Research on Key Genes for Flowering of Bambusaoldhamii Under Introduced Cultivation Conditions

Abstract

Background: Bambusaoldhamii is an important economic bamboo species. However, flowering occurred after its introduction and cultivation, resulting in damage to the economy of bamboo forests. Currently, the molecular mechanism of flowering induced by introduction stress is still unclear. This study systematically explored the key genes and regulatory pathways of flowering in Bambusaoldhamii under introduction stress through field experiments combined with transcriptome sequencing and weighted gene co-expression network analysis (WGCNA), with the aim of providing a basis for flower-resistant cultivation and molecular breeding of bamboo.

Results: The study conducted transcriptome sequencing on flowering and non-flowering Bambusaoldhamii bamboo introduced from Youxi, Fujian Province for 2 years, constructed a reference transcriptome containing 213,747 Unigenes, and screened out 36,800-42,980 significantly differentially expressed genes (FDR < 0.05). The results indicated that the photosensitive gene CRY and the temperature response gene COR413-PM were significantly upregulated in the flowering group; the expression level of the heavy metal detoxification gene MT3 increased by 27.77 times, combined with the upregulation of the symbiotic signaling gene NIN. WGCNA analysis showed that the expression level of the flower meristem determination gene AP1/CAL/FUL in the flowering group was 90.38 times that of the control group. Moreover, its expression is regulated by the cascade synergy of CRY-HRE/RAP2-12-COR413-PM signals.

Conclusions: This study clarifies for the first time that the stress of introducing Bambusaoldhamii species activates the triad pathways of photo-temperature signal perception (CRY/COR413-PM), heavy metal detoxification (MT3), and symbiotic regulation (NIN), collaboratively driving the AP1/CAL/FUL gene expression network and ultimately triggering the flowering process.

Keywords: Bambusaoldhamii; environmental stresses; flowering; introduced cultivation; key genes.

Figure 1

Bambusaoldhamii flowering bamboo (left) and non-flowering bamboo (right) samples.

Figure 2

Principal component analysis of Bambusaoldhamii samples.

Figure 3

Correlation analysis of Bambusaoldhamii samples.

Figure 4

Total unigene GO classification.

Figure 5

Total unigene KEGG classification.

Figure 6

Veen map of differential genes in Bambusaoldhamii before and after introduction and cultivation.

Figure 7

Differential genes GO enrichment analysis.

Figure 8

Differential genes KEGG enrichment analysis.

Figure 9

Heat map and FPKM of key genes related to external stimuli in different samples. (Error line: ±standard error, represents the degree of data dispersion; Significance mark: The same letter indicates an insignificant difference (p > 0.05), while different letters indicate a significant difference (p < 0.05)). (A) Heat maps of key gene expression associated with external stimuli in different samples; (B) FPKM of the light-sensing genes CRY and SHW among different samples; (C) FPKM of the oxygen-sensing gene HRE/RAP2-12 among different samples; (D) FPKM of the temperature-sensing genes COR413-PM and TOT3 among different samples; (E) FPKM of heavy metal detoxification genes MT3 and MT4 among different samples; (F) FPKM of the symbiotic signaling pathway gene NIN among different samples; (G) The FPKM of pathogen defense genes RIN4 and CHIA among different samples.

Figure 10

Shows heat maps of key gene expression related to floral organ development and their FPKM in different samples (Error line: ±standard error, represents the degree of data dispersion; Significance mark: The same letter indicates an insignificant difference (p > 0.05), while different letters indicate an significant difference (p < 0.05)). (A) Heat maps of key gene expression related to flower organ development in different samples; (B) The FPKM of FBH family members among different samples; (C) FPKM of the EDF1/2/++ gene among different samples; (D) The FPKM of the AP1/CAL/FUL gene among different samples.

Figure 11

Weighted gene co-expression network analysis of each sample.

Figure 12

The degree of gene expression in the blue module of each sample. Red represents positive correlation and green represents negative correlation.

Figure 13

Expression network map of 10 specific high-expression genes.

Figure 14

Quantitative real-time RT-PCR confirmation of seven candidate genes. (Error line: ±standard error, represents the degree of data dispersion; Significance mark: The same letter indicates an insignificant difference (p > 0.05), while different letters indicate a significant difference (p < 0.05); the correlation coefficient R between transcriptome data and qRT-PCR data).