Novel genomic tools have a significant role in efforts to revive the American chestnut tree, which has been functionally extinct since the late 19th century when the necrotrophic fungus, which causes chestnut blight, was introduced to North American on Asian chestnuts. Within a few decades, billions of the once-dominant trees in forests from Maine to Mississippi were lost.
Efforts to restore the American chestnut have persisted for more than a century, including by breeding trees resistant to disease. Although introgression of resistance alleles from Chinese chestnuts has contributed to the recovery of American chestnut populations, progress has been slow due to the complex and poorly understood genetic architecture of blight resistance.
Seeking a better understanding, researchers led by Jared W. Westbrook from The American Chestnut Foundation generated chromosome-scale genome assemblies for three pivotal founder chestnuts in hybrid breeding programs. These highly annotated reference genomes enabled detailed comparisons, revealing that most protein-coding genes are shared across species. The analysis, which was published in Science, pinpointed copy number variation as a contributor to blight resistance in Chinese chestnut.
Additional genomic techniques amplified these insights. RNA sequencing captured divergent responses to blight infection in American versus Chinese chestnuts. Metabolite profiling, informed by genomic data, identified high levels of antifungal compounds in Chinese chestnut, offering targets to enhance resistance in American hybrids.
Confronted with this genetic complexity, the researchers report that recurrent selection and multigenerational intercrossing are likely to be more effective at creating resistant hybrids through backcross breeding strategies. “It is important to evaluate genetic gains in tree breeding programs in long-term field trials,” Westbrook notes. “Ideally, individual families should be planted at more than one field site to separate the effects of the local environment from the genetic effects on traits.”
Publication details: Jared W. Westbrook et al. Genomic approaches to accelerate American chestnut restoration. Science 391,730-735(2026).DOI:10.1126/science.adw3225
Efforts to restore the American chestnut have persisted for more than a century, including by breeding trees resistant to disease. Although introgression of resistance alleles from Chinese chestnuts has contributed to the recovery of American chestnut populations, progress has been slow due to the complex and poorly understood genetic architecture of blight resistance.
Seeking a better understanding, researchers led by Jared W. Westbrook from The American Chestnut Foundation generated chromosome-scale genome assemblies for three pivotal founder chestnuts in hybrid breeding programs. These highly annotated reference genomes enabled detailed comparisons, revealing that most protein-coding genes are shared across species. The analysis, which was published in Science, pinpointed copy number variation as a contributor to blight resistance in Chinese chestnut.
Additional genomic techniques amplified these insights. RNA sequencing captured divergent responses to blight infection in American versus Chinese chestnuts. Metabolite profiling, informed by genomic data, identified high levels of antifungal compounds in Chinese chestnut, offering targets to enhance resistance in American hybrids.
Confronted with this genetic complexity, the researchers report that recurrent selection and multigenerational intercrossing are likely to be more effective at creating resistant hybrids through backcross breeding strategies. “It is important to evaluate genetic gains in tree breeding programs in long-term field trials,” Westbrook notes. “Ideally, individual families should be planted at more than one field site to separate the effects of the local environment from the genetic effects on traits.”
Publication details: Jared W. Westbrook et al. Genomic approaches to accelerate American chestnut restoration. Science 391,730-735(2026).DOI:10.1126/science.adw3225