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. 2024 Sep 26:15:1467432.
doi: 10.3389/fpls.2024.1467432. eCollection 2024.

Harnessing de novo transcriptome sequencing to identify and characterize genes regulating carbohydrate biosynthesis pathways in Salvia guaranitica L

Zahid Khorshid Abbas  1 , Arwa Abdulkreem Al-Huqail  2 , Aesha H Abdel Kawy  3 , Rabab A Abdulhai  4 , Doha A Albalawi  1   5 , Manal Abdullah AlShaqhaa  6 , Moodi Saham Alsubeie  7 , Doaa Bahaa Eldin Darwish  1 , Ahmed Ali Abdelhameed  8 , Fathia A Soudy  9 , Rania M Makki  10 , Maha Aljabri  11 , Nadiah Al-Sulami  10 , Mohammed Ali  12 , Muhammad Zayed  13
Affiliations

Harnessing de novo transcriptome sequencing to identify and characterize genes regulating carbohydrate biosynthesis pathways in Salvia guaranitica L

Zahid Khorshid Abbas et al. Front Plant Sci. .

Abstract

Introduction: Carbohydrate compounds serve multifaceted roles, from energy sources to stress protectants, found across diverse organisms including bacteria, fungi, and plants. Despite this broad importance, the molecular genetic framework underlying carbohydrate biosynthesis pathways, such as starch, sucrose, and glycolysis/gluconeogenesis in Salvia guaranitica, remains largely unexplored.

Methods: In this study, the Illumina-HiSeq 2500 platform was used to sequence the transcripts of S. guaranitica leaves, generating approximately 8.2 Gb of raw data. After filtering and removing adapter sequences, 38 million reads comprising 210 million high-quality nucleotide bases were obtained. De novo assembly resulted in 75,100 unigenes, which were annotated to establish a comprehensive database for investigating starch, sucrose, and glycolysis biosynthesis. Functional analyses of glucose-6-phosphate isomerase (SgGPI), trehalose-6-phosphate synthase/phosphatase (SgT6PS), and sucrose synthase (SgSUS) were performed using transgenic Arabidopsis thaliana.

Results: Among the unigenes, 410 were identified as putatively involved in these metabolic pathways, including 175 related to glycolysis/gluconeogenesis and 235 to starch and sucrose biosynthesis. Overexpression of SgGPI, SgT6PS, and SgSUS in transgenic A. thaliana enhanced leaf area, accelerated flower formation, and promoted overall growth compared to wild-type plants.

Discussion: These findings lay a foundation for understanding the roles of starch, sucrose, and glycolysis biosynthesis genes in S. guaranitica, offering insights into future metabolic engineering strategies for enhancing the production of valuable carbohydrate compounds in S. guaranitica or other plants.

Keywords: Salvia guaranitica; functional characterization; gluconeogenesis; glycolysis; starch; sucrose; transcriptome; transgenic Arabidopsis thaliana.

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Conflict of interest statement

The 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. The reviewer OH declared a past co-authorship with the author MA, and declared a shared affiliation with the author MZ to the handling editor at the time of the review.

Figures

Figure 1
Figure 1
Unigenes annotations in S. guaranitica. The three main categories are BP, CC, and MF. In order to ascertain the biofunctions of the S. guaranitica transcriptome, KEGG pathways of the 75,100 unigenes were determined, with 11,746 unigenes (15.64%) ascribed to 270 pathways. Primarily, five major pathways were identified: (A) Cellular Processes, (B) Environmental Information Processing, (C) Genetic Information Processing, (D) Metabolism, and (E) Organismal Systems ( Figure 2 ).
Figure 2
Figure 2
KEGG cellular processes pathways were classified into five largest categories; (A), environmental information processing (B), genetic information processing (C), metabolism (D) and organismal systems (E).
Figure 3
Figure 3
A heatmap illustrating the transcript levels of genes regulating (A) Glycolysis/Gluconeogenesis pathways and (B) Starch and Sucrose pathways.
Figure 4
Figure 4
Depicting the potential an ‘electronic fluorescent pictograph’ website for investigating A. thaliana orthologous genes’ potential tissue expression and their proteins’ cellular localizations as retrieved from the eFPbrowsers (http://bar.utoronto.ca/efp/cgi-bin/efpWeb.cgi). Panels (A, D) demonstrate where cells may express SgGPI (AT4G24620). Panels (B, E) indicate where cells may express SgT6PS (AT1G06410). Panels (C, F) demonstrate where cells may express SgSUS (AT5G37180). The color box shows expression scale (greater red indicates more gene expression).
Figure 5
Figure 5
Quantitative RT-PCR of glycolysis/gluconeogenesis, starch and sucrose metabolism genes. The relative expressions of SgGPI, SgT6PS, SgSUS, SgPFK9, SgALDH, SgALDO, SgPYK, SgFBP, SgACS, SgPCKA, SgGlGA, SgGlGC, SgBMY, SgGBE1, SgAGL, SgBGL, SgHK, SgPYG, SgUGDH, and SgINV were calculated. The values are means ± SE of three biological replicates. Significance levels were indicated as (*) for P-values less than 5%, (**) for P < 1%, and (***) for P < 0.1%.
Figure 6
Figure 6
Overexpression of the SgGPI, SgT6PS and SgSUS genes from S. guaranitica in transgenic A. thaliana. (A) Comparison of the phenotypes of the transgenic A.. thaliana and wild type A. thaliana. (B) Semi-qRT-PCR of the genes regulating starch, sucrose, and glycolysis biosynthesis.
Figure 7
Figure 7
Analysis of physiological and biochemical parameters from wild and transgenic A thaliana under the effects of overexpression of SgGPI, SgT6PS and SgSUS separately. (A) soluble sugar; (B) starch; (C) sugar; (D) fructose; (E) glucose; (F) total chlorophyll; (G) chlorophyll a; (H) chlorophyll (b) Significance levels were indicated as (*) for P-values less than 0.05, (**) for P < 0.01, and (***) for P < 0.001.
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