Genomic Selection for Crop Improvement
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Abstract
ABSTRACT Despite important strides in marker technologies, the use of marker‐assisted selection has stagnated for the improvement of quantitative traits. Biparental mating designs for the detection of loci affecting these traits (quantitative trait loci [QTL]) impede their application, and the statistical methods used are ill‐suited to the traits' polygenic nature. Genomic selection (GS) has been proposed to address these deficiencies. Genomic selection predicts the breeding values of lines in a population by analyzing their phenotypes and high‐density marker scores. A key to the success of GS is that it incorporates all marker information in the prediction model, thereby avoiding biased marker effect estimates and capturing more of the variation due to small‐effect QTL. In simulations, the correlation between true breeding value and the genomic estimated breeding value has reached levels of 0.85 even for polygenic low heritability traits. This level of accuracy is sufficient to consider selecting for agronomic performance using marker information alone. Such selection would substantially accelerate the breeding cycle, enhancing gains per unit time. It would dramatically change the role of phenotyping, which would then serve to update prediction models and no longer to select lines. While research to date shows the exceptional promise of GS, work remains to be done to validate it empirically and to incorporate it into breeding schemes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Crop Science
- Topic
- Genetic and phenotypic traits in livestock
- Field
- Biochemistry, Genetics and Molecular Biology
- Canadian institutions
- —
- Funders
- HatchU.S. Department of Agriculture
- Keywords
- BiologyQuantitative trait locusGenomic selectionSelection (genetic algorithm)HeritabilityMarker-assisted selectionTraitPopulationGeneticsBiotechnologyComputational biologyEvolutionary biologyMachine learningComputer scienceGeneSingle-nucleotide polymorphismGenotype
- Has abstract in OpenAlex
- yes