Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    Using genomic information to conserve genetic diversity in livestock
    Eynard, Sonia E. - \ 2018
    Wageningen University. Promotor(en): H. Komen, co-promotor(en): M.P.L. Calus; J.J. Windig; G. Restoux. - Wageningen : Wageningen University - ISBN 9789463432276 - 200

    Concern about the status of livestock breeds and their conservation has increased as selection and small population sizes caused loss of genetic diversity. Meanwhile, dense SNP chips and whole genome sequences (WGS) became available, providing opportunities to accurately quantify the impact of selection on genetic diversity and develop tools to better preserve such genetic diversity for long-term perspectives. This thesis aimed to infer the impact of selection and mitigate its effects on genetic diversity using genomic information. One of the advantages of WGS information, compared to pedigree and SNP chip information, is that it provides information on all variants, including rare ones, and ‘true’ relationships between individuals may be estimated thus being useful for evaluating genetic diversity. Taking into account rare variants had significant effects on estimated relationships. Moreover, optimal contribution (OC) strategy was used to perform selection either in a breeding program, maximising genetic merit while minimising loss of genetic diversity, or to build a gene bank, only maximising the conserved genetic diversity, with the aim to quantify loss of genetic diversity due to selection decisions. More genetic diversity was conserved when genomic information was used for selection decisions instead of pedigree and WGS information revealed a high loss of genetic diversity due to losing rare variants. Ways to reduce the loss of genetic diversity during a genomic selection program were investigated. The choice of individuals to update the reference population was proposed as a promising way to better conserve genetic diversity in a breeding population. In fact, changes in the reference population will lead to changes in prediction equations and thus ultimately to a shift in long-term selection decisions. Differences between reference population design using either random, truncation or OC selection of individuals, on the breeding population were modest but OC achieved conservation of more genetic diversity in the breeding population with only a small reduction in long-term genetic gain. Finally the potential of gene bank material as additional source of genetic diversity in the breeding population was examined, using the Dutch MRY cattle breed as a case study. Including old bulls, containing more genetic diversity than recent bulls, in the population of fathers for the next generation, selected with OC, resulted in both a slightly higher genetic merit and more genetic diversity conserved. The impact of selection on genetic diversity can be monitored by estimating the loss of rare variants over time. For the long-term perspectives of populations it is important to use specialised methods and genomic information to balance between selection response and conservation of genetic diversity.

    Which individuals to choose to update the reference population? Minimizing the loss of genetic diversity in animal genomic selection programs
    Eynard, Sonia E. ; Croiseau, Pascal ; Laloë, Denis ; Fritz, Sebastien ; Calus, Mario P.L. ; Restoux, Gwendal - \ 2018
    G3 : Genes Genomes Genetics 8 (2018)1. - ISSN 2160-1836 - p. 113 - 121.
    Genetic diversity - Genomic selection - GenPred - Optimal contribution - Reference population - Shared data resources
    Genomic selection (GS) is commonly used in livestock and increasingly in plant breeding. Relying on phenotypes and genotypes of a reference population, GS allows performance prediction for young individuals having only genotypes. This is expected to achieve fast high genetic gain but with a potential loss of genetic diversity. Existing methods to conserve genetic diversity depend mostly on the choice of the breeding individuals. In this study, we propose a modification of the reference population composition to mitigate diversity loss. Since the high cost of phenotyping is the limiting factor for GS, our findings are of major economic interest. This study aims to answer the following questions: how would decisions on the reference population affect the breeding population, and how to best select individuals to update the reference population and balance maximizing genetic gain and minimizing loss of genetic diversity? We investigated three updating strategies for the reference population: random, truncation, and optimal contribution (OC) strategies. OC maximizes genetic merit for a fixed loss of genetic diversity. A French Montbéliarde dairy cattle population with 50K SNP chip genotypes and simulations over 10 generations were used to compare these different strategies using milk production as the trait of interest. Candidates were selected to update the reference population. Prediction bias and both genetic merit and diversity were measured. Changes in the reference population composition slightly affected the breeding population. Optimal contribution strategy appeared to be an acceptable compromise to maintain both genetic gain and diversity in the reference and the breeding populations.
    Updating reference population in genomic selection for genetic diversity conservation. What can we learn from real data and simulations?
    Eynard, S.E. ; Croiseau, P. ; Laloë, Denis ; Calus, M.P.L. ; Fritz, S. ; Restoux, G. - \ 2017
    Updates in livestock genetic diversity conservation: Potential for wildlife populations
    Eynard, S.E. ; Calus, M.P.L. ; Restoux, G. - \ 2017
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