4.5 Article

Focused Identification of Germplasm Strategy (FIGS): polishing a rough diamond

Journal

CURRENT OPINION IN INSECT SCIENCE
Volume 45, Issue -, Pages 1-6

Publisher

ELSEVIER
DOI: 10.1016/j.cois.2020.11.001

Keywords

-

Funding

  1. BiodivERsA (the PlantCline project)
  2. SLU Centre for Biological Control
  3. Swedish Research Council FORMAS [2018-01036, 202002376]
  4. Formas [2018-01036] Funding Source: Formas
  5. Vinnova [2018-01036] Funding Source: Vinnova

Ask authors/readers for more resources

Although FIGS is advocated as an efficient approach for predicting and utilizing variation in adaptive traits, it currently has limitations in capturing elusive traits and historical selection pressures. By incorporating nonadaptive evolutionary processes and eco-evolutionary theory, further optimization can enhance the precision of the method and contribute to sustainable plant production.
Focused Identification of Germplasm Strategy (FIGS) has been advocated as an efficient approach to predict and harness variation in adaptive traits in genebanks or wild populations of plants. However, a weakness of the current FIGS approach is that it only utilizes a priori knowledge of one evolutionary factor: natural selection. Further optimization is needed to capture elusive traits, and this review shows that nonadaptive evolutionary processes (gene flow and genetic drift) should be incorporated to increase precision. Focusing on plant resistance to insect herbivores, we also note that historic selection pressures can be difficult to disentangle, and provide suggestions for successful mining based on eco-evolutionary theory. We conclude that with such refinement FIGS has high potential for enhancing breeding efforts and hence sustainable plant production.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available