A Bivariate Mapping Model Identifies Major Covariation QTLs for Biomass Allocation Between Leaf and Stem Growth of Catalpa bungei

Genetic architecture of leaf morphology revealed by integrated trait module in Catalpa bungei

Leaves are crucial for maintaining plant growth and development via photosynthesis, and their function is simultaneously regulated by a suite of phenotypic traits. Although much is known about the genetic architecture of individual leaf traits, unraveling the genetic basis of complex leaf morphology remains a challenge. Based on the functional correlation and coordination of multi-traits, we divided 15 leaf morphological traits into three modules, comprising size (area, length, width, and perimeter), shape (leaf lobes, aspect ratio, circularity, rectangularity, and the relevant ratios), and color (red, green, and blue) for an ornamental tree species, Catalpa bungei. A total of 189 significant single-nucleotide polymorphisms were identified in the leaves of C. bungei: 35, 82, and 76 in the size, shape, and color modules, respectively. Four quantitative trait loci were common between the size and shape modules, which were closely related according to phenotype correlation, genetic mapping, and mRNA analysis. The color module was independent of them. Synergistic changes in the aspect ratio, leaf lobe, and circularity suggest that these traits could be the core indicators of the leaf shape module. The LAS and SRK genes, associated with leaf lobe and circularity, were found to function in plant defense mechanisms and the growth of leaves. The associations between the SRK and CRK2 genes and the leaf lobe and circularity traits were further verified by RT-qPCR. Our findings demonstrate the importance of integrating multi-trait modules to characterize leaf morphology and facilitate a holistic understanding of the genetic architecture of intraspecific leaf morphology diversity.

Effects of arbuscular mycorrhizal fungus inoculation on the growth and nitrogen metabolism of Catalpa bungei C.A.Mey. under different nitrogen levels

Evidence suggests that arbuscular mycorrhizal fungi (AMF) may promote the growth of woody plants. However, the effects of AMF on nitrogen (N) metabolism in plants, especially trees, and its regulatory mechanism are rarely reported. Here, the effects of AMF inoculation on the growth and N nutrition status of Catalpa bungei under different N levels were reported. Three N levels (low, medium, high) and two mycorrhizal inoculation treatments (inoculation with Rhizophagus intraradices or not) were used with factorial design. The results showed that medium N could significantly improve the physiological metabolism and growth of C. bungei seedlings. However, when N was excessive, growth was significantly inhibited whether inoculated AMF or not. Compared with non-inoculated treatments, AMF inoculation could promote the absorption of N and P, improve photosynthesis under low to medium N levels, thus promoting the growth of seedlings. AMF changed the biomass allocation in seedlings by reducing the stem mass ratio and root/shoot ratio, and increasing the leaf mass ratio. At medium N levels, compared with non-inoculated treatment, AMF inoculation could significantly promote root growth by changing root hormone levels and improving root architecture and root activity. Under N addition, AMF inoculation could improve the absorption and assimilation of N by regulating the expression of key enzyme genes of N metabolism and nitrate transporter genes (NRT2.4, NRT2.5, NRT2.7) in roots, and enhancing the activities of the key enzyme of N metabolism. This study may provide a reference for the application of AMF in the cultivation and afforestation technology of C. bungei in Northwest China.

Multiple dynamic models reveal the genetic architecture for growth in height of Catalpa bungei in the field

Growth in height (GH) is a critical determinant for tree survival and development in forests and can be depicted using logistic growth curves. Our understanding of the genetic mechanism underlying dynamic GH, however, is limited, particularly under field conditions. We applied two mapping models (Funmap and FVTmap) to find quantitative trait loci responsible for dynamic GH and two epistatic models (2HiGWAS and 1HiGWAS) to detect epistasis in Catalpa bungei grown in the field. We identified 13 co-located quantitative trait loci influencing the growth curve by Funmap and three heterochronic parameters (the timing of the inflection point, maximum acceleration and maximum deceleration) by FVTmap. The combined use of FVTmap and Funmap reduced the number of candidate genes by >70%. We detected 76 significant epistatic interactions, amongst which a key gene, COMT14, co-located by three models (but not 1HiGWAS) interacted with three other genes, implying that a novel network of protein interaction centered on COMT14 may control the dynamic GH of C. bungei. These findings provide new insights into the genetic mechanisms underlying the dynamic growth in tree height in natural environments and emphasize the necessity of incorporating multiple dynamic models for screening more reliable candidate genes.