AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
This review surveyed tropical plant species with published whole-genome assemblies and categorized them based on the primary aims of their genomic investigations, illustrating how integrative, multi-dimensional genomic datasets have provided robust insights into tropical plant evolution, adaptation, and trait biology.
This review synthesizes the concepts, methodological advances, computational tools, and recent progress in plant pan-genomics, with a focused emphasis on tropical and subtropical fruit crops.
Medicinal plants constitute a vital resource for traditional and modern healthcare systems, owing to their rich repertoire of bioactive secondary metabolites. In recent years, genome sequencing has emerged as a powerful tool to elucidate the genetic basis of medicinal properties, facilitate conservation, and enable sustainable utilization of these valuable plant resources. Advances in next-generation and third-generation sequencing technologies have led to a rapid increase in the number and quality of sequenced medicinal plant genomes. High-quality chromosome-level assemblies have provided new insights into specialized metabolite biosynthesis, genome evolution, and genetic diversity. However, challenges such as large genome sizes, polyploidy, heterozygosity, and limited functional annotation remain significant. This review summarizes the current status of medicinal plant genome sequencing, highlights major technological and biological achievements, discusses existing challenges, and outlines future directions.
The future of crop improvement using GEd technologies lies in the harmonisation or alignment of global policies and regulations to support the trade of agricultural produce and ensure that growers and consumers can benefit from GEd technology.
Plant bioinformatics has emerged as a cornerstone of modern plant science by enabling the large-scale analysis and interpretation of genomic and post-genomic data for crop improvement. The rapid advancement of high-throughput sequencing technologies, coupled with powerful computational tools, has transformed traditional breeding approaches into data-driven strategies. Bioinformatics facilitates the identification of genes, quantitative trait loci (QTLs), regulatory networks, and molecular markers associated with agronomically important traits, particularly stress tolerance. Abiotic stresses such as drought, salinity, heat, and cold, as well as biotic stresses caused by pathogens and pests, significantly limit crop productivity worldwide. Integrating bioinformatics with genomics, transcriptomics, proteomics, metabolomics, and phenomics has enabled a deeper understanding of plant stress responses and accelerated the development of resilient crop varieties. This review comprehensively discusses the applications of plant bioinformatics in crop improvement and stress tolerance, highlighting major computational approaches, databases, tools, and emerging trends. The challenges and prospects of bioinformatics-driven plant breeding are also critically examined. Jagannath University Journal of Science, Volume 12, Number 1, Jun. 2025, pp. 177−187
This review synthesizes recent progress in Saccharum taxonomy, polyploid genome architecture and evolution, high-quality genomic resource development, germplasm exploration, and genome-informed breeding strategies and proposes an integrated framework connecting taxonomic refinement, genome biology, and breeding applications.
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