Understanding the triacylglycerol-based carbon anabolic differentiation in Cyperus esculentus and Cyperus rotundus developing tubers via transcriptomic and metabolomic approaches

Abstract

Background: Yellow nutsedge (Cyperus esculentus, known as 'YouShaDou' in China, YSD) and purple nutsedge (Cyperus rotundus, known as 'XiangFuZi' in China, XFZ), closely related Cyperaceae species, exhibit significant differences in triacylglycerol (TAG) accumulation within their tubers, a key factor in carbon flux repartitioning that highly impact the total lipid, carbohydrate and protein metabolisms. Previous studies have attempted to elucidate the carbon anabolic discrepancies between these two species, however, a lack of comprehensive genome-wide annotation has hindered a detailed understanding of the underlying molecular mechanisms.

Results: This study utilizes transcriptomic analyses, supported by a comprehensive YSD reference genome, and metabolomic profiling to uncover the mechanisms underlying the major carbon perturbations between the developing tubers of YSD and XFZ germplasms harvested in Yunnan province, China, where the plant biodiveristy is renowned worldwide and may contain more genetic variations relative to their counterparts in other places. Our findings indicate distinct expression patterns of key regulatory genes involved in TAG biosynthesis and lipid droplet formation, including transcriptional factors and structural genes such as ABI3 transcriptional factor, rate-limiting enzymes GPAT3/6/9 and DGAT2/3, and oleosin and caleosin homologs. Furthermore, our omics data suggest that these differences in gene expression are not the sole contributors to the diverse tuber compositions. Instead, complex interactions among highly regulated catalytic reactions, governing carbohydrate, protein, and species-specific metabolite metabolisms, such as starch and sucrose metabolic pathways, flavonoid and amino acids biosynthetic pathways, collectively contribute to the pronounced carbon anabolic differentiation primarily evident in TAG accumulation, as well as the starch properties in mature tubers.

Conclusion: This study offers new metabolic insights into the high-value underground non-photosynthetic tissues of Cyperaceae species, which harbors not only high biomass productivity but also abundant nutrients as favorable food or industrial sources in the modern agriculture. The detailed omics analyses aim to deepen our understanding of the Cyperaceae species, which may potentially broaden their application values and facilitate the molecular breeding of better varieties to ameliorate the food safety problem.

Keywords: Metabolomics; Purple nutsedge; Transcriptomics; Triacylglycerol; Yellow nutsedge.

Fig. 1

Morphology of YSD and XFZ tubers at three key developmental stages. S1 (tuber initiation stage): shows the initial form of tubers for both YSD and XFZ. S2 (tuber development stage): illustrates the intermediate growth phase of tubers, highlighting changes in size and structure. S3 (tuber maturation stage): depicts the fully matured tubers, characterized by increased size and morphological complexity

Fig. 2

Comparative Analyses of Major Carbon Anabolic Products in YSD and XFZ Tubers Across Three Developmental Stages. (a). contents of total lipids, (b). TAG, and (c). polar lipids in the tubers on a dry weight (DW) basis. (d). contents of total soluble sugars, (e). proteins, and (f). starch, also on a DW basis. Different letters above the bars or markers indicate the statistically significantly differences within the same component category, as determined by the LSD test (P < 0.05)

Fig. 3

Comparative transcriptomic analyses between developing tubers of YSD and XFZ. (a). The total number of up- and down-regulated DEGs. (b). A heat map visualization of the expression levels of these DEGs based on the FPKM values. (c). Lists of the top 30 classifications of upregulated DEGs according to the GO enrichment. (d). Top 30 classifications of downregulated DEGs based on GO enrichment. (e). Top 20 classifications of the upregulated DEGs as identified by KEGG enrichment. (f). Top 20 classifications of downregulated DEGs via KEGG enrichment

Fig. 4

Proposed metabolic pathways regulating TAG-based central carbon anabolism in developing YSD and XFZ tubers. (a). Starch and sucrose biosynthetic pathway. (b). TAG metabolic pathway. Upregulated genes are indicated by red positive numbers, while downregulated genes are marked with green negative numbers. (c). Heat map visualization of the gene expression differences in (a) and (b) (Supplementary Table S4). Abbreviations: F-6-P, fructose-6-phosphate; UDPG, uridine diphosphate glucose; G1P, glucose 1-phosphate; G6P, glucose 6-phosphate; ADPG, adenosine diphosphate glucose; SUS, sucrose synthase; UGP, UDP-glucose pyrophosphorylase; PFK, phosphofructokinase; PGI, pepsinogen I; PGM, phosphoglucomutase; GPT, glutamic-pyruvic transaminase; GBSS1, granule-bound starch synthase 1; SS, starch synthase; SBE, starch branching enzyme; ISA3, isoamylase 3; PHO, starch phosphorylase; CoA, Coenzyme A; ACP, acyl carrier protein; FAS, fatty acid synthase; FFA, free fatty acid; DHAP, dihydroxyacetone phosphate; G3P, sn-glycerol-3-phosphate; LPA, lysophosphatidic acid; PA, phosphatidic acid; DAG, diacylglycerol; ACCase, acetyl-CoA carboxylase; GPAT, sn-glycerol-3-phosphate acyltransferases; LPAAT, lysophospholipid acid actyltransferase; PAP, phosphatidic acid phosphatase; DGAT, diacylglycerol acyltransferase; PC, phosphatidylcholine; PDAT, phospholipid: diacylglycerol acyltransferase; PXA1, peroxisomal ABC-transporters 1; FatA/FatB, fatty acyl-ACP thioesterases A/B; SDP1, Sugar-dependent 1

Fig. 5

RT-qPCR validation of key regulatory DEGs identified from the transcriptomic analyses. (a). Relative expressions of selected typical unigenes from the starch and sucrose biosynthetic pathway. (b). Relative expressions of selected typical unigenes from the TAG metabolic pathway. Different letters above the bars indicate significant differences in the unigene expression levels, as determined by the LSD test (P < 0.05)

Fig. 6

Comparative metabolomic analyses between the YSD and XFZ developing tubers. (a). A Volcano map representing the 841 detected categories of metabolites. The fold change (FC) value was used to identify metabolites that are upregulated (FC > 1.5) and downregulated (FC < 0.67) at a significance level of P < 0.05. (b). A heat map visualization of the top 100 metabolites, consisting of 50 upregulated and 50 downregulated metabolites, based on the volcano map. (c) PLS-DA (partial least squares discrimination analyses) scores plot analyses of the YSD and XFZ experimental samples

Fig. 7

Joint analyses of DEGs and DAMs. (a). Venn diagram illustrating the overlap between DEGs and DAMs. (b). Bar chart depicting the top 10 enriched KEGG pathways. (c). Correlation network visualization displaying the top 100 relationships. Blue circles represent genes, and red circles indicate the metabolites. The connecting lines between genes and metabolites indicate their relationships, with yellow lines showing positive correlations and blue lines showing negative correlations, as determined by Pearson correlation coefficient analyses (P < 0.05)

Fig. 8

Primary starch property analyses of mature tubers from YSD and XFZ. (a). Contents of amylose and resistant starch. (b). Swelling power analyses. (c). RVA analyses of XFZ starch. (d). RVA analyses of YSD starch. (e). SEM observation of the XFZ starch granules. (f). SEM observation of YSD starch granules. Different letters above the bars indicate that the contents or values were significantly different, as determined by the LSD test (P < 0.05)