| Autor: |
Murphy, Matthew D., Lipka, Alexander E. |
| Zdroj: |
Crop Science; Sep/Oct2023, Vol. 63 Issue 5, p2807-2817, 11p |
| Abstrakt: |
Genomic regions containing loci with effect sizes that interact with environmental factors are desirable targets for selection because of increasingly unpredictable growing seasons. Although selecting upon such gene‐by‐environment (G × E) loci is vital, identifying significantly associated loci is challenging due to the multiple testing correction. Consequently, G × E loci of small‐ to moderate effect sizes may never be identified via traditional genome‐wide association studies (GWAS). Variance GWAS (vGWAS) have been previously shown to identify G × E loci. Combined with its inherent reduction in the severity of multiple testing, we hypothesized that vGWAS could be successfully used to identify genomic regions likely to contain G × E effects. We used publicly available genotypic and phenotypic data in maize (Zea mays L.) to test the ability of two vGWAS approaches to identify G × E loci controlling two flowering traits. We observed high inflation of −log10(p−values)$ - {\log }_{10}({p{\mathrm{ - values}}})$ from both approaches. This suggests that these two vGWAS approaches are not suitable to the task of identifying G × E loci. We advocate that similar future applications of vGWAS use more sophisticated models that can adequately control the inflation of −log10(p−values)$ - {\log }_{10}({p{\mathrm{ - values}}})$. Otherwise, the application of vGWAS to search for G × E effects that are critical for combating the effects of climate change will not reach its full potential. Core Ideas: We ran two commonly used vGWAS models to search for G × E interactions for two flowering‐time traits in maize.We identified SNPs associated with the flowering‐time traits.We observed severe inflation of false positives for all models and traits. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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