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作物学报 ›› 2021, Vol. 47 ›› Issue (9): 1690-1702.doi: 10.3724/SP.J.1006.2021.04137

• 研究论文 • 上一篇    下一篇

涝害对不同大豆品种根际微生物群落结构特征的影响

禹桃兵(), 石琪晗, 年海*(), 连腾祥*()   

  1. 华南农业大学农学院 / 国家大豆改良中心广东分中心, 广东广州 510642
  • 收稿日期:2020-06-23 接受日期:2020-09-13 出版日期:2021-09-12 网络出版日期:2020-09-22
  • 通讯作者: 年海,连腾祥
  • 作者简介:E-mail: 277885643@qq.com
  • 基金资助:
    国家重点研发计划项目“大田经济作物优质丰产的生理基础与调控”(2018YFD1000900)

Effects of waterlogging on rhizosphere microorganisms communities of different soybean varieties

YU Tao-Bing(), SHI Qi-Han, NIAN-Hai *(), LIAN Teng-Xiang*()   

  1. College of Agriculture, South China Agricultural University / Guangdong Subcenter of National Soybean Improvement Center, Guangzhou 510642, Guangdong, China
  • Received:2020-06-23 Accepted:2020-09-13 Published:2021-09-12 Published online:2020-09-22
  • Contact: NIAN-Hai ,LIAN Teng-Xiang
  • Supported by:
    National Key Research and Development Program of China “Physiological Basis and Agronomic Management for High-quality and High-yield of Field Cash Crops”(2018YFD1000900)

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摘要：

淹水影响不同大豆品种根际微生物群落组成, 不同基因型大豆植株耐涝性差异较大。本研究选取耐涝(waterlogging-tolerant, W-T)基因型大豆齐黄34和涝害敏感(waterlogging-sensitive, W-S)基因型大豆冀豆17为材料, 采用荧光定量PCR、Illumina MiSeq高通量测序技术, 分析了不同淹水时间下2个基因型根际细菌多样性、群落组成和网络特征。结果表明, 耐涝基因型大豆的生物量和细菌丰度明显高于涝害敏感基因型大豆。主坐标分析(PCoA)表明, 耐涝基因型与敏感基因型大豆微生物群落组成的差异随淹水时间的增加而变化(P< 0.05)。在淹水条件下, 耐涝基因型大豆富集了Yonghaparkia属和Unclassified-WD2101属以及OTU274 (Clostridium)和OTU2334 (Desulfosporosinus)等物种, 这些细菌的富集可能与耐涝性有关, 本研究提供了大豆根际微生物抗涝潜力的证据。

关键词: 大豆, 耐涝, 根际微生物, 16S rRNA, 网络分析

Abstract:

Waterlogging affects the composition of rhizosphere microbial community of different soybean varieties. The tolerance of soybean plant with different genotypes to waterlogging is quite different. In this study, waterlogging tolerant soybean genotype (Qihuang 34) and waterlogging sensitive soybean genotype (Jidou 17) were selected. The bacterial diversity, community composition, and network characteristics in the rhizosphere of the two genotypes under different waterlogging time were analyzed via fluorescence quantitative qPCR and Illumina Miseq high-throughput sequencing. The results showed that the biomass of waterlogging tolerant genotype and bacterial abundance in its rhizosphere were significantly higher than those for waterlogging sensitive genotype. The PCoA analysis showed that the difference in microbial community composition between waterlogging tolerant and sensitive soybean genotypes changed with waterlogging time (P < 0.05). Under the condition of waterlogging, Yonghaparkia and Unclassified-WD2101, OTU274 (Clostridium) and OTU2334 (Desulfosporosinus) enriched in the rhizosphere of the waterlogging tolerant genotype. The enrichment of these bacteria might be related to waterlogging tolerance. This study provides evidence of the microbial potential in the rhizosphere of soybean against waterlogging.

Key words: soybean, waterlogging tolerance, rhizosphere microorganism, 16S rRNA, network analysis

图1

不同淹水时长对耐涝和涝害敏感基因型大豆Chao 1丰度(a)、Shannon多样性(b)、生物量(c)和细菌丰度(d)的影响 不同字母表示相同处理下2个品种间差异显著(P< 0.05)。W-TCK; 耐涝品种淹水0 d; W-SCK: 涝害敏感品种淹水0 d; W-T1D: 耐涝品种淹水1 d; W-S1D: 涝害敏感品种淹水1 d; W-T5D: 耐涝品种淹水5 d; W-S5D: 涝害敏感品种淹水5 d。 "

图2

不同淹水时长处理下的门相对丰度 处理同图1。 "

图3

淹水时长0 d (a)、1 d (b)、5 d (c)下W-T和W-S基因型大豆根际细菌属的相对丰度 误差条表示6个重复样本的标准差。采用Benjamini-Hochberg法校正P值(P < 0.05)。处理同 图1。 "

图4

与无淹水对照相比, 不同淹水时长及大豆基因型富集和降低的OTU a: 耐涝品种淹水1 d和不淹水的对比分析; b: 耐涝品种淹水5 d和不淹水的对比分析; c: 涝害敏感品种淹水1 d和不淹水的对比分析; d: 涝害敏感品种淹水5 d和不淹水的对比分析; e: 不同淹水处理下根际土壤细菌在OTU水平的Venn分析。处理同图1。 "

图5

耐涝基因型大豆相关的OTU相对丰度 W-T: 耐涝基因型大豆; W-S: 涝害敏感基因型大豆。不同字母表示相同处理下2个品种间差异显著(P< 0.05)。处理同图1。 "

图6

不同淹水处理下的根际土壤细菌群落主坐标分析 处理同图1。 "

表1

通过变异多变量方差分析(PERMANOVA)评估大豆基因型对根际细菌群落结构的影响"

配对比较
Pairwise comparison 		统计值
F-value 		决定系数
R2 		P值
P-value
W-TCK vs. W-SCK 1.657 0.142 0.045*
W-T1D vs. W-S1D 1.970 0.165 0.003**
W-T5D vs. W-S5D 1.972 0.165 0.020*

图7

不同淹水时长和大豆基因型的根际细菌群落的共现网络结构 a: 耐涝品种淹水0 d时根际细菌网络结构; b: 涝害敏感品种淹水0 d时根际细菌网络结构; c: 耐涝品种淹水1 d时根际细菌网络结构; d: 涝害敏感品种淹水1 d时根际细菌网络结构; e: 耐涝品种淹水5 d时根际细菌网络结构; f: 涝害敏感品种淹水5 d时根际细菌网络结构。图上不同的颜色节点表示不同的门。红色连接线表示2个节点正相关, 蓝色连接线表示2个节点负相关。处理同图1。 "

表2

根际细菌网络的拓扑结构"

网络指标
Network metrics 		W-SCK W-TCK W-S1D W-T1D W-S5D W-T5D
节点数Number of nodes 81 79 79 74 89 86
边数Number of edges 338 346 536 317 521 579
正相关数Number of positive correlation 218 216 433 224 321 353
负相关数Number of negative correlations 120 130 103 93 200 226
平均路径长度Average path length 3.816 3.058 2.626 3.688 3.192 3.195
图密度Graph density 0.104 0.112 0.174 0.117 0.133 0.158
网络直径Network diameter 10 7 7 9 9 9
平均聚类系数Average clustering coefficient 0.641 0.594 0.72 0.688 0.638 0.649
平均加权度Average degree 2.301 2.931 8.219 3.459 2.723 3
连接部件Number of modules 4 4 5 5 3 3
模块化Modularity 8.518 6.313 0.613 2.164 4.412 3.709
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