Biodiversity and biogeography of rhizobia associated with soybean plants grown in the North China Plain

Abstract

As the putative center of origin for soybean and the second largest region of soybean production in China, the North China Plain covers temperate and subtropical regions with diverse soil characteristics. However, the soybean rhizobia in this plain have not been sufficiently studied. To investigate the biodiversity and biogeography of soybean rhizobia in this plain, a total of 309 isolates of symbiotic bacteria from the soybean nodules collected from 16 sampling sites were studied by molecular characterization. These isolates were classified into 10 genospecies belonging to the genera Sinorhizobium and Bradyrhizobium, including four novel groups, with S. fredii (68.28%) as the dominant group. The phylogeny of symbiotic genes nodC and nifH defined four lineages among the isolates associated with Sinorhizobium fredii, Bradyrhizobium elkanii, B. japonicum, and B. yuanmingense, demonstrating the different origins of symbiotic genes and their coevolution with the chromosome. The possible lateral transfer of symbiotic genes was detected in several cases. The association between soil factors (available N, P, and K and pH) and the distribution of genospecies suggest clear biogeographic patterns: Sinorhizobium spp. were superdominant in sampling sites with alkaline-saline soils, while Bradyrhizobium spp. were more abundant in neutral soils. This study clarified the biodiversity and biogeography of soybean rhizobia in the North China Plain.

Fig. 1.

Map of the Huang-Huai-Hai (HHH) Plain showing the sampling sites (•). ★, Capital of China, Beijing. The corresponding position of the HHH Plain in China is shown in the inset. The two maps were created using DIVA-GIS software (http//www.diva-gis.org), and the sampling sites were added according to GPS records.

Fig. 2.

Phylogenetic tree of 16S rRNA gene sequences showing the relationships between the representative isolates (in boldface) and the reference strains for defined rhizobial species. GenBank accession numbers in boldface were newly determined as a result of this study. The neighbor-joining (NJ) tree was derived from a 16S rRNA gene sequence distance matrix (Kimura two parameter). Bootstrap confidence levels of ≥50% are indicated at the internodes. The scale bar represents 1% nucleotide substitutions.

Fig. 3.

Phylogenetic tree of MLSA based on concatenated sequences of recA (375 nucleotides [nt]), glnII (519 nt), and atpD (359 nt). Taxa and GenBank accesion numbers in boldface were newly determined as a result of this study. Bootstrap confidence levels of ≥50% are indicated at the internodes. The bar indicates 2% nucleotide divergence.

Fig. 4.

Phylogenetic tree of nodC (A) and nifH (B) gene sequences showing the relationships between the representative strains (in boldface) and the related rhizobial species. GenBank accession numbers in boldface were newly determined as a result of this study. The neighbor-joining dendrograms were derived from a sequence distance matrix (Kimura two parameter). Bootstrap confidence levels of ≥50% are indicated at the internodes. Scale bars represent 5 or 2% nucleotide divergence.

Fig. 4.

Phylogenetic tree of nodC (A) and nifH (B) gene sequences showing the relationships between the representative strains (in boldface) and the related rhizobial species. GenBank accession numbers in boldface were newly determined as a result of this study. The neighbor-joining dendrograms were derived from a sequence distance matrix (Kimura two parameter). Bootstrap confidence levels of ≥50% are indicated at the internodes. Scale bars represent 5 or 2% nucleotide divergence.

Fig. 5.

Influence of soil pH in different sampling sites of the HHH Plain on the distribution and relative abundance of Sinorhizobium and Bradyrhizobium associated with soybean.

Fig. 6.

Biplot of the RDA on the 10 genospecies and their soil factors from sampling sites in the HHH Plain by CANOCO. A_N, available N; A_P, available P; A_K, available K. Canonical correspondence analyses (CCA) were used to evaluate influence. The longer the arrow is, the greater the influence it has; the smaller the angle is between two arrows, the closer their relationship.