1. Independent and Joint‐<scp>GWAS</scp>for growth traits inEucalyptusby assembling genome‐wide data for 3373 individuals across four breeding populations
- Author
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Bárbara S. F. Müller, Janeo Eustáquio de Almeida Filho, Aurélio Mendes Aguiar, Alexandre Alves Missiaggia, Orzenil B. Silva-Junior, Dario Grattapaglia, Leandro G. Neves, Elizabete Keiko Takahashi, Bruno Marco de Lima, Carla Garcia, Matias Kirst, Salvador A. Gezan, BÁRBARA S. F. MULLER, UNB, ORZENIL BONFIM DA SILVA JUNIOR, Cenargen, LEANDRO G. NEVES, RAPID GENOMICS LLC, USA, DARIO GRATTAPAGLIA, Cenargen., JANEO E. DE ALMEIDA FILHO, UENF, BRUNO M. LIMA, FIBRIA S.A. TECHNOLOGY CENTER, CARLA C. GARCIA, INTERNATIONAL PAPER OF BRAZIL, ALEXANDRE MISSIAGGIA, FIBRIA S.A. TECHNOLOGY CENTER, AURELIO M. AGUIAR, FIBRIA S.A. TECHNOLOGY CENTER, ELIZABETE TAKAHASHI, CELULOSE NIPO-BRASILEIRA (CENIBRA) S.A., MATIAS KIRST, UNIVERSITY OF FLORIDA, USA, and SALVADOR A. GEZAN, UNIVERSITY OF FLORIDA, USA
- Subjects
musculoskeletal diseases ,0106 biological sciences ,0301 basic medicine ,Physiology ,Population ,Inheritance Patterns ,Single-nucleotide polymorphism ,Genome-wide association study ,Plant Science ,Biology ,Polymorphism, Single Nucleotide ,01 natural sciences ,Genome ,Linkage Disequilibrium ,03 medical and health sciences ,Quantitative Trait, Heritable ,High-throughput SNP genotyping ,Joint-GWAS ,Regional heritability mapping (RHM) ,SNP ,education ,Genetic association ,Principal Component Analysis ,Eucalyptus ,education.field_of_study ,Genome-wide association study (GWAS) ,Heritability ,Plant Breeding ,Meta-analysis ,030104 developmental biology ,Evolutionary biology ,Tree breeding ,Relatedness ,Genome, Plant ,Genome-Wide Association Study ,010606 plant biology & botany - Abstract
Genome-wide association studies (GWAS) in plants typically suffer from limited statistical power. An alternative to the logistical and cost challenge of increasing sample sizes is to gain power by meta-analysis using information from independent studies. We carried out GWAS for growth traits with six single-marker models and regional heritability mapping (RHM) in four Eucalyptus breeding populations independently and by Joint-GWAS, using gene and segment-based models, with data for 3373 individuals genotyped with a communal EUChip60KSNP platform. While single-single nucleotide polymorphism (SNP) GWAS hardly detected significant associations at high-stringency in each population, gene-based Joint-GWAS revealed nine genes significantly associated with tree height. Associations detected using single-SNP GWAS, RHM and Joint-GWAS set-based models explained on average 3-20% of the phenotypic variance. Whole-genome regression, conversely, captured 64-89% of the pedigree-based heritability in all populations. Several associations independently detected for the same SNPs in different populations provided unprecedented GWAS validation results in forest trees. Rare and common associations were discovered in eight genes involved in cell wall biosynthesis and lignification. With the increasing adoption of genomic prediction of complex phenotypes using shared SNPs and much larger tree breeding populations, Joint-GWAS approaches should provide increasing power to pinpoint discrete associations potentially useful toward tree breeding and molecular applications.
- Published
- 2018