Harnessing Crop Wild Diversity for Climate Change Adaptation

Area of Science:

• Agricultural Science
• Genomics
• Plant Breeding

Background:

• Global warming and drought threaten crop production and exacerbate malnutrition.
• Plant genetics offers potential solutions for increasing crop yield and adaptability.
• Rapid climate change necessitates advanced strategies to meet global food demand.

Purpose of the Study:

• To review recent 'big data' genomics advancements for identifying, conserving, and breeding climate-resilient crop varieties.
• To highlight bottlenecks in utilizing genetic variation for abiotic stress tolerance.
• To explore modern analytical approaches for enhancing crop adaptability and yield.

Main Methods:

• Review of empirical and theoretical genomics literature.
• Emphasis on utilizing crop wild relatives and landraces for abiotic stress tolerance.
• Discussion of geo-referencing, environmental data, and genomic prediction.
• Exploration of machine learning and multi-trait gene editing.

Main Results:

• Crop wild relatives adapted to dry environments offer insights into plant responses to drought.
• Habitat-based collections and systematic studies of abiotic stress tolerance are encouraged.
• Genomic prediction, machine learning, and gene editing can accelerate breeding for complex traits.

Conclusions:

• Unlocking hidden adaptive genetic variation in wild species and landraces is key.
• Big data approaches, coupled with trans-disciplinary collaboration and open-source data, are vital.
• These strategies will enhance crop adaptability and yield to meet future food demands under climate change.