The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
The Genetic Architecture of Response to Long-Term Artificial Selection for Oil Concentration in the Maize Kernel
Abstract
In one of the longest-running experiments in biology, researchers at the University of Illinois have selected for altered composition of the maize kernel since 1896. Here we use an association study to infer the genetic basis of dramatic changes that occurred in response to selection for changes in oil concentration. The study population was produced by a cross between the high- and low-selection lines at generation 70, followed by 10 generations of random mating and the derivation of 500 lines by selfing. These lines were genotyped for 488 genetic markers and the oil concentration was evaluated in replicated field trials. Three methods of analysis were tested in simulations for ability to detect quantitative trait loci (QTL). The most effective method was model selection in multiple regression. This method detected ∼50 QTL accounting for ∼50% of the genetic variance, suggesting that >50 QTL are involved. The QTL effect estimates are small and largely additive. About 20% of the QTL have negative effects (i.e., not predicted by the parental difference), which is consistent with hitchhiking and small population size during selection. The large number of QTL detected accounts for the smooth and sustained response to selection throughout the twentieth century.
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Cites
The genetical theory of natural selection
Fisher, R. A. (1930) · doi:10.5962/bhl.title.27468 · Cited by 17,617
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
Precision mapping of quantitative trait loci.
Zeng, Z. B. (1994) · Genetics · doi:10.1093/genetics/136.4.1457 · Cited by 3,182
Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population.
(1995) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040269 · Cited by 1,950
Lohmueller, K. E., Pearce, C. L., Pike, M., Lander, E. S., & Hirschhorn, J. N. (2003) · Nature Genetics · doi:10.1038/ng1071 · Cited by 1,900
The Genetic Architecture of Quantitative Traits
Mackay, T. F. C. (2001) · Annual Review of Genetics · doi:10.1146/annurev.genet.35.102401.090633 · Cited by 1,106
Cited by
The Genetic Architecture of Maize Flowering Time
Buckler, E. S., Holland, J. B., Bradbury, P. J., Acharya, C. B., Brown, P. J., Browne, C., Ersoz, E., Flint-Garcia, S., Garcia, A., Glaubitz, J. C., et al. (2009) · Science · doi:10.1126/science.1174276 · Cited by 1,457
Self-citationAn integrative genomics approach to infer causal associations between gene expression and disease
Schadt, E. E., Lamb, J., Yang, X., Zhu, J., Edwards, S., GuhaThakurta, D., Sieberts, S. K., Monks, S., Reitman, M., Zhang, C., et al. (2005) · Nature Genetics · doi:10.1038/ng1589 · Cited by 1,043
Data and Theory Point to Mainly Additive Genetic Variance for Complex Traits
Hill, W. G., Goddard, M. E., & Visscher, P. M. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000008 · Cited by 1,039
Association mapping: critical considerations shift from genotyping to experimental design
Myles, S., Peiffer, J., Brown, P. J., Ersoz, E. S., Zhang, Z., Costich, D. E., & Buckler, E. S. (2009) · The Plant Cell · doi:10.1105/tpc.109.068437 · Cited by 857
Haidt, J., & Joseph, C. (2008) · The Innate Mind, Volume 3 · doi:10.1093/acprof:oso/9780195332834.003.0019 · Cited by 650
Metadata
- Authors
- Laurie, C. C., Chasalow, S. D., LeDeaux, J. R., McCarroll, R., Bush, D., Hauge, B., Lai, C., Clark, D., Rocheford, T. R., & Dudley, J. W.
- Venue
- Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2004-12-01
- Volume
- 168
- Issue
- 4
- Pages
- 2141-2155
- ISSN
- 0016-6731 (ISSN-L)
- 1943-2631
- OpenAlex
- W1996797740
- Cited by
- 313
- References
- 6
- FWCI
- 5.72
- Type
- journal article
- Language
- en
- Open access
- closed
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- Laurie, C. C., Chasalow, S. D., LeDeaux, J. R., McCarroll, R., Bush, D., Hauge, B., Lai, C., Clark, D., Rocheford, T. R., & Dudley, J. W. (2004). The Genetic Architecture of Response to Long-Term Artificial Selection for Oil Concentration in the Maize Kernel. Genetics. https://doi.org/10.1534/genetics.104.029686
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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