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. 2025 Jan 17;11(2):e42035.
doi: 10.1016/j.heliyon.2025.e42035. eCollection 2025 Jan 30.

Morpho-cultural, pathogenic, and genetic characterization of Indian isolates of Macrophomina phaseolina causing charcoal rot in soybean

Laxman Singh Rajput  1   2 , Sanjeev Kumar  1 , Kriti Pathak  1 , Palak Acharya  1 , Divyanshu Goswami  1 , Vennampally Nataraj  1 , Maranna Shivakumar  1 , Hemant Singh Maheshwari  1   3 , Saloni Mandloi  1   4 , Sapna Jaiswal  1   4 , Asha Yadav  1   5 , Raksha Vishwakarma  1   5
Affiliations

Morpho-cultural, pathogenic, and genetic characterization of Indian isolates of Macrophomina phaseolina causing charcoal rot in soybean

Laxman Singh Rajput et al. Heliyon. .

Abstract

Macrophomina phaseolina, a devastating soil and seed-borne fungus causing charcoal rot in soybean, poses a significant challenge to soybean production and breeding programs across all major soybean-growing regions of India. Fifty-five M. phaseolina isolates were collected from India's eight diverse soybean-growing agroecological regions. These isolates were examined for morpho-cultural, molecular, and pathogenic variability. All these isolates were pathogenic to the soybean and had significant variability for different Morpho-cultural characters. Principal component analysis (PCA) showed that most of Morpho-cultural traits are not having association with pathogenic traits. Cluster analysis showed that all these 55 isolates of M. phaseolina were classified into two major groups, and virulence characters did not separate based on origin. Group B showed more diversity and included the most virulent pathogen isolates. Phylogenetic analysis of the Internal Transcribed Spacer (ITS), a conserved rDNA region, revealed limited diversity among the 55 isolates. Irrespective of morpho-cultural and pathogenic characters, most isolates (n = 52) were clustered in a group. Pathogenic variability analysis has revealed region specific most virulent isolate from diverse agroecological regions of India. GGE biplot segregated the main effect of each component, cultivars (G), isolates (I), and G × I interactions with significant levels (p < 0.001). The virulence of isolates contributed 56.30 % of the total variation, followed by varieties (36.79 %) and G × I interaction (4.96 %). GGE biplot also provides information on two highly discriminative isolates. These isolates may be useful for screening genotypes and identifying quantitative trait loci (QTL) linked to soybean charcoal rot.

Keywords: Charcoal rot; ITS; Macrophomina phaseolina; Morpho-cultural and pathogenic; Soybean.

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Conflict of interest statement

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Hemant S. Maheshwari reports article publishing charges was provided by The University of Groningen, the Netherlands. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
GGE biplot for ranking cultivars (JS 95-60, JS 20–98, and Shivalik) focused scaling for comparison of the cultivars with the ideal cultivars, based on mean and stability to an AUDPC of 55 isolates of M. phaseolina (MP1 to MP55) collected from major soybean growing agroecological zone of India. Details of isolates (MP 1 to MP 55) were presented in Table 1 and AUDPC of 55 isolates of M. phaseolina was presented in Table S4.
Fig. 2
Fig. 2
A triangle view of the GGE biplot showing which isolates of Macrophomina phaseolina (MP1 to MP55) from major soybean-growing agroecological zones of India had higher AUDPC values against the soybean cultivars JS 95-60, JS 20–98, and Shivalik. Details of isolates (MP 1 to MP 55) were presented in Table 1 and AUDPC of 55 isolates of M. phaseolina was presented in Table S4. The isolates positioned closest to the cultivars, but located outside the triangle, are considered the winning isolates. The isolates located within the triangle did not exhibit dominance over any cultivars.
Fig. 3
Fig. 3
PCA for 15 morpho-cultural traits and 3 pathogenic traits of 55 isolates of M. phaseolina collected from major soybean growing agroecological zone of India. Details of isolates (MP 1 to MP 55) are presented in Table 1, and morpho-cultural and pathogenic characters are in Table 2 and Tables S1–S3. Morpho-cultural traits radial growth at 2 days (RG), radial growth at 3 days (RG2), growth rate (GR), dry weight (DW), number of sclerotia (NS), mycelial cell size (CS), hyphal width (HW), width of micro-sclerotia (SSB), length of micro-sclerotia (SSL), constriction at the base (CB), upper surface colony colour (USC), lower surface colony colour (LSC), colony surface (CoS), margin of colony (MC) and aerial growth (AG); and pathogenic traits AUDPC on JS 95-60 (A1), AUDPC on Shivalik (A2) and AUDPC on JS 20–98 (A3) were consider for PCA.
Fig. 4
Fig. 4
A phylogenetic tree employing the neighbor-joining (NJ) method was constructed for 55 M. phaseolina isolates (MP 1 to MP 55), considering 15 morpho-cultural and 3 pathogenic traits. Isolate numbers are depicted on the branch termini. To assess branch robustness, bootstrap analysis with 1000 replicates was performed. Detailed information regarding the isolates can be found in Table 1.
Fig. 5
Fig. 5
Phylogenetic tree showing phylogenetic relationships for Macrophomina phseolina isolates using rDNA ITS sequences. Detailed information regarding the isolates can be found in Table 1. Nucleotide sequence alignment was performed using CLUSTALW. Phylogenetic distances were determined based on the Kimura 2-parameter nucleotide substitution model. Values of Bootstrap were >50 %, calculated from 1000 replicates, are indicated alongside the branches. The scale bar indicates a single nucleotide substitution for every 100 base positions.
figs1
figs1
Correlation matrix for morpho-cultural and pathogenic characters of M. phaseolina isolates
figs2
figs2
Cluster dendrogram for pathogenic characters of M. phaseolina isolates
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