The approximately 20-year breeding cycle has severely restricted the progress of genetic improvement in poplar. Genomic selection (GS) breeding has been demonstrated as an effective approach to accelerate this process. However, its application in forest tree species remains at an early stage. To advance the genetic improvement of target traits in Populus deltoides, the primary species of poplar plantations in China, we systematically implemented GS breeding using 765 hybrid progenies from 32 multi-generational full-sib families. Firstly, we assembled a high-quality genome of one core parent P. deltoides ‘Danhong’, with a genome size of 419.4 Mb and scaffold N50 of 22.0 Mb, which is also the first telomere-to-telomere (T2T) level genome of P. deltoides. Through comparative genomic analysis, we identified 1395 specific structural variants closely associated with growth and development. Subsequently, through genome-wide association studies (GWAS), we identified 135 quantitative trait nucleotides (QTNs) associated with growth and wood quality traits. By systematically evaluating reference genomes, statistical models, and various marker selection strategies, we developed optimal genomic prediction (GP) models for six traits, with the highest prediction accuracy (PA) reaching 0.730 for DBH. Compared with using all markers, the PA was improved by an average of 136.34%. Furthermore, by integrating GP, GWAS, and RNA-seq results, we identified core breeding parents and elite clones for P. deltoides genetic improvement and discovered important candidate genes. Our results provide a promising strategy for accelerating breeding cycles and genetic improvement, offering valuable breeding and genetic resources for forest tree improvement.

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