Genomic selection proof-of-concept in two major conifer species

Genomic selection has been successfully implemented in both animal and agricultural crop breeding programmes. Recently, forest tree breeding has also implemented genomic tools to improve the efficiency of breeding and selection procedures. Due to high genetic complexity of most economically important traits, genomic selection shows promise in operational breeding programmes for forest trees. Our two case studies, performed in economically important conifer species, showed that a genomic-based approach can reach similar prediction accuracies compared to the pedigree-based alternative. However, larger training population sample sizes should be used to increase the efficiency of genomic selection and outperform the traditional pedigree-based scenario. Moreover, broad genetic diversity is needed to successfully estimate genetic correlations and perform multivariate analyses

Genomic selection proof-of-concept in two major conifer species

Genomic selection has been successfully implemented in both animal and agricultural crop breeding programmes. Recently, forest tree breeding has also implemented genomic tools to improve the efficiency of breeding and selection procedures. Due to high genetic complexity of most economically important traits, genomic selection shows promise in operational breeding programmes for forest trees. Our two case studies, performed in economically important conifer species, showed that a genomic-based approach can reach similar prediction accuracies compared to the pedigree-based alternative. However, larger training population sample sizes should be used to increase the efficiency of genomic selection and outperform the traditional pedigree-based scenario. Moreover, broad genetic diversity is needed to successfully estimate genetic correlations and perform multivariate analyses

Genomic selection proof-of-concept in two major conifer species

International audienceGenomic selection has been successfully implemented in both animal and agricultural crop breeding programmes. Recently, forest tree breeding has also implemented genomic tools to improve the efficiency of breeding and selection procedures. Due to high genetic complexity of most economically important traits, genomic selection shows promise in operational breeding programmes for forest trees. Our two case studies, performed in economically important conifer species, showed that a genomic-based approach can reach similar prediction accuracies compared to the pedigree-based alternative. However, larger training population sample sizes should be used to increase the efficiency of genomic selection and outperform the traditional pedigree-based scenario. Moreover, broad genetic diversity is needed to successfully estimate genetic correlations and perform multivariate analyses

Genetics of wood quality attributes in Western Larch

International audience& Context Wood quality traits are important to balance the negative decline of wood quality associated with selection for growth attributes in gymnosperm breeding programs. Obtaining wood quality estimates quickly is crucial for suc-cessful incorporation in breeding programs. & Aims The aims of this paper are to: (1) Estimate genetic and phenotypic correlations between growth and wood quality attributes, (2) Estimate heritability of the studied traits, and (3) Assess the accuracy of in situ non-destructive tools as a representative of actual wood density. & Methods Wood density (X-ray densitometry), tree height, diameter, volume, resistance drilling, acoustic velocity, and dynamic modulus of elasticity were estimated, along with their genetic parameters, for 1,200, 20-year-old trees from 25 open-pollinated families. & Results Individual tree level heritabilities for non-destructive evaluation attributes were moderate (b h 2 i ¼ 0:37−0:42), wood density and growth traits were lower (b h 2 i ¼ 0:23−0:35). Favorable genetic and phenotypic correlations between growth traits, wood density, and non-destructive evaluation traits were observed. A perfect genetic correlation was found between resistance drilling and wood density (r G =1.00±0.07), while acoustic velocity and dynamic modulus of elasticity showed weaker genetic correlations with wood density (r G =0.25± 0.24;0.46±0.21, respectively). & Conclusion This study confirmed that resistance drilling is a reliable predictor of wood density in western larch, while the weak genetic correlations displayed by acoustic velocity and dynamic modulus of elasticity suggest limited dependability for their use as fast in situ wood density assessment methods in this species. Keywords Western larch . In situ wood quality assessment . Wood density . Modulus of elasticity . X-ray densitometry . Genetic correlation . Heritabilit

Genomics-Enabled Management of Genetic Resources in Radiata Pine

Traditional tree improvement is cumbersome and costly. Our main objective was to assess the extent to which genomic data can currently accelerate and improve decision making in this field. We used diameter at breast height (DBH) and wood density (WD) data for 4430 tree genotypes and single-nucleotide polymorphism (SNP) data for 2446 tree genotypes. Pedigree reconstruction was performed using a combination of maximum likelihood parentage assignment and matching based on identity-by-state (IBS) similarity. In addition, we used best linear unbiased prediction (BLUP) methods to predict phenotypes using SNP markers (GBLUP), recorded pedigree information (ABLUP), and single-step “blended” BLUP (HBLUP) combining SNP and pedigree information. We substantially improved the accuracy of pedigree records, resolving the inconsistent parental information of 506 tree genotypes. This led to substantially increased predictive ability (i.e., by up to 87%) in HBLUP analyses compared to a baseline from ABLUP. Genomic prediction was possible across populations and within previously untested families with moderately large training populations (N = 800–1200 tree genotypes) and using as few as 2000–5000 SNP markers. HBLUP was generally more effective than traditional ABLUP approaches, particularly after dealing appropriately with pedigree uncertainties. Our study provides evidence that genome-wide marker data can significantly enhance tree improvement. The operational implementation of genomic selection has started in radiata pine breeding in New Zealand, but further reductions in DNA extraction and genotyping costs may be required to realise the full potential of this approach

Data from: Effect of hidden relatedness on single-step genetic evaluation in an advanced open-pollinated breeding program

Open-pollinated (OP) mating is frequently used in forest tree breeding due to the relative temporal and financial efficiency of the approach. The trade-off is the lower precision of the estimated genetic parameters. Pedigree/sib-ship reconstruction has been proven as a tool to correct and complete pedigree information and to improve the precision of genetic parameter estimates. Our study analyzed an advanced generation Eucalyptus population from an OP breeding program using single-step genetic evaluation. The relationship matrix inferred from sib-ship reconstruction was used to rescale the marker-based relationship matrix (G matrix). This was compared with a second scenario that used rescaling based on the documented pedigree. The proposed single-step model performed better with respect to both model fit and the theoretical accuracy of breeding values. We found that the prediction accuracy was superior when using the pedigree information only when compared with using a combination of the pedigree and genomic information. This pattern appeared to be mainly a result of accumulated unrecognized relatedness over several breeding cycles, resulting in breeding values being shrunk toward the population mean. Using biased, pedigree-based breeding values as the base with which to correlate predicted GEBVs, resulted in the underestimation of prediction accuracies. Using breeding values estimated on the basis of sib-ship reconstruction resulted in increased prediction accuracies of the genotyped individuals. Therefore, selection of the correct base for estimation of prediction accuracy is critical. The beneficial impact of sib-ship reconstruction using G matrix rescaling was profound, especially in traits with inbreeding depression, such as stem diameter