Project description:Purpose: Kraft pulp yield (KPY) is a key determinant of plantation profitability and increasing the KPY of trees grown in plantations is a major breeding objective. To speed up the breeding process, molecular markers that can predict KPY are desirable. To achieve this goal, we carried out RNA-Seq studies on trees at extremes of KPY in two different trials to identify genes and alleles whose expression correlated with KPY. Methods: We analyzed samples from the extremes of the distribution of KPY in two Eucalyptus nitens trials which also differed in growth to identify genes having differential expression between high and low KPY samples. We used reference-guided transcriptome mapping to study gene expression. Results: Several genes showed differential expression between low and high KPY samples. Gene ontology (GO) enrichment tests revealed up-regulation of stress-related gene categories and down-regulation of gene categories related to wood formation and growth in low KPY samples. More than 110,000 single nucleotide polymorphisms (SNPs) were detected in both the trials and 2103 of these showed differential allelic expression. Allelic expression of 30% of these variants was correlated with total gene expression. To identify the genes showing patterns of positive selection among the genes expressed in the cambial tissue we compared Ka/Ks ratios. The Ka/Ks ratios compare the rate of nonsynonymous substitutions (Ka) to synonymous substitutions (Ks) which can help identifying genes under selection. By comparing the two trials we observed in total 196 genes which had Ka/Ks ratios of more than 1.5 in both the trials strongly suggesting that these genes are under positive selection. A total of six GO categories were enriched in both trials for genes showing signatures of positive selection . All six categories include genes involved in apoptosis, cell death and defense responses. Conclusions: By conducting RNA-Seq analysis in two trials we identified a number of candidate genes and alleles whose expression is correlated with KPY and growth traits in E. nitens. Most of the down-regulated genes in low KPY samples are cell wall-related genes, suggesting that the identified candidate genes are biologically relevant. A number of potential functional polymorphisms were also identified that showed DAE. We detected positive selection signatures in numerous genes that are consistent with the results from RNA-Seq study in E. camaldulensis. The genes and alleles identified in this study form a valuable resource for association and genomic selection studies.

Project description:Purpose: Kraft pulp yield (KPY) is a key determinant of plantation profitability and increasing the KPY of trees grown in plantations is a major breeding objective. To speed up the breeding process, molecular markers that can predict KPY are desirable. To achieve this goal, we carried out RNA-Seq studies on trees at extremes of KPY in two different trials to identify genes and alleles whose expression correlated with KPY. Methods: We analyzed samples from the extremes of the distribution of KPY in two Eucalyptus nitens trials which also differed in growth to identify genes having differential expression between high and low KPY samples. We used reference-guided transcriptome mapping to study gene expression. Results: Several genes showed differential expression between low and high KPY samples. Gene ontology (GO) enrichment tests revealed up-regulation of stress-related gene categories and down-regulation of gene categories related to wood formation and growth in low KPY samples. More than 110,000 single nucleotide polymorphisms (SNPs) were detected in both the trials and 2103 of these showed differential allelic expression. Allelic expression of 30% of these variants was correlated with total gene expression. To identify the genes showing patterns of positive selection among the genes expressed in the cambial tissue we compared Ka/Ks ratios. The Ka/Ks ratios compare the rate of nonsynonymous substitutions (Ka) to synonymous substitutions (Ks) which can help identifying genes under selection. By comparing the two trials we observed in total 196 genes which had Ka/Ks ratios of more than 1.5 in both the trials strongly suggesting that these genes are under positive selection. A total of six GO categories were enriched in both trials for genes showing signatures of positive selection . All six categories include genes involved in apoptosis, cell death and defense responses. Conclusions: By conducting RNA-Seq analysis in two trials we identified a number of candidate genes and alleles whose expression is correlated with KPY and growth traits in E. nitens. Most of the down-regulated genes in low KPY samples are cell wall-related genes, suggesting that the identified candidate genes are biologically relevant. A number of potential functional polymorphisms were also identified that showed DAE. We detected positive selection signatures in numerous genes that are consistent with the results from RNA-Seq study in E. camaldulensis. The genes and alleles identified in this study form a valuable resource for association and genomic selection studies. Xylem mRNA profiles of Eucalyptus nitens from low and high KPY samples were generated by deep sequencing, in two trials, using Illumina HiSeq.

Project description:Genomic selection (GS) is being increasingly adopted by the tree breeding community. Most of the GS studies in trees are focused on estimating additive genetic effects. Exploiting the dominance effects offers additional opportunities to improve genetic gain. To detect dominance effects, trait-relevant markers may be important compared to nonselected markers. Here, we used preselected markers to study the dominance effects in a Eucalyptus nitens (E. nitens) breeding population consisting of open-pollinated (OP) and controlled-pollinated (CP) families. We used 8221 trees from six progeny trials in this study. Of these, 868 progeny and 255 parents were genotyped with the E. nitens marker panel. Three traits; diameter at breast height (DBH), wood basic density (DEN), and kraft pulp yield (KPY) were analyzed. Two types of genomic relationship matrices based on identity-by-state (IBS) and identity-by-descent (IBD) were tested. Performance of the genomic best linear unbiased prediction (GBLUP) models with IBS and IBD matrices were compared with pedigree-based additive best linear unbiased prediction (ABLUP) models with and without the pedigree reconstruction. Similarly, the performance of the single-step GBLUP (ssGBLUP) with IBS and IBD matrices were compared with ABLUP models using all 8221 trees. Significant dominance effects were observed with the GBLUP-AD model for DBH. The predictive ability of DBH is higher with the GBLUP-AD model compared to other models. Similarly, the prediction accuracy of genotypic values is higher with GBLUP-AD compared to the GBLUP-A model. Among the two GBLUP models (IBS and IBD), no differences were observed in predictive abilities and prediction accuracies. While the estimates of predictive ability with additive effects were similar among all four models, prediction accuracies of ABLUP were lower than the GBLUP models. The prediction accuracy of ssGBLUP-IBD is higher than the other three models while the theoretical accuracy of ssGBLUP-IBS is consistently higher than the other three models across all three groups tested (parents, genotyped, and nongenotyped). Significant inbreeding depression was observed for DBH and KPY. While there is a linear relationship between inbreeding and DBH, the relationship between inbreeding and KPY is nonlinear and quadratic. These results indicate that the inbreeding depression of DBH is mainly due to directional dominance while in KPY it may be due to epistasis. Inbreeding depression may be the main source of the observed dominance effects in DBH. The significant dominance effect observed for DBH may be used to select complementary parents to improve the genetic merit of the progeny in E. nitens.

Dataset Information

RNA-Seq using two populations reveals genes and alleles controlling wood traits and growth in Eucalyptus nitens.

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RNA-Seq using two populations reveals genes and alleles controlling wood traits and growth in Eucalyptus nitens.

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