Título:	Application of an improved 2-dimensional high-throughput soybean root phenotyping platform to identify novel genetic variants regulating root architecture traits.
Autoria:	CHANDNANI, R. QIN, T. YE, H. HU, H. PANJVANI, K. TOKIZAWA, M. MACIAS, J. M. MEDINA, A. A. BERNARDINO, K. C. PRADIER, P.-L. BANIK, P. MOONEY, A. MAGALHAES, J. V. de NGUYEN, H. T. KOCHIAN, L. V.
Afiliação:	RAHUL CHANDNANI, UNIVERSITY OF SASKATCHEWAN; TONGFEI QIN, UNIVERSITY OF SASKATCHEWAN; HENG YE, UNIVERSITY OF MISSOURI; HAIFEI HU, UNIVERSITY OF WESTERN AUSTRALIA; KARIM PANJVANI, UNIVERSITY OF SASKATCHEWAN; MUTSUTOMO TOKIZAWA, UNIVERSITY OF SASKATCHEWAN; JAVIER MORA MACIAS, UNIVERSITY OF SASKATCHEWAN; ALMA ARMENTA MEDINA, UNIVERSITY OF SASKATCHEWAN; KARINE C. BERNARDINO; PIERRE-LUC PRADIER UNIVERSITY OF SASKATCHEWAN, UNIVERSITY OF SASKATCHEWAN; PANKAJ BANIK, UNIVERSITY OF SASKATCHEWAN; ASHLYN MOONEY, UNIVERSITY OF SASKATCHEWAN; JURANDIR VIEIRA DE MAGALHAES, CNPMS; HENRY T. NGUYEN, UNIVERSITY OF MISSOURI; LEON V. KOCHIAN, UNIVERSITY OF SASKATCHEWAN.
Ano de publicação:	2023
Referência:	Plant Phenomics, v. 5, article 97, 2023.
Conteúdo:	Nutrient-efficient root system architecture (RSA) is becoming an important breeding objective for generating crop varieties with improved nutrient and water acquisition efficiency. Genetic variants shaping soybean RSA is key in improving nutrient and water acquisition. Here, we report on the use of an improved 2-dimensional high-throughput root phenotyping platform that minimizes background noise by imaging pouch-grown root systems submerged in water. We also developed a background image cleaning Python pipeline that computationally removes images of small pieces of debris and filter paper fibers, which can be erroneously quantified as root tips. This platform was used to phenotype root traits in 286 soybean lines genotyped with 5.4 million single-nucleotide polymorphisms. There was a substantially higher correlation in manually counted number of root tips with computationally quantified root tips (95% correlation), when the background was cleaned of nonroot materials compared to root images without the background corrected (79%). Improvements in our RSA phenotyping pipeline significantly reduced overestimation of the root traits influenced by the number of root tips. Genome-wide association studies conducted on the root phenotypic data and quantitative gene expression analysis of candidate genes resulted in the identification of 3 putative positive regulators of root system depth, total root length and surface area, and root system volume and surface area of thicker roots (DOF1-like zinc finger transcription factor, protein of unknown function, and C2H2 zinc finger protein). We also identified a putative negative regulator (gibberellin 20 oxidase 3) of the total number of lateral roots.
Thesagro:	Soja Genética Vegetal Seleção Fenótipa Raiz
Digital Object Identifier:	https://doi.org/10.34133/plantphenomics.0097
Tipo do material:	Artigo de periódico
Acesso:	openAccess
Aparece nas coleções:	Artigo em periódico indexado (CNPMS)