Abstract
Glycine soja, the wild progenitor of soybean, is a potential source of useful genetic variation in soybean improvement. The objective of our study was to map quantitative trait loci (QTL) from G. soja that could improve the crop. Five populations of BC2F4-derived lines were developed using the Glycine max cultivar IA2008 as a recurrent parent and the G. soja plant introduction (PI) 468916 as a donor parent. There were between 57 and 112 BC2F4-derived lines in each population and a total of 468 lines for the five populations. The lines were evaluated with simple sequence repeat markers and in field tests for yield, maturity, plant height, and lodging. The field testing was done over 2 years and at two locations each year. Marker data were analyzed for linkage and combined with field data to identify QTL. Using an experimentwise significance threshold of P=0.05, four yield QTL were identified across environments on linkage groups C2, E, K, and M. For these yield QTL, the IA2008 marker allele was associated with significantly greater yield than the marker allele from G. soja. In addition, one lodging QTL, four maturity QTL, and five QTL for plant height were identified across environments. Of the 14 QTL identified, eight mapped to regions where QTL with similar effects were previously mapped. Many regions carrying the yield QTL were also significant for other traits, such as plant height and lodging. When the significance threshold was reduced and the data were analyzed with simple linear regression, four QTL with a positive allele for yield from G. soja were mapped. One epistatic interaction between two genetic regions was identified for yield using an experimentwise significance threshold of P=0.05. Additional research is needed to establish whether multiple trait associations are the result of pleiotropy or genetic linkage and to retest QTL with a positive effect from G. soja.
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Acknowledgements
This material is based upon work supported by USDA-NRI Award No. 99–35300–7820. We appreciate the help of Kevin Chase and Gordon Lark for their assistance in using the program Epistat. This publication is a contribution of the University of Nebraska Agricultural Research Division, Lincoln, NE, 68583, Journal Series No. 13989.
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Wang, D., Graef, G.L., Procopiuk, A.M. et al. Identification of putative QTL that underlie yield in interspecific soybean backcross populations. Theor Appl Genet 108, 458–467 (2004). https://doi.org/10.1007/s00122-003-1449-z
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DOI: https://doi.org/10.1007/s00122-003-1449-z