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Microsatellite SSR OkraDb

Okra (Abelmoschus esculentus) is a highly nutritious vegetable crop, widely cultivated in tropical and subtropical regions. Despite its recognized health benefits, the mechanisms underlying its rich nutrient content remain largely unexplored. This study presents a chromosome-scale genome of okra, with a size of 1.19 Gb, providing valuable insights into its genetic makeup.

Known for its multiple health benefits, okra (Abelmoschus esculentus L.), also referred to as lady’s fingers, belongs to the Malvaceae family. It is not only a popular horticultural crop but also serves a medicinal role in treating conditions such as chronic dysentery, gonorrhea, urinary incontinence, and diarrhea. Recent pharmacological research highlights its antioxidant, anti-inflammatory, immunomodulatory, lipid-lowering, anticancer, antimicrobial, and antidiabetic properties. Studies have shown that dietary supplementation with okra polysaccharides can reduce body weight, blood glucose levels, and total serum cholesterol in C57BL/6 mice on a high-fat diet. The medicinal benefits of okra are attributed to its rich bioactive compounds, including phenolic acids, alkaloids, and flavonoids.

In addition, we present OkraDB, a specialized SSR (simple sequence repeat) database for Abelmoschus esculentus. This platform provides access to genome-wide SSR markers, which are crucial for genetic diversity studies, marker-assisted selection, and crop improvement. With a user-friendly interface, OkraDB allows easy searches for SSRs based on chromosome, scaffold, or motif type, offering valuable insights into the genetic architecture of okra. By harnessing the power of microsatellite markers, OkraDB plays a significant role in enhancing the crop’s nutritional value, disease resistance, and agronomic traits, supporting the advancement of okra genomics and breeding programs.

Abelmoschus esculentus OKRA

ICAR Data Use Licence

This database has been developed under DBT funded project

Establishment of Centre for Bioinformatics and Computational Biology in Agriculture- BIC at