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. 2024 Jun 7;13(12):1582.
doi: 10.3390/plants13121582.

Transcriptomic Insights into Molecular Response of Butter Lettuce to Different Light Wavelengths

Yongqi Liang  1 , Xinying Weng  2 , Hao Ling  2 , Ghazala Mustafa  3 , Bingxian Yang  2 , Na Lu  4
Affiliations

Transcriptomic Insights into Molecular Response of Butter Lettuce to Different Light Wavelengths

Yongqi Liang et al. Plants (Basel). .

Abstract

Lettuce is a widely consumed leafy vegetable; it became popular due to its enhanced nutritional content. Recently, lettuce is also regarded as one of the model plants for vegetable production in plant factories. Light and nutrients are essential environmental factors that affect lettuce growth and morphology. To evaluate the impact of light spectra on lettuce, butter lettuce was grown under the light wavelengths of 460, 525, and 660 nm, along with white light as the control. Plant morphology, physiology, nutritional content, and transcriptomic analyses were performed to study the light response mechanisms. The results showed that the leaf fresh weight and length/width were higher when grown at 460 nm and lower when grown at 525 nm compared to the control treatment. When exposed to 460 nm light, the sugar, crude fiber, mineral, and vitamin concentrations were favorably altered; however, these levels decreased when exposed to light with a wavelength of 525 nm. The transcriptomic analysis showed that co-factor and vitamin metabolism- and secondary metabolism-related genes were specifically induced by 460 nm light exposure. Furthermore, the pathway enrichment analysis found that flavonoid biosynthesis- and vitamin B6 metabolism-related genes were significantly upregulated in response to 460 nm light exposure. Additional experiments demonstrated that the vitamin B6 and B2 content was significantly higher in leaves exposed to 460 nm light than those grown under the other conditions. Our findings suggested that the addition of 460 nm light could improve lettuce's biomass and nutritional value and help us to further understand how the light spectrum can be tuned as needed for lettuce production.

Keywords: butter lettuce; light spectrum; nutritional content; physiology; transcriptomics.

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Conflict of interest statement

Yongqi Liang is employed by Shanxi Qingmei Biotechnology Company Limited. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Morphological characteristics of leaves of butter lettuce grown under different light wavelengths. Data are presented as mean ± SD of three independent biological replicates. The same letters on bar graph indicate no significant differences among the samples based on one-way ANOVA (p < 0.05).
Figure 2
Figure 2
Estimation of soluble sugar (a) and crude fiber (b) content in butter lettuce leaves. Data are presented as mean ± SD of three independent biological replicates. The same letters on bar graph indicate no significant differences among the samples based on one-way ANOVA (p < 0.05).
Figure 3
Figure 3
The metal ion content in leaves of butter lettuce. Data are presented as mean ± SD of three independent biological replicates. The same letters on bar graph indicate no significant differences among the samples based on one-way ANOVA (p < 0.05).
Figure 4
Figure 4
Transcriptomic analysis of leaves under different light wavelengths. (a) The correlation analysis between samples; (b) the PCA analysis of samples; (c) Venn diagram showing the overlap of identified genes in samples. The number of differentially expressed genes that were commonly identified is shown in the center of the Venn diagram.
Figure 5
Figure 5
Clusters of differentially expressed genes. Differentially expressed genes were clustered and are represented as line charts with the help of Mev. Six clusters were identified. The x-axis represents the samples from plants grown under different light wavelengths. The y-axis indicates the normalized gene expression level. In each cluster, the black line indicates the zero line while the purple line indicates the average expression level. The number at the upper left corner represents the number of DEGs in each cluster.
Figure 6
Figure 6
The GO enrichment analysis of genes. (a) GO enrichment analysis exposed to 460 nm light; (b) GO enrichment analysis exposed to 525 nm light.
Figure 7
Figure 7
Functional categorization and enrichment of genes. The comparisons between LE460 nm/LE525 nm/LE660 nm and LEC were performed to identify the differentially expressed genes. Gene functions were predicted and categorized using MapMan bin codes. The cluster analysis of the common differentially expressed genes produced three clusters.
Figure 8
Figure 8
The KEGG enrichment analysis of genes. (a) KEGG enrichment analysis result of signaling-related genes; (b) KEGG enrichment analysis result of stress related genes.
Figure 9
Figure 9
Function analysis of genes. Gene functions were predicted and categorized using MapMan bin codes. (a) Function analysis result of secondary metabolism related genes; (b) Function analysis result of Co-factor and vitamine metabolism genes.
Figure 10
Figure 10
The vitamin content in leaves grow under different light wavelengths. Data are presented as mean ± SD of three independent biological replicates. The same letters on bar graph indicate no significant differences among the samples based on one-way ANOVA (p < 0.05).
Figure 11
Figure 11
The chlorophyll and anthocyanin content in lettuce grown under different light wavelengths. Data are presented as mean ± SD of three independent biological replicates. The same letters on bar graph indicate no significant differences among the samples based on one-way ANOVA (p < 0.05).
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