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An informational view of accession rarity and allele specificity in germplasm banks for management and conservation

Author: Reyes-Valdés, M.H.
Author: Burgueño, J.
Author: Sukhwinder-Singh
Author: Martínez, O.
Author: Sansaloni, C.P.
Year: 2018
ISSN: ESSN: 1932-6203
URI: https://hdl.handle.net/10883/19951
Abstract: Germplasm banks are growing in their importance, number of accessions and amount of characterization data, with a large emphasis on molecular genetic markers. In this work, we offer an integrated view of accessions and marker data in an information theory framework. The basis of this development is the mutual information between accessions and allele frequencies for molecular marker loci, which can be decomposed in allele specificities, as well as in rarity and divergence of accessions. In this way, formulas are provided to calculate the specificity of the different marker alleles with reference to their distribution across accessions, accession rarity, defined as the weighted average of the specificity of its alleles, and divergence, defined by the Kullback-Leibler formula. Albeit being different measures, it is demonstrated that average rarity and divergence are equal for any collection. These parameters can contribute to the knowledge of the structure of a germplasm collection and to make decisions about the preservation of rare variants. The concepts herein developed served as the basis for a strategy for core subset selection called HCore, implemented in a publicly available R script. As a proof of concept, the mathematical view and tools developed in this research were applied to a large collection of Mexican wheat accessions, widely characterized by SNP markers. The most specific alleles were found to be private of a single accession, and the distribution of this parameter had its highest frequencies at low levels of specificity. Accession rarity and divergence had largely symmetrical distributions, and had a positive, albeit non-strictly linear relationship. Comparison of the HCore approach for core subset selection, with three state-of-the-art methods, showed it to be superior for average divergence and rarity, mean genetic distance and diversity. The proposed approach can be used for knowledge extraction and decision making in germplasm collections of diploid, inbred or outbred species.
Format: PDF
Language: English
Publisher: Public Library of Science
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
Type: Article
Place of Publication: San Francisco, Calif., U.S.
Issue: 2
Volume: 13
DOI: 10.1371/journal.pone.0193346
Agrovoc: WHEAT
Agrovoc: CLIMATE CHANGE
Agrovoc: ALLELES
Agrovoc: GERMPLASM BANKS
Agrovoc: PLANT BREEDING
Agrovoc: PLANT GENETICS
Agrovoc: GERMPLASM CONSERVATION
Related Datasets: http://hdl.handle.net/11529/10013
Related Datasets: https://ndownloader.figshare.com/articles/5935111/versions/1
Related Datasets: https://hdl.handle.net/11529/10547952
Elocator: e0193346
Journal: PLoS ONE


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  • Genetic Resources
    Genetic Resources including germplasm collections, wild relatives, genotyping, genomics, and IP

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