| Title |
Is there an optimum level of diversity in utilization of genetic resources?
|
|---|---|
| Published in |
Theoretical and Applied Genetics, August 2017
|
| DOI | 10.1007/s00122-017-2959-4 |
| Pubmed ID | |
| Authors |
Manfred Mayer, Sandra Unterseer, Eva Bauer, Natalia de Leon, Bernardo Ordas, Chris-Carolin Schön |
| Abstract |
Capitalizing upon the genomic characteristics of long-term random mating populations, sampling from pre-selected landraces is a promising approach for broadening the genetic base of elite germplasm for quantitative traits. Genome-enabled strategies for harnessing untapped allelic variation of landraces are currently evolving. The success of such approaches depends on the choice of source material. Thus, the analysis of different strategies for sampling allelic variation from landraces and their impact on population diversity and linkage disequilibrium (LD) is required to ensure the efficient utilization of diversity. We investigated the impact of different sampling strategies on diversity parameters and LD based on high-density genotypic data of 35 European maize landraces each represented by more than 20 individuals. On average, five landraces already captured ~95% of the molecular diversity of the entire dataset. Within landraces, absence of pronounced population structure, consistency of linkage phases and moderate to low LD levels were found. When combining data of up to 10 landraces, LD decay distances decreased to a few kilobases. Genotyping 24 individuals per landrace with 5k SNPs was sufficient for obtaining representative estimates of diversity and LD levels to allow an informed pre-selection of landraces. Integrating results from European with Central and South American landraces revealed that European landraces represent a unique and diverse spectrum of allelic variation. Sampling strategies for harnessing allelic variation from landraces depend on the study objectives. If the focus lies on the improvement of elite germplasm for quantitative traits, we recommend sampling from pre-selected landraces, as it yields a wide range of diversity, allows optimal marker imputation, control for population structure and avoids the confounding effects of strong adaptive alleles. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 4 | 20% |
| France | 2 | 10% |
| Netherlands | 2 | 10% |
| Chile | 1 | 5% |
| United States | 1 | 5% |
| India | 1 | 5% |
| Turkey | 1 | 5% |
| Australia | 1 | 5% |
| Unknown | 7 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 70% |
| Scientists | 5 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 73 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 26% |
| Student > Ph. D. Student | 18 | 25% |
| Student > Master | 8 | 11% |
| Student > Bachelor | 4 | 5% |
| Student > Doctoral Student | 3 | 4% |
| Other | 11 | 15% |
| Unknown | 10 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 57 | 78% |
| Biochemistry, Genetics and Molecular Biology | 1 | 1% |
| Immunology and Microbiology | 1 | 1% |
| Economics, Econometrics and Finance | 1 | 1% |
| Social Sciences | 1 | 1% |
| Other | 0 | 0% |
| Unknown | 12 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 20. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 August 2019.
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#1,681,736
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Outputs from Theoretical and Applied Genetics
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Outputs of similar age from Theoretical and Applied Genetics
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