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Acta Agronomica Sinica ›› 2022, Vol. 48 ›› Issue (5): 1103-1118.doi: 10.3724/SP.J.1006.2022.14055

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Transcriptome analysis of leaves responses to elevated CO2 concentration, drought and interaction conditions in soybean [Glycine max (Linn.) Merr.]

LI A-Li(), FENG Ya-Nan, LI Ping, ZHANG Dong-Sheng, ZONG Yu-Zheng, LIN Wen, HAO Xing-Yu*()   

  1. College of Agriculture, Shanxi Agricultural University, Taigu 030800, Shanxi, China
  • Received:2021-04-06 Accepted:2021-09-09 Online:2022-05-12 Published:2021-10-09
  • Contact: HAO Xing-Yu E-mail:lal19950713@126.com;haoxingyu1976@126.com
  • Supported by:
    State Key Laboratory of Integrative Sustainable Dryland Agriculture, the Shanxi Agricultural University(202105D121008-3-7);National Natural Science Foundation of China(31871517);National Natural Science Foundation of China(31971773);National Natural Science Foundation of China(31601212)

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Abstract:

Global consensus on climate warming and elevated atmospheric CO2 concentrations has increased the frequency and intensity of extreme weather events (droughts) and brought uncertainty about soybean production. In this study, the effects of elevated CO2 concentration, drought and their interaction on gene expression in soybean were elucidated by phenotypic and leaf transcriptome sequencing (RNA-seq) analysis. To provide theoretical reference for soybean breeding under the background of future climate change, we identified the regulatory pathway of CO2 affecting soybean drought tolerance. The phenotypic results showed that elevated CO2 concentration promoted the growth and alleviated the negative effects of drought stress on soybean. The results revealed that a total of 89 CO2-responsive genes were identified by transcriptome sequencing analysis. KEGG classification demonstrated that these genes were mainly involved in antioxidant metabolism (terpenoid, flavonoid, etc.), meanwhile, Functional of the specific differentially expressed gene mainly focused on cell components, growth, and development. Under drought condition, 1006 highly differentially expressed (16-fold) genes were screened out. These genes were mainly involved in various amino acid (proline, tryptophan, etc.) metabolic pathways, and almost all genes involved in protein synthesis and transport were up-regulated, indicating that there were a lot of material exchange processes in soybean leaves under drought stress. A total of 8566 differentially expressed genes, mainly involved in carbohydrate metabolism pathway, were detected under the interaction, and almost all genes related to the photosynthesis-antenna protein pathway were down-regulated, suggesting that the photosynthetic capacity of soybean was decreased under the interaction. 34 genes were found to be differentially expressed under all three conditions. These genes were mainly concentrated in antioxidant metabolism (flavonoids, glutathione, phenylpropanoids, etc.), and most of these genes were involved in the metabolism of various plant hormones and stimulus responses. The qRT-PCR results of six differentially expressed genes related to drought resistance in two soybean varieties with different genetic background showed that the RNA-seq data were accurate. In conclusion, elevated CO2 concentration could increase the relative expression levels of genes related to antioxidant metabolism, growth and development in soybean leaves. Drought stress induced the relative expression levels of genes related to amino acid metabolism and protein synthesis pathway. The photosynthetic capacity of soybean was inhibited under the interactive condition. Elevated CO2 concentration enhanced the tolerance of soybean to drought stress by regulating hormone metabolism, antioxidant (antioxidant enzyme, flavonoid, phenylpropanoid) metabolism and carbohydrate metabolism.

Key words: soybean, elevated CO2 concentration, drought, RNA-seq, differentially expressed genes

Table 1

Information of qRT-PCR primers"

基因名称
Gene ID		 GO注释
GO annotation		 引物序列
Primer sequence (5′-3′)
Actin — F: GGTGGTTCTATCTTGGCATC
R: CTTTCGCTTCAATAACCCTA
Glyma.11G155000.Wm82.a2.v1 侧根发育 Lateral root development (GO:0048527)
根毛伸长 Root hair elongation (GO:0048767)		 F: CTACTTATCCTTGCTTGTCT
R: GTTGTCTTGAACTGGTGG
Glyma.19G247500.Wm82.a2.v1 细胞水分缺失响应 Response to water deprivation (GO:0009414)
响应脱落酸 Response to abscisic acid (GO:0009737)		 F: ATTCAGCATCCACCACTT
R: GTCCTCAGGGACCTTTCT
Glyma.05G149900.Wm82.a2.v1 响应渗透胁迫 Response to osmotic stress (GO:0006970) F: TCTATCGGAGGGCACAGG
R: TGCGTCCTTCTTGTTGTG
Glyma.U012100.Wm82.a2.v1 响应脱落酸 Response to abscisic acid (GO:0009737) F: GGGTTCTAAGTCTGGTGCT
R: GTAATCTTCTGCCCGTTC
Glyma.02G125100.Wm82.a2.v1 类黄酮生物合成 Flavonoid biosynthetic process (GO:0009813)
氧化还原过程 Oxidation-reduction process (GO:0055114)		 F: CTTGTTTGGTGCCTTCTG
R: GATGGGAACTTGTGGTAAAG
Glyma.01G010200.Wm82.a2.v1 调节过氧化氢代谢
Regulation of hydrogen peroxide metabolic process (GO:0010310)		 F: CCAGATGACAACGAGGGT
R: TTGATGCCAGGGTAGGAG

Fig. 1

Effects of elevated CO2 concentration, drought, and interaction on phenotypes in soybean A: Williams 82; B: Zhonghuang 35. CK: normal CO2 concentration + normal water treatment; AC-D: normal CO2 concentration + PEG treatment; EC-C: elevated CO2 concentration + normal water treatment; EC-D: elevated CO2 concentration + PEG treatment."

Table 2

Effects of different treatments on morphological indexes of Williams 82"

处理
Treatment		 株高
Height (cm)		 茎粗
Stem diameter (mm)		 叶干重
Dry weight of leaves (g)		 茎干重
Dry weight of stem (g)		 根干重
Dry weight of root (g)
CK 16.40±0.92 ab 2.97±0.07 ab 0.45±0.06 c 0.15±0.01 b 0.29±0.05 b
AC-D 16.03±0.23 b 2.44±0.04 bc 0.25±0.02 d 0.16±0.01 b 0.24±0.03 b
EC-C 22.40±0.61 a 3.08±0.06 a 0.98±0.03 a 0.38±0.02 a 0.54±0.02 a
EC-D 18.13±0.32 b 2.78±0.06 b 0.66±0.07 b 0.35±0.03 a 0.65±0.03 a

Table 3

Effects of different treatments on morphological indexes of soybean variety Zhonghuang 35"

处理
Treatment		 株高
Height (cm)		 茎粗
Stem diameter (mm)		 叶干重
Dry weight of leave (g)		 茎干重
Dry weight of stem (g)		 根干重
Dry weight of root (g)
CK 13.32±0.54 a 3.63±0.02 b 1.27±0.02 ab 0.44±0.02 a 0.72±0.03 a
AC-D 12.87±0.20 a 3.01±0.18 c 0.74±0.17 c 0.31±0.02 b 0.53±0.02 b
EC-C 11.33±0.72 ab 4.02±0.15 a 1.45±0.04 a 0.44±0.01 a 0.75±0.05 a
EC-D 10.67±0.61 b 3.75±0.06 ab 1.05±0.05 b 0.38±0.03 a 0.71±0.06 a

Table 4

Quality assessment of transcriptome sequencing data"

样本
Sample		 总数据
Total reads		 比对数据
Mapped reads		 比对率
Mapped ratio (%)		 GC含量
GC content (%)		 Q30
(%)
CK-1 50,556,622 47,044,145 93.05 45.23 94.45
CK-2 51,658,426 49,028,122 94.91 45.72 94.30
CK-3 43,820,024 41,614,743 94.97 45.33 94.34
AC-D-1 43,120,330 41,119,245 95.36 44.83 94.01
AC-D-2 44,531,268 42,172,536 94.70 44.91 93.91
AC-D-3 45,104,672 40,243,601 89.22 45.90 94.10
EC-C-1 45,547,956 43,138,374 94.71 45.84 94.47
EC-C-2 41,472,902 35,771,431 86.25 45.22 93.95
EC-C-3 50,234,668 47,881,951 95.32 45.45 94.20
EC-D-1 50,456,872 48,117,672 95.36 45.42 93.99
EC-D-2 44,848,264 41,773,279 93.14 45.06 93.97
EC-D-3 46,186,506 44,120,098 95.53 45.07 93.76

Fig. 2

Venn diagram of DEG in soybean leaves under elevated CO2 concentrations, drought, and interactive conditions Treatments are the same as those given in Fig. 1."

Table 5

Summary of the number of differentially expressed genes"

分组
Grouping		 总基因数目
Total number of genes		 上调基因数目
No. of up-regulated genes		 下调基因数目
No. of down-regulated genes
CK vs AC-D 10,081 3932 6149
CK vs EC-C 89 75 14
CK vs EC-D 8566 3599 4967

Table 6

Top five genes with the highest up/down-regulation multiples under elevated CO2 concentration"

基因名称
Gene ID		 平均FPKM值
Average FPKM value		 log2 FC 相关性
Correlation		 基因注释
Gene annotation
CK EC-C
Glyma.02G058400.Wm82.a2.v1 0.016 3.199 3.842 上调 Up 预测: 蛋白质未定义结构域-2类。
PREDICTED: protein indeterminate-domain 2-like.
Glyma.15G199700.Wm82.a2.v1 5.073 65.190 2.649 上调 Up 假定蛋白GLYMA09G093000。
Hypothetical protein GLYMA09G093000.
Glyma.11G155000.Wm82.a2.v1 24.801 157.097 2.283 上调 Up 早期结瘤素-12A。
Early nodulin-12A.
Glyma.13G336600.Wm82.a2.v1 1.459 8.3240 1.806 上调 Up 预测: 膨胀素-A4。
PREDICTED: expansin-A4.
Glyma.15G054600.Wm82.a2.v1 2.069 18.329 1.607 上调 Up 预测: 蛋白质EXORDIUM类。
PREDICTED: protein EXORDIUM-like 2.
Glyma.01G003000.Wm82.a2.v1 42.373 16.676 -1.114 下调 Down MYB转录因子部分。
Transcription factor MYB129, partial.
Glyma.17G090500.Wm82.a2.v1 2.964 0.891 -1.202 下调 Down 未定义蛋白质LOC100787505。
Uncharacterized protein LOC100787505.
Glyma.17G242600.Wm82.a2.v1 11.048 3.420 -1.358 下调 Down 假定的钙离子结合蛋白CML15。
Putative calcium-binding protein CML15.
Glyma.09G149000.Wm82.a2.v1 14.753 3.794 -1.600 下调 Down 预测: 短截转录因子花椰菜D-类异构X1。
PREDICTED: truncated transcription factor
CAULIFLOWER D-like isoform X1.
Glyma.10G124300.Wm82.a2.v1 6.547 1.832 -1.677 下调 Down 预测: 未定义蛋白LOC100780762。
PREDICTED: uncharacterized protein
LOC100780762.

Table 7

Top 5 genes with the highest up/down regulation multiples under drought condition"

基因名称
Gene ID		 平均FPKM值
Average FPKM value		 log2 FC 相关性
Correlation		 基因注释
Gene annotation
CK AC-D
Glyma.06G157000.Wm82.a2.v1 0 53.699 11.538 上调 Up 预测: 未定义蛋白质LOC100778708。
PREDICTED: uncharacterized protein LOC100778708.
Glyma.17G040800.Wm82.a2.v1 0.031 96.173 11.027 上调 Up Lea蛋白前体。
Lea protein precursor.
Glycine_max_newGene_3981 0 19.590 10.767 上调 Up 假定蛋白GLYMA14G121700。
Hypothetical protein GLYMA14G121700.
Glyma.05G065800.Wm82.a2.v1 0.027 86.385 10.701 上调 Up 预测: 膨胀素-类B1。
PREDICTED: expansin-like B1.
Glyma.09G185500.Wm82.a2.v1 3.423 5737.775 10.468 上调 Up 假定蛋白GLYMA09G185500。
Hypothetical protein GLYMA09G185500.
Glyma.10G200800.Wm82.a2.v1 12.755 0 -9.720 下调 Down 假定蛋白GLYMA10G200800。
Hypothetical protein GLYMA10G200800.
Glyma.04G169600.Wm82.a2.v1 92.106 0 -10.029 下调 Down 预测: 赤霉素调节蛋白4。
PREDICTED: gibberellin-regulated protein 4.
Glyma.16G007700.Wm82.a2.v1 357.220 0.059 -10.503 下调 Down 预测: 生长素结合蛋白ABP19a-类。
PREDICTED: auxin-binding protein ABP19a-like.
Glyma.07G038500.Wm82.a2.v1 454.705 0.186 -10.984 下调 Down 立方形超级蛋白家族前体。
Cupin-like superfamily protein precursor.
Glyma.17G212200.Wm82.a2.v1 288.954 0.059 -11.088 下调 Down AAI-LTSS超级蛋白家族前体。
AAI-LTSS superfamily protein precursor.

Fig. 3

DEG analysis of soybean leaves under elevated CO2 concentration and drought condition A: KEGG classification of DEGs in soybean leaves under elevated CO2 concentration; B: KEGG enrichment of DEGs in soybean leaves under drought conditions."

Fig. 4

DEG analysis of soybean leaves under interactive conditions A: volcano map of DEGs in soybean leaves under interactive conditions; B: COG protein analysis of DEGs in soybean leaves under interactive conditions; C: KEGG enrichment of DEGs in soybean leaves under interactive conditions."

Fig. 5

Relative expression profiles of DEGs under oxidative stress and interactive condition A: heat map of cellular response to water deprivation genes; B: heat map of glutathione transferase activity genes."

Fig. 6

DEG analysis under elevated CO2 concentration, drought, and interactive conditions A: GO classification map of overlapping DEGs under elevated CO2 concentration, drought, and interactive conditions; B: KEGG enrichment of DEGs under elevated CO2 concentration, drought, and interactive conditions."

Fig. 7

qRT-PCR validation of transcriptome sequencing A-F are the expression profiles of six validated genes, respectively; G is the correlation diagram of validated gene."

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