Whole-genome DNA Methylation Analysis during the Flowering Processof Medicago truncatula

doi:10.13560/j.cnki.biotech.bull.1985.2025-0366

Abstract

Abstract:

Objective To investigate DNA methylation variations during flowering in Medicago ruthenica under long-day conditions and explore the potential relationship between photoperiod-related genes and DNA methylation. Method Whole-genome bisulfite sequencing (WGBS) was performed on M. ruthenica leaves at the vegetative and flowering stages to analyze differences in DNA methylation. Result 1) The predominant type of methylation was CG (69.74%), followed by CHG (35.22%) and CHH (21.81%). CHG methylation upstream of genes and CHH methylation in upstream, downstream, and gene body regions were all higher during the vegetative stage than in the flowering stage. 2) A total of 20 647 differentially methylated regions (DMRs) were identified, with CHH-type DMRs accounting for the majority (11 247), and 68% of them showing hypomethylation. 3) Gene Ontology (GO) and KEGG pathway analyses of all DMR-associated genes (DMGs) revealed that these genes were mainly involved in high-affinity oligopeptide transmembrane transporter activity, FAD-binding nucleoside triphosphatase activity, ATPase activity, and hydrolase activity acting on acid anhydrides, as well as in pathways such as tetrahydrofolate biosynthesis. 4) Key genes in the photoperiodic flowering pathway, including CRY1, CRY2, FKF1, PHYA, ELF3, COL2, FT, LHY, and ZTL,presented significant changes in DNA methylation levels. Conclusion DNA methylation may be involved in the regulation of flowering in M. ruthenica. This study provides new insights into the potential role of DNA methylation in photoperiod-induced flowering, offering valuable information for M. ruthenica breeding research.

Key words: Medicago truncatula, flowering, DNA methylation, transcription factors, photoperiod

JIANG Tian-wei, LI Ya-jiao, MA Pei-jie, CHEN Cai-jun, LIU Xiao-xia, CHEN Ying, WANG Xiao-li. Whole-genome DNA Methylation Analysis during the Flowering Processof Medicago truncatula[J]. Biotechnology Bulletin, 2025, 41(11): 301-310.

Figures/Tables 7

Table 1 Processing of whole-genome methylation sequencing data of Medicago truncatula

样本 Sample	总读取数 Total reads	比对读取数 Mapped reads	唯一比对读取数 Uniquely reads	测序深度 Seqencing depth	唯一比对率 Uniquely mapped reads （%）	比对率 Mapping rate （%）	Q30 （%）	转换率 Conversion rate （%）
FP_1	107573870	62923962	43437098	34.38	40.38	58.49	90.98	99.69
FP_2	93350734	52038408	34920690	29.86	37.41	55.75	91.34	99.67
FP_3	114432912	66064890	45284390	36.65	39.57	57.73	91.97	99.65
NP_1	103921110	60296822	44356076	33.25	42.68	58.02	91.44	99.67
NP_2	120328788	72294208	50808854	38.52	42.23	60.08	91.87	99.59
NP_3	129107620	74594082	51931090	41.32	40.22	57.78	91.59	99.61

Fig. 1 Variations in DNA methylation from the vegetative stage to the flowering stage in M. truncatulaA: Sample correlation analysis. B: Methylation level statistics for the three sequences. C: Methylation distribution in gene body regions and their flanking regions for the three sequences. FP refers to the flowering stage, and NP refers to the vegetative stage. The same below

Fig. 2 Differentially methylated region analysis between FP and NPA: Clustering heatmap of differentially methylated regions (DMRs) in the three sequences. B: Statistical chart of the number of DMRs. C: Proportional distribution of DMRs in the genome. In figure B and C, Hyper indicates hypermethylation, and Hypo indicates hypomethylation

Fig. 3 GO (A, B, C) and KEGG (D, E, F) enrichment analysis of genes associated with CG, CHG, and CHH types of DMRs in FP vs NP

Fig. 4 Transcription factor analysis associated with DMRsA: Proportion of transcription factor-encoding genes among DMR-associated genes in FP vs NP. B, C, D: Word clouds showing the abundance of DMR-associated transcription factor families under three sequence contexts. Figure B corresponds to CG, Figure C to CHG, and Figure D to CHH; the larger the text in Figure B, C, and D, the higher the abundance

Fig. 5 Protein-protein interaction network of transcription factor-encoding genesA: Protein-protein interaction network under CG context. B: Protein-protein interaction network under CHG context. C: Protein-protein interaction network under CHH context. Nodes indicate proteins, edges indicate interaction relationships, and red text next to the nodes indicates the gene IDs of key nodes

Table 2 DMR-associated genes related to photoperiod

序列类型 Type	基因 Gene	去甲基化 Hypo-DMR	超甲基化 Hyper-DMR
CG	ACTR4	-	Up
	GA20ox1	-	Up
	CRY1	-	Up
	UBOX13	-	Up
	NFYB3	-	Up
	CRY2	-	Up
	MYB1	-	Up
	CHS	-	Up
	SRO1	Down	-
	BHLH130	Down	-
CHG	CCX5	-	Up
	VOZ1	-	Up
	ACTR4	-	Up
	ATX2	-	Up
	FKF1	-	Up
	MYB75	-	Up
	PHYA	-	Up
	ELF3	-	Up
	UPF2	Down	-
	ELF6	Down	-
	BRN1	Down	-
	CHS	Down	-
	COL 2	Down	-
CHH	EZA1	-	Up
	PEPPER	-	Up
	MYB75	-	Up
	CSNK2A	-	Up
	CHS9	-	Up
	CHS2	Down	-
	DMR6-LIKE OXYGENASE 2	Down	-
	RENT3	Down	-
	FD	Down	-
	CCA1	Down	-
	DMR6-LIKE OXYGENASE 2	Down	-
	bHLH122	Down	-
	MYST family 2	Down	-
	COL 9	Down	-
	EZA1	Down	-
	BRN1	Down	-
	AGL18	Down	-
	FT	Down	-
	MYB114	Down	-
	LHY	Down	-
	MYB1	Down	-
	CHS	Down	-
	ZTL	Down	-
	COL2	Down	-

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