Crop Journal (Jun 2021)

Breeding by selective introgression: Theory, practices, and lessons learned from rice

  • Fan Zhang,
  • Yingyao Shi,
  • Jauhar Ali,
  • Jianlong Xu,
  • Zhikang Li

Journal volume & issue
Vol. 9, no. 3
pp. 646 – 657

Abstract

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Future demands for increased productivity and resilience to abiotic/biotic stresses of major crops require new technologies of breeding by design (BBD) built on massive information from functional and population genomics research. A novel strategy of breeding by selective introgression (BBSI) has been proposed and practiced for simultaneous improvement, genetic dissection and allele mining of complex traits to realize BBD. BBSI has three phases: a) developing large numbers of trait-specific introgression lines (ILs) using backcross breeding in elite genetic backgrounds as the material platform of BBD; b) efficiently identifying genes or quantitative trait loci (QTL) and mining desirable alleles affecting different target traits from diverse donors as the information platform of BBD; and c) developing superior cultivars by BBD using designed QTL pyramiding or marker-assisted recurrent selection. Phase (a) has been implemented massively in rice by many Chinese research institutions and IRRI, resulting in the development of many new green super rice cultivars plus large numbers of ILs in 30 + elite genetic backgrounds. Phase (b) has been demonstrated in a series of proof-of-concept studies of high-efficiency genetic dissection of rice yield and tolerance to abiotic stresses using ILs and DNA markers. Phase (c) has also been implemented by designed QTL pyramiding, resulting in a prototype of BBD in several successful cases. The BBSI strategy can be easily extended for simultaneous trait improvement, efficient gene and QTL discovery and allele mining of complex traits using advanced breeding lines from crosses between a common “backbone” parent and a set of elite parents in conventional pedigree breeding programs. BBSI can be relatively easily adopted by breeding programs with small budgets, but the BBSI-based BBD strategy can be fully and more efficiently implemented by large seed companies with sufficient capacity.

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