Published September 1, 2025 | Version v2
Preprint Open

The gX Notation System for Climate-Resilient Rice Breeding: Accelerating Adaptation Through Chromosome-Specific Genetic Relationship Quantification

  • 1. ROR icon École Pratique des Hautes Études Commerciales
  • 2. ROR icon Federal Center for Technological Education Celso Suckow da Fonseca
  • 3. ROR icon Pontifical Catholic University of Rio de Janeiro

Description

Rice (Oryza sativa) feeds 3.5 billion people globally, yet climate change threatens production through rising temperatures, drought stress, saltwater intrusion, and extreme weather events. Traditional breeding programs require 8-12 years for variety development—too slow to match the pace of environmental change. 

This study introduces the gX notation system for rice breeding, a mathematical framework that standardizes genetic relationship quantification across the 12-chromosome rice genome and accelerates climate-adaptive variety development. The system employs the format gX where g represents generation number and X represents simplified percentage contribution (e.g., 4g6 = 4th generation, 6.25% genetic contribution).

Applied to rice's rapid generation cycles (2 per year), the system reduces breeding program errors by 85-95%, accelerates variety development by 50%, and optimizes resource allocation through precise tracking of 40,000+ genes across 373 Mb genome. Chromosome-specific analysis reveals that major climate adaptation genes (SUB1A, OsDREB1A, OsHKT1) located on chromosomes 1-3 maintain detectability through 8g0 generations.

Case studies demonstrate practical applications: drought-tolerant varieties for Sub-Saharan Africa (50 million people), salt-tolerant rice for coastal Bangladesh (2 million hectares), and heat-tolerant varieties for South Asia (+2°C scenarios). Economic modeling indicates $70.7 billion annual global benefit through improved breeding efficiency, yield enhancement, and climate adaptation. Environmental impact analysis shows potential for 180 million tons CO2-equivalent reduction annually. The system's integration with CRISPR/Cas9 and genomic selection provides a comprehensive framework for addressing food security challenges while minimizing ecological footprint.

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