The genetic regulatory network centered on Pto-Wuschela and its targets involved in wood formation revealed by association studies

Abstract

Transcription factors (TFs) regulate gene expression and can strongly affect phenotypes. However, few studies have examined TF variants and TF interactions with their targets in plants. Here, we used genetic association in 435 unrelated individuals of Populus tomentosa to explore the variants in Pto-Wuschela and its targets to decipher the genetic regulatory network of Pto-Wuschela. Our bioinformatics and co-expression analysis identified 53 genes with the motif TCACGTGA as putative targets of Pto-Wuschela. Single-marker association analysis showed that Pto-Wuschela was associated with wood properties, which is in agreement with the observation that it has higher expression in stem vascular tissues in Populus. Also, SNPs in the 53 targets were associated with growth or wood properties under additive or dominance effects, suggesting these genes and Pto-Wuschela may act in the same genetic pathways that affect variation in these quantitative traits. Epistasis analysis indicated that 75.5% of these genes directly or indirectly interacted Pto-Wuschela, revealing the coordinated genetic regulatory network formed by Pto-Wuschela and its targets. Thus, our study provides an alternative method for dissection of the interactions between a TF and its targets, which will strength our understanding of the regulatory roles of TFs in complex traits in plants.

Genome-Wide Association Study With Growth-Related Traits and Secondary Metabolite Contents in Red- and White-Heart Chinese Fir

“…For example, Tian et al found that the SNP10 locus located in the PtGA20Ox gene was significantly associated with one wood growth trait and three texture traits, simultaneously (Tian et al, 2012). Yang et al (2015) also found that the SNP11 locus located in the Pto-Wuschela gene was significantly associated with tree height and volume per plant. The sites associated with multiple traits may be more effective in molecular marker-assisted selection and may also be helpful for mining important genomic regions.…”