Integrative genomics and zero‐shot deep learning–based phenotyping reveal the genetic architecture of seed traits in mungbean (Vigna radiata L.)
Venkata Naresh Boddepalli, Talukder Zaki Jubery, Steven B. Cannon, Andrew Farmer, Somak Dutta, Baskar Ganapathysubramanian, Arti Singh · 2026
Read Integrative genomics and zero‐shot deep learning–based phenotyping reveal the genetic architecture of seed traits in mungbean (Vigna radiata L.) by Venkata Naresh Boddepalli, Talukder Zaki Jubery, Steven B. Cannon, Andrew Farmer, Somak Dutta, Baskar Ganapathysubramanian, Arti Singh (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13492609.txt.
Description
Venkata Naresh Boddepalli and co-authors map the genes behind seed size and weight in mungbean, in a 2026 study. Bigger, heavier seeds are a main breeding goal for this food crop. The team paired gene scans with a deep learning tool that measures seeds from images without needing training examples for this crop.
The image tool measured seed traits with high accuracy, and those traits tracked seed weight closely. Gene scans found more than eighty markers across seven traits, with a set of shared markers that shape several seed features at once. A few gene regions explained more than a fifth of the trait gaps. Prediction models using the full gene profile worked well for selection. The authors offer the markers and models as a base for faster breeding of higher-yield mungbean.
Catalog record
| CREATOR | Venkata Naresh Boddepalli, Talukder Zaki Jubery, Steven B. Cannon, Andrew Farmer, Somak Dutta, Baskar Ganapathysubramanian, Arti Singh |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 79 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |