Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design

Abstract

With the advances in high-throughput sequencing technologies, it is not difficult to extract tens of thousands of single nucleotide polymorphisms (SNPs) across many individuals in a fast and cheap way, making it possible to perform genome-wide association studies (GWAS) of quantitative traits in outbred forest trees. It is very valuable to apply traditional breeding experiments in GWAS for identifying genome variants associated to ecologically and economically important traits in Populus. Here, we reported a GWAS of tree height measured at multiple time points from a randomized complete block design (RCBD), which was established with clones from an F1 hybrid population of Populus deltoides and Populus simonii. A total of 22,670 SNPs across 172 clones in the RCBD were obtained with restriction site-associated DNA sequencing (RADseq) technology. The multivariate mixed linear model was applied by incorporating the pedigree relationship matrix of individuals to test the association of each SNP to the tree heights over 8 time points. Consequently, 41 SNPs were identified significantly associated to the tree height under the p-value threshold determined by Bonferroni correction at the significant level of 0.01. These SNPs were distributed on all but 2 chromosomes (Chr02 and Chr18) and explained the phenotypic variance ranged from 0.26% to 2.64%, amounting to 63.68% in total. Comparison with previous mapping studies for poplar height as well as the candidate genes of these detected SNPs were also investigated. We therefore demonstrated that the application of multivariate linear mixed model to the longitudinal phenotypic data from the traditional breeding experimental design facilitated to identify far more genome-wide variants for tree height in poplar. The significant SNPs identified in this study would enhance understanding of molecular mechanism for growth traits and would accelerate marker-assisted breeding programs in Populus.

Genomic signatures of selection for resistance to stripe rust in Austrian winter wheat

“…Because of the unbalanced nature of the dataset, we used methods that maximize statistical power for GWA in unbalanced studies (George and Cavanagh 2015 ; Xue et al 2017 ; Chen et al 2021 ). For within-year GWA, we used the one-stage method, in which a mixed model is fit with plot-level phenotypes as the response and environmental (e.g., trial, year, location), genotypic (e.g., line, family), genetic background (e.g., relationship/kinship matrices, population structure components), and SNP information as fixed or random effects (Xue et al 2017 ; Chen et al 2021 ).…”

“…Because of the unbalanced nature of the dataset, we used methods that maximize statistical power for GWA in unbalanced studies (George and Cavanagh 2015 ; Xue et al 2017 ; Chen et al 2021 ). For within-year GWA, we used the one-stage method, in which a mixed model is fit with plot-level phenotypes as the response and environmental (e.g., trial, year, location), genotypic (e.g., line, family), genetic background (e.g., relationship/kinship matrices, population structure components), and SNP information as fixed or random effects (Xue et al 2017 ; Chen et al 2021 ). Plant breeding experiments can include large numbers of individuals and/or trials, making one-stage GWA computationally intensive when complex variance–covariance structures (e.g., relationship/kinship matrices) are included to control for background genetic effects (George and Cavanagh 2015 ; Xue et al 2017 ).…”

Genome Assembly of SalicaceaePopulus deltoides(Eastern Cottonwood)I-69Based on Nanopore Sequencing and Hi-C Technologies

“…First, the new assembly provides a specific parental reference sequence for extracting tens of thousands of SNP genotypes across an F 1 hybrid population in which the P. deltoides I-69 was as a female parent ( Mousavi et al 2016 ; Tong et al 2016 ). With the large number of SNPs, high-density genetic linkage maps of the parents can be constructed and thus the QTL mapping or genome-wide association studies could be conducted for growth and woody traits ( Tong et al 2020 ; Chen et al 2021 ). Second, this genome sequence allowed us to identify genes unique to the cultivar I-69 through orthologous analysis ( Supplementary Figure 4 ).…”

Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing

“…High-throughput genotyping technology and phenotyping platforms have enabled large-scale marker-trait association analysis, such as GWAS, to precisely dissect the genetic architecture of plant traits [222]. In trees, several studies have reported many putative genomic regions associated with variation of related-traits to tree phenology [223,224], wood properties [118,120,165,[225][226][227][228][229], growth (i.e., wood volume, tree height and diameter; [108,111,117,120,226,[230][231][232], resistance to pests and diseases [233][234][235][236], among others. For example, McKown et al (2018) [223] implemented a GWAS analysis with the motivation to understand the molecular mechanisms of the variation in bud-break of flowers in Populus trichocarpa Torr.…”