Genome-wide association and prediction of traits related to salt tolerance in autotetraploid alfalfa (Medicago sativa l.)

Cesar Augusto Medina, Charles Hawkins, Xiang Ping Liu, Michael Peel, Long Xi Yu

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17 Scopus citations


Soil salinity is a growing problem in world production agriculture. Continued improvement in crop salt tolerance will require the implementation of innovative breeding strategies such as marker-assisted selection (MAS) and genomic selection (GS). Genetic analyses for yield and vigor traits under salt stress in alfalfa breeding populations with three different phenotypic datasets was assessed. Genotype-by-sequencing (GBS) developed markers with allele dosage and phenotypic data were analyzed by genome-wide association studies (GWAS) and GS using different models. GWAS identified 27 single nucleotide polymorphism (SNP) markers associated with salt tolerance. Mapping SNPs markers against the Medicago truncatula reference genome revealed several putative candidate genes based on their roles in response to salt stress. Additionally, eight GS models were used to estimate breeding values of the training population under salt stress. Highest prediction accuracies and root mean square errors were used to determine the best prediction model. The machine learning methods (support vector machine and random forest) performance best with the prediction accuracy of 0.793 for yield. The marker loci and candidate genes identified, along with optimized GS prediction models, were shown to be useful in improvement of alfalfa with enhanced salt tolerance. DNA markers and the outcome of the GS will be made available to the alfalfa breeding community in efforts to accelerate genetic gains, in the development of biotic stress tolerant and more productive modern-day alfalfa cultivars.

Original languageEnglish (US)
Article number3361
JournalInternational journal of molecular sciences
Issue number9
StatePublished - May 1 2020
Externally publishedYes

Bibliographical note

Funding Information:
Funding: This research was funded by The United State Department of Agriculture National Institute of Food and Agriculture, grant Number 2015-70005-24071.

Funding Information:
Acknowledgments: The authors would like to acknowledge Brian Irish and Max Feldman for internal review of the manuscript, Martha Rivera for technical help. They would further like to thank USDA-NIFA for funding support (2015-70005-24071).

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.


  • Abiotic stress
  • Allele dosage
  • Association mapping
  • GBS
  • Genomic selection
  • Polyploid


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