Independent and Joint‐GWASfor growth traits inEucalyptusby assembling genome‐wide data for 3373 individuals across four breeding populations

Abstract

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 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.

Optimizing ddRADseq in Non-Model Species: A Case Study in Eucalyptus dunnii Maiden

“…Nevertheless, for the Eucalyptus genus, the use of RADseq-derived methods is scarce. To date, the easy access to the commercial SNP array (EUChip60K) has led researchers to use it in the analysis of the genus [41][42][43][44], rather than RADseq-derived methods. Some species are poorly or less frequently represented in this chip than E. grandis (which is represented for its economic importance), and for this reason, the population allele frequencies and genetic relationships between individuals can be affected [45][46][47].…”

Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding

“…The limitation of methods to interrogate DNA polymorphisms at the time only allowed candidate-gene approaches (Thumma et al, 2005 ; Gonzalez-Martinez et al, 2007 ), which were then followed by genome-wide association mapping (GWAS) in several forest tree species (Beaulieu et al, 2011 ; Cumbie et al, 2011 ; Cappa et al, 2013 ; Porth et al, 2013 ; Mckown et al, 2014 ). However, irrespective of the marker density used, population size and improved analytical methods to account for low-frequency variants (Fahrenkrog et al, 2017 ; Müller et al, 2017 , 2018 ; Resende et al, 2017a ), only few polymorphisms of very modest effect have been detected, largely still lacking independent validation, the cornerstone for the scientific credibility of GWAS results. In effect, after 25 years of research efforts based on the principle and experimental approaches of genetic dissection of quantitative traits, no translation of such efforts to operational tree breeding was achieved (Grattapaglia et al, 2009 ; Grattapaglia, 2014 ; Isik, 2014 ).…”

Potential of Genome-Wide Association Studies and Genomic Selection to Improve Productivity and Quality of Commercial Timber Species in Tropical Rainforest, a Case Study of Shorea platyclados

“…Under the high LD, although 5900 SNPs still has possibility not to be able to detect any of QTLs due to the sparse distribution, we, thus, applied five −log 10 (P) thresholds from stringent to weak to selected markers that were significantly associated with the focal traits for GS. This empirical approach has also been applied in previous studies of C. japonica and Eucalyptus [33,82], and it identified some SNPs that appeared to be significantly related to phenotypic traits. Under the high LD of the population, we expected that this approach may identify optimal balance to select makers.…”