Genomics-assisted prediction of salt and alkali tolerances and functional marker development in apple rootstocks

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Abstract

Background: Saline, alkaline, and saline-alkaline stress severely affect plant growth and development. The tolerance of plants to these stressors has long been important breeding objectives, especially for woody perennials like apple. The aims of this study were to identify quantitative trait loci (QTLs) and to develop genomics-assisted prediction models for salt, alkali, and salt-alkali tolerance in apple rootstock. Results: A total of 3258 hybrids derived from the apple rootstock cultivars 'Baleng Crab' (Malus robusta Rehd., tolerant) × 'M9' (M. pumila Mill., sensitive) were used to identify 17, 13, and two QTLs for injury indices of salt, alkali, and salt-alkali stress via bulked segregant analysis. The genotype effects of single nucleotide polymorphism (SNP) markers designed on candidate genes in each QTL interval were estimated. The genomic predicted value of an individual hybrid was calculated by adding the sum of all marker genotype effects to the mean phenotype value of the population. The prediction accuracy was 0.6569, 0.6695, and 0.5834 for injury indices of salt, alkali, and salt-alkali stress, respectively. SNP182G on MdRGLG3, which changes a leucine to an arginine at the vWFA-domain, conferred tolerance to salt, alkali, and salt-alkali stress. SNP761A on MdKCAB, affecting the Kv_beta domain that cooperated with the linked allelic variation SNP11, contributed to salt, alkali, and salt-alkali tolerance in apple rootstock. Conclusions: The genomics-assisted prediction models can potentially be used in breeding saline, alkaline, and saline-alkaline tolerant apple rootstocks. The QTLs and the functional markers may provide insight for future studies into the genetic variation of plant abiotic stress tolerance.

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Liu, J., Shen, F., Xiao, Y., Fang, H., Qiu, C., Li, W., … Han, Z. (2020). Genomics-assisted prediction of salt and alkali tolerances and functional marker development in apple rootstocks. BMC Genomics, 21(1). https://doi.org/10.1186/s12864-020-06961-9

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