Yu, Le
- Department of Plant Biology, Swedish University of Agricultural Sciences
- Chinese Academy of Agricultural Sciences
Abstract
With its high soluble protein content, large biomass yield, and ease of cultivation, tobacco leaves show strong potential as a novel protein source for livestock. However, the genetic basis underlying leaf protein content remains poorly understood, necessitating the use of genomic prediction models to screen germplasm resources and accelerate the improvement of this trait in future breeding programs. To address this, we analyzed 2517 tobacco germplasm accessions from the Chinese National Tobacco Germplasm Resource Bank, which represent broad genetic diversity, to investigate the genetic architecture of leaf protein content and construct genomic prediction models. Tobacco leaf protein content exhibited a moderate heritability of 0.16, and association analysis identified a significant peak that explained approximately 1% of the phenotypic variance. We further evaluated the performance of 16 mainstream genomic prediction models using five-fold cross-validation. Among these models, best linear unbiased prediction (rrBLUP) model achieved the highest prediction accuracy (0.87). In addition, rrBLUP required less computational time and resources compared with other models, highlighting its stability and efficiency. Field validation (Longshan County, Hunan Province, 111 degrees 37 ' 45 '' E, 27 degrees 30 ' 52 '' N) confirmed the robustness and accuracy of our genomic selection model. Overall, our results demonstrate that genomic prediction can enable rapid screening of tobacco germplasm resources and substantially enhance the efficiency of developing high-protein varieties.
Keywords
Nicotiana tabacum; Leaf protein content; Genomic selection; Genome-wide association study; Germplasm
Published in
Industrial Crops and Products
2026, volume: 243, article number: 123090
Publisher: ELSEVIER
SLU Authors
UKÄ Subject classification
Genetics and Breeding in Agricultural Sciences
Publication identifier
- DOI: https://doi.org/10.1016/j.indcrop.2026.123090
Permanent link to this page (URI)
https://res.slu.se/id/publ/146761