Ballesta Paulina, Maldonado Carlos, Pérez-Rodríguez Paulino, Mora Freddy
Institute of Biological Sciences, University of Talca, 2 Norte 685, Talca 3460000, Chile.
Colegio de Postgraduados, Statistics and Computer Sciences, Montecillos, Edo. de México 56230, Mexico.
Plants (Basel). 2019 Sep 5;8(9):331. doi: 10.3390/plants8090331.
(Labill.) is one of the most important cultivated eucalypts in temperate and subtropical regions and has been successfully subjected to intensive breeding. In this study, Bayesian genomic models that include the effects of haplotype and single nucleotide polymorphisms (SNP) were assessed to predict quantitative traits related to wood quality and tree growth in a 6-year-old breeding population. To this end, the following markers were considered: (a) ~14 K SNP markers (SNP), (b) ~3 K haplotypes (HAP), and (c) haplotypes and SNPs that were not assigned to a haplotype (HAP-SNP). Predictive ability values (PA) were dependent on the genomic prediction models and markers. On average, Bayesian ridge regression (BRR) and Bayes C had the highest PA for the majority of traits. Notably, genomic models that included the haplotype effect (either HAP or HAP-SNP) significantly increased the PA of low-heritability traits. For instance, BRR based on HAP had the highest PA (0.58) for stem straightness. Consistently, the heritability estimates from genomic models were higher than the pedigree-based estimates for these traits. The results provide additional perspectives for the implementation of genomic selection in breeding programs, which could be especially beneficial for improving traits with low heritability.
（Labill.）是温带和亚热带地区最重要的人工种植桉树之一，并且已成功进行了密集育种。在本研究中，评估了包含单倍型和单核苷酸多态性（SNP）效应的贝叶斯基因组模型，以预测一个6年生育种群体中与木材质量和树木生长相关的数量性状。为此，考虑了以下标记：（a）约14K个SNP标记（SNP），（b）约3K个单倍型（HAP），以及（c）未分配到单倍型的单倍型和SNP（HAP-SNP）。预测能力值（PA）取决于基因组预测模型和标记。平均而言，贝叶斯岭回归（BRR）和贝叶斯C对于大多数性状具有最高的PA。值得注意的是，包含单倍型效应的基因组模型（HAP或HAP-SNP）显著提高了低遗传力性状的PA。例如，基于HAP的BRR对于树干通直度具有最高的PA（0.58）。同样，这些性状的基因组模型遗传力估计值高于基于系谱的估计值。这些结果为在育种计划中实施基因组选择提供了额外的视角，这对于改善低遗传力性状可能特别有益。
