文献类型：期刊文献

英文题名：UAV-driven GWAS analysis of canopy temperature and new shoots genetics in slash pine

作者：Li, Yanjie[1] Xu, Cong[3] Zhong, Wenbin[4] Luan, Qifu[1] Wu, Chunyan[2]

第一作者：李彦杰

通信作者：Luan, QF[1];Wu, CY[2]

机构：[1]Chinese Acad Forestry, Res Inst Subtrop Forestry, State Key Lab Tree Genet & Breeding, Hangzhou 311400, Zhejiang, Peoples R China;[2]Chinese Acad Forestry, Res Inst Forestry, State Key Lab Tree Genet & Breeding, Key Lab Tree Breeding & Cultivat Natl Forestry & G, Beijing 100091, Peoples R China;[3]Univ Canterbury, Sch Forestry, Private Bag 4800, Christchurch 8140, New Zealand;[4]Chinese Acad Forestry, Expt Ctr Subtrop Forestry, Xinyu, Jiangxi, Peoples R China

年份：2024

卷号：212

外文期刊名：INDUSTRIAL CROPS AND PRODUCTS

收录：;EI(收录号：20241115747064);Scopus(收录号：2-s2.0-85187544955);WOS:【SCI-EXPANDED(收录号:WOS:001206822200001)】；

基金：This work was funded by the Science and Technology innovation 2030-Agricultural biological breeding major prject (2023ZD040580105) and the Fundamental Research Funds of CAF (CAFYBB2022QA001) .

语种：英文

外文关键词：Forest phenomics; High throughput; Tree breeding; Slash pine; GWAS analysis

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 GenomeWide 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.