From gene to biomolecular networks: a review of evidences for understanding complex biological function in plants

Unlocking nature's secrets: The pivotal role of WRKY transcription factors in plant flowering and fruit development

The WRKY transcription factor family is a key player in the regulatory mechanisms of flowering plants, significantly influencing both their biotic and abiotic response systems as well as being vital to numerous physiological and biological functions. Over the past two decades, the functionality of WRKY proteins has been the subject of extensive research in over 50 plant species, with a strong focus on their roles in responding to various stresses. Despite this extensive research, there remains a notable gap in comprehensive studies aimed at understanding how specific WRKY genes directly influence the timing of flowering and fruit development. This review offers an up-to-date look at WRKY family genes and provides insights into the key genes of WRKY to control flowering, enhance fruit ripening and secondary metabolism synthesis, and maintain fruit quality of various plants, including annuals, perennials, medicinal, and crop plants. The WRKY transcription factors serve as critical regulators within the transcriptional regulatory network, playing a crucial role in the precise enhancement of flowering processes. It is also involved in the up-regulation of fruit ripening was strongly demonstrated by combined transcriptomics and metabolomic investigation. Therefore, we speculated that the WRKY family is known to be a key regulator of flowering and fruiting in plants. This detailed insight will enable the identification of the series of molecular occurrences featuring WRKY proteins throughout the stages of flowering and fruiting.

Identification of the Shared Gene Signatures Between Alzheimer's Disease and Diabetes-Associated Cognitive Dysfunction by Bioinformatics Analysis Combined with Biological Experiment

Background

The connection between diabetes-associated cognitive dysfunction (DACD) and Alzheimer's disease (AD) has been shown in several observational studies. However, it remains controversial as to how the two related.

Objective

To explore shared genes and pathways between DACD and AD using bioinformatics analysis combined with biological experiment.

Methods

We analyzed GEO microarray data to identify DEGs in AD and type 2 diabetes mellitus (T2DM) induced-DACD datasets. Weighted gene co-expression network analysis was used to find modules, while R packages identified overlapping genes. A robust protein-protein interaction network was constructed, and hub genes were identified with Gene ontology enrichment and Kyoto Encyclopedia of Genome and Genome pathway analyses. HT22 cells were cultured under high glucose and amyloid-β 25-35 (Aβ25 - 35) conditions to establish DACD and AD models. Quantitative polymerase chain reaction with reverse transcription verification analysis was then performed on intersection genes.

Results

Three modules each in AD and T2DM induced-DACD were identified as the most relevant and 10 hub genes were screened, with analysis revealing enrichment in pathways such as synaptic vesicle cycle and GABAergic synapse. Through biological experimentation verification, 6 key genes were identified.

Conclusions

This study is the first to use bioinformatics tools to uncover the genetic link between AD and DACD. GAD1, UCHL1, GAP43, CARNS1, TAGLN3, and SH3GL2 were identified as key genes connecting AD and DACD. These findings offer new insights into the diseases' pathogenesis and potential diagnostic and therapeutic targets.

Recent advances in exploring transcriptional regulatory landscape of crops

Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses

The present day's ongoing global warming and climate change adversely affect plants through imposing environmental (abiotic) stresses and disease pressure. The major abiotic factors such as drought, heat, cold, salinity, etc., hamper a plant's innate growth and development, resulting in reduced yield and quality, with the possibility of undesired traits. In the 21st century, the advent of high-throughput sequencing tools, state-of-the-art biotechnological techniques and bioinformatic analyzing pipelines led to the easy characterization of plant traits for abiotic stress response and tolerance mechanisms by applying the 'omics' toolbox. Panomics pipeline including genomics, transcriptomics, proteomics, metabolomics, epigenomics, proteogenomics, interactomics, ionomics, phenomics, etc., have become very handy nowadays. This is important to produce climate-smart future crops with a proper understanding of the molecular mechanisms of abiotic stress responses by the plant's genes, transcripts, proteins, epigenome, cellular metabolic circuits and resultant phenotype. Instead of mono-omics, two or more (hence 'multi-omics') integrated-omics approaches can decipher the plant's abiotic stress tolerance response very well. Multi-omics-characterized plants can be used as potent genetic resources to incorporate into the future breeding program. For the practical utility of crop improvement, multi-omics approaches for particular abiotic stress tolerance can be combined with genome-assisted breeding (GAB) by being pyramided with improved crop yield, food quality and associated agronomic traits and can open a new era of omics-assisted breeding. Thus, multi-omics pipelines together are able to decipher molecular processes, biomarkers, targets for genetic engineering, regulatory networks and precision agriculture solutions for a crop's variable abiotic stress tolerance to ensure food security under changing environmental circumstances.

Application of molecular dynamics simulation for exploring the roles of plant biomolecules in promoting environmental health

Understanding the dynamic changes of plant biomolecules is vital for exploring their mechanisms in the environment. Molecular dynamics (MD) simulation has been widely used to study structural evolution and corresponding properties of plant biomolecules at the microscopic scale. Here, this review (i) outlines structural properties of plant biomolecules, and the crucial role of MD simulation in advancing studies of the biomolecules; (ii) describes the development of MD simulation in plant biomolecules, determinants of simulation, and analysis parameters; (iii) introduces the applications of MD simulation in plant biomolecules, including the response of the biomolecules to multiple stresses, their roles in corrosive environments, and their contributions in improving environmental health; (iv) reviews techniques integrated with MD simulation, such as molecular biology, quantum mechanics, molecular docking, and machine learning modeling, which bridge gaps in MD simulation. Finally, we make suggestions on determination of force field types, investigation of plant biomolecule mechanisms, and use of MD simulation in combination with other techniques. This review provides comprehensive summaries of the mechanisms of plant biomolecules in the environment revealed by MD simulation and validates it as an applicable tool for bridging gaps between macroscopic and microscopic behavior, providing insights into the wide application of MD simulation in plant biomolecules.

Wheat Biofortification: Utilizing Natural Genetic Diversity, Genome-Wide Association Mapping, Genomic Selection, and Genome Editing Technologies

Alleviating micronutrients associated problems in children below five years and women of childbearing age, remains a significant challenge, especially in resource-poor nations. One of the most important staple food crops, wheat attracts the highest global research priority for micronutrient (Fe, Zn, Se, and Ca) biofortification. Wild relatives and cultivated species of wheat possess significant natural genetic variability for these micronutrients, which has successfully been utilized for breeding micronutrient dense wheat varieties. This has enabled the release of 40 biofortified wheat cultivars for commercial cultivation in different countries, including India, Bangladesh, Pakistan, Bolivia, Mexico and Nepal. In this review, we have systematically analyzed the current understanding of availability and utilization of natural genetic variations for grain micronutrients among cultivated and wild relatives, QTLs/genes and different genomic regions regulating the accumulation of micronutrients, and the status of micronutrient biofortified wheat varieties released for commercial cultivation across the globe. In addition, we have also discussed the potential implications of emerging technologies such as genome editing to improve the micronutrient content and their bioavailability in wheat.