Marker-assisted selection and evaluation of high oil in vivo haploid inducers in maize |
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Authors: | Xin Dong Xiaowei Xu Liang Li Chenxu Liu Xiaolong Tian Wei Li Shaojiang Chen |
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Affiliation: | 1. National Maize Improvement Center of China, China Agricultural University, Yuanmingyuan West Road, Haidian District, Beijing, 100193, China 2. Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Yuanmingyuan West Road, Haidian District, Beijing, 100193, China
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Abstract: | Doubled haploid technology, which is used to rapidly purify genetic resources, is one of the key technologies in modern maize breeding. In a previous study, the major quantitative trait locus qhir1, which influences in vivo haploid induction, was narrowed down to a 243-kb region, which made it feasible to use marker-assisted selection (MAS) for inducer development. Recently, a new method was developed for haploid identification using oil content (OC). The objective of this study was to develop high oil inducer lines using MAS of the qhir1 locus. We constructed an F2 population, two backcross populations that were backcrossed to the inducer CAU5 (BC1F1-CAU5) and the high oil inbred line GY923 (BC1F1-GY923), respectively, which was derived from the cross GY923 × CAU5, and subjected continuous selfing to develop high oil inducer lines. In each cycle, three different parameters including kernel OC, marker genotype at qhir1 and haploid induction rate (HIR) were used for pedigree selection. Three candidate high oil inducer lines were developed, with an OC of approximately 8.5 %, an HIR of approximately 8 % and superior agronomic performance, which are suitable values for the application of these lines to haploid identification by OC. Our results confirm the notion that HIR selection combined with MAS for qhir1 is an effective approach to haploid inducer breeding. In addition, we determined that the accuracy of haploid identification by OC is influenced by the female germplasm resource and the high oil inducer and that appropriate critical points for OC can balance the false discovery rate and false negative rate. |
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