Dynamic genetic architecture of juvenile growth in poplar revealed by temporal unconditional and conditional QTL mapping

Understanding the genetic basis of dynamic growth traits is crucial for the genetic improvement of forest trees, and poplar is an ideal model system for such studies. Plant height (PH) and ground diameter (GD) are fundamental growth traits that directly determine biomass production and wood quality of poplar. In this study, a high-density genetic map was constructed based on whole-genome resequencing of two interspecific hybrid poplar parental clones and their 400 progeny. The map consisted of 5801 bin markers spread across 19 chromosomes, spanning 2229.6 cM with an average of 0.39 cM/bin marker. Using this map, temporal unconditional and conditional quantitative trait locus (QTL) mapping was conducted to dissect the dynamic genetic architecture of PH and GD in the F₁ population across seven time points. Unconditional mapping revealed a developmental shift from early large-effect to later small-effect QTLs, with a total of 16 major consensus QTLs identified for PH and GD, and 10 for their growth rates. Meanwhile, conditional analysis identified 11 stable consensus QTLs governing net growth increments, highlighting a more continuous genetic control throughout development. Comparison between unconditional and conditional QTLs revealed 35 co-localized regions, highlighting convergent genetic hotspots for both cumulative and net growth. Candidate gene screening within key QTL intervals implicated genes involved in cell wall biosynthesis, hormone signaling, RNA metabolism, and stress responses, suggesting their potential roles in the regulation of meristem activity, cell expansion, and structural integrity during poplar apical and radial growth. Results of this study not only provide a comprehensive temporal genetic map of poplar juvenile growth but also offer valuable insights for molecular breeding to improve growth performance of poplar. • A high-density genetic map of poplar was constructed using BIN markers. • Detecting stable and stage-specific regulators via unconditional and conditional QTL. • Precise mapping of pleiotropic QTLs governing plant growth traits. • Screening candidate genes within identified key genomic regions.