Nitrogen use efficiency gene discovery and breeding application in rice

Overview

Rising global demand for rice, environmental concerns over chemical fertilizer use, and climate-related risks are driving the need for rice varieties with improved nitrogen use efficiency (NUE). This research program aims to identify the key transcription factors and regulatory genes responsible for NUE in rice, providing molecular targets for breeding programs that reduce fertilizer inputs while maintaining or improving yield.

The work combines weighted gene co-expression network analysis (WGCNA) with the GENIE3 algorithm to construct transcriptome-based networks and transcription factor-centered regulatory networks. Candidate regulators are validated through CRISPR/Cas9 knockout and overexpression in transgenic rice lines, creating a clear pipeline from gene discovery to breeding application.

Technical specifications

Approach and methods:

• Strand-specific RNA sequencing (ssRNA-seq) of rice roots collected at multiple time points (1 hour, 1 day, 2 days, 4 days, and 8 days) under low-nitrogen treatment
• Pairwise differential expression analysis across time points to identify low-nitrogen-responsive genes
• WGCNA applied to approximately 4,780 low-nitrogen-inducible differentially expressed genes to build a co-expression network and predict hub genes
• GENIE3 used to construct a transcription factor-centered regulatory network and rank top candidate regulators
• Initial observations identified 12 MYB and 17 NAC transcription factors up-regulated and 22 WRKY transcription factors down-regulated under low nitrogen, with eight top candidate regulators selected for further study
• Validation through Cas9-based knockout and overexpression in transgenic rice lines
• Application of validated key transcription factors in rice breeding for NUE improvement

Technology readiness level

The program is at an early-to-mid discovery and validation stage. RNA-seq datasets and initial co-expression and regulatory network analyses have been completed, and candidate transcription factors have been prioritized. Remaining work includes final network construction, CRISPR-based functional validation in transgenic rice, and application of confirmed genes in breeding lines. The technology readiness level is consistent with pre-commercial research validation, suitable for partnership in further gene validation, breeding trials, and downstream trait development.