Association genetics in Populus reveal the allelic interactions of Pto-MIR167a and its targets in wood formation

Abstract

MicroRNAs (miRNAs) play crucial regulatory roles in plant growth and development by interacting with RNA molecules, including messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs); however, the genetic networks of miRNAs and their targets influencing the phenotypes of perennial trees remain to be investigated. Here, we integrated expression profiling and association analysis of underlying physiology and expression traits to dissect the allelic variations and genetic interactions of Pto-MIR167a and its targets, sponge lncRNA ARFRL, and Pto-ARF8, in 435 unrelated individuals of Populus tomentosa. Tissue-specific expression analysis in eight tissues, including stem, leaf, root, and shoot apex, revealed negative correlations between Pto-MIR167a and lncRNA ARFRL and Pto-ARF8 (r = −0.60 and −0.61, respectively, P < 0.01), and a positive correlation between sponge lncRNA ARFRL and Pto-ARF8 (r = 0.90, P < 0.01), indicating their potential regulatory roles in tree growth and wood formation. Single nucleotide polymorphism(SNP)-based association studies detected 53 significant associations (P < 0.01, Q < 0.1) representing 41 unique SNPs from the three genes and six traits, suggesting their potential roles in wood formation. Epistasis uncovered 88 pairwise interactions for 10 traits, which provided substantial evidence for genetic interactions among Pto-MIR167a, lncRNA ARFRL, and Pto-ARF8. Using gene expression-based association mapping, we also examined SNPs within the three genes that influence phenotypes by regulating the expression of Pto-ARF8. Interestingly, SNPs in the precursor region of Pto-MIR167a altered its secondary structure stability and transcription, thereby affecting the expression of its targets. In summary, we elucidated the genetic interactions between Pto-MIR167a and its targets, sponge lncRNA ARFRL, and Pto-ARF8, in tree growth and wood formation, and provide a feasible method for further investigation of multi-factor genetic networks influencing phenotypic variation in the population genetics of trees.