Background

The global agricultural ecosystem faces an unprecedented crisis due to climate change and the spread of pests. Extreme droughts and unpredictable heatwaves are drastically reducing the yields of traditional major crops. Researchers and breeders worldwide have been focusing on the genetic traits of wild relatives and landraces to develop new varieties capable of surviving harsh environments.

Research institutions, including the Agricultural Research Service (ARS) under the U.S. Department of Agriculture (USDA), have collected hundreds of thousands of plant genetic resources from around the world over the past several decades and stored them in seed banks such as the National Plant Germplasm System (NPGS). Seed specimens stored frozen in the repository are regarded as a treasure trove, possessing valuable traits such as drought resistance, disease tolerance, and high nutritional content.

However, this massive repository has long functioned like a closed box. While the physical characteristics and basic growth information of the collected seeds were recorded, the precise DNA sequences and alleles responsible for expressing specific traits had not been decoded. To find genes resistant to specific pathogens, breeders had to undergo the tedious process of directly planting, growing, and crossing hundreds or thousands of seeds. This led to continuous criticism that the actual utility for crop improvement was low compared to the massive preservation costs.

Key Findings

The U.S. Department of Agriculture has decided to launch a new $180 million project to sequence the DNA of vast crop genetic resources stored in the National Plant Germplasm System. This investment is a national-scale project that goes beyond simple individual crop surveys, mapping high-resolution genomic variations of over 100,000 major food and economic crops preserved in the U.S. National Plant Germplasm System.

Researchers plan to advance reference genomes and build a pan-genome ecosystem by combining Next-Generation Sequencing (NGS) and long-read sequencing technologies. Traditional genomics, which relied only on the standard sequences of single varieties, struggled to capture gene deletions or large-scale structural variations. This project has included not only core crops such as corn, soybean, wheat, sorghum, and cotton but also wild ancestors with climate resilience in its large-scale analysis list.

The genomic analysis pipeline will combine high-speed sequencing with AI-based variant annotation technology. Researchers plan to collect whole-genome sequences for each seed lineage while linking them with the ARS's vast phenotypic and genotypic data. By converting gene locations and functions into a digital catalog, the foundation will be laid so that breeders worldwide can immediately track specific environmental resistance genes through simple browser searches.

Significance and Outlook

This project to digitize hundreds of thousands of plant specimens is expected to be a turning point, shifting the paradigm of molecular breeding from physical cross-selection to data-driven precision breeding. Researchers will be able to use CRISPR gene-editing technology to precisely introduce superior stress-tolerance genes found in wild species into existing high-yield varieties, or significantly increase the predictive accuracy of genomic selection algorithms.

Given the significant expected effects, the prerequisites are also clear. The computing infrastructure costs for standardizing vast sequence data and managing/maintaining an open platform accessible to everyone are substantial. Furthermore, even after sequence information is obtained, the bottleneck of field phenotyping—verifying whether these genes express the same resistance traits in actual fields with varying temperature, humidity, and soil conditions—must be resolved.