Application of MaxEnt Modeling and HRM Analysis to Support the Conservation and Domestication of Gevuina avellana Mol. in Central Chile

被引:3
作者
Rene Moya-Moraga, Mario [1 ,2 ]
Perez-Ruiz, Cesar [3 ]
机构
[1] Polytech Univ Madrid UPM, Doctoral Program Biotechnol & Genet Resources Pla, Madrid 28040, Spain
[2] Metropolitan Technol Univ UTEM, Fac Nat Sci Math & Environm FCNMM, Dept Biotechnol, Nunoa 7750000, Chile
[3] Polytech Univ Madrid UPM, Sch Agr Food & Biosyst Engn, Dept Biotechnol & Plant Biol, Madrid 28040, Spain
来源
PLANTS-BASEL | 2022年 / 11卷 / 20期
关键词
Gevuina avellana Mol; high-resolution melting analysis (HRM); EST-SSR markers; maximum entropy modeling (MaxEnt); RESOLUTION-MELTING HRM; POTENTIAL DISTRIBUTION; MICROSATELLITE MARKERS; PREDICTING IMPACTS; GENETIC DIVERSITY; ISSR MARKERS; PLANT; EXTRACTION; OIL;
D O I
10.3390/plants11202803
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
The Chilean hazelnut (Gevuina avellana Mol., Proteaceae) is a native tree of Chile and Argentina of edible fruit-type nut. We applied two approaches to contribute to the development of strategies for mitigation of the effects of climate change and anthropic activities in G. avellana. It corresponds to the first report where both tools are integrated, the MaxEnt model to predict the current and future potential distribution coupled with High-Resolution Melting Analysis (HRM) to assess its genetic diversity and understand how the species would respond to these changes. Two global climate models: CNRM-CM6-1 and MIROC-ES2L for four Shared Socioeconomic Pathways: 126, 245, 370, and 585 (2021-2040; 2061-2080) were evaluated. The annual mean temperature (43.7%) and water steam (23.4%) were the key factors for the distribution current of G. avellana (AUC = 0.953). The future prediction model shows to the year 2040 those habitat range decreases at 50% (AUC = 0.918). The genetic structure was investigated in seven natural populations using eight EST-SSR markers, showing a percentage of polymorphic loci between 18.69 and 55.14% and low genetic differentiation between populations (Fst = 0.052; p < 0.001). According to the discriminant analysis of principal components (DAPC) we identified 10 genetic populations. We conclude that high-priority areas for protection correspond to Los Avellanos and Punta de aguila populations due to their greater genetic diversity and allelic richness.
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页数:29
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