Abstract
BackgroundGermplasm banks maintain collections representing the most comprehensive catalogue of native genetic diversity available for crop improvement. Users of germplasm banks are interested in a fixed number of samples representing as broadly as possible the diversity present in the wider collection. A relevant question is whether it is necessary to develop completely independent germplasm samples or it is possible to select nested sets from a pre-defined core set panel not from the whole collection. We used data from 15,384, maize landraces stored in the CIMMYT germplasm bank to study the impact on 8 diversity criteria and the sample representativeness of: (1) two core selection strategies, a statistical sampling (DM), or a numerical maximization method (CH); (2) selecting samples of varying sizes; and (3) selecting samples of different sizes independently of each other or in a nested manner.ResultsSample sizes greater than 10% of the whole population size retained more than 75% of the polymorphic markers for all selection strategies and types of sample; lower sample sizes showed more variability (instability) among repetitions; the strongest effect of sample size was observed on the CH-independent combination. Independent and nested samples showed similar performance for all the criteria for the DM method, but there were differences between them for the CH method. The DM method achieved better approximations to the known values in the population than the CH method; 2-d multidimensional scaling plots of the collection and samples highlighted tendency of sample selection towards the extremes of diversity in the CH method, compared with sampling more representative of the overall genotypic distribution of diversity under the DM method.ConclusionsThe use of core subsets of size greater than or equal to 10% of the whole collection satisfied well the requirement of representativeness and diversity. Nested samples showed similar diversity and representativeness characteristics as independent samples offering a cost effective method of sample definition for germplasm banks. For most criteria assessed the DM method achieved better approximations to the known values in the whole population than the CH method, that is, it generated more statistically representative samples from collections.
Highlights
Germplasm banks maintain collections representing the most comprehensive catalogue of native genetic diversity available for crop improvement
Based on the above consideration, the objective of this paper is to evaluate, using data from over 15,000 maize landraces stored in the CIMMYT maize germplasm bank, the impact on diversity and representativeness of (1) selecting samples of sizes 5, 10, 20, 30, 40 and 50% from the whole collection, (2) the influence of independent versus nested sampling of a collection, and (3) the relative merits of employing either a statistical sampling strategy represented by the D-method with Modified Roger genetic distance (MR) genetic distance or a numerical maximization method represented by Core Hunter 3 (CH3) and MR distance
Strategies for selecting samples (CH, DM methods) Results in this paper show that for all the criteria, for all sample sizes, and for both types of samples, the statistical DM method gives a better approximation to the known population values than the Core Hunter (CH) method
Summary
Germplasm banks maintain collections representing the most comprehensive catalogue of native genetic diversity available for crop improvement. Germplasm banks globally maintain national and international collections of the world’s most important food and forage species for the benefit of humanity Together these collections make up the most comprehensive catalogue of native genetic diversity offering a valuable underexplored resource for crop improvement in the face of challenges of population growth, climate change, changing diets etc. The maize and wheat focused “Seeds of Discovery” initiative (https://seedsofdiscovery.org/) and the rice focused “3000 genomes” project (http://iric.irri.org/resources/3 000-genomes-project) are two examples aiming to study the vast diversity stored in maize, wheat and rice germplasm banks This genomic characterization, either alone or in combination with other data resources, offers a new lens on germplasm bank collections, potentially facilitating more user-relevant germplasm selections to be made. Genetic markers have over the years been deployed as sources of information which can be used to assess representativeness of germplasm samples in genetic conservation activities such as accession regeneration and collection
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