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From model to crop: functional characterization of SPL8 in M. truncatula led to genetic improvement of biomass yield and abiotic stress tolerance in alfalfa.

ABSTRACT: Biomass yield, salt tolerance and drought tolerance are important targets for alfalfa (Medicago sativa L.) improvement. Medicago truncatula has been developed into a model plant for alfalfa and other legumes. By screening a Tnt1 retrotransposon-tagged M. truncatula mutant population, we identified three mutants with enhanced branching. Branch development determines shoot architecture which affects important plant functions such as light acquisition, resource use and ultimately impacts biomass production. Molecular analyses revealed that the mutations were caused by Tnt1 insertions in the SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 8 (SPL8) gene. The M. truncatula spl8 mutants had increased biomass yield, while overexpression of SPL8 in M. truncatula suppressed branching and reduced biomass yield. Scanning electron microscopy (SEM) analysis showed that SPL8 inhibited branching by directly suppressing axillary bud formation. Based on the M. truncatula SPL8 sequence, alfalfa SPL8 (MsSPL8) was cloned and transgenic alfalfa plants were produced. MsSPL8 down-regulated or up-regulated alfalfa plants exhibited similar phenotypes to the M. truncatula mutants or overexpression lines, respectively. Specifically, the MsSPL8 down-regulated alfalfa plants showed up to 43% increase in biomass yield in the first harvest. The impact was even more prominent in the second harvest, with up to 86% increase in biomass production compared to the control. Furthermore, down-regulation of MsSPL8 led to enhanced salt and drought tolerance in transgenic alfalfa. Results from this research offer a valuable approach to simultaneously improve biomass production and abiotic stress tolerance in legumes.

SUBMITTER: Gou J

PROVIDER: S-EPMC5866946 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Genomic selection based on genotyping-by-sequencing (GBS) data could accelerate alfalfa yield gains, if it displayed moderate ability to predict parent breeding values. Its interest would be enhanced by predicting ability also for germplasm/reference populations other than those for which it was defined. Predicting accuracy may be influenced by statistical models, SNP calling procedures and missing data imputation strategies.Landrace and variety material from two genetically-contrasting reference populations, i.e., 124 elite genotypes adapted to the Po Valley (sub-continental climate; PV population) and 154 genotypes adapted to Mediterranean-climate environments (Me population), were genotyped by GBS and phenotyped in separate environments for dry matter yield of their dense-planted half-sib progenies. Both populations showed no sub-population genetic structure. Predictive accuracy was higher by joint rather than separate SNP calling for the two data sets, and using random forest imputation of missing data. Highest accuracy was obtained using Support Vector Regression (SVR) for PV, and Ridge Regression BLUP and SVR for Me germplasm. Bayesian methods (Bayes A, Bayes B and Bayesian Lasso) tended to be less accurate. Random Forest Regression was the least accurate model. Accuracy attained about 0.35 for Me in the range of 0.30-0.50 missing data, and 0.32 for PV at 0.50 missing data, using at least 10,000 SNP markers. Cross-population predictions based on a smaller subset of common SNPs implied a relative loss of accuracy of about 25% for Me and 30% for PV. Genome-wide association analyses based on large subsets of M. truncatula-aligned markers revealed many SNPs with modest association with yield, and some genome areas hosting putative QTLs. A comparison of genomic vs. conventional selection for parent breeding value assuming 1-year vs. 5-year selection cycles, respectively, indicated over three-fold greater predicted yield gain per unit time for genomic selection.Genomic selection for alfalfa yield is promising, based on its moderate prediction accuracy, moderate value of cross-population predictions, and lack of sub-population structure. There is limited scope for searching individual QTLs with overwhelming effect on yield. Some of our results can contribute to better design of genomic selection experiments for alfalfa and other crops with similar mating systems.

Dataset Information

From model to crop: functional characterization of SPL8 in M. truncatula led to genetic improvement of biomass yield and abiotic stress tolerance in alfalfa.

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