temporal expression under the control of specific promoters is further explored. STTM technology will enhance our understanding of the miRNA activity in plant-tissue-specific development and stress responses for applications in improving plant traits via miRNA regulation.