Genetic changes in soybean cultivars derived from Heihe 54
Soybean (Glycine max) variety Heihe 54 has played a crucial role in the Heihe soybean breeding program in China, contributing to the development of over 85 cultivars. To elucidate the genetic changes that have occurred across multiple generations of selection during soybean breeding, we conducted co...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-08-01
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| Series: | Crop Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214514125001382 |
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| Summary: | Soybean (Glycine max) variety Heihe 54 has played a crucial role in the Heihe soybean breeding program in China, contributing to the development of over 85 cultivars. To elucidate the genetic changes that have occurred across multiple generations of selection during soybean breeding, we conducted comprehensive genotyping analysis using the 180K Axiom SoyaSNP array on 42 varieties from the Heihe breeding program, as well as eight parental lines. Cluster analysis revealed four distinct groups, reflecting various breeding phases that incorporated diverse genetic resources as parental lines within the pedigree. A detailed examination of the graphical genotype profile across the genome identified preferred chromosome segments for specific breeding phases. These conserved blocks, which have been consistently maintained in descendant varieties during the extensive breeding period, likely harbor genes related to critical agronomic traits. This is exemplified by the consistent transmission of two segments located on chromosomes 18 and 20, which harbor the stem growth habit-related gene Dt2 and the leaflet shape-related gene Ln, respectively. The widespread cultivation of Heihe 43, a soybean cultivar developed within this pedigree, is attributed to its broad genetic base and the pyramiding of elite alleles from its parental lines. The identification of favorable chromosome segments provides valuable insight for agronomic trait-related gene mining and targeted breeding in the future. |
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| ISSN: | 2214-5141 |