Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection in Eucalyptus dunnii (Maiden).

Eucalyptus dunnii is one of the most important Eucalyptus species for short-fiber pulp production in regions where other species of the genus are affected by poor soil and climatic conditions. In this context, E. dunnii holds promise as a resource to address and adapt to the challenges of climate change. Despite its rapid growth and favorable wood properties for solid wood products, the advancement of its improvement remains in its early stages. In this work, we evaluated the performance of two single nucleotide polymorphism, (SNP), genotyping methods for population genetics analysis and Genomic Selection in E. dunnii. Double digest restriction-site associated DNA sequencing (ddRADseq) was compared with the EUChip60K array in 308 individuals from a provenance-progeny trial. The compared SNP set included 8,011 and 19,008 informative SNPs distributed along the 11 chromosomes, respectively. Although the two datasets differed in the percentage of missing data, genome coverage, minor allele frequency and estimated genetic diversity parameters, they revealed a similar genetic structure, showing two subpopulations with little differentiation between them, and low linkage disequilibrium. GS analyses were performed for eleven traits using Genomic Best Linear Unbiased Prediction (GBLUP) and a conventional pedigree-based model (ABLUP). Regardless of the SNP dataset, the predictive ability (PA) of GBLUP was better than that of ABLUP for six traits (Cellulose content, Total and Ethanolic extractives, Total and Klason lignin content and Syringyl and Guaiacyl lignin monomer ratio). When contrasting the SNP datasets used to estimate PAs, the GBLUP-EUChip60K model gave higher and significant PA values for six traits, meanwhile, the values estimated using ddRADseq gave higher values for three other traits. The PAs correlated positively with narrow sense heritabilities, with the highest correlations shown by the ABLUP and GBLUP-EUChip60K. The two genotyping methods, ddRADseq and EUChip60K, are generally comparable for population genetics and genomic prediction, demonstrating the utility of the former when subjected to rigorous SNP filtering. The results of this study provide a basis for future whole-genome studies using ddRADseq in non-model forest species for which SNP arrays have not yet been developed.

Single-step genomic prediction of Eucalyptus dunnii using different identity-by-descent and identity-by-state relationship matrices.

Genomic selection based on the single-step genomic best linear unbiased prediction (ssGBLUP) approach is becoming an important tool in forest tree breeding. The quality of the variance components and the predictive ability of the estimated breeding values (GEBV) depends on how well marker-based genomic relationships describe the actual genetic relationships at unobserved causal loci. We investigated the performance of GEBV obtained when fitting models with genomic covariance matrices based on two identity-by-descent (IBD) and two identity-by-state (IBS) relationship measures. Multiple-trait multiple-site ssGBLUP models were fitted to diameter and stem straightness in five open-pollinated progeny trials of Eucalyptus dunnii, genotyped using the EUChip60K. We also fitted the conventional ABLUP model with a pedigree-based covariance matrix. Estimated relationships from the IBD estimators displayed consistently lower standard deviations than those from the IBS approaches. Although ssGBLUP based in IBS estimators resulted in higher trait-site heritabilities, the gain in accuracy of the relationships using IBD estimators has resulted in higher predictive ability and lower bias of GEBV, especially for low-heritability trait-site. ssGBLUP based on IBS and IBD approaches performed considerably better than the traditional ABLUP. In summary, our results advocate the use of the ssGBLUP approach jointly with the IBD relationship matrix in open-pollinated forest tree evaluation.

Microsatellite markers in candidate genes for wood properties and its application in functional diversity assessment in eucalyptus globulus

Background: Functional genetic markers have important implications for genetic analysis by providing direct estimation of functional diversity. Although high throughput sequencing techniques for functional diversity analysis are being developed nowadays, the use of already well established variable markers present in candidate genes is still an interesting alternative for mapping purposes and functional diversity studies. SSR markers are routinely used in most plant and animal breeding programs for many species including Eucalyptus. SSR markers derived from candidate genes (SSR-CG) can be used effectively in co-segregation studies and marker-assisted diversity management. Results: In the present study, eight new non reported SSRs were identified in seven candidate genes for wood properties in Eucalyptus globulus: cinnamoyl CoA reductase (CCR), homocysteine S-methyltransferase (HMT), shikimate kinase (SK), xyloglucan endotransglycosylase 2 (XTH2), cellulose synthase 3 (CesA3), glutathione S-transferase (GST) and the transcription factor LIM1. Microsatellites were located in promoters, introns and exons, being most of them CT dinucleotide repeats. Genetic diversity of these eight CG-derived SSR-markers was explored in 54 unrelated genotypes. Except for XTH2, high levels of polymorphism were detected: 93 alleles (mean of 13.1 sd 1.6 alleles per locus), a mean effective number of alleles (Ne) of 5.4 (sd 1.6), polymorphic information content values (PIC) from 0.617 to 0.855 and probability of Identity (PI) ranging from 0.030 to 0.151. Conclusions: This is the first report on the identification, characterization and diversity analysis of microsatellite markers located inside wood quality candidate genes (CG) from Eucalyptus globulus...