Genome-Wide SNP Markers Accelerate Perennial Forest Tree Breeding Rate for Disease Resistance through Marker-Assisted and Genome-Wide Selection

Abstract

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.

Multi-Omics Techniques in Genetic Studies and Breeding of Forest Plants

“…Although this approach is rarely applied in forest plants, it has great potential in mining hub genes encoding important traits of forest plants. Moreover, transcriptome sequence and RNA-seq data are also applied in the genome-wide detection of SNP and simple sequence repeat markers (Figure 3), which are valuable molecular tools in forest plant breeding [111].…”

Multi-Omics Techniques for Forest Plant Breeding

“…Although this approach is rarely applied in forest plants, it has great potential in mining hub genes encoding important traits of forest plants. Moreover, transcriptome sequence and RNA-seq data can also be applied in the genome-wide detection of SNP and simple sequence repeat markers (Figure 3), which are valuable molecular tools in forest plant breeding [106]. With the advances in RNA-seq and tissue processing approaches, single-cell RNA-seq (scRNAseq) has become a revolutionary tool for studying plant functional genomics at the cellular level [107].…”

Identifying genetic variation associated with environmental gradients and drought‐tolerance phenotypes in ponderosa pine

“…Several approaches to identifying more genetic variants for genome‐wide association studies (GWAS) utilizing next‐generation sequencing (NGS) have been proposed in recent years (Badenes et al., 2016 ; Davey et al., 2011 ; Poland & Rife, 2012 ; Younessi‐Hamzekhanlu & Gailing, 2022 ). Genotyping‐by‐Sequencing (GBS), which can generate tens of thousands of SNP markers without the need for a reference genome or whole transcriptome, has emerged as a cost‐effective strategy (Andrews et al., 2016 ; Elshire et al., 2011 ).…”