Understanding the population structure and genetic diversity in sugarcane (
Saccharum officinarum
L.) accessions from
INTA germplasm bank (Argentina) will be of great importance for germplasm collection and breeding improvement
as it will identify diverse parental combinations to create segregating progenies with maximum genetic variability for
further selection. A Bayesian approach, ordination methods (PCoA, Principal Coordinate Analysis) and clustering analysis
(UPGMA, Unweighted Pair Group Method with Arithmetic Mean) were applied to this purpose. Sixty three INTA sugarcane
hybrids were genotyped for 107 Simple Sequence Repeat (SSR) and 136 Amplified Fragment Length Polymorphism
(AFLP) loci. Given the low probability values found with AFLP for individual assignment (4.7%), microsatellites seemed
to perform better (54%) for STRUCTURE analysis that revealed the germplasm to exist in five optimum groups with partly
corresponding to their origin. However clusters shown high degree of admixture, F
ST values confirmed the existence of
differences among groups. Dissimilarity coefficients ranged from 0.079 to 0.651. PCoA separated sugarcane in groups that
did not agree with those identified by STRUCTURE. The clustering including all genotypes neither showed resemblance
to populations find by STRUCTURE, but clustering performed considering only individuals displaying a proportional
membership > 0.6 in their primary population obtained with STRUCTURE showed close similarities. The Bayesian method
indubitably brought more information on cultivar origins than classical PCoA and hierarchical clustering method.
