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Bridging the Pangenome Gap

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A new webapp could help scientists more rapidly breed staple food crops


ARS research biologist Xianran Li, the leader of the BRIDGEcereal project, using BRIDGEcereal.

Cereal crops such as wheat, corn, rice, barley, and sorghum are staple foods in nearly every regional diet across the globe. Global population growth, climate change, and the demand for quality food continue to put pressure on improving these crops. Changing climate conditions, emerging pests and diseases, and the use of pesticides and herbicides can limit production or affect traits desired by farmers and consumers, such as yield, taste, size, shelf life, and nutritional components.

While breeding new cultivars through genetic improvement can help meet the mounting demand for higher yields and better quality, the process is time-consuming; it can take years or even decades to improve a single trait. One of the bottlenecks is identifying the beneficial alleles underlying the desired traits, so that these alleles can be incorporated to breed elite cultivars. An allele is an alternative version of a specific gene.

Recent advances in sequencing technologies have the potential to significantly speed up this process by overcoming this bottleneck. Assembling multiple reference-grade genomes for the same crop species, called a pan-genome, enables researchers to catalog an entire spectrum of DNA polymorphisms (changes in the DNA genetic code) present in natural germplasm, including both small and large variants.

“From a cataloged polymorphism database, scientists can quickly identify large indel (insertion or deletion in the genome of an organism) DNA polymorphisms that alter gene expression or structure and select the beneficial alleles for developing new cultivars with a suite of desired traits,” said Xianran Li, research biologist at ARS’s Wheat, Health, Genetics, and Quality Research Unit in Pullman, WA. “Integration of pan-genome and other technologies such as gene editing and genomic selection presents a promising opportunity to accelerate the process of crop improvement through breeding to meet the ever-growing demand for high-quality crops more efficiently and effectively.”

In order to utilize these advances in sequencing technologies, researchers must be well versed in the field of bioinformatics, which are complex computation and analysis tools used to interpret biological data. However, the development of bioinformatic tools has not kept pace with pan-genome sequencing. As a result, publicly available pan-genomes remain largely inaccessible to scientists.

To address this challenge, Li and his team coordinated with ARS’s Partnership for Data Innovation and SCINet teams to develop the "BRIDGEcereal" webapp based on novel machine learning algorithms. The interactive graphical user interface allows scientists to efficiently mine publicly available pan-genome for all five major cereal crops. To identify potential large indels for genes of interest, the only requirement is the gene model ID.

Li and his team demonstrated the potential of BRIDGEcereal in uncovering promising causal large indel polymorphisms for wheat genes underlying three different kinds of traits.

“We hope this webapp can help to bridge the genome-to-phenome gap and accelerate gene discovery and characterization to improve crops,” said Bosen Zhang, Postdoctoral Research Associate leading the project.

By leveraging BRIDGEcereal, scientists can more efficiently and effectively breed cereal crops to adapt to changing climate conditions, make crops more resistant to pests and disease, and develop more appealing traits for farmers and consumers. Most importantly, these new technologies can ensure that communities across the globe have sustainable access to their most important food crops. By Todd Silver, ARS Office of Communications