Editorial: Advances in statistical methods for the genetic dissection of complex traits in plants

Yuan-Ming Zhang; Zhenyu Jia; Shang-Qian Xie; Jia Wen; Shibo Wang; Ya-Wen Zhang

doi:10.3389/fpls.2024.1357564

Editorial: Advances in statistical methods for the genetic dissection of complex traits in plants

Front Plant Sci. 2024 Jan 15:15:1357564. doi: 10.3389/fpls.2024.1357564. eCollection 2024.

Authors

Yuan-Ming Zhang¹, Zhenyu Jia², Shang-Qian Xie³, Jia Wen⁴, Shibo Wang², Ya-Wen Zhang⁵

Affiliations

¹ College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China.
² Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA, United States.
³ Department of Animal, Veterinary & Food Sciences, University of Idaho, Moscow, ID, United States.
⁴ Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
⁵ International Genome Center, Jiangsu University, Zhenjiang, China.

No abstract available

Keywords: 3VmrMLM; complex traits; genome-wide association study; multi-omics profiling; plants.

Publication types

Editorial

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The work was supported by the National Natural Science Foundation of China (32070557; 32270673; 32060149).