Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice

Nitrogen (N) and Water (W) - two resources critical for crop productivity – are becoming increasingly limited in soils globally. To address this issue, we aim to uncover the gene regulatory networks (GRNs) that regulate nitrogen use efficiency (NUE) - as a function of water availability - in Oryza s...

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Autores principales: Shanks, Carly M., Huang, Ji, Cheng, Chia-Yi, Shih, Hung-Jui S., Brooks, Matthew D., Álvarez, José M., Araus, Viviana, Swift, Joseph, Henry, Amelia, Coruzzi, Gloria M.
Formato: Journal Article
Lenguaje:Inglés
Publicado: Frontiers Media 2022
Materias:
Acceso en línea:https://hdl.handle.net/10568/127525
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author Shanks, Carly M.
Huang, Ji
Cheng, Chia-Yi
Shih, Hung-Jui S.
Brooks, Matthew D.
Álvarez, José M.
Araus, Viviana
Swift, Joseph
Henry, Amelia
Coruzzi, Gloria M.
author_browse Araus, Viviana
Brooks, Matthew D.
Cheng, Chia-Yi
Coruzzi, Gloria M.
Henry, Amelia
Huang, Ji
Shanks, Carly M.
Shih, Hung-Jui S.
Swift, Joseph
Álvarez, José M.
author_facet Shanks, Carly M.
Huang, Ji
Cheng, Chia-Yi
Shih, Hung-Jui S.
Brooks, Matthew D.
Álvarez, José M.
Araus, Viviana
Swift, Joseph
Henry, Amelia
Coruzzi, Gloria M.
author_sort Shanks, Carly M.
collection Repository of Agricultural Research Outputs (CGSpace)
description Nitrogen (N) and Water (W) - two resources critical for crop productivity – are becoming increasingly limited in soils globally. To address this issue, we aim to uncover the gene regulatory networks (GRNs) that regulate nitrogen use efficiency (NUE) - as a function of water availability - in Oryza sativa, a staple for 3.5 billion people. In this study, we infer and validate GRNs that correlate with rice NUE phenotypes affected by N-by-W availability in the field. We did this by exploiting RNA-seq and crop phenotype data from 19 rice varieties grown in a 2x2 N-by-W matrix in the field. First, to identify gene-to-NUE field phenotypes, we analyzed these datasets using weighted gene co-expression network analysis (WGCNA). This identified two network modules ("skyblue" & "grey60") highly correlated with NUE grain yield (NUEg). Next, we focused on 90 TFs contained in these two NUEg modules and predicted their genome-wide targets using the N-and/or-W response datasets using a random forest network inference approach (GENIE3). Next, to validate the GENIE3 TF→target gene predictions, we performed Precision/Recall Analysis (AUPR) using nine datasets for three TFs validated in planta. This analysis sets a precision threshold of 0.31, used to "prune" the GENIE3 network for high-confidence TF→target gene edges, comprising 88 TFs and 5,716 N-and/or-W response genes. Next, we ranked these 88 TFs based on their significant influence on NUEg target genes responsive to N and/or W signaling. This resulted in a list of 18 prioritized TFs that regulate 551 NUEg target genes responsive to N and/or W signals. We validated the direct regulated targets of two of these candidate NUEg TFs in a plant cell-based TF assay called TARGET, for which we also had in planta data for comparison. Gene ontology analysis revealed that 6/18 NUEg TFs - OsbZIP23 (LOC_Os02g52780), Oshox22 (LOC_Os04g45810), LOB39 (LOC_Os03g41330), Oshox13 (LOC_Os03g08960), LOC_Os11g38870, and LOC_Os06g14670 - regulate genes annotated for N and/or W signaling. Our results show that OsbZIP23 and Oshox22, known regulators of drought tolerance, also coordinate W-responses with NUEg. This validated network can aid in developing/breeding rice with improved yield on marginal, low N-input, drought-prone soils.
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spelling CGSpace1275252025-12-08T10:29:22Z Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice Shanks, Carly M. Huang, Ji Cheng, Chia-Yi Shih, Hung-Jui S. Brooks, Matthew D. Álvarez, José M. Araus, Viviana Swift, Joseph Henry, Amelia Coruzzi, Gloria M. rice drought nitrogen genes Nitrogen (N) and Water (W) - two resources critical for crop productivity – are becoming increasingly limited in soils globally. To address this issue, we aim to uncover the gene regulatory networks (GRNs) that regulate nitrogen use efficiency (NUE) - as a function of water availability - in Oryza sativa, a staple for 3.5 billion people. In this study, we infer and validate GRNs that correlate with rice NUE phenotypes affected by N-by-W availability in the field. We did this by exploiting RNA-seq and crop phenotype data from 19 rice varieties grown in a 2x2 N-by-W matrix in the field. First, to identify gene-to-NUE field phenotypes, we analyzed these datasets using weighted gene co-expression network analysis (WGCNA). This identified two network modules ("skyblue" & "grey60") highly correlated with NUE grain yield (NUEg). Next, we focused on 90 TFs contained in these two NUEg modules and predicted their genome-wide targets using the N-and/or-W response datasets using a random forest network inference approach (GENIE3). Next, to validate the GENIE3 TF→target gene predictions, we performed Precision/Recall Analysis (AUPR) using nine datasets for three TFs validated in planta. This analysis sets a precision threshold of 0.31, used to "prune" the GENIE3 network for high-confidence TF→target gene edges, comprising 88 TFs and 5,716 N-and/or-W response genes. Next, we ranked these 88 TFs based on their significant influence on NUEg target genes responsive to N and/or W signaling. This resulted in a list of 18 prioritized TFs that regulate 551 NUEg target genes responsive to N and/or W signals. We validated the direct regulated targets of two of these candidate NUEg TFs in a plant cell-based TF assay called TARGET, for which we also had in planta data for comparison. Gene ontology analysis revealed that 6/18 NUEg TFs - OsbZIP23 (LOC_Os02g52780), Oshox22 (LOC_Os04g45810), LOB39 (LOC_Os03g41330), Oshox13 (LOC_Os03g08960), LOC_Os11g38870, and LOC_Os06g14670 - regulate genes annotated for N and/or W signaling. Our results show that OsbZIP23 and Oshox22, known regulators of drought tolerance, also coordinate W-responses with NUEg. This validated network can aid in developing/breeding rice with improved yield on marginal, low N-input, drought-prone soils. 2022-11-25 2023-01-19T11:11:55Z 2023-01-19T11:11:55Z Journal Article https://hdl.handle.net/10568/127525 en Open Access application/pdf Frontiers Media Shanks, C.M., Huang, J., Cheng, C.-Y., Shih, H.-J.S., Brooks, M.D., Alvarez, J.M., Araus, V., Swift, J., Henry, A. and Coruzzi, G.M. 2022. Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice. Frontiers in Plant Science 13:1006044.
spellingShingle rice
drought
nitrogen
genes
Shanks, Carly M.
Huang, Ji
Cheng, Chia-Yi
Shih, Hung-Jui S.
Brooks, Matthew D.
Álvarez, José M.
Araus, Viviana
Swift, Joseph
Henry, Amelia
Coruzzi, Gloria M.
Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice
title Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice
title_full Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice
title_fullStr Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice
title_full_unstemmed Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice
title_short Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice
title_sort validation of a high confidence regulatory network for gene to nue phenotype in field grown rice
topic rice
drought
nitrogen
genes
url https://hdl.handle.net/10568/127525
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