Validation and molecular analysis of β-1,3-GLU2 SNP marker associated with resistance to Colletotrichum gloeosporioides in mango (Mangifera indica L.)

Anthracnose caused by Colletotrichum gloeosporioides is one of the most destructive diseases of mango worldwide. Breeding for genetic resistance to anthracnose is necessary to improve the yield and fruit quality of mango. Here, we identified and analyzed the molecular basis of a SNP within the pathogenesis-related β-1,3-glucanase 2 (β-1,3-GLU2) gene putatively linked with resistance to anthracnose. This SNP designated ‘21881933’ causes a missense mutation (I196V) in the highly conserved glycosyl hydrolase family 17 (GH17) domain—a structural unit involved in physiologically important processes in plants, notably in response to biotic and abiotic stresses, activation of phytohormones, lignification, and cell wall remodeling. Structural analysis suggested that the I196V mutation results in unfavorable conformational changes in the enzyme's (β/α)8 TIM-barrel motif and catalytic groove. In phenotyping and AS-PCR assays, we found that the two alleles of SNP 21881933 are significantly correlated to anthracnose resistance. Mango genotypes with the β-1,3-GLU2 allele ‘G’ showed significantly higher disease severity post-inoculation while those with β-1,3-GLU2 allele ‘A’ showed phenotypic resistance to the disease. These results indicate that β-1,3-GLU2 is involved in the primary defense response of mango against C. gloeosporioides and that SNP 21881933 enhances the activities of β-1,3-glucanases. To our knowledge, this is the first report describing the molecular basis of anthracnose resistance in mango involving β-1,3-glucanases. Furthermore, we developed a marker that can discriminate β-1,3-GLU2 SNP alleles using a simple and cost-effective allele-specific PCR assay. Our findings support the utilization of this marker for marker-assisted selection (MAS) and genotyping of resistant mangoes as early as the seedling stage. This will help improve mango breeding efficiency and significantly reduce the expenses in field inputs, maintenance, and evaluation of material over the years.