Identification of Genetic Loci Associated With Crude Protein Content and Fiber Composition in Alfalfa (Medicago sativa L.) Using QTL Mapping

Overexpression of MsDREB1C Modulates Growth and Improves Forage Quality in Tetraploid Alfalfa (Medicago sativa L.)

DREB has been reported to be involved in plant growth and response to environmental factors. However, the function of DREB in growth and development has not been elucidated in alfalfa (Medicago sativa L.), a perennial tetraploid forage cultivated worldwide. In this study, an ortholog of MtDREB1C was characterized from alfalfa and named MsDREB1C accordingly. MsDREB1C was significantly induced by abiotic stress. The transcription factor MsDREB1C resided in the nucleus and had self-transactivation activity. The MsDREB1C overexpression (OE) alfalfa displayed growth retardation under both long-day and short-day conditions, which was supported by decreased MsGA20ox and upregulated MsGA2ox in the OE lines. Consistently, a decrease in active gibberellin (GA) was detected, suggesting a negative effect of MsDREB1C on GA accumulation in alfalfa. Interestingly, the forage quality of the OE lines was better than that of WT lines, with higher crude protein and lower lignin content, which was supported by an increase in the leaf-stem ratio (LSR) and repression of several lignin-synthesis genes (MsNST, MsPAL1, MsC4H, and Ms4CL). Therefore, this study revealed the effects of MsDREB1C overexpression on growth and forage quality via modifying GA accumulation and lignin synthesis, respectively. Our findings provide a valuable candidate for improving the critical agronomic traits of alfalfa, such as overwintering and feeding value of the forage.

Shoots

BACKGROUND

Brassica napus is one of the most important oil crops in the world, and B. napus shoots are nutrient-rich fresh vegetables. The crude fiber (CF) component is one of the most important factors affecting the taste quality of B. napus shoots, but the factors underlying the desirable low-CF trait remain poorly understood.

METHODS

In this study, a high-density single-nucleotide polymorphism (SNP) map was used to map quantitative trait loci (QTLs) for five CF-related traits in a recombinant inbred population.

RESULTS

A total of 49 QTLs were obtained in four environments, including eleven, twelve, eight, twelve and six QTLs for content of neutral detergent fiber, acid detergent fiber, acid detergent lignin, hemicellulose and cellulose, respectively. The phenotypic variation explained by single QTL ranged from 4.62% to 14.76%. Eight of these QTLs were further integrated into four unique QTLs, which controlled two different traits simultaneously. Five CF-component-related candidate genes were identified, among which BnaC03g07110D and BnaC07g21271D were considered to be the most likely candidate genes. In addition, five lines with low CF content were selected, which can be used as excellent germplasm resources in breeding.

CONCLUSIONS

The QTLs identified in this study will contribute to our understanding of the genetic mechanism of CF and can be used as targets for reducing CF content in B. napus shoots. In addition, this study also provided excellent germplasm resources for low CF content breeding.

Identification of QTL and candidate genes associated with biomass yield and Feed Quality in response to water deficit in alfalfa (Medicago sativa L.) using linkage mapping and RNA-Seq

Biomass yield and Feed Quality are the most important traits in alfalfa (Medicago sativa L.), which directly affect its economic value. Drought stress is one of the main limiting factors affecting alfalfa production worldwide. However, the genetic and especially the molecular mechanisms for drought tolerance in alfalfa are poorly understood. In this study, linkage mapping was performed in an F1 population by combining 12 phenotypic data (biomass yield, plant height, and 10 Feed Quality-related traits). A total of 48 significant QTLs were identified on the high-density genetic linkage maps that were constructed in our previous study. Among them, nine main QTLs, which explained more than 10% phenotypic variance, were detected for biomass yield (one), plant height (one), CP (two), ASH (one), P (two), K(one), and Mg (one). A total of 31 candidate genes were identified in the nine main QTL intervals based on the RNA-seq analysis under the drought condition. Blast-P was further performed to screen candidate genes controlling drought tolerance, and 22 functional protein candidates were finally identified. The results of the present study will be useful for improving drought tolerance of alfalfa varieties by marker-assisted selection (MAS), and provide promising candidates for further gene cloning and mechanism study.

Distinct rhizosphere soil responses to nitrogen in relation to microbial biomass and community composition at initial flowering stages of alfalfa cultivars

In the long-term growth process, alfalfa rhizosphere forms specific microbiome to provide nutrition for its growth and development. However, the effects of different perennial alfalfa cultivars on changes in the rhizosphere soil characteristics and microbiome are not well understood. In this study, 12 perennial alfalfa cultivars were grown continuously for eight years. Rhizosphere samples were tested using Illumina sequencing of the 16S rRNA gene coupled with co-occurrence network analysis to explore the relationship between alfalfa (biomass and crude protein content), soil properties, and the microbial composition and diversity. Redundancy analysis showed SOC and pH had the greatest impact on the composition of the rhizosphere microbial community. Moreover, microbial diversity also contributes to microbial composition. Soil properties (AP, EC, SOC and pH) exhibited a significant positive correlation with soil bacterial communities, which was attributed to the differences between plant cultivars. Partial least squares path modeling (PLS-PM) revealed that microbial biomass and community composition rather than diversity, are the dominant determinants in the rhizosphere soil nitrogen content of perennial alfalfa. Our findings demonstrate that the soil microbial biomass and composition of rhizosphere bacterial communities are strongly affected by cultivar, driving the changes in soil nitrogen content, and variances in the selective capacities of plants.

Genome-Wide Association Study of Six Forage Traits in Ramie (Boehmeria nivea L. Gaud)

Genome-wide association study (GWAS) of six forage traits using whole-genome sequencing data generated from 301 ramie accessions found that traits were continuously distributed; the maximum variant coefficient was fresh weight per clump (FWPC) (2019) and individual plant height (IPH) (2019) minimum. Correlation analysis demonstrated that 2019 and 2020 results were similar; all traits were correlated. GWAS analysis demonstrated that six traits exhibited consistent and precise association signals. Of the latter, 104 were significant and detected in 43 genomic regions. By screening forage trait-associated single nucleotide polymorphisms and combining Manhattan map with genome annotation, signals were categorized according to functional annotations. One loci associated with fresh weight per plant (FWP) (chromosome 5; Bnt05G007759), two associated with FWPC (chromosome 13; Bnt13G018582, and Bnt13G018583), and two associated with leaf dry weight per plant (LDWP) and dry weight per plant (DWP) (chromosome 4; Bnt04G005779 and Bnt04G005780), were identified. We describe forage trait candidate genes that are highly correlated with FWP and FWPC; Bnt05G007759 may be involved in nitrogen metabolism, while Bnt13G018582 and Bnt13G018583 may encode TEOSINTE branch 1/CYCLOIDEA/proliferating cytokine 1 (TCP) domains. Bnt04G005779 and Bnt04G005780, which may regulate growth and development, are highly related to LDWP and DWP. These genomic resources will provide a basis for breeding varieties.