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Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review

Authors :
Qinlin Xiao
Xiulin Bai
Chu Zhang
Yong He
Source :
Journal of Advanced Research, Vol 35, Iss , Pp 215-230 (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Background: Linking phenotypes and genotypes to identify genetic architectures that regulate important traits is crucial for plant breeding and the development of plant genomics. In recent years, genome-wide association studies (GWASs) have been applied extensively to interpret relationships between genes and traits. Successful GWAS application requires comprehensive genomic and phenotypic data from large populations. Although multiple high-throughput DNA sequencing approaches are available for the generation of genomics data, the capacity to generate high-quality phenotypic data is lagging far behind. Traditional methods for plant phenotyping mostly rely on manual measurements, which are laborious, inaccurate, and time-consuming, greatly impairing the acquisition of phenotypic data from large populations. In contrast, high-throughput phenotyping has unique advantages, facilitating rapid, non-destructive, and high-throughput detection, and, in turn, addressing the shortcomings of traditional methods.Aim of Review: This review summarizes the current status with regard to the integration of high-throughput phenotyping and GWAS in plants, in addition to discussing the inherent challenges and future prospects.Key Scientific Concepts of Review: High-throughput phenotyping, which facilitates non-contact and dynamic measurements, has the potential to offer high-quality trait data for GWAS and, in turn, to enhance the unraveling of genetic structures of complex plant traits. In conclusion, high-throughput phenotyping integration with GWAS could facilitate the revealing of coding information in plant genomes.

Details

Language :
English
ISSN :
20901232
Volume :
35
Issue :
215-230
Database :
Directory of Open Access Journals
Journal :
Journal of Advanced Research
Publication Type :
Academic Journal
Accession number :
edsdoj.8c69562f0774f32884feca84b7939b8
Document Type :
article
Full Text :
https://doi.org/10.1016/j.jare.2021.05.002