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Integrating QTL mapping and transcriptomics identifies candidate genes underlying QTLs associated with soybean tolerance to low-phosphorus stress.

Authors
  • Zhang, Dan1
  • Zhang, Hengyou2
  • Chu, Shanshan3
  • Li, Hongyan3
  • Chi, Yingjun4
  • Triebwasser-Freese, Daniella2
  • Lv, Haiyan3
  • Yu, Deyue4
  • 1 Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, 95 Wenhua Road, Zhengzhou, 450002, Henan Province, People's Republic of China. [email protected] , (China)
  • 2 Department of Biological Sciences, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223-0001, USA.
  • 3 Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, 95 Wenhua Road, Zhengzhou, 450002, Henan Province, People's Republic of China. , (China)
  • 4 National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, No. 1 Weigang, Nanjing, 210095, Jiangsu, People's Republic of China. , (China)
Type
Published Article
Journal
Plant molecular biology
Publication Date
Jan 01, 2017
Volume
93
Issue
1-2
Pages
137–150
Identifiers
DOI: 10.1007/s11103-016-0552-x
PMID: 27815671
Source
Medline
Keywords
License
Unknown

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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