Stacking for success: enhancing chickpea yield with superior haplotypes

Chickpea (Cicer arietinum L.) plays a vital role in food systems and sustainable agriculture, but its genetic improvement has been hindered by a narrow cultivated gene pool and limited integration of modern genomic tools. This restricted diversity limits the opportunities for breeding chickpea varieties more resilient to biotic and abiotic stresses. The germplasm maintained by the International Center for Agricultural Research in the Dry Areas (ICARDA) offers a valuable reservoir of haplotype diversity that can drive genetic gain when effectively harnessed through genomics-enabled breeding strategies. In this study, we developed a haplotype catalogue with 289 diverse ICARDA chickpea accessions by combining high-density genotyping with yield phenotypic data. Linkage disequilibrium haploblocks were defined based on recombination patterns observed in the genotyping data. Each haplotype, defined by SNP combinations within a block, was assigned a local genomic estimated breeding value (localGEBV) based on the sum of SNP effect estimates. We investigated haploblocks with high variance for haplotype effect across the genome, and targeted superior haplotypes with strong, positive effect on yield. Using AI-guided parent selection and simulation-based haplotype stacking, we investigated optimal parental combinations and crossing pathways to accumulate favourable haplotypes for yield improvement that can outperform traditionnal selection strategies while maintaining genetic diversity. This approach provides a practical support tool for ICARDA and Australian breeders to develop high performing chickpea lines. The discovery of superior haplotypes within ICARDAs' germplasm can also benefit other breeding programs by enriching their genetic base with valuable and novel diversity