Quantitative genetics and genomics converge to accelerate forest tree breeding

Authors
Grattapaglia, Dario; Silva Junior, Orzenil B.; Resende, Rafael T.; Cappa, Eduardo Pablo; Müller, Bárbara S. F.; Tan, Biyue; Isik, Fikret; Ratcliffe, Blaise; El-Kassaby, Yousry A.
Publication Year
2018
Language
English
Format
article
Status
Published version
Description
Forest tree breeding has been successful at delivering genetically improved material for multiple traits based on recurrent cycles of selection, mating, and testing. However, long breeding cycles, late flowering, variable juvenile-mature correlations, emerging pests and diseases, climate, and market changes, all pose formidable challenges. Genetic dissection approaches such as quantitative trait mapping and association genetics have been fruitless to effectively drive operational marker-assisted selection (MAS) in forest trees, largely because of the complex multifactorial inheritance of most, if not all traits of interest. The convergence of high-throughput genomics and quantitative genetics has established two new paradigms that are changing contemporary tree breeding dogmas. Genomic selection (GS) uses large number of genome-wide markers to predict complex phenotypes. It has the potential to accelerate breeding cycles, increase selection intensity and improve the accuracy of breeding values. Realized genomic relationships matrices, on the other hand, provide innovations in genetic parameters’ estimation and breeding approaches by tracking the variation arising from random Mendelian segregation in pedigrees. In light of a recent flow of promising experimental results, here we briefly review the main concepts, analytical tools and remaining challenges that currently underlie the application of genomics data to tree breeding. With easy and cost-effective genotyping, we are now at the brink of extensive adoption of GS in tree breeding. Areas for future GS research include optimizing strategies for updating prediction models, adding validated functional genomics data to improve prediction accuracy, and integrating genomic and multi-environment data for forecasting the performance of genetic material in untested sites or under changing climate scenarios. The buildup of phenotypic and genome-wide data across large-scale breeding populations and advances in computational prediction of discrete genomic features should also provide opportunities to enhance the application of genomics to tree breeding.
Fil: Grattapaglia, Dario. EMBRAPA Recursos Genéticos e Biotecnologia; Brasil. Universidade Católica de Brasília. Programa de Ciências Genômicas e Biotecnologia; Brasil. Universidade de Brasília. Departamento de Biologia Celular; Brasil. North Carolina State University. Department of Forestry and Environmental Resources; Estados Unidos
Fil: Silva-Junior, Orzenil B. EMBRAPA Recursos Genéticos e Biotecnologia; Brasil. Universidade Católica de Brasília. Programa de Ciências Genômicas e Biotecnologia; Brasil
Fil: Resende, Rafael T. EMBRAPA Recursos Genéticos e Biotecnologia; Brasil
Fil: Cappa, Eduardo Pablo. INTA. Instituto de Recursos Biológicos; Argentina
Fil: Müller, Bárbara S. F. EMBRAPA Recursos Genéticos e Biotecnologia; Brasil. Universidade de Brasília. Departamento de Biologia Celular; Brasil
Fil: Tan, Biyue. Stora Enso AB. Biomaterials Division; Suecia
Fil: Isik, Fikret. North Carolina State University. Department of Forestry and Environmental Resources; Estados Unidos
Fil: Rateliffe, Blaise. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá
Fil: El-Kassaby, Yousry A. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá
Source
Frontiers in Plant Science 9 : 1693 (November 2018)
Subject
Quantitative Genetics
Quantitative Trait Loci
Forest Trees
Genética Cuantitativa
Loci de Rasgos Cuantitativos
Árboles Forestales
Genomic Selection
Tree Breeding
Whole-genome Regression
Single Nucleotide Polymorphisms
Marker Assisted Selection
Realized Genomic Relationship
Selección Genómica
Cría de Arboles
Regresión de Todo el Genoma
Polimorfismos de un Sólo Nucleótido
Selección Asistida por Marcador
Relación Genómica Realizada
Access level
Open access
License
Repository
INTA Digital (INTA)
Institution
Instituto Nacional de Tecnología Agropecuaria
OAI Identifier
oai:localhost:20.500.12123/4605