Plant Science Research

Advanced Genomic Approaches: Paving the Way for Improved Forest Genetic Programs

In a breakthrough study by Guilherme Bravim Canal and colleagues (2023), novel genomic methods have been employed to enhance understanding of the genetic architecture behind the trait variability in non-domesticated forest species, specifically in Juçaizeiro, for fruit production.

In many forest genetic improvement initiatives, limited knowledge of kinship or genetic relationships can hinder or even estimate variance components and genetic parameters of target traits impossible. Canal and his team overcame this challenge using a two-pronged approach of mixed models and genomics, considering both additive and non-additive effects.

They studied a group of 275 Juçaizeiro genotypes, phenotyped over three years, for which there was no prior knowledge of genetic relationships. These were then genotyped using whole genome SNP (single nucleotide polymorphism) markers. The results showed that the genomic models provided superior fit quality, the higher prediction accuracy for unbalanced data, and allowed for the decomposition of genetic effects into additive and non-additive terms.

The researchers found that estimates from additive models may be inflated. When they factored in the dominance effect in their models, there were substantial reductions in these estimates. They discovered that this dominance effect strongly influenced traits such as the number of bunches, fresh fruit mass of a bunch, rachis length, fresh mass of 25 fruits, and amount of pulp.

The study’s findings highlight the importance of integrating genomic information-based approaches into forest genetic improvement programs, particularly for populations with strange kinship and experimental designs. They argue that genomic models incorporating dominance effects should be considered for these traits. This could lead to more accurate genomic breeding values and, in turn, result in selective improvements.

Canal and his team’s study sheds light on the additive and non-additive genetic control of the evaluated traits, stressing the vital role of genomic data in revealing the genetic control architecture of quantitative traits. These insights could prove instrumental in advancing the genetic improvement of non-domesticated species, paving the way for more productive and sustainable forest ecosystems.

Photo by Sergei A on Unsplash 


%d bloggers like this: