Plant transcriptome analysis reveals specific molecular interactions between alfalfa and its rhizobial symbionts below the species level

Abstract

Background: Leguminous plants alter patterns of gene expression in response to symbiotic colonization and infection by their cognate rhizobial bacteria, but the extent of the transcriptomic response has rarely been examined below the species level. Here we describe the identification of 12 rhizobial biotypes of Ensifer meliloti, which form nitrogen-fixing nodules in the roots of alfalfa (Medicago sativa L.), followed by a comparative RNA-seq analysis of four alfalfa cultivars each inoculated with two E. meliloti strains varying in symbiotic performance and phylogenetic relatedness. Results: Rhizobial biotypes were identified on the basis of their symbiotic performance, particularly shoot dry weight. Differentially expressed genes (DEGs) and metabolic pathways were determined by comparing the RNA-seq data with that of the uninoculated control plant. Significant differences were found between DEGs generated in each cultivar with the inoculation of two rhizobial strains in comparison (P < 0.01). A total of 8111 genes was differentially expressed, representing~17.1% of the M. sativa genome. The proportion of DEGs ranges from 0.5 to 12.2% for each alfalfa cultivar. Interestingly, genes with predicted roles in flavonoid biosynthesis and plant-pathogen interaction (NBS-LRR) were identified as the most significant DEGs. Other DEGs include Medsa002106 and genes encoding nodulins and NCR peptides whose expression is specifically induced during the development of nitrogenfixing nodules. More importantly, strong significant positive correlations were observed between plant transcriptomes (DEGs and KEGG pathways) and phylogenetic distances between the two rhizobial inoculants. Conclusions: Alfalfa expresses significantly distinct sets of genes in response to infection by different rhizobial strains at the below-species levels (i.e. biotype or strain). Candidate genes underlying the specific interactions include Medsa002106 and those encoding nodulins and NCR peptides and proteins in the NBS-LRR family.

Why Should Nodule Cysteine-Rich (NCR) Peptides Be Absent From Nodules of Some Groups of Legumes but Essential for Symbiotic N-Fixation in Others?

“…Rhizobial-specific nitrogen fixation appears to be common among different accessions of M. truncatula (Liu et al, 2014) and discrimination between some rhizobial strains can be attributed directly to the presence of specific NCR genes (Wang et al, 2017(Wang et al, , 2018Yang et al, 2017). As observed in alfalfa and M. truncatula, different NCRs can be induced by different rhizobial strains (Burghardt et al, 2017;Kang et al, 2020). Mutation of some NCR genes conferred nitrogen fixation on a strain that was unable to fix nitrogen in plants carrying the NCR gene.…”

Legume tasters: symbiotic rhizobia host preference and smart inoculant formulations

“…Modification of the plant-associated microbiome (mainly, but not only, involving PGPR) has an effective potential to improve plant yield and resistance to biotic and abiotic stresses; this potential is stirring the attention of many investigators (Turner et al, 2013). This approach of "microbiome engineering" is based on reconstructing synthetic microbial communities after laboratory selection of microbes with the best ability to deliver PGP traits to the plants (Ke et al, 2020). The principal aims of microbiome manipulation are to: 1) reduce the incidence of plant diseases (Malfanova, 2013) ; 2) increase agricultural production (Bakker et al, 2012); 3) reduce chemical inputs (Adesemoye et al, 2009) and 4) reduce emissions of greenhouse gases (Singh et al, 2010).…”

De novo hydroponics system efficiency for the cuttings of alfalfa (Medicago sativa L.)

“…Alfalfa with 25–75% natural outcrossing rate results in the same variety producing contaminated seeds may the breeding lines. Previous studies (Cong et al 2017a , b ; Cui et al 2020 ; Kang et al 2020 ; Xiong et al 2020 ) on alfalfa proteomics, transcriptomics, and gene mining experiments used variety as source material with diverse genetic backgrounds, and such a mixed genotype will affect the accuracy of bioinformatics analysis and gene mining. However, the primary benefit of cuttings is that all offspring are genetically/ phenotypically similar clones as like maternal source.…”