Younessi-Hamzekhanlu Mehdi, Gailing Oliver
Department of Forestry and Medicinal Plants, Ahar Faculty of Agriculture and Natural Resources, University of Tabriz, 29 Bahman Blvd., Tabriz P.O. Box 5166616471, Iran.
Department of Forest Genetics and Forest Tree Breeding, University of Göttingen, Büsgenweg 2, D-37077 Göttingen, Germany.
Int J Mol Sci. 2022 Oct 14;23(20):12315. doi: 10.3390/ijms232012315.
The ecological and economic importance of forest trees is evident and their survival is necessary to provide the raw materials needed for wood and paper industries, to preserve the diversity of associated animal and plant species, to protect water and soil, and to regulate climate. Forest trees are threatened by anthropogenic factors and biotic and abiotic stresses. Various diseases, including those caused by fungal pathogens, are one of the main threats to forest trees that lead to their dieback. Genomics and transcriptomics studies using next-generation sequencing (NGS) methods can help reveal the architecture of resistance to various diseases and exploit natural genetic diversity to select elite genotypes with high resistance to diseases. In the last two decades, QTL mapping studies led to the identification of QTLs related to disease resistance traits and gene families and transcription factors involved in them, including NB-LRR, WRKY, bZIP and MYB. On the other hand, due to the limitation of recombination events in traditional QTL mapping in families derived from bi-parental crosses, genome-wide association studies (GWAS) that are based on linkage disequilibrium (LD) in unstructured populations overcame these limitations and were able to narrow down QTLs to single genes through genotyping of many individuals using high-throughput markers. Association and QTL mapping studies, by identifying markers closely linked to the target trait, are the prerequisite for marker-assisted selection (MAS) and reduce the breeding period in perennial forest trees. The genomic selection (GS) method uses the information on all markers across the whole genome, regardless of their significance for development of a predictive model for the performance of individuals in relation to a specific trait. GS studies also increase gain per unit of time and dramatically increase the speed of breeding programs. This review article is focused on the progress achieved in the field of dissecting forest tree disease resistance architecture through GWAS and QTL mapping studies. Finally, the merit of methods such as GS in accelerating forest tree breeding programs is also discussed.
林木的生态和经济重要性显而易见，其存续对于提供木材和造纸工业所需的原材料、维护相关动植物物种的多样性、保护水土以及调节气候而言必不可少。林木受到人为因素以及生物和非生物胁迫的威胁。包括由真菌病原体引起的各种病害，是导致林木死亡的主要威胁之一。利用新一代测序（NGS）方法进行的基因组学和转录组学研究，有助于揭示对各种病害的抗性结构，并利用自然遗传多样性来选择对病害具有高抗性的优良基因型。在过去二十年中，数量性状基因座（QTL）定位研究导致了与抗病性状相关的QTL以及参与其中的基因家族和转录因子的鉴定，包括NB-LRR、WRKY、bZIP和MYB。另一方面，由于在双亲亲本杂交衍生的家族中传统QTL定位中重组事件的局限性，基于非结构化群体中的连锁不平衡（LD）的全基因组关联研究（GWAS）克服了这些局限性，并能够通过使用高通量标记对许多个体进行基因分型将QTL缩小到单个基因。关联和QTL定位研究通过识别与目标性状紧密连锁的标记，是标记辅助选择（MAS）的先决条件，并缩短了多年生林木的育种周期。基因组选择（GS）方法使用整个基因组中所有标记的信息，而不管它们对于与特定性状相关的个体表现的预测模型开发的重要性如何。GS研究还提高了单位时间的增益，并显著提高了育种计划的速度。这篇综述文章重点关注通过GWAS和QTL定位研究在剖析林木抗病结构领域所取得的进展。最后，还讨论了诸如GS等方法在加速林木育种计划方面的优点。
