Plant parasitic nematodes occurrence and genetic diversity of banana cultivars grown in Tanzania

• Published in: Plant omics Vol. 13; no. 1; pp. 21 - 29
• Main Authors: Mgonja, Doreen M., Temu, Gladness E., Lyantagaye, Sylvester L., Makaranga, Abdalah, Ndunguru, Joseph C., Luambano, Nessie D.
• Format: Journal Article
• Language: English
• Published: 20.05.2020
• Subjects: Bananas; Breeding; Genetic polymorphisms; Microsatellites (Genetics); Plant nematodes; Varieties; Tanzania
• ISSN: 1836-0661; 1836-3644
• DOI: 10.21475/POJ.13.01.20.P2085

The genetic diversity of bananas ('Musa spp.'), one of the most economically important crops in Tanzania, is underestimated with scarce reports available. In addition, cultivation of banana is severely constrained by plant parasitic nematodes (PPN). We assessed genetic diversity and population structure of 159 banana varieties from four agro-ecological zones (Northern, Southern highlands, Lake and Zanzibar islands) of Tanzania using 20 SSR markers analysed with UPGMA method. We also, assessed the PPN occurrence through isolation and counting of PPN from each banana genotype where leaf samples were collected. SSR primer pairs were polymorphic; and generated 63 distinct reproducible bands. The polymorphic information content values of each SSR marker ranged from 0.50 to 0.75 indicating high level of genetic diversity among banana varieties. The 159 banana varieties were grouped into two clusters: A and B, based on UPGMA cluster and population structure analysis. A total of 128 independent and 31 overlapping genotypes were identified. Higher kinship among genotypes was observed in cluster A compared with cluster B. Some of the clusters in A and B genotypes showed high genetic distance. The most prevalent and abundant nematode species was 'Pratylenchus goodeyi' with a mean count of 63%, followed by 'Radopholus similis' (31%) and 'P. coffeae' (6%). The results from this study provides a foundation for understanding genetic variability of bananas existing in Tanzania and PPN occurrence that will be valuable information for breeding disease and pest-resistant bananas with high yield traits.