Dissecting the genetic architecture of key agronomic traits in lettuce using a MAGIC population

The MAGIC population's lack of structure and high mapping resolution enables the efficient dissection of complex traits. The identified loci and candidate genes provide significant genetic resources for improving agronomic performance and leaf quality in lettuce.

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Publication Details

Journal
Genome biology
Published
2025-03-23
DOI
https://doi.org/10.1186/s13059-025-03541-6
Citations
8
Primary Topic
Genetics and Plant Breeding
Type
article
Field-Weighted Citation Impact
14.00

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article

Dissecting the genetic architecture of key agronomic traits in lettuce using a MAGIC population

Hui Feng, Ruifang Zhai, Dean Lavelle, Zedong Geng et al.
8 citations
Genome biology
Genetics and Plant Breeding
14.00
article

Dissecting the genetic architecture of key agronomic traits in lettuce using a MAGIC population

Hui Feng, Ruifang Zhai, Dean Lavelle, Zedong Geng, Yue Jia, Wandi Wang, Richard W. Michelmore, Jiongjiong Chen, Tong Wei, Wanneng Yang, Junru An, Guangbao Luo, Jianzhong Zhu, Hanhui Kuang, Shoulong Deng, Qiwei Tang, Ting Zhu, Meng‐Lu Wang, Sunil Kumar Sahu, Xin Wang, Huan Liu, Xiaoyan Zhang, Weiyi Zhang, Jiansheng Liu, Weibo Li, Hongyun Chen
article en
8 citations

Abstract

The MAGIC population's lack of structure and high mapping resolution enables the efficient dissection of complex traits. The identified loci and candidate genes provide significant genetic resources for improving agronomic performance and leaf quality in lettuce.

Genome biologyVol. 26(1)
BGI Group (China) (CN), Huazhong Agricultural University (CN), BGI Research (CN), University of California, Davis (US)
U.S. Department of Agriculture, National Natural Science Foundation of China, Natural Science Foundation of Hubei Province, Huazhong Agricultural University
Zero hunger
Openalex Percentile: Top 1%
Genetics and Plant Breeding
14.00
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