Abstract
Bread wheat (Triticum aestivum L.) has the A, B, and D genomes, whereas durum wheat (Triticum turgidum L. ssp. durum) has the A and B genomes. This study aimed to assess the usefulness of the square of predictive ability for subgenome i [rMP(i)2] for estimating subgenome contributions to trait variation and to determine which subgenomes in bread wheat and durum wheat populations had the largest and smallest contributions for different traits. Phenotypic and marker data were obtained for four populations used in published studies to map quantitative trait loci (QTL). Subgenome rMP(i) was calculated by analyzing only the markers within each subgenome. Clear differences were found in subgenome contributions for several but not all traits in the populations studied. In the Louise × Penawawa bread wheat population, the rMP(i)2 values indicated that the B genome had the largest contribution to variation for milling and baking quality traits, and these results were consistent with prior results showing QTL for such traits on chromosome 3B. For yield, no significant differences in subgenome contributions were found in any of the populations. The D genome, despite its lower polymorphism, had the largest rMP(i)2 for heading date in the ‘Seri’ × ‘Babax’ bread wheat population. In a bread wheat association mapping panel, the rMP(i)2 values were problematic in that their sum exceeded 1.0 and the subgenome rMP(i) values were not significantly different from the whole-genome rMP. This result was probably caused by linkage disequilibrium between markers found in different subgenomes in the association mapping panel.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1002-1012 |
| Number of pages | 11 |
| Journal | Crop Science |
| Volume | 61 |
| Issue number | 2 |
| DOIs | |
| State | Published - Mar 1 2021 |
Bibliographical note
Funding Information:I conducted most of the work described here while I was on sabbatical leave at the University of Bologna in the autumn of 2019. I thank Professors Roberto Tuberosa, Elisabetta Frascaroli, and Marco Maccaferri for being very gracious hosts who taught me some wheat genetics, and the Institute for Advanced Studies in Bologna for providing sabbatical funding. I deeply thank Carter et al. (2012), Godoy et al. (2018), Liu et al. (2019), and Zaïm et al. (2020) for making their data available, and Dr. Sushan Ru for compiling much of the published data and running the rrBLUP analysis that confirmed the results for the wheat panel.
Publisher Copyright:
© 2020 The Authors. Crop Science © 2020 Crop Science Society of America