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Direct introgression of untapped diversity into elite wheat lines


The effective utilization of natural variation has become essential in addressing the challenges that climate change and population growth pose to global food security. Currently adopted protracted approaches to introgress exotic alleles into elite cultivars need substantial transformation. Here, through a strategic three-way crossing scheme among diverse exotics and the best historical elites (exotic/elite1//elite2), 2,867 pre-breeding lines were developed, genotyped and screened for multiple agronomic traits in four mega-environments. A meta-genome-wide association study, selective sweeps and haplotype-block-based analyses unveiled selection footprints in the genomes of pre-breeding lines as well as exotic-specific associations with agronomic traits. A simulation with a neutrality assumption demonstrated that many pre-breeding lines had significant exotic contributions despite substantial selection bias towards elite genomes. National breeding programmes worldwide have adopted 95 lines for germplasm enhancement, and 7 additional lines are being advanced in varietal release trials. This study presents a great leap forwards in the mobilization of GenBank variation to the breeding pipelines.

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Fig. 1: Simulation of the pre-breeding germplasm.
Fig. 2: Meta-GWAS and selective sweep results.

Data availability

All data used in the present study are provided in the supplementary files and on GitHub at Source data are provided with this paper.

Code availability

All codes used in the present study can be found at


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We acknowledge the Seeds of Discovery project of CIMMYT and the directors of the Genetic Resources Program, as well as the Global Wheat Program, for their valuable support and encouragement of the team. We acknowledge the financial support received from the Secretariat of Agriculture and Rural Development. We thank R. Singh, M. Ellis and T. Payne, who provided seeds of elite and exotic germplasm lines. We also thank Punjab Agricultural University, Ludhiana; ICAR-IIWBR, Karnal; and CSKHP Palampur, India, for providing valuable support in conducting phenotypic evaluation of the pre-breeding germplasm. We also thank IFS, Sweden, for grant number C-5897-I for phenotyping at the Nuclear Institute for Agriculture and Biology. We acknowledge the direct and indirect support of researchers and non-scientific staff. We thank C. J. Vander Jagt (Agriculture Victoria, Australia) for editing the manuscript.

Author information

Authors and Affiliations



Sukhwinder Singh, P.V. and P.W. conceived and designed the experiments. Sukhwinder Singh, A.J. and D.S. planned the structure of the paper. A.S., S.K.S., K.A.L., Sanjay Singh, M.A.R.A., D.B., A.K.B., N.P., Sukhwinder Singh and P.V. conducted the traits evaluation. C.P.S., P.V., N.P. and Sukhwinder Singh did the genotyping. J.B., Sukhwinder Singh, N.P. and P.V. conducted the experimental design and field data analysis. A.J. carried out the GGE, genetic correlation and simulation analyses. R.J. conducted the exotic contribution, meta-GWAS and selective sweep analyses. D.S. and Sukhwinder Singh conducted the haplotype detection and haplotype-based GWAS. Sukhwinder Singh, A.J., D.S., J.B. and R.J. interpreted the results. Sukhwinder Singh, A.J., D.S., R.J., J.B., A.S., S.K.S., N.S.B. and H.K.C. prepared the manuscript. All authors read and approved the final version of manuscript.

Corresponding author

Correspondence to Sukhwinder Singh.

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The authors declare no competing interests.

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Peer review information Nature Food thanks Xuehui Huang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–9.

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Supplementary Tables

Supplementary Tables 1–20.

Source data

Source Data Fig. 1

Statistical analysis. Sheet ‘LD’ contains the LD decay results for empirical and simulated PBLs with Syn and LR backgrounds used for Fig. 1a. Sheet ‘Contribution’ contains the percentage of the exotic parent contribution to each PBL used for Fig. 1b,c.

Source Data Fig. 2

Statistical analysis (−log10(P) for SNPs) for SL, PH, YLD and Fe as well as iHS scores.

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Singh, S., Jighly, A., Sehgal, D. et al. Direct introgression of untapped diversity into elite wheat lines. Nat Food 2, 819–827 (2021).

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