The Application of New GWAS Methods on the Genetic Dissection of Quantitative Traits in Crops

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 1001

Special Issue Editors


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Guest Editor
College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
Interests: genome-wide association studies; QTL mapping; comparative genomics and bioinformatics
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Guest Editor
Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
Interests: statistical genetics and genomics
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Guest Editor
College of Forestry, Hainan University, Haikou 570228, China
Interests: genomics and bioinformatics
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Guest Editor
Department of Genetics, School of Medicine, University of Noth Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
Interests: statistical genetics and genomics
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Guest Editor
Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
Interests: statistical genomics

Special Issue Information

Dear Colleagues,

Background & history of this topic:

Although genome-wide association study (GWAS) is widely used to mine genes for complex traits, the methodologies of detecting QTNs, QTN-by-environment interactions (QEIs) and QTN-by-QTN interactions (QQIs) are imperfect, e.g., effects to be estimated are confounded, the QEI detection methods are indirect, and polygenic background controls are simple. To address these issues, all the effects to be estimated in QTN, QEI and QQI detection are, respectively, compressed into an effect-related vector, while all the polygenic backgrounds are compressed into one polygenic background. This model was integrated with our mrMLM to establish the 3VmrMLM method that detects all types of loci and estimates their effects. This method is available in animal, plant, forest tree, and human genetics. To further test and improve the new method, it is necessary to analyze real datasets.

Aim and scope of the Special Issue:

Although multiple environment GWAS experiments (MEGE) are frequently conducted, single environment data analyses are frequently reported. Thus, the MEGE should be jointly analyzed via 3VmrMLM, and its purpose is to test 3VmrMLM, compare it with existing methods, and mine more novel genes for complex traits in crops.

Cutting-edge research:

Detecting elite main-effect genes, gene-by-environment interactions, gene-by-gene interaction for complex traits in crops.

What kind of papers we are soliciting:

Reviews; Perspectives; Research

Dr. Yuan-Ming Zhang
Dr. Zhenyu Jia
Dr. Shang-Qian Xie
Dr. Jia Wen
Dr. Shi-Bo Wang
Guest Editors

Manuscript Submission Information

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Keywords

  • 3VmrMLM
  • crop
  • genome-wide association study
  • multi-omics traits
  • quantitative traits

Published Papers

There is no accepted submissions to this special issue at this moment.
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