Dataset Information

Improvement of alfalfa forage quality and management through the down-regulation of MsFTa1.

ABSTRACT: Alfalfa (Medicago sativa L.) is one of the most important forage crops worldwide. As a perennial, alfalfa is cut several times each year. Farmers face a dilemma: if cut earlier, forage nutritive value is much higher but regrowth is affected and the longevity of the stand is severely compromised. On the other hand, if alfalfa is cut later at full flower, stands persist longer and more biomass may be harvested, but the nutritive value diminishes. Alfalfa is a strict long-day plant. We reasoned that by manipulating the response to photoperiod, we could delay flowering to improve forage quality and widen each harvesting window, facilitating management. With this aim, we functionally characterized the FLOWERING LOCUS T family of genes, represented by five members: MsFTa1, MsFTa2, MsFTb1, MsFTb2 and MsFTc. The expression of MsFTa1 correlated with photoperiodic flowering and its down-regulation led to severe delayed flowering. Altogether, with late flowering, low expression of MsFTa1 led to changes in plant architecture resulting in increased leaf to stem biomass ratios and forage digestibility. By manipulating photoperiodic flowering, we were able to improve the quality of alfalfa forage and management, which may allow farmers to cut alfalfa of high nutritive value without compromising stand persistence.

SUBMITTER: Lorenzo CD

PROVIDER: S-EPMC7061867 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Improvement of alfalfa forage quality and management through the down-regulation of MsFTa1.

Lorenzo Christian D CD García-Gagliardi Pedro P Antonietti Mariana S MS Sánchez-Lamas Maximiliano M Mancini Estefanía E Dezar Carlos A CA Vazquez Martin M Watson Gerónimo G Yanovsky Marcelo J MJ Cerdán Pablo D PD

Plant biotechnology journal 20191013 4

Alfalfa (Medicago sativa L.) is one of the most important forage crops worldwide. As a perennial, alfalfa is cut several times each year. Farmers face a dilemma: if cut earlier, forage nutritive value is much higher but regrowth is affected and the longevity of the stand is severely compromised. On the other hand, if alfalfa is cut later at full flower, stands persist longer and more biomass may be harvested, but the nutritive value diminishes. Alfalfa is a strict long-day plant. We reasoned tha ...[more]

PMID: 31536663

Similar Datasets

Project description:Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3-0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits (by genomic selection or MAS) and forage yield.

Dataset Information

Improvement of alfalfa forage quality and management through the down-regulation of MsFTa1.

Publications

Improvement of alfalfa forage quality and management through the down-regulation of MsFTa1.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets