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

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 t...

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Autores principales: Xiao, Qinlin, Bai, Xiulin, Zhang, Chu, He, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8721248/
https://www.ncbi.nlm.nih.gov/pubmed/35003802
http://dx.doi.org/10.1016/j.jare.2021.05.002
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author Xiao, Qinlin
Bai, Xiulin
Zhang, Chu
He, Yong
author_facet Xiao, Qinlin
Bai, Xiulin
Zhang, Chu
He, Yong
author_sort Xiao, Qinlin
collection PubMed
description 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.
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spelling pubmed-87212482022-01-07 Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review Xiao, Qinlin Bai, Xiulin Zhang, Chu He, Yong J Adv Res Agricultural Science 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. Elsevier 2021-05-12 /pmc/articles/PMC8721248/ /pubmed/35003802 http://dx.doi.org/10.1016/j.jare.2021.05.002 Text en © 2021 The Authors. Published by Elsevier B.V. on behalf of Cairo University. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Agricultural Science
Xiao, Qinlin
Bai, Xiulin
Zhang, Chu
He, Yong
Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review
title Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review
title_full Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review
title_fullStr Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review
title_full_unstemmed Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review
title_short Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review
title_sort advanced high-throughput plant phenotyping techniques for genome-wide association studies: a review
topic Agricultural Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8721248/
https://www.ncbi.nlm.nih.gov/pubmed/35003802
http://dx.doi.org/10.1016/j.jare.2021.05.002
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