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Independent and Joint‐ GWAS for growth traits in Eucalyptus by assembling genome‐wide data for 3373 individuals across four breeding populations

2018; Wiley; Volume: 221; Issue: 2 Linguagem: Inglês

10.1111/nph.15449

1469-8137

Bárbara S. F. Müller, Janeo Eustáquio de Almeida Filho, Bruno Marco de Lima, Carla Costa Garcia, Alexandre Alves Missiaggia, Aurélio Mendes Aguiar, Elizabete Keiko Takahashi, Matias Kirst, Salvador A. Gezan, Orzenil B. Silva‐Junior, Leandro G. Neves, Dário Grattapaglia,

Forest ecology and management

Summary 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 EUC hip60 KSNP 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 SNP s 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 SNP s 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.