Red and Blue Light Affect the Formation of Adventitious Roots of Tea Cuttings (Camellia sinensis) by Regulating Hormone Synthesis and Signal Transduction Pathways of Mature Leaves.

Abstract

Light is an important environmental factor which affects plant growth, through changes of intensity and quality. In this study, monochromatic white (control), red (660 nm), and blue (430 nm) light-emitting diodes (LEDs) were used to treat tea short cuttings. The results showed the most adventitious roots in blue light treated tea cuttings, but the lowest roots in that treated by red light. In order to explore the molecular mechanism of light quality affecting adventitious root formation, we performed full-length transcriptome and metabolome analyses of mature leaves under three light qualities, and then conducted weighted gene co-expression network analysis (WGCNA). Phytohormone analysis showed that Indole-3-carboxylic acid (ICA), Abscisic acid (ABA), ABA-glucosyl ester (ABA-GE), trans-Zeatin (tZ), and Jasmonic acid (JA) contents in mature leaves under blue light were significantly higher than those under white and red light. A crosstalk regulatory network comprising 23 co-expression modules was successfully constructed. Among them, the “MEblue” module which had a highly positive correlation with ICA (R = 0.92, P = 4e-04). KEGG analysis showed that related genes were significantly enriched in the “Plant hormone signal transduction (ko04075)” pathway. YUC (a flavin-containing monooxygenase), AUX1, AUX/IAA, and ARF were identified as hub genes, and gene expression analysis showed that the expression levels of these hub genes under blue light were higher than those under white and red light. In addition, we also identified 6 auxin transport-related genes, including PIN1, PIN3, PIN4, PILS5, PILS6, and PILS7. Except PILS5, all of these genes showed the highest expression level under blue light. In conclusion, this study elucidated the molecular mechanism of light quality regulating adventitious root formation of tea short cutting through WGCNA analysis, which provided an innovation for “rapid seedling” of tea plants.