Evaluating the accuracy of genomic prediction for the management and conservation of relictual natural tree populations

Abstract

Studying and understanding the evolution of relictual natural populations is critical for developing conservation initiatives of endangered species, such as management in situ and assisted migration. Recently, genomic and bioinformatics tools have promised a wide avenue for developing more efficient programs. Genomic prediction (GP) models are one of such tools; although, in trees, only some successful examples exit. They have mostly been used to increase predictive ability in commercial traits and reduce breeding cycle length. Thus, it remains to be tested whether GP can be extended for the management and conservation of natural small and secluded populations. Here, we explored such a possibility in a pilot study to predict the performance of introduced saplings in a managed population of sacred fir (Abies religiosa; Pinaceae) in central Mexico. We genotyped over 200 naturally re-generated and introduced individuals with 2286 single nucleotide polymorphisms (SNP), derived from genotyping by sequencing, and used them to develop GP models for growth and physiological traits. After testing different training and validation datasets, and determining predictive ability of “across-groups” models with cross-validation techniques, acceptable predictive abilities (ry) were obtained for growth during the previous growing season, water potential, stem diameter, and aboveground biomass (0.36, 0.27, 0.26, and 0.24, respectively). The best models were always those built with natural saplings and used to predict the early performance of introduced individuals in the same environment, although fair predictabilities were also obtained when predicting performance between natural populations. Model fine-tuning resulted in reduced datasets of approximately 700 SNPs that helped optimizing phenotype predictability, particularly for water potential, for which ry was up to 0.28. These pilot-scale results are preliminary but encouraging and justify additional research efforts for implementing GP in small and secluded natural populations, particularly for endangered non-model species.

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Acknowledgments

We express our gratitude to the “ejidatarios” from Rincón de Guadalupe and San Bartolo and Andrés Juarez, Eusebio Roldán, and Lucia Madrid at the “Consejo Civil Mexicano para la Sivilcultura Sotenible” for granting access to the forest trials and sharing their knowledge. We also thank Gustavo Giles, Veronica Reyes, Jorge Cruz, Alfredo Villarruel, Karen Carrasco, and Armando Sunny for fieldwork assistance, and Tania Garrido, Nancy Gálvez, Laura Giraldo, and Azalea Guerra for valuable help in laboratory analyses. We are grateful to Ernesto Campos, Felipe López-Hernández, Leopoldo Vázquez, and Gustavo Giles for assistance in bioinformatics analyses. We additionally thank the Department of Environmental and Soil Sciences of the Institute of Geology (UNAM) for edaphic analyses and the Functional Ecology (IE-UNAM) and Tissue Culture (Jardín Botánico-UNAM) laboratories at UNAM, and the Department of Forest Sciences at Universidad Nacional de Colombia for logistic support. Bioinformatic analyses were performed on a computing cluster at the Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), which is supported by the system administrator and the subcoordinación de soporte informático at CONABIO. This paper is part of the doctoral research conducted by SA, who thanks the “Posgrado en Ciencias Biológicas at the Universidad Nacional Autónoma de México” and acknowledges a scholarship from the “Consejo Nacional de Ciencia y Tecnología (CONACyT; grant no. 480152)”.

Data archiving statement

Data will be available in the FigShare data repository (https://figshare.com/) upon manuscript acceptance. Access links will be provided when available.

Funding

This work was financially supported by grants from CONACyT (CB-2016-284457 and 278987) and both the “Dirección General de Asuntos del Personal Académico” (PAPIIT project: IN208416) and the Institute of Ecology (presupuesto operativo) at UNAM to JPJ-C.

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SA, AM-Y, and JPJ-C designed the study. SA and AM-Y performed fieldwork. SA carried out molecular and phenotypic analyses. SA and AJC performed statistical analyses and interpreted results. SA and JPJ-C drafted the manuscript. All authors reviewed and approved the final manuscript.

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Correspondence to Juan Pablo Jaramillo-Correa.

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Authors declare that the work here described has not been previously published and is not under consideration for publication elsewhere. In addition, its publication is approved by all authors and the responsible authorities where the field work was carried out (Consejo Civil Mexicano para la Silvicultura Sostenible), and that, if accepted, it will not be published elsewhere in the same form, in English or any other language, including electronically.

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Arenas, S., Cortés, A.J., Mastretta-Yanes, A. et al. Evaluating the accuracy of genomic prediction for the management and conservation of relictual natural tree populations. Tree Genetics & Genomes 17, 12 (2021). https://doi.org/10.1007/s11295-020-01489-1

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Keywords

  • Abies
  • Forest management
  • Genomic prediction (GP)
  • Mexico
  • Predictive ability
  • Secluded natural populations