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Data from: An SSR based approach incorporating a novel algorithm for identification of rare maize genotypes facilitates criteria for landrace conservation in Mexico

Citation

Hayano-Kanashiro, Corina et al. (2018), Data from: An SSR based approach incorporating a novel algorithm for identification of rare maize genotypes facilitates criteria for landrace conservation in Mexico, Dryad, Dataset, https://doi.org/10.5061/dryad.c9086

Abstract

Since maize was domesticated in Mexico around 9000 years ago, local farmers have selected and maintained seed stocks with particular traits and adapted to local conditions. In the present day many of these landraces are still cultivated, however increased urbanization and migration from rural areas implies a risk that this invaluable maize germplasm may be lost. In order to implement an efficient mechanism of conservation in situ, the diversity of these landrace populations must be estimated. Development of a method to select the minimum number of samples that would include the maximum number of alleles and identify germplasm harboring rare combinations of particular alleles will also safeguard the efficient ex-situ conservation of this germplasm. To reach this goal a strategy based on SSR analysis and a novel algorithm to define a minimum collection and rare genotypes using landrace populations from Puebla State, Mexico was developed as a “proof of concept” for methodology that could be extended to all maize landrace populations in Mexico and eventually to other native crops. The SSR based strategy using bulked DNA samples allows rapid processing of large numbers of samples and can be set up in most laboratories equipped for basic molecular biology. Therefore, continuous monitoring of landrace populations locally could easily be carried out. This methodology can now be applied to support incentives for small farmers for the in situ conservation of these traditional cultivars.

Usage Notes

Location

México
Puebla state