Comparative Root Transcriptome Profiling and Gene Regulatory Network Analysis between Eastern and Western Carrot (Daucus carota L.) Cultivars Reveals Candidate Genes for Vascular Tissue Patterning

Abstract

Carrot (Daucus carota L.) is a highly consumed vegetable rich in carotenoids, known for their potent antioxidant, anti-inflammatory, and immune-protecting properties. While genetic and molecular studies have largely focused on wild and Western carrot cultivars (cvs), little is known about the evolutionary interactions between closely related Eastern and Western cvs. In this study, we conducted comparative transcriptome profiling of root tissues from Eastern (UHSBC-23-1) and Western (UHSBC-100) carrot cv. to better understand differentially expressed genes (DEGs) associated with storage root development and vascular cambium (VC) tissue patterning. Through reference-guided TopHat mapping, we achieved an average mapping rate of 73.87% and identified a total of 3544 DEGs (p < 0.05). Functional annotation and gene ontology classification revealed 97 functional categories, including 33 biological processes, 19 cellular components, 45 metabolic processes, and 26 KEGG pathways. Notably, Eastern cv. exhibited enrichment in cell wall, plant-pathogen interaction, and signal transduction terms, while Western cv. showed dominance in photosynthesis, metabolic process, and carbon metabolism terms. Moreover, constructed gene regulatory network (GRN) for both cvs. obtained orthologs with 1222 VC-responsive genes of Arabidopsis thaliana. In Western cv, GRN revealed VC-responsive gene clusters primarily associated with photosynthetic processes and carbon metabolism. In contrast, Eastern cv. exhibited a higher number of stress-responsive genes, and transcription factors (e.g., MYB15, WRKY46, AP2/ERF TF connected via signaling pathways with NAC036) were identified as master regulators of xylem vessel differentiation and secondary cell wall thickening. By elucidating the comparative transcriptome profiles of Eastern and Western cvs. for the first time, our study provides valuable insights into the differentially expressed genes involved in root development and VC tissue patterning. The identification of key regulatory genes and their roles in these processes represents a significant advancement in our understanding of the evolutionary relations and molecular mechanisms underlying secondary growth of carrot and regulation by vascular cambium.

Keywords: candidate genes; carrot; gene regulatory network; plant stress response; vascular cambium.

Figure 1

Differentially expressed genes in Eastern and Western cultivars root transcriptome. (a) Bar plot representing the total number of up- and down-regulated DEGs in the root transcriptome by RNAseq analysis; (b) Chromosome-wise distribution of 3544 DEGs on 9 haploid sets of chromosomes of Carrot reference genome; up- (red dots) and down-regulated (blue dots) DEGs across Eastern and Western cv. are highlighted with different colors. (c) Volcano plot showing the up- (blue dots) and down-regulated (green dots) DEGs in Eastern and Western cv. of carrot, respectively.

Figure 2

(a): Gene ontology categorization of Biological processes (BP) across Eastern and Western carrot cultivars and the number of genes showing respective BP. (b): Gene ontology categorization of Cellular Components (CC) across Eastern and Western carrot cultivars and the respective genes involved in CC. (c): Gene ontology categorization of Molecular Functions (MF) across Eastern and Western carrots and the respective number of genes involved in MF. (d): Comparison of DEGs involved in KEGG. Red bars indicate KEGG pathways upregulated in Eastern cv, while blue/green bars indicate KEGG pathways upregulated in Western cv.

Figure 2

(a): Gene ontology categorization of Biological processes (BP) across Eastern and Western carrot cultivars and the number of genes showing respective BP. (b): Gene ontology categorization of Cellular Components (CC) across Eastern and Western carrot cultivars and the respective genes involved in CC. (c): Gene ontology categorization of Molecular Functions (MF) across Eastern and Western carrots and the respective number of genes involved in MF. (d): Comparison of DEGs involved in KEGG. Red bars indicate KEGG pathways upregulated in Eastern cv, while blue/green bars indicate KEGG pathways upregulated in Western cv.

Figure 3

KEGG pathways enrichment analysis by gene set enrichment analysis in (a) Eastern cv. and (b) Western cv.

Figure 4

Heat map constructed based on Euclidean distance depicting the significant differentially expressed transcripts across Eastern and Western cvs. involved in (a) cell cycle and cell wall metabolism, (b) signal transduction, (c) starch and sucrose metabolism. Heatmaps are drawn based on FPKM values of significant DEGs across cvs.

Figure 5

Gene regulatory network showing the interconnections of vascular cambium (VC) responsive genes and DEGs with stress-responsive genes and photosynthesis and carbon metabolism pathways in (a) Eastern carrot and (b) Western carrot based on an orthology search with A. thaliana and network drawn in STRING v. 11. Western and Eastern cv. root morphology and the vascular tissue (xylem, phloem and cambium and color) that are distinct across the cultivars are highlighted in the carrot vascular tissue.

Figure 5

Gene regulatory network showing the interconnections of vascular cambium (VC) responsive genes and DEGs with stress-responsive genes and photosynthesis and carbon metabolism pathways in (a) Eastern carrot and (b) Western carrot based on an orthology search with A. thaliana and network drawn in STRING v. 11. Western and Eastern cv. root morphology and the vascular tissue (xylem, phloem and cambium and color) that are distinct across the cultivars are highlighted in the carrot vascular tissue.

Figure 6

Validation of eastern vs. western DEGs identified in RNA seq by quantitative real-time PCR (qRT-PCR) in storage root transcriptome of cultivars of carrot by Log₂FC. Red dots indicate the candidate genes used for RNAseq (Table S1) the linear line is the regression line explaining qPCR and RNAseq results and R² is the regression coefficient.