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 1033
Special Issue Editors
Interests: genome-wide association studies; QTL mapping; comparative genomics and bioinformatics
Special Issues, Collections and Topics in MDPI journals
Interests: statistical genetics and genomics
Special Issues, Collections and Topics in MDPI journals
Interests: genomics and bioinformatics
Special Issues, Collections and Topics in MDPI journals
Interests: statistical genetics and genomics
Special Issues, Collections and Topics in MDPI journals
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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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.
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Keywords
- 3VmrMLM
- crop
- genome-wide association study
- multi-omics traits
- quantitative traits
