Abstract:
Objective Explore the growth adaptability pattern of Populus euphratica root under normal and salt stress conditions, effectively locate the significant quantitative trait loci (QTL) that affect the phenotypic traits of P. euphratica root, visualize the genetic regulation network, and explore the genetic regulation mechanism of the phenotypic traits of P. euphratica root under salt stress.
Method Based on phenotypic and genotypic data of P. euphratica under normal and salt stress conditions, statistical methods such as principal component analysis, variance analysis, and dynamic model fitting were used to analyze phenotypic variation patterns, locate significant QTL by functional mapping, and visualize the genetic network of phenotypic traits in the root system under salt stress.
Result (1) Correlation analysis showed that P. euphratica root traits exhibited high synergy under normal conditions, but under salt stress, the roots reduced in number while increasing in average length. PCA identified main root length, main root surface area, and main root number as the primary phenotypic traits for study. Compared to normal conditions, salt stress inhibited the growth of these three traits. Comparison of the goodness-of-fit R2 revealed that the Gompertz model performed best among Logistic, Richards, and Weibull growth equations. (2) Under normal conditions, 100, 89, and 85 significant QTLs regulating main root length, main root surface area, and main root number were identified, respectively, mainly distributed on linkage groups 1, 4, 5, 14, and 15. Under salt stress, 91, 85, and 87 significant QTLs regulating these three traits were located, concentrated on linkage groups 2, 3, 5, 13, and 18. (3) Genetic effect analysis showed that the significant QTLs affecting main root length exhibited continuously increasing genetic effects over time under both conditions. The significant QTLs influencing main root number mainly showed a continuous increase, with some loci displaying trends of first increasing then decreasing or first decreasing then increasing. The significant QTLs affecting main root surface area exhibited three patterns under normal conditions: first increasing then decreasing, continuously fluctuating upwards, and first increasing then decreasing before increasing again, while most showed a continuous increase under salt stress. (4) Under normal conditions, 21, 14, and 14 candidate genes were annotated for traits of main root length, main root surface area, and main root number, respectively, mainly involved in basic metabolic processes, auxin transport, and chromosome segregation functions. Under salt stress, 19, 17, and 15 candidate genes were annotated for these traits, respectively, primarily enriched in stress response, redox balance, iron ion transport, and tRNA modification functions. (5) The genetic network was visualized, revealing hub genes (LOC105114908 and LOC105120566) might involve in P. euphratica’s response to salt stress.
Conclusion Salt stress significantly affected the growth and development of P. euphratica roots. Using various statistical models, significant QTLs influencing root growth were located, demonstrating their dynamic genetic effects with environmental changes. The results provide new insights into understanding the genetic regulatory basis of P. euphratica’s adaptation to salt stress and offer methodological support for forest tree genetic improvement research.