Abstract
Soybean is a high phosphorus (P) demand species that is sensitive to low-P stress. Although many quantitative trait loci (QTL) for P efficiency have been identified in soybean, but few of these have been cloned and agriculturally applied mainly due to various limitations on identifying suitable P efficiency candidate genes. Here, we combined QTL mapping, transcriptome profiling, and plant transformation to identify candidate genes underlying QTLs associated with low-P tolerance and response mechanisms to low-P stress in soybean. By performing QTL linkage mapping using 152 recombinant inbred lines (RILs) that were derived from a cross between a P-efficient variety, Nannong 94–156, and P-sensitive Bogao, we identified four major QTLs underlying P efficiency. Within these four QTL regions, 34/81 candidate genes in roots/leaves were identified using comparative transcriptome analysis between two transgressive RILs, low-P tolerant genotype B20 and sensitive B18. A total of 22 phosphatase family genes were up-regulated significantly under low-P condition in B20. Overexpression of an acid phosphatase candidate gene, GmACP2, in soybean hairy roots increased P efficiency by 15.43–24.54 % compared with that in controls. Our results suggest that integrating QTL mapping and transcriptome profiling could be useful for rapidly identifying candidate genes underlying complex traits, and phosphatase-encoding genes, such as GmACP2, play important roles involving in low-P stress tolerance in soybean.
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Acknowledgments
We thank Prof. Gresshoff (University of Queensland, Australia) for providing the A. rhizogenes strain K599. We thank the two anonymous reviewers for their critical and highly valuable comments. This research was supported by the National Natural Science Foundation of China (31301336), the Science and Technology Innovation Talents Projects of the Education Department of Henan Province (15HASTIT034) and China Postdoctoral Science Foundation (2015M580630).
Author contributions
DZ, HZ conceived and designed the experiments. DZ, SC, HL, and YC performed the experiments. DZ and HZ performed data analyses. DZ and HZ wrote the manuscript. DT and DY contributed reagents, materials or analysis tools. All authors read and approved the final version of the manuscript to be published.
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Dan Zhang and Hengyou Zhang have contributed equally to this work.
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Zhang, D., Zhang, H., Chu, S. et al. Integrating QTL mapping and transcriptomics identifies candidate genes underlying QTLs associated with soybean tolerance to low-phosphorus stress. Plant Mol Biol 93, 137–150 (2017). https://doi.org/10.1007/s11103-016-0552-x
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DOI: https://doi.org/10.1007/s11103-016-0552-x