Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice
dc.contributor.author | Shanks, Carly M. | |
dc.contributor.author | Huang, Ji | |
dc.contributor.author | Cheng, Chia-Yi | |
dc.contributor.author | Shih, Hung-Jui S. | |
dc.contributor.author | Brooks, Matthew D. | |
dc.contributor.author | Alvarez, Jose M. | |
dc.contributor.author | Araus, Viviana | |
dc.contributor.author | Swift, Joseph | |
dc.contributor.author | Henry, Amelia | |
dc.contributor.author | Coruzzi, Gloria M. | |
dc.date.accessioned | 2025-01-20T21:01:03Z | |
dc.date.available | 2025-01-20T21:01:03Z | |
dc.date.issued | 2022 | |
dc.description.abstract | 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. | |
dc.fuente.origen | WOS | |
dc.identifier.doi | 10.3389/fpls.2022.1006044 | |
dc.identifier.issn | 1664-462X | |
dc.identifier.uri | https://doi.org/10.3389/fpls.2022.1006044 | |
dc.identifier.uri | https://repositorio.uc.cl/handle/11534/92813 | |
dc.identifier.wosid | WOS:000895180200001 | |
dc.language.iso | en | |
dc.revista | Frontiers in plant science | |
dc.rights | acceso restringido | |
dc.subject | rice | |
dc.subject | drought | |
dc.subject | nitrogen | |
dc.subject | gene regulatory network | |
dc.subject | network validation | |
dc.subject | NUE | |
dc.subject | GENIE3 | |
dc.subject | WGCNA | |
dc.subject.ods | 02 Zero Hunger | |
dc.subject.odspa | 02 Hambre cero | |
dc.title | Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice | |
dc.type | artículo | |
dc.volumen | 13 | |
sipa.index | WOS | |
sipa.trazabilidad | WOS;2025-01-12 |