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UAV-driven GWAS analysis of canopy temperature and new shoots genetics in slash pine

天蓬 湿地松 生物 开枪 斜杠(日志) 农学 植物 松属 生态学
作者
Yanjie Li,Cong Xu,Wenbin Zhong,Qifu Luan,Chunyan Wu
出处
期刊:Industrial Crops and Products [Elsevier]
卷期号:212: 118330-118330 被引量:1
标识
DOI:10.1016/j.indcrop.2024.118330
摘要

Canopy temperature and new shoot counts are pivotal traits for evaluating the adaptability and productivity of slash pine (Pinus elliottii Engelm.). Traditional methods for assessing these traits are labor-intensive and lack the required accuracy. Despite their ecological and economic importance, the genetic and molecular underpinnings of these traits remain largely unexplored. In this study, we utilized UAV remote sensing technology for conducting high-throughput phenotyping of canopy temperature and new shoot counts and performed a Genome-Wide Association Study (GWAS) to identify key candidate genes associated with these traits. Our Manhattan plot analysis revealed intriguing patterns. The GWAS analysis of both July and August identified the same four key candidate genes for new shoot counts including scaffold119881_56626, scaffold119881_56642, scaffold96999_96025, and scaffold7133_48553 respectively. However, for canopy temperature, no key candidate genes were identified in the overall monthly analysis. Interestingly, diurnal variations in canopy temperature influenced the identification of key genes. While no key genes were identified during the afternoon and evening, two were found in the morning: scaffold33143_278946 and super3157_662643. Our UAV-based approach proved to be highly accurate and portable, with significant heritability estimates for both traits. This study represents the first GWAS analysis on these traits and underscores the importance of integrating high-throughput phenotyping and genotyping technologies for advancing forest genetic improvement programs, particularly in the selection of key candidate genes influenced by diurnal and monthly variations.
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