DataSheet_3_Improving Short- and Long-Term Genetic Gain by Accounting for Within-Family Variance in Optimal Cross-Selection.pdf
The implementation of genomic selection in recurrent breeding programs raises the concern that a higher inbreeding rate could compromise the long-term genetic gain. An optimized mating strategy that maximizes the performance in progeny and maintains diversity for long-term genetic gain is therefore essential. The optimal cross-selection approach aims at identifying the optimal set of crosses that maximizes the expected genetic value in the progeny under a constraint on genetic diversity in the progeny. Optimal cross-selection usually does not account for within-family selection, i.e., the fact that only a selected fraction of each family is used as parents of the next generation. In this study, we consider within-family variance accounting for linkage disequilibrium between quantitative trait loci to predict the expected mean performance and the expected genetic diversity in the selected progeny of a set of crosses. These predictions rely on the usefulness criterion parental contribution (UCPC) method. We compared UCPC-based optimal cross-selection and the optimal cross-selection approach in a long-term simulated recurrent genomic selection breeding program considering overlapping generations. UCPC-based optimal cross-selection proved to be more efficient to convert the genetic diversity into short- and long-term genetic gains than optimal cross-selection. We also showed that, using the UCPC-based optimal cross-selection, the long-term genetic gain can be increased with only a limited reduction of the short-term commercial genetic gain.
History
References
- https://doi.org//10.3389/fgene.2016.00210
- https://doi.org//10.1101/209080
- https://doi.org//10.1007/s00122-019-03280-w
- https://doi.org//10.1534/g3.119.400129
- https://doi.org//10.2135/cropsci2006.01-0057
- https://doi.org//10.1186/s12711-016-0214-0
- https://doi.org//10.1038/hdy.1971.81
- https://doi.org//10.1186/1297-9686-34-2-145
- https://doi.org//10.1186/1297-9686-43-18
- https://doi.org//10.1534/genetics.112.147983
- https://doi.org//10.1534/genetics.115.178038
- https://doi.org//10.1534/genetics.116.194449
- https://doi.org//10.1017/S1357729800013667
- https://doi.org//10.1371/journal.pbio.3000071
- https://doi.org//10.1007/s00122-006-0467-z
- https://doi.org//10.1371/journal.pone.0028334
- https://doi.org//10.1534/genetics.115.182410
- https://doi.org//10.1534/genetics.114.169367
- https://doi.org//10.1007/s00122-018-3125-3
- https://doi.org//10.1093/bioinformatics/bty375
- https://doi.org//10.1109/TSMC.1971.4308298
- https://doi.org//10.1371/journal.pgen.1001139
- https://doi.org//10.2135/cropsci2014.03.0249
- https://doi.org//10.1186/1297-9686-42-35
- https://doi.org//10.1007/978-1-4020-9005-9_13
- https://doi.org//10.1186/1297-9686-43-4
- https://doi.org//10.1111/jbg.12268
- https://doi.org//10.1534/genetics.117.300403
- https://doi.org//10.3835/plantgenome2015.06.0046
- https://doi.org//10.1007/s00122-017-2863-y
- https://doi.org//10.2527/1997.754934x
- https://doi.org//10.1111/j.1439-0388.2008.00774.x
- https://doi.org//10.2135/cropsci2015.01.0030
- https://doi.org//10.1534/g3.118.200091
- https://doi.org//10.1073/pnas.70.12.3321
- https://doi.org//10.1007/s10681-007-9449-8
- https://doi.org//10.3168/jds.2011-4254
- https://doi.org//10.3168/jds.2011-4338
- https://doi.org//10.1007/s00122-018-3196-1
- https://doi.org//10.3835/plantgenome2014.10.0074
- https://doi.org//10.1186/1297-9686-46-42
- https://doi.org//10.1023/A:1008202821328
- https://doi.org//10.1007/s00122-011-1562-3
- https://doi.org//10.1017/S0016672312000274
- https://doi.org//10.1111/jbg.12148
- https://doi.org//10.1186/1297-9686-26-5-431
- https://doi.org//10.1534/genetics.107.075358
Usage metrics
Read the peer-reviewed publication
Categories
- Gene and Molecular Therapy
- Biomarkers
- Genetics
- Genetically Modified Animals
- Developmental Genetics (incl. Sex Determination)
- Epigenetics (incl. Genome Methylation and Epigenomics)
- Gene Expression (incl. Microarray and other genome-wide approaches)
- Livestock Cloning
- Genome Structure and Regulation
- Genetic Engineering
- Genomics