bioRxivGeneticsPreprint
Genetic Diversity Analysis of a Multi-Gene Bank Collection of Eggplant (Solanum melongena L.): Insights from Morphological Traits and SSR Markers
Patrick Louie G. Lipio, Ian Bien M. Oloc-oloc, Timothy D. Guinto, Bryan Anthony A. Diamante, John Albert M. CaraaniD, Richard T. Hermoso, V. C. Huelgas, Desiree M. HauteaiD
Abstract
Multiple pests and diseases significantly affect eggplant (Solanum melongena L.) yield. Its principal pest, the eggplant fruit and shoot borer [EFSB, Leucinodes orbonalis Guenee (Lepidoptera: Crambidae)], damages plants from the early vegetative stage to the late fruiting stage, while infestation by the green leafhopper [Amrasca biguttula Ishida (Hemiptera: Cicadellidae)] stunts vegetative growth. Analyzing the diversity of the worldwide collections in different gene banks would allow for the effective use of stockpiled genetic resources for the breeding of insect-resistant eggplant. The genetic diversity and population structure of 96 accessions from four (4) germplasm collections were assessed using marker data from 20 poly-morphic microsatellite (SSR, simple sequence repeats) markers distributed among all 14 linkage groups. Phenotypes that were given focus included those linked to possible physical barriers to herbivory and possible presence of defensive compounds. The average number of alleles (n) across loci was 4.8, with an average polymorphism information content (PIC) value of 0.59, suggesting that the SSR loci were moderately informative. Population structure analysis yielded two subgroups with moderate to highly significant differentiation within each cluster (Fst1 and Fst2 = 0.23 and 0.14, respectively). Taken together, hierarchical clustering and population structure analysis were able to discriminate accessions by vegetative characters but were not able to effectively discriminate based on geo-graphic provenance, fruit phenotype, nor mean EFSB incidence.
- organism: plant (other)
- assay: DNA methylation
- research focus: genome assembly
- research focus: variant calling
- research focus: GWAS / association mapping
- research focus: fine-mapping
- approach: statistical model
- Citations
- 0
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