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<p><i>Pinus taeda</i> (loblolly pine) is one of the most economically significant forest trees worldwide. Among growth traits, stem volume is the most widely considered trait in tree improvement programs. However, deciphering the genetic markers associated with growth trait variations in conifers is challenging due to the intricate complexity of <i>Pinus</i> genomes. In this study, we present a comprehensive genetic analysis of loblolly pine, focusing on single-nucleotide polymorphisms (SNPs) associated with stem volume variation to elucidate the molecular mechanisms governing high-performance phenotypes. We used 1,692 individuals phenotyped for stem volume and genotyped using sequence capture probes. To determine genome-wide associations, we utilized both genome-wide association study (GWAS) analysis and machine learning (ML). The SNPs identified in association with stem volume best linear unbiased estimates (BLUEs) were linked with assembled genes from three distinct transcriptomes, which were employed to construct gene coexpression networks. Through topological evaluations, we identified key genes with potential regulatory roles within stem volume variation. From 31,589 SNPs, we defined 7 GWAS-associated SNPs and 128 ML-associated SNPs, affecting genes involved in diverse molecular mechanisms. Key genes directly implicated in the regulation of growth and response to stress were identified. Gene coexpression network analysis revealed functional relationships between genes near SNPs associated with stem volume BLUEs, highlighting potential key regulators. These findings significantly advance our understanding of the genetics influencing growth traits, reveal candidate genes for functional studies, and contribute to the understanding of the genetic architecture underlying volume traits in loblolly pine.</p>

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Genome-wide association reveals novel insights into the molecular mechanisms regulating stem volume in Pinus taeda

  • 期刊论文

  • 发表日期：

    2025年5月24日

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  • Alexandre Hild Aono,
  • Stephanie Karenina Bajay,
  • Felipe Roberto Francisco,
  • Anete Pereira de Souza

摘要

Pinus taeda (loblolly pine) is one of the most economically significant forest trees worldwide. Among growth traits, stem volume is the most widely considered trait in tree improvement programs. However, deciphering the genetic markers associated with growth trait variations in conifers is challenging due to the intricate complexity of Pinus genomes. In this study, we present a comprehensive genetic analysis of loblolly pine, focusing on single-nucleotide polymorphisms (SNPs) associated with stem volume variation to elucidate the molecular mechanisms governing high-performance phenotypes. We used 1,692 individuals phenotyped for stem volume and genotyped using sequence capture probes. To determine genome-wide associations, we utilized both genome-wide association study (GWAS) analysis and machine learning (ML). The SNPs identified in association with stem volume best linear unbiased estimates (BLUEs) were linked with assembled genes from three distinct transcriptomes, which were employed to construct gene coexpression networks. Through topological evaluations, we identified key genes with potential regulatory roles within stem volume variation. From 31,589 SNPs, we defined 7 GWAS-associated SNPs and 128 ML-associated SNPs, affecting genes involved in diverse molecular mechanisms. Key genes directly implicated in the regulation of growth and response to stress were identified. Gene coexpression network analysis revealed functional relationships between genes near SNPs associated with stem volume BLUEs, highlighting potential key regulators. These findings significantly advance our understanding of the genetics influencing growth traits, reveal candidate genes for functional studies, and contribute to the understanding of the genetic architecture underlying volume traits in loblolly pine.