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Published on: May 1, 2014
Harnessing cytonuclear diversity to map barley spike traits using the cytonuclear multi-parent population
Schewach Bodenheimer1,2, Eyal Bdolach1,3, Avital Be'ery1
1The Institute of Plant Sciences, Agricultural Research Organization, Volcani Center, Rishon LeZion 7505101, Israel.
None:
The interplay between nuclear and cytoplasmic genomes, collectively known as cytonuclear interactions (CNIs), is increasingly recognized as a key driver of phenotypic variation and adaptive potential across diverse organisms. Yet, leveraging cytoplasmic diversity and fully understanding the role of CNIs in agriculturally important traits remain major challenges in crop improvement. Here, we present the Cytonuclear Multi-Parent Population (CMPP), a novel interspecific resource comprising 951 doubled haploid lines, generated from 2 backcrosses between ten genetically diverse wild barley accessions (Hordeum vulgare ssp. spontaneum) used as female founders and the elite cultivar Noga (H. vulgare). Phenotyping across multiple environments revealed that up to 5% of variation in key spike and grain trait values are explained by cytoplasm (η2 = 0.05). Notably, wild cytoplasms influenced trait stability, with the B1K-50-04 cytoplasm increasing grain weight stability based on Shukla's measure. Genome-wide association studies employing Nested Association Mapping (NAM), FASTmrMLM, and MatrixEpistasis (ME) identified 76 marker-trait associations (MTAs). The ME approach specifically uncovered 16 cytonuclear QTL (cnQTL) exhibiting cytoplasm-dependent effects. Furthermore, we developed a genomic prediction strategy incorporating interactions between significant MTAs and population structure variables (subfamily and cytoplasm), which achieved cross-validation accuracies comparable to, or even exceeding, models using the full set of 6,679 SNPs, despite utilizing substantially fewer predictors, enabling quicker and more efficient validation runs. The CMPP provides a unique platform for dissecting cytoplasmic effects and CNIs, highlighting the importance of incorporating cytonuclear context in genetic mapping and prediction to effectively harness both nuclear and cytoplasmic diversity for crop improvement.
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