Transcriptional-metabolic networks in beta-carotene-enriched potato tubers: the long and winding road to the Golden phenotype

Abstract

Vitamin A deficiency is a public health problem in a large number of countries. Biofortification of major staple crops (wheat [Triticum aestivum], rice [Oryza sativa], maize [Zea mays], and potato [Solanum tuberosum]) with β-carotene has the potential to alleviate this nutritional problem. Previously, we engineered transgenic "Golden" potato tubers overexpressing three bacterial genes for β-carotene synthesis (CrtB, CrtI, and CrtY, encoding phytoene synthase, phytoene desaturase, and lycopene β-cyclase, respectively) and accumulating the highest amount of β-carotene in the four aforementioned crops. Here, we report the systematic quantitation of carotenoid metabolites and transcripts in 24 lines carrying six different transgene combinations under the control of the 35S and Patatin (Pat) promoters. Low levels of B-I expression are sufficient for interfering with leaf carotenogenesis, but not for β-carotene accumulation in tubers and calli, which requires high expression levels of all three genes under the control of the Pat promoter. Tubers expressing the B-I transgenes show large perturbations in the transcription of endogenous carotenoid genes, with only minor changes in carotenoid content, while the opposite phenotype (low levels of transcriptional perturbation and high carotenoid levels) is observed in Golden (Y-B-I) tubers. We used hierarchical clustering and pairwise correlation analysis, together with a new method for network correlation analysis, developed for this purpose, to assess the perturbations in transcript and metabolite levels in transgenic leaves and tubers. Through a "guilt-by-profiling" approach, we identified several endogenous genes for carotenoid biosynthesis likely to play a key regulatory role in Golden tubers, which are candidates for manipulations aimed at the further optimization of tuber carotenoid content.

Figure 1.

Carotenoid biosynthesis in potato leaves/tubers. Bacterial enzymes are underlined.

Figure 2.

Phenotypes of transgenic plants. A, In vitro phenotypes of explants. B, In vitro phenotypes of regenerated plantlets. C, Leaf phenotypes of expressor plants grown in the greenhouse. Wt, Wild type.

Figure 3.

Expression of endogenous carotenoid metabolites and transcripts in the different segments of the leaf carotenoid pathway. A, Metabolite data (from Supplemental Table S1). B, Transcript data (from Supplemental Table S2). Transcript data are normalized to the housekeeping tubulin transcript. Early transcripts include PSY1, PSY2, PDS, ZDS, and CrtISO. α-Xanthophyll and β-xanthophyll synthases include LCY-e, LCY-b, LUT1, and LUT5 and LCY-b, CHY1, CHY2, LUT5, ZEP, and NXS, respectively. See also Figure 1. DW, Dry weight. [See online article for color version of this figure.]

Figure 4.

Expression of endogenous carotenoid metabolites and transcripts in the different segments of the tuber carotenoid pathway. A, Metabolite data (from Supplemental Table S3). B, Transcript data (from Supplemental Table S4). Transcript data are normalized to the housekeeping tubulin transcript. Early transcripts, α-xanthophyll, and β-xanthophyll synthases are as in Figure 3. DW, Dry weight. [See online article for color version of this figure.]

Figure 5.

Hierarchical clustering of transcript/metabolite fold changes in transgenic leaves and tubers. A, Leaf data. B, Tuber data. Colored squares represent the values of log₂-transformed fold changes of a transcript or metabolite with respect to the wild type, according to the color scale shown. Gray squares indicate no detectable expression of the corresponding transcript/metabolite. Hierarchical clustering was calculated both on columns and rows, applying the Pearson correlation coefficient with the average linkage algorithm. For details, see “Materials and Methods.”

Figure 6.

Matrix correlation analysis of transcript and metabolite levels in transgenic leaves and tubers. Visualization of the correlations is shown between carotenoid metabolites and transcript levels in wild-type and transgenic leaves (A) and tubers (B). Each square represents the correlation between the gene/metabolite heading the column and the gene/metabolite heading the row. Correlation coefficients and significances were calculated by applying the Pearson formula using Excel and visualized using the Heatmapper software. Pearson ρ values are shown and highlighted with different shades of red (positive correlations) or blue (negative correlations). For details, see “Materials and Methods.”

Figure 7.

Correlation networks of carotenoid transcripts and metabolites in transgenic leaves and tubers. Networks are visualized as circles, with each node representing an endogenous transcript (turquoise circles), a transgene (green triangles), or a metabolite (yellow diamonds). Lines joining the nodes represent correlations; direct correlations are shown in red, while inverse correlations are in blue. Node sizes are proportional to the respective node strengths, which are shown in Supplemental Table S5. Number of nodes (N) and network strength (NS) are shown on top of each network.