The exploitation of heterosis through hybrid breeding is one of the major breeding objectives for productivity increase in crop plants. This research analyzes the genetic basis of heterosis in by using a doubled haploid (DH) mapping population derived from F between two heterotic inbred parents, one belonging to the Indian and the other belonging to the east European gene pool, and their two corresponding sets of backcross hybrids. An Illumina Infinium Brassica 90K SNP array-based genetic map was used to identify yield influencing quantitative trait loci (QTL) related to plant architecture, flowering, and silique- and seed-related traits using five different data sets from multiple trials, allowing the estimation of additive and dominance effects, as well as digenic epistatic interactions. In total, 695 additive QTL were detected for the 14 traits in the three trials using five data sets, with overdominance observed to be the predominant type of effect in determining the expression of heterotic QTL. The results indicated that the design in the present study was efficient for identifying common QTL across multiple trials and populations, which constitute a valuable resource for marker-assisted selection and further research. In addition, a total of 637 epistatic loci were identified, and it was concluded that epistasis among loci without detectable main effects plays an important role in controlling heterosis in yield of .
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http://dx.doi.org/10.3389/fpls.2021.721631 | DOI Listing |
J Integr Plant Biol
January 2025
Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
Lodging reduces grain yield and quality in cereal crops. Lodging resistance is affected by the strength of the culm, which is influenced by the culm diameter, culm wall thickness, and cell wall composition. To explore the genetic architecture of culm diameter in rice (Oryza sativa), we conducted a genome-wide association study (GWAS).
View Article and Find Full Text PDFJ Integr Plant Biol
December 2024
Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization (MOE) and Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
Starch biosynthesis is a critical factor in wheat (Triticum aestivum L.) quality and yield. However, the full scope of its regulation is not fully understood.
View Article and Find Full Text PDFFront Plant Sci
December 2024
Key Laboratory of Cultivation and Protection for Non-Wood Forest Trees of the Ministry of Education, Central South University of Forestry and Technology, Changsha, China.
() is one of the key genes in regulating photosynthesis and plant architecture. As the antagonistic effects of have concurrent impacts on photosynthesis and yield component traits, how we can effectively utilize the gene to further increase rice yield is not clear. In this study, we used two different main functional alleles, each of which has previously been proven to have specifically advantageous traits, and tested whether the combined alleles have a higher yield than the homozygous alleles.
View Article and Find Full Text PDFBackground: Orange maize genotypes are sources of provitamin A (PVA) carotenoids, which are precursors of vitamin A. PVA deficiency and drought constitute major challenges causing increasing food and nutritional insecurity in sub-Saharan Africa (SSA). Breeding of drought-tolerant provitamin A hybrid maize can mitigate these challenges.
View Article and Find Full Text PDFBehav Genet
December 2024
Department of Evolution, Ecology, and Organismal Biology, University of California, Riverside, CA, USA.
Artificial selection yielded four replicate high runner (HR) lines of mice that reached apparent selection limits (~ threefold increase in wheel revolutions per day vs. four control lines), despite maintenance of additive genetic variance. After 68 generations, we used animal models to test for changes in additive-genetic variances and covariance of the two measured components (average speed and duration) of running distance.
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