Kainer David, Lanfear Robert, Foley William J, Külheim Carsten
Research School of Biology, The Australian National University, Canberra, ACT, 2601, Australia.
Department of Biological Sciences, Macquarie University, Sydney, NSW, 2109, Australia.
Theor Appl Genet. 2015 Dec;128(12):2351-65. doi: 10.1007/s00122-015-2591-0. Epub 2015 Aug 4.
The yield of essential oil in commercially harvested perennial species (e.g. 'Oil Mallee' eucalypts, Tea Trees and Hop) is dependent on complex quantitative traits such as foliar oil concentration, biomass and adaptability. These often show large natural variation and some are highly heritable, which has enabled significant gains in oil yield via traditional phenotypic recurrent selection. Analysis of transcript abundance and allelic diversity has revealed that essential oil yield is likely to be controlled by large numbers of quantitative trait loci that range from a few of medium/large effect to many of small effect. Molecular breeding techniques that exploit this information could increase gains per unit time and address complications of traditional breeding such as genetic correlations between key traits and the lower heritability of biomass. Genomic selection (GS) is a technique that uses the information from markers genotyped across the whole genome in order to predict the phenotype of progeny well before they reach maturity, allowing selection at an earlier age. In this review, we investigate the feasibility of genomic selection (GS) for the improvement of essential oil yield. We explore the challenges facing breeders selecting for oil yield, and how GS might deal with them. We then assess the factors that affect the accuracy of genomic estimated breeding values, such as linkage disequilibrium (LD), heritability, relatedness and the genetic architecture of desirable traits. We conclude that GS has the potential to significantly improve the efficiency of selection for essential oil yield.
商业采收的多年生植物(如“油桉”桉、茶树和啤酒花)中精油的产量取决于复杂的数量性状,如叶片含油浓度、生物量和适应性。这些性状通常表现出很大的自然变异,有些具有高度遗传性,这使得通过传统的表型轮回选择在精油产量上取得了显著提高。转录本丰度和等位基因多样性分析表明,精油产量可能受大量数量性状位点控制,这些位点从少数几个中/大效应到许多小效应不等。利用这些信息的分子育种技术可以提高单位时间内的遗传增益,并解决传统育种中的复杂问题,如关键性状之间的遗传相关性以及生物量较低的遗传力。基因组选择(GS)是一种利用全基因组标记分型信息来预测后代在成熟前表型的技术,从而能够在更早的年龄进行选择。在这篇综述中,我们研究了基因组选择(GS)用于提高精油产量的可行性。我们探讨了育种者在选择精油产量时面临的挑战,以及GS如何应对这些挑战。然后,我们评估了影响基因组估计育种值准确性的因素,如连锁不平衡(LD)、遗传力、亲缘关系和目标性状的遗传结构。我们得出结论,GS有潜力显著提高精油产量的选择效率。